24_BackTesting_de_Carteira_com_Python_(BT).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "24 - BackTesting de Carteira com Python (BT)",
      "provenance": [],
      "authorship_tag": "ABX9TyP4CTeQ9WjaO3oBc/gbdiaf",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ricospeloacaso/python_para_investimentos/blob/master/24_BackTesting_de_Carteira_com_Python_(BT).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b2A8eh8FbRkw",
        "colab_type": "text"
      },
      "source": [
        "###Python para Investimentos - BackTesting de Carteira com Python (BT)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HFCzJqCTbSe3",
        "colab_type": "text"
      },
      "source": [
        "**Python para Investimentos** é um conjunto de códigos e vídeos em que mostro como utilizar a linguagem de programação PYTHON através da ferramenta online Google Colab para fazer estudos no mercado financeiro."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_3fqaPymbSpm",
        "colab_type": "text"
      },
      "source": [
        "**Canal no Youtube:** https://www.youtube.com/ricospeloacaso?sub_confirmation=1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TmhVRnMLbSwg",
        "colab_type": "text"
      },
      "source": [
        "Link para o Vídeo: https://youtu.be/Ag9-Hn5A0Og"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b8zXIUpnbS8n",
        "colab_type": "code",
        "cellView": "form",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "outputId": "8beac781-cb2f-4de1-f72e-2b7d73aeba6e"
      },
      "source": [
        "#@title Vídeo\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('Ag9-Hn5A0Og', width=854, height=480)"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"854\"\n",
              "            height=\"480\"\n",
              "            src=\"https://www.youtube.com/embed/Ag9-Hn5A0Og\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f02c3424358>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lbUMgnwd9YVj",
        "colab_type": "text"
      },
      "source": [
        "## Biblioteca de Backtesting BT\n",
        "\n",
        "Documentação: https://pmorissette.github.io/bt/"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KcqEzLDoIwyG",
        "colab_type": "text"
      },
      "source": [
        "## Instalação e configurações Iniciais"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sJWgRWjBVeQp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install bt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UH9EP8pxuqHz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install yfinance"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3-9nCXPXVvE8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import bt\n",
        "import yfinance as yf\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib\n",
        "matplotlib.style.use('seaborn-darkgrid')\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NxxzAX1KcWFK",
        "colab_type": "text"
      },
      "source": [
        "##Funções"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QFM6eRwPcCF0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def consulta_bc(codigo_bcb):\n",
        "  url = 'http://api.bcb.gov.br/dados/serie/bcdata.sgs.{}/dados?formato=json'.format(codigo_bcb)\n",
        "  df = pd.read_json(url)\n",
        "  df['data'] = pd.to_datetime(df['data'], dayfirst=True)\n",
        "  df.set_index('data', inplace=True)\n",
        "  return df"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nnf88c9-dB1V",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def cdi_acumulado(data_inicio, data_fim):\n",
        "  cdi = consulta_bc(12)\n",
        "  cdi_acumulado = (1 + cdi[data_inicio : data_fim] / 100).cumprod()\n",
        "  cdi_acumulado.iloc[0] = 1\n",
        "  return cdi_acumulado"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LLxLw1p0cZCG",
        "colab_type": "text"
      },
      "source": [
        "##Obtendo e tratando os dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xXAg331Rcs7e",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "data_inicio = '2015-01-02'\n",
        "data_fim    = '2019-12-31'"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3pRSOL9qe08G",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "cdi = cdi_acumulado(data_inicio=data_inicio, data_fim=data_fim)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EGZD7G62vC1M",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "tickers_carteira = ['BOVA11.SA', 'SMAL11.SA']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s0Gq9vQguz0D",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "6edbae2f-35e9-4975-ce3d-d35ac98deae1"
      },
      "source": [
        "carteira = yf.download(tickers_carteira, start=data_inicio, end=data_fim)['Adj Close']"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  2 of 2 completed\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C56cbrf984y7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "carteira['renda_fixa'] = cdi\n",
        "carteira.dropna(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oy6UvsFhrQIA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "outputId": "bc524c09-c667-41d8-a46e-925c1df0e555"
      },
      "source": [
        "carteira"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BOVA11.SA</th>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <th>renda_fixa</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>47.259998</td>\n",
              "      <td>52.020000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>46.320000</td>\n",
              "      <td>50.549999</td>\n",
              "      <td>1.000869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-06</th>\n",
              "      <td>46.580002</td>\n",
              "      <td>50.000000</td>\n",
              "      <td>1.001304</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-07</th>\n",
              "      <td>48.150002</td>\n",
              "      <td>51.250000</td>\n",
              "      <td>1.001739</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-08</th>\n",
              "      <td>48.509998</td>\n",
              "      <td>52.000000</td>\n",
              "      <td>1.002175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-20</th>\n",
              "      <td>110.839996</td>\n",
              "      <td>133.199997</td>\n",
              "      <td>1.598532</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-23</th>\n",
              "      <td>111.669998</td>\n",
              "      <td>134.580002</td>\n",
              "      <td>1.598805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-26</th>\n",
              "      <td>112.809998</td>\n",
              "      <td>136.809998</td>\n",
              "      <td>1.599352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-27</th>\n",
              "      <td>112.169998</td>\n",
              "      <td>136.949997</td>\n",
              "      <td>1.599625</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-30</th>\n",
              "      <td>111.230003</td>\n",
              "      <td>136.440002</td>\n",
              "      <td>1.599898</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1235 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             BOVA11.SA   SMAL11.SA  renda_fixa\n",
              "Date                                          \n",
              "2015-01-02   47.259998   52.020000    1.000000\n",
              "2015-01-05   46.320000   50.549999    1.000869\n",
              "2015-01-06   46.580002   50.000000    1.001304\n",
              "2015-01-07   48.150002   51.250000    1.001739\n",
              "2015-01-08   48.509998   52.000000    1.002175\n",
              "...                ...         ...         ...\n",
              "2019-12-20  110.839996  133.199997    1.598532\n",
              "2019-12-23  111.669998  134.580002    1.598805\n",
              "2019-12-26  112.809998  136.809998    1.599352\n",
              "2019-12-27  112.169998  136.949997    1.599625\n",
              "2019-12-30  111.230003  136.440002    1.599898\n",
              "\n",
              "[1235 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GVw0ihJa2yzh",
        "colab_type": "text"
      },
      "source": [
        "##Backtesting"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6XIwWt6jFumR",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "rebalanceamento = bt.Strategy('rebalanceamento', \n",
        "                [bt.algos.RunMonthly(run_on_end_of_period=True),\n",
        "                 bt.algos.SelectAll(),\n",
        "                 bt.algos.WeighEqually(),\n",
        "                 bt.algos.Rebalance()])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wWjvG8DIFui-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "buy_hold = bt.Strategy('Buy&Hold', \n",
        "                   [ bt.algos.RunOnce(),\n",
        "                     bt.algos.SelectAll(),\n",
        "                     bt.algos.WeighEqually(),\n",
        "                     bt.algos.Rebalance()]\n",
        "                    )"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gI5gmvm1_HQ4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "bt1 = bt.Backtest(rebalanceamento, carteira)\n",
        "bt2 = bt.Backtest(buy_hold, carteira[['BOVA11.SA', 'SMAL11.SA']])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NqxvtpFtFupI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "97f119f1-d521-481c-89f2-a653b49496cf"
      },
      "source": [
        "resultados = bt.run(bt1, bt2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "rebalanceamento\n",
            "0% [############################# ] 100% | ETA: 00:00:00Buy&Hold\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ffn/core.py:2056: RuntimeWarning: divide by zero encountered in true_divide\n",
            "  res = np.divide(er.mean(), std)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "0% [############################# ] 100% | ETA: 00:00:00"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YfETtuvSxEgb",
        "colab_type": "text"
      },
      "source": [
        "#Resultados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2TWrJn6-Furn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 988
        },
        "outputId": "663d2043-ba09-4a10-fb9a-535fd4b00bc6"
      },
      "source": [
        "resultados.display()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Stat                 rebalanceamento    Buy&Hold\n",
            "-------------------  -----------------  ----------\n",
            "Start                2015-01-01         2015-01-01\n",
            "End                  2019-12-30         2019-12-30\n",
            "Risk-free rate       0.00%              0.00%\n",
            "\n",
            "Total Return         119.97%            148.81%\n",
            "Daily Sharpe         1.24               1.00\n",
            "Daily Sortino        2.06               1.66\n",
            "CAGR                 17.10%             20.02%\n",
            "Max Drawdown         -21.41%            -34.15%\n",
            "Calmar Ratio         0.80               0.59\n",
            "\n",
            "MTD                  6.51%              9.66%\n",
            "3m                   10.62%             15.58%\n",
            "6m                   15.94%             22.98%\n",
            "YTD                  30.15%             43.68%\n",
            "1Y                   30.15%             43.68%\n",
            "3Y (ann.)            22.68%             30.26%\n",
            "5Y (ann.)            17.10%             20.02%\n",
            "10Y (ann.)           17.10%             20.02%\n",
            "Since Incep. (ann.)  17.10%             20.02%\n",
            "\n",
            "Daily Sharpe         1.24               1.00\n",
            "Daily Sortino        2.06               1.66\n",
            "Daily Mean (ann.)    17.04%             20.75%\n",
            "Daily Vol (ann.)     13.75%             20.68%\n",
            "Daily Skew           -0.34              -0.31\n",
            "Daily Kurt           3.45               3.30\n",
            "Best Day             3.72%              5.52%\n",
            "Worst Day            -6.26%             -9.27%\n",
            "\n",
            "Monthly Sharpe       1.39               1.14\n",
            "Monthly Sortino      3.26               2.49\n",
            "Monthly Mean (ann.)  17.82%             21.93%\n",
            "Monthly Vol (ann.)   12.81%             19.28%\n",
            "Monthly Skew         0.07               0.05\n",
            "Monthly Kurt         -0.29              -0.32\n",
            "Best Month           10.04%             14.67%\n",
            "Worst Month          -7.21%             -11.06%\n",
            "\n",
            "Yearly Sharpe        2.55               2.22\n",
            "Yearly Sortino       inf                inf\n",
            "Yearly Mean          24.12%             31.61%\n",
            "Yearly Vol           9.44%              14.22%\n",
            "Yearly Skew          -1.94              -1.55\n",
            "Yearly Kurt          3.82               2.79\n",
            "Best Year            30.15%             43.68%\n",
            "Worst Year           10.03%             11.08%\n",
            "\n",
            "Avg. Drawdown        -1.94%             -3.29%\n",
            "Avg. Drawdown Days   22.65              26.58\n",
            "Avg. Up Month        3.47%              4.96%\n",
            "Avg. Down Month      -2.38%             -3.85%\n",
            "Win Year %           100.00%            100.00%\n",
            "Win 12m %            89.80%             85.71%\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LOTIwGpK_HUS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        },
        "outputId": "2b993047-22fd-4e17-df5d-fd3815f9dd03"
      },
      "source": [
        "resultados.plot();"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WVSzRbZX51yi",
        "colab_type": "text"
      },
      "source": [
        "###Operações"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jLgibBzRQN-r",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "outputId": "99dd6365-1c5d-4796-c5ca-ef0001869348"
      },
      "source": [
        "resultados.get_transactions()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>price</th>\n",
              "      <th>quantity</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th>Security</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">2015-01-02</th>\n",
              "      <th>BOVA11.SA</th>\n",
              "      <td>47.259998</td>\n",
              "      <td>7053.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <td>52.020000</td>\n",
              "      <td>6407.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>renda_fixa</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>333333.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2015-01-30</th>\n",
              "      <th>BOVA11.SA</th>\n",
              "      <td>45.610001</td>\n",
              "      <td>-52.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <td>46.790001</td>\n",
              "      <td>417.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">2019-10-31</th>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <td>115.570000</td>\n",
              "      <td>-43.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>renda_fixa</th>\n",
              "      <td>1.588157</td>\n",
              "      <td>5140.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"3\" valign=\"top\">2019-11-29</th>\n",
              "      <th>BOVA11.SA</th>\n",
              "      <td>104.349998</td>\n",
              "      <td>67.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <td>121.199997</td>\n",
              "      <td>-153.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>renda_fixa</th>\n",
              "      <td>1.594198</td>\n",
              "      <td>7323.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>179 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            price  quantity\n",
              "Date       Security                        \n",
              "2015-01-02 BOVA11.SA    47.259998    7053.0\n",
              "           SMAL11.SA    52.020000    6407.0\n",
              "           renda_fixa    1.000000  333333.0\n",
              "2015-01-30 BOVA11.SA    45.610001     -52.0\n",
              "           SMAL11.SA    46.790001     417.0\n",
              "...                           ...       ...\n",
              "2019-10-31 SMAL11.SA   115.570000     -43.0\n",
              "           renda_fixa    1.588157    5140.0\n",
              "2019-11-29 BOVA11.SA   104.349998      67.0\n",
              "           SMAL11.SA   121.199997    -153.0\n",
              "           renda_fixa    1.594198    7323.0\n",
              "\n",
              "[179 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OUzNGlxj556z",
        "colab_type": "text"
      },
      "source": [
        "###Pesos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K7_XMKIBjHX9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "outputId": "f3ad3c46-1a2b-4fc8-b934-c5289f875fbd"
      },
      "source": [
        "resultados.get_security_weights()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>BOVA11.SA</th>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <th>renda_fixa</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-01</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>0.333325</td>\n",
              "      <td>0.333292</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>0.331926</td>\n",
              "      <td>0.329059</td>\n",
              "      <td>0.338964</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-06</th>\n",
              "      <td>0.334314</td>\n",
              "      <td>0.325991</td>\n",
              "      <td>0.339645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-07</th>\n",
              "      <td>0.338950</td>\n",
              "      <td>0.327728</td>\n",
              "      <td>0.333272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-20</th>\n",
              "      <td>0.335707</td>\n",
              "      <td>0.347352</td>\n",
              "      <td>0.316922</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-23</th>\n",
              "      <td>0.336148</td>\n",
              "      <td>0.348800</td>\n",
              "      <td>0.315034</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-26</th>\n",
              "      <td>0.336444</td>\n",
              "      <td>0.351306</td>\n",
              "      <td>0.312232</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-27</th>\n",
              "      <td>0.335037</td>\n",
              "      <td>0.352192</td>\n",
              "      <td>0.312753</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-30</th>\n",
              "      <td>0.333585</td>\n",
              "      <td>0.352313</td>\n",
              "      <td>0.314083</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1236 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            BOVA11.SA  SMAL11.SA  renda_fixa\n",
              "2015-01-01   0.000000   0.000000    0.000000\n",
              "2015-01-02   0.333325   0.333292    0.333333\n",
              "2015-01-05   0.331926   0.329059    0.338964\n",
              "2015-01-06   0.334314   0.325991    0.339645\n",
              "2015-01-07   0.338950   0.327728    0.333272\n",
              "...               ...        ...         ...\n",
              "2019-12-20   0.335707   0.347352    0.316922\n",
              "2019-12-23   0.336148   0.348800    0.315034\n",
              "2019-12-26   0.336444   0.351306    0.312232\n",
              "2019-12-27   0.335037   0.352192    0.312753\n",
              "2019-12-30   0.333585   0.352313    0.314083\n",
              "\n",
              "[1236 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JzANQaIGxF3s",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "outputId": "e018b2c8-baf3-4458-c54e-c3504d0d42dc"
      },
      "source": [
        "resultados.plot_security_weights()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3LjCzboCDZoM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}