{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/cyrus723/my-first-binder/blob/main/regression_FactSet3.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Source: FactSet, searching for all S&P500 company PE ratio, no theoretical justification regarding the model specification"
      ],
      "metadata": {
        "id": "TQXcsiSyMtj6"
      },
      "id": "TQXcsiSyMtj6"
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "id": "4efee966-1f45-44e6-9f0c-37ba284e366b",
      "metadata": {
        "id": "4efee966-1f45-44e6-9f0c-37ba284e366b"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from pylab import mpl, plt\n",
        "import statsmodels.formula.api as smf\n",
        "import statsmodels.api as sm\n",
        "plt.style.use('seaborn')\n",
        "mpl.rcParams['font.family'] = 'serif'\n",
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "id": "e7c64e59-e05f-4c95-91fd-5734f40908ee",
      "metadata": {
        "id": "e7c64e59-e05f-4c95-91fd-5734f40908ee",
        "outputId": "c82621dc-ea56-4324-faa3-27d675192003",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'/content'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 37
        }
      ],
      "source": [
        "import os \n",
        "os.getcwd()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "id": "2bfd132b-f851-4651-9788-d04f8d19c569",
      "metadata": {
        "id": "2bfd132b-f851-4651-9788-d04f8d19c569",
        "outputId": "992adb53-5bf0-4da6-e9a7-0fb674cce82b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 536
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Symbol                          Name  beta    roe      de     pe     ps  \\\n",
              "0      MMM                    3M Company  0.89  42.42  121.74  17.56   2.94   \n",
              "1      AOS       A. O. Smith Corporation  1.10  26.47   12.59  28.43   3.91   \n",
              "2      ABT           Abbott Laboratories  0.75  20.53   53.77  35.75   5.85   \n",
              "..     ...                           ...   ...    ...     ...    ...    ...   \n",
              "501    ZBH  Zimmer Biomet Holdings, Inc.  1.13   3.23   58.12  66.55   3.41   \n",
              "502   ZION    Zions Bancorporation, N.A.  1.25  14.55   28.63   9.30   3.42   \n",
              "503    ZTS          Zoetis, Inc. Class A  0.83  49.01  149.33  57.11  14.96   \n",
              "\n",
              "      pfcf         mv     gm  ...  cap_s    dy    cr   cur  naics    eps  \\\n",
              "0    17.77  101576.90  46.99  ...   4.53  3.33  0.53  1.70     31  10.12   \n",
              "1    24.47   13534.47  37.07  ...   2.12  1.23  0.56  1.57     31   3.02   \n",
              "2    29.11  248276.90  53.89  ...   4.38  1.29  0.78  1.85     31   3.94   \n",
              "..     ...        ...    ...  ...    ...   ...   ...   ...    ...    ...   \n",
              "501  26.07   26551.36  62.28  ...   6.45  0.76  0.14  1.41     31   1.91   \n",
              "502  19.61    9576.64    NaN  ...   6.97  2.28  0.01  0.32     52   6.79   \n",
              "503  67.01  115322.30  68.31  ...   6.13  0.44  1.94  3.86     31   4.27   \n",
              "\n",
              "     growth_capitalexp                                       gics_ind  \\\n",
              "0                  0.1                                  Capital Goods   \n",
              "1                  0.0                                  Capital Goods   \n",
              "2                  0.0               Health Care Equipment & Services   \n",
              "..                 ...                                            ...   \n",
              "501                0.0               Health Care Equipment & Services   \n",
              "502                NaN                                          Banks   \n",
              "503                0.0  Pharmaceuticals Biotechnology & Life Sciences   \n",
              "\n",
              "                     fs_sec     gics_sec  \n",
              "0    Producer Manufacturing  Industrials  \n",
              "1    Producer Manufacturing  Industrials  \n",
              "2         Health Technology  Health Care  \n",
              "..                      ...          ...  \n",
              "501       Health Technology  Health Care  \n",
              "502                 Finance   Financials  \n",
              "503       Health Technology  Health Care  \n",
              "\n",
              "[504 rows x 23 columns]"
            ],
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Name</th>\n",
              "      <th>beta</th>\n",
              "      <th>roe</th>\n",
              "      <th>de</th>\n",
              "      <th>pe</th>\n",
              "      <th>ps</th>\n",
              "      <th>pfcf</th>\n",
              "      <th>mv</th>\n",
              "      <th>gm</th>\n",
              "      <th>...</th>\n",
              "      <th>cap_s</th>\n",
              "      <th>dy</th>\n",
              "      <th>cr</th>\n",
              "      <th>cur</th>\n",
              "      <th>naics</th>\n",
              "      <th>eps</th>\n",
              "      <th>growth_capitalexp</th>\n",
              "      <th>gics_ind</th>\n",
              "      <th>fs_sec</th>\n",
              "      <th>gics_sec</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MMM</td>\n",
              "      <td>3M Company</td>\n",
              "      <td>0.89</td>\n",
              "      <td>42.42</td>\n",
              "      <td>121.74</td>\n",
              "      <td>17.56</td>\n",
              "      <td>2.94</td>\n",
              "      <td>17.77</td>\n",
              "      <td>101576.90</td>\n",
              "      <td>46.99</td>\n",
              "      <td>...</td>\n",
              "      <td>4.53</td>\n",
              "      <td>3.33</td>\n",
              "      <td>0.53</td>\n",
              "      <td>1.70</td>\n",
              "      <td>31</td>\n",
              "      <td>10.12</td>\n",
              "      <td>0.1</td>\n",
              "      <td>Capital Goods</td>\n",
              "      <td>Producer Manufacturing</td>\n",
              "      <td>Industrials</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AOS</td>\n",
              "      <td>A. O. Smith Corporation</td>\n",
              "      <td>1.10</td>\n",
              "      <td>26.47</td>\n",
              "      <td>12.59</td>\n",
              "      <td>28.43</td>\n",
              "      <td>3.91</td>\n",
              "      <td>24.47</td>\n",
              "      <td>13534.47</td>\n",
              "      <td>37.07</td>\n",
              "      <td>...</td>\n",
              "      <td>2.12</td>\n",
              "      <td>1.23</td>\n",
              "      <td>0.56</td>\n",
              "      <td>1.57</td>\n",
              "      <td>31</td>\n",
              "      <td>3.02</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Capital Goods</td>\n",
              "      <td>Producer Manufacturing</td>\n",
              "      <td>Industrials</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABT</td>\n",
              "      <td>Abbott Laboratories</td>\n",
              "      <td>0.75</td>\n",
              "      <td>20.53</td>\n",
              "      <td>53.77</td>\n",
              "      <td>35.75</td>\n",
              "      <td>5.85</td>\n",
              "      <td>29.11</td>\n",
              "      <td>248276.90</td>\n",
              "      <td>53.89</td>\n",
              "      <td>...</td>\n",
              "      <td>4.38</td>\n",
              "      <td>1.29</td>\n",
              "      <td>0.78</td>\n",
              "      <td>1.85</td>\n",
              "      <td>31</td>\n",
              "      <td>3.94</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Health Care Equipment &amp; Services</td>\n",
              "      <td>Health Technology</td>\n",
              "      <td>Health Care</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>501</th>\n",
              "      <td>ZBH</td>\n",
              "      <td>Zimmer Biomet Holdings, Inc.</td>\n",
              "      <td>1.13</td>\n",
              "      <td>3.23</td>\n",
              "      <td>58.12</td>\n",
              "      <td>66.55</td>\n",
              "      <td>3.41</td>\n",
              "      <td>26.07</td>\n",
              "      <td>26551.36</td>\n",
              "      <td>62.28</td>\n",
              "      <td>...</td>\n",
              "      <td>6.45</td>\n",
              "      <td>0.76</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.41</td>\n",
              "      <td>31</td>\n",
              "      <td>1.91</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Health Care Equipment &amp; Services</td>\n",
              "      <td>Health Technology</td>\n",
              "      <td>Health Care</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>ZION</td>\n",
              "      <td>Zions Bancorporation, N.A.</td>\n",
              "      <td>1.25</td>\n",
              "      <td>14.55</td>\n",
              "      <td>28.63</td>\n",
              "      <td>9.30</td>\n",
              "      <td>3.42</td>\n",
              "      <td>19.61</td>\n",
              "      <td>9576.64</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>6.97</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.32</td>\n",
              "      <td>52</td>\n",
              "      <td>6.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Banks</td>\n",
              "      <td>Finance</td>\n",
              "      <td>Financials</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>Zoetis, Inc. Class A</td>\n",
              "      <td>0.83</td>\n",
              "      <td>49.01</td>\n",
              "      <td>149.33</td>\n",
              "      <td>57.11</td>\n",
              "      <td>14.96</td>\n",
              "      <td>67.01</td>\n",
              "      <td>115322.30</td>\n",
              "      <td>68.31</td>\n",
              "      <td>...</td>\n",
              "      <td>6.13</td>\n",
              "      <td>0.44</td>\n",
              "      <td>1.94</td>\n",
              "      <td>3.86</td>\n",
              "      <td>31</td>\n",
              "      <td>4.27</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Pharmaceuticals Biotechnology &amp; Life Sciences</td>\n",
              "      <td>Health Technology</td>\n",
              "      <td>Health Care</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>504 rows × 23 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cac77cab-865f-4c07-93ae-58f4b452adbc')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-convert {\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ],
      "source": [
        "data = pd.read_csv('https://raw.githubusercontent.com/cyrus723/my-first-binder/main/data/sp500.csv', header=0)  \n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "id": "28e4e30f-477a-4e66-81f9-518120d53f4e",
      "metadata": {
        "id": "28e4e30f-477a-4e66-81f9-518120d53f4e",
        "outputId": "f024af5a-43d9-4000-804f-f618733bf117",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 504 entries, 0 to 503\n",
            "Data columns (total 23 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   Symbol             504 non-null    object \n",
            " 1   Name               504 non-null    object \n",
            " 2   beta               504 non-null    float64\n",
            " 3   roe                478 non-null    float64\n",
            " 4   de                 473 non-null    float64\n",
            " 5   pe                 480 non-null    float64\n",
            " 6   ps                 503 non-null    float64\n",
            " 7   pfcf               456 non-null    float64\n",
            " 8   mv                 499 non-null    float64\n",
            " 9   gm                 452 non-null    float64\n",
            " 10  gsales             504 non-null    float64\n",
            " 11  altman             402 non-null    float64\n",
            " 12  pvol               504 non-null    float64\n",
            " 13  cap_s              501 non-null    float64\n",
            " 14  dy                 500 non-null    float64\n",
            " 15  cr                 454 non-null    float64\n",
            " 16  cur                454 non-null    float64\n",
            " 17  naics              504 non-null    int64  \n",
            " 18  eps                504 non-null    float64\n",
            " 19  growth_capitalexp  455 non-null    float64\n",
            " 20  gics_ind           504 non-null    object \n",
            " 21  fs_sec             504 non-null    object \n",
            " 22  gics_sec           504 non-null    object \n",
            "dtypes: float64(17), int64(1), object(5)\n",
            "memory usage: 90.7+ KB\n"
          ]
        }
      ],
      "source": [
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['cr'].plot.hist()"
      ],
      "metadata": {
        "id": "wNyAw-QAAC6T",
        "outputId": "8c5ddb1e-b178-4ff1-a8a6-d8654cb1c661",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "id": "wNyAw-QAAC6T",
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8ee0d6d090>"
            ]
          },
          "metadata": {},
          "execution_count": 48
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data2=data.loc[(data['pe'] < 200) & (data['gm'] < 10000)]\n",
        "data2.plot.scatter(x='pe', y='gm')"
      ],
      "metadata": {
        "id": "grufkZyHA05b",
        "outputId": "5f243198-abc7-4786-836e-f76b73914ef3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "id": "grufkZyHA05b",
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f8ee08ae610>"
            ]
          },
          "metadata": {},
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "QPG7CYHYA0OF"
      },
      "id": "QPG7CYHYA0OF",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data2=data.dropna(subset=['mv'],axis=0)"
      ],
      "metadata": {
        "id": "b5ru8BAA5Qg9"
      },
      "id": "b5ru8BAA5Qg9",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "-yjR3w_WAyV0"
      },
      "id": "-yjR3w_WAyV0",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 800
        },
        "id": "b-0HdTcN5iHo",
        "outputId": "d465fc0f-86dc-4495-fdf6-1fe256e8c4de"
      },
      "id": "b-0HdTcN5iHo",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Symbol                                    Name  beta    roe      de  \\\n",
              "0      MMM                              3M Company  0.89  42.42  121.74   \n",
              "1      AOS                 A. O. Smith Corporation  1.10  26.47   12.59   \n",
              "2      ABT                     Abbott Laboratories  0.75  20.53   53.77   \n",
              "3     ABBV                            AbbVie, Inc.  0.82  80.52  503.47   \n",
              "4     ABMD                           ABIOMED, Inc.  1.46   9.64     NaN   \n",
              "..     ...                                     ...   ...    ...     ...   \n",
              "499    YUM                       Yum! Brands, Inc.  1.25    NaN     NaN   \n",
              "500   ZBRA  Zebra Technologies Corporation Class A  1.73  32.64   38.37   \n",
              "501    ZBH            Zimmer Biomet Holdings, Inc.  1.13   3.23   58.12   \n",
              "502   ZION              Zions Bancorporation, N.A.  1.25  14.55   28.63   \n",
              "503    ZTS                    Zoetis, Inc. Class A  0.83  49.01  149.33   \n",
              "\n",
              "         pe     ps   pfcf         mv     gm  ...  cap_s    dy    cr   cur  \\\n",
              "0     17.56   2.94  17.77  101576.90  46.99  ...   4.53  3.33  0.53  1.70   \n",
              "1     28.43   3.91  24.47   13534.47  37.07  ...   2.12  1.23  0.56  1.57   \n",
              "2     35.75   5.85  29.11  248276.90  53.89  ...   4.38  1.29  0.78  1.85   \n",
              "3     20.98   4.28  10.94  239432.90  69.49  ...   1.40  3.92  0.28  0.79   \n",
              "4    111.15  14.73    NaN   15086.33  81.76  ...    NaN   NaN  5.48  7.05   \n",
              "..      ...    ...    ...        ...    ...  ...    ...   ...   ...   ...   \n",
              "499   26.63   6.37  28.41   40130.54  48.09  ...   3.49  1.44  0.52  1.08   \n",
              "500   38.33   5.70  31.77   31792.77  44.68  ...   1.05  0.00  0.19  0.94   \n",
              "501   66.55   3.41  26.07   26551.36  62.28  ...   6.45  0.76  0.14  1.41   \n",
              "502    9.30   3.42  19.61    9576.64    NaN  ...   6.97  2.28  0.01  0.32   \n",
              "503   57.11  14.96  67.01  115322.30  68.31  ...   6.13  0.44  1.94  3.86   \n",
              "\n",
              "     naics    eps  growth_capitalexp  \\\n",
              "0       31  10.12                0.1   \n",
              "1       31   3.02                0.0   \n",
              "2       31   3.94                0.0   \n",
              "3       31   6.45                1.4   \n",
              "4       31   2.98                0.0   \n",
              "..     ...    ...                ...   \n",
              "499     72   5.22                0.0   \n",
              "500     31  15.53                0.0   \n",
              "501     31   1.91                0.0   \n",
              "502     52   6.79                NaN   \n",
              "503     31   4.27                0.0   \n",
              "\n",
              "                                          gics_ind                  fs_sec  \\\n",
              "0                                    Capital Goods  Producer Manufacturing   \n",
              "1                                    Capital Goods  Producer Manufacturing   \n",
              "2                 Health Care Equipment & Services       Health Technology   \n",
              "3    Pharmaceuticals Biotechnology & Life Sciences       Health Technology   \n",
              "4                 Health Care Equipment & Services       Health Technology   \n",
              "..                                             ...                     ...   \n",
              "499                              Consumer Services       Consumer Services   \n",
              "500                Technology Hardware & Equipment   Electronic Technology   \n",
              "501               Health Care Equipment & Services       Health Technology   \n",
              "502                                          Banks                 Finance   \n",
              "503  Pharmaceuticals Biotechnology & Life Sciences       Health Technology   \n",
              "\n",
              "                   gics_sec  \n",
              "0               Industrials  \n",
              "1               Industrials  \n",
              "2               Health Care  \n",
              "3               Health Care  \n",
              "4               Health Care  \n",
              "..                      ...  \n",
              "499  Consumer Discretionary  \n",
              "500  Information Technology  \n",
              "501             Health Care  \n",
              "502              Financials  \n",
              "503             Health Care  \n",
              "\n",
              "[499 rows x 23 columns]"
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              "      <td>53.89</td>\n",
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              "      <th>4</th>\n",
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              "      <td>Zebra Technologies Corporation Class A</td>\n",
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              "      <td>44.68</td>\n",
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              "      <td>0.76</td>\n",
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              "      <td>1.41</td>\n",
              "      <td>31</td>\n",
              "      <td>1.91</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>Health Care</td>\n",
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              "    <tr>\n",
              "      <th>502</th>\n",
              "      <td>ZION</td>\n",
              "      <td>Zions Bancorporation, N.A.</td>\n",
              "      <td>1.25</td>\n",
              "      <td>14.55</td>\n",
              "      <td>28.63</td>\n",
              "      <td>9.30</td>\n",
              "      <td>3.42</td>\n",
              "      <td>19.61</td>\n",
              "      <td>9576.64</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>6.97</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.32</td>\n",
              "      <td>52</td>\n",
              "      <td>6.79</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Banks</td>\n",
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              "      <td>Financials</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>503</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>Zoetis, Inc. Class A</td>\n",
              "      <td>0.83</td>\n",
              "      <td>49.01</td>\n",
              "      <td>149.33</td>\n",
              "      <td>57.11</td>\n",
              "      <td>14.96</td>\n",
              "      <td>67.01</td>\n",
              "      <td>115322.30</td>\n",
              "      <td>68.31</td>\n",
              "      <td>...</td>\n",
              "      <td>6.13</td>\n",
              "      <td>0.44</td>\n",
              "      <td>1.94</td>\n",
              "      <td>3.86</td>\n",
              "      <td>31</td>\n",
              "      <td>4.27</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Pharmaceuticals Biotechnology &amp; Life Sciences</td>\n",
              "      <td>Health Technology</td>\n",
              "      <td>Health Care</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>499 rows × 23 columns</p>\n",
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          "metadata": {},
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      "id": "5_EYCXcO-wwT",
      "execution_count": null,
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 499 entries, 0 to 503\n",
            "Data columns (total 23 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   Symbol             499 non-null    object \n",
            " 1   Name               499 non-null    object \n",
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            " 11  altman             402 non-null    float64\n",
            " 12  pvol               499 non-null    float64\n",
            " 13  cap_s              498 non-null    float64\n",
            " 14  dy                 497 non-null    float64\n",
            " 15  cr                 449 non-null    float64\n",
            " 16  cur                449 non-null    float64\n",
            " 17  naics              499 non-null    int64  \n",
            " 18  eps                499 non-null    float64\n",
            " 19  growth_capitalexp  450 non-null    float64\n",
            " 20  gics_ind           499 non-null    object \n",
            " 21  fs_sec             499 non-null    object \n",
            " 22  gics_sec           499 non-null    object \n",
            "dtypes: float64(17), int64(1), object(5)\n",
            "memory usage: 93.6+ KB\n"
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      "source": [
        "data2.describe()"
      ],
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          "height": 364
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      "id": "p1TPiaQ4-qx5",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             beta          roe           de          pe          ps  \\\n",
              "count  499.000000   474.000000   469.000000  476.000000  499.000000   \n",
              "mean     1.066092    55.780380   156.405714   36.689853    5.092465   \n",
              "std      0.499602   368.240081   274.977253   48.280792    5.041844   \n",
              "min     -0.430000  -132.810000     0.340000    4.390000    0.100000   \n",
              "25%      0.750000    10.430000    45.560000   15.607500    1.745000   \n",
              "50%      1.060000    18.445000    82.070000   24.845000    3.310000   \n",
              "75%      1.315000    31.650000   149.330000   39.127500    6.380000   \n",
              "max      4.710000  5863.580000  3494.650000  573.370000   27.790000   \n",
              "\n",
              "              pfcf            mv          gm       gsales      altman  \\\n",
              "count   454.000000  4.990000e+02  447.000000   499.000000  402.000000   \n",
              "mean     40.172841  8.570345e+04   40.001790    25.513547    5.025746   \n",
              "std     100.845676  2.190224e+05   29.486308   101.378348    5.998500   \n",
              "min       2.630000  6.376470e+03 -249.200000   -65.900000   -3.080000   \n",
              "25%      13.702500  1.877855e+04   26.575000     6.365000    2.112500   \n",
              "50%      23.945000  3.344233e+04   38.380000    14.350000    3.325000   \n",
              "75%      36.805000  6.918584e+04   56.320000    24.380000    5.420000   \n",
              "max    1473.550000  2.413423e+06   95.840000  2191.900000   55.750000   \n",
              "\n",
              "             pvol       cap_s          dy          cr         cur       naics  \\\n",
              "count  499.000000  498.000000  497.000000  449.000000  449.000000  499.000000   \n",
              "mean     9.571383    8.016365    1.534406    0.650490    1.612183   40.817635   \n",
              "std      3.817050   14.891767    1.438945    0.798887    1.114226   12.558170   \n",
              "min      4.080000    0.000000    0.000000    0.010000    0.050000   11.000000   \n",
              "25%      7.205000    1.937500    0.240000    0.160000    0.930000   31.000000   \n",
              "50%      8.640000    3.760000    1.270000    0.380000    1.330000   42.000000   \n",
              "75%     10.645000    7.845000    2.400000    0.810000    1.940000   52.000000   \n",
              "max     41.850000  189.050000    8.460000    5.480000    7.870000   72.000000   \n",
              "\n",
              "              eps  growth_capitalexp  \n",
              "count  499.000000         450.000000  \n",
              "mean     8.381323          -0.010889  \n",
              "std     19.061651           2.781380  \n",
              "min    -20.890000         -23.700000  \n",
              "25%      2.585000           0.000000  \n",
              "50%      4.940000           0.000000  \n",
              "75%      8.555000           0.000000  \n",
              "max    320.480000          35.600000  "
            ],
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              "\n",
              "  <div id=\"df-ec7b3093-d1e9-46d4-9cb4-cbe8173f3d39\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>beta</th>\n",
              "      <th>roe</th>\n",
              "      <th>de</th>\n",
              "      <th>pe</th>\n",
              "      <th>ps</th>\n",
              "      <th>pfcf</th>\n",
              "      <th>mv</th>\n",
              "      <th>gm</th>\n",
              "      <th>gsales</th>\n",
              "      <th>altman</th>\n",
              "      <th>pvol</th>\n",
              "      <th>cap_s</th>\n",
              "      <th>dy</th>\n",
              "      <th>cr</th>\n",
              "      <th>cur</th>\n",
              "      <th>naics</th>\n",
              "      <th>eps</th>\n",
              "      <th>growth_capitalexp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>499.000000</td>\n",
              "      <td>474.000000</td>\n",
              "      <td>469.000000</td>\n",
              "      <td>476.000000</td>\n",
              "      <td>499.000000</td>\n",
              "      <td>454.000000</td>\n",
              "      <td>4.990000e+02</td>\n",
              "      <td>447.000000</td>\n",
              "      <td>499.000000</td>\n",
              "      <td>402.000000</td>\n",
              "      <td>499.000000</td>\n",
              "      <td>498.000000</td>\n",
              "      <td>497.000000</td>\n",
              "      <td>449.000000</td>\n",
              "      <td>449.000000</td>\n",
              "      <td>499.000000</td>\n",
              "      <td>499.000000</td>\n",
              "      <td>450.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.066092</td>\n",
              "      <td>55.780380</td>\n",
              "      <td>156.405714</td>\n",
              "      <td>36.689853</td>\n",
              "      <td>5.092465</td>\n",
              "      <td>40.172841</td>\n",
              "      <td>8.570345e+04</td>\n",
              "      <td>40.001790</td>\n",
              "      <td>25.513547</td>\n",
              "      <td>5.025746</td>\n",
              "      <td>9.571383</td>\n",
              "      <td>8.016365</td>\n",
              "      <td>1.534406</td>\n",
              "      <td>0.650490</td>\n",
              "      <td>1.612183</td>\n",
              "      <td>40.817635</td>\n",
              "      <td>8.381323</td>\n",
              "      <td>-0.010889</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.499602</td>\n",
              "      <td>368.240081</td>\n",
              "      <td>274.977253</td>\n",
              "      <td>48.280792</td>\n",
              "      <td>5.041844</td>\n",
              "      <td>100.845676</td>\n",
              "      <td>2.190224e+05</td>\n",
              "      <td>29.486308</td>\n",
              "      <td>101.378348</td>\n",
              "      <td>5.998500</td>\n",
              "      <td>3.817050</td>\n",
              "      <td>14.891767</td>\n",
              "      <td>1.438945</td>\n",
              "      <td>0.798887</td>\n",
              "      <td>1.114226</td>\n",
              "      <td>12.558170</td>\n",
              "      <td>19.061651</td>\n",
              "      <td>2.781380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-0.430000</td>\n",
              "      <td>-132.810000</td>\n",
              "      <td>0.340000</td>\n",
              "      <td>4.390000</td>\n",
              "      <td>0.100000</td>\n",
              "      <td>2.630000</td>\n",
              "      <td>6.376470e+03</td>\n",
              "      <td>-249.200000</td>\n",
              "      <td>-65.900000</td>\n",
              "      <td>-3.080000</td>\n",
              "      <td>4.080000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.050000</td>\n",
              "      <td>11.000000</td>\n",
              "      <td>-20.890000</td>\n",
              "      <td>-23.700000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>0.750000</td>\n",
              "      <td>10.430000</td>\n",
              "      <td>45.560000</td>\n",
              "      <td>15.607500</td>\n",
              "      <td>1.745000</td>\n",
              "      <td>13.702500</td>\n",
              "      <td>1.877855e+04</td>\n",
              "      <td>26.575000</td>\n",
              "      <td>6.365000</td>\n",
              "      <td>2.112500</td>\n",
              "      <td>7.205000</td>\n",
              "      <td>1.937500</td>\n",
              "      <td>0.240000</td>\n",
              "      <td>0.160000</td>\n",
              "      <td>0.930000</td>\n",
              "      <td>31.000000</td>\n",
              "      <td>2.585000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.060000</td>\n",
              "      <td>18.445000</td>\n",
              "      <td>82.070000</td>\n",
              "      <td>24.845000</td>\n",
              "      <td>3.310000</td>\n",
              "      <td>23.945000</td>\n",
              "      <td>3.344233e+04</td>\n",
              "      <td>38.380000</td>\n",
              "      <td>14.350000</td>\n",
              "      <td>3.325000</td>\n",
              "      <td>8.640000</td>\n",
              "      <td>3.760000</td>\n",
              "      <td>1.270000</td>\n",
              "      <td>0.380000</td>\n",
              "      <td>1.330000</td>\n",
              "      <td>42.000000</td>\n",
              "      <td>4.940000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1.315000</td>\n",
              "      <td>31.650000</td>\n",
              "      <td>149.330000</td>\n",
              "      <td>39.127500</td>\n",
              "      <td>6.380000</td>\n",
              "      <td>36.805000</td>\n",
              "      <td>6.918584e+04</td>\n",
              "      <td>56.320000</td>\n",
              "      <td>24.380000</td>\n",
              "      <td>5.420000</td>\n",
              "      <td>10.645000</td>\n",
              "      <td>7.845000</td>\n",
              "      <td>2.400000</td>\n",
              "      <td>0.810000</td>\n",
              "      <td>1.940000</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>8.555000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>4.710000</td>\n",
              "      <td>5863.580000</td>\n",
              "      <td>3494.650000</td>\n",
              "      <td>573.370000</td>\n",
              "      <td>27.790000</td>\n",
              "      <td>1473.550000</td>\n",
              "      <td>2.413423e+06</td>\n",
              "      <td>95.840000</td>\n",
              "      <td>2191.900000</td>\n",
              "      <td>55.750000</td>\n",
              "      <td>41.850000</td>\n",
              "      <td>189.050000</td>\n",
              "      <td>8.460000</td>\n",
              "      <td>5.480000</td>\n",
              "      <td>7.870000</td>\n",
              "      <td>72.000000</td>\n",
              "      <td>320.480000</td>\n",
              "      <td>35.600000</td>\n",
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          "metadata": {},
          "execution_count": 30
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      "execution_count": null,
      "id": "04ca0560-f5f0-40e1-8773-79f555fb104e",
      "metadata": {
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          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c8e4eee0-765c-4ad3-f58e-ec1e47d20b03"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ],
      "source": [
        "data2['log_mv'] = np.log(data2['mv'])"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "LJ90vLrb5Aec"
      },
      "id": "LJ90vLrb5Aec",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "vFWpu_vs5AYE"
      },
      "id": "vFWpu_vs5AYE",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "outputId": "97af6223-4e02-4385-ff49-6f2c584f50b1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FaLMIm9F422p"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                            OLS Regression Results                            \n",
            "==============================================================================\n",
            "Dep. Variable:                     pe   R-squared:                       0.194\n",
            "Model:                            OLS   Adj. R-squared:                  0.165\n",
            "Method:                 Least Squares   F-statistic:                     6.776\n",
            "Date:                Thu, 19 May 2022   Prob (F-statistic):           5.88e-11\n",
            "Time:                        20:26:38   Log-Likelihood:                -1795.1\n",
            "No. Observations:                 351   AIC:                             3616.\n",
            "Df Residuals:                     338   BIC:                             3666.\n",
            "Df Model:                          12                                         \n",
            "Covariance Type:            nonrobust                                         \n",
            "==============================================================================\n",
            "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "Intercept    -22.4419     28.073     -0.799      0.425     -77.663      32.779\n",
            "beta          -2.8807      8.362     -0.344      0.731     -19.329      13.568\n",
            "roe           -0.2866      0.081     -3.551      0.000      -0.445      -0.128\n",
            "de             0.0351      0.015      2.387      0.018       0.006       0.064\n",
            "altman         2.4576      0.517      4.752      0.000       1.440       3.475\n",
            "log_mv         4.1409      2.303      1.798      0.073      -0.389       8.670\n",
            "gm             0.2643      0.136      1.943      0.053      -0.003       0.532\n",
            "gsales        -0.0301      0.023     -1.329      0.185      -0.075       0.014\n",
            "pvol           1.8613      1.210      1.538      0.125      -0.519       4.242\n",
            "cap_s          0.1892      0.239      0.792      0.429      -0.281       0.659\n",
            "dy            -4.4782      1.747     -2.564      0.011      -7.914      -1.043\n",
            "cr             5.4418      5.925      0.918      0.359      -6.212      17.096\n",
            "cur           -9.7856      4.203     -2.328      0.020     -18.053      -1.519\n",
            "==============================================================================\n",
            "Omnibus:                      489.711   Durbin-Watson:                   2.116\n",
            "Prob(Omnibus):                  0.000   Jarque-Bera (JB):            72928.702\n",
            "Skew:                           6.818   Prob(JB):                         0.00\n",
            "Kurtosis:                      72.287   Cond. No.                     3.59e+03\n",
            "==============================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
            "[2] The condition number is large, 3.59e+03. This might indicate that there are\n",
            "strong multicollinearity or other numerical problems.\n"
          ]
        }
      ],
      "source": [
        "formula = 'pe ~ beta + roe + de + altman + log_mv + gm + gsales + pvol\t+ cap_s\t+ dy\t+ cr\t+ cur'\n",
        "results = smf.ols(formula, data2).fit()\n",
        "print(results.summary())"
      ],
      "id": "FaLMIm9F422p"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2740154c-e1f0-493c-b29f-eb62e4767d86",
      "metadata": {
        "id": "2740154c-e1f0-493c-b29f-eb62e4767d86"
      },
      "outputs": [],
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3945b46c-c01d-4979-a230-21ef60b6fbbf",
      "metadata": {
        "id": "3945b46c-c01d-4979-a230-21ef60b6fbbf",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 678
        },
        "outputId": "cdc130a6-6c6a-47cd-98d5-4c9d45c7c2c4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       beta       roe        de        pe        ps      pfcf  \\\n",
              "beta               1.000000 -0.079395 -0.092053  0.068494  0.063886 -0.002039   \n",
              "roe               -0.079395  1.000000  0.688829 -0.097493  0.087583 -0.053414   \n",
              "de                -0.092053  0.688829  1.000000 -0.044639 -0.115563  0.095510   \n",
              "pe                 0.068494 -0.097493 -0.044639  1.000000  0.593247  0.327988   \n",
              "ps                 0.063886  0.087583 -0.115563  0.593247  1.000000  0.165828   \n",
              "pfcf              -0.002039 -0.053414  0.095510  0.327988  0.165828  1.000000   \n",
              "mv                 0.018675  0.091196 -0.048443  0.053075  0.214163 -0.002806   \n",
              "gm                -0.101625  0.147294 -0.058295  0.215156  0.621423 -0.087149   \n",
              "gsales             0.159374  0.125849 -0.060532 -0.029283  0.017286 -0.000703   \n",
              "altman             0.054296  0.097988 -0.174033  0.286280  0.706467  0.095019   \n",
              "pvol               0.775831 -0.064803 -0.070414  0.082177  0.051855  0.064714   \n",
              "cap_s              0.028896 -0.130779 -0.041466  0.080169  0.038678  0.122443   \n",
              "dy                -0.222000 -0.019617  0.061359 -0.237169 -0.408821 -0.158816   \n",
              "cr                 0.076676 -0.015204 -0.145291  0.177014  0.480707  0.104814   \n",
              "cur                0.078979 -0.047372 -0.215181  0.078290  0.348642  0.070986   \n",
              "naics              0.039516  0.021315  0.135928  0.103943  0.096871  0.020150   \n",
              "eps               -0.012030  0.090308 -0.036949 -0.094833 -0.014581 -0.040744   \n",
              "growth_capitalexp -0.080412  0.030906  0.031790  0.000932  0.002545 -0.023627   \n",
              "\n",
              "                         mv        gm    gsales    altman      pvol     cap_s  \\\n",
              "beta               0.018675 -0.101625  0.159374  0.054296  0.775831  0.028896   \n",
              "roe                0.091196  0.147294  0.125849  0.097988 -0.064803 -0.130779   \n",
              "de                -0.048443 -0.058295 -0.060532 -0.174033 -0.070414 -0.041466   \n",
              "pe                 0.053075  0.215156 -0.029283  0.286280  0.082177  0.080169   \n",
              "ps                 0.214163  0.621423  0.017286  0.706467  0.051855  0.038678   \n",
              "pfcf              -0.002806 -0.087149 -0.000703  0.095019  0.064714  0.122443   \n",
              "mv                 1.000000  0.161233  0.012807  0.172525 -0.063880  0.101586   \n",
              "gm                 0.161233  1.000000  0.096531  0.357395 -0.047744  0.017925   \n",
              "gsales             0.012807  0.096531  1.000000  0.047899  0.432890  0.004500   \n",
              "altman             0.172525  0.357395  0.047899  1.000000  0.036324 -0.034857   \n",
              "pvol              -0.063880 -0.047744  0.432890  0.036324  1.000000  0.093602   \n",
              "cap_s              0.101586  0.017925  0.004500 -0.034857  0.093602  1.000000   \n",
              "dy                -0.061784 -0.300490 -0.044612 -0.341119 -0.197214  0.113233   \n",
              "cr                 0.166952  0.383953  0.060785  0.552764  0.167022  0.107054   \n",
              "cur                0.047235  0.245208  0.018272  0.541831  0.121421  0.005705   \n",
              "naics              0.074423  0.091483  0.029131 -0.007095 -0.025478 -0.043567   \n",
              "eps                0.222852 -0.001708  0.059474  0.094992 -0.031780 -0.034861   \n",
              "growth_capitalexp  0.015418  0.011326 -0.021103 -0.036804 -0.069099 -0.034913   \n",
              "\n",
              "                         dy        cr       cur     naics       eps  \\\n",
              "beta              -0.222000  0.076676  0.078979  0.039516 -0.012030   \n",
              "roe               -0.019617 -0.015204 -0.047372  0.021315  0.090308   \n",
              "de                 0.061359 -0.145291 -0.215181  0.135928 -0.036949   \n",
              "pe                -0.237169  0.177014  0.078290  0.103943 -0.094833   \n",
              "ps                -0.408821  0.480707  0.348642  0.096871 -0.014581   \n",
              "pfcf              -0.158816  0.104814  0.070986  0.020150 -0.040744   \n",
              "mv                -0.061784  0.166952  0.047235  0.074423  0.222852   \n",
              "gm                -0.300490  0.383953  0.245208  0.091483 -0.001708   \n",
              "gsales            -0.044612  0.060785  0.018272  0.029131  0.059474   \n",
              "altman            -0.341119  0.552764  0.541831 -0.007095  0.094992   \n",
              "pvol              -0.197214  0.167022  0.121421 -0.025478 -0.031780   \n",
              "cap_s              0.113233  0.107054  0.005705 -0.043567 -0.034861   \n",
              "dy                 1.000000 -0.275627 -0.271625 -0.157792 -0.118787   \n",
              "cr                -0.275627  1.000000  0.834780 -0.029683  0.125976   \n",
              "cur               -0.271625  0.834780  1.000000 -0.221567  0.141528   \n",
              "naics             -0.157792 -0.029683 -0.221567  1.000000 -0.029311   \n",
              "eps               -0.118787  0.125976  0.141528 -0.029311  1.000000   \n",
              "growth_capitalexp -0.043085 -0.040837 -0.014548  0.017290  0.044753   \n",
              "\n",
              "                   growth_capitalexp  \n",
              "beta                       -0.080412  \n",
              "roe                         0.030906  \n",
              "de                          0.031790  \n",
              "pe                          0.000932  \n",
              "ps                          0.002545  \n",
              "pfcf                       -0.023627  \n",
              "mv                          0.015418  \n",
              "gm                          0.011326  \n",
              "gsales                     -0.021103  \n",
              "altman                     -0.036804  \n",
              "pvol                       -0.069099  \n",
              "cap_s                      -0.034913  \n",
              "dy                         -0.043085  \n",
              "cr                         -0.040837  \n",
              "cur                        -0.014548  \n",
              "naics                       0.017290  \n",
              "eps                         0.044753  \n",
              "growth_capitalexp           1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a8b68322-4676-4eca-ac93-748ece0f9362\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>beta</th>\n",
              "      <th>roe</th>\n",
              "      <th>de</th>\n",
              "      <th>pe</th>\n",
              "      <th>ps</th>\n",
              "      <th>pfcf</th>\n",
              "      <th>mv</th>\n",
              "      <th>gm</th>\n",
              "      <th>gsales</th>\n",
              "      <th>altman</th>\n",
              "      <th>pvol</th>\n",
              "      <th>cap_s</th>\n",
              "      <th>dy</th>\n",
              "      <th>cr</th>\n",
              "      <th>cur</th>\n",
              "      <th>naics</th>\n",
              "      <th>eps</th>\n",
              "      <th>growth_capitalexp</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>beta</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.079395</td>\n",
              "      <td>-0.092053</td>\n",
              "      <td>0.068494</td>\n",
              "      <td>0.063886</td>\n",
              "      <td>-0.002039</td>\n",
              "      <td>0.018675</td>\n",
              "      <td>-0.101625</td>\n",
              "      <td>0.159374</td>\n",
              "      <td>0.054296</td>\n",
              "      <td>0.775831</td>\n",
              "      <td>0.028896</td>\n",
              "      <td>-0.222000</td>\n",
              "      <td>0.076676</td>\n",
              "      <td>0.078979</td>\n",
              "      <td>0.039516</td>\n",
              "      <td>-0.012030</td>\n",
              "      <td>-0.080412</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>roe</th>\n",
              "      <td>-0.079395</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.688829</td>\n",
              "      <td>-0.097493</td>\n",
              "      <td>0.087583</td>\n",
              "      <td>-0.053414</td>\n",
              "      <td>0.091196</td>\n",
              "      <td>0.147294</td>\n",
              "      <td>0.125849</td>\n",
              "      <td>0.097988</td>\n",
              "      <td>-0.064803</td>\n",
              "      <td>-0.130779</td>\n",
              "      <td>-0.019617</td>\n",
              "      <td>-0.015204</td>\n",
              "      <td>-0.047372</td>\n",
              "      <td>0.021315</td>\n",
              "      <td>0.090308</td>\n",
              "      <td>0.030906</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>de</th>\n",
              "      <td>-0.092053</td>\n",
              "      <td>0.688829</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.044639</td>\n",
              "      <td>-0.115563</td>\n",
              "      <td>0.095510</td>\n",
              "      <td>-0.048443</td>\n",
              "      <td>-0.058295</td>\n",
              "      <td>-0.060532</td>\n",
              "      <td>-0.174033</td>\n",
              "      <td>-0.070414</td>\n",
              "      <td>-0.041466</td>\n",
              "      <td>0.061359</td>\n",
              "      <td>-0.145291</td>\n",
              "      <td>-0.215181</td>\n",
              "      <td>0.135928</td>\n",
              "      <td>-0.036949</td>\n",
              "      <td>0.031790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pe</th>\n",
              "      <td>0.068494</td>\n",
              "      <td>-0.097493</td>\n",
              "      <td>-0.044639</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.593247</td>\n",
              "      <td>0.327988</td>\n",
              "      <td>0.053075</td>\n",
              "      <td>0.215156</td>\n",
              "      <td>-0.029283</td>\n",
              "      <td>0.286280</td>\n",
              "      <td>0.082177</td>\n",
              "      <td>0.080169</td>\n",
              "      <td>-0.237169</td>\n",
              "      <td>0.177014</td>\n",
              "      <td>0.078290</td>\n",
              "      <td>0.103943</td>\n",
              "      <td>-0.094833</td>\n",
              "      <td>0.000932</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ps</th>\n",
              "      <td>0.063886</td>\n",
              "      <td>0.087583</td>\n",
              "      <td>-0.115563</td>\n",
              "      <td>0.593247</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.165828</td>\n",
              "      <td>0.214163</td>\n",
              "      <td>0.621423</td>\n",
              "      <td>0.017286</td>\n",
              "      <td>0.706467</td>\n",
              "      <td>0.051855</td>\n",
              "      <td>0.038678</td>\n",
              "      <td>-0.408821</td>\n",
              "      <td>0.480707</td>\n",
              "      <td>0.348642</td>\n",
              "      <td>0.096871</td>\n",
              "      <td>-0.014581</td>\n",
              "      <td>0.002545</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pfcf</th>\n",
              "      <td>-0.002039</td>\n",
              "      <td>-0.053414</td>\n",
              "      <td>0.095510</td>\n",
              "      <td>0.327988</td>\n",
              "      <td>0.165828</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.002806</td>\n",
              "      <td>-0.087149</td>\n",
              "      <td>-0.000703</td>\n",
              "      <td>0.095019</td>\n",
              "      <td>0.064714</td>\n",
              "      <td>0.122443</td>\n",
              "      <td>-0.158816</td>\n",
              "      <td>0.104814</td>\n",
              "      <td>0.070986</td>\n",
              "      <td>0.020150</td>\n",
              "      <td>-0.040744</td>\n",
              "      <td>-0.023627</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mv</th>\n",
              "      <td>0.018675</td>\n",
              "      <td>0.091196</td>\n",
              "      <td>-0.048443</td>\n",
              "      <td>0.053075</td>\n",
              "      <td>0.214163</td>\n",
              "      <td>-0.002806</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.161233</td>\n",
              "      <td>0.012807</td>\n",
              "      <td>0.172525</td>\n",
              "      <td>-0.063880</td>\n",
              "      <td>0.101586</td>\n",
              "      <td>-0.061784</td>\n",
              "      <td>0.166952</td>\n",
              "      <td>0.047235</td>\n",
              "      <td>0.074423</td>\n",
              "      <td>0.222852</td>\n",
              "      <td>0.015418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>gm</th>\n",
              "      <td>-0.101625</td>\n",
              "      <td>0.147294</td>\n",
              "      <td>-0.058295</td>\n",
              "      <td>0.215156</td>\n",
              "      <td>0.621423</td>\n",
              "      <td>-0.087149</td>\n",
              "      <td>0.161233</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.096531</td>\n",
              "      <td>0.357395</td>\n",
              "      <td>-0.047744</td>\n",
              "      <td>0.017925</td>\n",
              "      <td>-0.300490</td>\n",
              "      <td>0.383953</td>\n",
              "      <td>0.245208</td>\n",
              "      <td>0.091483</td>\n",
              "      <td>-0.001708</td>\n",
              "      <td>0.011326</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>gsales</th>\n",
              "      <td>0.159374</td>\n",
              "      <td>0.125849</td>\n",
              "      <td>-0.060532</td>\n",
              "      <td>-0.029283</td>\n",
              "      <td>0.017286</td>\n",
              "      <td>-0.000703</td>\n",
              "      <td>0.012807</td>\n",
              "      <td>0.096531</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.047899</td>\n",
              "      <td>0.432890</td>\n",
              "      <td>0.004500</td>\n",
              "      <td>-0.044612</td>\n",
              "      <td>0.060785</td>\n",
              "      <td>0.018272</td>\n",
              "      <td>0.029131</td>\n",
              "      <td>0.059474</td>\n",
              "      <td>-0.021103</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>altman</th>\n",
              "      <td>0.054296</td>\n",
              "      <td>0.097988</td>\n",
              "      <td>-0.174033</td>\n",
              "      <td>0.286280</td>\n",
              "      <td>0.706467</td>\n",
              "      <td>0.095019</td>\n",
              "      <td>0.172525</td>\n",
              "      <td>0.357395</td>\n",
              "      <td>0.047899</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.036324</td>\n",
              "      <td>-0.034857</td>\n",
              "      <td>-0.341119</td>\n",
              "      <td>0.552764</td>\n",
              "      <td>0.541831</td>\n",
              "      <td>-0.007095</td>\n",
              "      <td>0.094992</td>\n",
              "      <td>-0.036804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pvol</th>\n",
              "      <td>0.775831</td>\n",
              "      <td>-0.064803</td>\n",
              "      <td>-0.070414</td>\n",
              "      <td>0.082177</td>\n",
              "      <td>0.051855</td>\n",
              "      <td>0.064714</td>\n",
              "      <td>-0.063880</td>\n",
              "      <td>-0.047744</td>\n",
              "      <td>0.432890</td>\n",
              "      <td>0.036324</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.093602</td>\n",
              "      <td>-0.197214</td>\n",
              "      <td>0.167022</td>\n",
              "      <td>0.121421</td>\n",
              "      <td>-0.025478</td>\n",
              "      <td>-0.031780</td>\n",
              "      <td>-0.069099</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cap_s</th>\n",
              "      <td>0.028896</td>\n",
              "      <td>-0.130779</td>\n",
              "      <td>-0.041466</td>\n",
              "      <td>0.080169</td>\n",
              "      <td>0.038678</td>\n",
              "      <td>0.122443</td>\n",
              "      <td>0.101586</td>\n",
              "      <td>0.017925</td>\n",
              "      <td>0.004500</td>\n",
              "      <td>-0.034857</td>\n",
              "      <td>0.093602</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.113233</td>\n",
              "      <td>0.107054</td>\n",
              "      <td>0.005705</td>\n",
              "      <td>-0.043567</td>\n",
              "      <td>-0.034861</td>\n",
              "      <td>-0.034913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dy</th>\n",
              "      <td>-0.222000</td>\n",
              "      <td>-0.019617</td>\n",
              "      <td>0.061359</td>\n",
              "      <td>-0.237169</td>\n",
              "      <td>-0.408821</td>\n",
              "      <td>-0.158816</td>\n",
              "      <td>-0.061784</td>\n",
              "      <td>-0.300490</td>\n",
              "      <td>-0.044612</td>\n",
              "      <td>-0.341119</td>\n",
              "      <td>-0.197214</td>\n",
              "      <td>0.113233</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.275627</td>\n",
              "      <td>-0.271625</td>\n",
              "      <td>-0.157792</td>\n",
              "      <td>-0.118787</td>\n",
              "      <td>-0.043085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cr</th>\n",
              "      <td>0.076676</td>\n",
              "      <td>-0.015204</td>\n",
              "      <td>-0.145291</td>\n",
              "      <td>0.177014</td>\n",
              "      <td>0.480707</td>\n",
              "      <td>0.104814</td>\n",
              "      <td>0.166952</td>\n",
              "      <td>0.383953</td>\n",
              "      <td>0.060785</td>\n",
              "      <td>0.552764</td>\n",
              "      <td>0.167022</td>\n",
              "      <td>0.107054</td>\n",
              "      <td>-0.275627</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.834780</td>\n",
              "      <td>-0.029683</td>\n",
              "      <td>0.125976</td>\n",
              "      <td>-0.040837</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>cur</th>\n",
              "      <td>0.078979</td>\n",
              "      <td>-0.047372</td>\n",
              "      <td>-0.215181</td>\n",
              "      <td>0.078290</td>\n",
              "      <td>0.348642</td>\n",
              "      <td>0.070986</td>\n",
              "      <td>0.047235</td>\n",
              "      <td>0.245208</td>\n",
              "      <td>0.018272</td>\n",
              "      <td>0.541831</td>\n",
              "      <td>0.121421</td>\n",
              "      <td>0.005705</td>\n",
              "      <td>-0.271625</td>\n",
              "      <td>0.834780</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.221567</td>\n",
              "      <td>0.141528</td>\n",
              "      <td>-0.014548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>naics</th>\n",
              "      <td>0.039516</td>\n",
              "      <td>0.021315</td>\n",
              "      <td>0.135928</td>\n",
              "      <td>0.103943</td>\n",
              "      <td>0.096871</td>\n",
              "      <td>0.020150</td>\n",
              "      <td>0.074423</td>\n",
              "      <td>0.091483</td>\n",
              "      <td>0.029131</td>\n",
              "      <td>-0.007095</td>\n",
              "      <td>-0.025478</td>\n",
              "      <td>-0.043567</td>\n",
              "      <td>-0.157792</td>\n",
              "      <td>-0.029683</td>\n",
              "      <td>-0.221567</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.029311</td>\n",
              "      <td>0.017290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>eps</th>\n",
              "      <td>-0.012030</td>\n",
              "      <td>0.090308</td>\n",
              "      <td>-0.036949</td>\n",
              "      <td>-0.094833</td>\n",
              "      <td>-0.014581</td>\n",
              "      <td>-0.040744</td>\n",
              "      <td>0.222852</td>\n",
              "      <td>-0.001708</td>\n",
              "      <td>0.059474</td>\n",
              "      <td>0.094992</td>\n",
              "      <td>-0.031780</td>\n",
              "      <td>-0.034861</td>\n",
              "      <td>-0.118787</td>\n",
              "      <td>0.125976</td>\n",
              "      <td>0.141528</td>\n",
              "      <td>-0.029311</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.044753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>growth_capitalexp</th>\n",
              "      <td>-0.080412</td>\n",
              "      <td>0.030906</td>\n",
              "      <td>0.031790</td>\n",
              "      <td>0.000932</td>\n",
              "      <td>0.002545</td>\n",
              "      <td>-0.023627</td>\n",
              "      <td>0.015418</td>\n",
              "      <td>0.011326</td>\n",
              "      <td>-0.021103</td>\n",
              "      <td>-0.036804</td>\n",
              "      <td>-0.069099</td>\n",
              "      <td>-0.034913</td>\n",
              "      <td>-0.043085</td>\n",
              "      <td>-0.040837</td>\n",
              "      <td>-0.014548</td>\n",
              "      <td>0.017290</td>\n",
              "      <td>0.044753</td>\n",
              "      <td>1.000000</td>\n",
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