tej87681088/TEJAPI_Medium資料科學11.ipynb

## TEJAPI_Medium資料科學11.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8299361b",
   "metadata": {},
   "source": [
    "## Import basic packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "46bafb73",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Bad key The font.family property has five values in file /Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/matplotlibrc, line 211 ('The font.family property has five values:')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.3.4/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n",
      "\n",
      "Bad key The font.family property has five values in file /Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/matplotlib/mpl-data/matplotlibrc, line 211 ('The font.family property has five values:')\n",
      "You probably need to get an updated matplotlibrc file from\n",
      "https://github.com/matplotlib/matplotlib/blob/v3.3.4/matplotlibrc.template\n",
      "or from the matplotlib source distribution\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "import tejapi\n",
    "tejapi.ApiConfig.api_key = 'Your Key'\n",
    "tejapi.ApiConfig.ignoretz = True"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a2dac12",
   "metadata": {},
   "source": [
    "## Load data & Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ed4a655",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盤價</th>\n",
       "      <th>日報酬率(%)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年月日</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-06-30</th>\n",
       "      <td>37.08</td>\n",
       "      <td>0.2704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-07-01</th>\n",
       "      <td>38.05</td>\n",
       "      <td>2.6160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-07-02</th>\n",
       "      <td>38.69</td>\n",
       "      <td>1.6820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-07-03</th>\n",
       "      <td>39.00</td>\n",
       "      <td>0.8012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-07-04</th>\n",
       "      <td>39.26</td>\n",
       "      <td>0.6667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-24</th>\n",
       "      <td>143.05</td>\n",
       "      <td>0.2804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-27</th>\n",
       "      <td>144.15</td>\n",
       "      <td>0.7690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-28</th>\n",
       "      <td>145.30</td>\n",
       "      <td>0.7978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-29</th>\n",
       "      <td>145.95</td>\n",
       "      <td>0.4474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-30</th>\n",
       "      <td>145.50</td>\n",
       "      <td>-0.3083</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4577 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               收盤價  日報酬率(%)\n",
       "年月日                        \n",
       "2003-06-30   37.08   0.2704\n",
       "2003-07-01   38.05   2.6160\n",
       "2003-07-02   38.69   1.6820\n",
       "2003-07-03   39.00   0.8012\n",
       "2003-07-04   39.26   0.6667\n",
       "...            ...      ...\n",
       "2021-12-24  143.05   0.2804\n",
       "2021-12-27  144.15   0.7690\n",
       "2021-12-28  145.30   0.7978\n",
       "2021-12-29  145.95   0.4474\n",
       "2021-12-30  145.50  -0.3083\n",
       "\n",
       "[4577 rows x 2 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = tejapi.get('TWN/APRCD', # 公司交易資料-收盤價\n",
    "                  coid= '0050', # 台灣50\n",
    "                  mdate={'gte': '2003-01-01', 'lte':'2021-12-31'},\n",
    "                  opts={'columns': ['mdate', 'close_d', 'roi']},\n",
    "                  chinese_column_name=True,\n",
    "                  paginate=True)\n",
    "data['年月日'] = pd.to_datetime(data['年月日'])\n",
    "data = data.set_index('年月日')\n",
    "data = data.rename(columns = {'收盤價(元)':'收盤價', '報酬率％':'日報酬率(%)'})\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3dedcae7",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_date = data.index.get_level_values('年月日') <= '2020-12-31'\n",
    "train_data = data[train_date].drop(columns = ['收盤價'])\n",
    "test_data = data[~train_date]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6c38d54",
   "metadata": {},
   "source": [
    "## ARMA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b13bb676",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'aic':               0             1             2\n",
       " 0  14226.906706  14227.321283  14227.900929\n",
       " 1  14227.265956  14219.250184  14229.774573\n",
       " 2  14227.939920  14229.156037  14214.877848\n",
       " 3  14229.450540  14223.929779  14219.608347\n",
       " 4  14225.725645  14220.976704  14220.782924,\n",
       " 'bic':               0             1             2\n",
       " 0  14239.654737  14246.443329  14253.396990\n",
       " 1  14246.388002  14244.746246  14261.644650\n",
       " 2  14253.435981  14261.026115  14253.121941\n",
       " 3  14261.320618  14262.173871  14264.226455\n",
       " 4  14263.969738  14265.594812  14271.775047,\n",
       " 'aic_min_order': (2, 2),\n",
       " 'bic_min_order': (0, 0)}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "sm.tsa.stattools.arma_order_select_ic(train_data, ic=[\"aic\", \"bic\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9063d86d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
      "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
      "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
      "between arima and model) and\n",
      "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
      "\n",
      "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
      "is both well tested and maintained.\n",
      "\n",
      "To silence this warning and continue using ARMA and ARIMA until they are\n",
      "removed, use:\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
      "                        FutureWarning)\n",
      "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
      "                        FutureWarning)\n",
      "\n",
      "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/base/tsa_model.py:581: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.\n",
      "  warnings.warn('A date index has been provided, but it has no'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                              ARMA Model Results                              \n",
      "==============================================================================\n",
      "Dep. Variable:                日報酬率(%)   No. Observations:                 4333\n",
      "Model:                     ARMA(2, 2)   Log Likelihood               -7101.439\n",
      "Method:                       css-mle   S.D. of innovations              1.246\n",
      "Date:                Mon, 07 Feb 2022   AIC                          14214.878\n",
      "Time:                        15:44:55   BIC                          14253.122\n",
      "Sample:                             0   HQIC                         14228.379\n",
      "                                                                              \n",
      "=================================================================================\n",
      "                    coef    std err          z      P>|z|      [0.025      0.975]\n",
      "---------------------------------------------------------------------------------\n",
      "const             0.0486      0.019      2.531      0.011       0.011       0.086\n",
      "ar.L1.日報酬率(%)     0.8184      0.014     58.107      0.000       0.791       0.846\n",
      "ar.L2.日報酬率(%)    -0.9647      0.016    -62.229      0.000      -0.995      -0.934\n",
      "ma.L1.日報酬率(%)    -0.8162      0.011    -71.041      0.000      -0.839      -0.794\n",
      "ma.L2.日報酬率(%)     0.9801      0.011     86.470      0.000       0.958       1.002\n",
      "                                    Roots                                    \n",
      "=============================================================================\n",
      "                  Real          Imaginary           Modulus         Frequency\n",
      "-----------------------------------------------------------------------------\n",
      "AR.1            0.4242           -0.9256j            1.0181           -0.1816\n",
      "AR.2            0.4242           +0.9256j            1.0181            0.1816\n",
      "MA.1            0.4164           -0.9203j            1.0101           -0.1824\n",
      "MA.2            0.4164           +0.9203j            1.0101            0.1824\n",
      "-----------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.arima_model import ARMA\n",
    "\n",
    "model = ARMA(train_data, order = (2, 2))\n",
    "arma = model.fit() \n",
    "print(arma.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84ec58df",
   "metadata": {},
   "source": [
    "## GARCH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "adc6300d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from arch import arch_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "193c3072",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31928.313185615734\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27480.929726371425\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 838059011.6943483\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6537.910947925134\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7943.349260176782\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6597.600559527966\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6567.792889766998\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6502.015111004817\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6496.366673278075\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6496.362537874973\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6496.362353150593\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6496.362331579887\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6496.362331582379\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6496.362331579887\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "                     Constant Mean - GARCH Model Results                      \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.000\n",
      "Mean Model:             Constant Mean   Adj. R-squared:                  0.000\n",
      "Vol Model:                      GARCH   Log-Likelihood:               -6496.36\n",
      "Distribution:                  Normal   AIC:                           13000.7\n",
      "Method:            Maximum Likelihood   BIC:                           13026.2\n",
      "                                        No. Observations:                 4333\n",
      "Date:                Mon, Feb 07 2022   Df Residuals:                     4332\n",
      "Time:                        15:44:56   Df Model:                            1\n",
      "                                  Mean Model                                 \n",
      "=============================================================================\n",
      "                 coef    std err          t      P>|t|       95.0% Conf. Int.\n",
      "-----------------------------------------------------------------------------\n",
      "mu             0.0252  1.510e-02      1.666  9.570e-02 [-4.439e-03,5.476e-02]\n",
      "                              Volatility Model                              \n",
      "============================================================================\n",
      "                 coef    std err          t      P>|t|      95.0% Conf. Int.\n",
      "----------------------------------------------------------------------------\n",
      "omega          0.0188  6.330e-03      2.966  3.015e-03 [6.369e-03,3.118e-02]\n",
      "alpha[1]       0.0596  1.140e-02      5.232  1.674e-07 [3.729e-02,8.196e-02]\n",
      "beta[1]        0.9269  1.354e-02     68.459      0.000     [  0.900,  0.953]\n",
      "============================================================================\n",
      "\n",
      "Covariance estimator: robust\n"
     ]
    }
   ],
   "source": [
    "arma_resid = list(arma.resid)\n",
    "\n",
    "mdl_garch = arch_model(arma_resid, vol = 'GARCH', p = 1, q = 1)\n",
    "garch = mdl_garch.fit()\n",
    "print(garch.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f32b27",
   "metadata": {},
   "source": [
    "# Forecasting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b53d1a4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/statsmodels/tsa/base/tsa_model.py:376: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`.\n",
      "  warnings.warn('No supported index is available.'\n"
     ]
    }
   ],
   "source": [
    "# len(train_data) = 4333, len(data) = 4577\n",
    "forecast_mu = arma.predict(start = 4333, end = 4576) # 預測函式的end包含當期，所以需進行4577-1=4576。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b9bd83f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-9-2e806c6e299a>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['ARMA預測報酬(%)'] = list(forecast_mu)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fae73aa9460>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "test_data['ARMA預測報酬(%)'] = list(forecast_mu)\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['Arial Unicode MS']\n",
    "\n",
    "plt.figure(figsize=(15,8))\n",
    "\n",
    "plt.plot(test_data['日報酬率(%)'])\n",
    "plt.plot(test_data['ARMA預測報酬(%)'])\n",
    "\n",
    "plt.legend(('實際報酬', 'ARMA預測報酬'), fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "348b1759",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30853.594196576025\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7028.576135038324\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1608110949.2268696\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 179511658.82114768\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6098.965046944551\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6872.589841625309\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6079.6109343952\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6301.83893805864\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6082.174003365658\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6067.706217257855\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6067.674945283197\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6067.674760783788\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6067.674754360744\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6067.674754361463\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6067.674754360744\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30871.990940924807\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7030.034887590999\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 26399268.10687401\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 419230689.90148985\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6099.769620186066\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6865.6564691727945\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6081.57959779354\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 9637.10722853261\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6079.649922014465\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6068.406491199074\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6068.405240701242\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6068.405232763871\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6068.405232762094\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6068.405232763871\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30810.633806909726\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7031.861295132617\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 5501169.420590801\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 314175254.72973114\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6101.50373131316\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6887.022162009612\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6082.285447803845\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6270.859145921275\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6084.07363733738\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6070.32009673695\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6070.301051286304\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6070.300976880435\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6070.300973745847\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6070.300973746051\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6070.300973745847\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30803.166135476375\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7033.380778013811\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 5283664.39389584\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 396193145.6666526\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6102.419763540743\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6879.139342903608\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6083.16538314437\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6304.695641041637\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6085.623235275903\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6071.185534741734\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6071.155203375491\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6071.155024005706\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6071.155017633032\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6071.155017633703\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6071.155017633032\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30785.86271290589\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7034.957526844242\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 4071282.597668659\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 420071396.0240715\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6103.490106833905\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6875.408399220952\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6084.274890332895\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6331.563285857897\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6087.125420777622\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6072.211353114837\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6072.167933289109\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6072.167597731424\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6072.167586328607\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6072.167586329895\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6072.167586328607\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30863.455064531183\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7036.568825134757\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 219217785.44809508\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 364100964.8915146\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6105.102714751635\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6904.135798172963\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6086.110754804299\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6250.875595953408\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6087.048667764441\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6074.025469493283\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6074.012521799942\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6074.012485520159\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6074.012483635035\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6074.012483635074\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6074.012483635035\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30877.71626028004\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7038.023626183525\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 2388225.444885287\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 361408394.8586944\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6105.9578904535365\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6896.3615851363065\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6086.8468712205095\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6273.0726468608145\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6088.387350755668\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6074.8677443954075\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6074.851074184309\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6074.851013448394\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6074.851010818155\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6074.8510108182945\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6074.851010818155\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30905.02270811965\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7039.514343147379\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 8329016.355913687\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 377509219.50991476\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6107.04891198214\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6896.968139897154\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6087.927258152885\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6275.597888559735\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6089.496901331117\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6075.976394692764\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6075.959645612509\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6075.959584193119\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6075.959581564797\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6075.959581564946\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6075.959581564797\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30934.30163001076\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7040.986304320118\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1611429995.2326279\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 392271675.40527374\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6108.023511753319\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6892.569332069563\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6088.871277967423\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6288.405945104798\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6090.829617190751\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6076.9386084139605\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6076.917429287314\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6076.917335128486\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6076.917331451372\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6076.917331451672\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6076.917331451372\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30893.120604571297\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7042.759801593283\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10970876.08787577\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 273948881.6524086\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6109.674832742865\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6908.132662810998\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6090.698912481106\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6256.964767841968\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6091.649797301388\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6078.632954301507\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6078.619994636341\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6078.619958201056\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6078.6199563216505\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6078.619956321688\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6078.6199563216505\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30895.71135964409\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7044.291780409577\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 13764799.635300463\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 380504441.918128\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6110.598574133761\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6901.254271392443\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6091.520591294836\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6277.701450597741\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6093.021775373189\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6079.536656773316\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6079.520171978125\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6079.520112472325\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6079.520109879527\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6079.520109879657\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6079.520109879527\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30900.7074329117\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7045.758606255053\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 15321107.389460474\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 400382718.8137788\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6111.404050516839\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6892.101899302543\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6092.29919983133\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6321.120116458327\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6094.59544124266\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6080.296384349074\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6080.267227331101\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6080.2670492004345\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6080.267042919868\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6080.2670429205555\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6080.267042919868\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 30922.560892628608\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7047.217742316969\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1611836864.9642372\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 414807135.50636554\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6112.314176265327\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6887.479770793625\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 6093.300372260742\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6360.034478553672\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6096.066916108826\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6081.18078094001\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6081.133327751837\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6081.132914873209\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6081.132900922015\n",
      "Iteration:     14,   Func. Count:     83,   Neg. LLF: 6081.132900923675\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6081.132900922015\n",
      "            Iterations: 14\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 1768613043.1662564\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4008069643.1295843\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9005.48704684544\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6150.5571584406425\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 1202375416.3970666\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6123.7966234339565\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6108.241904030299\n",
      "Iteration:      8,   Func. Count:     54,   Neg. LLF: 6114.191623023268\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6106.310782773222\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6106.309666112569\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6106.308663884573\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6106.308599950036\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6106.308598299136\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6106.30859829826\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6106.308598299136\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 6818532326.030575\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 585343095.7204475\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9006.297417240454\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6160.850710752387\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6134.155907046741\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6381.050544513426\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6109.123252721702\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6107.7650482399295\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6107.753996600606\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6107.754006086033\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6107.753365034174\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6107.753365035945\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6107.753365034174\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 23402431706513.957\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4400317975.540555\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9010.718990753247\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6162.518138515912\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6135.914179914516\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6384.677373753921\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6110.752209701731\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6109.349529783438\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6109.337454268489\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6109.337138228064\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6109.336330397202\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6109.336330402979\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6109.336330397202\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22965228710380.547\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 382369820.31615186\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9010.021275451949\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6164.468036077671\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6137.639996702836\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6385.05053909222\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6112.679137824956\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6111.322486137164\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6111.311370924535\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6111.311357380593\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6111.310694947242\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6111.310694949335\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6111.310694947242\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 679954556.925897\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4464250780.751141\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9011.352159387403\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6165.974110266314\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6139.3144819663285\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6390.652963555153\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6114.099920928315\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6112.660639709815\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6112.6475113887145\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6112.6469082322765\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6112.646042093677\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6112.646041397904\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6112.646041397904\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 641226744.2942648\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 439481256.65602654\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9013.878790264294\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6167.820134368691\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6141.02320703802\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6392.448362638145\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6115.909313920445\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6114.488735039711\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6114.476052472659\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6114.475627166114\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6114.474788538124\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6114.474788544951\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6114.474788538124\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 2099187692.8325686\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 1373783791.084691\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9019.04041868711\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6169.555337130358\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6142.743920720762\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6394.593126797753\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6117.625877909817\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6116.1989830210505\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6116.186178250908\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6116.1857389081015\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6116.184900669459\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6116.184900172721\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6116.184900172721\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 454551819.41149956\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4464662647.991152\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9022.093743849919\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6171.020632249631\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6144.307696857895\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6399.120324966446\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6119.001599874123\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6117.51330962558\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6117.498941729704\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6117.498136018878\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6117.497244852571\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6117.4972439547855\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6117.4972439547855\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 3784921403.0120583\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 344238019.0976833\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9023.050637567705\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6172.558715240903\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6145.8480994825795\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6402.83019914774\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6120.454202116231\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6118.9330842354675\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6118.9178993026635\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6118.9169868513145\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6118.916081987692\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6118.916080988196\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6118.916080988196\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22446101595629.773\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4516426639.160191\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9024.143051553448\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6174.149584545821\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6147.402470724427\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6405.880604841712\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6121.972592877444\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6120.436200908315\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6120.420704625949\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6120.419811441634\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6120.418905217716\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6120.418904265231\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6120.418904265231\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 380370540.34555274\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4518527791.826673\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9026.842178982586\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6175.530905899258\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6148.780842196224\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6409.64489750814\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6123.231927768642\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6121.660804976542\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6121.644628854201\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6121.64373849139\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6121.642830900124\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6121.6428299933705\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6121.6428299933705\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 663405844.8257861\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4517737259.87127\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9029.231739908479\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6176.8751767192225\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6150.085139049401\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6413.032531125194\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6124.444515841124\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6122.852085488344\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6122.835697261276\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6122.834944044331\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6122.834052649176\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6122.834051932129\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6122.834051932129\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 3842629156.1181097\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4501260764.91783\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9034.171135032322\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6178.337189720105\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6151.520733327748\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6415.303464074521\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6125.838678116185\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6124.24065278062\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6124.224362835311\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6124.223733785537\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6124.222864262162\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6124.222863688754\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6124.222863688754\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22840591710554.324\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 595389665.4748589\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9037.769810468293\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6180.057602169779\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6153.308606379463\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6416.300179413167\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6127.618665240068\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6126.017572222205\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6126.001139196644\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6126.000403560811\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6125.999520241279\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6125.999519551846\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6125.999519551846\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22619965200205.277\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 3183940567.1267776\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9038.978693394474\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6181.680654859752\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6154.892594923333\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6418.0497601534935\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6129.216617131671\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6127.621392412448\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6127.605166638348\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6127.604506550397\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6127.603633710256\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6127.603633099244\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6127.603633099244\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22685731925379.086\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4494192879.010641\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9042.595913454104\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6183.005549664977\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6156.132436787668\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6419.97197443975\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6130.412012791188\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6128.820322786163\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6128.804523186906\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6128.804097716249\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6128.803278427835\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6128.803278434733\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6128.803278427835\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 22776022196572.598\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 594850290.1028987\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9046.097480982155\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6184.347293673037\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6157.389102154344\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6421.435464516883\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6131.645269772834\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6130.064026766746\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6130.048730177663\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6130.04851787445\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6130.047783166096\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6130.047783169139\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6130.047783166096\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 2581381855.3682866\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4468619772.780736\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9048.924357196975\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6186.090263932778\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6159.289649068946\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6422.536936046056\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6133.500062378018\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6131.901036364878\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6131.885214459764\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6131.884769088506\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6131.883951562562\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6131.883951569671\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6131.883951562562\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 891169021.9144368\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4476465120.425962\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9052.008178856544\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6187.347533239954\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6160.394517028\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6423.589142717214\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6134.599872185156\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6133.022719985384\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6133.007691665376\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6133.007535901561\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6133.0068389865755\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6133.006838989003\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6133.0068389865755\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 2155521109.56022\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 454043045.15664876\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9056.312655768255\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6188.790119027995\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6161.819063885212\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6424.546315555742\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6136.006582932522\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6134.436550471397\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6134.421787841606\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6134.421698543022\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6134.421054256631\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6134.421054258297\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6134.421054256631\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 23148039569332.16\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 998924717.4201434\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9059.146649500055\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6190.168132429311\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6163.138148450917\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6425.288366497629\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6137.320087240954\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6135.763498969198\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6135.749116993196\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6135.749112264688\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6135.748570485898\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6135.748570486519\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6135.748570485898\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 23381171148639.83\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4446803073.584899\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9060.889894679574\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6191.957479320629\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6165.186177702426\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6427.154879360095\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6139.276193202515\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6137.683067101394\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6137.667829368896\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6137.667552404481\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6137.666804836421\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6137.666804840175\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6137.666804836421\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 1133816630.8568177\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 616738416.7730906\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9062.063396106418\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6193.595627974082\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6166.848338833276\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6428.767143844076\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6140.942184965636\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6139.348157915726\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6139.332866925357\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6139.332558548616\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6139.3317983968245\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6139.331798400935\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6139.3317983968245\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 16047864256.063\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4466004349.075409\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9064.094058886843\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6194.8850149954815\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6167.995543254448\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6429.02869257523\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6142.10146117102\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6140.534852266284\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6140.52035238342\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6140.5202582322345\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6140.519617711238\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6140.519617713004\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6140.519617711238\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 3191124706.6772804\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 362917620.9559942\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9065.725094437998\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6196.38261323265\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6169.461241922919\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6430.0779977811935\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6143.575352966434\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6142.018571650839\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6142.004315467051\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6142.00426785305\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6142.003671952094\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6142.003671953319\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6142.003671952094\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 23259806456282.633\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4457468845.652223\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9066.36662413375\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6198.703967768657\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6172.3707972492075\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6435.161459797935\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6146.338585005161\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6144.666601293749\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6144.6487917327895\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6144.647750357164\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6144.646864313562\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6144.646863309303\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6144.64686330893\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6144.646863309303\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 352263827.2631805\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4391900283.451004\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9070.957811123673\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6201.95877339989\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6176.178823706768\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6443.312692964528\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6150.350836670799\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6148.544615445559\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6148.521002492981\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6148.518866251218\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6148.5179173483375\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6148.5179151639895\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6148.517915163359\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6148.5179151639895\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 23759458866520.65\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 661740333.0187787\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9072.38471575113\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6203.368911810157\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6177.5953047395715\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6444.627254353893\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6151.653840144704\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6149.826530016991\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6149.802280742668\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6149.800074229096\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6149.799126485871\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6149.799124244548\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6149.799124243916\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6149.799124244548\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 1343116091.1716356\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 318478157.7560054\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9077.768336389287\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6205.005646761041\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6179.227228011646\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6446.009198370305\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6153.275903412742\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6151.4480383937935\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6151.423879255392\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6151.421688427976\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6151.420743775943\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6151.420741553744\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6151.420741553116\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6151.420741553744\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 25327352806374.395\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4245493288.039079\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9091.480631208833\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6209.290076350149\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6183.588099436709\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6451.874729759677\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6158.522461948392\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6156.727814010179\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6156.702905254924\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6156.700410295215\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6156.699431876397\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6156.699429273778\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6156.699429273087\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6156.699429273778\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 25722832157624.17\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 4207058004.0154705\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9096.701594091053\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6211.116198088242\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 6185.355580523847\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6453.55914832835\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6160.312639329288\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6158.5210029767695\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6158.496284100127\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6158.493818264144\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6158.492840845654\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6158.492838274047\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6158.4928382733615\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6158.492838274047\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 735469661.6325903\n",
      "Iteration:      2,   Func. Count:     15,   Neg. LLF: 1308880365.0950804\n",
      "Iteration:      3,   Func. Count:     23,   Neg. LLF: 9115.317758822244\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6206.783634362047\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 1173102423.818342\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6180.543453464734\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6167.6197369163\n",
      "Iteration:      8,   Func. Count:     54,   Neg. LLF: 6172.060577865604\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6164.207989319163\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6164.206871446074\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6164.204087720249\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6164.20394760536\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6164.20394760528\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6164.20394760536\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31833.266816243027\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25918.775140867394\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 808466148.3652278\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6214.6522646680005\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 1833286065.1753592\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6183.001070715264\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6856.388106259367\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6205.632970311326\n",
      "Iteration:      9,   Func. Count:     63,   Neg. LLF: 6168.161771015573\n",
      "Iteration:     10,   Func. Count:     69,   Neg. LLF: 6167.225801088166\n",
      "Iteration:     11,   Func. Count:     74,   Neg. LLF: 6167.20057932591\n",
      "Iteration:     12,   Func. Count:     79,   Neg. LLF: 6167.20042767497\n",
      "Iteration:     13,   Func. Count:     84,   Neg. LLF: 6167.200421935794\n",
      "Iteration:     14,   Func. Count:     88,   Neg. LLF: 6167.200421935006\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6167.200421935794\n",
      "            Iterations: 14\n",
      "            Function evaluations: 88\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 32060.249349647285\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25890.858609790994\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 814096586.1604881\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6217.122223290945\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 1859183873.7666419\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6185.54357753389\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6860.291521852958\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6208.6218095121485\n",
      "Iteration:      9,   Func. Count:     63,   Neg. LLF: 6171.144661532499\n",
      "Iteration:     10,   Func. Count:     69,   Neg. LLF: 6169.8208764793835\n",
      "Iteration:     11,   Func. Count:     74,   Neg. LLF: 6169.779449610991\n",
      "Iteration:     12,   Func. Count:     79,   Neg. LLF: 6169.779138940297\n",
      "Iteration:     13,   Func. Count:     84,   Neg. LLF: 6169.779128373773\n",
      "Iteration:     14,   Func. Count:     88,   Neg. LLF: 6169.779128372438\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6169.779128373773\n",
      "            Iterations: 14\n",
      "            Function evaluations: 88\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 32643.97077347362\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25820.793809644434\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 746311372.338587\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6219.301891140691\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 14935.353675784998\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6198.551131244273\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6841.9318983042285\n",
      "Iteration:      8,   Func. Count:     57,   Neg. LLF: 6193.189256765641\n",
      "Iteration:      9,   Func. Count:     63,   Neg. LLF: 6175.933018523187\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6176.593832533445\n",
      "Iteration:     11,   Func. Count:     74,   Neg. LLF: 6175.768462872751\n",
      "Iteration:     12,   Func. Count:     79,   Neg. LLF: 6175.7202399509715\n",
      "Iteration:     13,   Func. Count:     84,   Neg. LLF: 6175.720001135072\n",
      "Iteration:     14,   Func. Count:     89,   Neg. LLF: 6175.720000410718\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6175.720000410718\n",
      "            Iterations: 14\n",
      "            Function evaluations: 89\n",
      "            Gradient evaluations: 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 32013.492132993844\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7138.849467940216\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 26334169.153442804\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 246280627.75784978\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6219.669955286421\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7447.761526885648\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6208.786593996412\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6192.651857346609\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6184.156854738005\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6182.892768250609\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6182.887939989842\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6182.887933253938\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6182.887933254198\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6182.887933253938\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 32393.496889855145\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7143.751019134618\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1736054439.5379329\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 74185131.5177425\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6222.885308243605\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7605.618054660774\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6212.7147670275635\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6195.1729539673215\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6186.9722365109865\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6185.942105101758\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6185.93523693395\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6185.935230505426\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6185.935230505484\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6185.935230505426\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31945.065134135886\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7148.662090259447\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 14036225.182398213\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 24712318.83389757\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6226.277151717577\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7743.261395396237\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6217.792983878684\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6198.071892427293\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6189.998639019028\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6189.141659030465\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6189.1338139431045\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6189.133809218947\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6189.133809218784\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6189.133809218947\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31636.658154101166\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7151.826576022516\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 37624899.62676729\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 29178039.619241588\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6228.966014839701\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7763.28351251166\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6221.2191818843385\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6200.613688663184\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6192.82565641835\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6191.7766335858905\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6191.768641656539\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6191.768634669243\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6191.768634669205\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6191.768634669243\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31612.68648232649\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7153.285732673421\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1734831924.5982172\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 27600745.367650207\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6230.983742423194\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7746.815948931455\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6223.477964339417\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6202.734579992939\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6195.074084175203\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6193.872076377716\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6193.863989590024\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6193.86398009343\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6193.863980093573\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6193.86398009343\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31693.302482157356\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7154.9301717984235\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1732518217.8619852\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 17523831.53076164\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6233.021001184604\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7742.238116286455\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6225.581492267411\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6204.823001637713\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6197.294259855036\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6195.964737050819\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6195.956613289495\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6195.956600902536\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6195.956600902933\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6195.956600902536\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31785.500020584943\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7156.632999790253\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1730705178.0333931\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 8364345.419714857\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6235.06121384717\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7744.4658122199435\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6227.677991151297\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6206.880149991857\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6199.491133131289\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6198.041451337336\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6198.033309959435\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6198.033294223407\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6198.033294224137\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6198.033294223407\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31755.592596910978\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7158.096385729945\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 16606701.757955743\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 5676310.888243292\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6237.0293384222105\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7742.1531978824005\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6230.013029289198\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6208.858242696928\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6201.644712551084\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6200.0360933133525\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6200.0279666681\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6200.027946875466\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6200.027946876626\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6200.027946875466\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31789.374557278097\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7159.604088868543\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1724149649.006165\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 3271291.822051157\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6238.971473476719\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7741.8975994027\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6232.236772602435\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6210.80250631851\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6203.722679791803\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6201.993486128076\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6201.985410572797\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6201.985387022749\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6201.985387024359\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6201.985387022749\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31674.197279935463\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7161.318001133437\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1720519040.521862\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 2855581.560050445\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6241.029856804518\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7744.161299420758\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6234.858253873531\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6212.831178763358\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6205.944987042749\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6204.044966666888\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6204.036965999594\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6204.036938252377\n",
      "Iteration:     13,   Func. Count:     79,   Neg. LLF: 6204.036938254489\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6204.036938252377\n",
      "            Iterations: 13\n",
      "            Function evaluations: 79\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31535.479585533525\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7163.186770534712\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1717328024.1263676\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 2790797.351117279\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6243.153822446386\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7748.145760782217\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6237.569053454366\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6214.915292662356\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6208.246900205289\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6206.152253244839\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6206.144361798848\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6206.144329640342\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6206.144329142997\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6206.144329142997\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31439.96685088604\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7164.8493126619815\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1714115102.8375921\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 2405759.096605861\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6245.16489291269\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7751.6612129447885\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6240.21075179067\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6216.887299681875\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6210.372466094281\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6208.141125149179\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6208.133318195214\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6208.13328247478\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6208.133281866356\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6208.133281866356\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31489.800969919936\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7166.385731420842\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 15195359.763945568\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 982984.9678859874\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6248.1114275655\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7753.073778815937\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6242.921729947073\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6218.608328918615\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6212.784725784188\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6210.000732273282\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6209.991742024487\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6209.991686861511\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6209.991685676436\n",
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6209.991685676874\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6209.991685676436\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31497.726419355582\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7167.847900536396\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 17394692.64325132\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 491377.81788263813\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6254.404625407143\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7712.785705586271\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6246.845141242939\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6219.960160305309\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6220.166429214983\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6211.80776443491\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6211.794895935021\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6211.794652263097\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6211.794641075371\n",
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6211.79464107683\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6211.794641075371\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31555.604827863288\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7169.423925114513\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 26241080.753068015\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 232262.29864156275\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6261.929310865111\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6223.207599637857\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7879.592019208296\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6271.522360897802\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6213.610768127383\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6213.60230065828\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6213.602200400785\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6213.602198406417\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6213.602198406787\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6213.602198406417\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31362.225491048914\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7171.9228683857355\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 12825793.769763114\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 739837.035561547\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6260.358464259929\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7703.313560923026\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6252.175948445152\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6224.120193575505\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6230.527906475259\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6216.046787888237\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6216.033169163725\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6216.032873349781\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6216.0328581526865\n",
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6216.032858154349\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6216.0328581526865\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31359.686294285737\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7173.379703638602\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1708852487.6350956\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 441950.7307504135\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6267.323101400565\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6227.510017855813\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7853.950071285382\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6275.740820743039\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6217.788105702466\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6217.779512709289\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6217.7794168205055\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6217.779414806939\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6217.779414807244\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6217.779414806939\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31416.16409521301\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7174.945780425333\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1709267412.916766\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 218435.51862861647\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6276.021168415184\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6228.500951057278\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7786.164848837546\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6282.108025519357\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6219.535170425283\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6219.527326195555\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6219.527186786952\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6219.527185101411\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6219.52718510185\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6219.527185101411\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31209.46689549709\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7177.67924612342\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 11755279.0222582\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 1215341.1688874175\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6269.066106377781\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7687.626700302399\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6259.939020859945\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6230.171907228918\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6254.69670730244\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6222.163186502881\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6222.148937736678\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6222.148766616372\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6222.148759720683\n",
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6222.148759721742\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6222.148759720683\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31248.713836414066\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7179.177852635254\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1711020322.066821\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 634902.1269748013\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6276.491652789739\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6233.529674090125\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7808.167677342215\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6283.312106113401\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6223.8652369215\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6223.856780561597\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6223.856681095516\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6223.856679216358\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6223.85667921662\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6223.856679216358\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31429.029562810087\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7182.271015630999\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 16203205.303166714\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 942882.7697457492\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6274.993670022182\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6236.944825434667\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7865.868768075404\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6281.183270380902\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6226.504394749699\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6226.494201293084\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6226.494136920576\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6226.494134458305\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6226.494134458217\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6226.494134458305\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31442.47161855877\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7183.738619058675\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 5889754.570842309\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 567281.5737481338\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6282.045974026534\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6237.838711087077\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7801.565387962006\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6287.7089630311475\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6228.189625965062\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6228.181148141596\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6228.181052359294\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6228.181050460813\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6228.1810504610075\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6228.181050460813\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31428.54947372365\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7185.19790844625\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1717163473.573772\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 395934.06862372626\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6289.218976308841\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6239.0247474823755\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7745.318070475877\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6292.286735392281\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6229.852096538903\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6229.843960473106\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6229.843834335998\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6229.84383258615\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6229.843832586435\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6229.84383258615\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31440.348327111733\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7186.662284513771\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 569267960.9289168\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 232972.25494771227\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6298.449094779982\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6240.223143921554\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7685.139910726162\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6267.273450822431\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6231.4693934525385\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6231.460477547846\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6231.460389533993\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6231.460388128655\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6231.460388128823\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6231.460388128655\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31321.876551629754\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7188.6592280043205\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 12837227.653346492\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 442606.06850583944\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6296.642550498975\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6242.621200401081\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7709.000925146083\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6296.4498321530245\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6233.566317339066\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6233.558009680046\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6233.557864764329\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6233.557862873605\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6233.557862873888\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6233.557862873605\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31342.07790168619\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7190.128639493931\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1721031385.1347768\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 283084.71003023867\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6305.336544254096\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6243.880152183076\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7656.520684361308\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6246.017344663961\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6235.147587935309\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6235.13732225861\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6235.137286145089\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6235.137285605411\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6235.137285605411\n",
      "            Iterations: 12\n",
      "            Function evaluations: 73\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31275.700422072587\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7191.78689324339\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 27294031.566129178\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 300292.25719587866\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6309.197551492031\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6245.630673855586\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7640.185315356701\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6242.092989623154\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6236.923946317819\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6236.913191225911\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6236.913153355364\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6236.9131528666585\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6236.9131528666585\n",
      "            Iterations: 12\n",
      "            Function evaluations: 73\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31154.36603478151\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7193.841226576717\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 7540826.593238357\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 678215.0403784446\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6304.618435199365\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6248.173167454109\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7681.808675483581\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6279.979608681288\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6239.082171183247\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6239.073057447929\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6239.072957751034\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6239.072956183026\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6239.072956183182\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6239.072956183026\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31288.67512399422\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7196.984219959757\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1715238684.8030114\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 1537050.9869240755\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6298.1378495248455\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6251.7886102872835\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7778.014707496526\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6303.331345823528\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6241.922679735493\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6241.914269549649\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6241.91417278603\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6241.91417102431\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6241.914171024491\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6241.91417102431\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31272.210571770433\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7198.449117178308\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 4067030.3109149868\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 1120525.8493221283\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6304.423518743351\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6253.009992659044\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7729.264023570699\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6307.380094642645\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6243.517936648199\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6243.509571122659\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6243.509447416834\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6243.5094456665975\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6243.509445666834\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6243.5094456665975\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31278.38649504523\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7199.906140683003\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1721306723.109336\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 840575.4881805171\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6310.915224546713\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6254.257111754191\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7685.025194950511\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6297.3888755844455\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6245.05827550046\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6245.049074704137\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6245.048940778499\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6245.048938878776\n",
      "Iteration:     13,   Func. Count:     77,   Neg. LLF: 6245.048938878997\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6245.048938878776\n",
      "            Iterations: 13\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31268.67920968844\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7201.367684847678\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1724455806.7520995\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 567398.3290575714\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6318.668419401912\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6255.527280183589\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7639.465833709168\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6252.626885491412\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6246.585924062505\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6246.573859578859\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6246.573819890313\n",
      "Iteration:     12,   Func. Count:     73,   Neg. LLF: 6246.573819388693\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6246.573819388693\n",
      "            Iterations: 12\n",
      "            Function evaluations: 73\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31253.683942885447\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7202.841051308762\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10833493.781998282\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 429560.48804110364\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6325.979035100596\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6256.883733457602\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7601.677163621148\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6248.9461933757975\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6248.095578227929\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6248.086577524302\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6248.086562169026\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6248.086562172003\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6248.086562169026\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31230.555548650813\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7204.344786710859\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 8171504.875422708\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 363356.4863398254\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6332.12745902532\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6258.331528613742\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7573.3440731764795\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6249.7769156000995\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6249.618258164259\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6249.615383287422\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6249.615379149608\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6249.615379152502\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6249.615379149608\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31297.103183275914\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7206.157364665416\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1732328280.045601\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 289207.85869132704\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6336.937550186574\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6259.981316820642\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7562.113630846047\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6251.394659014997\n",
      "Iteration:      9,   Func. Count:     57,   Neg. LLF: 6251.3289738338635\n",
      "Iteration:     10,   Func. Count:     62,   Neg. LLF: 6251.327342921981\n",
      "Iteration:     11,   Func. Count:     67,   Neg. LLF: 6251.32722575801\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6251.327222850365\n",
      "Iteration:     13,   Func. Count:     76,   Neg. LLF: 6251.327222850354\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6251.327222850365\n",
      "            Iterations: 13\n",
      "            Function evaluations: 76\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31297.849064949063\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7207.6151463404885\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 28786763.39490465\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 217873.33997886212\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6344.948254971597\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6261.318816191355\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7525.9781358828905\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6252.776117687978\n",
      "Iteration:      9,   Func. Count:     57,   Neg. LLF: 6252.733474960956\n",
      "Iteration:     10,   Func. Count:     62,   Neg. LLF: 6252.7312292484\n",
      "Iteration:     11,   Func. Count:     67,   Neg. LLF: 6252.730806703043\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6252.730804135044\n",
      "Iteration:     13,   Func. Count:     76,   Neg. LLF: 6252.730804135849\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6252.730804135044\n",
      "            Iterations: 13\n",
      "            Function evaluations: 76\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31353.399636631304\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7209.3939210432145\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10560601.557154682\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 180801.53379838294\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6349.376684437387\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6262.950709608089\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7516.88312255753\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6254.454638196211\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6254.39410275975\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6254.388662496922\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6254.388661717661\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6254.388661717661\n",
      "            Iterations: 11\n",
      "            Function evaluations: 69\n",
      "            Gradient evaluations: 11\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31335.018086628537\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7210.883333916656\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1742010667.1884274\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 165598.66613183182\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6354.322514510687\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6264.378048170771\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7494.674776074454\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6255.9568584566005\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6255.827250181646\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6255.814711528146\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6255.81471075897\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6255.81471075897\n",
      "            Iterations: 11\n",
      "            Function evaluations: 69\n",
      "            Gradient evaluations: 11\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31375.210458491365\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7212.539103684134\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 15054460.122281862\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 130124.92082876308\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6360.282044614219\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6265.86632818529\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7475.0246094144\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6257.585473625864\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6257.3355603133095\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6257.316576983654\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6257.316576125411\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6257.316576125411\n",
      "            Iterations: 11\n",
      "            Function evaluations: 69\n",
      "            Gradient evaluations: 11\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31355.11460782181\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7214.058210429119\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 20514581.684066817\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 123515.39585826789\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6363.7279940602075\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6267.323272025156\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7459.777319267293\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6259.153658814827\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6258.773925719633\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6258.754578630114\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6258.7545777524165\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6258.7545777524165\n",
      "            Iterations: 11\n",
      "            Function evaluations: 69\n",
      "            Gradient evaluations: 11\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31371.440499379325\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7215.536011376547\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 12087556.752690256\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 101550.94817944821\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6369.722633771737\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6268.616137201989\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7429.13790411061\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6260.702126283346\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6260.049039322539\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6260.02992317781\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6260.029922188854\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6260.029922188854\n",
      "            Iterations: 11\n",
      "            Function evaluations: 69\n",
      "            Gradient evaluations: 11\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31361.158694325604\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7217.051032705185\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1756064398.0219855\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 102159.29298100366\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6370.934864857008\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6270.040093447933\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7420.152230585965\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6262.191095994818\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6261.441851595186\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6261.425510165222\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6261.425490178256\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6261.425490178501\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6261.425490178256\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31389.636013677828\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7219.229460380206\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 6028333.239014027\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 110381.42230878974\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6367.318674807968\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6272.212047050933\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7476.8468332486345\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6264.040454524233\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6263.629018191106\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6263.613939561601\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6263.613924440951\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6263.613924440553\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6263.613924440951\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31374.09051742251\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7220.716443611382\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1754090008.542832\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 110887.95483835482\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6369.595170219303\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6273.581413125971\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7460.277100819939\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6265.50478493488\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6264.957580428492\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6264.9440048443375\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6264.943990668822\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6264.9439906686575\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6264.943990668822\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31352.038248804292\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7222.295267301515\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 23678611.419292115\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 107950.65725215328\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6371.534382985802\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6275.128616366753\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7456.923672241297\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6267.064037353004\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6266.483690112807\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6266.470629913021\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6266.4706164166\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6266.470616416529\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6266.4706164166\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31370.474006963694\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7223.776593262239\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1760132554.7750351\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 96862.28317948399\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6375.25945693685\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6276.3737934577075\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7430.483310023475\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6268.467538938916\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6267.688561550347\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6267.676764164584\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6267.676751554579\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6267.676751554831\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6267.676751554579\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31394.05384662227\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7225.366393486278\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1763638230.8774872\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 86551.91620072135\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6378.398261666327\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6277.709411201541\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7412.980979616066\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6269.887145221435\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6268.994126853052\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6268.98321860845\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6268.983207024634\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6268.983207025105\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6268.983207024634\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31391.18292167042\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7226.855867061113\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1767148251.371575\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 82193.52907322487\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6380.154656100023\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6279.016784853537\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7397.951883770664\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6271.213311502821\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6270.264283943687\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6270.254343725233\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6270.254333539585\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6270.254333540263\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6270.254333539585\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31396.61617582185\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7228.326019157401\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1771368426.410009\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 80712.40987482712\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6380.981269687105\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6280.255279627543\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7381.825079415664\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6272.433881673677\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6271.458459448183\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6271.4495671378645\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6271.4495584836895\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6271.449558484561\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6271.4495584836895\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31409.247146428843\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7229.783808858629\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1776099864.145978\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 76138.52011814277\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6381.947108631925\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6281.445826792355\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7362.28699358161\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6273.575420193846\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6272.604031033806\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6272.595781738251\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6272.595774148758\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6272.595774149822\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6272.595774148758\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31390.25474259722\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7231.603966128631\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 58332327.88087236\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 70141.54680970692\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6383.265502006435\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6283.501589097134\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7414.5713522961905\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6275.510412843892\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6274.712099505371\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6274.703438201028\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6274.703430421727\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6274.703430422322\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6274.703430421727\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31393.070633802614\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7233.119355095319\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 11647802.246290142\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 68900.7365053742\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6384.670851616879\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6284.853055980607\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7405.694452212592\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6276.835125408453\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6276.031104578349\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6276.022870280426\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6276.022863041027\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6276.022863041733\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6276.022863041027\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31402.238884109676\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7234.622679640005\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1773008700.365398\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 68690.67345026422\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6385.682872142224\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6286.163822853856\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7396.470237409565\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6278.107506475746\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6277.306795318973\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6277.299018357397\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6277.2990116789315\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6277.299011679743\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6277.2990116789315\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31381.245831570668\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7236.258159657829\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 48571595.90297086\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 69434.86449184349\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6386.496994545052\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6287.794865185484\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7410.621282075372\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6279.671840382245\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6278.938271580323\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6278.930412126764\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6278.930405547554\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6278.930405548288\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6278.930405547554\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31421.98885441895\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7237.710475261538\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 57674505.36456703\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 63257.58851615143\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6389.428482864556\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6288.903689923759\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7383.782165559854\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6280.778919735964\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6279.997556773754\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6279.989960568781\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6279.989954172332\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6279.989954173296\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6279.989954172332\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31429.358144767895\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7239.241139452513\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 52749823.69723402\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 62232.6849214098\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6390.556937918454\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6290.264980370373\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7380.401434360076\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6282.087500187519\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6281.336635313687\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6281.329139000727\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6281.329132790674\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6281.329132791698\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6281.329132790674\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31386.04406112343\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7241.275201097205\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1769464561.8020608\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 65809.73644787511\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6390.057306867899\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6292.345122182987\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7431.728948296175\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6284.124782579842\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6283.463600350159\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6283.456384529033\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6283.456378771708\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6283.456378772303\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6283.456378771708\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31414.67429078467\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7242.975474542229\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1770253290.9867692\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 60366.355282575314\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6392.98000424933\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6293.795094103267\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7425.753503973572\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6285.582587887473\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6284.8998268024225\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6284.892551890729\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6284.89254597714\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6284.89254597779\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6284.89254597714\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31440.04901154181\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7244.895599895454\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1767979078.7456975\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 55253.01960584834\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6394.282739958753\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6295.641213051977\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7445.261951890281\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6287.409724151489\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6286.773841379484\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6286.766187265193\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6286.76618114636\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6286.7661811468715\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6286.76618114636\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31400.959981559896\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7247.008923319978\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1761784600.8619823\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 63100.67496204505\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6385.784499451889\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6298.381980346823\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7537.777084957159\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6289.953648698704\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6289.611844337918\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6289.603678530207\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6289.603673342643\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6289.603673342641\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6289.603673342643\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31413.765606799057\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7248.464984526339\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 30160173.259079143\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 58916.059337183426\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6392.776488184714\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6299.575494241433\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7499.981408724258\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6291.243600712201\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6290.756370165151\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6290.748038712569\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6290.748032579906\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6290.748032580075\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6290.748032579906\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31438.358737956514\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7249.951661658829\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 18678573.723147653\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 54598.09586273163\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6399.669533409631\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6300.754450704594\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7466.797427987847\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6292.517254522929\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6291.885556075622\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6291.877070737102\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6291.877063778662\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6291.877063779034\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6291.877063778662\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31459.66653706823\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7251.43619269951\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 12487664.652732525\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 51330.0410562431\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6406.302545481137\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6301.903588745592\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7436.872259104737\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6293.739927699184\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6292.9823208719845\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6292.973644507779\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6292.973636797737\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6292.973636798342\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6292.973636797737\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31471.157174942553\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7252.890866737337\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 19905576.86291092\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 49865.16804630759\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6412.240662533876\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6303.012733044971\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7410.0310963333595\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6294.884416097769\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6294.037039374523\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6294.028138616362\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6294.0281302506655\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6294.028130251527\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6294.0281302506655\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31478.837609818584\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7254.3561643911\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1769632037.6932802\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 49422.04953845467\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6416.607365099971\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6304.161315587501\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7390.864781926619\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6296.023568855112\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6295.1413747525385\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6295.132242453139\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6295.132233619253\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6295.132233620341\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6295.132233619253\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31488.52487725112\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7255.839499469851\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 17567260.46744275\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 49062.56010867685\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6419.82596517534\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6305.356998925282\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7377.957487683852\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6297.185067718964\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6296.303473919251\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6296.2941063955805\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6296.29409722323\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6296.294097224494\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6296.29409722323\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31496.245600136397\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7257.577378528607\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1770388725.3846858\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 48514.76190360106\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6420.275880751765\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6306.862204379005\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7387.414974887514\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6298.673250077398\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6297.809311050564\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6297.800341892389\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6297.800333233509\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6297.800333234677\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6297.800333233509\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31501.87029794447\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7259.082374183033\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 25509798.649922233\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 47120.55785245502\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6423.359456310167\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6308.098818737395\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7376.988525432856\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6299.878573209842\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6299.0188566257675\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6299.009551671472\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6299.009542567818\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6299.009542569143\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6299.009542567818\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31515.45992743114\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7260.548604985186\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1772954313.0884304\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 48918.0323380399\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6425.712413122822\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6309.230820980161\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7365.616801374157\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6300.96804927832\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6300.116549987137\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6300.107047958923\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6300.1070385303265\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6300.107038531818\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6300.1070385303265\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31519.6488591289\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7262.1309061240445\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 4557388.428057863\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 45401.85272495562\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6426.716318433559\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6310.7253726718245\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7373.018524680714\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6302.434176722738\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6301.616963591269\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6301.607519925982\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6301.6075107617735\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6301.607510763223\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6301.6075107617735\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31513.79513363329\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7263.7354839692625\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1772274979.051594\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 46321.80328524999\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6425.379158654546\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6312.288311963815\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7388.793215072444\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6303.9742612620785\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6303.192493607936\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6303.183724596862\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6303.183716336375\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6303.183716337668\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6303.183716336375\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31456.332361172972\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7265.546452621776\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1769212135.3145583\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 45925.81581812776\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6419.845570625124\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6314.449043296447\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7436.729951709375\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6306.108134119504\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6305.421403571192\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6305.4138102219495\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6305.413803782677\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6305.413803783507\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6305.413803782677\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31491.294112598636\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7266.998337184659\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 18824545.645979036\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 43107.09635462208\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6427.04166879099\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6315.523471524239\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7408.499141774184\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6307.21478965457\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6306.443295359921\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6306.434830345737\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6306.4348225745925\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6306.434822575708\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6306.4348225745925\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31516.788480156098\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7268.4672040637115\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1772192394.2875438\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 45417.74449628097\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6430.568517705915\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6316.654888882031\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7395.027695856037\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6308.339256454441\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6307.53540959128\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6307.526646309775\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6307.526637987042\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6307.5266379883205\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6307.526637987042\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31556.240704061795\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7269.917278112283\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1671022598.6239967\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 42185.2806462061\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6437.391380067627\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6317.684135532092\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7369.703048195732\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6309.345522994781\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6308.516911359203\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6308.506694325764\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6308.506684082942\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6308.506684084576\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6308.506684082942\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31576.997826717\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7271.547162371586\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10139644.396969773\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 40674.1075478085\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6440.144897084474\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6318.953276318917\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7365.213995119504\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6310.595225294259\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6309.769530985139\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6309.759022868586\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6309.759012219358\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6309.759012221072\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6309.759012219358\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31546.88830951429\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7273.273683690383\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 35372369.689691596\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 37628.310183460766\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6436.113044410682\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6320.913807602268\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7399.44476608142\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6312.5689451990265\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6311.784894548082\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6311.776053980538\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6311.776045672686\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6311.776045673979\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6311.776045672686\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31571.12453172423\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7274.741595600005\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1773832689.6617904\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 40789.37812510191\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6439.09813968358\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6322.035283465228\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7389.121885589358\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6313.681489792637\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6312.869884124861\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6312.860779554697\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6312.860770689122\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6312.8607706905495\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6312.860770689122\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31609.980872422064\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7276.191538643572\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 23679856.732704725\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 37904.35217248378\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6446.432737797179\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6323.04398314191\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7364.1131117680125\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6314.660208516822\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6313.830065907228\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6313.819105812307\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6313.819094541296\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6313.819094543108\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6313.819094541296\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31604.06923595444\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7277.9485583311925\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 75420127.05225718\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 35841.17901242093\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6446.418344733182\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6324.590164088661\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7375.392887922788\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6316.217490924002\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6315.3888515069075\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6315.378703269427\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6315.37869298653\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6315.378692988181\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6315.37869298653\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31600.93013269559\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7279.5407478988745\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 13258595.350041393\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 34770.91251028289\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6445.86915802058\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6326.11846278698\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7384.970184597921\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6317.739717599972\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6316.930768803806\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6316.921180062491\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6316.921170575872\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6316.9211705774205\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6316.921170575872\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31636.100872676503\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7281.009092803053\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 43548403.81338799\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 35308.19867498086\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6451.9557698028275\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6327.102555271027\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7365.117605021797\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6318.702086351479\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6317.864983046215\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6317.853951425466\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6317.853939922763\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6317.853939924618\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6317.853939922763\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31509.324633489625\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7283.281045364866\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1770113767.767211\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 28465.765272969133\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6431.249880010789\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6330.7746584656625\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7486.7961116587685\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6322.4178550143315\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6321.737192411467\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6321.731386160002\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6321.731381912294\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6321.731381912789\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6321.731381912294\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31541.8901084596\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7284.731309008871\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 17110240.334960856\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 27754.47180822955\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6440.087662357073\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6331.872516888378\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7456.259316243015\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6323.620849667739\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6322.776674920484\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6322.770142430726\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6322.770136978251\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6322.770136978934\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6322.770136978251\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31583.70953502535\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7286.2290709719455\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1771245352.9855099\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 26670.66867996115\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6448.634348824799\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6332.978489859926\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7430.465256907341\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6324.801834035794\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6323.826668702661\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6323.819269368209\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6323.81926241138\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6323.819262412256\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6323.81926241138\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31620.799582702548\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7287.756025457862\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1771847784.6211364\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 25832.23773948224\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6456.346209208856\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6334.103388847511\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7409.945138738307\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6325.962091019706\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6324.901091453177\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6324.8927210419415\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6324.892712393782\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6324.8927123948515\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6324.892712393782\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31109.183161357636\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7293.016562969955\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1076347342.2816105\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 314541.5201938082\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6377.6596786902355\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 8014.188622853199\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6407.782614773729\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6347.09972970373\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6337.169295498608\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6337.123551802924\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6337.123006325137\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6337.1229913163625\n",
      "Iteration:     13,   Func. Count:     78,   Neg. LLF: 6337.122991318936\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6337.1229913163625\n",
      "            Iterations: 13\n",
      "            Function evaluations: 78\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31109.902661820364\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7294.476436479221\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1762727476.1309776\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 333443.573569031\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6379.707804034286\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7986.319579683606\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6410.7682094346765\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6348.478149030589\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6338.582189660363\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6338.525787788841\n",
      "Iteration:     11,   Func. Count:     69,   Neg. LLF: 6338.5250677372505\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6338.52504692504\n",
      "Iteration:     13,   Func. Count:     78,   Neg. LLF: 6338.525046928156\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6338.52504692504\n",
      "            Iterations: 13\n",
      "            Function evaluations: 78\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31195.19643728564\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7296.2360770610985\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1763927302.335193\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 252790.84505838316\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6382.779489880288\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7954.67715946243\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6415.029704820891\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6349.999981736526\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6340.227544224594\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6340.161311829131\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6340.161035983836\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6340.1610359820315\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6340.161035983836\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31138.51357619372\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7297.864139643784\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1762787855.3883734\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 273942.3602807635\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6385.445556605668\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7936.412270382881\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6419.6421799594245\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6351.568420130403\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6341.873323202479\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6341.8022702997205\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6341.801947757119\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6341.801947755001\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6341.801947757119\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31181.920523279336\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7299.369751056047\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1761470472.0964828\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 216746.35229852845\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6389.734853940312\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7883.562153205998\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6427.555465564632\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6352.761834785925\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6343.237324401049\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6343.148694930549\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6343.148236728803\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6343.14823672569\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6343.148236728803\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31272.876333739256\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7301.412296417197\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1764539816.0200987\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 165724.48603567178\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6391.546300748851\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7890.003853529191\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6427.86729925725\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6354.728061914149\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6345.204583003322\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6345.117770325418\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6345.117312437969\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6345.1173124349125\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6345.117312437969\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31206.312683992226\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7303.108394657095\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 18343861.428389728\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 178592.5229691111\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6393.831131317931\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7885.911948983306\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6431.548872958787\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6356.439841410697\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6346.944715031749\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6346.858587087861\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6346.858113336739\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6346.858113333604\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6346.858113336739\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31170.12721556804\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7304.661314890669\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 11407778.063166777\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 171807.46544487705\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6397.37137104043\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7858.328728771402\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6438.500214761234\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6357.8648254764375\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6348.451020396664\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6348.358763604674\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6348.358221353402\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6348.358221349765\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6348.358221353402\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31144.909610515686\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7306.186784341284\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1760725254.223268\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 166833.99604395582\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6401.145029528196\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7829.780041923721\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6446.455802881713\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6359.242269362628\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6349.894867076534\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6349.797689574681\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6349.797085464509\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6349.797085460386\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6349.797085464509\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31205.69986412805\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7307.864772951165\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 23290664.11474553\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 119490.0870929723\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6405.541273686014\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7798.64854577734\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6454.373084088557\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6360.66824198209\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6351.388929253257\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6351.28693688142\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6351.286256212126\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6351.286256207424\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6351.286256212126\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31183.719890024095\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7309.386162887065\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 27065496.045594692\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 107510.42573176674\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6409.918039574035\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7771.860332551573\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6464.416844572404\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6362.035740403846\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6352.794184950535\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6352.693931280664\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6352.693209563744\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6352.693209558649\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6352.693209563744\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31228.856157748673\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7310.956920187993\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1759484178.1592877\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 85112.00848754321\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6415.24737356783\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7739.031522840851\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6476.766001188907\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6363.328260337517\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6354.11487534984\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6354.01821544238\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6354.017447949988\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6354.017447944361\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6354.017447949988\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31284.49560038292\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7312.836851047534\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1760756117.332926\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 79662.92073177037\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6416.594525815107\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7743.2257189774655\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6475.949143776808\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6365.091528511476\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6355.879359790264\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6355.77873137528\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6355.777948587851\n",
      "Iteration:     12,   Func. Count:     74,   Neg. LLF: 6355.777948582188\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6355.777948587851\n",
      "            Iterations: 12\n",
      "            Function evaluations: 74\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31260.245138542665\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7314.368234392917\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10874332.067348152\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 71073.624402645\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6421.097877423657\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7722.743905340252\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6487.348566344838\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6366.480195255853\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6357.273288839966\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6357.181146641476\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6357.180355694199\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6357.180355240516\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6357.180355240516\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31274.590190126226\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7315.826539856695\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 34224254.46937849\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 54861.57488956098\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6428.294565699132\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7686.342173199081\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6508.409655883445\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6367.637665712111\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6358.421790499089\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6358.345952815417\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6358.345159070192\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6358.345158433116\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6358.345158433116\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31259.149405476164\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7317.3593780540305\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1759172381.2684455\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 53665.03131586021\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6432.1543669002385\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6368.9402960121715\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7680.656311910192\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6360.219872190339\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6359.728191819686\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6359.726579453889\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6359.726577944484\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6359.726577944558\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6359.726577944484\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31291.285161408672\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7318.912820464928\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 195511427.2730667\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 41198.696369016914\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6439.122600716428\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6370.1115312858965\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7644.828586120061\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6361.771413631432\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6360.958486426897\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6360.9563598664645\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6360.9563576240635\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6360.956357624289\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6360.9563576240635\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31318.41573989652\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7320.485066241379\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1760001221.29921\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 36013.22157795582\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6444.963230049834\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6371.327290058454\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7619.194373187346\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6363.338348476107\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6362.198422455961\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6362.195977385995\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6362.195974703566\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6362.195974703905\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6362.195974703566\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31343.30103056678\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 22353.913397022643\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 643068615.0445346\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6408.05683796678\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7764.220615643611\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9566.107564569653\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6406.361198489087\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6368.204420765334\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6370.855944100336\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6368.204442970729\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6367.799055408363\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6367.798734630895\n",
      "Iteration:     13,   Func. Count:     83,   Neg. LLF: 6367.79873367404\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6367.79873367404\n",
      "            Iterations: 13\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31252.07558880216\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21915.8532173036\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 743544572.8677123\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6410.228493144319\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7762.6423648595855\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9052.349897877426\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6408.685039532012\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6371.067327588533\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6378.324944429882\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6370.112904958423\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6370.112729761783\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6370.112729764602\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6370.112729761783\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31248.596015910785\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21899.090160688043\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 879742018.0793142\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6411.650383686754\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7773.991432593655\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 10070.726032858876\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6409.989258644251\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6371.71774415057\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6372.733958722136\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6372.017331280418\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6371.419057074945\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6371.418843588201\n",
      "Iteration:     13,   Func. Count:     83,   Neg. LLF: 6371.418840639859\n",
      "Iteration:     14,   Func. Count:     87,   Neg. LLF: 6371.418840640245\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6371.418840639859\n",
      "            Iterations: 14\n",
      "            Function evaluations: 87\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31220.810434515293\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21759.807847227352\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 833772762.0536379\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6413.11479406772\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7784.425519609002\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 10629.817547627219\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6411.39726794958\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6372.9943681697105\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6372.828118892751\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6373.106398755675\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6372.801114357059\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6372.800845873551\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6372.800825007145\n",
      "Iteration:     14,   Func. Count:     86,   Neg. LLF: 6372.800825010199\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6372.800825007145\n",
      "            Iterations: 14\n",
      "            Function evaluations: 86\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31213.08505875012\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21584.02929715986\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 882321240.531145\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6414.491800825417\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7795.854207566232\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9914.190275153538\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6412.7592623043565\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6374.274221868812\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6374.360278275496\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6374.303882052058\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6374.07477600323\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6374.074745792126\n",
      "Iteration:     13,   Func. Count:     83,   Neg. LLF: 6374.074744726865\n",
      "Iteration:     14,   Func. Count:     87,   Neg. LLF: 6374.074744726928\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6374.074744726865\n",
      "            Iterations: 14\n",
      "            Function evaluations: 87\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31214.365314865005\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21304.394188439444\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 884288331.9214966\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6415.817072309341\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7808.034598511385\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 8267.523103846084\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6414.226376273744\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6375.518613964752\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6375.539666706163\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6375.3997480776\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6375.297953957637\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6375.297950633864\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6375.297950628741\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6375.297950633864\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31261.23565937623\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21240.0125720521\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 866800321.7520174\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6417.387668314735\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7812.672717884892\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7711.6977405228245\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6415.915476786702\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6377.0784711228325\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6377.079492635167\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6376.913968613284\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6376.824647401689\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6376.824645556026\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6376.824645552884\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6376.824645556026\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31328.53534581653\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21732.028947731073\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 806881527.6173887\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6419.443917732238\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7803.099729699979\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 8705.427934668802\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6417.714908382084\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6379.145471132522\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6379.203283203004\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6379.078900488394\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6378.937147841258\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6378.937138032152\n",
      "Iteration:     13,   Func. Count:     83,   Neg. LLF: 6378.937137509154\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6378.937137509154\n",
      "            Iterations: 13\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31279.57993924138\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21691.678487820198\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 777650702.4449303\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6421.197798579422\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7804.442000199999\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9129.04514293954\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6419.460508748478\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6380.930985357962\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6380.999300046909\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6380.893460228297\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6380.726811740007\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6380.726796075397\n",
      "Iteration:     13,   Func. Count:     83,   Neg. LLF: 6380.726795393122\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6380.726795393122\n",
      "            Iterations: 13\n",
      "            Function evaluations: 83\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31299.305276957184\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21431.031707346716\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 773342283.0575063\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6422.524781635926\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7815.083744262511\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7857.949670783063\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6420.9762514433305\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6382.196511273258\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6382.210400607128\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6382.053368648284\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6381.960151494235\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6381.960149373779\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6381.960149370109\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6381.960149373779\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31294.49499442571\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20987.94892395427\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 886643776.5830841\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6423.512233877777\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7865.793401152663\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6604.377925546969\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6424.683584385781\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6388.1478617541\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6383.28634952853\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6383.149249559287\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6383.149239068053\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6383.14923906674\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6383.149239068053\n",
      "            Iterations: 12\n",
      "            Function evaluations: 76\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31324.901640571057\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20713.749861376622\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 876913708.2776911\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6425.0106602695705\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7858.179605294215\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6594.814330137032\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6427.341828639292\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6389.749227418676\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6384.620078485952\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6384.5019359204725\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6384.501923616743\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6384.501923615555\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6384.501923616743\n",
      "            Iterations: 12\n",
      "            Function evaluations: 76\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31334.126360694798\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 19826.20128715645\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 822740432.683258\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6426.323507105704\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7859.330143564004\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6534.463791930664\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6436.657417392679\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6393.245182522924\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6385.687340941917\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6385.647165581415\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6385.646800343222\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6385.646794662454\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6385.64679466602\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6385.646794662454\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31325.421494441383\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 18318.572568453324\n",
      "Iteration:      3,   Func. Count:     24,   Neg. LLF: 824508600.900178\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6426.5220013395965\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 7965.747920534719\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6439.347783520505\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6441.244159614356\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6406.9894831651945\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6386.863439892702\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6386.82606470958\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6386.824712199195\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6386.824688900802\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6386.824683356555\n",
      "Iteration:     14,   Func. Count:     85,   Neg. LLF: 6386.8246833572575\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6386.824683356555\n",
      "            Iterations: 14\n",
      "            Function evaluations: 85\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31341.827841230002\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 16099.470767121758\n",
      "Iteration:      3,   Func. Count:     24,   Neg. LLF: 896349131.976949\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6432.103340194615\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 7863.444609978774\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6489.092495451255\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6443.087615383207\n",
      "Iteration:      8,   Func. Count:     54,   Neg. LLF: 6403.584618512439\n",
      "Iteration:      9,   Func. Count:     60,   Neg. LLF: 6388.102118528056\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6388.075109149682\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6388.074356791947\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6388.074311854474\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6388.074309787819\n",
      "Iteration:     14,   Func. Count:     84,   Neg. LLF: 6388.074309791411\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6388.074309787819\n",
      "            Iterations: 14\n",
      "            Function evaluations: 84\n",
      "            Gradient evaluations: 14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31336.431573099067\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 12205.566844452756\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 116131184.95879577\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 16932.34213841179\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 1836287599.5102232\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6413.961746854302\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 8801.4650718956\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6403.497289284438\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6389.421231694128\n",
      "Iteration:     10,   Func. Count:     64,   Neg. LLF: 6389.508465612211\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6389.404307174016\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6389.404005066699\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6389.404002716994\n",
      "Iteration:     14,   Func. Count:     85,   Neg. LLF: 6389.404002007799\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6389.404002007799\n",
      "            Iterations: 14\n",
      "            Function evaluations: 85\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31344.06599851647\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7349.862980621778\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1763989803.1880608\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 117478.66085482997\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6462.087971869761\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7695.482880813515\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6557.368235860302\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6399.909390451905\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6390.55929550449\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6390.437380992206\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6390.436467532339\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6390.436467030459\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6390.436467030459\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31348.254954856267\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7351.464005151434\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 24924642.249570332\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 124292.73594054823\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6461.995535705984\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7704.790859433654\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6553.515260146108\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6401.467917001516\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6392.111379296565\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6391.98148639763\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6391.980589360602\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6391.980588897304\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6391.980588897304\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31362.44291957959\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7352.919079838775\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 10420823.670078643\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 91501.88376328959\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6467.802883383878\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 7685.929743245825\n",
      "Iteration:      7,   Func. Count:     47,   Neg. LLF: 6576.467614878658\n",
      "Iteration:      8,   Func. Count:     53,   Neg. LLF: 6402.519923745398\n",
      "Iteration:      9,   Func. Count:     59,   Neg. LLF: 6393.107255700897\n",
      "Iteration:     10,   Func. Count:     65,   Neg. LLF: 6393.015482898785\n",
      "Iteration:     11,   Func. Count:     70,   Neg. LLF: 6393.0146607302195\n",
      "Iteration:     12,   Func. Count:     75,   Neg. LLF: 6393.014660161505\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6393.014660161505\n",
      "            Iterations: 12\n",
      "            Function evaluations: 75\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31355.255030212684\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 19143.326751455796\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 889585860.907954\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6435.588698171753\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7889.573253609038\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6491.872238224198\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6455.377746773545\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6406.33902324004\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6394.933802614616\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6394.923787854401\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6394.923453920073\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6394.923429123527\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6394.923429125976\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6394.923429123527\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31371.342420564553\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20337.239475336286\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 885304611.7948756\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6437.2585588035345\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7862.202847468735\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6595.678668851697\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6441.83210364265\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6399.651801498307\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6396.536064229185\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6396.4502590547945\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6396.450247412029\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6396.450247411007\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6396.450247412029\n",
      "            Iterations: 12\n",
      "            Function evaluations: 76\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31389.64372074113\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 18006.303600881354\n",
      "Iteration:      3,   Func. Count:     24,   Neg. LLF: 580888889.1248614\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6437.5027569467575\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 7959.200829174546\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6449.884555628944\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6493.979729787991\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6406.592422458146\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6397.487687170593\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6397.467561527766\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6397.467065399795\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6397.4670440303535\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6397.467042149894\n",
      "Iteration:     14,   Func. Count:     85,   Neg. LLF: 6397.467042150776\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6397.467042149894\n",
      "            Iterations: 14\n",
      "            Function evaluations: 85\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31402.803723885823\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 18216.337655825286\n",
      "Iteration:      3,   Func. Count:     24,   Neg. LLF: 933385724.4951177\n",
      "Iteration:      4,   Func. Count:     30,   Neg. LLF: 6438.710932823855\n",
      "Iteration:      5,   Func. Count:     36,   Neg. LLF: 7972.646954832897\n",
      "Iteration:      6,   Func. Count:     42,   Neg. LLF: 6451.4700833290335\n",
      "Iteration:      7,   Func. Count:     48,   Neg. LLF: 6546.787975858936\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6402.45843659532\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6398.801900112179\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6398.792548328702\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6398.792376074711\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6398.792361495063\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6398.792361495383\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6398.792361495063\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31414.02908117189\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21390.36623165191\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 897181502.0956032\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6441.5223516110145\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7848.261213149099\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6900.624015654697\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6442.246031688464\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6401.302176136776\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6400.881639112879\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6400.621359397822\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6400.62135008587\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6400.621350083183\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6400.62135008587\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31413.806925312874\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20200.748006364796\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 891711239.7435143\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6442.4877737632005\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7871.758468466757\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6575.54166848997\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6450.659705181156\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6404.650787541162\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6401.683553271232\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6401.633735161088\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6401.633397693953\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6401.633394340899\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6401.63339434376\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6401.633394340899\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31483.125424789774\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24962.031762997278\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 868973930.9393696\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6446.257371138864\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7831.20104283064\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7793.02333518432\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6445.426993184817\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6405.613804655961\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6405.623650799649\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6405.432365244707\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6405.343628816203\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6405.343627101623\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6405.34362709886\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6405.343627101623\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31465.557259308094\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24798.19507034574\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 881690485.8380258\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6447.445070760587\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7835.734459155699\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7208.676780499949\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6448.473913908702\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6407.018285803102\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6406.801713432185\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6406.44013579119\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6406.440121828511\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6406.440121825269\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6406.440121828511\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31447.172477940276\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25066.682131871785\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 884357378.0993221\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6449.3579110793125\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7833.54269069576\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 8174.210053168749\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6448.184586649881\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6408.679168865108\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6408.7022173662945\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6408.5462829294265\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6408.4602455818795\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6408.460244064049\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6408.460244061158\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6408.460244064049\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31444.246850895313\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24899.07645280326\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 885032952.4340377\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6450.556688158609\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7838.532309123029\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7293.743972057007\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6451.487793831351\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6410.084977523698\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6409.919844359396\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6409.552764350204\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6409.552751112353\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6409.552751109144\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6409.552751112353\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31439.75504716439\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24689.22847859499\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 885272800.3304327\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6451.736639435016\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7842.633035265064\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6901.997769784901\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6454.253276933196\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6411.709851224196\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6410.8816047150285\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6410.641398488562\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6410.641386536246\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6410.641386533089\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6410.641386536246\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31446.165667302215\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24401.695764653356\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 889097543.4809799\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6452.856828272428\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7846.444702274265\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6698.731534584524\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6456.756910391206\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6413.947798792463\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6411.816829875424\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6411.668306902146\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6411.668301477908\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6411.66830147555\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6411.668301477908\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31439.47784652849\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24542.32708435993\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 828866009.7326229\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6454.372775595848\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7847.301011244985\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6757.6317811440995\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6457.884284710761\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6414.87668682733\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6413.377233445932\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6413.204337198029\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6413.20432995\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6413.20432994734\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6413.20432995\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31444.355299959243\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24282.3817461767\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 885115852.0879714\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6455.5457324402705\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7850.112861108595\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6679.0540705368385\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6459.8022866154515\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6416.913568013781\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6414.449421244146\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6414.316119257739\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6414.316114281348\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6414.316114279105\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6414.316114281348\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31433.43566919442\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24606.4471039204\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 818745315.7427874\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6457.189632307198\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7850.339753915914\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6776.382977852396\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6460.739437729609\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6417.542955406259\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6416.179954812823\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6416.005656756732\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6416.005649194029\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6416.005649191265\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6416.005649194029\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31441.284648947174\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24403.259499804437\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 859847765.2591121\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6458.416651182851\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7852.7271358836715\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6710.924542049772\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6462.506585934422\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6419.243531853557\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6417.331934251459\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6417.187187685733\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6417.187182329724\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6417.187182327286\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6417.187182329724\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31471.637726101137\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23991.752369064587\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 889443912.9636638\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6459.472795197742\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7855.897392327063\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6650.11722527951\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6465.016933870799\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6421.776867904668\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6418.266885013762\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6418.165325402195\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6418.165317450901\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6418.165317449348\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6418.165317450901\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31496.888221896254\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23614.49451725653\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 878908509.2699292\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6460.561351028777\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7858.806365286791\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6626.756894887729\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6468.826655396925\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6422.723089159498\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6419.278222166007\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6419.208197525153\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6419.207652761972\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6419.207646895072\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6419.207646898918\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6419.207646895072\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31502.120351806403\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23809.854120650503\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 813923579.7793841\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6461.925655435695\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7859.732200745193\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6632.999028782751\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6469.78738422565\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6424.028072126486\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6420.644055889166\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6420.569153740174\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6420.569142185635\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6420.569142184591\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6420.569142185635\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31513.20531122928\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23342.982995497863\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 890842206.0347278\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6462.965534387255\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7862.956543245018\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6616.00386822588\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6472.9358395482595\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6424.909680878065\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6421.636209192181\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6421.5802260564815\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6421.57984731776\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6421.579843237777\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6421.579843241112\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6421.579843237777\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31530.82969712033\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24120.017651156064\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 888162856.5365725\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6464.624368774188\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7861.632187691492\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6645.828496552118\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6471.49893045801\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6426.567878979937\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6423.3401865164615\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6423.254127196932\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6423.2541180532335\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6423.254118051911\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6423.2541180532335\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31544.083835401878\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23958.516193308635\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 664277262.2174199\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6465.805108867789\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7863.597660878718\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6637.294521239128\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6473.84142827426\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6427.657558430451\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6424.486770348962\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6424.412925924928\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6424.412914943514\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6424.412914942428\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6424.412914943514\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31555.887923152706\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23354.04992046524\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 892170335.1129091\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6466.7584226500785\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7867.121309155484\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6617.600175552452\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6477.1752870403025\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6428.46584771195\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6425.39035999567\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6425.33727444501\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6425.336933815871\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6425.336930134297\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6425.336930137444\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6425.336930134297\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31567.893271471614\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 22423.16106502209\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 760713305.8751006\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6467.640809537212\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7873.810483780315\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6590.554494042635\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6481.410884416166\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6429.369076229867\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6426.251032241918\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6426.21834791449\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6426.218168430774\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6426.218165916885\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6426.218165919075\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6426.218165916885\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31580.575099390557\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20736.700090164984\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 839748818.9684422\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6468.279477757249\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7906.727993868928\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6513.8832883571595\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6495.520397036847\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6441.166931160849\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6427.075816285807\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6427.069011129834\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6427.068854469039\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6427.068835896332\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6427.068835899814\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6427.068835896332\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31593.019586735623\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7394.602443736816\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1773654366.6902196\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 71160.9059837393\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6517.403765139765\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6437.472214342481\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7619.6656587288835\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6431.786760674604\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6427.894362016794\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6427.892489727328\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6427.892487217936\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6427.892487217998\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6427.892487217936\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31576.549014825225\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7396.190539241834\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 20141891.229521286\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 69476.52935212223\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6519.307135489041\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6438.540359804744\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7620.932960010722\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6432.773427236855\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6428.97560734632\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6428.973690031806\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6428.973687605208\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6428.973687605217\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6428.973687605208\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31557.80158659435\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 7397.766955548989\n",
      "Iteration:      3,   Func. Count:     22,   Neg. LLF: 1774516343.3754945\n",
      "Iteration:      4,   Func. Count:     28,   Neg. LLF: 74109.89994059432\n",
      "Iteration:      5,   Func. Count:     34,   Neg. LLF: 6520.4023541253255\n",
      "Iteration:      6,   Func. Count:     40,   Neg. LLF: 6439.574831028638\n",
      "Iteration:      7,   Func. Count:     46,   Neg. LLF: 7625.346121403575\n",
      "Iteration:      8,   Func. Count:     52,   Neg. LLF: 6433.626405383702\n",
      "Iteration:      9,   Func. Count:     58,   Neg. LLF: 6430.017254863247\n",
      "Iteration:     10,   Func. Count:     63,   Neg. LLF: 6430.015335830918\n",
      "Iteration:     11,   Func. Count:     68,   Neg. LLF: 6430.015333538566\n",
      "Iteration:     12,   Func. Count:     72,   Neg. LLF: 6430.01533353851\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6430.015333538566\n",
      "            Iterations: 12\n",
      "            Function evaluations: 72\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31528.810584214145\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21654.403384056393\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 632889191.9718641\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6473.104474938413\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7889.099906117191\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6589.337040535504\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6487.151007147558\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6434.408425467979\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6431.758351520326\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6431.730404183251\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6431.730261537043\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6431.73025936307\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6431.7302593648055\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6431.73025936307\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31512.497473464526\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 21838.745163873784\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 910434686.3153044\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6474.332043753124\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7888.912847652957\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6604.530305778708\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6486.5801715898815\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6435.455280359663\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6432.994776059739\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6432.95882787636\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6432.958642949176\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6432.958640753881\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6432.958640756016\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6432.958640753881\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31510.851660394543\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 20392.870448255635\n",
      "Iteration:      3,   Func. Count:     25,   Neg. LLF: 898769176.1085216\n",
      "Iteration:      4,   Func. Count:     31,   Neg. LLF: 6475.143809668985\n",
      "Iteration:      5,   Func. Count:     37,   Neg. LLF: 7911.468985344325\n",
      "Iteration:      6,   Func. Count:     43,   Neg. LLF: 6533.781100257237\n",
      "Iteration:      7,   Func. Count:     49,   Neg. LLF: 6498.859871354618\n",
      "Iteration:      8,   Func. Count:     55,   Neg. LLF: 6440.463251417603\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6433.88420442246\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6433.8776351567985\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6433.877425066652\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6433.877409256635\n",
      "Iteration:     13,   Func. Count:     80,   Neg. LLF: 6433.877409258388\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6433.877409256635\n",
      "            Iterations: 13\n",
      "            Function evaluations: 80\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31571.565315907017\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 22692.257720353824\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 819235382.1069285\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6476.8769582518335\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7883.881333948446\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6670.8470631797245\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6482.31363856274\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6437.710302878556\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6435.568530878734\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6435.472605234807\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6435.472599745726\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6435.4725997437035\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6435.472599745726\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31610.197137452808\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24240.26560053337\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 895851404.1559398\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6478.765181899493\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7877.623073077783\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6956.9581051515415\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6482.9495526548\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6438.093489552529\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6437.533684215951\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6437.372209276378\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6437.372200530321\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6437.3722005267755\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6437.372200530321\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31625.235319883068\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23709.675563563796\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 902307228.6450136\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6479.708695763504\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7881.149416437289\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6744.25191836438\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6484.867564951597\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6439.539718819931\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6438.388868860162\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6438.270398821094\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6438.270394145344\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6438.270394142544\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6438.270394145344\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31643.49047213563\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 23201.874485560103\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 808981613.1583842\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6480.713983084252\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7884.937357598015\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6682.773514183585\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6486.287548241941\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6441.206892929541\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6439.354205467129\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6439.254686666436\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6439.254682184226\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6439.254682181936\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6439.254682184226\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31658.763190691643\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24512.967662025054\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 785650820.2199388\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6482.564754497014\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7880.77993441847\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7057.731168583994\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6486.67400038783\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6441.783828168067\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6441.325467848868\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6441.155045864083\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6441.155036128084\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6441.155036124412\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6441.155036128084\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31666.026602605394\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24636.99245086399\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 886441283.865451\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6483.882134167172\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7881.760099662537\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7088.909133337163\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6487.9905695424295\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6443.0872377081805\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6442.648189858896\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6442.475674412808\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6442.475664415859\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6442.475664412157\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6442.475664415859\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31663.26361888512\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25456.582763082035\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 725968454.3205914\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6485.795042669892\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7880.676946628957\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9940.904844378882\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6486.985503162544\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6444.710294263725\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6444.668993608136\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6444.568480742675\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6444.513364941874\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6444.513363639377\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6444.513363637017\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6444.513363639377\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31691.280919426194\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 25122.895748419585\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 885147616.3333544\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6486.802918995393\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7882.963725269552\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7458.464335711355\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6490.285467443631\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6445.865154179211\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6445.623235747054\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6445.419065493028\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6445.419054029986\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6445.419054026483\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6445.419054029986\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31715.353499761528\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 24713.721532686264\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 813428942.7202604\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6487.789277786788\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7886.043628483778\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6872.041055299787\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6492.863245028229\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6447.230670030662\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6446.463667995337\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6446.32769724077\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6446.327690177795\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6446.327690174441\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6446.327690177795\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31520.695229543027\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27332.410489628754\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 834123695.9073662\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6493.830981294935\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7881.85538033786\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 11810.618730354021\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6492.404962487933\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6454.036035360017\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6453.445427006616\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6453.138357802537\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6453.138249974285\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6453.138249107664\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6453.138249107664\n",
      "            Iterations: 12\n",
      "            Function evaluations: 78\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31512.462586327412\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27342.452028042346\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 762902888.0226727\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6495.186094020689\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7884.523366779111\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 11634.169827316566\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6493.668506047859\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6455.035946873219\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6454.618351765032\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6454.42391056883\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6454.423842576294\n",
      "Iteration:     12,   Func. Count:     78,   Neg. LLF: 6454.423841434473\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6454.423841434772\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6454.423841434473\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31516.21858676851\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27349.10998082884\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 876181968.3702271\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6496.478581690404\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7887.876247413719\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 11361.69071598419\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6494.849250080151\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6455.994256796202\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6455.756734210611\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6455.716511596471\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6455.626847476247\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6455.626564071125\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6455.626556151975\n",
      "Iteration:     14,   Func. Count:     85,   Neg. LLF: 6455.626556155281\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6455.626556151975\n",
      "            Iterations: 14\n",
      "            Function evaluations: 85\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31560.298461346014\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27344.650347906634\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 851320708.2549378\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6497.706211167226\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7891.68006357754\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 10900.650604929684\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6497.861049767144\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6456.8858500036\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6456.7486529687685\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6456.749677413296\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6456.733616954017\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6456.732778599506\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6456.732777329073\n",
      "Iteration:     14,   Func. Count:     86,   Neg. LLF: 6456.732777331778\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6456.732777329073\n",
      "            Iterations: 14\n",
      "            Function evaluations: 86\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31598.83423034123\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27341.647876919626\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 880318980.8862936\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6498.89712859369\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7895.428591191259\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 10275.626206728259\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6501.7520795252085\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6457.968331305284\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6457.873604851116\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6457.856823857239\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6457.798247530134\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6457.797542427605\n",
      "Iteration:     13,   Func. Count:     82,   Neg. LLF: 6457.7975417877105\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6457.7975417877105\n",
      "            Iterations: 13\n",
      "            Function evaluations: 82\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31571.25168372549\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27357.499462878695\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 709808001.4140244\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6500.511956040381\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7896.0470765881655\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 10522.026661270107\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6502.50735547644\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6459.588101774394\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6459.481949832428\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6459.4953593801165\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6459.44818407503\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6459.447926529386\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6459.4479265279815\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6459.447926529386\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31612.014714701363\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27353.75195708181\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 698979835.1827304\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6501.7124841527075\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7899.29199290633\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9854.943280573129\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6505.860787815067\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6460.809179444448\n",
      "Iteration:      9,   Func. Count:     61,   Neg. LLF: 6460.653667677056\n",
      "Iteration:     10,   Func. Count:     66,   Neg. LLF: 6460.600785868208\n",
      "Iteration:     11,   Func. Count:     71,   Neg. LLF: 6460.538805134085\n",
      "Iteration:     12,   Func. Count:     76,   Neg. LLF: 6460.53783196921\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6460.537814939129\n",
      "Iteration:     14,   Func. Count:     85,   Neg. LLF: 6460.537814937361\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6460.537814939129\n",
      "            Iterations: 14\n",
      "            Function evaluations: 85\n",
      "            Gradient evaluations: 14\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31645.1360058765\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27352.028995564124\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 869234724.431315\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6503.071990852336\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7901.360064482002\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 9193.80769134744\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6508.049724238468\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6462.253108248905\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6462.016091891288\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6461.846667785818\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6461.846650345113\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6461.846650341423\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6461.846650345113\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31650.97123078173\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27358.124084816704\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 873694817.7738799\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6504.30225806998\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7903.738234222066\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7249.499659988578\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6511.097163661283\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6463.71113414476\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6463.131334227222\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6463.0101559052655\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6463.010146317963\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6463.010146313972\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6463.010146317963\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31679.99635191757\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27357.35669402113\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 877419380.6406734\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6505.40941861099\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7906.130012587449\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6734.574982708269\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6514.271884881269\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6466.001529558537\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6464.103538464176\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6464.022145488467\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6464.022137771513\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6464.022137769485\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6464.022137771513\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31686.26446509918\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27363.232026993086\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 860574159.6265241\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6507.06172094851\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7907.476383943326\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6830.507311182355\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6515.159962661432\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6466.954265448861\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6465.820435935785\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6465.727025950999\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6465.727022252589\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6465.727022249387\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6465.727022252589\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31684.67674764743\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27371.47807322252\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 859374522.4668242\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6508.402483702264\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7909.09337367268\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6785.624937864146\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6516.844415173517\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6468.475449466547\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6467.13996015418\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6467.052007375365\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6467.052003427258\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6467.05200342435\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6467.052003427258\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31682.32669545973\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27380.264078155487\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 748214196.1620936\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6509.8065764632665\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7910.603109838601\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6798.110384781568\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6518.2309492029435\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6469.807814986217\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6468.546223543378\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6468.457725974377\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6468.457722217505\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6468.457722214491\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6468.457722217505\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31707.61485368695\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27380.513683379995\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 871117656.1036994\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6510.834044381635\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7912.44929329009\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6686.314308472713\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6523.928461936217\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6471.36723891759\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6469.4560042313515\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6469.409082720751\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6469.409065907316\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6469.409065906574\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6469.409065907316\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31690.661766717665\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27395.082971405613\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 806594818.474781\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6512.721489981281\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7913.91027818882\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6821.899574546394\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6521.0997046078455\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6472.643052428704\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6471.471877801148\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6471.382151236188\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6471.382147609573\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6471.382147606444\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6471.382147609573\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31697.373152090782\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27401.279870283866\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 734612296.646648\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6513.98317986349\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7915.494943708233\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6757.781662758467\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6522.968306232376\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6474.299933427651\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6472.7013619028785\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6472.619796048973\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6472.619790418795\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6472.619790416406\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6472.619790418795\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31669.86768722432\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27417.84374349127\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 758172384.3408445\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6515.727334006047\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7916.706363350363\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 7100.666054445444\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6523.192705422218\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6475.219183946761\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6474.530376218722\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6474.423376771082\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6474.423369750162\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6474.423369746395\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6474.423369750162\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31708.643773969994\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27414.893074485735\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 877586258.9983244\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6516.768746357465\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7918.5648358886\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6739.270004530029\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6526.550991166634\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6477.3182052445645\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6475.462984483494\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6475.389474955653\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6475.389465982696\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6475.3894659809175\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6475.389465982696\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31712.306043442346\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27420.328531268526\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 845672154.5879631\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6518.431954689979\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7920.182198063705\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6786.570788637767\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6527.264735669689\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6478.55820906638\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6477.169454273932\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6477.085726534307\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6477.08572222834\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6477.085722225611\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6477.08572222834\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31737.006726743046\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27420.843384411284\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 880568923.7775272\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6519.451654932196\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7921.917791420497\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6691.834106462136\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6533.216752793616\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6479.984692369617\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6478.083919557474\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6478.040680988957\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6478.04048446795\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6478.040482301498\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6478.04048230391\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6478.040482301498\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31759.393651510898\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27421.706361376026\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 869505312.9599967\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6520.563921747826\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7923.339459229415\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6656.602031086589\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6538.036624107622\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6481.189335538023\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6479.140840818202\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6479.114981536482\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6479.114863530223\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6479.114861274282\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6479.114861275596\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6479.114861274282\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31764.545841210147\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27427.785833587535\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 882575208.5832233\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6522.04739834816\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7925.210687800368\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6661.7380800918845\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6539.163719408424\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6482.677651141188\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6480.640478841346\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6480.613295517411\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6480.61317334619\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6480.613171172943\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6480.613171174358\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6480.613171172943\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31763.441720363917\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27440.198389403296\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 855303990.269125\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6524.625282038334\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7926.941170403763\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6910.163268728312\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6532.686396341991\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6484.38523672185\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6483.402244550642\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6483.307837406952\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6483.307833563566\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6483.307833560235\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6483.307833563566\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31792.20778871377\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27439.78594015167\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 825517326.1229546\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6525.808625217227\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7928.908486551719\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6732.021385258521\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6536.988966848951\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6486.403906028263\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6484.493138081686\n",
      "Iteration:     10,   Func. Count:     68,   Neg. LLF: 6484.4325816439505\n",
      "Iteration:     11,   Func. Count:     73,   Neg. LLF: 6484.432569154898\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6484.432569153862\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6484.432569154898\n",
      "            Iterations: 12\n",
      "            Function evaluations: 77\n",
      "            Gradient evaluations: 12\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31814.141787859753\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27441.087616833018\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 802985097.439593\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6526.93148826977\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7930.767487298455\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6667.912505273482\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6544.027918373682\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6487.669405648156\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6485.524153703739\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6485.497232739862\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6485.497107015781\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6485.497104712216\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6485.497104713584\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6485.497104712216\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31814.7061776937\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27448.588742630593\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 865468692.7351764\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6528.203558633237\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7932.215617741083\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6657.004041733462\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6546.729591360763\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6489.018835995676\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6486.775892065344\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6486.75403183277\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6486.753916015452\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6486.75391308557\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6486.753913086496\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6486.75391308557\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31827.212067294815\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27453.106735650956\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 851792657.7741628\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6529.839142157857\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7933.778252238515\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6674.5874716598355\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6546.580304010113\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6490.556916187064\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6488.442006689824\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6488.413699523461\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6488.413569924055\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6488.413567721374\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6488.413567722853\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6488.413567721374\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31833.53487782045\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27458.174472073275\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 811256845.4248843\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6530.85423646554\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7935.483325710416\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6631.66380342204\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6553.183541658372\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6492.2164251568\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6489.383663382987\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6489.37169982888\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6489.371550566519\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6489.371542443834\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6489.371542444197\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6489.371542443834\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31839.471866329422\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27463.7857770627\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 848212040.9739316\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6531.961650613774\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7936.8003111550515\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6617.2188187190695\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6556.779446512433\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6493.893264530518\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6490.460598374721\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6490.452704644498\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6490.452502094233\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6490.45248781727\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6490.452487817945\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6490.45248781727\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31853.87727632497\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27466.68549680272\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 875274785.6897595\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6532.907332331924\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7937.7199238574485\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6600.349182525127\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6561.071863641504\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6496.181180384296\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6491.364961692082\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6491.360123685872\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6491.359898086661\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6491.359877614705\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6491.359877616653\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6491.359877614705\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31870.123553768964\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27470.329666947822\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 791138744.828109\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6534.072880569374\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7938.7816854758175\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6599.413532660676\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6562.677974356542\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6497.425818688427\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6492.5275976966095\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6492.5229974196045\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6492.52278051033\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6492.522759964229\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6492.522759966323\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6492.522759964229\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31888.545825315483\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27471.88239896716\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 848531115.0729666\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6534.984591482951\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7939.318728378417\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6593.414437038108\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6565.155643990614\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6499.096420875911\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6493.426668281576\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6493.422571460904\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6493.422395464659\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6493.422374351441\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6493.422374353946\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6493.422374351441\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n",
      "Iteration:      1,   Func. Count:      6,   Neg. LLF: 31905.289248432866\n",
      "Iteration:      2,   Func. Count:     16,   Neg. LLF: 27479.196887403108\n",
      "Iteration:      3,   Func. Count:     26,   Neg. LLF: 877729892.6406671\n",
      "Iteration:      4,   Func. Count:     32,   Neg. LLF: 6536.862589991959\n",
      "Iteration:      5,   Func. Count:     38,   Neg. LLF: 7942.628148206317\n",
      "Iteration:      6,   Func. Count:     44,   Neg. LLF: 6601.5700685750635\n",
      "Iteration:      7,   Func. Count:     50,   Neg. LLF: 6565.590568740126\n",
      "Iteration:      8,   Func. Count:     56,   Neg. LLF: 6500.371997792154\n",
      "Iteration:      9,   Func. Count:     62,   Neg. LLF: 6495.327974647998\n",
      "Iteration:     10,   Func. Count:     67,   Neg. LLF: 6495.323476274916\n",
      "Iteration:     11,   Func. Count:     72,   Neg. LLF: 6495.323260299759\n",
      "Iteration:     12,   Func. Count:     77,   Neg. LLF: 6495.323239215251\n",
      "Iteration:     13,   Func. Count:     81,   Neg. LLF: 6495.323239217434\n",
      "Optimization terminated successfully    (Exit mode 0)\n",
      "            Current function value: 6495.323239215251\n",
      "            Iterations: 13\n",
      "            Function evaluations: 81\n",
      "            Gradient evaluations: 13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/arch/__future__/_utility.py:11: FutureWarning: \n",
      "The default for reindex is True. After September 2021 this will change to\n",
      "False. Set reindex to True or False to silence this message. Alternatively,\n",
      "you can use the import comment\n",
      "\n",
      "from arch.__future__ import reindexing\n",
      "\n",
      "to globally set reindex to True and silence this warning.\n",
      "\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "garch_forecast = []\n",
    "\n",
    "for i in range(len(test_data)):\n",
    "    train = arma_resid[:-(len(test_data)-i)]\n",
    "    model = arch_model(train, vol = 'GARCH', p = 1, q = 1)\n",
    "    garch_fit = model.fit()\n",
    "    prediction = garch_fit.forecast(horizon=1)\n",
    "    garch_forecast.append(np.sqrt(prediction.variance.values[-1:][0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5e190195",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-11-016751a6e38b>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['GARCH預測波動度'] = (garch_forecast)\n"
     ]
    }
   ],
   "source": [
    "test_data['GARCH預測波動度'] = (garch_forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f58d75d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-12-f2b3397fd39e>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測區間上限'] = test_data['ARMA預測報酬(%)'] + test_data['GARCH預測波動度']\n",
      "<ipython-input-12-f2b3397fd39e>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測區間下限'] = test_data['ARMA預測報酬(%)'] - test_data['GARCH預測波動度']\n"
     ]
    }
   ],
   "source": [
    "test_data['預測區間上限'] = test_data['ARMA預測報酬(%)'] + test_data['GARCH預測波動度']\n",
    "test_data['預測區間下限'] = test_data['ARMA預測報酬(%)'] - test_data['GARCH預測波動度']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "da6aded9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盤價</th>\n",
       "      <th>日報酬率(%)</th>\n",
       "      <th>ARMA預測報酬(%)</th>\n",
       "      <th>GARCH預測波動度</th>\n",
       "      <th>預測區間上限</th>\n",
       "      <th>預測區間下限</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年月日</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-04</th>\n",
       "      <td>124.35</td>\n",
       "      <td>1.7178</td>\n",
       "      <td>0.007639</td>\n",
       "      <td>[0.8279701855095494]</td>\n",
       "      <td>[0.8356094020683877]</td>\n",
       "      <td>[-0.820330968950711]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-05</th>\n",
       "      <td>124.60</td>\n",
       "      <td>0.2010</td>\n",
       "      <td>0.103229</td>\n",
       "      <td>[0.8091855341421339]</td>\n",
       "      <td>[0.9124143619831312]</td>\n",
       "      <td>[-0.7059567063011366]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-06</th>\n",
       "      <td>125.95</td>\n",
       "      <td>1.0835</td>\n",
       "      <td>0.132871</td>\n",
       "      <td>[0.8441208942549913]</td>\n",
       "      <td>[0.9769922034464709]</td>\n",
       "      <td>[-0.7112495850635117]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-07</th>\n",
       "      <td>128.90</td>\n",
       "      <td>2.3422</td>\n",
       "      <td>0.064917</td>\n",
       "      <td>[0.8296300476106613]</td>\n",
       "      <td>[0.8945467540845707]</td>\n",
       "      <td>[-0.7647133411367518]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-08</th>\n",
       "      <td>131.20</td>\n",
       "      <td>1.7843</td>\n",
       "      <td>-0.019291</td>\n",
       "      <td>[0.8238660699703705]</td>\n",
       "      <td>[0.8045751953491894]</td>\n",
       "      <td>[-0.8431569445915515]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-24</th>\n",
       "      <td>143.05</td>\n",
       "      <td>0.2804</td>\n",
       "      <td>0.049718</td>\n",
       "      <td>[0.9865795261408391]</td>\n",
       "      <td>[1.0362978734712274]</td>\n",
       "      <td>[-0.936861178810451]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-27</th>\n",
       "      <td>144.15</td>\n",
       "      <td>0.7690</td>\n",
       "      <td>0.048563</td>\n",
       "      <td>[0.9597117572942437]</td>\n",
       "      <td>[1.0082750887850893]</td>\n",
       "      <td>[-0.9111484258033982]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-28</th>\n",
       "      <td>145.30</td>\n",
       "      <td>0.7978</td>\n",
       "      <td>0.047542</td>\n",
       "      <td>[0.9506302616278288]</td>\n",
       "      <td>[0.9981720612572778]</td>\n",
       "      <td>[-0.9030884619983799]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-29</th>\n",
       "      <td>145.95</td>\n",
       "      <td>0.4474</td>\n",
       "      <td>0.047820</td>\n",
       "      <td>[0.9271465317681756]</td>\n",
       "      <td>[0.9749665565744965]</td>\n",
       "      <td>[-0.8793265069618548]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-30</th>\n",
       "      <td>145.50</td>\n",
       "      <td>-0.3083</td>\n",
       "      <td>0.049033</td>\n",
       "      <td>[0.9613430278034946]</td>\n",
       "      <td>[1.0103761933904474]</td>\n",
       "      <td>[-0.9123098622165418]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               收盤價  日報酬率(%)  ARMA預測報酬(%)            GARCH預測波動度  \\\n",
       "年月日                                                              \n",
       "2021-01-04  124.35   1.7178     0.007639  [0.8279701855095494]   \n",
       "2021-01-05  124.60   0.2010     0.103229  [0.8091855341421339]   \n",
       "2021-01-06  125.95   1.0835     0.132871  [0.8441208942549913]   \n",
       "2021-01-07  128.90   2.3422     0.064917  [0.8296300476106613]   \n",
       "2021-01-08  131.20   1.7843    -0.019291  [0.8238660699703705]   \n",
       "...            ...      ...          ...                   ...   \n",
       "2021-12-24  143.05   0.2804     0.049718  [0.9865795261408391]   \n",
       "2021-12-27  144.15   0.7690     0.048563  [0.9597117572942437]   \n",
       "2021-12-28  145.30   0.7978     0.047542  [0.9506302616278288]   \n",
       "2021-12-29  145.95   0.4474     0.047820  [0.9271465317681756]   \n",
       "2021-12-30  145.50  -0.3083     0.049033  [0.9613430278034946]   \n",
       "\n",
       "                          預測區間上限                 預測區間下限  \n",
       "年月日                                                      \n",
       "2021-01-04  [0.8356094020683877]   [-0.820330968950711]  \n",
       "2021-01-05  [0.9124143619831312]  [-0.7059567063011366]  \n",
       "2021-01-06  [0.9769922034464709]  [-0.7112495850635117]  \n",
       "2021-01-07  [0.8945467540845707]  [-0.7647133411367518]  \n",
       "2021-01-08  [0.8045751953491894]  [-0.8431569445915515]  \n",
       "...                          ...                    ...  \n",
       "2021-12-24  [1.0362978734712274]   [-0.936861178810451]  \n",
       "2021-12-27  [1.0082750887850893]  [-0.9111484258033982]  \n",
       "2021-12-28  [0.9981720612572778]  [-0.9030884619983799]  \n",
       "2021-12-29  [0.9749665565744965]  [-0.8793265069618548]  \n",
       "2021-12-30  [1.0103761933904474]  [-0.9123098622165418]  \n",
       "\n",
       "[244 rows x 6 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "26fcb950",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fae76275f70>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "\n",
    "plt.plot(test_data['日報酬率(%)'])\n",
    "plt.plot(test_data['ARMA預測報酬(%)'])\n",
    "plt.plot(test_data['預測區間上限'], color = 'g')\n",
    "plt.plot(test_data['預測區間下限'], color = 'g')\n",
    "\n",
    "\n",
    "plt.legend(('實際報酬', 'ARMA預測報酬', 'GARCH預測波動上限', 'GARCH預測波動下限'), fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b92462c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "first_price = test_data['收盤價'][0] / (1+test_data['日報酬率(%)'][0]*0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "111366ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-16-aab6e2119d29>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['ARMA預測價格'] = first_price * (1 + test_data['ARMA預測報酬(%)']*0.01)\n",
      "<ipython-input-16-aab6e2119d29>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測價格區間上限'] = first_price * (1 + test_data['預測區間上限']*0.01)\n",
      "<ipython-input-16-aab6e2119d29>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測價格區間下限'] = first_price * (1 + test_data['預測區間下限']*0.01)\n"
     ]
    }
   ],
   "source": [
    "test_data['ARMA預測價格'] = first_price * (1 + test_data['ARMA預測報酬(%)']*0.01)\n",
    "test_data['預測價格區間上限'] = first_price * (1 + test_data['預測區間上限']*0.01)\n",
    "test_data['預測價格區間下限'] = first_price * (1 + test_data['預測區間下限']*0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2deae054",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-17-dc5ea089bca3>:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['ARMA預測價格'][i] = test_data['ARMA預測價格'][i-1] * (1 + test_data['ARMA預測報酬(%)'][i]*0.01)\n",
      "/Users/wujinru/opt/anaconda3/lib/python3.8/site-packages/IPython/core/interactiveshell.py:3437: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "<ipython-input-17-dc5ea089bca3>:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測價格區間上限'][i] = test_data['預測價格區間上限'][i-1] * (1 + test_data['預測區間上限'][i]*0.01)\n",
      "<ipython-input-17-dc5ea089bca3>:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測價格區間下限'][i] = test_data['預測價格區間下限'][i-1] * (1 + test_data['預測區間下限'][i]*0.01)\n"
     ]
    }
   ],
   "source": [
    "for i in range(1, len(test_data)):\n",
    "    test_data['ARMA預測價格'][i] = test_data['ARMA預測價格'][i-1] * (1 + test_data['ARMA預測報酬(%)'][i]*0.01)\n",
    "    test_data['預測價格區間上限'][i] = test_data['預測價格區間上限'][i-1] * (1 + test_data['預測區間上限'][i]*0.01)\n",
    "    test_data['預測價格區間下限'][i] = test_data['預測價格區間下限'][i-1] * (1 + test_data['預測區間下限'][i]*0.01)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b2452e54",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-18-3c370926619f>:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  test_data['預測平均價格'] = (test_data['預測價格區間上限'] + test_data['預測價格區間下限']) / 2\n"
     ]
    }
   ],
   "source": [
    "test_data['預測平均價格'] = (test_data['預測價格區間上限'] + test_data['預測價格區間下限']) / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "a948b2e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fae765548e0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "\n",
    "plt.plot(test_data['收盤價'])\n",
    "plt.plot(test_data['ARMA預測價格'], color = 'r')\n",
    "plt.plot(test_data['預測平均價格'], color = 'r', linestyle='dashed')\n",
    "plt.plot(test_data['預測價格區間上限'], color = 'g')\n",
    "plt.plot(test_data['預測價格區間下限'], color = 'g')\n",
    "\n",
    "\n",
    "plt.legend(('實際價格', 'ARMA預測價格', '上下區間均價', '預測價格上區間', '預測價格下區間'), fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "61e8b3ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_date = test_data.index.get_level_values('年月日') <= '2021-03-01'\n",
    "\n",
    "new_test = test_data[new_date]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1ef5ee00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fae766b1070>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "\n",
    "plt.plot(new_test['收盤價'])\n",
    "plt.plot(new_test['ARMA預測價格'],color = 'r')\n",
    "plt.plot(new_test['預測平均價格'], color = 'r', linestyle='dashed')\n",
    "plt.plot(new_test['預測價格區間上限'], color = 'g')\n",
    "plt.plot(new_test['預測價格區間下限'], color = 'g')\n",
    "\n",
    "\n",
    "plt.legend(('實際價格', 'ARMA預測價格', '上下區間均價', '預測價格上區間', '預測價格下區間'), fontsize=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "add27d89",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "10999974",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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