obb_02-10_modules_quant-analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 02.10 Modules: Quantitative Analysis\n",
    "\n",
    "> https://docs.openbb.co/sdk/guides/intros/quantitative-analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `openbb.qa.acf` - `Plot` - Auto and Partial Correlation of Returns and Change in Returns\n",
    "- `openbb.qa.bw` - `Plot` - Box and Whisker Plot\n",
    "- `openbb.qa.calculate_adjusted_var` - `Risk` - Calculates VaR, adjusted for skew and kurtosis (Cornish-Fisher-Expansion)\n",
    "- `openbb.qa.cdf` - `Plot` - Plots the Cumulative Distribution Function\n",
    "- `openbb.qa.cusum` - `Plot` - Plots the Cumulative Sum Algorithm\n",
    "- `openbb.qa.decompose` - `Plot` - Decomposition in Cyclic-Trend, Season & Residuals of Prices\n",
    "- `openbb.qa.es` - `Statistics` - Expected Shortfall per percentile\n",
    "- `openbb.qa.kurtosis` - `Rolling Metrics` - Rolling Kurtosis of Distribution of Prices\n",
    "- `openbb.qa.line` - `Plot` - Customizable Line Plot, With Annotations\n",
    "- `openbb.qa.normality` - `Statistics` - Normality Statistics and Tests\n",
    "- `openbb.qa.omega` - `Risk` - Omega Ratio (Risk/Return Performance Measure)\n",
    "- `openbb.qa.quantile` - `Rolling Metrics` - Rolling Median and Quantile of Prices\n",
    "- `openbb.qa.qqplot` - `Plot` - QQ Plot for Data Against Normal Quantiles\n",
    "- `openbb.qa.rolling` - `Rolling Metrics` - Rolling Mean and Standard Deviation of Prices\n",
    "- `openbb.qa.sharpe` - `Risk` - Sharpe Ratio (Measure of Risk-Adjusted Return)\n",
    "- `openbb.qa.skew` - `Rolling Metrics` - Rolling Skewness of Distribution of Prices\n",
    "- `openbb.qa.spread` - `Rolling Metrics` - Rolling Variance and Standard Deviation of Prices\n",
    "- `openbb.qa.so` - `Risk` - Sortino Ratio Risk Adjustment Metric\n",
    "- `openbb.qa.summary` - `Statistics` - A Brief Summary of Statistics for the DataFrame\n",
    "- `openbb.qa.unitroot` - `Statistics` - Normality Statistics and Tests\n",
    "- `openbb.qa.var` - `Risk` - Value at Risk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import quandl\n",
    "import pandas as pd\n",
    "from openbb_terminal.sdk import openbb\n",
    "from openbb_terminal import config_terminal as cfg\n",
    "\n",
    "# %matplotlib inline (uncomment if using a Jupyter environment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on Breadcrumb in module openbb_terminal.core.library.breadcrumb:\n",
      "\n",
      "<openbb_terminal.core.library.breadcrumb.Breadcrumb object>\n",
      "    QA Menu\n",
      "    \n",
      "    The SDK commands of the the menu:\n",
      "            <openbb>.qa.cdf\n",
      "            <openbb>.qa.spread\n",
      "            <openbb>.qa.spread_chart\n",
      "            <openbb>.qa.acf\n",
      "            <openbb>.qa.es\n",
      "            <openbb>.qa.es_chart\n",
      "            <openbb>.qa.quantile\n",
      "            <openbb>.qa.quantile_chart\n",
      "            <openbb>.qa.omega\n",
      "            <openbb>.qa.omega_chart\n",
      "            <openbb>.qa.skew\n",
      "            <openbb>.qa.skew_chart\n",
      "            <openbb>.qa.kurtosis\n",
      "            <openbb>.qa.kurtosis_chart\n",
      "            <openbb>.qa.summary\n",
      "            <openbb>.qa.summary_chart\n",
      "            <openbb>.qa.rolling\n",
      "            <openbb>.qa.rolling_chart\n",
      "            <openbb>.qa.var\n",
      "            <openbb>.qa.var_chart\n",
      "            <openbb>.qa.sharpe\n",
      "            <openbb>.qa.sharpe_chart\n",
      "            <openbb>.qa.calculate_adjusted_var\n",
      "            <openbb>.qa.sortino\n",
      "            <openbb>.qa.sortino_chart\n",
      "            <openbb>.qa.cusum\n",
      "            <openbb>.qa.qqplot\n",
      "            <openbb>.qa.hist\n",
      "            <openbb>.qa.decompose\n",
      "            <openbb>.qa.line\n",
      "            <openbb>.qa.normality\n",
      "            <openbb>.qa.normality_chart\n",
      "            <openbb>.qa.unitroot\n",
      "            <openbb>.qa.unitroot_chart\n",
      "            <openbb>.qa.bw\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(openbb.qa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>S&amp;P Inflation-Adjusted Value</th>\n",
       "      <th>S&amp;P 500 % Change</th>\n",
       "      <th>P/E Ratio</th>\n",
       "      <th>P/E % Change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1871-01-31</th>\n",
       "      <td>106.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871-02-28</th>\n",
       "      <td>104.34</td>\n",
       "      <td>-0.016495</td>\n",
       "      <td>10.92</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871-03-31</th>\n",
       "      <td>105.33</td>\n",
       "      <td>0.009488</td>\n",
       "      <td>11.19</td>\n",
       "      <td>0.024725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871-04-30</th>\n",
       "      <td>112.35</td>\n",
       "      <td>0.066648</td>\n",
       "      <td>12.05</td>\n",
       "      <td>0.076854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1871-05-31</th>\n",
       "      <td>117.92</td>\n",
       "      <td>0.049577</td>\n",
       "      <td>12.59</td>\n",
       "      <td>0.044813</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>2022-09-30</th>\n",
       "      <td>3585.62</td>\n",
       "      <td>-0.093396</td>\n",
       "      <td>26.84</td>\n",
       "      <td>-0.094467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-31</th>\n",
       "      <td>3871.98</td>\n",
       "      <td>0.079863</td>\n",
       "      <td>28.53</td>\n",
       "      <td>0.062966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-11-30</th>\n",
       "      <td>4080.11</td>\n",
       "      <td>0.053753</td>\n",
       "      <td>29.90</td>\n",
       "      <td>0.048020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>3912.38</td>\n",
       "      <td>-0.041109</td>\n",
       "      <td>28.65</td>\n",
       "      <td>-0.041806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-31</th>\n",
       "      <td>3824.14</td>\n",
       "      <td>-0.022554</td>\n",
       "      <td>27.96</td>\n",
       "      <td>-0.024084</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1825 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            S&P Inflation-Adjusted Value  S&P 500 % Change  P/E Ratio  \\\n",
       "Date                                                                    \n",
       "1871-01-31                        106.09               NaN        NaN   \n",
       "1871-02-28                        104.34         -0.016495      10.92   \n",
       "1871-03-31                        105.33          0.009488      11.19   \n",
       "1871-04-30                        112.35          0.066648      12.05   \n",
       "1871-05-31                        117.92          0.049577      12.59   \n",
       "...                                  ...               ...        ...   \n",
       "2022-09-30                       3585.62         -0.093396      26.84   \n",
       "2022-10-31                       3871.98          0.079863      28.53   \n",
       "2022-11-30                       4080.11          0.053753      29.90   \n",
       "2022-12-31                       3912.38         -0.041109      28.65   \n",
       "2023-01-31                       3824.14         -0.022554      27.96   \n",
       "\n",
       "            P/E % Change  \n",
       "Date                      \n",
       "1871-01-31           NaN  \n",
       "1871-02-28           NaN  \n",
       "1871-03-31      0.024725  \n",
       "1871-04-30      0.076854  \n",
       "1871-05-31      0.044813  \n",
       "...                  ...  \n",
       "2022-09-30     -0.094467  \n",
       "2022-10-31      0.062966  \n",
       "2022-11-30      0.048020  \n",
       "2022-12-31     -0.041806  \n",
       "2023-01-31     -0.024084  \n",
       "\n",
       "[1825 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing os module \n",
    "import os\n",
    "\n",
    "# get environment variable API KEY \n",
    "NASDAQ_QUANDL_DATA_LINK = os.environ.get('NASDAQ_QUANDL_DATA_LINK')\n",
    "\n",
    "# Get data from Nasdaq Data Link\n",
    "shiller_pe_rdiff = quandl.get('MULTPL/SHILLER_PE_RATIO_MONTH', collapse = 'monthly', transform = 'rdiff', api_key = NASDAQ_QUANDL_DATA_LINK)\n",
    "shiller_pe_rdiff.rename(columns={'Value':'P/E % Change'}, inplace = True)\n",
    "shiller_pe_ratio = quandl.get('MULTPL/SHILLER_PE_RATIO_MONTH', collapse = 'monthly', api_key = NASDAQ_QUANDL_DATA_LINK)\n",
    "shiller_pe_ratio.rename(columns={'Value':'P/E Ratio'}, inplace = True)\n",
    "\n",
    "sp500_inf_adj = quandl.get('MULTPL/SP500_INFLADJ_MONTH', collapse = 'monthly', api_key = NASDAQ_QUANDL_DATA_LINK)\n",
    "sp500_inf_adj.rename(columns = {'Value': 'S&P Inflation-Adjusted Value'}, inplace = True)\n",
    "sp500_inf_adj_rdiff = quandl.get('MULTPL/SP500_INFLADJ_MONTH', collapse = 'monthly', transform = 'rdiff', api_key = NASDAQ_QUANDL_DATA_LINK)\n",
    "sp500_inf_adj_rdiff.rename(columns = {'Value':'S&P 500 % Change'}, inplace = True)\n",
    "\n",
    "shiller_pe = shiller_pe_ratio.join(shiller_pe_rdiff)\n",
    "sp500_inf_adj = sp500_inf_adj.join(sp500_inf_adj_rdiff)\n",
    "\n",
    "sp500_df = sp500_inf_adj.join(shiller_pe)\n",
    "\n",
    "sp500_df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statistical Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>S&amp;P Inflation-Adjusted Value</th>\n",
       "      <th>S&amp;P 500 % Change</th>\n",
       "      <th>P/E Ratio</th>\n",
       "      <th>P/E % Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1825.000000</td>\n",
       "      <td>1824.000000</td>\n",
       "      <td>1824.000000</td>\n",
       "      <td>1823.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>702.937173</td>\n",
       "      <td>0.002865</td>\n",
       "      <td>17.004693</td>\n",
       "      <td>0.001363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>842.944046</td>\n",
       "      <td>0.042523</td>\n",
       "      <td>7.078427</td>\n",
       "      <td>0.041228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>80.550000</td>\n",
       "      <td>-0.264725</td>\n",
       "      <td>4.780000</td>\n",
       "      <td>-0.268992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10%</th>\n",
       "      <td>152.984000</td>\n",
       "      <td>-0.044699</td>\n",
       "      <td>9.310000</td>\n",
       "      <td>-0.044929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>204.170000</td>\n",
       "      <td>-0.017292</td>\n",
       "      <td>11.700000</td>\n",
       "      <td>-0.018396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>311.330000</td>\n",
       "      <td>0.005533</td>\n",
       "      <td>15.905000</td>\n",
       "      <td>0.004470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>782.930000</td>\n",
       "      <td>0.026003</td>\n",
       "      <td>20.562500</td>\n",
       "      <td>0.024679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90%</th>\n",
       "      <td>1918.560000</td>\n",
       "      <td>0.045094</td>\n",
       "      <td>26.477000</td>\n",
       "      <td>0.042664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4801.350000</td>\n",
       "      <td>0.514179</td>\n",
       "      <td>44.190000</td>\n",
       "      <td>0.511986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>var</th>\n",
       "      <td>710554.664224</td>\n",
       "      <td>0.001808</td>\n",
       "      <td>50.104124</td>\n",
       "      <td>0.001700</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       S&P Inflation-Adjusted Value  S&P 500 % Change    P/E Ratio  \\\n",
       "count                   1825.000000       1824.000000  1824.000000   \n",
       "mean                     702.937173          0.002865    17.004693   \n",
       "std                      842.944046          0.042523     7.078427   \n",
       "min                       80.550000         -0.264725     4.780000   \n",
       "10%                      152.984000         -0.044699     9.310000   \n",
       "25%                      204.170000         -0.017292    11.700000   \n",
       "50%                      311.330000          0.005533    15.905000   \n",
       "75%                      782.930000          0.026003    20.562500   \n",
       "90%                     1918.560000          0.045094    26.477000   \n",
       "max                     4801.350000          0.514179    44.190000   \n",
       "var                   710554.664224          0.001808    50.104124   \n",
       "\n",
       "       P/E % Change  \n",
       "count   1823.000000  \n",
       "mean       0.001363  \n",
       "std        0.041228  \n",
       "min       -0.268992  \n",
       "10%       -0.044929  \n",
       "25%       -0.018396  \n",
       "50%        0.004470  \n",
       "75%        0.024679  \n",
       "90%        0.042664  \n",
       "max        0.511986  \n",
       "var        0.001700  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "openbb.qa.summary(sp500_df)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spread"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>S&amp;P Inflation-Adjusted Value</th>\n",
       "      <th>S&amp;P 500 % Change</th>\n",
       "      <th>P/E Ratio</th>\n",
       "      <th>P/E % Change</th>\n",
       "      <th>Three-Month Standard Deviation</th>\n",
       "      <th>Three-Month Variance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>3912.38</td>\n",
       "      <td>-0.041109</td>\n",
       "      <td>28.65</td>\n",
       "      <td>-0.041806</td>\n",
       "      <td>0.063659</td>\n",
       "      <td>0.004052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-31</th>\n",
       "      <td>3824.14</td>\n",
       "      <td>-0.022554</td>\n",
       "      <td>27.96</td>\n",
       "      <td>-0.024084</td>\n",
       "      <td>0.050276</td>\n",
       "      <td>0.002528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            S&P Inflation-Adjusted Value  S&P 500 % Change  P/E Ratio  \\\n",
       "date                                                                    \n",
       "2022-12-31                       3912.38         -0.041109      28.65   \n",
       "2023-01-31                       3824.14         -0.022554      27.96   \n",
       "\n",
       "            P/E % Change  Three-Month Standard Deviation  Three-Month Variance  \n",
       "date                                                                            \n",
       "2022-12-31     -0.041806                        0.063659              0.004052  \n",
       "2023-01-31     -0.024084                        0.050276              0.002528  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "std,variance = openbb.qa.spread(data = sp500_df['S&P 500 % Change'], window = 3)\n",
    "\n",
    "std.rename(columns = {'STDEV_3':'Three-Month Standard Deviation'}, inplace = True)\n",
    "variance.rename(columns = {'VAR_3': 'Three-Month Variance'}, inplace =True)\n",
    "\n",
    "sp500_df = sp500_df.join([std,variance])\n",
    "sp500_df.rename_axis('date', inplace = True)\n",
    "\n",
    "sp500_df.tail(2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rolling Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "openbb.qa.rolling_chart(sp500_df, target = 'P/E Ratio', window = 60, symbol = '')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit Root Test\n",
    "\n",
    "> The null hypothesis is that the series contains a unit root, and the alternative is that the series is stationary.\n",
    "> https://www.stata.com/features/overview/panel-data-unit-root-tests/\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ADF</th>\n",
       "      <th>KPSS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Test Statistic</th>\n",
       "      <td>-1.071523e+01</td>\n",
       "      <td>0.340613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P-Value</th>\n",
       "      <td>3.254300e-19</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NLags</th>\n",
       "      <td>2.000000e+01</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nobs</th>\n",
       "      <td>1.802000e+03</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ICBest</th>\n",
       "      <td>-6.497543e+03</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         ADF      KPSS\n",
       "Test Statistic -1.071523e+01  0.340613\n",
       "P-Value         3.254300e-19       0.1\n",
       "NLags           2.000000e+01         2\n",
       "Nobs            1.802000e+03          \n",
       "ICBest         -6.497543e+03          "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "openbb.qa.unitroot(sp500_df['P/E % Change'])"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "obb",
   "language": "python",
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