{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "name": "#%%\n",
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "from linearmodels import PanelOLS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "         code       date  code_return       mkt  ten_return       smg  \\\n0           1 2010-01-05      -0.0173  0.006584     -0.0062  0.005921   \n1        2142 2010-01-05       0.0024  0.006584     -0.0062  0.005921   \n2      600000 2010-01-05       0.0076  0.006584     -0.0062  0.005921   \n3      600015 2010-01-05       0.0252  0.006584     -0.0062  0.005921   \n4      600016 2010-01-05       0.0177  0.006584     -0.0062  0.005921   \n...       ...        ...          ...       ...         ...       ...   \n46006  601398 2021-12-31      -0.0022  0.005888     -0.0086 -0.004844   \n46007  601818 2021-12-31       0.0000  0.005888     -0.0086 -0.004844   \n46008  601939 2021-12-31      -0.0017  0.005888     -0.0086 -0.004844   \n46009  601988 2021-12-31       0.0000  0.005888     -0.0086 -0.004844   \n46010  601998 2021-12-31       0.0022  0.005888     -0.0086 -0.004844   \n\n            hml       umd       rmw       cma  \n0     -0.002548 -0.001689  0.001728  0.000770  \n1     -0.002548 -0.001689  0.001728  0.000770  \n2     -0.002548 -0.001689  0.001728  0.000770  \n3     -0.002548 -0.001689  0.001728  0.000770  \n4     -0.002548 -0.001689  0.001728  0.000770  \n...         ...       ...       ...       ...  \n46006  0.003232  0.002873 -0.004371  0.004678  \n46007  0.003232  0.002873 -0.004371  0.004678  \n46008  0.003232  0.002873 -0.004371  0.004678  \n46009  0.003232  0.002873 -0.004371  0.004678  \n46010  0.003232  0.002873 -0.004371  0.004678  \n\n[46011 rows x 10 columns]",
      "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>code</th>\n      <th>date</th>\n      <th>code_return</th>\n      <th>mkt</th>\n      <th>ten_return</th>\n      <th>smg</th>\n      <th>hml</th>\n      <th>umd</th>\n      <th>rmw</th>\n      <th>cma</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1</td>\n      <td>2010-01-05</td>\n      <td>-0.0173</td>\n      <td>0.006584</td>\n      <td>-0.0062</td>\n      <td>0.005921</td>\n      <td>-0.002548</td>\n      <td>-0.001689</td>\n      <td>0.001728</td>\n      <td>0.000770</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2142</td>\n      <td>2010-01-05</td>\n      <td>0.0024</td>\n      <td>0.006584</td>\n      <td>-0.0062</td>\n      <td>0.005921</td>\n      <td>-0.002548</td>\n      <td>-0.001689</td>\n      <td>0.001728</td>\n      <td>0.000770</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>600000</td>\n      <td>2010-01-05</td>\n      <td>0.0076</td>\n      <td>0.006584</td>\n      <td>-0.0062</td>\n      <td>0.005921</td>\n      <td>-0.002548</td>\n      <td>-0.001689</td>\n      <td>0.001728</td>\n      <td>0.000770</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>600015</td>\n      <td>2010-01-05</td>\n      <td>0.0252</td>\n      <td>0.006584</td>\n      <td>-0.0062</td>\n      <td>0.005921</td>\n      <td>-0.002548</td>\n      <td>-0.001689</td>\n      <td>0.001728</td>\n      <td>0.000770</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>600016</td>\n      <td>2010-01-05</td>\n      <td>0.0177</td>\n      <td>0.006584</td>\n      <td>-0.0062</td>\n      <td>0.005921</td>\n      <td>-0.002548</td>\n      <td>-0.001689</td>\n      <td>0.001728</td>\n      <td>0.000770</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    </tr>\n    <tr>\n      <th>46006</th>\n      <td>601398</td>\n      <td>2021-12-31</td>\n      <td>-0.0022</td>\n      <td>0.005888</td>\n      <td>-0.0086</td>\n      <td>-0.004844</td>\n      <td>0.003232</td>\n      <td>0.002873</td>\n      <td>-0.004371</td>\n      <td>0.004678</td>\n    </tr>\n    <tr>\n      <th>46007</th>\n      <td>601818</td>\n      <td>2021-12-31</td>\n      <td>0.0000</td>\n      <td>0.005888</td>\n      <td>-0.0086</td>\n      <td>-0.004844</td>\n      <td>0.003232</td>\n      <td>0.002873</td>\n      <td>-0.004371</td>\n      <td>0.004678</td>\n    </tr>\n    <tr>\n      <th>46008</th>\n      <td>601939</td>\n      <td>2021-12-31</td>\n      <td>-0.0017</td>\n      <td>0.005888</td>\n      <td>-0.0086</td>\n      <td>-0.004844</td>\n      <td>0.003232</td>\n      <td>0.002873</td>\n      <td>-0.004371</td>\n      <td>0.004678</td>\n    </tr>\n    <tr>\n      <th>46009</th>\n      <td>601988</td>\n      <td>2021-12-31</td>\n      <td>0.0000</td>\n      <td>0.005888</td>\n      <td>-0.0086</td>\n      <td>-0.004844</td>\n      <td>0.003232</td>\n      <td>0.002873</td>\n      <td>-0.004371</td>\n      <td>0.004678</td>\n    </tr>\n    <tr>\n      <th>46010</th>\n      <td>601998</td>\n      <td>2021-12-31</td>\n      <td>0.0022</td>\n      <td>0.005888</td>\n      <td>-0.0086</td>\n      <td>-0.004844</td>\n      <td>0.003232</td>\n      <td>0.002873</td>\n      <td>-0.004371</td>\n      <td>0.004678</td>\n    </tr>\n  </tbody>\n</table>\n<p>46011 rows × 10 columns</p>\n</div>"
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data.csv',  usecols=range(10))\n",
    "data['date'] = pd.to_datetime(data['date'], format='%Y-%m-%d %H:%M:%S')\n",
    "data.columns=['code','date','code_return','mkt','ten_return','smg','hml','umd','rmw','cma']\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[     1   2142 600000 600015 600016 600036 601009 601166 601169 601288\n",
      " 601328 601398 601818 601939 601988 601998]\n"
     ]
    },
    {
     "data": {
      "text/plain": "{'2010':         code       date  code_return       mkt  ten_return       smg  \\\n 0          1 2010-01-05      -0.0173  0.006584     -0.0062  0.005921   \n 1       2142 2010-01-05       0.0024  0.006584     -0.0062  0.005921   \n 2     600000 2010-01-05       0.0076  0.006584     -0.0062  0.005921   \n 3     600015 2010-01-05       0.0252  0.006584     -0.0062  0.005921   \n 4     600016 2010-01-05       0.0177  0.006584     -0.0062  0.005921   \n ...      ...        ...          ...       ...         ...       ...   \n 3423  601398 2010-12-31       0.0000  0.021355      0.2259 -0.001975   \n 3424  601818 2010-12-31       0.0128  0.021355      0.2259 -0.001975   \n 3425  601939 2010-12-31       0.0066  0.021355      0.2259 -0.001975   \n 3426  601988 2010-12-31       0.0031  0.021355      0.2259 -0.001975   \n 3427  601998 2010-12-31       0.0096  0.021355      0.2259 -0.001975   \n \n            hml       umd       rmw      cma  \n 0    -0.002548 -0.001689  0.001728  0.00077  \n 1    -0.002548 -0.001689  0.001728  0.00077  \n 2    -0.002548 -0.001689  0.001728  0.00077  \n 3    -0.002548 -0.001689  0.001728  0.00077  \n 4    -0.002548 -0.001689  0.001728  0.00077  \n ...        ...       ...       ...      ...  \n 3423 -0.006747  0.012053 -0.002152  0.00191  \n 3424 -0.006747  0.012053 -0.002152  0.00191  \n 3425 -0.006747  0.012053 -0.002152  0.00191  \n 3426 -0.006747  0.012053 -0.002152  0.00191  \n 3427 -0.006747  0.012053 -0.002152  0.00191  \n \n [3428 rows x 10 columns],\n '2011':         code       date  code_return       mkt  ten_return       smg  \\\n 3428       1 2011-01-04       0.0146  0.017028      0.3170  0.000556   \n 3429    2142 2011-01-04       0.0282  0.017028      0.3170  0.000556   \n 3430  600000 2011-01-04       0.0178  0.017028      0.3170  0.000556   \n 3431  600015 2011-01-04       0.0211  0.017028      0.3170  0.000556   \n 3432  600016 2011-01-04       0.0100  0.017028      0.3170  0.000556   \n ...      ...        ...          ...       ...         ...       ...   \n 7276  601398 2011-12-30       0.0095  0.013180      0.1924  0.001986   \n 7277  601818 2011-12-30       0.0213  0.013180      0.1924  0.001986   \n 7278  601939 2011-12-30       0.0067  0.013180      0.1924  0.001986   \n 7279  601988 2011-12-30       0.0034  0.013180      0.1924  0.001986   \n 7280  601998 2011-12-30       0.0151  0.013180      0.1924  0.001986   \n \n            hml       umd       rmw       cma  \n 3428  0.003693 -0.003027 -0.004089 -0.000740  \n 3429  0.003693 -0.003027 -0.004089 -0.000740  \n 3430  0.003693 -0.003027 -0.004089 -0.000740  \n 3431  0.003693 -0.003027 -0.004089 -0.000740  \n 3432  0.003693 -0.003027 -0.004089 -0.000740  \n ...        ...       ...       ...       ...  \n 7276 -0.007290 -0.006930 -0.004865 -0.004061  \n 7277 -0.007290 -0.006930 -0.004865 -0.004061  \n 7278 -0.007290 -0.006930 -0.004865 -0.004061  \n 7279 -0.007290 -0.006930 -0.004865 -0.004061  \n 7280 -0.007290 -0.006930 -0.004865 -0.004061  \n \n [3853 rows x 10 columns],\n '2012':          code       date  code_return       mkt  ten_return       smg  \\\n 7281        1 2012-01-04      -0.0276 -0.018629     -0.0459 -0.002342   \n 7282     2142 2012-01-04      -0.0273 -0.018629     -0.0459 -0.002342   \n 7283   600000 2012-01-04      -0.0094 -0.018629     -0.0459 -0.002342   \n 7284   600015 2012-01-04      -0.0098 -0.018629     -0.0459 -0.002342   \n 7285   600016 2012-01-04      -0.0051 -0.018629     -0.0459 -0.002342   \n ...       ...        ...          ...       ...         ...       ...   \n 11118  601398 2012-12-31       0.0122  0.011597      0.0155 -0.004285   \n 11119  601818 2012-12-31       0.0235  0.011597      0.0155 -0.004285   \n 11120  601939 2012-12-31       0.0155  0.011597      0.0155 -0.004285   \n 11121  601988 2012-12-31       0.0104  0.011597      0.0155 -0.004285   \n 11122  601998 2012-12-31       0.0239  0.011597      0.0155 -0.004285   \n \n             hml       umd       rmw       cma  \n 7281   0.010385  0.010148  0.007820  0.005923  \n 7282   0.010385  0.010148  0.007820  0.005923  \n 7283   0.010385  0.010148  0.007820  0.005923  \n 7284   0.010385  0.010148  0.007820  0.005923  \n 7285   0.010385  0.010148  0.007820  0.005923  \n ...         ...       ...       ...       ...  \n 11118  0.001947  0.001989  0.001233 -0.003117  \n 11119  0.001947  0.001989  0.001233 -0.003117  \n 11120  0.001947  0.001989  0.001233 -0.003117  \n 11121  0.001947  0.001989  0.001233 -0.003117  \n 11122  0.001947  0.001989  0.001233 -0.003117  \n \n [3842 rows x 10 columns],\n '2013':          code       date  code_return       mkt  ten_return       smg  \\\n 11123       1 2013-01-04      -0.0019 -0.002649     -0.1471 -0.000036   \n 11124    2142 2013-01-04      -0.0103 -0.002649     -0.1471 -0.000036   \n 11125  600000 2013-01-04       0.0101 -0.002649     -0.1471 -0.000036   \n 11126  600015 2013-01-04      -0.0019 -0.002649     -0.1471 -0.000036   \n 11127  600016 2013-01-04       0.0153 -0.002649     -0.1471 -0.000036   \n ...       ...        ...          ...       ...         ...       ...   \n 14919  601398 2013-12-31       0.0085  0.005728      0.0551 -0.009074   \n 14920  601818 2013-12-31       0.0114  0.005728      0.0551 -0.009074   \n 14921  601939 2013-12-31       0.0122  0.005728      0.0551 -0.009074   \n 14922  601988 2013-12-31       0.0038  0.005728      0.0551 -0.009074   \n 14923  601998 2013-12-31       0.0238  0.005728      0.0551 -0.009074   \n \n             hml       umd       rmw       cma  \n 11123  0.010271 -0.004640 -0.001565  0.003320  \n 11124  0.010271 -0.004640 -0.001565  0.003320  \n 11125  0.010271 -0.004640 -0.001565  0.003320  \n 11126  0.010271 -0.004640 -0.001565  0.003320  \n 11127  0.010271 -0.004640 -0.001565  0.003320  \n ...         ...       ...       ...       ...  \n 14919 -0.002442 -0.006581  0.005080 -0.005503  \n 14920 -0.002442 -0.006581  0.005080 -0.005503  \n 14921 -0.002442 -0.006581  0.005080 -0.005503  \n 14922 -0.002442 -0.006581  0.005080 -0.005503  \n 14923 -0.002442 -0.006581  0.005080 -0.005503  \n \n [3801 rows x 10 columns],\n '2014':          code       date  code_return       mkt  ten_return       smg  \\\n 14924       1 2014-01-02      -0.0016  0.002230     -0.0918  0.010387   \n 14925    2142 2014-01-02      -0.0108  0.002230     -0.0918  0.010387   \n 14926  600000 2014-01-02      -0.0106  0.002230     -0.0918  0.010387   \n 14927  600015 2014-01-02      -0.0315  0.002230     -0.0918  0.010387   \n 14928  600016 2014-01-02       0.0013  0.002230     -0.0918  0.010387   \n ...       ...        ...          ...       ...         ...       ...   \n 18834  601398 2014-12-31       0.0340  0.018676     -0.1972 -0.009086   \n 18835  601818 2014-12-31       0.0083  0.018676     -0.1972 -0.009086   \n 18836  601939 2014-12-31       0.0244  0.018676     -0.1972 -0.009086   \n 18837  601988 2014-12-31       0.0533  0.018676     -0.1972 -0.009086   \n 18838  601998 2014-12-31       0.0162  0.018676     -0.1972 -0.009086   \n \n             hml       umd       rmw       cma  \n 14924 -0.006336  0.013168 -0.008146 -0.003061  \n 14925 -0.006336  0.013168 -0.008146 -0.003061  \n 14926 -0.006336  0.013168 -0.008146 -0.003061  \n 14927 -0.006336  0.013168 -0.008146 -0.003061  \n 14928 -0.006336  0.013168 -0.008146 -0.003061  \n ...         ...       ...       ...       ...  \n 18834  0.007772 -0.004115  0.012705 -0.005498  \n 18835  0.007772 -0.004115  0.012705 -0.005498  \n 18836  0.007772 -0.004115  0.012705 -0.005498  \n 18837  0.007772 -0.004115  0.012705 -0.005498  \n 18838  0.007772 -0.004115  0.012705 -0.005498  \n \n [3915 rows x 10 columns],\n '2015':          code       date  code_return       mkt  ten_return       smg  \\\n 18839       1 2015-01-05       0.0114  0.039612      0.2365 -0.029235   \n 18840    2142 2015-01-05      -0.0013  0.039612      0.2365 -0.029235   \n 18841  600000 2015-01-05       0.0242  0.039612      0.2365 -0.029235   \n 18842  600015 2015-01-05       0.0059  0.039612      0.2365 -0.029235   \n 18843  600016 2015-01-05      -0.0092  0.039612      0.2365 -0.029235   \n ...       ...        ...          ...       ...         ...       ...   \n 22671  601398 2015-12-31      -0.0065 -0.013746      0.1485 -0.004086   \n 22672  601818 2015-12-31      -0.0047 -0.013746      0.1485 -0.004086   \n 22673  601939 2015-12-31      -0.0017 -0.013746      0.1485 -0.004086   \n 22674  601988 2015-12-31      -0.0050 -0.013746      0.1485 -0.004086   \n 22675  601998 2015-12-31      -0.0137 -0.013746      0.1485 -0.004086   \n \n             hml       umd       rmw       cma  \n 18839  0.029515  0.014860  0.029674  0.001048  \n 18840  0.029515  0.014860  0.029674  0.001048  \n 18841  0.029515  0.014860  0.029674  0.001048  \n 18842  0.029515  0.014860  0.029674  0.001048  \n 18843  0.029515  0.014860  0.029674  0.001048  \n ...         ...       ...       ...       ...  \n 22671  0.002671 -0.009198  0.007788  0.002567  \n 22672  0.002671 -0.009198  0.007788  0.002567  \n 22673  0.002671 -0.009198  0.007788  0.002567  \n 22674  0.002671 -0.009198  0.007788  0.002567  \n 22675  0.002671 -0.009198  0.007788  0.002567  \n \n [3837 rows x 10 columns],\n '2016':          code       date  code_return       mkt  ten_return       smg  \\\n 22676       1 2016-01-04      -0.0550 -0.082439     -0.1033 -0.010223   \n 22677    2142 2016-01-04      -0.0722 -0.082439     -0.1033 -0.010223   \n 22678  600000 2016-01-04      -0.0257 -0.082439     -0.1033 -0.010223   \n 22679  600015 2016-01-04      -0.0585 -0.082439     -0.1033 -0.010223   \n 22680  600016 2016-01-04      -0.0633 -0.082439     -0.1033 -0.010223   \n ...       ...        ...          ...       ...         ...       ...   \n 26550  601398 2016-12-30       0.0068  0.001458      0.4018 -0.002856   \n 26551  601818 2016-12-30       0.0051  0.001458      0.4018 -0.002856   \n 26552  601939 2016-12-30       0.0018  0.001458      0.4018 -0.002856   \n 26553  601988 2016-12-30       0.0058  0.001458      0.4018 -0.002856   \n 26554  601998 2016-12-30       0.0079  0.001458      0.4018 -0.002856   \n \n             hml       umd       rmw       cma  \n 22676  0.004140 -0.017415  0.015976  0.015416  \n 22677  0.004140 -0.017415  0.015976  0.015416  \n 22678  0.004140 -0.017415  0.015976  0.015416  \n 22679  0.004140 -0.017415  0.015976  0.015416  \n 22680  0.004140 -0.017415  0.015976  0.015416  \n ...         ...       ...       ...       ...  \n 26550  0.000766  0.002952  0.005182 -0.003431  \n 26551  0.000766  0.002952  0.005182 -0.003431  \n 26552  0.000766  0.002952  0.005182 -0.003431  \n 26553  0.000766  0.002952  0.005182 -0.003431  \n 26554  0.000766  0.002952  0.005182 -0.003431  \n \n [3879 rows x 10 columns],\n '2017':          code       date  code_return       mkt  ten_return       smg  \\\n 26555       1 2017-01-03       0.0066  0.009260     -0.1594  0.003536   \n 26556    2142 2017-01-03       0.0457  0.009260     -0.1594  0.003536   \n 26557  600000 2017-01-03       0.0056  0.009260     -0.1594  0.003536   \n 26558  600015 2017-01-03       0.0267  0.009260     -0.1594  0.003536   \n 26559  600016 2017-01-03       0.0033  0.009260     -0.1594  0.003536   \n ...       ...        ...          ...       ...         ...       ...   \n 30444  601398 2017-12-29       0.0098  0.005047      0.0149  0.004887   \n 30445  601818 2017-12-29       0.0000  0.005047      0.0149  0.004887   \n 30446  601939 2017-12-29       0.0172  0.005047      0.0149  0.004887   \n 30447  601988 2017-12-29       0.0102  0.005047      0.0149  0.004887   \n 30448  601998 2017-12-29       0.0032  0.005047      0.0149  0.004887   \n \n             hml       umd       rmw       cma  \n 26555  0.003988  0.000802 -0.005529  0.003971  \n 26556  0.003988  0.000802 -0.005529  0.003971  \n 26557  0.003988  0.000802 -0.005529  0.003971  \n 26558  0.003988  0.000802 -0.005529  0.003971  \n 26559  0.003988  0.000802 -0.005529  0.003971  \n ...         ...       ...       ...       ...  \n 30444 -0.003170 -0.005223 -0.002752 -0.000086  \n 30445 -0.003170 -0.005223 -0.002752 -0.000086  \n 30446 -0.003170 -0.005223 -0.002752 -0.000086  \n 30447 -0.003170 -0.005223 -0.002752 -0.000086  \n 30448 -0.003170 -0.005223 -0.002752 -0.000086  \n \n [3894 rows x 10 columns],\n '2018':          code       date  code_return       mkt  ten_return       smg  \\\n 30449       1 2018-01-02       0.0301  0.014167      0.0403 -0.001160   \n 30450    2142 2018-01-02       0.0387  0.014167      0.0403 -0.001160   \n 30451  600000 2018-01-02       0.0103  0.014167      0.0403 -0.001160   \n 30452  600015 2018-01-02       0.0122  0.014167      0.0403 -0.001160   \n 30453  600016 2018-01-02       0.0155  0.014167      0.0403 -0.001160   \n ...       ...        ...          ...       ...         ...       ...   \n 34332  601398 2018-12-28       0.0019  0.003514      0.1253 -0.004391   \n 34333  601818 2018-12-28       0.0137  0.003514      0.1253 -0.004391   \n 34334  601939 2018-12-28       0.0127  0.003514      0.1253 -0.004391   \n 34335  601988 2018-12-28      -0.0055  0.003514      0.1253 -0.004391   \n 34336  601998 2018-12-28       0.0149  0.003514      0.1253 -0.004391   \n \n             hml       umd       rmw       cma  \n 30449  0.011184  0.006522  0.007271  0.005406  \n 30450  0.011184  0.006522  0.007271  0.005406  \n 30451  0.011184  0.006522  0.007271  0.005406  \n 30452  0.011184  0.006522  0.007271  0.005406  \n 30453  0.011184  0.006522  0.007271  0.005406  \n ...         ...       ...       ...       ...  \n 34332 -0.000968  0.006954  0.002116  0.000542  \n 34333 -0.000968  0.006954  0.002116  0.000542  \n 34334 -0.000968  0.006954  0.002116  0.000542  \n 34335 -0.000968  0.006954  0.002116  0.000542  \n 34336 -0.000968  0.006954  0.002116  0.000542  \n \n [3888 rows x 10 columns],\n '2019':          code       date  code_return       mkt  ten_return       smg  \\\n 34337       1 2019-01-02      -0.0203 -0.009177      0.3417  0.012049   \n 34338    2142 2019-01-02      -0.0142 -0.009177      0.3417  0.012049   \n 34339  600000 2019-01-02      -0.0102 -0.009177      0.3417  0.012049   \n 34340  600015 2019-01-02      -0.0108 -0.009177      0.3417  0.012049   \n 34341  600016 2019-01-02      -0.0140 -0.009177      0.3417  0.012049   \n ...       ...        ...          ...       ...         ...       ...   \n 38236  601398 2019-12-31      -0.0017  0.006101      0.0911 -0.000255   \n 38237  601818 2019-12-31       0.0046  0.006101      0.0911 -0.000255   \n 38238  601939 2019-12-31       0.0000  0.006101      0.0911 -0.000255   \n 38239  601988 2019-12-31      -0.0054  0.006101      0.0911 -0.000255   \n 38240  601998 2019-12-31       0.0000  0.006101      0.0911 -0.000255   \n \n             hml       umd       rmw       cma  \n 34337  0.000279 -0.002372 -0.012153  0.006228  \n 34338  0.000279 -0.002372 -0.012153  0.006228  \n 34339  0.000279 -0.002372 -0.012153  0.006228  \n 34340  0.000279 -0.002372 -0.012153  0.006228  \n 34341  0.000279 -0.002372 -0.012153  0.006228  \n ...         ...       ...       ...       ...  \n 38236  0.000730  0.001421  0.000284 -0.002076  \n 38237  0.000730  0.001421  0.000284 -0.002076  \n 38238  0.000730  0.001421  0.000284 -0.002076  \n 38239  0.000730  0.001421  0.000284 -0.002076  \n 38240  0.000730  0.001421  0.000284 -0.002076  \n \n [3904 rows x 10 columns],\n '2020':          code       date  code_return       mkt  ten_return       smg  \\\n 38241       1 2020-01-02       0.0255  0.014510     -0.0003  0.005617   \n 38242    2142 2020-01-02       0.0337  0.014510     -0.0003  0.005617   \n 38243  600000 2020-01-02       0.0081  0.014510     -0.0003  0.005617   \n 38244  600015 2020-01-02       0.0039  0.014510     -0.0003  0.005617   \n 38245  600016 2020-01-02       0.0079  0.014510     -0.0003  0.005617   \n ...       ...        ...          ...       ...         ...       ...   \n 42124  601398 2020-12-31       0.0060  0.015867     -0.0748 -0.003778   \n 42125  601818 2020-12-31       0.0101  0.015867     -0.0748 -0.003778   \n 42126  601939 2020-12-31       0.0096  0.015867     -0.0748 -0.003778   \n 42127  601988 2020-12-31       0.0032  0.015867     -0.0748 -0.003778   \n 42128  601998 2020-12-31       0.0059  0.015867     -0.0748 -0.003778   \n \n             hml      umd       rmw       cma  \n 38241  0.002060 -0.00219 -0.006972  0.007840  \n 38242  0.002060 -0.00219 -0.006972  0.007840  \n 38243  0.002060 -0.00219 -0.006972  0.007840  \n 38244  0.002060 -0.00219 -0.006972  0.007840  \n 38245  0.002060 -0.00219 -0.006972  0.007840  \n ...         ...      ...       ...       ...  \n 42124 -0.007969  0.01043  0.001471 -0.008525  \n 42125 -0.007969  0.01043  0.001471 -0.008525  \n 42126 -0.007969  0.01043  0.001471 -0.008525  \n 42127 -0.007969  0.01043  0.001471 -0.008525  \n 42128 -0.007969  0.01043  0.001471 -0.008525  \n \n [3888 rows x 10 columns],\n '2021':          code       date  code_return       mkt  ten_return       smg  \\\n 42129       1 2021-01-04      -0.0383  0.017862     -0.1330 -0.003693   \n 42130    2142 2021-01-04      -0.0113  0.017862     -0.1330 -0.003693   \n 42131  600000 2021-01-04       0.0010  0.017862     -0.1330 -0.003693   \n 42132  600015 2021-01-04      -0.0064  0.017862     -0.1330 -0.003693   \n 42133  600016 2021-01-04       0.0000  0.017862     -0.1330 -0.003693   \n ...       ...        ...          ...       ...         ...       ...   \n 46006  601398 2021-12-31      -0.0022  0.005888     -0.0086 -0.004844   \n 46007  601818 2021-12-31       0.0000  0.005888     -0.0086 -0.004844   \n 46008  601939 2021-12-31      -0.0017  0.005888     -0.0086 -0.004844   \n 46009  601988 2021-12-31       0.0000  0.005888     -0.0086 -0.004844   \n 46010  601998 2021-12-31       0.0022  0.005888     -0.0086 -0.004844   \n \n             hml       umd       rmw       cma  \n 42129 -0.008104  0.020164  0.004206 -0.005063  \n 42130 -0.008104  0.020164  0.004206 -0.005063  \n 42131 -0.008104  0.020164  0.004206 -0.005063  \n 42132 -0.008104  0.020164  0.004206 -0.005063  \n 42133 -0.008104  0.020164  0.004206 -0.005063  \n ...         ...       ...       ...       ...  \n 46006  0.003232  0.002873 -0.004371  0.004678  \n 46007  0.003232  0.002873 -0.004371  0.004678  \n 46008  0.003232  0.002873 -0.004371  0.004678  \n 46009  0.003232  0.002873 -0.004371  0.004678  \n 46010  0.003232  0.002873 -0.004371  0.004678  \n \n [3882 rows x 10 columns]}"
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将年份分组\n",
    "print(np.unique(data['code']))\n",
    "grouped_df = {str(year): data.loc[data['date'].dt.year == year] for year in data['date'].dt.year.unique()}\n",
    "grouped_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4         5         6   \\\n0   0.013148  0.005773 -0.002174 -0.011488 -0.003769 -0.008502  0.000224   \n1    0.00311  0.006051 -0.000892 -0.006017   0.00272 -0.002792  0.006169   \n2    0.00621  0.006622 -0.001221 -0.000178  0.002632  0.000758   0.00916   \n3    0.01093  0.011443 -0.003068 -0.004101  0.001881  0.001777  0.005978   \n4   0.003502  0.004323 -0.005825  0.000091   0.00042 -0.002892 -0.000686   \n5   0.008415  0.007548 -0.005569  -0.00101 -0.002053 -0.004033  0.001196   \n6   0.011578  0.005271 -0.005497 -0.001595 -0.000909 -0.006777   0.00702   \n7   0.012647  0.007237 -0.004455 -0.006842 -0.000847 -0.004233  0.002475   \n8   0.014949  0.006399 -0.006739 -0.003964 -0.001614  0.001471 -0.004751   \n9   0.007986  0.002128 -0.003844 -0.004521  0.003023 -0.005343  0.006551   \n10  0.001892  0.002028 -0.006251  0.001014 -0.004072 -0.000999  0.001618   \n11  0.005183  0.002499 -0.004634  0.003188 -0.005132 -0.004965  0.006515   \n12  0.000884  0.004752 -0.003889  0.001368  0.003177  0.005302  0.003047   \n13  0.007043  0.006164 -0.008906 -0.005824  0.001187   -0.0038   0.00797   \n14  0.011256  0.003021 -0.008492 -0.002728 -0.004721  0.000146  0.001244   \n15 -0.002598   0.00713  -0.00268 -0.002117   -0.0014 -0.002143  0.007368   \n\n          7         8         9         10        11  \n0  -0.005029  0.006808 -0.007678  -0.00327 -0.041562  \n1    0.00631  0.002925 -0.007352  0.008641 -0.038542  \n2   0.007962  0.008392 -0.001293 -0.004359 -0.010352  \n3   0.001063  0.004835 -0.002413  0.000799 -0.004831  \n4    0.00123  0.002731 -0.004258 -0.002813 -0.006835  \n5   0.000351 -0.003022   0.00475  -0.00051 -0.028943  \n6   0.000757 -0.004006 -0.013887  0.000157 -0.032707  \n7   0.004029  0.002705 -0.006041 -0.000705 -0.034017  \n8  -0.000544  0.001677 -0.004262 -0.001848 -0.002259  \n9   0.004729  0.000891  0.001353 -0.004274 -0.005001  \n10  0.000193 -0.007897 -0.002905 -0.004985 -0.009041  \n11  0.001243 -0.012194 -0.010153 -0.008684 -0.017869  \n12  0.001169 -0.005335 -0.005862 -0.006693 -0.001391  \n13  0.004833  0.002482  -0.00693 -0.004475 -0.006643  \n14 -0.001826 -0.011347 -0.002271 -0.003724 -0.005624  \n15  0.003498   -0.0006  0.001028 -0.005841 -0.009565  ",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n      <th>11</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.013148</td>\n      <td>0.005773</td>\n      <td>-0.002174</td>\n      <td>-0.011488</td>\n      <td>-0.003769</td>\n      <td>-0.008502</td>\n      <td>0.000224</td>\n      <td>-0.005029</td>\n      <td>0.006808</td>\n      <td>-0.007678</td>\n      <td>-0.00327</td>\n      <td>-0.041562</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.00311</td>\n      <td>0.006051</td>\n      <td>-0.000892</td>\n      <td>-0.006017</td>\n      <td>0.00272</td>\n      <td>-0.002792</td>\n      <td>0.006169</td>\n      <td>0.00631</td>\n      <td>0.002925</td>\n      <td>-0.007352</td>\n      <td>0.008641</td>\n      <td>-0.038542</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.00621</td>\n      <td>0.006622</td>\n      <td>-0.001221</td>\n      <td>-0.000178</td>\n      <td>0.002632</td>\n      <td>0.000758</td>\n      <td>0.00916</td>\n      <td>0.007962</td>\n      <td>0.008392</td>\n      <td>-0.001293</td>\n      <td>-0.004359</td>\n      <td>-0.010352</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.01093</td>\n      <td>0.011443</td>\n      <td>-0.003068</td>\n      <td>-0.004101</td>\n      <td>0.001881</td>\n      <td>0.001777</td>\n      <td>0.005978</td>\n      <td>0.001063</td>\n      <td>0.004835</td>\n      <td>-0.002413</td>\n      <td>0.000799</td>\n      <td>-0.004831</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.003502</td>\n      <td>0.004323</td>\n      <td>-0.005825</td>\n      <td>0.000091</td>\n      <td>0.00042</td>\n      <td>-0.002892</td>\n      <td>-0.000686</td>\n      <td>0.00123</td>\n      <td>0.002731</td>\n      <td>-0.004258</td>\n      <td>-0.002813</td>\n      <td>-0.006835</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>0.008415</td>\n      <td>0.007548</td>\n      <td>-0.005569</td>\n      <td>-0.00101</td>\n      <td>-0.002053</td>\n      <td>-0.004033</td>\n      <td>0.001196</td>\n      <td>0.000351</td>\n      <td>-0.003022</td>\n      <td>0.00475</td>\n      <td>-0.00051</td>\n      <td>-0.028943</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.011578</td>\n      <td>0.005271</td>\n      <td>-0.005497</td>\n      <td>-0.001595</td>\n      <td>-0.000909</td>\n      <td>-0.006777</td>\n      <td>0.00702</td>\n      <td>0.000757</td>\n      <td>-0.004006</td>\n      <td>-0.013887</td>\n      <td>0.000157</td>\n      <td>-0.032707</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.012647</td>\n      <td>0.007237</td>\n      <td>-0.004455</td>\n      <td>-0.006842</td>\n      <td>-0.000847</td>\n      <td>-0.004233</td>\n      <td>0.002475</td>\n      <td>0.004029</td>\n      <td>0.002705</td>\n      <td>-0.006041</td>\n      <td>-0.000705</td>\n      <td>-0.034017</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.014949</td>\n      <td>0.006399</td>\n      <td>-0.006739</td>\n      <td>-0.003964</td>\n      <td>-0.001614</td>\n      <td>0.001471</td>\n      <td>-0.004751</td>\n      <td>-0.000544</td>\n      <td>0.001677</td>\n      <td>-0.004262</td>\n      <td>-0.001848</td>\n      <td>-0.002259</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>0.007986</td>\n      <td>0.002128</td>\n      <td>-0.003844</td>\n      <td>-0.004521</td>\n      <td>0.003023</td>\n      <td>-0.005343</td>\n      <td>0.006551</td>\n      <td>0.004729</td>\n      <td>0.000891</td>\n      <td>0.001353</td>\n      <td>-0.004274</td>\n      <td>-0.005001</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>0.001892</td>\n      <td>0.002028</td>\n      <td>-0.006251</td>\n      <td>0.001014</td>\n      <td>-0.004072</td>\n      <td>-0.000999</td>\n      <td>0.001618</td>\n      <td>0.000193</td>\n      <td>-0.007897</td>\n      <td>-0.002905</td>\n      <td>-0.004985</td>\n      <td>-0.009041</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>0.005183</td>\n      <td>0.002499</td>\n      <td>-0.004634</td>\n      <td>0.003188</td>\n      <td>-0.005132</td>\n      <td>-0.004965</td>\n      <td>0.006515</td>\n      <td>0.001243</td>\n      <td>-0.012194</td>\n      <td>-0.010153</td>\n      <td>-0.008684</td>\n      <td>-0.017869</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>0.000884</td>\n      <td>0.004752</td>\n      <td>-0.003889</td>\n      <td>0.001368</td>\n      <td>0.003177</td>\n      <td>0.005302</td>\n      <td>0.003047</td>\n      <td>0.001169</td>\n      <td>-0.005335</td>\n      <td>-0.005862</td>\n      <td>-0.006693</td>\n      <td>-0.001391</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>0.007043</td>\n      <td>0.006164</td>\n      <td>-0.008906</td>\n      <td>-0.005824</td>\n      <td>0.001187</td>\n      <td>-0.0038</td>\n      <td>0.00797</td>\n      <td>0.004833</td>\n      <td>0.002482</td>\n      <td>-0.00693</td>\n      <td>-0.004475</td>\n      <td>-0.006643</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>0.011256</td>\n      <td>0.003021</td>\n      <td>-0.008492</td>\n      <td>-0.002728</td>\n      <td>-0.004721</td>\n      <td>0.000146</td>\n      <td>0.001244</td>\n      <td>-0.001826</td>\n      <td>-0.011347</td>\n      <td>-0.002271</td>\n      <td>-0.003724</td>\n      <td>-0.005624</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>-0.002598</td>\n      <td>0.00713</td>\n      <td>-0.00268</td>\n      <td>-0.002117</td>\n      <td>-0.0014</td>\n      <td>-0.002143</td>\n      <td>0.007368</td>\n      <td>0.003498</td>\n      <td>-0.0006</td>\n      <td>0.001028</td>\n      <td>-0.005841</td>\n      <td>-0.009565</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_stocks=data['code'].unique()\n",
    "return_board=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)))\n",
    "return_board_t=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)))\n",
    "return_board_p=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)))\n",
    "coef=[]\n",
    "for i,(year,dt) in enumerate(grouped_df.items()):\n",
    "    for j,stock in enumerate(unique_stocks):\n",
    "        stock_data=dt[dt['code']==stock]\n",
    "        X=stock_data[['mkt','ten_return','smg','hml','umd','rmw','cma']]\n",
    "        X=sm.add_constant(X)\n",
    "        y=stock_data[['code_return']]\n",
    "        model= sm.OLS(y,X).fit()\n",
    "\n",
    "        nobs, _ = X.shape\n",
    "        nw_lags = round(pow(nobs,0.25))\n",
    "        nw_model = model.get_robustcov_results(cov_type='HAC', maxlags=nw_lags)\n",
    "        return_board.iloc[j, i] = nw_model.params[2]\n",
    "        return_board_t.iloc[j,i]=nw_model.tvalues[2]\n",
    "        return_board_p.iloc[j,i]=nw_model.pvalues[2]\n",
    "\n",
    "\n",
    "return_board"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4         5         6   \\\n0   2.672289   1.65195 -0.584873 -1.422226 -0.679915 -1.713695   0.08846   \n1   0.678286  1.692203 -0.176714 -1.473519  0.581675 -0.359514  0.837783   \n2   1.607803  2.091248 -0.338955 -0.033024  0.498631  0.133049  1.979966   \n3   1.940856  3.025431 -0.648008 -0.946093  0.335058   0.34687  0.834401   \n4   1.085603  1.450319  -1.33474  0.016554  0.066288 -0.531891 -0.124888   \n5   1.598023  2.408994 -1.237503 -0.186233  -0.47784 -0.775524   0.22234   \n6   2.263565  2.002715  -1.12967 -0.485346 -0.149489 -0.935721  0.913949   \n7   2.510193  2.194232 -1.085532 -1.116724 -0.167024 -0.657669   0.53287   \n8   3.156239  2.608247 -1.773021 -0.792807 -0.300002  0.227941 -0.970723   \n9   1.908888  1.020874 -1.252643 -1.284519  0.497454 -0.836817   1.27097   \n10  0.561323  0.883705 -2.458834  0.414353 -1.002247 -0.225703  0.449829   \n11  1.362467  0.934725 -1.563937    1.1194 -1.284628 -0.927656  1.304006   \n12  0.305835  2.200871 -1.515957  0.545774   0.48452   0.69731  0.767691   \n13  1.369513  1.560162 -2.678799 -1.219179  0.151721 -0.401658  1.072173   \n14  2.598002  1.386932 -2.718241 -0.893891 -1.022888  0.033951  0.494426   \n15 -0.196477    3.3033 -0.800184 -0.702422 -0.236832 -0.296001  1.363649   \n\n          7         8         9         10        11  \n0  -0.887568  0.642572 -0.747215 -0.552356 -2.734635  \n1   0.949781  0.315842 -0.874458  1.209169 -3.172067  \n2   1.892292  1.470652 -0.186103 -1.553808 -2.368739  \n3   0.293936  1.262213 -0.562626  0.281094 -1.246859  \n4   0.316434  0.630516 -1.259602 -1.052676 -2.037289  \n5   0.064866 -0.333926  0.667069 -0.072881 -2.340295  \n6   0.124861    -0.562 -1.711675  0.039256 -3.033372  \n7   1.338756  0.683224 -0.783068 -0.160481 -2.897619  \n8  -0.134426  0.391561 -0.843345 -0.826849 -0.660071  \n9   1.555012  0.203586  0.223907 -1.930875 -1.255167  \n10  0.048612 -0.713581 -0.459602 -1.550026 -2.076934  \n11  0.329955 -1.061675 -1.275117 -2.293483 -3.000142  \n12   0.31758 -0.897544 -1.397265 -3.070039 -0.571298  \n13  0.801546   0.32417 -0.905452 -1.320242 -1.672305  \n14 -0.454492 -1.306354  -0.38196 -1.448341 -1.798889  \n15  0.961712 -0.125835  0.116913 -1.284976 -1.702698  ",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n      <th>11</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2.672289</td>\n      <td>1.65195</td>\n      <td>-0.584873</td>\n      <td>-1.422226</td>\n      <td>-0.679915</td>\n      <td>-1.713695</td>\n      <td>0.08846</td>\n      <td>-0.887568</td>\n      <td>0.642572</td>\n      <td>-0.747215</td>\n      <td>-0.552356</td>\n      <td>-2.734635</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.678286</td>\n      <td>1.692203</td>\n      <td>-0.176714</td>\n      <td>-1.473519</td>\n      <td>0.581675</td>\n      <td>-0.359514</td>\n      <td>0.837783</td>\n      <td>0.949781</td>\n      <td>0.315842</td>\n      <td>-0.874458</td>\n      <td>1.209169</td>\n      <td>-3.172067</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.607803</td>\n      <td>2.091248</td>\n      <td>-0.338955</td>\n      <td>-0.033024</td>\n      <td>0.498631</td>\n      <td>0.133049</td>\n      <td>1.979966</td>\n      <td>1.892292</td>\n      <td>1.470652</td>\n      <td>-0.186103</td>\n      <td>-1.553808</td>\n      <td>-2.368739</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.940856</td>\n      <td>3.025431</td>\n      <td>-0.648008</td>\n      <td>-0.946093</td>\n      <td>0.335058</td>\n      <td>0.34687</td>\n      <td>0.834401</td>\n      <td>0.293936</td>\n      <td>1.262213</td>\n      <td>-0.562626</td>\n      <td>0.281094</td>\n      <td>-1.246859</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1.085603</td>\n      <td>1.450319</td>\n      <td>-1.33474</td>\n      <td>0.016554</td>\n      <td>0.066288</td>\n      <td>-0.531891</td>\n      <td>-0.124888</td>\n      <td>0.316434</td>\n      <td>0.630516</td>\n      <td>-1.259602</td>\n      <td>-1.052676</td>\n      <td>-2.037289</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>1.598023</td>\n      <td>2.408994</td>\n      <td>-1.237503</td>\n      <td>-0.186233</td>\n      <td>-0.47784</td>\n      <td>-0.775524</td>\n      <td>0.22234</td>\n      <td>0.064866</td>\n      <td>-0.333926</td>\n      <td>0.667069</td>\n      <td>-0.072881</td>\n      <td>-2.340295</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2.263565</td>\n      <td>2.002715</td>\n      <td>-1.12967</td>\n      <td>-0.485346</td>\n      <td>-0.149489</td>\n      <td>-0.935721</td>\n      <td>0.913949</td>\n      <td>0.124861</td>\n      <td>-0.562</td>\n      <td>-1.711675</td>\n      <td>0.039256</td>\n      <td>-3.033372</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2.510193</td>\n      <td>2.194232</td>\n      <td>-1.085532</td>\n      <td>-1.116724</td>\n      <td>-0.167024</td>\n      <td>-0.657669</td>\n      <td>0.53287</td>\n      <td>1.338756</td>\n      <td>0.683224</td>\n      <td>-0.783068</td>\n      <td>-0.160481</td>\n      <td>-2.897619</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>3.156239</td>\n      <td>2.608247</td>\n      <td>-1.773021</td>\n      <td>-0.792807</td>\n      <td>-0.300002</td>\n      <td>0.227941</td>\n      <td>-0.970723</td>\n      <td>-0.134426</td>\n      <td>0.391561</td>\n      <td>-0.843345</td>\n      <td>-0.826849</td>\n      <td>-0.660071</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>1.908888</td>\n      <td>1.020874</td>\n      <td>-1.252643</td>\n      <td>-1.284519</td>\n      <td>0.497454</td>\n      <td>-0.836817</td>\n      <td>1.27097</td>\n      <td>1.555012</td>\n      <td>0.203586</td>\n      <td>0.223907</td>\n      <td>-1.930875</td>\n      <td>-1.255167</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>0.561323</td>\n      <td>0.883705</td>\n      <td>-2.458834</td>\n      <td>0.414353</td>\n      <td>-1.002247</td>\n      <td>-0.225703</td>\n      <td>0.449829</td>\n      <td>0.048612</td>\n      <td>-0.713581</td>\n      <td>-0.459602</td>\n      <td>-1.550026</td>\n      <td>-2.076934</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>1.362467</td>\n      <td>0.934725</td>\n      <td>-1.563937</td>\n      <td>1.1194</td>\n      <td>-1.284628</td>\n      <td>-0.927656</td>\n      <td>1.304006</td>\n      <td>0.329955</td>\n      <td>-1.061675</td>\n      <td>-1.275117</td>\n      <td>-2.293483</td>\n      <td>-3.000142</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>0.305835</td>\n      <td>2.200871</td>\n      <td>-1.515957</td>\n      <td>0.545774</td>\n      <td>0.48452</td>\n      <td>0.69731</td>\n      <td>0.767691</td>\n      <td>0.31758</td>\n      <td>-0.897544</td>\n      <td>-1.397265</td>\n      <td>-3.070039</td>\n      <td>-0.571298</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>1.369513</td>\n      <td>1.560162</td>\n      <td>-2.678799</td>\n      <td>-1.219179</td>\n      <td>0.151721</td>\n      <td>-0.401658</td>\n      <td>1.072173</td>\n      <td>0.801546</td>\n      <td>0.32417</td>\n      <td>-0.905452</td>\n      <td>-1.320242</td>\n      <td>-1.672305</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>2.598002</td>\n      <td>1.386932</td>\n      <td>-2.718241</td>\n      <td>-0.893891</td>\n      <td>-1.022888</td>\n      <td>0.033951</td>\n      <td>0.494426</td>\n      <td>-0.454492</td>\n      <td>-1.306354</td>\n      <td>-0.38196</td>\n      <td>-1.448341</td>\n      <td>-1.798889</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>-0.196477</td>\n      <td>3.3033</td>\n      <td>-0.800184</td>\n      <td>-0.702422</td>\n      <td>-0.236832</td>\n      <td>-0.296001</td>\n      <td>1.363649</td>\n      <td>0.961712</td>\n      <td>-0.125835</td>\n      <td>0.116913</td>\n      <td>-1.284976</td>\n      <td>-1.702698</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_board_t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4         5         6   \\\n0   0.008214  0.099921  0.559219  0.156321  0.497225  0.087898  0.929586   \n1   0.498269   0.09195  0.859886  0.141979  0.561341  0.719532  0.403004   \n2   0.109306   0.03758  0.734947  0.973684  0.618504  0.894275  0.048965   \n3   0.053577  0.002759  0.517615  0.345094  0.737878  0.728998  0.404899   \n4   0.278781   0.14832  0.183275  0.986807  0.947204  0.595302  0.900719   \n5   0.111435   0.01677  0.217141   0.85243  0.633205  0.438823  0.824242   \n6   0.024559  0.046357  0.259772  0.627893  0.881296  0.350394  0.361676   \n7    0.01277  0.029198  0.278827  0.265277  0.867493  0.511392  0.594636   \n8   0.001811  0.009692  0.077554  0.428707   0.76444  0.819919   0.33268   \n9   0.057549  0.308368  0.211597  0.200253   0.61933  0.403542  0.204991   \n10  0.575138  0.377762  0.014667  0.679002  0.317246  0.821628  0.653247   \n11  0.174413  0.350894   0.11919  0.264137  0.200177  0.354534  0.193502   \n12  0.760014  0.028723  0.130886  0.585751  0.628464  0.486295  0.443438   \n13   0.17218  0.120121  0.007915  0.224025  0.879536  0.688302  0.284738   \n14  0.010723  0.166782  0.007056  0.372315  0.307404  0.972945  0.621465   \n15  0.844741  0.001107  0.424416  0.483126  0.812992  0.767502  0.173983   \n\n          7         8         9         10        11  \n0   0.375677  0.521128  0.455678   0.58123  0.006721  \n1   0.343195  0.752403  0.382758  0.227813  0.001721  \n2   0.059676  0.142723  0.852524  0.121576  0.018659  \n3   0.769065  0.208123  0.574223  0.778885  0.213691  \n4   0.751953   0.52897  0.209057  0.293571  0.042742  \n5   0.948336  0.738733  0.505379  0.941962  0.020106  \n6   0.900741  0.574652   0.08827   0.96872   0.00269  \n7   0.181938  0.495138  0.434372   0.87264  0.004115  \n8   0.893184  0.695738  0.399889  0.409161  0.509855  \n9   0.121283  0.838853  0.823023  0.054701  0.210665  \n10  0.961269  0.476194  0.646225  0.122481  0.038894  \n11  0.741727  0.289473  0.203522  0.022704  0.002989  \n12  0.751084  0.370347  0.163646  0.002392  0.568344  \n13  0.423622  0.746097   0.36615  0.188039  0.095795  \n14  0.649893  0.192709  0.702834  0.148855  0.073319  \n15  0.337179   0.89997  0.907028  0.200066  0.089947  ",
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<tr>\n      <th>7</th>\n      <td>0.01277</td>\n      <td>0.029198</td>\n      <td>0.278827</td>\n      <td>0.265277</td>\n      <td>0.867493</td>\n      <td>0.511392</td>\n      <td>0.594636</td>\n      <td>0.181938</td>\n      <td>0.495138</td>\n      <td>0.434372</td>\n      <td>0.87264</td>\n      <td>0.004115</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.001811</td>\n      <td>0.009692</td>\n      <td>0.077554</td>\n      <td>0.428707</td>\n      <td>0.76444</td>\n      <td>0.819919</td>\n      <td>0.33268</td>\n      <td>0.893184</td>\n      <td>0.695738</td>\n      <td>0.399889</td>\n      <td>0.409161</td>\n      <td>0.509855</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>0.057549</td>\n      <td>0.308368</td>\n      <td>0.211597</td>\n      <td>0.200253</td>\n      <td>0.61933</td>\n      <td>0.403542</td>\n      <td>0.204991</td>\n      <td>0.121283</td>\n      <td>0.838853</td>\n      <td>0.823023</td>\n      <td>0.054701</td>\n      <td>0.210665</td>\n    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     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_board_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          date    code           gap         price\n0   2010-01-01       1 -6.894123e+10  5.502837e+10\n1   2011-01-01       1  9.845070e+08  7.987303e+10\n2   2012-01-01       1 -1.279340e+11  8.207607e+10\n3   2013-01-01       1 -8.280000e+10  1.000000e+11\n4   2014-01-01       1 -9.816000e+10  1.810000e+11\n..         ...     ...           ...           ...\n139 2017-01-01  601998 -1.191440e+12  7.367929e+10\n140 2018-01-01  601998 -1.148510e+12  6.111160e+10\n141 2019-01-01  601998 -1.075820e+12  6.936214e+10\n142 2020-01-01  601998 -7.523680e+11  6.024817e+10\n143 2021-01-01  601998 -9.567740e+11  5.621883e+10\n\n[192 rows x 4 columns]",
      "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>date</th>\n      <th>code</th>\n      <th>gap</th>\n      <th>price</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2010-01-01</td>\n      <td>1</td>\n      <td>-6.894123e+10</td>\n      <td>5.502837e+10</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2011-01-01</td>\n      <td>1</td>\n      <td>9.845070e+08</td>\n      <td>7.987303e+10</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2012-01-01</td>\n      <td>1</td>\n      <td>-1.279340e+11</td>\n      <td>8.207607e+10</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2013-01-01</td>\n      <td>1</td>\n      <td>-8.280000e+10</td>\n      <td>1.000000e+11</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2014-01-01</td>\n      <td>1</td>\n      <td>-9.816000e+10</td>\n      <td>1.810000e+11</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>139</th>\n      <td>2017-01-01</td>\n      <td>601998</td>\n      <td>-1.191440e+12</td>\n      <td>7.367929e+10</td>\n    </tr>\n    <tr>\n      <th>140</th>\n      <td>2018-01-01</td>\n      <td>601998</td>\n      <td>-1.148510e+12</td>\n      <td>6.111160e+10</td>\n    </tr>\n    <tr>\n      <th>141</th>\n      <td>2019-01-01</td>\n      <td>601998</td>\n      <td>-1.075820e+12</td>\n      <td>6.936214e+10</td>\n    </tr>\n    <tr>\n      <th>142</th>\n      <td>2020-01-01</td>\n      <td>601998</td>\n      <td>-7.523680e+11</td>\n      <td>6.024817e+10</td>\n    </tr>\n    <tr>\n      <th>143</th>\n      <td>2021-01-01</td>\n      <td>601998</td>\n      <td>-9.567740e+11</td>\n      <td>5.621883e+10</td>\n    </tr>\n  </tbody>\n</table>\n<p>192 rows × 4 columns</p>\n</div>"
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = pd.read_csv('data2.csv',  usecols=range(4))\n",
    "data2.columns=['date','code','gap','price']\n",
    "data2['date'] = pd.to_datetime(data2['date'], format='%Y')\n",
    "data2 = data2.sort_values(by=['code','date'])\n",
    "data2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p1=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)))\n",
    "p2=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)))\n",
    "unique_stocks=data2['code'].unique()\n",
    "unique_years=data2['date'].unique()\n",
    "def to_panel(x):\n",
    "    global p1,p2\n",
    "    p1[np.where(unique_years == x[0])[0][0]][np.where(unique_stocks == x[1])[0][0]] =x[2]\n",
    "    p2[np.where(unique_years == x[0])[0][0]][np.where(unique_stocks == x[1])[0][0]] =x[3]\n",
    "data2.apply(to_panel,axis=1)\n",
    "p1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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<td>225000000000.0</td>\n      <td>342000000000.0</td>\n      <td>371000000000.0</td>\n      <td>363000000000.0</td>\n      <td>599000000000.0</td>\n      <td>520000000000.0</td>\n      <td>775000000000.0</td>\n      <td>907000000000.0</td>\n      <td>1000000000000.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>140000000000.0</td>\n      <td>129000000000.0</td>\n      <td>137000000000.0</td>\n      <td>123000000000.0</td>\n      <td>260000000000.0</td>\n      <td>230000000000.0</td>\n      <td>218000000000.0</td>\n      <td>211000000000.0</td>\n      <td>186000000000.0</td>\n      <td>210000000000.0</td>\n      <td>174000000000.0</td>\n      <td>157000000000.0</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>163000000000.0</td>\n      <td>147000000000.0</td>\n      <td>194000000000.0</td>\n      <td>151000000000.0</td>\n      <td>267000000000.0</td>\n      <td>253000000000.0</td>\n      <td>226000000000.0</td>\n      <td>244000000000.0</td>\n      <td>227000000000.0</td>\n      <td>221000000000.0</td>\n      <td>176000000000.0</td>\n      <td>181000000000.0</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>632000000000.0</td>\n      <td>571000000000.0</td>\n      <td>571000000000.0</td>\n      <td>513000000000.0</td>\n      <td>851000000000.0</td>\n      <td>845000000000.0</td>\n      <td>725000000000.0</td>\n      <td>837000000000.0</td>\n      <td>761000000000.0</td>\n      <td>778000000000.0</td>\n      <td>670000000000.0</td>\n      <td>643000000000.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>113000000000.0</td>\n      <td>133000000000.0</td>\n      <td>178000000000.0</td>\n      <td>174000000000.0</td>\n      <td>296000000000.0</td>\n      <td>285000000000.0</td>\n      <td>268000000000.0</td>\n      <td>248000000000.0</td>\n      <td>203000000000.0</td>\n      <td>224000000000.0</td>\n      <td>184000000000.0</td>\n      <td>138000000000.0</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>54396758644.0</td>\n      <td>76922420464.0</td>\n      <td>51651968071.0</td>\n      <td>76312794872.0</td>\n      <td>120000000000.0</td>\n      <td>130000000000.0</td>\n      <td>116000000000.0</td>\n      <td>115000000000.0</td>\n      <td>94759654366.0</td>\n      <td>118000000000.0</td>\n      <td>96170149894.0</td>\n      <td>86168454305.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>788000000000.0</td>\n      <td>770000000000.0</td>\n      <td>823000000000.0</td>\n      <td>729000000000.0</td>\n      <td>1090000000000.0</td>\n      <td>950000000000.0</td>\n      <td>912000000000.0</td>\n      <td>1130000000000.0</td>\n      <td>1150000000000.0</td>\n      <td>1180000000000.0</td>\n      <td>1000000000000.0</td>\n      <td>939000000000.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>71243307919.0</td>\n      <td>57791774256.0</td>\n      <td>81841483713.0</td>\n      <td>66089198138.0</td>\n      <td>115000000000.0</td>\n      <td>133000000000.0</td>\n      <td>148000000000.0</td>\n      <td>151000000000.0</td>\n      <td>119000000000.0</td>\n      <td>120000000000.0</td>\n      <td>102000000000.0</td>\n      <td>93874850168.0</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>29511195948.0</td>\n      <td>27551700040.0</td>\n      <td>27314185385.0</td>\n      <td>24018669539.0</td>\n      <td>43494871292.0</td>\n      <td>59577412810.0</td>\n      <td>65676524215.0</td>\n      <td>65652289332.0</td>\n      <td>54795063189.0</td>\n      <td>74388963493.0</td>\n      <td>80856697142.0</td>\n      <td>89663519653.0</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>160000000000.0</td>\n      <td>116000000000.0</td>\n      <td>123000000000.0</td>\n      <td>106000000000.0</td>\n      <td>194000000000.0</td>\n      <td>169000000000.0</td>\n      <td>156000000000.0</td>\n      <td>161000000000.0</td>\n      <td>147000000000.0</td>\n      <td>176000000000.0</td>\n      <td>165000000000.0</td>\n      <td>137000000000.0</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>144000000000.0</td>\n      <td>135000000000.0</td>\n      <td>180000000000.0</td>\n      <td>193000000000.0</td>\n      <td>314000000000.0</td>\n      <td>325000000000.0</td>\n      <td>308000000000.0</td>\n      <td>353000000000.0</td>\n      <td>310000000000.0</td>\n      <td>411000000000.0</td>\n      <td>434000000000.0</td>\n      <td>396000000000.0</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>1110000000000.0</td>\n      <td>1110000000000.0</td>\n      <td>1090000000000.0</td>\n      <td>947000000000.0</td>\n      <td>1300000000000.0</td>\n      <td>1230000000000.0</td>\n      <td>1190000000000.0</td>\n      <td>1670000000000.0</td>\n      <td>1430000000000.0</td>\n      <td>1590000000000.0</td>\n      <td>1350000000000.0</td>\n      <td>1250000000000.0</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>44034888412.0</td>\n      <td>43555205531.0</td>\n      <td>44130824988.0</td>\n      <td>39717742489.0</td>\n      <td>64565315688.0</td>\n      <td>55451340963.0</td>\n      <td>52189497377.0</td>\n      <td>73679290414.0</td>\n      <td>61111598950.0</td>\n      <td>69362144491.0</td>\n      <td>60248169766.0</td>\n      <td>56218833571.0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "           0          1          2         3          4          5   \\\n0    0.012326  -1.558725     -0.828  -0.54232  -0.916703  -3.260923   \n1    -1.17162   -2.09448  -3.632487  -1.78103  -4.716693  -4.611005   \n2   -0.777133  -1.421314    -2.1215 -1.604754  -2.888484   -2.19002   \n3   -0.097328  -0.520667   0.023627  0.239939  -0.885515  -0.893366   \n4    21.69845  28.586788   3.354561  0.986165   0.944683  -0.291546   \n5   -1.002816  -1.833814  -3.625351 -1.845876  -1.240344  -3.419876   \n6   -0.139848  -0.151343  -0.173326 -0.138348  -0.152186   -0.29188   \n7   -1.133451  -3.055949  -3.337414 -2.051348  -4.099579  -5.047799   \n8    0.161999  -0.806993  -1.739276  -0.59905  -1.220823  -1.702474   \n9   -2.023169  -1.902066  -2.391838 -1.681459  -2.540926  -3.525154   \n10   -5.43612   -1.53311  -7.368224 -1.710513  -3.034128  -4.110486   \n11 -68.490873  -56.36595 -46.079988 -24.08192 -24.866471 -24.018476   \n12  -0.665621  -2.324813  -1.897877 -0.607974  -0.619343  -1.284301   \n13 -13.116074  -9.753611 -10.175544 -5.387389  -6.095877  -5.972013   \n14   0.566501    0.59222   0.709553  0.540993   0.613883   0.798871   \n15   2.717035  -3.269211  -3.887985 -9.168576  -9.542997  -22.49648   \n\n           6         7          8          9          10  \n0   -1.384627 -1.182236  -1.744298  -2.032587  -2.575797  \n1   -5.003581 -4.983206   -2.80538  -2.978882  -2.889723  \n2   -2.651684 -2.140792  -2.251782  -7.363099   -7.29128  \n3   -0.483689  0.230656  -0.060741  -0.514357  -0.370309  \n4   -3.326024 -1.752677  -2.429157  -7.650345   7.165159  \n5   -5.715574 -5.982863  -6.884118 -12.306705 -12.883039  \n6   -0.248661 -0.040215   0.113682  -0.236037  -0.216633  \n7   -3.970073 -1.736852   0.500156  -2.486587  -6.860761  \n8   -1.582409 -0.610239  -1.119246  -2.774042  -1.880874  \n9   -2.641903 -2.616496    -3.0845   -7.17961  -6.088285  \n10  -5.036033 -2.291723    -5.7807 -14.299216 -20.283068  \n11  -14.49101 -2.443596 -21.425087  -78.89093 -71.825086  \n12  -1.057248   0.66766   1.344812   3.263545   2.203569  \n13  -6.730425 -3.289677   -4.12708  -6.599355  -9.986439  \n14    0.41599  0.309616   0.452123   0.715199   0.752506  \n15 -16.170623 -18.79365 -15.510189 -12.487815 -17.018745  ",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.012326</td>\n      <td>-1.558725</td>\n      <td>-0.828</td>\n      <td>-0.54232</td>\n      <td>-0.916703</td>\n      <td>-3.260923</td>\n      <td>-1.384627</td>\n      <td>-1.182236</td>\n      <td>-1.744298</td>\n      <td>-2.032587</td>\n      <td>-2.575797</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-1.17162</td>\n      <td>-2.09448</td>\n      <td>-3.632487</td>\n      <td>-1.78103</td>\n      <td>-4.716693</td>\n      <td>-4.611005</td>\n      <td>-5.003581</td>\n      <td>-4.983206</td>\n      <td>-2.80538</td>\n      <td>-2.978882</td>\n      <td>-2.889723</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>-0.777133</td>\n      <td>-1.421314</td>\n      <td>-2.1215</td>\n      <td>-1.604754</td>\n      <td>-2.888484</td>\n      <td>-2.19002</td>\n      <td>-2.651684</td>\n      <td>-2.140792</td>\n      <td>-2.251782</td>\n      <td>-7.363099</td>\n      <td>-7.29128</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-0.097328</td>\n      <td>-0.520667</td>\n      <td>0.023627</td>\n      <td>0.239939</td>\n      <td>-0.885515</td>\n      <td>-0.893366</td>\n      <td>-0.483689</td>\n      <td>0.230656</td>\n      <td>-0.060741</td>\n      <td>-0.514357</td>\n      <td>-0.370309</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>21.69845</td>\n      <td>28.586788</td>\n      <td>3.354561</td>\n      <td>0.986165</td>\n      <td>0.944683</td>\n      <td>-0.291546</td>\n      <td>-3.326024</td>\n      <td>-1.752677</td>\n      <td>-2.429157</td>\n      <td>-7.650345</td>\n      <td>7.165159</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>-1.002816</td>\n      <td>-1.833814</td>\n      <td>-3.625351</td>\n      <td>-1.845876</td>\n      <td>-1.240344</td>\n      <td>-3.419876</td>\n      <td>-5.715574</td>\n      <td>-5.982863</td>\n      <td>-6.884118</td>\n      <td>-12.306705</td>\n      <td>-12.883039</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>-0.139848</td>\n      <td>-0.151343</td>\n      <td>-0.173326</td>\n      <td>-0.138348</td>\n      <td>-0.152186</td>\n      <td>-0.29188</td>\n      <td>-0.248661</td>\n      <td>-0.040215</td>\n      <td>0.113682</td>\n      <td>-0.236037</td>\n      <td>-0.216633</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>-1.133451</td>\n      <td>-3.055949</td>\n      <td>-3.337414</td>\n      <td>-2.051348</td>\n      <td>-4.099579</td>\n      <td>-5.047799</td>\n      <td>-3.970073</td>\n      <td>-1.736852</td>\n      <td>0.500156</td>\n      <td>-2.486587</td>\n      <td>-6.860761</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.161999</td>\n      <td>-0.806993</td>\n      <td>-1.739276</td>\n      <td>-0.59905</td>\n      <td>-1.220823</td>\n      <td>-1.702474</td>\n      <td>-1.582409</td>\n      <td>-0.610239</td>\n      <td>-1.119246</td>\n      <td>-2.774042</td>\n      <td>-1.880874</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>-2.023169</td>\n      <td>-1.902066</td>\n      <td>-2.391838</td>\n      <td>-1.681459</td>\n      <td>-2.540926</td>\n      <td>-3.525154</td>\n      <td>-2.641903</td>\n      <td>-2.616496</td>\n      <td>-3.0845</td>\n      <td>-7.17961</td>\n      <td>-6.088285</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>-5.43612</td>\n      <td>-1.53311</td>\n      <td>-7.368224</td>\n      <td>-1.710513</td>\n      <td>-3.034128</td>\n      <td>-4.110486</td>\n      <td>-5.036033</td>\n      <td>-2.291723</td>\n      <td>-5.7807</td>\n      <td>-14.299216</td>\n      <td>-20.283068</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>-68.490873</td>\n      <td>-56.36595</td>\n      <td>-46.079988</td>\n      <td>-24.08192</td>\n      <td>-24.866471</td>\n      <td>-24.018476</td>\n      <td>-14.49101</td>\n      <td>-2.443596</td>\n      <td>-21.425087</td>\n      <td>-78.89093</td>\n      <td>-71.825086</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>-0.665621</td>\n      <td>-2.324813</td>\n      <td>-1.897877</td>\n      <td>-0.607974</td>\n      <td>-0.619343</td>\n      <td>-1.284301</td>\n      <td>-1.057248</td>\n      <td>0.66766</td>\n      <td>1.344812</td>\n      <td>3.263545</td>\n      <td>2.203569</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>-13.116074</td>\n      <td>-9.753611</td>\n      <td>-10.175544</td>\n      <td>-5.387389</td>\n      <td>-6.095877</td>\n      <td>-5.972013</td>\n      <td>-6.730425</td>\n      <td>-3.289677</td>\n      <td>-4.12708</td>\n      <td>-6.599355</td>\n      <td>-9.986439</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>0.566501</td>\n      <td>0.59222</td>\n      <td>0.709553</td>\n      <td>0.540993</td>\n      <td>0.613883</td>\n      <td>0.798871</td>\n      <td>0.41599</td>\n      <td>0.309616</td>\n      <td>0.452123</td>\n      <td>0.715199</td>\n      <td>0.752506</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>2.717035</td>\n      <td>-3.269211</td>\n      <td>-3.887985</td>\n      <td>-9.168576</td>\n      <td>-9.542997</td>\n      <td>-22.49648</td>\n      <td>-16.170623</td>\n      <td>-18.79365</td>\n      <td>-15.510189</td>\n      <td>-12.487815</td>\n      <td>-17.018745</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beta_1= p1.div(p2)\n",
    "beta_1=beta_1.drop(beta_1.columns[0],axis=1)\n",
    "beta_1.rename(columns=lambda x:int(x-1),inplace=True)\n",
    "beta_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "            0          1          2          3          4          5   \\\n0    -0.863135   0.011995   -1.27934  -0.457459  -0.570698  -1.010724   \n1     -0.89675  -1.006757  -2.418977  -1.891406  -1.505244  -4.396389   \n2    -0.894481  -0.663714  -1.493994  -1.274348  -1.378865  -2.814209   \n3    -0.135536  -0.084111   -0.56232   0.015544   0.221183   -0.90503   \n4     2.107233  20.431387  31.840569   1.586965   1.114796   0.996683   \n5     -1.41515  -0.759866  -2.356026  -2.050292   -1.94802  -1.388527   \n6    -0.110558  -0.139848  -0.168453  -0.104485   -0.13933  -0.177375   \n7    -0.693459  -0.846904  -3.126201  -1.961858  -2.130523  -4.359627   \n8     0.829276   0.241255   -0.54621  -1.106075  -0.552969  -1.368164   \n9    -2.197091   -1.89288  -2.147325  -1.599679  -1.929253  -2.646798   \n10   -8.713385  -3.838677  -1.898525  -4.234435  -1.479015  -2.726615   \n11 -145.343844 -69.086446  -64.09972 -25.446219  -17.58116 -22.557223   \n12   -0.597011   -0.62774   -2.69766  -1.036985  -0.697911  -0.670955   \n13  -14.677333  -9.837056  -9.096632  -6.254395  -5.205046  -6.432338   \n14    0.494493   0.576895   0.681647   0.516882   0.571781   0.634518   \n15    0.819167   2.681595  -3.632457  -2.391718 -10.675522 -10.139435   \n\n           6          7          8          9          10  \n0   -2.231158  -1.960839  -0.596677  -1.483816  -2.381937  \n1   -3.313917  -5.347635  -2.664525  -2.090802  -2.496138  \n2   -2.071641  -3.406677  -1.698479  -2.878158   -8.36448  \n3   -0.541389  -0.557173   0.154763  -0.051901  -0.466522  \n4   -0.301218   -3.77307  -1.552371  -2.931741  -8.478726  \n5    -3.16759  -6.143612  -6.145294  -8.644261  -11.96674  \n6   -0.252823  -0.273494  -0.039337   0.132007  -0.245949  \n7   -5.454879  -4.850138  -1.574022   0.608886  -3.315449  \n8   -1.717278  -1.920406  -0.490051  -1.373306  -3.096029  \n9    -2.84508  -2.595957  -2.549975   -3.63971  -7.646017  \n10  -4.028821  -6.390261  -2.272625  -6.800824 -15.536856  \n11 -24.027342 -17.362294  -1.799958 -19.711292 -71.142199  \n12  -1.244416  -1.157939   0.557648   1.434467   3.930547  \n13  -5.210708     -7.664  -2.481265  -3.908364  -7.232626  \n14   0.569255   0.485806    0.27846     0.5325   0.772414  \n15 -15.935007 -19.496135 -16.558167 -17.856476 -13.382846  ",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>-0.863135</td>\n      <td>0.011995</td>\n      <td>-1.27934</td>\n      <td>-0.457459</td>\n      <td>-0.570698</td>\n      <td>-1.010724</td>\n      <td>-2.231158</td>\n      <td>-1.960839</td>\n      <td>-0.596677</td>\n      <td>-1.483816</td>\n      <td>-2.381937</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-0.89675</td>\n      <td>-1.006757</td>\n      <td>-2.418977</td>\n      <td>-1.891406</td>\n      <td>-1.505244</td>\n      <td>-4.396389</td>\n      <td>-3.313917</td>\n      <td>-5.347635</td>\n      <td>-2.664525</td>\n      <td>-2.090802</td>\n      <td>-2.496138</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>-0.894481</td>\n      <td>-0.663714</td>\n      <td>-1.493994</td>\n      <td>-1.274348</td>\n      <td>-1.378865</td>\n      <td>-2.814209</td>\n      <td>-2.071641</td>\n      <td>-3.406677</td>\n      <td>-1.698479</td>\n      <td>-2.878158</td>\n      <td>-8.36448</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-0.135536</td>\n      <td>-0.084111</td>\n      <td>-0.56232</td>\n      <td>0.015544</td>\n      <td>0.221183</td>\n      <td>-0.90503</td>\n      <td>-0.541389</td>\n      <td>-0.557173</td>\n      <td>0.154763</td>\n      <td>-0.051901</td>\n      <td>-0.466522</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2.107233</td>\n      <td>20.431387</td>\n      <td>31.840569</td>\n      <td>1.586965</td>\n      <td>1.114796</td>\n      <td>0.996683</td>\n      <td>-0.301218</td>\n      <td>-3.77307</td>\n      <td>-1.552371</td>\n      <td>-2.931741</td>\n      <td>-8.478726</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>-1.41515</td>\n      <td>-0.759866</td>\n      <td>-2.356026</td>\n      <td>-2.050292</td>\n      <td>-1.94802</td>\n      <td>-1.388527</td>\n      <td>-3.16759</td>\n      <td>-6.143612</td>\n      <td>-6.145294</td>\n      <td>-8.644261</td>\n      <td>-11.96674</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>-0.110558</td>\n      <td>-0.139848</td>\n      <td>-0.168453</td>\n      <td>-0.104485</td>\n      <td>-0.13933</td>\n      <td>-0.177375</td>\n      <td>-0.252823</td>\n      <td>-0.273494</td>\n      <td>-0.039337</td>\n      <td>0.132007</td>\n      <td>-0.245949</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>-0.693459</td>\n      <td>-0.846904</td>\n      <td>-3.126201</td>\n      <td>-1.961858</td>\n      <td>-2.130523</td>\n      <td>-4.359627</td>\n      <td>-5.454879</td>\n      <td>-4.850138</td>\n      <td>-1.574022</td>\n      <td>0.608886</td>\n      <td>-3.315449</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.829276</td>\n      <td>0.241255</td>\n      <td>-0.54621</td>\n      <td>-1.106075</td>\n      <td>-0.552969</td>\n      <td>-1.368164</td>\n      <td>-1.717278</td>\n      <td>-1.920406</td>\n      <td>-0.490051</td>\n      <td>-1.373306</td>\n      <td>-3.096029</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>-2.197091</td>\n      <td>-1.89288</td>\n      <td>-2.147325</td>\n      <td>-1.599679</td>\n      <td>-1.929253</td>\n      <td>-2.646798</td>\n      <td>-2.84508</td>\n      <td>-2.595957</td>\n      <td>-2.549975</td>\n      <td>-3.63971</td>\n      <td>-7.646017</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>-8.713385</td>\n      <td>-3.838677</td>\n      <td>-1.898525</td>\n      <td>-4.234435</td>\n      <td>-1.479015</td>\n      <td>-2.726615</td>\n      <td>-4.028821</td>\n      <td>-6.390261</td>\n      <td>-2.272625</td>\n      <td>-6.800824</td>\n      <td>-15.536856</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>-145.343844</td>\n      <td>-69.086446</td>\n      <td>-64.09972</td>\n      <td>-25.446219</td>\n      <td>-17.58116</td>\n      <td>-22.557223</td>\n      <td>-24.027342</td>\n      <td>-17.362294</td>\n      <td>-1.799958</td>\n      <td>-19.711292</td>\n      <td>-71.142199</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>-0.597011</td>\n      <td>-0.62774</td>\n      <td>-2.69766</td>\n      <td>-1.036985</td>\n      <td>-0.697911</td>\n      <td>-0.670955</td>\n      <td>-1.244416</td>\n      <td>-1.157939</td>\n      <td>0.557648</td>\n      <td>1.434467</td>\n      <td>3.930547</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>-14.677333</td>\n      <td>-9.837056</td>\n      <td>-9.096632</td>\n      <td>-6.254395</td>\n      <td>-5.205046</td>\n      <td>-6.432338</td>\n      <td>-5.210708</td>\n      <td>-7.664</td>\n      <td>-2.481265</td>\n      <td>-3.908364</td>\n      <td>-7.232626</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>0.494493</td>\n      <td>0.576895</td>\n      <td>0.681647</td>\n      <td>0.516882</td>\n      <td>0.571781</td>\n      <td>0.634518</td>\n      <td>0.569255</td>\n      <td>0.485806</td>\n      <td>0.27846</td>\n      <td>0.5325</td>\n      <td>0.772414</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>0.819167</td>\n      <td>2.681595</td>\n      <td>-3.632457</td>\n      <td>-2.391718</td>\n      <td>-10.675522</td>\n      <td>-10.139435</td>\n      <td>-15.935007</td>\n      <td>-19.496135</td>\n      <td>-16.558167</td>\n      <td>-17.856476</td>\n      <td>-13.382846</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beta_2=pd.DataFrame(index=range(len(unique_stocks)),columns=range(len(grouped_df)-1))\n",
    "for n in range(11):\n",
    "    beta_2[n]=p1.iloc[:,n].div(p2.iloc[:,n+1])\n",
    "beta_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "          0         1         2         3         4         5         6   \\\n0   0.005773 -0.002174 -0.011488 -0.003769 -0.008502  0.000224 -0.005029   \n1   0.006051 -0.000892 -0.006017   0.00272 -0.002792  0.006169   0.00631   \n2   0.006622 -0.001221 -0.000178  0.002632  0.000758   0.00916  0.007962   \n3   0.011443 -0.003068 -0.004101  0.001881  0.001777  0.005978  0.001063   \n4   0.004323 -0.005825  0.000091   0.00042 -0.002892 -0.000686   0.00123   \n5   0.007548 -0.005569  -0.00101 -0.002053 -0.004033  0.001196  0.000351   \n6   0.005271 -0.005497 -0.001595 -0.000909 -0.006777   0.00702  0.000757   \n7   0.007237 -0.004455 -0.006842 -0.000847 -0.004233  0.002475  0.004029   \n8   0.006399 -0.006739 -0.003964 -0.001614  0.001471 -0.004751 -0.000544   \n9   0.002128 -0.003844 -0.004521  0.003023 -0.005343  0.006551  0.004729   \n10  0.002028 -0.006251  0.001014 -0.004072 -0.000999  0.001618  0.000193   \n11  0.002499 -0.004634  0.003188 -0.005132 -0.004965  0.006515  0.001243   \n12  0.004752 -0.003889  0.001368  0.003177  0.005302  0.003047  0.001169   \n13  0.006164 -0.008906 -0.005824  0.001187   -0.0038   0.00797  0.004833   \n14  0.003021 -0.008492 -0.002728 -0.004721  0.000146  0.001244 -0.001826   \n15   0.00713  -0.00268 -0.002117   -0.0014 -0.002143  0.007368  0.003498   \n\n          7         8         9         10  \n0   0.006808 -0.007678  -0.00327 -0.041562  \n1   0.002925 -0.007352  0.008641 -0.038542  \n2   0.008392 -0.001293 -0.004359 -0.010352  \n3   0.004835 -0.002413  0.000799 -0.004831  \n4   0.002731 -0.004258 -0.002813 -0.006835  \n5  -0.003022   0.00475  -0.00051 -0.028943  \n6  -0.004006 -0.013887  0.000157 -0.032707  \n7   0.002705 -0.006041 -0.000705 -0.034017  \n8   0.001677 -0.004262 -0.001848 -0.002259  \n9   0.000891  0.001353 -0.004274 -0.005001  \n10 -0.007897 -0.002905 -0.004985 -0.009041  \n11 -0.012194 -0.010153 -0.008684 -0.017869  \n12 -0.005335 -0.005862 -0.006693 -0.001391  \n13  0.002482  -0.00693 -0.004475 -0.006643  \n14 -0.011347 -0.002271 -0.003724 -0.005624  \n15   -0.0006  0.001028 -0.005841 -0.009565  ",
      "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>0</th>\n      <th>1</th>\n      <th>2</th>\n      <th>3</th>\n      <th>4</th>\n      <th>5</th>\n      <th>6</th>\n      <th>7</th>\n      <th>8</th>\n      <th>9</th>\n      <th>10</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.005773</td>\n      <td>-0.002174</td>\n      <td>-0.011488</td>\n      <td>-0.003769</td>\n      <td>-0.008502</td>\n      <td>0.000224</td>\n      <td>-0.005029</td>\n      <td>0.006808</td>\n      <td>-0.007678</td>\n      <td>-0.00327</td>\n      <td>-0.041562</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0.006051</td>\n      <td>-0.000892</td>\n      <td>-0.006017</td>\n      <td>0.00272</td>\n      <td>-0.002792</td>\n      <td>0.006169</td>\n      <td>0.00631</td>\n      <td>0.002925</td>\n      <td>-0.007352</td>\n      <td>0.008641</td>\n      <td>-0.038542</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.006622</td>\n      <td>-0.001221</td>\n      <td>-0.000178</td>\n      <td>0.002632</td>\n      <td>0.000758</td>\n      <td>0.00916</td>\n      <td>0.007962</td>\n      <td>0.008392</td>\n      <td>-0.001293</td>\n      <td>-0.004359</td>\n      <td>-0.010352</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0.011443</td>\n      <td>-0.003068</td>\n      <td>-0.004101</td>\n      <td>0.001881</td>\n      <td>0.001777</td>\n      <td>0.005978</td>\n      <td>0.001063</td>\n      <td>0.004835</td>\n      <td>-0.002413</td>\n      <td>0.000799</td>\n      <td>-0.004831</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0.004323</td>\n      <td>-0.005825</td>\n      <td>0.000091</td>\n      <td>0.00042</td>\n      <td>-0.002892</td>\n      <td>-0.000686</td>\n      <td>0.00123</td>\n      <td>0.002731</td>\n      <td>-0.004258</td>\n      <td>-0.002813</td>\n      <td>-0.006835</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>0.007548</td>\n      <td>-0.005569</td>\n      <td>-0.00101</td>\n      <td>-0.002053</td>\n      <td>-0.004033</td>\n      <td>0.001196</td>\n      <td>0.000351</td>\n      <td>-0.003022</td>\n      <td>0.00475</td>\n      <td>-0.00051</td>\n      <td>-0.028943</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>0.005271</td>\n      <td>-0.005497</td>\n      <td>-0.001595</td>\n      <td>-0.000909</td>\n      <td>-0.006777</td>\n      <td>0.00702</td>\n      <td>0.000757</td>\n      <td>-0.004006</td>\n      <td>-0.013887</td>\n      <td>0.000157</td>\n      <td>-0.032707</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>0.007237</td>\n      <td>-0.004455</td>\n      <td>-0.006842</td>\n      <td>-0.000847</td>\n      <td>-0.004233</td>\n      <td>0.002475</td>\n      <td>0.004029</td>\n      <td>0.002705</td>\n      <td>-0.006041</td>\n      <td>-0.000705</td>\n      <td>-0.034017</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.006399</td>\n      <td>-0.006739</td>\n      <td>-0.003964</td>\n      <td>-0.001614</td>\n      <td>0.001471</td>\n      <td>-0.004751</td>\n      <td>-0.000544</td>\n      <td>0.001677</td>\n      <td>-0.004262</td>\n      <td>-0.001848</td>\n      <td>-0.002259</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>0.002128</td>\n      <td>-0.003844</td>\n      <td>-0.004521</td>\n      <td>0.003023</td>\n      <td>-0.005343</td>\n      <td>0.006551</td>\n      <td>0.004729</td>\n      <td>0.000891</td>\n      <td>0.001353</td>\n      <td>-0.004274</td>\n      <td>-0.005001</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>0.002028</td>\n      <td>-0.006251</td>\n      <td>0.001014</td>\n      <td>-0.004072</td>\n      <td>-0.000999</td>\n      <td>0.001618</td>\n      <td>0.000193</td>\n      <td>-0.007897</td>\n      <td>-0.002905</td>\n      <td>-0.004985</td>\n      <td>-0.009041</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>0.002499</td>\n      <td>-0.004634</td>\n      <td>0.003188</td>\n      <td>-0.005132</td>\n      <td>-0.004965</td>\n      <td>0.006515</td>\n      <td>0.001243</td>\n      <td>-0.012194</td>\n      <td>-0.010153</td>\n      <td>-0.008684</td>\n      <td>-0.017869</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>0.004752</td>\n      <td>-0.003889</td>\n      <td>0.001368</td>\n      <td>0.003177</td>\n      <td>0.005302</td>\n      <td>0.003047</td>\n      <td>0.001169</td>\n      <td>-0.005335</td>\n      <td>-0.005862</td>\n      <td>-0.006693</td>\n      <td>-0.001391</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>0.006164</td>\n      <td>-0.008906</td>\n      <td>-0.005824</td>\n      <td>0.001187</td>\n      <td>-0.0038</td>\n      <td>0.00797</td>\n      <td>0.004833</td>\n      <td>0.002482</td>\n      <td>-0.00693</td>\n      <td>-0.004475</td>\n      <td>-0.006643</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>0.003021</td>\n      <td>-0.008492</td>\n      <td>-0.002728</td>\n      <td>-0.004721</td>\n      <td>0.000146</td>\n      <td>0.001244</td>\n      <td>-0.001826</td>\n      <td>-0.011347</td>\n      <td>-0.002271</td>\n      <td>-0.003724</td>\n      <td>-0.005624</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>0.00713</td>\n      <td>-0.00268</td>\n      <td>-0.002117</td>\n      <td>-0.0014</td>\n      <td>-0.002143</td>\n      <td>0.007368</td>\n      <td>0.003498</td>\n      <td>-0.0006</td>\n      <td>0.001028</td>\n      <td>-0.005841</td>\n      <td>-0.009565</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_panel=return_board.drop(return_board.columns[0],axis=1)\n",
    "y_panel.rename(columns=lambda x:int(x-1),inplace=True)\n",
    "y_panel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                   y            p1            p2  dummy-stock-0  \\\nstock year                                                        \n0     0     0.005773 -6.894123e+10  5.502837e+10            1.0   \n      1    -0.002174  9.845070e+08  7.987303e+10            1.0   \n      2    -0.011488 -1.279340e+11  8.207607e+10            1.0   \n      3    -0.003769 -8.280000e+10  1.000000e+11            1.0   \n      4    -0.008502 -9.816000e+10  1.810000e+11            1.0   \n...              ...           ...           ...            ...   \n15    6     0.003498 -1.174080e+12  5.218950e+10            0.0   \n      7    -0.000600 -1.191440e+12  7.367929e+10            0.0   \n      8     0.001028 -1.148510e+12  6.111160e+10            0.0   \n      9    -0.005841 -1.075820e+12  6.936214e+10            0.0   \n      10   -0.009565 -7.523680e+11  6.024817e+10            0.0   \n\n            dummy-stock-1  dummy-stock-2  dummy-stock-3  dummy-stock-4  \\\nstock year                                                               \n0     0               0.0            0.0            0.0            0.0   \n      1               0.0            0.0            0.0            0.0   \n      2               0.0            0.0            0.0            0.0   \n      3               0.0            0.0            0.0            0.0   \n      4               0.0            0.0            0.0            0.0   \n...                   ...            ...            ...            ...   \n15    6               0.0            0.0            0.0            0.0   \n      7               0.0            0.0            0.0            0.0   \n      8               0.0            0.0            0.0            0.0   \n      9               0.0            0.0            0.0            0.0   \n      10              0.0            0.0            0.0            0.0   \n\n            dummy-stock-5  dummy-stock-6  ...  dummy-year-0  dummy-year-1  \\\nstock year                                ...                               \n0     0               0.0            0.0  ...           1.0           0.0   \n      1               0.0            0.0  ...           0.0           1.0   \n      2               0.0            0.0  ...           0.0           0.0   \n      3               0.0            0.0  ...           0.0           0.0   \n      4               0.0            0.0  ...           0.0           0.0   \n...                   ...            ...  ...           ...           ...   \n15    6               0.0            0.0  ...           0.0           0.0   \n      7               0.0            0.0  ...           0.0           0.0   \n      8               0.0            0.0  ...           0.0           0.0   \n      9               0.0            0.0  ...           0.0           0.0   \n      10              0.0            0.0  ...           0.0           0.0   \n\n            dummy-year-2  dummy-year-3  dummy-year-4  dummy-year-5  \\\nstock year                                                           \n0     0              0.0           0.0           0.0           0.0   \n      1              0.0           0.0           0.0           0.0   \n      2              1.0           0.0           0.0           0.0   \n      3              0.0           1.0           0.0           0.0   \n      4              0.0           0.0           1.0           0.0   \n...                  ...           ...           ...           ...   \n15    6              0.0           0.0           0.0           0.0   \n      7              0.0           0.0           0.0           0.0   \n      8              0.0           0.0           0.0           0.0   \n      9              0.0           0.0           0.0           0.0   \n      10             0.0           0.0           0.0           0.0   \n\n            dummy-year-6  dummy-year-7  dummy-year-8  dummy-year-9  \nstock year                                                          \n0     0              0.0           0.0           0.0           0.0  \n      1              0.0           0.0           0.0           0.0  \n      2              0.0           0.0           0.0           0.0  \n      3              0.0           0.0           0.0           0.0  \n      4              0.0           0.0           0.0           0.0  \n...                  ...           ...           ...           ...  \n15    6              1.0           0.0           0.0           0.0  \n      7              0.0           1.0           0.0           0.0  \n      8              0.0           0.0           1.0           0.0  \n      9              0.0           0.0           0.0           1.0  \n      10             0.0           0.0           0.0           0.0  \n\n[176 rows x 28 columns]",
      "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>y</th>\n      <th>p1</th>\n      <th>p2</th>\n      <th>dummy-stock-0</th>\n      <th>dummy-stock-1</th>\n      <th>dummy-stock-2</th>\n      <th>dummy-stock-3</th>\n      <th>dummy-stock-4</th>\n      <th>dummy-stock-5</th>\n      <th>dummy-stock-6</th>\n      <th>...</th>\n      <th>dummy-year-0</th>\n      <th>dummy-year-1</th>\n      <th>dummy-year-2</th>\n      <th>dummy-year-3</th>\n      <th>dummy-year-4</th>\n      <th>dummy-year-5</th>\n      <th>dummy-year-6</th>\n      <th>dummy-year-7</th>\n      <th>dummy-year-8</th>\n      <th>dummy-year-9</th>\n    </tr>\n    <tr>\n      <th>stock</th>\n      <th>year</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 rowspan=\"5\" valign=\"top\">0</th>\n      <th>0</th>\n      <td>0.005773</td>\n      <td>-6.894123e+10</td>\n      <td>5.502837e+10</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-0.002174</td>\n      <td>9.845070e+08</td>\n      <td>7.987303e+10</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>-0.011488</td>\n      <td>-1.279340e+11</td>\n      <td>8.207607e+10</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>-0.003769</td>\n      <td>-8.280000e+10</td>\n      <td>1.000000e+11</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>-0.008502</td>\n      <td>-9.816000e+10</td>\n      <td>1.810000e+11</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\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      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">15</th>\n      <th>6</th>\n      <td>0.003498</td>\n      <td>-1.174080e+12</td>\n      <td>5.218950e+10</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>-0.000600</td>\n      <td>-1.191440e+12</td>\n      <td>7.367929e+10</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>0.001028</td>\n      <td>-1.148510e+12</td>\n      <td>6.111160e+10</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>-0.005841</td>\n      <td>-1.075820e+12</td>\n      <td>6.936214e+10</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>1.0</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>-0.009565</td>\n      <td>-7.523680e+11</td>\n      <td>6.024817e+10</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n    </tr>\n  </tbody>\n</table>\n<p>176 rows × 28 columns</p>\n</div>"
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years = y_panel.columns\n",
    "stocks = y_panel.index\n",
    "\n",
    "# 创建多索引数据框\n",
    "multi_index = pd.MultiIndex.from_product([stocks, years], names=['stock', 'year'])\n",
    "\n",
    "# 初始化面板数据框\n",
    "panel_data = pd.DataFrame(index=multi_index, columns=['y', 'p1', 'p2'])\n",
    "\n",
    "# 填充面板数据框\n",
    "for stock in stocks:\n",
    "    for year in years:\n",
    "        panel_data.loc[(stock, year), 'y'] = y_panel.loc[stock, year]\n",
    "        panel_data.loc[(stock, year), 'p1'] = p1.loc[stock, year]\n",
    "        panel_data.loc[(stock, year), 'p2'] = p2.loc[stock, year]\n",
    "        for i in range(len(y_panel.index)-1):\n",
    "            panel_data.loc[(stock,year),'dummy-stock-'+str(i)] = 1 if i==stock else 0\n",
    "        for i in range(len(y_panel.columns)-1):\n",
    "            panel_data.loc[(stock,year),'dummy-year-'+str(i)] = 1 if i==year else 0\n",
    "# 转换为linearmodels库可识别的格式\n",
    "panel_data = panel_data.astype(np.float64)\n",
    "panel_data = panel_data.reset_index().set_index(['stock', 'year'])\n",
    "panel_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "dummy1=['dummy-stock-'+str(i) for i in range(len(y_panel.index)-1)]\n",
    "dummy2=['dummy-year-'+str(i) for i in range(len(y_panel.columns)-1)]\n",
    "\n",
    "const_col = pd.DataFrame(np.ones((len(panel_data), 1)), index=panel_data.index, columns=['const'])\n",
    "panel_data = pd.concat([const_col,panel_data], axis=1)\n",
    "\n",
    "col_names = ['const','p1', 'p2'] + list(dummy1+dummy2)\n",
    "mod = PanelOLS(panel_data.y, panel_data[col_names],check_rank=False)\n",
    "res = mod.fit()\n",
    "\n",
    "# 输出回归结果\n",
    "print(res)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
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