tej87681088/TEJAPI_Medium實戰應用12.ipynb

## TEJAPI_Medium實戰應用12.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "34122c25-426f-455a-a7c3-63ff6e5a85de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\anaconda3\\lib\\site-packages\\numpy\\_distributor_init.py:30: UserWarning: loaded more than 1 DLL from .libs:\n",
      "C:\\Users\\User\\anaconda3\\lib\\site-packages\\numpy\\.libs\\libopenblas.el2c6ple4zyw3eceviv3oxxgrn2nrfm2.gfortran-win_amd64.dll\n",
      "C:\\Users\\User\\anaconda3\\lib\\site-packages\\numpy\\.libs\\libopenblas.XWYDX2IKJW2NMTWSFYNGFUWKQU3LYTCZ.gfortran-win_amd64.dll\n",
      "  warnings.warn(\"loaded more than 1 DLL from .libs:\"\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import tejapi\n",
    "import matplotlib.pyplot as plt\n",
    "tejapi.ApiConfig.api_key = \"your key\"\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['Microsoft JhengHei'] # 解決 plot中文問題\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d39da8fb-305d-4a04-92fd-2f7cb903aeb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_return = tejapi.get('TWN/AAPRCM1',\n",
    "                         coid = '0050',\n",
    "                         mdate= {'gte': '2010-01-01','lte':'2015-12-31'},\n",
    "                         opts={'columns':['coid','mdate','roi']},\n",
    "                         chinese_column_name=True,paginate=True)\n",
    "\n",
    "data_return['勝率'] = np.where(data_return['報酬率％_月'] >= 0 ,1,0)\n",
    "data_return['勝率'] = data_return.rolling(12)['勝率'].sum() / 12\n",
    "\n",
    "data_return['獲利'] = np.where(data_return['報酬率％_月'] >= 0 ,data_return['報酬率％_月'],np.nan)\n",
    "data_return['虧損'] = np.where(data_return['報酬率％_月'] < 0 ,data_return['報酬率％_月'],np.nan)\n",
    "\n",
    "data_return['賠率'] = data_return.rolling(12, min_periods=1)['獲利'].mean() \\\n",
    "    / data_return.rolling(12, min_periods=1)['虧損'].mean().abs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "58c0bf7b-7b18-43f7-bf23-d1f5455dd4bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_return['下注比例'] = \\\n",
    "    np.where(data_return['勝率'] * data_return['賠率'] - (1 - data_return['勝率']) < 0,0,\n",
    "             (data_return['勝率'] * data_return['賠率'] - (1 - data_return['勝率'])) / data_return['賠率']\n",
    "             )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "611c9735-9ac8-4e4b-bb6d-9822cc704816",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>證券代碼</th>\n",
       "      <th>年月</th>\n",
       "      <th>報酬率％_月</th>\n",
       "      <th>勝率</th>\n",
       "      <th>獲利</th>\n",
       "      <th>虧損</th>\n",
       "      <th>賠率</th>\n",
       "      <th>下注比例</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0050</td>\n",
       "      <td>2010-12-01 00:00:00+00:00</td>\n",
       "      <td>7.5308</td>\n",
       "      <td>0.583333</td>\n",
       "      <td>7.5308</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>0050</td>\n",
       "      <td>2011-01-01 00:00:00+00:00</td>\n",
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       "      <td>1.340156</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-02-01 00:00:00+00:00</td>\n",
       "      <td>-5.5555</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.5555</td>\n",
       "      <td>1.108934</td>\n",
       "      <td>0.417939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-03-01 00:00:00+00:00</td>\n",
       "      <td>0.0842</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.0842</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.951266</td>\n",
       "      <td>0.366078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-04-01 00:00:00+00:00</td>\n",
       "      <td>4.1141</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>4.1141</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.046112</td>\n",
       "      <td>0.316257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-05-01 00:00:00+00:00</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.0001</td>\n",
       "      <td>2.201370</td>\n",
       "      <td>0.348026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-06-01 00:00:00+00:00</td>\n",
       "      <td>-5.0807</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.0807</td>\n",
       "      <td>1.455108</td>\n",
       "      <td>0.515246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-07-01 00:00:00+00:00</td>\n",
       "      <td>1.7844</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>1.7844</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.157456</td>\n",
       "      <td>0.437589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-08-01 00:00:00+00:00</td>\n",
       "      <td>-8.9315</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-8.9315</td>\n",
       "      <td>0.694984</td>\n",
       "      <td>0.378679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-09-01 00:00:00+00:00</td>\n",
       "      <td>-5.3164</td>\n",
       "      <td>0.583333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.3164</td>\n",
       "      <td>0.543759</td>\n",
       "      <td>0.187039</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   證券代碼                        年月  報酬率％_月        勝率      獲利      虧損        賠率  \\\n",
       "0  0050 2010-12-01 00:00:00+00:00  7.5308  0.583333  7.5308     NaN  1.223815   \n",
       "1  0050 2011-01-01 00:00:00+00:00  2.6058  0.666667  2.6058     NaN  1.340156   \n",
       "2  0050 2011-02-01 00:00:00+00:00 -5.5555  0.666667     NaN -5.5555  1.108934   \n",
       "3  0050 2011-03-01 00:00:00+00:00  0.0842  0.666667  0.0842     NaN  0.951266   \n",
       "4  0050 2011-04-01 00:00:00+00:00  4.1141  0.666667  4.1141     NaN  1.046112   \n",
       "5  0050 2011-05-01 00:00:00+00:00 -0.0001  0.666667     NaN -0.0001  2.201370   \n",
       "6  0050 2011-06-01 00:00:00+00:00 -5.0807  0.666667     NaN -5.0807  1.455108   \n",
       "7  0050 2011-07-01 00:00:00+00:00  1.7844  0.666667  1.7844     NaN  1.157456   \n",
       "8  0050 2011-08-01 00:00:00+00:00 -8.9315  0.666667     NaN -8.9315  0.694984   \n",
       "9  0050 2011-09-01 00:00:00+00:00 -5.3164  0.583333     NaN -5.3164  0.543759   \n",
       "\n",
       "       下注比例  \n",
       "0       NaN  \n",
       "1  0.242868  \n",
       "2  0.417939  \n",
       "3  0.366078  \n",
       "4  0.316257  \n",
       "5  0.348026  \n",
       "6  0.515246  \n",
       "7  0.437589  \n",
       "8  0.378679  \n",
       "9  0.187039  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_return['下注比例'] = data_return['下注比例'].shift() # 前一個月的下注比例\n",
    "data_return = data_return.dropna(subset=['勝率']).reset_index(drop=True)\n",
    "\n",
    "data_return.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ea6dc663-ef78-42c5-8892-40e12f22519b",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_return['報酬率％_月'] = data_return['報酬率％_月'] * 0.01\n",
    "\n",
    "\n",
    "data_return['累積報酬率％_月'] = 1 + data_return['報酬率％_月']\n",
    "data_return['累積報酬率％_月'] = data_return['累積報酬率％_月'].cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "34ac7d66-1581-4696-af92-8d61e78b482f",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(0,len(data_return)):\n",
    "    if i == 0:\n",
    "        data_return['buy & hold本金'] = 1000000 # 起始本金\n",
    "    else:\n",
    "        data_return.loc[i,'buy & hold本金'] = 1000000 * data_return.loc[i-1,'累積報酬率％_月']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4698472d-7196-474e-b93d-a065626aee00",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>證券代碼</th>\n",
       "      <th>年月</th>\n",
       "      <th>報酬率％_月</th>\n",
       "      <th>勝率</th>\n",
       "      <th>獲利</th>\n",
       "      <th>虧損</th>\n",
       "      <th>賠率</th>\n",
       "      <th>下注比例</th>\n",
       "      <th>累積報酬率％_月</th>\n",
       "      <th>buy &amp; hold本金</th>\n",
       "      <th>凱利本金</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0050</td>\n",
       "      <td>2010-12-01 00:00:00+00:00</td>\n",
       "      <td>0.075308</td>\n",
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       "      <th>1</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-01-01 00:00:00+00:00</td>\n",
       "      <td>0.026058</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>2.6058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.340156</td>\n",
       "      <td>0.242868</td>\n",
       "      <td>1.103328</td>\n",
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       "      <td>1.006329e+06</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-02-01 00:00:00+00:00</td>\n",
       "      <td>-0.055555</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-5.5555</td>\n",
       "      <td>1.108934</td>\n",
       "      <td>0.417939</td>\n",
       "      <td>1.042033</td>\n",
       "      <td>1.103328e+06</td>\n",
       "      <td>9.829631e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-03-01 00:00:00+00:00</td>\n",
       "      <td>0.000842</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.0842</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.951266</td>\n",
       "      <td>0.366078</td>\n",
       "      <td>1.042910</td>\n",
       "      <td>1.042033e+06</td>\n",
       "      <td>9.832661e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0050</td>\n",
       "      <td>2011-04-01 00:00:00+00:00</td>\n",
       "      <td>0.041141</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>4.1141</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.046112</td>\n",
       "      <td>0.316257</td>\n",
       "      <td>1.085817</td>\n",
       "      <td>1.042910e+06</td>\n",
       "      <td>9.960595e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   證券代碼                        年月    報酬率％_月        勝率      獲利      虧損  \\\n",
       "0  0050 2010-12-01 00:00:00+00:00  0.075308  0.583333  7.5308     NaN   \n",
       "1  0050 2011-01-01 00:00:00+00:00  0.026058  0.666667  2.6058     NaN   \n",
       "2  0050 2011-02-01 00:00:00+00:00 -0.055555  0.666667     NaN -5.5555   \n",
       "3  0050 2011-03-01 00:00:00+00:00  0.000842  0.666667  0.0842     NaN   \n",
       "4  0050 2011-04-01 00:00:00+00:00  0.041141  0.666667  4.1141     NaN   \n",
       "\n",
       "         賠率      下注比例  累積報酬率％_月  buy & hold本金          凱利本金  \n",
       "0  1.223815       NaN  1.075308  1.000000e+06  1.000000e+06  \n",
       "1  1.340156  0.242868  1.103328  1.075308e+06  1.006329e+06  \n",
       "2  1.108934  0.417939  1.042033  1.103328e+06  9.829631e+05  \n",
       "3  0.951266  0.366078  1.042910  1.042033e+06  9.832661e+05  \n",
       "4  1.046112  0.316257  1.085817  1.042910e+06  9.960595e+05  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in range(0,len(data_return)):\n",
    "    if i == 0:\n",
    "        data_return['凱利本金'] = 1000000 # 起始本金\n",
    "    else:\n",
    "        if data_return.loc[i,'下注比例'] > 0:\n",
    "            data_return.loc[i,'凱利本金'] = data_return.loc[i-1,'凱利本金'] * (1 - data_return.loc[i,'下注比例']) \\\n",
    "                + data_return.loc[i-1,'凱利本金'] * data_return.loc[i,'下注比例'] * (1 + data_return.loc[i,'報酬率％_月']) \n",
    "        else:\n",
    "            data_return.loc[i,'凱利本金'] = data_return.loc[i-1,'凱利本金']\n",
    "            \n",
    "data_return.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9a21aef3-34bb-45b4-9c5c-ac495ff6092a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_return = data_return.set_index('年月')\n",
    "\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1,figsize=(20,10), gridspec_kw={'height_ratios': [2,1]})\n",
    "   \n",
    "ax1.set_title('凱利公式', fontsize=17, fontweight='bold')\n",
    "ax1.plot(data_return['凱利本金'], linewidth=2, alpha=1)\n",
    "ax1.plot(data_return['buy & hold本金'], linewidth=2, alpha=1)\n",
    "ax1.set_ylabel('本金(元)', fontsize=12,rotation=0)\n",
    "ax1.grid(axis='y')\n",
    "fig.legend(['凱利本金','buy & hold本金'], prop={'size': 12})\n",
    "\n",
    "ax2.plot(data_return['凱利本金'] - data_return['凱利本金'].cummax(),linewidth=2, alpha=1, color='r')\n",
    "ax2.fill_between(data_return.index, 0 ,\n",
    "                 data_return['凱利本金'] - data_return['凱利本金'].cummax(),\n",
    "                 facecolor='r', alpha=0.1)\n",
    "ax2.set_title(\"最大回撤\", fontsize=17, fontweight='bold')\n",
    "ax2.set_ylabel('本金(元)', fontsize=12,rotation=0)\n",
    "ax2.grid(axis='y')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
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