bennylp/View Brosum.ipynb

## View Brosum.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c3b4ac2b",
   "metadata": {},
   "source": [
    "# Advanced Bandarmologi and Foreign Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db32c2b4",
   "metadata": {},
   "source": [
    "## Preamble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fe80828b",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ebdddbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17:39:04.278 INFO  Default dataset root \"/data/bennylp/SharedDrives-Stosia/IDX-Dataset\" added, 28 dataset directories found\n",
      "Latest date: 2024-05-29\n",
      "Got 43 brokers\n",
      "StockSummary is up to date. Last is 2024-05-29\n"
     ]
    }
   ],
   "source": [
    "from collections import OrderedDict\n",
    "import datetime\n",
    "import glob\n",
    "#import ipywidgets as widgets\n",
    "from IPython.display import display, Markdown, HTML\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "from scipy.stats import pearsonr\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from statsmodels.tsa.stattools import coint, adfuller\n",
    "import sys\n",
    "from typing import Dict, List, Tuple\n",
    "\n",
    "\n",
    "p = os.path.abspath('../../tradelib')\n",
    "if p not in sys.path:\n",
    "    sys.path.insert(0, p)\n",
    "\n",
    "p = os.path.abspath('../../hotsauto')\n",
    "if p not in sys.path:\n",
    "    sys.path.insert(0, p)\n",
    "\n",
    "from hots import HOTS\n",
    "\n",
    "from tradelib.dataset import config, StockSummary, IndexSummary\n",
    "import tradelib.pipeline as P\n",
    "import tradelib.plotting as pt\n",
    "import tradelib.priceaction as pa\n",
    "from tradelib.trading.bei import BEI\n",
    "from tradelib import broker_analyzer as ba\n",
    "from tradelib.logging import Logger\n",
    "\n",
    "register_matplotlib_converters()\n",
    "config.set_dataset_root('/data/bennylp/SharedDrives-Stosia/IDX-Dataset')\n",
    "\n",
    "bei = BEI()\n",
    "hots = HOTS('brosumview', \n",
    "            os.path.join(config.get_dataset_root(), 'hots/brosum/1d'),\n",
    "            False)\n",
    "\n",
    "\n",
    "def get_brokers(date: datetime.date) -> List[str]:\n",
    "    date = pd.Timestamp(date)\n",
    "    path = os.path.join(config.get_dataset_root(), 'hots', 'brosum', '1d', date.strftime('%Y-%m-%d'))\n",
    "    files = os.listdir(path)\n",
    "    files = [f for f in files if f[-4:]=='.csv']\n",
    "    brokers = sorted([f.replace('.csv', '') for f in files])\n",
    "    return brokers\n",
    "\n",
    "if pd.Timestamp.now().time() > datetime.time(17,10):\n",
    "    latest_date = bei.get_last_market_time().date()\n",
    "else:\n",
    "    latest_date = bei.get_last_market_time( pd.Timestamp.now().replace(hour=0) ).date()\n",
    "\n",
    "    \n",
    "latest_brokers = get_brokers( latest_date )\n",
    "assert len(latest_brokers) >= 43\n",
    "print(f'Latest date: {latest_date}')\n",
    "print(f'Got {len(latest_brokers)} brokers')\n",
    "\n",
    "last_market_date = StockSummary.last_market_date()\n",
    "last_ss_date = StockSummary.last_saved_date()\n",
    "\n",
    "if last_ss_date < last_market_date:\n",
    "    sys.stderr.write(f'StockSummary is {last_market_date - last_ss_date} late\\n')\n",
    "    assert False\n",
    "else:\n",
    "    print(f'StockSummary is up to date. Last is {last_ss_date}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e167deb4",
   "metadata": {},
   "source": [
    "### Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8b884b31",
   "metadata": {},
   "outputs": [],
   "source": [
    "WATCHLIST = ['ANTM', 'HATM', 'INCO', 'KKGI', 'NELY', 'PTBA', 'TAPG', 'TUGU', 'WINS', ]\n",
    "BANKS = ['BBCA', 'BBRI', 'BMRI', 'BNGA', 'BRIS', 'BTPS', 'NISP']\n",
    "TICKERS = sorted(set(WATCHLIST + BANKS))\n",
    "FROM_DATE = datetime.date(2023,11,1)\n",
    "ADJUST_TO_LATEST = True\n",
    "DAYS_TO_REVIEW = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c26e57de",
   "metadata": {},
   "source": [
    "### Load IDX Dataset with foreign"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c4830a76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17:39:04.363 DEBUG Entering StockSummary.load():\n",
      "17:39:05.546 DEBUG | Reading files.. [####################] [131/131] 100% [1.1s]     \n",
      "17:39:05.557 DEBUG | Concatenating..\n",
      "17:39:05.720 DEBUG | 131 files loaded..\n",
      "17:39:05.804 DEBUG | Fixing data..\n",
      "17:39:05.807 INFO  | Warning: fixing individualIndex for ['ANDI', 'BEEF', 'BPTR', 'BTPS', 'BRIS', 'CAKK', 'CITY', 'CLAY', 'DEAL', 'DIGI', 'DIVA', 'DUCK', 'FILM', 'FOOD', 'GOOD', 'HEAL', 'HKMU', 'IPCC', 'JAYA', 'KPAL', 'KPAS', 'LAND', 'LUCK', 'MAPA', 'MGRO', 'MOLI', 'MPRO', 'MSIN', 'NATO', 'NFCX', 'NUSA', 'PANI', 'PEHA', 'POLA', 'POLI', 'POLL', 'PRIM', 'PZZA', 'RISE', 'SAPX', 'SATU', 'SKRN', 'SOSS', 'SOTS', 'SPTO', 'SURE', 'SWAT', 'TCPI', 'TNCA', 'TRUK', 'TUGU', 'URBN', 'YELO', 'ZONE']\n",
      "17:39:06.380 DEBUG Adjusting WINS.. [####################] [16/16] 100% [0.5s]     \n",
      "17:39:06.483 DEBUG Summary:\n",
      "17:39:06.485 DEBUG | dataset contains 1 data(s):\n",
      "17:39:06.490 DEBUG | | stocksum: shape: (2096, 25), size: 0.6 MB\n",
      "17:39:06.492 DEBUG | | | 16 tickers: ['ANTM', 'BB...GU', 'WINS']\n",
      "17:39:06.493 DEBUG | | | 25 columns: ['prev', 'open', 'first', 'high', 'low', 'close', 'vol', 'value', 'freq', 'individualIndex', 'ratio', 'listedShares', 'offer', 'offerVol', 'bid', 'bidVol', 'lastTradingDate', 'tradeableShares', 'weightForIndex', 'foreignSell', 'foreignBuy', 'nonRgVol', 'nonRgValue', 'nonRgFreq', 'unadjClose']\n",
      "17:39:06.494 DEBUG | dataset contains 0 info(s):\n",
      "17:39:06.496 DEBUG | | {}\n",
      "CPU times: user 2.65 s, sys: 302 ms, total: 2.95 s\n",
      "Wall time: 2.91 s\n"
     ]
    },
    {
     "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>prev</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>vol</th>\n",
       "      <th>buy_qty</th>\n",
       "      <th>sell_qty</th>\n",
       "      <th>buy_val</th>\n",
       "      <th>sell_val</th>\n",
       "      <th>net_val</th>\n",
       "      <th>net_qty</th>\n",
       "      <th>qty</th>\n",
       "      <th>cum_net_val</th>\n",
       "      <th>avg</th>\n",
       "      <th>pl</th>\n",
       "      <th>stock_value</th>\n",
       "      <th>cum_pl</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2023-11-01</th>\n",
       "      <td>1704.971739</td>\n",
       "      <td>1704.971739</td>\n",
       "      <td>1714.971573</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>4.364862e+07</td>\n",
       "      <td>5.740695e+06</td>\n",
       "      <td>1.576826e+07</td>\n",
       "      <td>9.471990e+09</td>\n",
       "      <td>2.601720e+10</td>\n",
       "      <td>-1.654521e+10</td>\n",
       "      <td>-1.002757e+07</td>\n",
       "      <td>2.799358e+08</td>\n",
       "      <td>4.182009e+11</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4.618863e+11</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-02</th>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1684.972070</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>3.166092e+07</td>\n",
       "      <td>7.431223e+06</td>\n",
       "      <td>1.112418e+07</td>\n",
       "      <td>1.226131e+10</td>\n",
       "      <td>1.835460e+10</td>\n",
       "      <td>-6.093285e+09</td>\n",
       "      <td>-3.692961e+06</td>\n",
       "      <td>2.762428e+08</td>\n",
       "      <td>4.121076e+11</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>-2.529347e-06</td>\n",
       "      <td>4.557930e+11</td>\n",
       "      <td>-2.529347e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-03</th>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1674.977353</td>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1654.977623</td>\n",
       "      <td>2.787938e+07</td>\n",
       "      <td>6.247984e+06</td>\n",
       "      <td>3.950753e+06</td>\n",
       "      <td>1.034027e+10</td>\n",
       "      <td>6.538408e+09</td>\n",
       "      <td>3.801866e+09</td>\n",
       "      <td>2.297231e+06</td>\n",
       "      <td>2.785400e+08</td>\n",
       "      <td>4.159095e+11</td>\n",
       "      <td>1650.083348</td>\n",
       "      <td>1.933607e+07</td>\n",
       "      <td>4.609775e+11</td>\n",
       "      <td>1.933607e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-06</th>\n",
       "      <td>1655.021785</td>\n",
       "      <td>1655.021785</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>1660.021850</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>3.642812e+07</td>\n",
       "      <td>1.705368e+07</td>\n",
       "      <td>2.432068e+06</td>\n",
       "      <td>2.899163e+10</td>\n",
       "      <td>4.134570e+09</td>\n",
       "      <td>2.485706e+10</td>\n",
       "      <td>1.462161e+07</td>\n",
       "      <td>2.931616e+08</td>\n",
       "      <td>4.407665e+11</td>\n",
       "      <td>1652.964478</td>\n",
       "      <td>1.144480e+08</td>\n",
       "      <td>4.983813e+11</td>\n",
       "      <td>1.337841e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-07</th>\n",
       "      <td>1700.012505</td>\n",
       "      <td>1700.012505</td>\n",
       "      <td>1715.012616</td>\n",
       "      <td>1675.012321</td>\n",
       "      <td>1690.012432</td>\n",
       "      <td>2.215334e+07</td>\n",
       "      <td>6.781050e+06</td>\n",
       "      <td>4.932364e+06</td>\n",
       "      <td>1.146006e+10</td>\n",
       "      <td>8.335756e+09</td>\n",
       "      <td>3.124303e+09</td>\n",
       "      <td>1.848686e+06</td>\n",
       "      <td>2.950103e+08</td>\n",
       "      <td>4.438908e+11</td>\n",
       "      <td>1653.802052</td>\n",
       "      <td>1.786028e+08</td>\n",
       "      <td>4.985711e+11</td>\n",
       "      <td>3.123868e+08</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>1654.881681</td>\n",
       "      <td>1654.881681</td>\n",
       "      <td>1594.885971</td>\n",
       "      <td>1539.889903</td>\n",
       "      <td>1564.888115</td>\n",
       "      <td>5.924194e+07</td>\n",
       "      <td>9.552783e+06</td>\n",
       "      <td>1.536440e+07</td>\n",
       "      <td>1.494904e+10</td>\n",
       "      <td>2.404356e+10</td>\n",
       "      <td>-9.094528e+09</td>\n",
       "      <td>-5.811615e+06</td>\n",
       "      <td>3.362683e+07</td>\n",
       "      <td>5.107916e+10</td>\n",
       "      <td>1612.802147</td>\n",
       "      <td>-7.361703e+08</td>\n",
       "      <td>5.262223e+10</td>\n",
       "      <td>-4.053120e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>1565.000000</td>\n",
       "      <td>1565.000000</td>\n",
       "      <td>1580.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1525.000000</td>\n",
       "      <td>4.217750e+07</td>\n",
       "      <td>4.004200e+06</td>\n",
       "      <td>2.813420e+07</td>\n",
       "      <td>6.106405e+09</td>\n",
       "      <td>4.290466e+10</td>\n",
       "      <td>-3.679825e+10</td>\n",
       "      <td>-2.413000e+07</td>\n",
       "      <td>9.496834e+06</td>\n",
       "      <td>1.428091e+10</td>\n",
       "      <td>1603.459396</td>\n",
       "      <td>-2.207392e+09</td>\n",
       "      <td>1.448267e+10</td>\n",
       "      <td>-4.273859e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>1524.969565</td>\n",
       "      <td>1524.969565</td>\n",
       "      <td>1534.969366</td>\n",
       "      <td>1489.970264</td>\n",
       "      <td>1494.970164</td>\n",
       "      <td>3.450669e+07</td>\n",
       "      <td>7.617752e+06</td>\n",
       "      <td>1.314356e+07</td>\n",
       "      <td>1.138831e+10</td>\n",
       "      <td>1.964923e+10</td>\n",
       "      <td>-8.260921e+09</td>\n",
       "      <td>-5.525810e+06</td>\n",
       "      <td>3.971023e+06</td>\n",
       "      <td>6.019992e+09</td>\n",
       "      <td>1555.170523</td>\n",
       "      <td>-7.912472e+08</td>\n",
       "      <td>5.936562e+09</td>\n",
       "      <td>-4.352984e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>1494.990186</td>\n",
       "      <td>1494.990186</td>\n",
       "      <td>1534.989923</td>\n",
       "      <td>1499.990153</td>\n",
       "      <td>1514.990055</td>\n",
       "      <td>3.367952e+07</td>\n",
       "      <td>6.312741e+06</td>\n",
       "      <td>9.891065e+06</td>\n",
       "      <td>9.563741e+09</td>\n",
       "      <td>1.498486e+10</td>\n",
       "      <td>-5.421124e+09</td>\n",
       "      <td>-3.578323e+06</td>\n",
       "      <td>3.927000e+05</td>\n",
       "      <td>5.988675e+08</td>\n",
       "      <td>1530.505538</td>\n",
       "      <td>-1.534647e+08</td>\n",
       "      <td>5.949366e+08</td>\n",
       "      <td>-4.368330e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>1515.000000</td>\n",
       "      <td>1515.000000</td>\n",
       "      <td>1540.000000</td>\n",
       "      <td>1505.000000</td>\n",
       "      <td>1525.000000</td>\n",
       "      <td>2.707680e+07</td>\n",
       "      <td>9.361700e+06</td>\n",
       "      <td>9.754400e+06</td>\n",
       "      <td>1.427659e+10</td>\n",
       "      <td>1.487546e+10</td>\n",
       "      <td>-5.988675e+08</td>\n",
       "      <td>-3.927000e+05</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1525.221646</td>\n",
       "      <td>-2.162025e+06</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-4.368546e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   prev         open         high          low        close  \\\n",
       "date                                                                          \n",
       "2023-11-01  1704.971739  1704.971739  1714.971573  1649.972650  1649.972650   \n",
       "2023-11-02  1649.972650  1649.972650  1684.972070  1649.972650  1649.972650   \n",
       "2023-11-03  1649.977691  1649.977691  1674.977353  1649.977691  1654.977623   \n",
       "2023-11-06  1655.021785  1655.021785  1700.022377  1660.021850  1700.022377   \n",
       "2023-11-07  1700.012505  1700.012505  1715.012616  1675.012321  1690.012432   \n",
       "...                 ...          ...          ...          ...          ...   \n",
       "2024-05-21  1654.881681  1654.881681  1594.885971  1539.889903  1564.888115   \n",
       "2024-05-22  1565.000000  1565.000000  1580.000000  1520.000000  1525.000000   \n",
       "2024-05-27  1524.969565  1524.969565  1534.969366  1489.970264  1494.970164   \n",
       "2024-05-28  1494.990186  1494.990186  1534.989923  1499.990153  1514.990055   \n",
       "2024-05-29  1515.000000  1515.000000  1540.000000  1505.000000  1525.000000   \n",
       "\n",
       "                     vol       buy_qty      sell_qty       buy_val  \\\n",
       "date                                                                 \n",
       "2023-11-01  4.364862e+07  5.740695e+06  1.576826e+07  9.471990e+09   \n",
       "2023-11-02  3.166092e+07  7.431223e+06  1.112418e+07  1.226131e+10   \n",
       "2023-11-03  2.787938e+07  6.247984e+06  3.950753e+06  1.034027e+10   \n",
       "2023-11-06  3.642812e+07  1.705368e+07  2.432068e+06  2.899163e+10   \n",
       "2023-11-07  2.215334e+07  6.781050e+06  4.932364e+06  1.146006e+10   \n",
       "...                  ...           ...           ...           ...   \n",
       "2024-05-21  5.924194e+07  9.552783e+06  1.536440e+07  1.494904e+10   \n",
       "2024-05-22  4.217750e+07  4.004200e+06  2.813420e+07  6.106405e+09   \n",
       "2024-05-27  3.450669e+07  7.617752e+06  1.314356e+07  1.138831e+10   \n",
       "2024-05-28  3.367952e+07  6.312741e+06  9.891065e+06  9.563741e+09   \n",
       "2024-05-29  2.707680e+07  9.361700e+06  9.754400e+06  1.427659e+10   \n",
       "\n",
       "                sell_val       net_val       net_qty           qty  \\\n",
       "date                                                                 \n",
       "2023-11-01  2.601720e+10 -1.654521e+10 -1.002757e+07  2.799358e+08   \n",
       "2023-11-02  1.835460e+10 -6.093285e+09 -3.692961e+06  2.762428e+08   \n",
       "2023-11-03  6.538408e+09  3.801866e+09  2.297231e+06  2.785400e+08   \n",
       "2023-11-06  4.134570e+09  2.485706e+10  1.462161e+07  2.931616e+08   \n",
       "2023-11-07  8.335756e+09  3.124303e+09  1.848686e+06  2.950103e+08   \n",
       "...                  ...           ...           ...           ...   \n",
       "2024-05-21  2.404356e+10 -9.094528e+09 -5.811615e+06  3.362683e+07   \n",
       "2024-05-22  4.290466e+10 -3.679825e+10 -2.413000e+07  9.496834e+06   \n",
       "2024-05-27  1.964923e+10 -8.260921e+09 -5.525810e+06  3.971023e+06   \n",
       "2024-05-28  1.498486e+10 -5.421124e+09 -3.578323e+06  3.927000e+05   \n",
       "2024-05-29  1.487546e+10 -5.988675e+08 -3.927000e+05  0.000000e+00   \n",
       "\n",
       "             cum_net_val          avg            pl   stock_value  \\\n",
       "date                                                                \n",
       "2023-11-01  4.182009e+11  1649.972650  0.000000e+00  4.618863e+11   \n",
       "2023-11-02  4.121076e+11  1649.972650 -2.529347e-06  4.557930e+11   \n",
       "2023-11-03  4.159095e+11  1650.083348  1.933607e+07  4.609775e+11   \n",
       "2023-11-06  4.407665e+11  1652.964478  1.144480e+08  4.983813e+11   \n",
       "2023-11-07  4.438908e+11  1653.802052  1.786028e+08  4.985711e+11   \n",
       "...                  ...          ...           ...           ...   \n",
       "2024-05-21  5.107916e+10  1612.802147 -7.361703e+08  5.262223e+10   \n",
       "2024-05-22  1.428091e+10  1603.459396 -2.207392e+09  1.448267e+10   \n",
       "2024-05-27  6.019992e+09  1555.170523 -7.912472e+08  5.936562e+09   \n",
       "2024-05-28  5.988675e+08  1530.505538 -1.534647e+08  5.949366e+08   \n",
       "2024-05-29  0.000000e+00  1525.221646 -2.162025e+06  0.000000e+00   \n",
       "\n",
       "                  cum_pl  \n",
       "date                      \n",
       "2023-11-01  0.000000e+00  \n",
       "2023-11-02 -2.529347e-06  \n",
       "2023-11-03  1.933607e+07  \n",
       "2023-11-06  1.337841e+08  \n",
       "2023-11-07  3.123868e+08  \n",
       "...                  ...  \n",
       "2024-05-21 -4.053120e+10  \n",
       "2024-05-22 -4.273859e+10  \n",
       "2024-05-27 -4.352984e+10  \n",
       "2024-05-28 -4.368330e+10  \n",
       "2024-05-29 -4.368546e+10  \n",
       "\n",
       "[131 rows x 18 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "def load_master_ohlc() -> Tuple[pd.DataFrame, pd.DataFrame]:\n",
    "    \"\"\"\n",
    "    Load master OHLC and master foreign flow data frame\n",
    "    \"\"\"\n",
    "    p = P.Pipeline([\n",
    "        P.LoadStockSummary('1d', from_date=FROM_DATE, tickers=TICKERS,\n",
    "                           adjust_to_latest=ADJUST_TO_LATEST),\n",
    "        P.Summary(),\n",
    "    ])\n",
    "    dataset = p.run( verbose=False )\n",
    "    df = next(iter(dataset.data.values()))\n",
    "    df = df[['prev', 'open', 'high', 'low', 'close', 'vol', 'foreignBuy', 'foreignSell']].copy()\n",
    "    df['open'] = df['prev']\n",
    "\n",
    "    df = df.rename(columns={'foreignBuy': 'buy_qty', 'foreignSell': 'sell_qty'})\n",
    "    df['buy_val'] = df['buy_qty'] * df['close']\n",
    "    df['sell_val'] = df['sell_qty'] * df['close']\n",
    "    \n",
    "    ohlc = df[['open', 'high', 'low', 'close', 'vol']].copy()\n",
    "    ff = df.groupby('ticker').apply(ba.analyze_broker_single_security)\n",
    "    return ohlc, ff\n",
    "\n",
    "\n",
    "master_ohlc, master_ff = load_master_ohlc()\n",
    "\n",
    "# Sample ff data\n",
    "master_ff.loc[ TICKERS[0] ]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e03d6fc9",
   "metadata": {},
   "source": [
    "### All brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "51ffb56a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "43 brokers: AG, AI, AK, AO, AZ, BB, BK, BQ, CC, CP, DH, DP, DR, DX, EP, FS, GR, HP, IF, IN, KK, KZ, LG, MG, NI, OD, PD, PG, PP, PS, RF, RG, RX, SQ, TP, XA, XC, XL, YB, YJ, YP, YU, ZP\n"
     ]
    }
   ],
   "source": [
    "BROKERS = get_brokers( pd.Timestamp('2023-11-01') )\n",
    "print(f'{len(BROKERS)} brokers: {\", \".join(BROKERS)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "134f0ffe",
   "metadata": {},
   "source": [
    "### Retail brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9f774ed4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CC', 'GR', 'KK', 'NI', 'PD', 'SQ', 'XC', 'XL', 'YP']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RETAIL_BROKERS = ['CC', 'GR', 'KK', 'NI', 'PD', 'SQ', 'XC', 'XL', 'YP']\n",
    "RETAIL_BROKERS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0717b859",
   "metadata": {},
   "source": [
    "## Analysis Utilities\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c35a4e29",
   "metadata": {},
   "source": [
    "### detect_pivot_points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fa7f522c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2023-11-01', '2023-11-06', '2023-11-13', '2023-11-14',\n",
       "               '2023-11-16', '2023-11-23', '2023-12-04', '2023-12-07',\n",
       "               '2023-12-13', '2023-12-15', '2023-12-20', '2023-12-21',\n",
       "               '2023-12-27', '2024-01-02', '2024-01-10', '2024-01-16',\n",
       "               '2024-01-19', '2024-01-22', '2024-01-24', '2024-01-26',\n",
       "               '2024-02-07', '2024-02-13', '2024-02-21', '2024-02-23',\n",
       "               '2024-03-05', '2024-03-15', '2024-03-21', '2024-04-01',\n",
       "               '2024-04-16', '2024-04-18', '2024-04-22', '2024-04-25',\n",
       "               '2024-04-30', '2024-05-03', '2024-05-08', '2024-05-14',\n",
       "               '2024-05-20', '2024-05-27', '2024-05-29'],\n",
       "              dtype='datetime64[ns]', name='date', freq=None)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def detect_pivot_points(ohlc: pd.DataFrame, include_first_last=True) -> pd.Index:\n",
    "    \"\"\"\n",
    "    Return indices from ohlc where the price is pivotting.\n",
    "    If include_first_last is True, the first and last indices will be\n",
    "    included for convenience.\n",
    "    \"\"\"\n",
    "    \n",
    "    # ohlc is for one ticker\n",
    "    assert 'ticker' not in ohlc.index.names\n",
    "    close = ohlc['close']\n",
    "    close = close.astype(int)\n",
    "\n",
    "    top_pivot = ((close >= close.shift()) &\n",
    "                 #(close.shift() >= close.shift(2)) & \n",
    "                 (close > close.shift(2)) & \n",
    "                 (close.shift(-1) <= close) &\n",
    "                 #(close.shift(-2) <= close.shift(-1)) &\n",
    "                 (close.shift(-2) < close)\n",
    "                 )\n",
    "    bottom_pivot = ((close <= close.shift()) &\n",
    "                    #(close.shift() <= close.shift(2)) & \n",
    "                    (close < close.shift(2)) &\n",
    "                    (close.shift(-1) >= close) &\n",
    "                    #(close.shift(-2) >= close.shift(-1)) &\n",
    "                    (close.shift(-2) > close)\n",
    "                    )\n",
    "    top_pivot = top_pivot[ top_pivot != 0 ].astype(int)\n",
    "    bottom_pivot = bottom_pivot[ bottom_pivot != 0 ].astype(int).replace(1, -1)\n",
    "    pivots = sorted(top_pivot.index.tolist() + bottom_pivot.index.tolist())\n",
    "    if include_first_last:\n",
    "        pivots = [ohlc.index[0]] + pivots + [ohlc.index[-1]]\n",
    "        \n",
    "    return pd.Index(pivots, name=ohlc.index.name)\n",
    "\n",
    "# Testing\n",
    "detect_pivot_points(master_ohlc.loc[ TICKERS[0] ])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd7999ed",
   "metadata": {},
   "source": [
    "### plot_legs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0f5ea1b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_legs(ohlc: pd.DataFrame, ax):\n",
    "    pivot_points = detect_pivot_points(ohlc)\n",
    "    legs = ohlc.loc[pivot_points, 'close']\n",
    "    x = [ohlc.index.get_loc(day) for day in pivot_points]\n",
    "    ax.plot(x, legs, color='k', zorder=10, alpha=0.7, linestyle='--')\n",
    "    plt.show()\n",
    "\n",
    "    \n",
    "# Demo\n",
    "def demo_plot_legs():\n",
    "    df = master_ohlc.loc[ TICKERS[0] ]\n",
    "    fig = pt.Figure([\n",
    "        pt.Chart([\n",
    "            pt.Plot('close', kind='candlestick', alpha=0.5)\n",
    "        ])\n",
    "    ], row_height=5)\n",
    "    fig.plot(df, show=False)\n",
    "\n",
    "    plot_legs(df, fig.charts[0].ax1 )\n",
    "    plt.show()\n",
    "    \n",
    "demo_plot_legs()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89bf7196",
   "metadata": {},
   "source": [
    "### load_brosum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "123dcaa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_brosum(broker: str):\n",
    "    \"\"\"\n",
    "    Create broker summary for one broker for multiple tickers and dates.\n",
    "    The tickers and dates are taken from ohlc index.\n",
    "    \"\"\"\n",
    "    ohlc = master_ohlc\n",
    "    assert ohlc.index.names == ['ticker', 'date']\n",
    "    from_date = ohlc.index.get_level_values('date').min().date()\n",
    "    to_date = ohlc.index.get_level_values('date').max().date()\n",
    "    dates = bei.date_range(from_date, to_date)\n",
    "    \n",
    "    tickers = list(ohlc.index.get_level_values('ticker').unique())\n",
    "    ohlc = ohlc[['open', 'high', 'low', 'close', 'vol']]\n",
    "    \n",
    "    dfs = []\n",
    "    bs_cols = ['buy_val', 'buy_qty', 'sell_val', 'sell_qty']\n",
    "    for date in dates:\n",
    "        try:\n",
    "            df = hots.brosum(broker, date)\n",
    "        except:\n",
    "            continue\n",
    "        \n",
    "        df = df[['ticker', 'date'] + bs_cols]\n",
    "        df['date'] = df['date'].apply(lambda d: pd.Timestamp(d))\n",
    "        df = df[ df['ticker'].isin(tickers) ]\n",
    "        df = df.set_index(['ticker', 'date'], drop=True)\n",
    "        df = df.sort_index()\n",
    "        \n",
    "        dfs.append(df)\n",
    "        \n",
    "    if not dfs:\n",
    "        return None\n",
    "    \n",
    "    # bs is the brosum\n",
    "    bs = pd.concat(dfs)\n",
    "    \n",
    "    # df is join between brosum and ohlc\n",
    "    df = ohlc.join(bs, how='left')\n",
    "    df[bs_cols] = df[bs_cols].fillna(0)\n",
    "\n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d63f853",
   "metadata": {},
   "source": [
    "### load_analyze_brosums"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7f7fc70c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17:41:14.277 INFO  Loading ZP.. [####################] [43/43] 100% [02:05]         \n"
     ]
    },
    {
     "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></th>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>vol</th>\n",
       "      <th>buy_val</th>\n",
       "      <th>buy_qty</th>\n",
       "      <th>sell_val</th>\n",
       "      <th>sell_qty</th>\n",
       "      <th>net_val</th>\n",
       "      <th>net_qty</th>\n",
       "      <th>qty</th>\n",
       "      <th>cum_net_val</th>\n",
       "      <th>avg</th>\n",
       "      <th>pl</th>\n",
       "      <th>stock_value</th>\n",
       "      <th>cum_pl</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>broker</th>\n",
       "      <th>ticker</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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 rowspan=\"5\" valign=\"top\">AG</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">ANTM</th>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>1704.971739</td>\n",
       "      <td>1714.971573</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>4.364862e+07</td>\n",
       "      <td>7.068700e+07</td>\n",
       "      <td>42300.0</td>\n",
       "      <td>8.667400e+08</td>\n",
       "      <td>512600.0</td>\n",
       "      <td>-7.960530e+08</td>\n",
       "      <td>-470300.0</td>\n",
       "      <td>10718400.0</td>\n",
       "      <td>1.755138e+10</td>\n",
       "      <td>1671.087470</td>\n",
       "      <td>1.014056e+07</td>\n",
       "      <td>1.768507e+10</td>\n",
       "      <td>1.014056e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-02</th>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1684.972070</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>3.166092e+07</td>\n",
       "      <td>3.449240e+08</td>\n",
       "      <td>208300.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.449240e+08</td>\n",
       "      <td>208300.0</td>\n",
       "      <td>10926700.0</td>\n",
       "      <td>1.789630e+10</td>\n",
       "      <td>1670.797948</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.802876e+10</td>\n",
       "      <td>1.014056e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-03</th>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1674.977353</td>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1654.977623</td>\n",
       "      <td>2.787938e+07</td>\n",
       "      <td>5.184160e+08</td>\n",
       "      <td>311500.0</td>\n",
       "      <td>1.835500e+08</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>3.348660e+08</td>\n",
       "      <td>201500.0</td>\n",
       "      <td>11128200.0</td>\n",
       "      <td>1.823117e+10</td>\n",
       "      <td>1670.616642</td>\n",
       "      <td>-2.178306e+05</td>\n",
       "      <td>1.841692e+10</td>\n",
       "      <td>9.922732e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-06</th>\n",
       "      <td>1655.021785</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>1660.021850</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>3.642812e+07</td>\n",
       "      <td>1.971802e+09</td>\n",
       "      <td>1167500.0</td>\n",
       "      <td>1.630950e+08</td>\n",
       "      <td>96300.0</td>\n",
       "      <td>1.808707e+09</td>\n",
       "      <td>1071200.0</td>\n",
       "      <td>12199400.0</td>\n",
       "      <td>2.003987e+10</td>\n",
       "      <td>1672.353596</td>\n",
       "      <td>2.047349e+06</td>\n",
       "      <td>2.073925e+10</td>\n",
       "      <td>1.197008e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-07</th>\n",
       "      <td>1700.012505</td>\n",
       "      <td>1715.012616</td>\n",
       "      <td>1675.012321</td>\n",
       "      <td>1690.012432</td>\n",
       "      <td>2.215334e+07</td>\n",
       "      <td>1.764180e+08</td>\n",
       "      <td>104700.0</td>\n",
       "      <td>1.012420e+09</td>\n",
       "      <td>602000.0</td>\n",
       "      <td>-8.360020e+08</td>\n",
       "      <td>-497300.0</td>\n",
       "      <td>11702100.0</td>\n",
       "      <td>1.920387e+10</td>\n",
       "      <td>1672.461087</td>\n",
       "      <td>5.598426e+06</td>\n",
       "      <td>1.977669e+10</td>\n",
       "      <td>1.756851e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">ZP</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">WINS</th>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>483.876944</td>\n",
       "      <td>485.876436</td>\n",
       "      <td>477.878470</td>\n",
       "      <td>479.877961</td>\n",
       "      <td>2.015712e+06</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.282400e+07</td>\n",
       "      <td>110100.0</td>\n",
       "      <td>-5.282400e+07</td>\n",
       "      <td>-110100.0</td>\n",
       "      <td>8054000.0</td>\n",
       "      <td>3.439969e+09</td>\n",
       "      <td>487.376819</td>\n",
       "      <td>-8.361877e+05</td>\n",
       "      <td>3.864937e+09</td>\n",
       "      <td>4.821429e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>479.993773</td>\n",
       "      <td>499.993513</td>\n",
       "      <td>475.993825</td>\n",
       "      <td>497.993539</td>\n",
       "      <td>4.286156e+06</td>\n",
       "      <td>9.104900e+07</td>\n",
       "      <td>185200.0</td>\n",
       "      <td>1.344400e+07</td>\n",
       "      <td>28000.0</td>\n",
       "      <td>7.760500e+07</td>\n",
       "      <td>157200.0</td>\n",
       "      <td>8211200.0</td>\n",
       "      <td>3.517574e+09</td>\n",
       "      <td>487.472315</td>\n",
       "      <td>-2.052248e+05</td>\n",
       "      <td>4.089125e+09</td>\n",
       "      <td>4.819377e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>498.000000</td>\n",
       "      <td>535.000000</td>\n",
       "      <td>496.000000</td>\n",
       "      <td>515.000000</td>\n",
       "      <td>1.129330e+07</td>\n",
       "      <td>2.890665e+09</td>\n",
       "      <td>5678500.0</td>\n",
       "      <td>1.542760e+08</td>\n",
       "      <td>303000.0</td>\n",
       "      <td>2.736389e+09</td>\n",
       "      <td>5375500.0</td>\n",
       "      <td>13586700.0</td>\n",
       "      <td>6.253963e+09</td>\n",
       "      <td>496.295649</td>\n",
       "      <td>3.898418e+06</td>\n",
       "      <td>6.997150e+09</td>\n",
       "      <td>4.858361e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>515.018302</td>\n",
       "      <td>525.018658</td>\n",
       "      <td>498.017698</td>\n",
       "      <td>505.017947</td>\n",
       "      <td>6.379473e+06</td>\n",
       "      <td>1.406199e+09</td>\n",
       "      <td>2793600.0</td>\n",
       "      <td>2.626000e+06</td>\n",
       "      <td>5200.0</td>\n",
       "      <td>1.403573e+09</td>\n",
       "      <td>2788400.0</td>\n",
       "      <td>16375100.0</td>\n",
       "      <td>7.657536e+09</td>\n",
       "      <td>497.501211</td>\n",
       "      <td>3.899370e+04</td>\n",
       "      <td>8.269719e+09</td>\n",
       "      <td>4.858751e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>505.000000</td>\n",
       "      <td>520.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>515.000000</td>\n",
       "      <td>4.856600e+06</td>\n",
       "      <td>4.619300e+08</td>\n",
       "      <td>909700.0</td>\n",
       "      <td>2.499000e+06</td>\n",
       "      <td>4900.0</td>\n",
       "      <td>4.594310e+08</td>\n",
       "      <td>904800.0</td>\n",
       "      <td>17279900.0</td>\n",
       "      <td>8.116967e+09</td>\n",
       "      <td>498.042331</td>\n",
       "      <td>5.859258e+04</td>\n",
       "      <td>8.899148e+09</td>\n",
       "      <td>4.859337e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90128 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 open         high          low        close  \\\n",
       "broker ticker date                                                             \n",
       "AG     ANTM   2023-11-01  1704.971739  1714.971573  1649.972650  1649.972650   \n",
       "              2023-11-02  1649.972650  1684.972070  1649.972650  1649.972650   \n",
       "              2023-11-03  1649.977691  1674.977353  1649.977691  1654.977623   \n",
       "              2023-11-06  1655.021785  1700.022377  1660.021850  1700.022377   \n",
       "              2023-11-07  1700.012505  1715.012616  1675.012321  1690.012432   \n",
       "...                               ...          ...          ...          ...   \n",
       "ZP     WINS   2024-05-21   483.876944   485.876436   477.878470   479.877961   \n",
       "              2024-05-22   479.993773   499.993513   475.993825   497.993539   \n",
       "              2024-05-27   498.000000   535.000000   496.000000   515.000000   \n",
       "              2024-05-28   515.018302   525.018658   498.017698   505.017947   \n",
       "              2024-05-29   505.000000   520.000000   500.000000   515.000000   \n",
       "\n",
       "                                   vol       buy_val    buy_qty      sell_val  \\\n",
       "broker ticker date                                                              \n",
       "AG     ANTM   2023-11-01  4.364862e+07  7.068700e+07    42300.0  8.667400e+08   \n",
       "              2023-11-02  3.166092e+07  3.449240e+08   208300.0  0.000000e+00   \n",
       "              2023-11-03  2.787938e+07  5.184160e+08   311500.0  1.835500e+08   \n",
       "              2023-11-06  3.642812e+07  1.971802e+09  1167500.0  1.630950e+08   \n",
       "              2023-11-07  2.215334e+07  1.764180e+08   104700.0  1.012420e+09   \n",
       "...                                ...           ...        ...           ...   \n",
       "ZP     WINS   2024-05-21  2.015712e+06  0.000000e+00        0.0  5.282400e+07   \n",
       "              2024-05-22  4.286156e+06  9.104900e+07   185200.0  1.344400e+07   \n",
       "              2024-05-27  1.129330e+07  2.890665e+09  5678500.0  1.542760e+08   \n",
       "              2024-05-28  6.379473e+06  1.406199e+09  2793600.0  2.626000e+06   \n",
       "              2024-05-29  4.856600e+06  4.619300e+08   909700.0  2.499000e+06   \n",
       "\n",
       "                          sell_qty       net_val    net_qty         qty  \\\n",
       "broker ticker date                                                        \n",
       "AG     ANTM   2023-11-01  512600.0 -7.960530e+08  -470300.0  10718400.0   \n",
       "              2023-11-02       0.0  3.449240e+08   208300.0  10926700.0   \n",
       "              2023-11-03  110000.0  3.348660e+08   201500.0  11128200.0   \n",
       "              2023-11-06   96300.0  1.808707e+09  1071200.0  12199400.0   \n",
       "              2023-11-07  602000.0 -8.360020e+08  -497300.0  11702100.0   \n",
       "...                            ...           ...        ...         ...   \n",
       "ZP     WINS   2024-05-21  110100.0 -5.282400e+07  -110100.0   8054000.0   \n",
       "              2024-05-22   28000.0  7.760500e+07   157200.0   8211200.0   \n",
       "              2024-05-27  303000.0  2.736389e+09  5375500.0  13586700.0   \n",
       "              2024-05-28    5200.0  1.403573e+09  2788400.0  16375100.0   \n",
       "              2024-05-29    4900.0  4.594310e+08   904800.0  17279900.0   \n",
       "\n",
       "                           cum_net_val          avg            pl  \\\n",
       "broker ticker date                                                  \n",
       "AG     ANTM   2023-11-01  1.755138e+10  1671.087470  1.014056e+07   \n",
       "              2023-11-02  1.789630e+10  1670.797948  0.000000e+00   \n",
       "              2023-11-03  1.823117e+10  1670.616642 -2.178306e+05   \n",
       "              2023-11-06  2.003987e+10  1672.353596  2.047349e+06   \n",
       "              2023-11-07  1.920387e+10  1672.461087  5.598426e+06   \n",
       "...                                ...          ...           ...   \n",
       "ZP     WINS   2024-05-21  3.439969e+09   487.376819 -8.361877e+05   \n",
       "              2024-05-22  3.517574e+09   487.472315 -2.052248e+05   \n",
       "              2024-05-27  6.253963e+09   496.295649  3.898418e+06   \n",
       "              2024-05-28  7.657536e+09   497.501211  3.899370e+04   \n",
       "              2024-05-29  8.116967e+09   498.042331  5.859258e+04   \n",
       "\n",
       "                           stock_value        cum_pl  \n",
       "broker ticker date                                    \n",
       "AG     ANTM   2023-11-01  1.768507e+10  1.014056e+07  \n",
       "              2023-11-02  1.802876e+10  1.014056e+07  \n",
       "              2023-11-03  1.841692e+10  9.922732e+06  \n",
       "              2023-11-06  2.073925e+10  1.197008e+07  \n",
       "              2023-11-07  1.977669e+10  1.756851e+07  \n",
       "...                                ...           ...  \n",
       "ZP     WINS   2024-05-21  3.864937e+09  4.821429e+08  \n",
       "              2024-05-22  4.089125e+09  4.819377e+08  \n",
       "              2024-05-27  6.997150e+09  4.858361e+08  \n",
       "              2024-05-28  8.269719e+09  4.858751e+08  \n",
       "              2024-05-29  8.899148e+09  4.859337e+08  \n",
       "\n",
       "[90128 rows x 17 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def load_analyze_brosums() -> pd.DataFrame:\n",
    "    \"\"\"\n",
    "    Load all required brosum for the tickers and dates in master_ohlc, and\n",
    "    perform analysis as well\n",
    "    \"\"\"\n",
    "\n",
    "    logger = Logger.get()\n",
    "\n",
    "    dfs = []\n",
    "    for i, broker in enumerate(BROKERS):\n",
    "        logger.info(f'Loading {broker}..', progress=(i, len(BROKERS)))\n",
    "        bs = load_brosum(broker)\n",
    "        for ticker, group in bs.groupby('ticker'):\n",
    "            tmp = ba.analyze_broker_single_security(group)\n",
    "            tmp['broker'] = broker\n",
    "            tmp = tmp.reset_index().set_index(['broker', 'ticker', 'date'], drop=True)\n",
    "            tmp = tmp.sort_index()\n",
    "            dfs.append(tmp)\n",
    "    \n",
    "    df = pd.concat(dfs)\n",
    "    logger.end_progress()\n",
    "    return df\n",
    "\n",
    "master_brosum = load_analyze_brosums()\n",
    "master_brosum"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfeb66e6",
   "metadata": {},
   "source": [
    "### calc_ts_statistics\n",
    "\n",
    "Compare the cummulative net buy/sell value with the price and calculates several time series statistics:\n",
    "\n",
    "- **Daily cointegration p-value**: in layman term, cointegration test is used to establish if there is a correlation between several time series in the long term. Lower p-value, such as below 0.1 for two stock prices, indicates better correlation.\n",
    "- **Daily correlation**: \n",
    "- **Daily mean error**:\n",
    "- **Trend/legs correlation**:\n",
    "- **Trend matching direction**: \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "29469081",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "def calc_ts_statistics(close: pd.Series, cum_net_val: pd.Series):\n",
    "    \"\"\"\n",
    "    Calculate various time series statistics between price and the\n",
    "    specified value time series.\n",
    "    \"\"\"\n",
    "    data = {}\n",
    "    \n",
    "    # Cointegration\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.filterwarnings(\"error\")\n",
    "        try:\n",
    "            _, p_val, _ = coint(cum_net_val, close)\n",
    "        except RuntimeWarning:\n",
    "            p_val = 1.0\n",
    "    data['Daily cointegration p-value'] = p_val\n",
    "    \n",
    "    # Scale them first, there will be many uses\n",
    "    scaler0 = MinMaxScaler()\n",
    "    scaler0.fit( np.expand_dims(close, axis=1) )\n",
    "    values0 = scaler0.transform(np.expand_dims(close, axis=1))\n",
    "    close_norm = values0.squeeze()\n",
    "    \n",
    "    scaler1 = MinMaxScaler()\n",
    "    scaler1.fit( np.expand_dims(cum_net_val, axis=1) )\n",
    "    values1 = scaler1.transform( np.expand_dims(cum_net_val, axis=1) )\n",
    "    cum_norm = values1.squeeze()\n",
    "    \n",
    "    # Daily correlation\n",
    "    close_chg = close.pct_change().iloc[1:]\n",
    "    val_chg = cum_net_val.pct_change().iloc[1:]\n",
    "    val_chg = val_chg.replace(np.inf, 0)\n",
    "    raw_corr = np.corrcoef(close_chg, val_chg)\n",
    "    data['Daily correlation'] = raw_corr[0][1]\n",
    "    \n",
    "    # Mean absolute error\n",
    "    err = cum_norm - close_norm\n",
    "    mean_err = np.mean(np.abs(err))\n",
    "    data['Daily mean error'] = mean_err\n",
    "    \n",
    "    # Trend correlation\n",
    "    dummy_ohlc = pd.DataFrame({'close': close})\n",
    "    pivot_points = detect_pivot_points(dummy_ohlc)\n",
    "    \n",
    "    close_legs = close.loc[pivot_points]\n",
    "    val_legs = cum_net_val.loc[pivot_points]\n",
    "    close_legs_chg = close_legs.pct_change().iloc[1:]\n",
    "    val_legs_chg = val_legs.pct_change().iloc[1:]\n",
    "    val_legs_chg = val_legs_chg.replace(np.inf, 0)\n",
    "    leg_corr = np.corrcoef(close_legs_chg, val_legs_chg)\n",
    "    data['Trend/legs correlation'] = leg_corr[0][1]\n",
    "\n",
    "    # Matching between leg direction and value change direction\n",
    "    close_sign = np.sign(close_legs_chg)\n",
    "    val_sign = np.sign(val_legs_chg)\n",
    "    match_sign = (close_sign == val_sign)\n",
    "    n_match_sign = match_sign.sum()\n",
    "    data['Trend matching direction'] = n_match_sign / len(close_sign)\n",
    "        \n",
    "    stats = pd.DataFrame({cum_net_val.name: data.values()}, index=data.keys())\n",
    "    return stats\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0f806b7",
   "metadata": {},
   "source": [
    "### display_ts_statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7796685c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_541e3_row3_col1, #T_541e3_row4_col1 {\n",
       "  background-color: lightgreen;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_541e3_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >BK</th>\n",
       "      <th class=\"col_heading level0 col1\" >foreign</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_541e3_level0_row0\" class=\"row_heading level0 row0\" >Daily cointegration p-value</th>\n",
       "      <td id=\"T_541e3_row0_col0\" class=\"data row0 col0\" >0.70</td>\n",
       "      <td id=\"T_541e3_row0_col1\" class=\"data row0 col1\" >0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_541e3_level0_row1\" class=\"row_heading level0 row1\" >Daily correlation</th>\n",
       "      <td id=\"T_541e3_row1_col0\" class=\"data row1 col0\" >15.4%</td>\n",
       "      <td id=\"T_541e3_row1_col1\" class=\"data row1 col1\" >32.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_541e3_level0_row2\" class=\"row_heading level0 row2\" >Daily mean error</th>\n",
       "      <td id=\"T_541e3_row2_col0\" class=\"data row2 col0\" >20.5%</td>\n",
       "      <td id=\"T_541e3_row2_col1\" class=\"data row2 col1\" >23.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_541e3_level0_row3\" class=\"row_heading level0 row3\" >Trend/legs correlation</th>\n",
       "      <td id=\"T_541e3_row3_col0\" class=\"data row3 col0\" >20.1%</td>\n",
       "      <td id=\"T_541e3_row3_col1\" class=\"data row3 col1\" >51.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_541e3_level0_row4\" class=\"row_heading level0 row4\" >Trend matching direction</th>\n",
       "      <td id=\"T_541e3_row4_col0\" class=\"data row4 col0\" >47.4%</td>\n",
       "      <td id=\"T_541e3_row4_col1\" class=\"data row4 col1\" >71.1%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x771a2c6cb910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "COINT_LIMIT = 0.1\n",
    "CORR_LIMIT = 0.5\n",
    "ME_LIMIT = 0.1\n",
    "\n",
    "def display_ts_statistics(df: pd.DataFrame):\n",
    "    display(df.style.applymap(lambda val: 'background-color:lightgreen' if val < COINT_LIMIT else '', \n",
    "                              subset=('Daily cointegration p-value', ))\n",
    "                    .applymap(lambda val: 'background-color:lightgreen' if val > CORR_LIMIT else '', \n",
    "                              subset=('Daily correlation', ))\n",
    "                    .applymap(lambda val: 'background-color:lightgreen' if val < ME_LIMIT else '', \n",
    "                              subset=('Daily mean error', ))\n",
    "                    .applymap(lambda val: 'background-color:lightgreen' if val > CORR_LIMIT else '', \n",
    "                              subset=('Trend/legs correlation', ))\n",
    "                    .applymap(lambda val: 'background-color:lightgreen' if val > CORR_LIMIT else '', \n",
    "                              subset=('Trend matching direction', ))\n",
    "                    .format('{:.1%}', subset=(['Daily correlation', 'Daily mean error',\n",
    "                                               'Trend/legs correlation', 'Trend matching direction'], ))\n",
    "                    .format('{:.2f}', subset=('Daily cointegration p-value', ))\n",
    "           )\n",
    "\n",
    "# Testing with combining broker and ff\n",
    "df0 = master_brosum.loc[('BK', TICKERS[0])]\n",
    "df0 = calc_ts_statistics(df0['close'], df0['cum_net_val'].rename('BK'))\n",
    "\n",
    "df1 = master_ff.loc[ TICKERS[0] ]\n",
    "df1 = calc_ts_statistics(df1['close'], df1['cum_net_val'].rename('foreign'))\n",
    "\n",
    "df = pd.concat([df0, df1], axis=1)\n",
    "display_ts_statistics(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b783646f",
   "metadata": {},
   "source": [
    "### compare_ts_statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9c454ff7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def compare_ts_statistics(stat0: pd.Series, stat1: pd.Series) -> int:\n",
    "    \"\"\"\n",
    "    -1 means stat0 is worse than stat1.\n",
    "    1 means stat0 is better than stat1\n",
    "    \"\"\"\n",
    "    assert isinstance(stat0, pd.Series)\n",
    "    assert isinstance(stat1, pd.Series)\n",
    "    \n",
    "    def cmp_less_is_better(val0, val1, limit):\n",
    "        if val0 > limit:\n",
    "            return 0 if val1 > limit else -1\n",
    "        else:\n",
    "            return 1 if val1 > limit else (1 if val0<val1 else (0 if val0==val1 else -1))\n",
    "    def cmp_more_is_better(val0, val1, limit):\n",
    "        if val0 < limit:\n",
    "            return 0 if val1 < limit else -1\n",
    "        else:\n",
    "            return 1 if val1 < limit else (-1 if val0<val1 else (0 if val0==val1 else 1))\n",
    "        \n",
    "    # Test vectors\n",
    "    assert cmp_less_is_better(0.2, 0.2, COINT_LIMIT)==0\n",
    "    assert cmp_less_is_better(0.2, COINT_LIMIT, COINT_LIMIT)==-1\n",
    "    assert cmp_less_is_better(COINT_LIMIT, 0.2, COINT_LIMIT)==1\n",
    "    assert cmp_less_is_better(COINT_LIMIT, COINT_LIMIT, COINT_LIMIT)==0\n",
    "    assert cmp_less_is_better(COINT_LIMIT-0.01, COINT_LIMIT, COINT_LIMIT)==1\n",
    "    assert cmp_less_is_better(COINT_LIMIT-0.01, COINT_LIMIT-0.02, COINT_LIMIT)==-1\n",
    "    \n",
    "    assert cmp_more_is_better(0.4, 0.4, CORR_LIMIT)==0\n",
    "    assert cmp_more_is_better(0.4, CORR_LIMIT+0.1, CORR_LIMIT)==-1\n",
    "    assert cmp_more_is_better(CORR_LIMIT, 0.4, CORR_LIMIT)==1\n",
    "    assert cmp_more_is_better(CORR_LIMIT, CORR_LIMIT, CORR_LIMIT)==0\n",
    "    assert cmp_more_is_better(CORR_LIMIT+0.01, CORR_LIMIT, CORR_LIMIT)==1\n",
    "    assert cmp_more_is_better(CORR_LIMIT+0.01, CORR_LIMIT+0.02, CORR_LIMIT)==-1\n",
    "    \n",
    "    def cmp_item(item, cmp_fn, limit):\n",
    "        return cmp_fn( round(stat0.loc[item], 2), round(stat1.loc[item], 2), limit )\n",
    "    \n",
    "    scores = [\n",
    "        cmp_item('Daily cointegration p-value', cmp_less_is_better, COINT_LIMIT),\n",
    "        cmp_item('Daily correlation', cmp_more_is_better, CORR_LIMIT),\n",
    "        cmp_item('Daily mean error', cmp_less_is_better, ME_LIMIT),\n",
    "        cmp_item('Trend/legs correlation', cmp_more_is_better, CORR_LIMIT),\n",
    "        cmp_item('Trend matching direction', cmp_more_is_better, CORR_LIMIT),\n",
    "    ]\n",
    "    score = np.sum(scores)\n",
    "    #return np.sign(score)\n",
    "    \n",
    "    # At the end of the day, I think daily mean (absolute) error is the best\n",
    "    # metric to compare the statistics\n",
    "    err0 = stat0.loc['Daily mean error']\n",
    "    err1 = stat1.loc['Daily mean error']\n",
    "    return 1 if err0 < err1 else -1 if err0 > err1 else 0\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "345d3ec7",
   "metadata": {},
   "source": [
    "### top_brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "be865e1e",
   "metadata": {
    "scrolled": false
   },
   "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>cum_net_val</th>\n",
       "      <th>trade_qty_pct</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>broker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ZP</th>\n",
       "      <td>2.453240e+11</td>\n",
       "      <td>0.083044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AK</th>\n",
       "      <td>2.243146e+11</td>\n",
       "      <td>0.074297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PD</th>\n",
       "      <td>1.506819e+11</td>\n",
       "      <td>0.063052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YP</th>\n",
       "      <td>1.311065e+11</td>\n",
       "      <td>0.086111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BB</th>\n",
       "      <td>1.151072e+11</td>\n",
       "      <td>0.021410</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         cum_net_val  trade_qty_pct\n",
       "broker                             \n",
       "ZP      2.453240e+11       0.083044\n",
       "AK      2.243146e+11       0.074297\n",
       "PD      1.506819e+11       0.063052\n",
       "YP      1.311065e+11       0.086111\n",
       "BB      1.151072e+11       0.021410"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_top_brokers(order_by: str = 'cum_net_val'):\n",
    "    \"\"\"\n",
    "    Top brokers are brokers with highest gross trade quantity or\n",
    "    net accummulation/distribution.\n",
    "    \"\"\"\n",
    "    df = master_brosum.groupby(['ticker', 'broker']).agg({\n",
    "        'cum_net_val': 'max',\n",
    "        'buy_qty': 'sum',\n",
    "        'sell_qty': 'sum',\n",
    "        'vol': 'sum',\n",
    "        \n",
    "    })\n",
    "    trade_qty = df[['buy_qty', 'sell_qty']].max(axis=1)\n",
    "    df['trade_qty_pct'] = trade_qty / df['vol']\n",
    "    df = df.drop(columns=['vol', 'buy_qty', 'sell_qty'])\n",
    "    df = df.sort_values(['ticker', order_by], ascending=[True, False])\n",
    "    return df\n",
    "    \n",
    "master_top_brokers = get_top_brokers()\n",
    "\n",
    "# Test\n",
    "master_top_brokers.loc[ TICKERS[0] ].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8458f10",
   "metadata": {},
   "source": [
    "### transpose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a0e208fb",
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>AG</th>\n",
       "      <th>AI</th>\n",
       "      <th>AK</th>\n",
       "      <th>AO</th>\n",
       "      <th>AZ</th>\n",
       "      <th>BB</th>\n",
       "      <th>...</th>\n",
       "      <th>SQ</th>\n",
       "      <th>TP</th>\n",
       "      <th>XA</th>\n",
       "      <th>XC</th>\n",
       "      <th>XL</th>\n",
       "      <th>YB</th>\n",
       "      <th>YJ</th>\n",
       "      <th>YP</th>\n",
       "      <th>YU</th>\n",
       "      <th>ZP</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2023-11-01</th>\n",
       "      <td>2480.061648</td>\n",
       "      <td>2470.061399</td>\n",
       "      <td>2350.058416</td>\n",
       "      <td>2360.058665</td>\n",
       "      <td>1.153556e+10</td>\n",
       "      <td>4.114722e+10</td>\n",
       "      <td>4.724417e+10</td>\n",
       "      <td>414285000.0</td>\n",
       "      <td>6.167070e+09</td>\n",
       "      <td>3.583402e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.464191e+10</td>\n",
       "      <td>1.054580e+10</td>\n",
       "      <td>5.446102e+09</td>\n",
       "      <td>9.143460e+08</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.622940e+08</td>\n",
       "      <td>9.285291e+09</td>\n",
       "      <td>1.790058e+10</td>\n",
       "      <td>5.002256e+10</td>\n",
       "      <td>3.677004e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-02</th>\n",
       "      <td>2360.068329</td>\n",
       "      <td>2410.069776</td>\n",
       "      <td>2360.068329</td>\n",
       "      <td>2380.068908</td>\n",
       "      <td>1.129188e+10</td>\n",
       "      <td>4.114915e+10</td>\n",
       "      <td>4.354575e+10</td>\n",
       "      <td>414285000.0</td>\n",
       "      <td>6.191588e+09</td>\n",
       "      <td>3.583402e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.541782e+10</td>\n",
       "      <td>1.056476e+10</td>\n",
       "      <td>4.782083e+09</td>\n",
       "      <td>2.886637e+09</td>\n",
       "      <td>9.804200e+08</td>\n",
       "      <td>3.138150e+08</td>\n",
       "      <td>9.366047e+09</td>\n",
       "      <td>1.919107e+10</td>\n",
       "      <td>4.871968e+10</td>\n",
       "      <td>3.648641e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-03</th>\n",
       "      <td>2380.073719</td>\n",
       "      <td>2420.074958</td>\n",
       "      <td>2380.073719</td>\n",
       "      <td>2390.074029</td>\n",
       "      <td>1.127238e+10</td>\n",
       "      <td>4.124574e+10</td>\n",
       "      <td>3.785625e+10</td>\n",
       "      <td>419065000.0</td>\n",
       "      <td>6.656069e+09</td>\n",
       "      <td>3.385112e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.347385e+10</td>\n",
       "      <td>1.091035e+10</td>\n",
       "      <td>4.810247e+09</td>\n",
       "      <td>3.932721e+09</td>\n",
       "      <td>2.311572e+09</td>\n",
       "      <td>3.617570e+08</td>\n",
       "      <td>9.358341e+09</td>\n",
       "      <td>2.001205e+10</td>\n",
       "      <td>4.900428e+10</td>\n",
       "      <td>3.718751e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-06</th>\n",
       "      <td>2390.078821</td>\n",
       "      <td>2420.079810</td>\n",
       "      <td>2390.078821</td>\n",
       "      <td>2400.079151</td>\n",
       "      <td>1.123935e+10</td>\n",
       "      <td>4.124231e+10</td>\n",
       "      <td>3.902987e+10</td>\n",
       "      <td>419065000.0</td>\n",
       "      <td>6.396993e+09</td>\n",
       "      <td>3.385112e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.075477e+10</td>\n",
       "      <td>1.085843e+10</td>\n",
       "      <td>4.993393e+09</td>\n",
       "      <td>4.459282e+09</td>\n",
       "      <td>2.431938e+09</td>\n",
       "      <td>3.461040e+08</td>\n",
       "      <td>9.351596e+09</td>\n",
       "      <td>2.479211e+10</td>\n",
       "      <td>4.897529e+10</td>\n",
       "      <td>3.694478e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-07</th>\n",
       "      <td>2400.059659</td>\n",
       "      <td>2410.059908</td>\n",
       "      <td>2350.058416</td>\n",
       "      <td>2360.058665</td>\n",
       "      <td>1.133426e+10</td>\n",
       "      <td>4.126627e+10</td>\n",
       "      <td>3.969751e+10</td>\n",
       "      <td>419303000.0</td>\n",
       "      <td>6.414884e+09</td>\n",
       "      <td>3.019051e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>2.156296e+10</td>\n",
       "      <td>1.116995e+10</td>\n",
       "      <td>5.249661e+09</td>\n",
       "      <td>5.762127e+09</td>\n",
       "      <td>3.582295e+09</td>\n",
       "      <td>3.828180e+08</td>\n",
       "      <td>9.376713e+09</td>\n",
       "      <td>2.842048e+10</td>\n",
       "      <td>4.865385e+10</td>\n",
       "      <td>3.718156e+10</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>2930.058389</td>\n",
       "      <td>2640.052610</td>\n",
       "      <td>2530.050418</td>\n",
       "      <td>2570.051215</td>\n",
       "      <td>1.503647e+09</td>\n",
       "      <td>5.446100e+08</td>\n",
       "      <td>4.971116e+09</td>\n",
       "      <td>478800000.0</td>\n",
       "      <td>1.190556e+09</td>\n",
       "      <td>3.929411e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.497801e+10</td>\n",
       "      <td>2.497546e+10</td>\n",
       "      <td>5.524823e+09</td>\n",
       "      <td>4.701552e+10</td>\n",
       "      <td>6.338140e+10</td>\n",
       "      <td>5.113956e+09</td>\n",
       "      <td>1.455500e+08</td>\n",
       "      <td>3.259723e+10</td>\n",
       "      <td>1.150675e+10</td>\n",
       "      <td>2.755129e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>2570.060984</td>\n",
       "      <td>2600.061696</td>\n",
       "      <td>2570.060984</td>\n",
       "      <td>2590.061458</td>\n",
       "      <td>1.600514e+09</td>\n",
       "      <td>9.712783e+09</td>\n",
       "      <td>3.302565e+09</td>\n",
       "      <td>478800000.0</td>\n",
       "      <td>1.897590e+09</td>\n",
       "      <td>3.929411e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.514252e+10</td>\n",
       "      <td>2.499753e+10</td>\n",
       "      <td>5.576126e+09</td>\n",
       "      <td>4.801374e+10</td>\n",
       "      <td>6.201286e+10</td>\n",
       "      <td>4.613214e+09</td>\n",
       "      <td>2.092210e+08</td>\n",
       "      <td>3.429997e+10</td>\n",
       "      <td>1.159920e+10</td>\n",
       "      <td>2.666607e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>2590.026319</td>\n",
       "      <td>2600.026421</td>\n",
       "      <td>2520.025608</td>\n",
       "      <td>2520.025608</td>\n",
       "      <td>2.712319e+09</td>\n",
       "      <td>2.223761e+10</td>\n",
       "      <td>2.815473e+09</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.173581e+09</td>\n",
       "      <td>3.929411e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.437807e+10</td>\n",
       "      <td>2.492447e+10</td>\n",
       "      <td>5.596215e+09</td>\n",
       "      <td>4.850148e+10</td>\n",
       "      <td>6.358581e+10</td>\n",
       "      <td>4.688761e+09</td>\n",
       "      <td>2.240520e+08</td>\n",
       "      <td>3.333254e+10</td>\n",
       "      <td>1.133396e+10</td>\n",
       "      <td>1.727217e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>2520.020568</td>\n",
       "      <td>2560.020894</td>\n",
       "      <td>2510.020486</td>\n",
       "      <td>2510.020486</td>\n",
       "      <td>2.728908e+09</td>\n",
       "      <td>2.225255e+10</td>\n",
       "      <td>1.702427e+09</td>\n",
       "      <td>11340000.0</td>\n",
       "      <td>1.298590e+09</td>\n",
       "      <td>3.929411e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.697364e+10</td>\n",
       "      <td>2.494852e+10</td>\n",
       "      <td>5.682707e+09</td>\n",
       "      <td>4.941745e+10</td>\n",
       "      <td>6.549923e+10</td>\n",
       "      <td>4.664107e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3.476282e+10</td>\n",
       "      <td>1.183362e+10</td>\n",
       "      <td>1.104028e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>2510.000000</td>\n",
       "      <td>2530.000000</td>\n",
       "      <td>2460.000000</td>\n",
       "      <td>2470.000000</td>\n",
       "      <td>2.741080e+09</td>\n",
       "      <td>2.230819e+10</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4917000.0</td>\n",
       "      <td>1.384584e+09</td>\n",
       "      <td>3.929411e+10</td>\n",
       "      <td>...</td>\n",
       "      <td>1.723845e+10</td>\n",
       "      <td>2.483219e+10</td>\n",
       "      <td>5.723966e+09</td>\n",
       "      <td>5.055562e+10</td>\n",
       "      <td>6.677666e+10</td>\n",
       "      <td>4.796355e+09</td>\n",
       "      <td>5.342380e+08</td>\n",
       "      <td>3.289600e+10</td>\n",
       "      <td>1.016747e+10</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 47 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   open         high          low        close            AG  \\\n",
       "date                                                                           \n",
       "2023-11-01  2480.061648  2470.061399  2350.058416  2360.058665  1.153556e+10   \n",
       "2023-11-02  2360.068329  2410.069776  2360.068329  2380.068908  1.129188e+10   \n",
       "2023-11-03  2380.073719  2420.074958  2380.073719  2390.074029  1.127238e+10   \n",
       "2023-11-06  2390.078821  2420.079810  2390.078821  2400.079151  1.123935e+10   \n",
       "2023-11-07  2400.059659  2410.059908  2350.058416  2360.058665  1.133426e+10   \n",
       "...                 ...          ...          ...          ...           ...   \n",
       "2024-05-21  2930.058389  2640.052610  2530.050418  2570.051215  1.503647e+09   \n",
       "2024-05-22  2570.060984  2600.061696  2570.060984  2590.061458  1.600514e+09   \n",
       "2024-05-27  2590.026319  2600.026421  2520.025608  2520.025608  2.712319e+09   \n",
       "2024-05-28  2520.020568  2560.020894  2510.020486  2510.020486  2.728908e+09   \n",
       "2024-05-29  2510.000000  2530.000000  2460.000000  2470.000000  2.741080e+09   \n",
       "\n",
       "                      AI            AK           AO            AZ  \\\n",
       "date                                                                \n",
       "2023-11-01  4.114722e+10  4.724417e+10  414285000.0  6.167070e+09   \n",
       "2023-11-02  4.114915e+10  4.354575e+10  414285000.0  6.191588e+09   \n",
       "2023-11-03  4.124574e+10  3.785625e+10  419065000.0  6.656069e+09   \n",
       "2023-11-06  4.124231e+10  3.902987e+10  419065000.0  6.396993e+09   \n",
       "2023-11-07  4.126627e+10  3.969751e+10  419303000.0  6.414884e+09   \n",
       "...                  ...           ...          ...           ...   \n",
       "2024-05-21  5.446100e+08  4.971116e+09  478800000.0  1.190556e+09   \n",
       "2024-05-22  9.712783e+09  3.302565e+09  478800000.0  1.897590e+09   \n",
       "2024-05-27  2.223761e+10  2.815473e+09          0.0  1.173581e+09   \n",
       "2024-05-28  2.225255e+10  1.702427e+09   11340000.0  1.298590e+09   \n",
       "2024-05-29  2.230819e+10  0.000000e+00    4917000.0  1.384584e+09   \n",
       "\n",
       "                      BB  ...            SQ            TP            XA  \\\n",
       "date                      ...                                             \n",
       "2023-11-01  3.583402e+10  ...  2.464191e+10  1.054580e+10  5.446102e+09   \n",
       "2023-11-02  3.583402e+10  ...  2.541782e+10  1.056476e+10  4.782083e+09   \n",
       "2023-11-03  3.385112e+10  ...  2.347385e+10  1.091035e+10  4.810247e+09   \n",
       "2023-11-06  3.385112e+10  ...  2.075477e+10  1.085843e+10  4.993393e+09   \n",
       "2023-11-07  3.019051e+10  ...  2.156296e+10  1.116995e+10  5.249661e+09   \n",
       "...                  ...  ...           ...           ...           ...   \n",
       "2024-05-21  3.929411e+10  ...  1.497801e+10  2.497546e+10  5.524823e+09   \n",
       "2024-05-22  3.929411e+10  ...  1.514252e+10  2.499753e+10  5.576126e+09   \n",
       "2024-05-27  3.929411e+10  ...  1.437807e+10  2.492447e+10  5.596215e+09   \n",
       "2024-05-28  3.929411e+10  ...  1.697364e+10  2.494852e+10  5.682707e+09   \n",
       "2024-05-29  3.929411e+10  ...  1.723845e+10  2.483219e+10  5.723966e+09   \n",
       "\n",
       "                      XC            XL            YB            YJ  \\\n",
       "date                                                                 \n",
       "2023-11-01  9.143460e+08  0.000000e+00  3.622940e+08  9.285291e+09   \n",
       "2023-11-02  2.886637e+09  9.804200e+08  3.138150e+08  9.366047e+09   \n",
       "2023-11-03  3.932721e+09  2.311572e+09  3.617570e+08  9.358341e+09   \n",
       "2023-11-06  4.459282e+09  2.431938e+09  3.461040e+08  9.351596e+09   \n",
       "2023-11-07  5.762127e+09  3.582295e+09  3.828180e+08  9.376713e+09   \n",
       "...                  ...           ...           ...           ...   \n",
       "2024-05-21  4.701552e+10  6.338140e+10  5.113956e+09  1.455500e+08   \n",
       "2024-05-22  4.801374e+10  6.201286e+10  4.613214e+09  2.092210e+08   \n",
       "2024-05-27  4.850148e+10  6.358581e+10  4.688761e+09  2.240520e+08   \n",
       "2024-05-28  4.941745e+10  6.549923e+10  4.664107e+09  0.000000e+00   \n",
       "2024-05-29  5.055562e+10  6.677666e+10  4.796355e+09  5.342380e+08   \n",
       "\n",
       "                      YP            YU            ZP  \n",
       "date                                                  \n",
       "2023-11-01  1.790058e+10  5.002256e+10  3.677004e+10  \n",
       "2023-11-02  1.919107e+10  4.871968e+10  3.648641e+10  \n",
       "2023-11-03  2.001205e+10  4.900428e+10  3.718751e+10  \n",
       "2023-11-06  2.479211e+10  4.897529e+10  3.694478e+10  \n",
       "2023-11-07  2.842048e+10  4.865385e+10  3.718156e+10  \n",
       "...                  ...           ...           ...  \n",
       "2024-05-21  3.259723e+10  1.150675e+10  2.755129e+09  \n",
       "2024-05-22  3.429997e+10  1.159920e+10  2.666607e+09  \n",
       "2024-05-27  3.333254e+10  1.133396e+10  1.727217e+09  \n",
       "2024-05-28  3.476282e+10  1.183362e+10  1.104028e+09  \n",
       "2024-05-29  3.289600e+10  1.016747e+10  0.000000e+00  \n",
       "\n",
       "[131 rows x 47 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def transpose_brosum(ticker: str,\n",
    "                     additional_columns: List[str] = [],\n",
    "                     fillnas: List[str] = []) -> pd.DataFrame:\n",
    "    \"\"\"\n",
    "    Transpose broker summary into simplified format with one broker per column containing\n",
    "    cummulative net buy/sell value (cum_net_val). Additional columns may be specified.\n",
    "    Each additional column will add one column per broker.\n",
    "    \"\"\"\n",
    "    assert not len(fillnas) or len(fillnas)==len(additional_columns), \"fillna specs must match number of additional columns\"\n",
    "    \n",
    "    df = master_brosum[ master_brosum.index.get_level_values('ticker')==ticker ]\n",
    "    df = df.droplevel('ticker')\n",
    "    data = {}\n",
    "    brokers = []\n",
    "    for broker, group in df.groupby('broker'):\n",
    "        brokers.append(broker)\n",
    "        group = group.droplevel('broker')\n",
    "        if 'close' not in data:\n",
    "            for col in ['open', 'high', 'low', 'close']:\n",
    "                data[col] = group[col]\n",
    "        ser = group['cum_net_val']\n",
    "        ser.name = broker\n",
    "        data[broker] = ser\n",
    "        for col in additional_columns:\n",
    "            ser = group[col]\n",
    "            ser.name = f'{broker} {col}'\n",
    "            data[f'{broker} {col}'] = ser\n",
    "\n",
    "    df = pd.concat(data.values(), axis=1)\n",
    "    df[brokers] = df[brokers].fillna(method='pad')\n",
    "    if fillnas:\n",
    "        for i, col in enumerate(additional_columns):\n",
    "            cols = [f'{broker} {col}' for broker in brokers]\n",
    "            if isinstance(fillnas[i], str):\n",
    "                df[cols] = df[cols].fillna(method=fillnas[i])\n",
    "            else:\n",
    "                df[cols] = df[cols].fillna(fillnas[i])\n",
    "            \n",
    "    return df\n",
    "\n",
    "# Test\n",
    "transpose_brosum('PTBA')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "775bd68d",
   "metadata": {},
   "source": [
    "### aggregate_brosum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "289c518f",
   "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>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>vol</th>\n",
       "      <th>buy_qty</th>\n",
       "      <th>sell_qty</th>\n",
       "      <th>buy_val</th>\n",
       "      <th>sell_val</th>\n",
       "      <th>net_val</th>\n",
       "      <th>net_qty</th>\n",
       "      <th>qty</th>\n",
       "      <th>cum_net_val</th>\n",
       "      <th>stock_value</th>\n",
       "      <th>pl</th>\n",
       "      <th>cum_pl</th>\n",
       "      <th>avg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>2023-11-01</th>\n",
       "      <td>1704.971739</td>\n",
       "      <td>1714.971573</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>4.364862e+07</td>\n",
       "      <td>8104600.0</td>\n",
       "      <td>3961100.0</td>\n",
       "      <td>1.356357e+10</td>\n",
       "      <td>6.624538e+09</td>\n",
       "      <td>6.939034e+09</td>\n",
       "      <td>4143500.0</td>\n",
       "      <td>4143500.0</td>\n",
       "      <td>6.939034e+09</td>\n",
       "      <td>6.836662e+09</td>\n",
       "      <td>-4.631887e+06</td>\n",
       "      <td>-4.631887e+06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-02</th>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1684.972070</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>1649.972650</td>\n",
       "      <td>3.166092e+07</td>\n",
       "      <td>3700900.0</td>\n",
       "      <td>1662100.0</td>\n",
       "      <td>6.152864e+09</td>\n",
       "      <td>2.777501e+09</td>\n",
       "      <td>3.375363e+09</td>\n",
       "      <td>2038800.0</td>\n",
       "      <td>6182300.0</td>\n",
       "      <td>1.031440e+10</td>\n",
       "      <td>1.020063e+10</td>\n",
       "      <td>3.722557e+06</td>\n",
       "      <td>-9.093296e+05</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-03</th>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1674.977353</td>\n",
       "      <td>1649.977691</td>\n",
       "      <td>1654.977623</td>\n",
       "      <td>2.787938e+07</td>\n",
       "      <td>5705000.0</td>\n",
       "      <td>1273600.0</td>\n",
       "      <td>9.445945e+09</td>\n",
       "      <td>2.112027e+09</td>\n",
       "      <td>7.333918e+09</td>\n",
       "      <td>4431400.0</td>\n",
       "      <td>10613700.0</td>\n",
       "      <td>1.764832e+10</td>\n",
       "      <td>1.756544e+10</td>\n",
       "      <td>-4.999603e+06</td>\n",
       "      <td>-5.908932e+06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-06</th>\n",
       "      <td>1655.021785</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>1660.021850</td>\n",
       "      <td>1700.022377</td>\n",
       "      <td>3.642812e+07</td>\n",
       "      <td>2120200.0</td>\n",
       "      <td>3708800.0</td>\n",
       "      <td>3.575189e+09</td>\n",
       "      <td>6.246902e+09</td>\n",
       "      <td>-2.671713e+09</td>\n",
       "      <td>-1588600.0</td>\n",
       "      <td>9025100.0</td>\n",
       "      <td>1.497660e+10</td>\n",
       "      <td>1.534287e+10</td>\n",
       "      <td>6.742604e+07</td>\n",
       "      <td>6.151711e+07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-07</th>\n",
       "      <td>1700.012505</td>\n",
       "      <td>1715.012616</td>\n",
       "      <td>1675.012321</td>\n",
       "      <td>1690.012432</td>\n",
       "      <td>2.215334e+07</td>\n",
       "      <td>2401000.0</td>\n",
       "      <td>1560000.0</td>\n",
       "      <td>4.069732e+09</td>\n",
       "      <td>2.644640e+09</td>\n",
       "      <td>1.425092e+09</td>\n",
       "      <td>841000.0</td>\n",
       "      <td>9866100.0</td>\n",
       "      <td>1.640169e+10</td>\n",
       "      <td>1.667383e+10</td>\n",
       "      <td>3.603566e+07</td>\n",
       "      <td>9.755277e+07</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>1654.881681</td>\n",
       "      <td>1594.885971</td>\n",
       "      <td>1539.889903</td>\n",
       "      <td>1564.888115</td>\n",
       "      <td>5.924194e+07</td>\n",
       "      <td>9063100.0</td>\n",
       "      <td>5988200.0</td>\n",
       "      <td>1.418168e+10</td>\n",
       "      <td>9.388993e+09</td>\n",
       "      <td>4.792685e+09</td>\n",
       "      <td>3074900.0</td>\n",
       "      <td>60953100.0</td>\n",
       "      <td>8.163560e+10</td>\n",
       "      <td>9.538478e+10</td>\n",
       "      <td>-1.215813e+08</td>\n",
       "      <td>1.512301e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>1565.000000</td>\n",
       "      <td>1580.000000</td>\n",
       "      <td>1520.000000</td>\n",
       "      <td>1525.000000</td>\n",
       "      <td>4.217750e+07</td>\n",
       "      <td>4971500.0</td>\n",
       "      <td>2194000.0</td>\n",
       "      <td>7.660842e+09</td>\n",
       "      <td>3.396661e+09</td>\n",
       "      <td>4.264181e+09</td>\n",
       "      <td>2777500.0</td>\n",
       "      <td>63730600.0</td>\n",
       "      <td>8.589979e+10</td>\n",
       "      <td>9.718917e+10</td>\n",
       "      <td>-7.869742e+07</td>\n",
       "      <td>1.504431e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>1524.969565</td>\n",
       "      <td>1534.969366</td>\n",
       "      <td>1489.970264</td>\n",
       "      <td>1494.970164</td>\n",
       "      <td>3.450669e+07</td>\n",
       "      <td>4490500.0</td>\n",
       "      <td>3408100.0</td>\n",
       "      <td>6.744205e+09</td>\n",
       "      <td>5.121184e+09</td>\n",
       "      <td>1.623021e+09</td>\n",
       "      <td>1082400.0</td>\n",
       "      <td>64813000.0</td>\n",
       "      <td>8.752281e+10</td>\n",
       "      <td>9.689350e+10</td>\n",
       "      <td>-2.534204e+08</td>\n",
       "      <td>1.479089e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>1494.990186</td>\n",
       "      <td>1534.989923</td>\n",
       "      <td>1499.990153</td>\n",
       "      <td>1514.990055</td>\n",
       "      <td>3.367952e+07</td>\n",
       "      <td>2623200.0</td>\n",
       "      <td>1997900.0</td>\n",
       "      <td>3.991173e+09</td>\n",
       "      <td>3.040302e+09</td>\n",
       "      <td>9.508710e+08</td>\n",
       "      <td>625300.0</td>\n",
       "      <td>65438300.0</td>\n",
       "      <td>8.847368e+10</td>\n",
       "      <td>9.913837e+10</td>\n",
       "      <td>-1.080517e+08</td>\n",
       "      <td>1.468284e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>1515.000000</td>\n",
       "      <td>1540.000000</td>\n",
       "      <td>1505.000000</td>\n",
       "      <td>1525.000000</td>\n",
       "      <td>2.707680e+07</td>\n",
       "      <td>3480200.0</td>\n",
       "      <td>3219200.0</td>\n",
       "      <td>5.296980e+09</td>\n",
       "      <td>4.878367e+09</td>\n",
       "      <td>4.186130e+08</td>\n",
       "      <td>261000.0</td>\n",
       "      <td>65699300.0</td>\n",
       "      <td>8.889229e+10</td>\n",
       "      <td>1.001914e+11</td>\n",
       "      <td>-1.819448e+08</td>\n",
       "      <td>1.450090e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   open         high          low        close           vol  \\\n",
       "date                                                                           \n",
       "2023-11-01  1704.971739  1714.971573  1649.972650  1649.972650  4.364862e+07   \n",
       "2023-11-02  1649.972650  1684.972070  1649.972650  1649.972650  3.166092e+07   \n",
       "2023-11-03  1649.977691  1674.977353  1649.977691  1654.977623  2.787938e+07   \n",
       "2023-11-06  1655.021785  1700.022377  1660.021850  1700.022377  3.642812e+07   \n",
       "2023-11-07  1700.012505  1715.012616  1675.012321  1690.012432  2.215334e+07   \n",
       "...                 ...          ...          ...          ...           ...   \n",
       "2024-05-21  1654.881681  1594.885971  1539.889903  1564.888115  5.924194e+07   \n",
       "2024-05-22  1565.000000  1580.000000  1520.000000  1525.000000  4.217750e+07   \n",
       "2024-05-27  1524.969565  1534.969366  1489.970264  1494.970164  3.450669e+07   \n",
       "2024-05-28  1494.990186  1534.989923  1499.990153  1514.990055  3.367952e+07   \n",
       "2024-05-29  1515.000000  1540.000000  1505.000000  1525.000000  2.707680e+07   \n",
       "\n",
       "              buy_qty   sell_qty       buy_val      sell_val       net_val  \\\n",
       "date                                                                         \n",
       "2023-11-01  8104600.0  3961100.0  1.356357e+10  6.624538e+09  6.939034e+09   \n",
       "2023-11-02  3700900.0  1662100.0  6.152864e+09  2.777501e+09  3.375363e+09   \n",
       "2023-11-03  5705000.0  1273600.0  9.445945e+09  2.112027e+09  7.333918e+09   \n",
       "2023-11-06  2120200.0  3708800.0  3.575189e+09  6.246902e+09 -2.671713e+09   \n",
       "2023-11-07  2401000.0  1560000.0  4.069732e+09  2.644640e+09  1.425092e+09   \n",
       "...               ...        ...           ...           ...           ...   \n",
       "2024-05-21  9063100.0  5988200.0  1.418168e+10  9.388993e+09  4.792685e+09   \n",
       "2024-05-22  4971500.0  2194000.0  7.660842e+09  3.396661e+09  4.264181e+09   \n",
       "2024-05-27  4490500.0  3408100.0  6.744205e+09  5.121184e+09  1.623021e+09   \n",
       "2024-05-28  2623200.0  1997900.0  3.991173e+09  3.040302e+09  9.508710e+08   \n",
       "2024-05-29  3480200.0  3219200.0  5.296980e+09  4.878367e+09  4.186130e+08   \n",
       "\n",
       "              net_qty         qty   cum_net_val   stock_value            pl  \\\n",
       "date                                                                          \n",
       "2023-11-01  4143500.0   4143500.0  6.939034e+09  6.836662e+09 -4.631887e+06   \n",
       "2023-11-02  2038800.0   6182300.0  1.031440e+10  1.020063e+10  3.722557e+06   \n",
       "2023-11-03  4431400.0  10613700.0  1.764832e+10  1.756544e+10 -4.999603e+06   \n",
       "2023-11-06 -1588600.0   9025100.0  1.497660e+10  1.534287e+10  6.742604e+07   \n",
       "2023-11-07   841000.0   9866100.0  1.640169e+10  1.667383e+10  3.603566e+07   \n",
       "...               ...         ...           ...           ...           ...   \n",
       "2024-05-21  3074900.0  60953100.0  8.163560e+10  9.538478e+10 -1.215813e+08   \n",
       "2024-05-22  2777500.0  63730600.0  8.589979e+10  9.718917e+10 -7.869742e+07   \n",
       "2024-05-27  1082400.0  64813000.0  8.752281e+10  9.689350e+10 -2.534204e+08   \n",
       "2024-05-28   625300.0  65438300.0  8.847368e+10  9.913837e+10 -1.080517e+08   \n",
       "2024-05-29   261000.0  65699300.0  8.889229e+10  1.001914e+11 -1.819448e+08   \n",
       "\n",
       "                  cum_pl  avg  \n",
       "date                           \n",
       "2023-11-01 -4.631887e+06  NaN  \n",
       "2023-11-02 -9.093296e+05  NaN  \n",
       "2023-11-03 -5.908932e+06  NaN  \n",
       "2023-11-06  6.151711e+07  NaN  \n",
       "2023-11-07  9.755277e+07  NaN  \n",
       "...                  ...  ...  \n",
       "2024-05-21  1.512301e+10  NaN  \n",
       "2024-05-22  1.504431e+10  NaN  \n",
       "2024-05-27  1.479089e+10  NaN  \n",
       "2024-05-28  1.468284e+10  NaN  \n",
       "2024-05-29  1.450090e+10  NaN  \n",
       "\n",
       "[131 rows x 17 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def aggregate_brosum(ticker: str, brokers: List[str]) -> pd.DataFrame:\n",
    "    df = master_brosum[(master_brosum.index.get_level_values('ticker')==ticker) & \n",
    "                       (master_brosum.index.get_level_values('broker').isin(brokers))\n",
    "                      ]\n",
    "    df = df.groupby('date').agg({\n",
    "        'open': 'first',\n",
    "        'high': 'first',\n",
    "        'low': 'first',\n",
    "        'close': 'first',\n",
    "        'vol': 'first',\n",
    "        'buy_qty': 'sum',\n",
    "        'sell_qty': 'sum',\n",
    "        'buy_val': 'sum',\n",
    "        'sell_val': 'sum',\n",
    "        'net_val': 'sum',\n",
    "        'net_qty': 'sum',\n",
    "        'qty': 'sum',\n",
    "        'cum_net_val': 'sum',\n",
    "        'stock_value': 'sum',\n",
    "        'pl': 'sum',\n",
    "        'cum_pl': 'sum',\n",
    "    })\n",
    "    df['avg'] = np.NaN\n",
    "    return df\n",
    "\n",
    "# Sample\n",
    "aggregate_brosum( TICKERS[0], ['YP', 'XL'] )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e8e8e3d",
   "metadata": {},
   "source": [
    "### display_aggregate_brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "99486acb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def display_aggregate_brokers(ticker: str, brokers: List[str], title: str = 'Aggregate', show_legs=True):\n",
    "    bs = master_brosum[(master_brosum.index.get_level_values('ticker')==ticker) & \n",
    "                       (master_brosum.index.get_level_values('broker').isin(brokers))\n",
    "                      ]\n",
    "    bs = aggregate_brosum(ticker, brokers)\n",
    "\n",
    "    fig = ba.display_single_broker_single_security_analysis(bs, f'{title}', show=False)\n",
    "    if show_legs:\n",
    "        plot_legs(bs, fig.charts[0].ax2 )\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "# Sample\n",
    "display_aggregate_brokers(TICKERS[0], \n",
    "                          master_top_brokers.loc[ TICKERS[0] ].head(10).index, \n",
    "                          'Top 10 Brokers Aggregate')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "29ebcff3",
   "metadata": {},
   "source": [
    "### display_individual_brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "91fada55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x864 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def display_individual_brokers(ticker: str, brokers: List[str], title: str = None):\n",
    "    MILYAR = 1e9\n",
    "    \n",
    "    df = transpose_brosum(ticker, ['net_val'])\n",
    "    brokers = list(brokers)\n",
    "    \n",
    "    # Change to milyar\n",
    "    broker_cols = brokers + [f'{broker} net_val' for broker in brokers]\n",
    "    df[broker_cols] /= MILYAR\n",
    "    \n",
    "    A = 0.3\n",
    "    charts = []\n",
    "    \n",
    "    # Main chart: all brokers at once\n",
    "    plots = [pt.Plot(broker, alpha=1.0, zorder=20-j) for j,broker in enumerate(brokers)]\n",
    "    plots.append( pt.Plot('close', secondary_y=True, alpha=A,\n",
    "                          kind='candlestick' if len(df) < 200 else 'line' ) )\n",
    "    chart = pt.Chart(plots, ylabel='Milyar (Rp)', secondary_ylabel='Price', row_span=3)\n",
    "    charts.append(chart)\n",
    "\n",
    "    # Individual net buy/sell\n",
    "    for broker in brokers:\n",
    "        col_name = broker + ' net_val'\n",
    "        last = df[col_name].iloc[-1]\n",
    "        label = f'{col_name} (last: {last:+.1f})'\n",
    "        chart = pt.Chart([\n",
    "            pt.Plot(col_name, alpha=0.5, kind='bar', zorder=10, label=label,\n",
    "                    color_cb=lambda v: 'blue' if (not pd.isnull(v) and v>=0) else 'red'),\n",
    "            pt.HLine(0, color='k', alpha=0.5, zorder=0),\n",
    "        ], ylabel='Milyar (Rp)', legend_loc='upper center', )\n",
    "        charts.append(chart)\n",
    "    \n",
    "    if not title:\n",
    "        title = f'{ticker}: {\", \".join(brokers)}'\n",
    "    fig = pt.Figure(charts, row_height=2, title=title)\n",
    "    fig.plot(df)\n",
    "\n",
    "\n",
    "# Test\n",
    "display_individual_brokers(TICKERS[0], \n",
    "                           master_top_brokers.loc[ TICKERS[0] ].head(3).index)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f5fa0a9",
   "metadata": {},
   "source": [
    "## Global Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a54734a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def global_analysis(brokers: List[str]):\n",
    "    bs = master_brosum.loc[brokers]\n",
    "    bs = bs.groupby('date')[['buy_val', 'sell_val', 'net_val', 'stock_value', 'cum_pl']].sum()\n",
    "    bs['close'] = np.NaN\n",
    "    bs['avg'] = np.NaN\n",
    "    bs['cum_net_val'] = bs['net_val'].cumsum()\n",
    "    ba.display_single_broker_single_security_analysis(bs, ', '.join(brokers))\n",
    "    return bs[['net_val']].iloc[-5:].iloc[::-1] / 1e9"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b44f8cba",
   "metadata": {},
   "source": [
    "### YP-mologi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "af890cc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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>net_val</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>143.910578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>14.392533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>184.428375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>62.208572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>260.691010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               net_val\n",
       "date                  \n",
       "2024-05-29  143.910578\n",
       "2024-05-28   14.392533\n",
       "2024-05-27  184.428375\n",
       "2024-05-22   62.208572\n",
       "2024-05-21  260.691010"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_analysis(['YP'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f78828df",
   "metadata": {},
   "source": [
    "### Retail Brokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "00e5a558",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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>net_val</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-05-29</th>\n",
       "      <td>780.174771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-28</th>\n",
       "      <td>318.155611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-27</th>\n",
       "      <td>870.015128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-22</th>\n",
       "      <td>141.249465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-21</th>\n",
       "      <td>898.368804</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               net_val\n",
       "date                  \n",
       "2024-05-29  780.174771\n",
       "2024-05-28  318.155611\n",
       "2024-05-27  870.015128\n",
       "2024-05-22  141.249465\n",
       "2024-05-21  898.368804"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "global_analysis(RETAIL_BROKERS)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b56c3d78",
   "metadata": {},
   "source": [
    "## Analyze Foreign and Bandarmologi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "799a434c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_top_brokers(ticker: str) -> List[str]:\n",
    "    top_broker_stas = master_top_brokers.loc[ticker]\n",
    "    \n",
    "    # Brokers with top wealth movement\n",
    "    top_cum_val_brokers = top_broker_stas.sort_values('cum_net_val', ascending=False).iloc[:20]\n",
    "    # Brokers with total trading quantity at least 1%\n",
    "    top_traders = top_broker_stas[ top_broker_stas['trade_qty_pct'] >= 0.01 ]\n",
    "    # Combine to make top_brokers\n",
    "    top_brokers = list(top_cum_val_brokers.index) + [broker for broker in top_traders.index \n",
    "                                                     if broker not in top_cum_val_brokers.index]\n",
    "\n",
    "    return top_brokers"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "035c2b63",
   "metadata": {},
   "source": [
    "### Find most correlated broker(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2dd013c1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def find_next_correlated_brokers(ticker: str, \n",
    "                                 initial_brokers: List[str],\n",
    "                                 initial_stat: pd.DataFrame,  # Can be None if initial_brokers is empty\n",
    "                                 available_brokers: List[str]) -> pd.DataFrame:\n",
    "    available_brokers = [b for b in available_brokers if b not in initial_brokers]\n",
    "    best_stat = initial_stat\n",
    "    for i, broker in enumerate(available_brokers):\n",
    "        brokers = initial_brokers + [broker]\n",
    "        #logger.info(f'Analyzing {\" \".join(brokers)}..', progress=(i, len(available_brokers)))\n",
    "        df = aggregate_brosum(ticker, brokers)\n",
    "        stat = calc_ts_statistics(df['close'], df['cum_net_val'])\n",
    "        stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "        \n",
    "        if best_stat is None or compare_ts_statistics(stat['cum_net_val'], best_stat['cum_net_val']) > 0:\n",
    "            best_stat = stat\n",
    "    \n",
    "    #logger.end_progress()\n",
    "    return best_stat\n",
    "\n",
    "\n",
    "def find_most_correlated_brokers(ticker: str, max_brokers: int = 15) -> pd.DataFrame:\n",
    "    last_stat = None\n",
    "    logger = Logger.get()\n",
    "    for i in range(max_brokers):\n",
    "        logger.info(f'{ticker} search {i+1} broker(s)..', progress=(i, max_brokers))\n",
    "        if last_stat is None:\n",
    "            stat = find_next_correlated_brokers(ticker, [], None, BROKERS)\n",
    "        else:\n",
    "            stat = find_next_correlated_brokers(ticker, last_stat.loc['Brokers', 'cum_net_val'].split(), \n",
    "                                                last_stat, BROKERS)\n",
    "\n",
    "        if last_stat is not None:\n",
    "            me = stat.loc['Daily mean error', 'cum_net_val']\n",
    "            last_me = last_stat.loc['Daily mean error', 'cum_net_val']\n",
    "            if me/last_me > 0.99:\n",
    "                # Not improving or improving less than 1%\n",
    "                break\n",
    "\n",
    "        last_stat = stat\n",
    "    \n",
    "    logger.end_progress()\n",
    "    last_stat.columns = ['Auto Search']\n",
    "    return last_stat\n",
    "\n",
    "\n",
    "#stat = find_most_correlated_brokers('TSPC')\n",
    "#display(stat)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b915277e",
   "metadata": {},
   "source": [
    "### Additional bandarmologi specs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c784204e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ADDITIONAL_BANDARMOLOGI_SPECS = {\n",
    "    'ANTM': {\n",
    "        'desc': 'Undecided between foreign and non-retail brokers',\n",
    "        'Possible actors': ['ZP', 'KZ', 'BK'],\n",
    "    },\n",
    "    'BBRI': {\n",
    "        'Usual Foreign': ['ZP', 'KZ', 'BK', 'AK', 'RX'],\n",
    "    },\n",
    "    'BTPS': {\n",
    "        'Possible actors': ['RX', 'KZ', 'AK', 'ZP', 'BK', ],\n",
    "    },\n",
    "    'ELPI': {\n",
    "         'Possible actors': ['LG', 'BK', 'DR'], # 'PD', \n",
    "         'Possible actors minus LG': ['BK', 'DR'], # 'PD', \n",
    "    },\n",
    "    'ELSA': {\n",
    "        'desc': 'Use foreign!',\n",
    "    },\n",
    "    'HATM': {\n",
    "        'desc': 'Use foreign!',\n",
    "    },\n",
    "    'MNCN': {\n",
    "        'desc': 'Bandarmologinya udah lumayan kedeteksi.\\n\\n' +\n",
    "                'Kebanyakan brokers jualan, dan ditampung oleh EP (MNC sekuritas). ' +\n",
    "                'Di bawah akan ditunjukkan 2 jenis chart brokers, i.e. tanpa dan dengan EP',\n",
    "        'Possible actors minus EP': ['YU', 'CC', 'ZP', 'BK', 'AI', 'AK', 'KZ', 'TP', ],\n",
    "        'Possible actors': ['EP', 'YU', 'CC', 'ZP', 'BK', 'AI', 'AK', 'KZ', 'TP', ],\n",
    "    },\n",
    "    'SMDR': {\n",
    "        'Clever': ['PG'],\n",
    "        'Possible actors': ['AK', 'GR', 'BB'],\n",
    "        'Buyers': ['XL', 'CC', 'NI', 'SQ', 'XC', ],\n",
    "    },\n",
    "    'TUGU': {\n",
    "        'RF': ['RF'],\n",
    "    },\n",
    "    'TSPC': {\n",
    "        'Possible actors': ['CC', 'TP', 'AK', 'YP', 'YU', 'EP', 'GR', 'KK', 'BK', ],\n",
    "        'Major players': ['CC', 'TP', 'AK', ],\n",
    "    },\n",
    "}\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e76eec72",
   "metadata": {},
   "source": [
    "### analyze_foreign_bandarmologi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7c2e50c4",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "from functools import cmp_to_key\n",
    "\n",
    "def analyze_foreign_bandarmologi(ticker, additional_specs: Dict = None):\n",
    "    LAST_BUYERS_SELLERS = 5\n",
    "    LAST_BUYERS_SELLERS_DAYS = 2\n",
    "    \n",
    "    top_brokers = get_top_brokers(ticker)\n",
    "    \n",
    "    # Data\n",
    "    ohlc = master_ohlc.loc[ticker]\n",
    "    ff = master_ff.loc[ticker]\n",
    "    ts_stats = []\n",
    "    \n",
    "    # TIme series statistics for foreign\n",
    "    stat = calc_ts_statistics(ff['close'], ff['cum_net_val'].rename('Foreign'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ''\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for last buyers\n",
    "    last_date = ohlc.index.get_level_values('date').max().normalize()\n",
    "    if LAST_BUYERS_SELLERS_DAYS:\n",
    "        last_date = bei.get_last_market_time(last_date).normalize()\n",
    "        #print('Last date', last_date)\n",
    "    bs_tkr = master_brosum[(master_brosum.index.get_level_values('ticker')==ticker) &\n",
    "                           (master_brosum.index.get_level_values('date')>=last_date)\n",
    "                          ]\n",
    "    net_val = bs_tkr.groupby('broker')['net_val'].sum()\n",
    "    net_val = net_val.sort_values(ascending=False)\n",
    "    brokers = net_val.index.get_level_values('broker')[:LAST_BUYERS_SELLERS]\n",
    "    #print('Top buyers:', net_val.iloc[:LAST_BUYERS_SELLERS])\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], \n",
    "                              df['cum_net_val']\n",
    "                                .rename(f'Top {LAST_BUYERS_SELLERS} Last Buyers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for last sellers\n",
    "    brokers = net_val.index.get_level_values('broker')[-LAST_BUYERS_SELLERS:]\n",
    "    #print('Top sellers:', net_val.iloc[-LAST_BUYERS_SELLERS:])\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], \n",
    "                              df['cum_net_val']\n",
    "                                .rename(f'Top {LAST_BUYERS_SELLERS} Last Sellers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for automatically searched most correlated brokers\n",
    "    stat = find_most_correlated_brokers(ticker)\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for top_brokers\n",
    "    brokers = top_brokers\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], df['cum_net_val'].rename(f'Top Brokers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "\n",
    "    # Time series statistics for top non retail\n",
    "    brokers = [broker for broker in top_brokers if broker not in RETAIL_BROKERS]\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], df['cum_net_val'].rename(f'Top Non-retail Brokers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for non-retail brokers\n",
    "    brokers = [broker for broker in BROKERS if broker not in RETAIL_BROKERS]\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], \n",
    "                              df['cum_net_val']\n",
    "                                .rename(f'All Non-retail Brokers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "    \n",
    "    # Time series statistics for retail brokers\n",
    "    brokers = RETAIL_BROKERS\n",
    "    df = aggregate_brosum(ticker, brokers)\n",
    "    stat = calc_ts_statistics(df['close'], \n",
    "                              df['cum_net_val']\n",
    "                                .rename(f'Retail Brokers'))\n",
    "    stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "    ts_stats.append(stat)\n",
    "\n",
    "    # Additional specs\n",
    "    if additional_specs:\n",
    "        for title, brokers in additional_specs.items():\n",
    "            if title=='desc':\n",
    "                continue\n",
    "            df = aggregate_brosum(ticker, brokers)\n",
    "            stat = calc_ts_statistics(df['close'], \n",
    "                                      df['cum_net_val']\n",
    "                                        .rename(title))\n",
    "            stat.loc['Brokers', stat.columns[0]] = ' '.join(brokers)\n",
    "            ts_stats.append(stat)\n",
    "    \n",
    "    # ts_stat (without s) is stats as dataframe\n",
    "    ts_stat = pd.concat(ts_stats, axis=1)\n",
    "    \n",
    "    # Get the best stat\n",
    "    best_stats = sorted([ts_stat[ts_stat.columns[i]] for i in range(len(ts_stat.columns))],\n",
    "                        key=cmp_to_key(compare_ts_statistics),\n",
    "                        reverse=True)\n",
    "    for i, stat in enumerate(best_stats):\n",
    "        ts_stat.loc['Calculated Rank', stat.name] = i\n",
    "    \n",
    "    return ts_stat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "9fe9039f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sample\n",
    "if False:\n",
    "    stat = analyze_foreign_bandarmologi( TICKERS[0], ADDITIONAL_BANDARMOLOGI_SPECS.get( TICKERS[0] ) )\n",
    "    display_ts_statistics( stat )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1f68b8f",
   "metadata": {},
   "source": [
    "### analyze_bandarmologi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "a12c74bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "master_stats = {}\n",
    "for ticker in TICKERS:\n",
    "    #master_stats[ticker] = analyze_foreign_bandarmologi( ticker, ADDITIONAL_BANDARMOLOGI_SPECS.get(ticker) )\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15c99ce1",
   "metadata": {},
   "source": [
    "## Display Bandarmologi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "b90520b8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def display_bandarmologi(ticker: str, detail: bool = False):\n",
    "    display(Markdown(f'### {ticker}'))\n",
    "    #display(Markdown(f'#### Time series analysis results'))\n",
    "    #stat = master_stats[ticker]\n",
    "    stat = analyze_foreign_bandarmologi( ticker, ADDITIONAL_BANDARMOLOGI_SPECS.get(ticker) )\n",
    "    \n",
    "    ranked = list(stat.loc['Calculated Rank'].sort_values().index)\n",
    "    \n",
    "    stat = stat[ranked]\n",
    "    display_ts_statistics(stat)\n",
    "    \n",
    "    for bandarmologi in ranked:\n",
    "        display(Markdown(f'#### {bandarmologi}'))\n",
    "        display_ts_statistics( stat[[bandarmologi]] )\n",
    "        \n",
    "        brokers = stat.loc['Brokers', bandarmologi].split()\n",
    "        \n",
    "        if brokers:\n",
    "            display_aggregate_brokers(ticker, \n",
    "                                      brokers, \n",
    "                                      f'{ticker}: {bandarmologi}')\n",
    "            if detail:\n",
    "                brkrs = brokers[:5]\n",
    "                display_individual_brokers(ticker, brkrs, title=f'{bandarmologi}: {\", \".join(brkrs)}')\n",
    "                \n",
    "        elif bandarmologi=='Foreign':\n",
    "            df = master_ff.loc[ticker]\n",
    "            ba.display_single_broker_single_security_analysis(df, f'{ticker}: Foreign')\n",
    "                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "0505510e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "### ANTM"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19:13:27.120 INFO  ANTM search 5 broker(s).. [####################] [15/15] 100% [19.9s]        \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_03216_row1_col2, #T_03216_row1_col4, #T_03216_row3_col0, #T_03216_row3_col2, #T_03216_row3_col4, #T_03216_row3_col6, #T_03216_row3_col7, #T_03216_row4_col0, #T_03216_row4_col1, #T_03216_row4_col2, #T_03216_row4_col3, #T_03216_row4_col4, #T_03216_row4_col5, #T_03216_row4_col6, #T_03216_row4_col7 {\n",
       "  background-color: lightgreen;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_03216_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >Auto Search</th>\n",
       "      <th class=\"col_heading level0 col1\" >Top 5 Last Sellers</th>\n",
       "      <th class=\"col_heading level0 col2\" >All Non-retail Brokers</th>\n",
       "      <th class=\"col_heading level0 col3\" >Possible actors</th>\n",
       "      <th class=\"col_heading level0 col4\" >Top Non-retail Brokers</th>\n",
       "      <th class=\"col_heading level0 col5\" >Top Brokers</th>\n",
       "      <th class=\"col_heading level0 col6\" >Foreign</th>\n",
       "      <th class=\"col_heading level0 col7\" >Top 5 Last Buyers</th>\n",
       "      <th class=\"col_heading level0 col8\" >Retail Brokers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row0\" class=\"row_heading level0 row0\" >Daily cointegration p-value</th>\n",
       "      <td id=\"T_03216_row0_col0\" class=\"data row0 col0\" >0.15</td>\n",
       "      <td id=\"T_03216_row0_col1\" class=\"data row0 col1\" >0.19</td>\n",
       "      <td id=\"T_03216_row0_col2\" class=\"data row0 col2\" >0.64</td>\n",
       "      <td id=\"T_03216_row0_col3\" class=\"data row0 col3\" >0.95</td>\n",
       "      <td id=\"T_03216_row0_col4\" class=\"data row0 col4\" >0.83</td>\n",
       "      <td id=\"T_03216_row0_col5\" class=\"data row0 col5\" >0.97</td>\n",
       "      <td id=\"T_03216_row0_col6\" class=\"data row0 col6\" >0.91</td>\n",
       "      <td id=\"T_03216_row0_col7\" class=\"data row0 col7\" >0.80</td>\n",
       "      <td id=\"T_03216_row0_col8\" class=\"data row0 col8\" >0.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row1\" class=\"row_heading level0 row1\" >Daily correlation</th>\n",
       "      <td id=\"T_03216_row1_col0\" class=\"data row1 col0\" >23.4%</td>\n",
       "      <td id=\"T_03216_row1_col1\" class=\"data row1 col1\" >20.2%</td>\n",
       "      <td id=\"T_03216_row1_col2\" class=\"data row1 col2\" >62.8%</td>\n",
       "      <td id=\"T_03216_row1_col3\" class=\"data row1 col3\" >45.0%</td>\n",
       "      <td id=\"T_03216_row1_col4\" class=\"data row1 col4\" >62.3%</td>\n",
       "      <td id=\"T_03216_row1_col5\" class=\"data row1 col5\" >15.5%</td>\n",
       "      <td id=\"T_03216_row1_col6\" class=\"data row1 col6\" >32.8%</td>\n",
       "      <td id=\"T_03216_row1_col7\" class=\"data row1 col7\" >47.4%</td>\n",
       "      <td id=\"T_03216_row1_col8\" class=\"data row1 col8\" >-60.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row2\" class=\"row_heading level0 row2\" >Daily mean error</th>\n",
       "      <td id=\"T_03216_row2_col0\" class=\"data row2 col0\" >15.8%</td>\n",
       "      <td id=\"T_03216_row2_col1\" class=\"data row2 col1\" >18.4%</td>\n",
       "      <td id=\"T_03216_row2_col2\" class=\"data row2 col2\" >20.6%</td>\n",
       "      <td id=\"T_03216_row2_col3\" class=\"data row2 col3\" >22.2%</td>\n",
       "      <td id=\"T_03216_row2_col4\" class=\"data row2 col4\" >22.4%</td>\n",
       "      <td id=\"T_03216_row2_col5\" class=\"data row2 col5\" >23.3%</td>\n",
       "      <td id=\"T_03216_row2_col6\" class=\"data row2 col6\" >23.8%</td>\n",
       "      <td id=\"T_03216_row2_col7\" class=\"data row2 col7\" >27.9%</td>\n",
       "      <td id=\"T_03216_row2_col8\" class=\"data row2 col8\" >43.2%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row3\" class=\"row_heading level0 row3\" >Trend/legs correlation</th>\n",
       "      <td id=\"T_03216_row3_col0\" class=\"data row3 col0\" >53.7%</td>\n",
       "      <td id=\"T_03216_row3_col1\" class=\"data row3 col1\" >17.3%</td>\n",
       "      <td id=\"T_03216_row3_col2\" class=\"data row3 col2\" >77.1%</td>\n",
       "      <td id=\"T_03216_row3_col3\" class=\"data row3 col3\" >48.8%</td>\n",
       "      <td id=\"T_03216_row3_col4\" class=\"data row3 col4\" >76.7%</td>\n",
       "      <td id=\"T_03216_row3_col5\" class=\"data row3 col5\" >7.0%</td>\n",
       "      <td id=\"T_03216_row3_col6\" class=\"data row3 col6\" >51.5%</td>\n",
       "      <td id=\"T_03216_row3_col7\" class=\"data row3 col7\" >57.4%</td>\n",
       "      <td id=\"T_03216_row3_col8\" class=\"data row3 col8\" >-69.9%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row4\" class=\"row_heading level0 row4\" >Trend matching direction</th>\n",
       "      <td id=\"T_03216_row4_col0\" class=\"data row4 col0\" >60.5%</td>\n",
       "      <td id=\"T_03216_row4_col1\" class=\"data row4 col1\" >52.6%</td>\n",
       "      <td id=\"T_03216_row4_col2\" class=\"data row4 col2\" >71.1%</td>\n",
       "      <td id=\"T_03216_row4_col3\" class=\"data row4 col3\" >63.2%</td>\n",
       "      <td id=\"T_03216_row4_col4\" class=\"data row4 col4\" >71.1%</td>\n",
       "      <td id=\"T_03216_row4_col5\" class=\"data row4 col5\" >52.6%</td>\n",
       "      <td id=\"T_03216_row4_col6\" class=\"data row4 col6\" >71.1%</td>\n",
       "      <td id=\"T_03216_row4_col7\" class=\"data row4 col7\" >55.3%</td>\n",
       "      <td id=\"T_03216_row4_col8\" class=\"data row4 col8\" >21.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row5\" class=\"row_heading level0 row5\" >Brokers</th>\n",
       "      <td id=\"T_03216_row5_col0\" class=\"data row5 col0\" >KZ FS DP XA</td>\n",
       "      <td id=\"T_03216_row5_col1\" class=\"data row5 col1\" >AG AK NI HP BK</td>\n",
       "      <td id=\"T_03216_row5_col2\" class=\"data row5 col2\" >AG AI AK AO AZ BB BK BQ CP DH DP DR DX EP FS HP IF IN KZ LG MG OD PG PP PS RF RG RX TP XA YB YJ YU ZP</td>\n",
       "      <td id=\"T_03216_row5_col3\" class=\"data row5 col3\" >ZP KZ BK</td>\n",
       "      <td id=\"T_03216_row5_col4\" class=\"data row5 col4\" >ZP AK BB YU OD LG BK KZ RX TP YJ HP IF AZ MG DR EP CP</td>\n",
       "      <td id=\"T_03216_row5_col5\" class=\"data row5 col5\" >ZP AK PD YP BB YU OD CC LG BK NI KZ RX TP XC SQ YJ HP IF XL GR AZ MG DR KK EP CP</td>\n",
       "      <td id=\"T_03216_row5_col6\" class=\"data row5 col6\" ></td>\n",
       "      <td id=\"T_03216_row5_col7\" class=\"data row5 col7\" >ZP CC PD LG OD</td>\n",
       "      <td id=\"T_03216_row5_col8\" class=\"data row5 col8\" >CC GR KK NI PD SQ XC XL YP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_03216_level0_row6\" class=\"row_heading level0 row6\" >Calculated Rank</th>\n",
       "      <td id=\"T_03216_row6_col0\" class=\"data row6 col0\" >0</td>\n",
       "      <td id=\"T_03216_row6_col1\" class=\"data row6 col1\" >1</td>\n",
       "      <td id=\"T_03216_row6_col2\" class=\"data row6 col2\" >2</td>\n",
       "      <td id=\"T_03216_row6_col3\" class=\"data row6 col3\" >3</td>\n",
       "      <td id=\"T_03216_row6_col4\" class=\"data row6 col4\" >4</td>\n",
       "      <td id=\"T_03216_row6_col5\" class=\"data row6 col5\" >5</td>\n",
       "      <td id=\"T_03216_row6_col6\" class=\"data row6 col6\" >6</td>\n",
       "      <td id=\"T_03216_row6_col7\" class=\"data row6 col7\" >7</td>\n",
       "      <td id=\"T_03216_row6_col8\" class=\"data row6 col8\" >8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x771a2d2a5b20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "#### Auto Search"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_4d663_row3_col0, #T_4d663_row4_col0 {\n",
       "  background-color: lightgreen;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_4d663_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >Auto Search</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row0\" class=\"row_heading level0 row0\" >Daily cointegration p-value</th>\n",
       "      <td id=\"T_4d663_row0_col0\" class=\"data row0 col0\" >0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row1\" class=\"row_heading level0 row1\" >Daily correlation</th>\n",
       "      <td id=\"T_4d663_row1_col0\" class=\"data row1 col0\" >23.4%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row2\" class=\"row_heading level0 row2\" >Daily mean error</th>\n",
       "      <td id=\"T_4d663_row2_col0\" class=\"data row2 col0\" >15.8%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row3\" class=\"row_heading level0 row3\" >Trend/legs correlation</th>\n",
       "      <td id=\"T_4d663_row3_col0\" class=\"data row3 col0\" >53.7%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row4\" class=\"row_heading level0 row4\" >Trend matching direction</th>\n",
       "      <td id=\"T_4d663_row4_col0\" class=\"data row4 col0\" >60.5%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row5\" class=\"row_heading level0 row5\" >Brokers</th>\n",
       "      <td id=\"T_4d663_row5_col0\" class=\"data row5 col0\" >KZ FS DP XA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_4d663_level0_row6\" class=\"row_heading level0 row6\" >Calculated Rank</th>\n",
       "      <td id=\"T_4d663_row6_col0\" class=\"data row6 col0\" >0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x771a28eeb2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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