Ações_Analises5.ipynb

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  "metadata": {
    "colab": {
      "name": "Ações_Analises5.ipynd",
      "provenance": [],
      "authorship_tag": "ABX9TyP+XV//wreCmtDFJ+eB4jZn",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/fonsecajr/Projects/blob/master/A%C3%A7%C3%B5es_Analises5_ipynd.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "96CWP44m7Ewu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 395
        },
        "outputId": "836ebb88-2b7e-4162-a6a5-ff93150c00ee"
      },
      "source": [
        "!pip install yfinance --upgrade --no-cache-dir\n",
        "import yfinance as yf\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "sns.set()\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib\n",
        "matplotlib.rcParams['figure.figsize'] = (22,8)\n",
        "matplotlib.rcParams.update({'font.size': 22})\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "from scipy.stats import norm,t"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting yfinance\n",
            "  Downloading https://files.pythonhosted.org/packages/c2/31/8b374a12b90def92a4e27d0fc595fc43635f395984e36a075244d98bd265/yfinance-0.1.54.tar.gz\n",
            "Requirement already satisfied, skipping upgrade: pandas>=0.24 in /usr/local/lib/python3.6/dist-packages (from yfinance) (1.0.3)\n",
            "Requirement already satisfied, skipping upgrade: numpy>=1.15 in /usr/local/lib/python3.6/dist-packages (from yfinance) (1.18.4)\n",
            "Requirement already satisfied, skipping upgrade: requests>=2.20 in /usr/local/lib/python3.6/dist-packages (from yfinance) (2.23.0)\n",
            "Requirement already satisfied, skipping upgrade: multitasking>=0.0.7 in /usr/local/lib/python3.6/dist-packages (from yfinance) (0.0.9)\n",
            "Requirement already satisfied, skipping upgrade: python-dateutil>=2.6.1 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.24->yfinance) (2.8.1)\n",
            "Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.24->yfinance) (2018.9)\n",
            "Requirement already satisfied, skipping upgrade: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->yfinance) (2020.4.5.1)\n",
            "Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->yfinance) (3.0.4)\n",
            "Requirement already satisfied, skipping upgrade: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->yfinance) (1.24.3)\n",
            "Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests>=2.20->yfinance) (2.9)\n",
            "Requirement already satisfied, skipping upgrade: six>=1.5 in /usr/local/lib/python3.6/dist-packages (from python-dateutil>=2.6.1->pandas>=0.24->yfinance) (1.12.0)\n",
            "Building wheels for collected packages: yfinance\n",
            "  Building wheel for yfinance (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for yfinance: filename=yfinance-0.1.54-py2.py3-none-any.whl size=22409 sha256=e3f0d42f98b76c1a3ea065c7bd08a58bc335ed48978d7bf3fda4c0f8302a0d01\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-m3gz6vrx/wheels/f9/e3/5b/ec24dd2984b12d61e0abf26289746c2436a0e7844f26f2515c\n",
            "Successfully built yfinance\n",
            "Installing collected packages: yfinance\n",
            "Successfully installed yfinance-0.1.54\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hMJZcGy48sMX",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "outputId": "001f0c76-20a3-4bd5-caba-90771c5b7874"
      },
      "source": [
        "bvsp = yf.download(\"^BVSP\")[[\"Adj Close\"]]\n",
        "bvsp"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Adj Close</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1993-04-27</th>\n",
              "      <td>24.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993-04-28</th>\n",
              "      <td>24.299999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993-04-29</th>\n",
              "      <td>23.700001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993-04-30</th>\n",
              "      <td>24.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993-05-03</th>\n",
              "      <td>24.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>79065.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>77872.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>77772.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>79011.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>77557.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>6692 rows × 1 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               Adj Close\n",
              "Date                    \n",
              "1993-04-27     24.500000\n",
              "1993-04-28     24.299999\n",
              "1993-04-29     23.700001\n",
              "1993-04-30     24.100000\n",
              "1993-05-03     24.100000\n",
              "...                  ...\n",
              "2020-05-11  79065.000000\n",
              "2020-05-12  77872.000000\n",
              "2020-05-13  77772.000000\n",
              "2020-05-14  79011.000000\n",
              "2020-05-15  77557.000000\n",
              "\n",
              "[6692 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SVSF5GH59LqM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "bvsp['retorno'] = bvsp[\"Adj Close\"].pct_change()\n",
        "bvsp.dropna(inplace=True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aCq7iSwY9lLM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "784c3625-3c4b-4377-e3a9-19006a05e9d1"
      },
      "source": [
        "media_bvsp = bvsp['retorno'].mean()\n",
        "print('Retorno médio = {:.2f}%'.format(media_bvsp*100))"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Retorno médio = 0.15%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y9qEZhtQ_yoz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "aaa30856-8a8e-4077-df18-797d75064d02"
      },
      "source": [
        "desvio_padrao_bvsp= bvsp['retorno'].std()\n",
        "print('Desvio padrao = {:.2f}%' .format(desvio_padrao_bvsp*100))"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Desvio padrao = 2.28%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-MdK7yH0Ab3y",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 220
        },
        "outputId": "9d727408-fd00-4bd5-9eb9-7de32cccacdb"
      },
      "source": [
        "bvsp[bvsp['retorno'] < -0.12]"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>retorno</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1997-10-27</th>\n",
              "      <td>9817.0</td>\n",
              "      <td>-0.149675</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1998-09-10</th>\n",
              "      <td>4761.0</td>\n",
              "      <td>-0.158090</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-09</th>\n",
              "      <td>86067.0</td>\n",
              "      <td>-0.121738</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-12</th>\n",
              "      <td>72583.0</td>\n",
              "      <td>-0.147797</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-16</th>\n",
              "      <td>71168.0</td>\n",
              "      <td>-0.139215</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Adj Close   retorno\n",
              "Date                           \n",
              "1997-10-27     9817.0 -0.149675\n",
              "1998-09-10     4761.0 -0.158090\n",
              "2020-03-09    86067.0 -0.121738\n",
              "2020-03-12    72583.0 -0.147797\n",
              "2020-03-16    71168.0 -0.139215"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gl9KZPVICZg9",
        "colab_type": "text"
      },
      "source": [
        "Qual a probabilidade do bvsp cair mais que 12% considerando que os retornos seguem uma dristribuição normal?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-kTUpjk-CjOu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "ecc61fa8-b78b-4860-dcfb-562b2bb3a904"
      },
      "source": [
        "probabilidade_teorica = norm.cdf(-0.12, loc=media_bvsp, scale=desvio_padrao_bvsp)\n",
        "print('{:.8f}%'.format(probabilidade_teorica*100))"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.00000476%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A8v9TXskDT79",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 50
        },
        "outputId": "8c666701-2623-4cfa-8799-34a512a86e37"
      },
      "source": [
        "frequencia_teorica = 1 / probabilidade_teorica\n",
        "print('Uma vez a cada {} dias'.format(int(round(frequencia_teorica, 5))))\n",
        "print('Ou uma vez a cada {} anos'.format(int(round(frequencia_teorica/252, 5))))"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Uma vez a cada 21001396 dias\n",
            "Ou uma vez a cada 83338 anos\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0vo8sZ4QEFxC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 368
        },
        "outputId": "b72f2ce3-ad5d-4812-c53f-701dc1ace8d8"
      },
      "source": [
        "bvsp['retorno'].plot(title=\"Retorno Diário do Índice Bovespa\", figsize=(20, 8));"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gGifZraBHOOe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "bvsp['retorno_teorico'] = norm.rvs(size=bvsp['retorno'].size, loc=media_bvsp, scale=desvio_padrao_bvsp)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MFOi9P0yHptV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 353
        },
        "outputId": "02461789-10b2-4a46-8d9e-3700f8d2765a"
      },
      "source": [
        "ax = bvsp['retorno_teorico'].plot(title=\"Retorno Normal Simulado\", figsize=(22, 8));\n",
        "ax.set_ylim(-0.2, 0.4)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(-0.2, 0.4)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1584x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZouukrS-I6I5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 301
        },
        "outputId": "452a2f52-a61d-4643-a89c-1b1579186c04"
      },
      "source": [
        "sns.distplot(bvsp['retorno'], bins=100, kde=False, fit=norm);"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f50219c2cc0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "No4gEL4gJfJq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "outputId": "7e8f1d0d-76ab-4164-b553-7a41ef22d0f6"
      },
      "source": [
        "sns.distplot(bvsp['retorno'], bins=100, kde=False, fit=t);"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3JgwUhJJJh_p",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 82
        },
        "outputId": "35f3b5c2-75da-4c94-999a-1da40e4c2ef0"
      },
      "source": [
        "(graus_de_liberdade, media_t, desvio_padrao_t) = t.fit(bvsp['retorno'])\n",
        "print('Distribuição T-Student\\nGraus de liberdade={:.2f} \\nMédia={:.4f} \\nDesvio padrão={:.5f}'.format(graus_de_liberdade, media_t, desvio_padrao_t))"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Distribuição T-Student\n",
            "Graus de liberdade=3.24 \n",
            "Média=0.0012 \n",
            "Desvio padrão=0.01447\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RtuGqIkrK4l3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "e992c0e3-8d80-4ae8-d313-a2d662410e70"
      },
      "source": [
        "probabilidade_teorica_t = t.cdf(-0.12, graus_de_liberdade, loc=media_t, scale=desvio_padrao_t)\n",
        "print('{:.8f}%'.format(probabilidade_teorica_t*100))"
      ],
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.13360139%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KixqgkzzMWU2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66
        },
        "outputId": "139ae321-6e7c-4ae4-bba8-480e3a03a128"
      },
      "source": [
        "frequencia_teorica_t = 1 / probabilidade_teorica_t\n",
        "print('Para uma distribuição T-Student: \\nUma vez a cada {} dias'.format(int(round(frequencia_teorica_t, 5))))\n",
        "print('Ou uma vez a cada {} anos'.format(int(round(frequencia_teorica_t/252, 5))))"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Para uma distribuição T-Student: \n",
            "Uma vez a cada 748 dias\n",
            "Ou uma vez a cada 2 anos\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cIN__ZasM9_m",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66
        },
        "outputId": "bfe0879b-fed3-4ef2-e88c-93f0c0e81176"
      },
      "source": [
        "frequencia_teorica = 1 / probabilidade_teorica\n",
        "print('Para uma distribuição Normal: \\nUma vez a casa {} dias'.format(int(round(frequencia_teorica, 5))))\n",
        "print('Ou uma vez a cada {} anos'.format(int(round(frequencia_teorica/252, 5))))"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Para uma distribuição Normal: \n",
            "Uma vez a casa 21001396 dias\n",
            "Ou uma vez a cada 83338 anos\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V8bjgMDdOB_4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 66
        },
        "outputId": "4ec4ae60-f56a-43f2-b19f-6513eb6f840c"
      },
      "source": [
        "frequencia_observada = bvsp['retorno'].size / bvsp[bvsp['retorno'] < -0.12].size\n",
        "print(\"Na vida real aconteceu (T-Student no fit=t): \\nUma vez a cada {} dias\".format(int(round(frequencia_observada, 5))))\n",
        "print(\"Impossível calcular baixas probabilidades \\ É sobre estar preparado para os Cisnes Negros -Nassim Taleb\")"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Na vida real aconteceu (T-Student no fit=t): \n",
            "Uma vez a cada 446 dias\n",
            "Impossível calcular baixas probabilidades \\ É sobre estar preparado para os Cisnes Negros -Nassim Taleb\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}