20220313_Novos_aportes_na_carteira.ipynb

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  "metadata": {
    "colab": {
      "name": "20220313 - Novos aportes na carteira.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyP9WuKnZsB5ClfsV7aeULyN",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Trading-com-Dados/codigos_videos/blob/main/20220313_Novos_aportes_na_carteira.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Simulação de carteiras que levam em consideração novos aportes"
      ],
      "metadata": {
        "id": "PtvIl_YH2Ay4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Premissas:\n",
        "\n",
        "1. Só faremos aportes em ativos que já estão na carteira\n",
        "2. Novos aportes são feitos logo no início do pregão"
      ],
      "metadata": {
        "id": "VJ-VJ2aA0pR7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 0. Instalando e importando bibliotecas"
      ],
      "metadata": {
        "id": "RI8tNhuf2FIR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install yfinance"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wIxN8fgM2Omu",
        "outputId": "c33f378a-a845-4207-d843-4fe967eadefe"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.70-py2.py3-none-any.whl (26 kB)\n",
            "Collecting lxml>=4.5.1\n",
            "  Downloading lxml-4.8.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (6.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.4 MB 5.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.10)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.5)\n",
            "Collecting requests>=2.26\n",
            "  Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB)\n",
            "\u001b[K     |████████████████████████████████| 63 kB 1.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.15.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2021.10.8)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.0.12)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (1.24.3)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.10)\n",
            "Installing collected packages: requests, lxml, yfinance\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.27.1 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed lxml-4.8.0 requests-2.27.1 yfinance-0.1.70\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import yfinance as yf"
      ],
      "metadata": {
        "id": "M1UbPVUA2TK5"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "metadata": {
        "id": "26QY2LKC2Ywe"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1. Criação da carteira de referência"
      ],
      "metadata": {
        "id": "MXuvP7wu0avv"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Como referência, assista ao vídeo: https://youtu.be/AzIXSFZOSrw"
      ],
      "metadata": {
        "id": "sSv2915U2bEN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ativos = ['PETR4.SA','VALE3.SA', 'WEGE3.SA', \n",
        "          'RADL3.SA', 'OIBR3.SA','AAPL34.SA','IVVB11.SA']"
      ],
      "metadata": {
        "id": "o5QIg6VP2o3O"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "inicio = '2020-05-01'\n",
        "fim = '2022-03-11'"
      ],
      "metadata": {
        "id": "WqP32nBU23le"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "precos = yf.download(ativos, start = inicio, end = fim)['Adj Close']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uRSVVTJo2733",
        "outputId": "793f626e-c193-4efb-a2e6-a5dca3db1140"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[*********************100%***********************]  7 of 7 completed\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dicionário contendo as alocações iniciais no primeiro dia"
      ],
      "metadata": {
        "id": "PKrcBL7k3MoH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "compras = {'PETR4.SA': 2500, 'VALE3.SA': 2300, 'WEGE3.SA': 2000, \n",
        "           'RADL3.SA': 1700, 'OIBR3.SA': 1500, 'AAPL34.SA': 1100, 'IVVB11.SA': 900}"
      ],
      "metadata": {
        "id": "kGIOtaiM3EfO"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "compras_df = pd.Series(data = compras, index = list(compras.keys()) )"
      ],
      "metadata": {
        "id": "Qfb2mTrx3QMx"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sum(compras.values())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mGl-5yNo3aAg",
        "outputId": "315736d7-e0c5-434b-849d-30dc2bfd3d81"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12000"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Preço dos ativos no primeiro dia do investimento"
      ],
      "metadata": {
        "id": "x9IUWCTM3fXi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "primeiro = precos.iloc[0]"
      ],
      "metadata": {
        "id": "ptJTaF_p3vnt"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "primeiro"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6r3VzAF23zMP",
        "outputId": "9b7104cf-d425-4653-a4d7-9dbddfbf6b54"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "AAPL34.SA     39.877621\n",
              "IVVB11.SA    169.199997\n",
              "OIBR3.SA       0.680000\n",
              "PETR4.SA      14.126041\n",
              "RADL3.SA      20.637646\n",
              "VALE3.SA      34.517658\n",
              "WEGE3.SA      19.485765\n",
              "Name: 2020-05-04 00:00:00, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Quantidade de papéis comprados de cada ativo"
      ],
      "metadata": {
        "id": "J2kLAekj3pKz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qtd_acoes = compras_df/primeiro"
      ],
      "metadata": {
        "id": "QuGWJ2gX30bW"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dataframe que contém a posição diária de cada ativo"
      ],
      "metadata": {
        "id": "KHPhUJfh3sGg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "PL = precos*qtd_acoes"
      ],
      "metadata": {
        "id": "6qvKl_vg3_Va"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PL.head()"
      ],
      "metadata": {
        "colab": {
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          "height": 237
        },
        "id": "F_VigLgw4DZp",
        "outputId": "fafee9b7-294b-430c-eb1e-69963b27b264"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
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              "              AAPL34.SA   IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
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              "2020-05-06  1175.442177  928.989346  1544.117605  2485.615938  1683.090923   \n",
              "2020-05-07  1210.000116  973.404273  1477.941198  2508.630876  1685.854897   \n",
              "2020-05-08  1221.059801  961.436188  1522.058802  2658.228053  1701.951059   \n",
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              "               VALE3.SA     WEGE3.SA  \n",
              "Date                                  \n",
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              "2020-05-06  2320.942650  1949.297353  \n",
              "2020-05-07  2410.995130  1962.349037  \n",
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        "PL['PL Total'] = PL.sum(axis = 1)"
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      "metadata": {
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      "outputs": []
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      "execution_count": 18,
      "outputs": [
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          "data": {
            "text/plain": [
              "              AAPL34.SA   IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
              "Date                                                                         \n",
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    {
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      "execution_count": 19,
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              "2022-03-07  2232.129110  1244.680874  1742.647088  5627.903513  1888.006057   \n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
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          "metadata": {},
          "execution_count": 19
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    },
    {
      "cell_type": "code",
      "source": [
        "PL['PL Total'].plot();"
      ],
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        "outputId": "0e84f489-d645-467e-d17c-351acc6d1ea0"
      },
      "execution_count": 22,
      "outputs": [
        {
          "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": [
        "# Criando função que recebe carteira e compara com o IBOV\n",
        "\n",
        "def comparaibov(i, f, carteira, largura,altura,nome):\n",
        "   import matplotlib.pyplot as plt\n",
        "   ibov = pd.DataFrame(yf.download('^BVSP', start = i, end =  f, progress=False)['Adj Close'].rename('IBOV', inplace = True))\n",
        "   consolidado = pd.merge(ibov, carteira, how = 'inner', on = 'Date')\n",
        "   consolidado_adj = consolidado/consolidado.iloc[0]\n",
        "   comparativo = consolidado_adj[['IBOV', 'PL Total']]\n",
        "   comparativo.plot(figsize = (largura,altura))\n",
        "   plt.legend([\"IBOV\", str(nome)]);"
      ],
      "metadata": {
        "id": "TvO7FB404qjO"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "comparaibov(inicio, fim, PL, 8, 8, 'Carteira com Um Aporte')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 473
        },
        "id": "ACbK0lkA4zZ3",
        "outputId": "333cc008-444e-49c1-a4dd-a5bf5350ef98"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2. Reformular a carteira considerando novo aporte"
      ],
      "metadata": {
        "id": "8GFPQpFG0ukd"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Quando foi o novo aporte?"
      ],
      "metadata": {
        "id": "y94B9-zc6hkA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data_aporte = '2021-09-14'"
      ],
      "metadata": {
        "id": "9Fmm5ZRz6VmY"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Quanto nossa carteira tinha nesse dia?"
      ],
      "metadata": {
        "id": "pofZDw5Z6flY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "PL.loc[data_aporte]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IZzYVDcM6lWw",
        "outputId": "d611d768-32c0-4657-8310-c20b70e1b0d2"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "AAPL34.SA     2148.324088\n",
              "IVVB11.SA     1351.063854\n",
              "OIBR3.SA      2227.941132\n",
              "PETR4.SA      4077.224912\n",
              "RADL3.SA      2126.490790\n",
              "VALE3.SA      5469.220632\n",
              "WEGE3.SA      4008.407078\n",
              "PL Total     21408.672485\n",
              "Name: 2021-09-14 00:00:00, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Determine os novos aportes"
      ],
      "metadata": {
        "id": "b8Y8P-846udZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "segunda_compra = {'OIBR3.SA': 6000, 'RADL3.SA': 2000, 'VALE3.SA': 1000}"
      ],
      "metadata": {
        "id": "aKl81sFA6y7B"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "segunda_compra_df = pd.Series(data = segunda_compra, index = list(segunda_compra.keys()) )"
      ],
      "metadata": {
        "id": "Y1hUFPRn7CWK"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sum(segunda_compra.values())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GC5XhHrl7JYv",
        "outputId": "b9c39ee5-6f89-4b24-cbf8-d0da07a9279c"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9000"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Preço dos ativos no dia do aporte"
      ],
      "metadata": {
        "id": "l0TgRSiy7RIK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "precos_segundo_aporte = precos.loc[data_aporte]"
      ],
      "metadata": {
        "id": "03iaM9he7Xy6"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "precos_segundo_aporte"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MkKV0jWR7dCo",
        "outputId": "ace312bc-7296-4335-f06c-774d3245c596"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "AAPL34.SA     77.881866\n",
              "IVVB11.SA    254.000000\n",
              "OIBR3.SA       1.010000\n",
              "PETR4.SA      23.038019\n",
              "RADL3.SA      25.815155\n",
              "VALE3.SA      82.080299\n",
              "WEGE3.SA      39.053440\n",
              "Name: 2021-09-14 00:00:00, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Número de papéis comprados no segundo aporte"
      ],
      "metadata": {
        "id": "SyGiaKFd7ia_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "qtd_acoes_segundo = segunda_compra_df/precos_segundo_aporte"
      ],
      "metadata": {
        "id": "e3Gemq3a7mLL"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "qtd_acoes_segundo"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m0hgDAdm7w9F",
        "outputId": "2068b6b1-e089-463b-c2f8-d4a12fe42fe7"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "AAPL34.SA            NaN\n",
              "IVVB11.SA            NaN\n",
              "OIBR3.SA     5940.594115\n",
              "PETR4.SA             NaN\n",
              "RADL3.SA       77.473871\n",
              "VALE3.SA       12.183191\n",
              "WEGE3.SA             NaN\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos criar um data frame novo exclusivo para o novo aporte. As operações serão consideradas separadamente, e depois vamos juntar com a carteira original."
      ],
      "metadata": {
        "id": "TaXElzWe7z8y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "novo_PL = pd.DataFrame(data = None, index = precos.index, columns = precos.columns)"
      ],
      "metadata": {
        "id": "7R1hd1o68LHo"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "novo_PL.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "6IzGnsaf8dzj",
        "outputId": "ec98bfa4-b207-4be2-9581-8ef73bf9d39d"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           AAPL34.SA IVVB11.SA OIBR3.SA PETR4.SA RADL3.SA VALE3.SA WEGE3.SA\n",
              "Date                                                                       \n",
              "2020-05-04       NaN       NaN      NaN      NaN      NaN      NaN      NaN\n",
              "2020-05-05       NaN       NaN      NaN      NaN      NaN      NaN      NaN\n",
              "2020-05-06       NaN       NaN      NaN      NaN      NaN      NaN      NaN\n",
              "2020-05-07       NaN       NaN      NaN      NaN      NaN      NaN      NaN\n",
              "2020-05-08       NaN       NaN      NaN      NaN      NaN      NaN      NaN"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-324398d3-13c0-4dfc-884a-b3fc310b1e9a\">\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>AAPL34.SA</th>\n",
              "      <th>IVVB11.SA</th>\n",
              "      <th>OIBR3.SA</th>\n",
              "      <th>PETR4.SA</th>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [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",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Qual a variação de patrimônio para as novas posições montadas?"
      ],
      "metadata": {
        "id": "LdvGPvLl8ljJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "novos_PL = precos*qtd_acoes_segundo"
      ],
      "metadata": {
        "id": "D5EA7Sv88rlS"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "novos_PL.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "8-yIrsXK8zLi",
        "outputId": "fd09aac0-5b89-4462-8bfb-8ca0f0f09e9d"
      },
      "execution_count": 42,
      "outputs": [
        {
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [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",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos preencher os NaN com zeros"
      ],
      "metadata": {
        "id": "_wFAwfd79J-C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "novos_PL = novos_PL.fillna(0)"
      ],
      "metadata": {
        "id": "tLR8aqG89NZA"
      },
      "execution_count": 43,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "O que houve antes do aporte deve ser zero"
      ],
      "metadata": {
        "id": "TOheL9p19R_Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "novos_PL[novos_PL.index < data_aporte] = 0"
      ],
      "metadata": {
        "id": "NB73d5dK9Vc5"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "novos_PL.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "uQkUEABf9aPg",
        "outputId": "65ddb68d-c127-463a-de82-d6949cb9b763"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
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    {
      "cell_type": "code",
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        "novos_PL.tail()"
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      "execution_count": 46,
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        "Agora precisamos somar a carteira original com as operações após aporte"
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        "carteira_full = pd.concat([PL, novos_PL], axis = 1)"
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      "metadata": {
        "id": "fc881Tn292KS"
      },
      "execution_count": 47,
      "outputs": []
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        "carteira_full.head()"
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        "id": "RuCCTJIX96tM",
        "outputId": "52b10f2f-51c1-4f74-abbe-e33c4846aa57"
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      "execution_count": 48,
      "outputs": [
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              "\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": {},
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    {
      "cell_type": "code",
      "source": [
        "carteira_full['PL Total'] = carteira_full.sum(axis = 1)"
      ],
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      },
      "execution_count": 56,
      "outputs": []
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        "carteira_full.head()"
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [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",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PL.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "i3edko55-8Ri",
        "outputId": "b3d1682e-bce2-41f9-eb95-6f369c96cd99"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              AAPL34.SA    IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
              "Date                                                                          \n",
              "2022-03-04  2269.643902  1271.808566  1852.941099  6057.960355  1959.671278   \n",
              "2022-03-07  2232.129110  1244.680874  1742.647088  5627.903513  1888.006057   \n",
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              "2022-03-10  2184.408226  1241.489352  1852.941099  5964.162177  1841.876809   \n",
              "\n",
              "               VALE3.SA     WEGE3.SA      PL Total  \n",
              "Date                                                \n",
              "2022-03-04  6542.974231  3234.155753  23189.155185  \n",
              "2022-03-07  6741.887720  3190.020940  22667.275302  \n",
              "2022-03-08  6446.083719  3240.314040  22510.462726  \n",
              "2022-03-09  6276.121171  3353.216813  22670.961517  \n",
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              "      <th>2022-03-04</th>\n",
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              "      <td>1852.941099</td>\n",
              "      <td>6057.960355</td>\n",
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              "      <th>2022-03-07</th>\n",
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              "      <td>1244.680874</td>\n",
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              "      <td>5627.903513</td>\n",
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              "      <th>2022-03-08</th>\n",
              "      <td>2194.062722</td>\n",
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              "      <td>1808.823495</td>\n",
              "      <td>5744.709034</td>\n",
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              "      <td>3240.314040</td>\n",
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              "      <th>2022-03-09</th>\n",
              "      <td>2261.644403</td>\n",
              "      <td>1244.680874</td>\n",
              "      <td>1875.000033</td>\n",
              "      <td>5762.407249</td>\n",
              "      <td>1897.890975</td>\n",
              "      <td>6276.121171</td>\n",
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              "      <th>2022-03-10</th>\n",
              "      <td>2184.408226</td>\n",
              "      <td>1241.489352</td>\n",
              "      <td>1852.941099</td>\n",
              "      <td>5964.162177</td>\n",
              "      <td>1841.876809</td>\n",
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              "      <td>3255.709855</td>\n",
              "      <td>22823.935997</td>\n",
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              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
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              "\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-71fa14d3-2273-41dc-bccb-ff7655a589ba button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-71fa14d3-2273-41dc-bccb-ff7655a589ba');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [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",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "carteira_full[['OIBR3.SA']].plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 277
        },
        "id": "LrtQB9jB-74N",
        "outputId": "f9434b03-f91d-41e2-99c5-4b99ff1f960b"
      },
      "execution_count": 60,
      "outputs": [
        {
          "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": [
        "carteira_full[['RADL3.SA']].plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 277
        },
        "id": "BtlZhFnI-7gg",
        "outputId": "3c2bead2-cc1f-4c55-826c-ab2f69ba1581"
      },
      "execution_count": 61,
      "outputs": [
        {
          "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": [
        "carteira_full[['VALE3.SA']].plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 277
        },
        "id": "3yKG9Xrb_PNK",
        "outputId": "6d5dd48e-915e-4cba-cead-97ba72035093"
      },
      "execution_count": 62,
      "outputs": [
        {
          "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": [
        "carteira_full[['PL Total']].plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "kbxoDhw-_fPY",
        "outputId": "acb4e96c-598b-406f-f44a-e675e8c9ed8c"
      },
      "execution_count": 64,
      "outputs": [
        {
          "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": "markdown",
      "source": [
        "# 3. Cálculo dos retornos diários e da rentabilidade acumulada da carteira"
      ],
      "metadata": {
        "id": "X1ZYYD470xs6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Vamos agora para o cálculo dos retornos diários. \n",
        "\n",
        "Só que esse cálculo não pode ser feito da forma tradicional, ou seja, considerando simplesmente o retorno de um dia para o outro. Isso porque o retorno do dia quando houve o aporte será distorcido se calcularmos utilizando o valor do aporte. Para que o cálculo seja feito corretamente, precisaremos separar os dataframes em dois momentos: antes e depois do aporte."
      ],
      "metadata": {
        "id": "ta9du0d3_2B6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "carteira_full.drop(['PL Total'], axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "2Km-54e8_11D"
      },
      "execution_count": 66,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Dividindo o cálculo da rentabilidade em antes e depois do aportea"
      ],
      "metadata": {
        "id": "32ZD1PA0_1eI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "antes_aporte = carteira_full[carteira_full.index < data_aporte]\n",
        "depois_aporte = carteira_full[carteira_full.index >= data_aporte]"
      ],
      "metadata": {
        "id": "e-GGw6Oi_1RZ"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "antes_aporte['PL Total'] = antes_aporte.sum(axis = 1)\n",
        "depois_aporte['PL Total'] = depois_aporte.sum(axis = 1)"
      ],
      "metadata": {
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        "id": "0kddvafsAvvy",
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      "execution_count": 68,
      "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",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: 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",
            "  \n"
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              "              AAPL34.SA    IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
              "Date                                                                          \n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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      "cell_type": "markdown",
      "source": [
        "Configurando posição imediatamente antes do aporte"
      ],
      "metadata": {
        "id": "IlI9bwm5C_sy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import datetime, timedelta"
      ],
      "metadata": {
        "id": "j5j3bRUxC_hs"
      },
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dia_antes_aporte = (datetime.strptime(data_aporte, '%Y-%m-%d') - timedelta(1)).strftime('%Y-%m-%d')"
      ],
      "metadata": {
        "id": "m4rHpr3AC_Wy"
      },
      "execution_count": 78,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dia_antes_aporte"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "mjbJUe9gC_KC",
        "outputId": "d99a7d33-3496-4730-a151-78e3c7dbf60a"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2021-09-13'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Qual era o tamanho da nossa posição no dia imediatamente após o aporte?"
      ],
      "metadata": {
        "id": "z5H9tg2yC-6H"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "antes_aporte.loc[dia_antes_aporte]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CAFMtPilEm5q",
        "outputId": "2fa8042b-9381-4b31-bbd6-99ecfaac8b2a"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "AAPL34.SA     2143.647208\n",
              "IVVB11.SA     1344.946865\n",
              "OIBR3.SA      2249.999934\n",
              "PETR4.SA      4132.365165\n",
              "RADL3.SA      2132.215919\n",
              "VALE3.SA      5508.166559\n",
              "WEGE3.SA      3959.549157\n",
              "PL Total     21470.890807\n",
              "Name: 2021-09-13 00:00:00, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Transformando isso em um data frame transposto"
      ],
      "metadata": {
        "id": "i8leTt-ZEmn-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "posicao_original = pd.DataFrame(antes_aporte.loc[dia_antes_aporte]).T"
      ],
      "metadata": {
        "id": "hkKfHamCFAtC"
      },
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "segunda_compra_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MtPw6sACFAbE",
        "outputId": "6d7b2702-bb7d-4ad9-ae77-65abb4b95750"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "OIBR3.SA    6000\n",
              "RADL3.SA    2000\n",
              "VALE3.SA    1000\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aportes  = pd.DataFrame(segunda_compra_df, columns = [dia_antes_aporte]).T\n",
        "aportes.index = pd.to_datetime(aportes.index)"
      ],
      "metadata": {
        "id": "FsodGlF_FXIB"
      },
      "execution_count": 87,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "operacoes = pd.concat([posicao_original, aportes], axis = 1)"
      ],
      "metadata": {
        "id": "bUpeDBzgFvFG"
      },
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "operacoes = operacoes.groupby(lambda x:x, axis = 1).sum()"
      ],
      "metadata": {
        "id": "B7PLyr_eFu5M"
      },
      "execution_count": 91,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "operacoes.drop('PL Total', axis = 1, inplace = True)\n",
        "operacoes['PL Total'] = operacoes.sum(axis = 1)"
      ],
      "metadata": {
        "id": "5sRigAqfFut7"
      },
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "operacoes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 80
        },
        "id": "BvQle2B6GSia",
        "outputId": "8c848fc8-5b54-45d7-ff77-c3c571398712"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              AAPL34.SA    IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
              "2021-09-13  2143.647208  1344.946865  8249.999934  4132.365165  4132.215919   \n",
              "\n",
              "               VALE3.SA     WEGE3.SA      PL Total  \n",
              "2021-09-13  6508.166559  3959.549157  30470.890807  "
            ],
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              "      <td>8249.999934</td>\n",
              "      <td>4132.365165</td>\n",
              "      <td>4132.215919</td>\n",
              "      <td>6508.166559</td>\n",
              "      <td>3959.549157</td>\n",
              "      <td>30470.890807</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6aa434a5-9569-4ddf-9a90-087413287b67')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6aa434a5-9569-4ddf-9a90-087413287b67');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [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",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
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              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        " Agora vamos anexar a linha acima ao data frame \"depois_aporte\""
      ],
      "metadata": {
        "id": "FZqOqQxbGiDT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "depois_aporte = pd.concat([operacoes, depois_aporte], axis = 0)"
      ],
      "metadata": {
        "id": "Vc95pUAmGgHO"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rentabilidade_antes_aporte = antes_aporte.pct_change()\n",
        "rentabilidade_depois_aporte = depois_aporte.pct_change()"
      ],
      "metadata": {
        "id": "9dCgEL27Gf7s"
      },
      "execution_count": 97,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rentabilidade_antes_aporte.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "Fh4cI7sxGfyh",
        "outputId": "5d0101de-7314-41ad-a82d-9ddfbf972e51"
      },
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            AAPL34.SA  IVVB11.SA  OIBR3.SA  PETR4.SA  RADL3.SA  VALE3.SA  \\\n",
              "Date                                                                       \n",
              "2021-09-06   0.018218  -0.000975  0.009901  0.004937  0.002683 -0.015718   \n",
              "2021-09-08   0.009804   0.020488 -0.039216 -0.056311 -0.029816 -0.020812   \n",
              "2021-09-09  -0.019296  -0.021033  0.051020  0.021226  0.018125 -0.003578   \n",
              "2021-09-10  -0.030937   0.000000 -0.048544 -0.006274 -0.011223  0.001162   \n",
              "2021-09-13  -0.004980  -0.012305  0.040816  0.035122  0.020352 -0.000527   \n",
              "\n",
              "            WEGE3.SA  PL Total  \n",
              "Date                            \n",
              "2021-09-06  0.003586  0.000476  \n",
              "2021-09-08  0.003024 -0.020597  \n",
              "2021-09-09  0.064401  0.017935  \n",
              "2021-09-10 -0.004635 -0.011188  \n",
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        "rentabilidade_antes_aporte = rentabilidade_antes_aporte.dropna()\n",
        "rentabilidade_depois_aporte = rentabilidade_depois_aporte.dropna()"
      ],
      "metadata": {
        "id": "Wc9pv5PPHSxD"
      },
      "execution_count": 101,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "rentabilidade_total = pd.concat([rentabilidade_antes_aporte, rentabilidade_depois_aporte], axis = 0)"
      ],
      "metadata": {
        "id": "FBAVDdJfHSpW"
      },
      "execution_count": 102,
      "outputs": []
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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    {
      "cell_type": "code",
      "source": [
        "retorno_acumulado = (1 + rentabilidade_total).cumprod()"
      ],
      "metadata": {
        "id": "q9NZQrYhHSXR"
      },
      "execution_count": 104,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "retorno_acumulado['Date'] = pd.to_datetime(retorno_acumulado.index)\n",
        "retorno_acumulado.index = retorno_acumulado['Date']\n",
        "retorno_acumulado.drop(['Date'], axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "veBocu-PH-hG"
      },
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
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        "comparaibov(inicio, fim, retorno_acumulado, 8, 6, 'Carteira Após Segundo Aporte')"
      ],
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        "colab": {
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          "height": 375
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        "id": "WIca6ikyH-SM",
        "outputId": "9cbd6f73-c142-41aa-9c49-c1c1fc2c6bb0"
      },
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "comparaibov(inicio, fim, PL, 8, 6, 'Carteira com apenas um aporte')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "id": "MQF_3COSHSFr",
        "outputId": "59477623-8f13-4c28-f50d-0a38c9adab7a"
      },
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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ngBPm9VJN0w4AvYD9VqfNB943p+tv1jQtVNO0HuZrFYrTj4p8ufQNNvZpGky9TTai0WPuVaqTmOL05Oqrr+bqq692tRhOITU11dUitAqnx9Q1TYsFRgFbGhzqBaRbbWeY9zV1j+s1TUvSNC0pNzfXEWIqFB3n6FoI7QvBPWz3z3kYYqeCn7kXvLLUFQqFnXCqUtc0LQj4HLhNCFHS3vsIIV4XQowVQoyNilKxSEUnJXU9DJgprfOm8De3BVVKvUmcke+jUHRm2vM34DSlrmmaN1KhLxNCfNHEKZlAH6vt3uZ9CsXpR30tVJdAyCkaZfgrS705/Pz8yM/PV4pd0WURQpCfn9/mOnanxNTNme1vAQeEEM82c9rXwC2api0HJgDFKp6uOG1pKkmuIX7m4S5KqTeid+/eZGRkoMJriq6Mn59fmzvoOauj3BTgCmCPpml6hf19QF8AIcRrwEpkOVsysqTtGifJplDYn9YodQ9PCIqBYuWQaoi3t7elTahCoWg9zsp+34DNMOkmzxHAzc6QR6FwOHVN9H1visjBkNe2Gd0KhULRHKqjnELhCHRL3auFeFjkIMj4HTa+0Px9SrLsK5tCoXBblFJXKBxBUy1imyK4p1yuegDqGw/SYPnl8OxQUAljCoWiFSilrlA4glpzY5lTxdQBRl8B0ebmiukNWzcAKb/IZUWB/WRTKBRui1LqCoUjaGqWelMEd4drf5K94A83nsBloTit6f2Fx+HXf0N5XvvkVCgUboVS6gqFI7C431tRY+obLDvMHfqh+XOydkJ5vuGirymHXx+Fl8fDuqdgz6cdl1kh2f81FByT60JAcYZr5VEo2oBS6gqFI2itpa4z+FzIPwL5Kca+L24w1r+9DZ4eAK9OhtJseGUirHsahl4IPsG21ynaj8kEn1wBr0+X27s/geeGw6FTeFEUik6EUuoKhSOoa0WdujWDz5bLQ9/LZjRCwO7lxnFPX5h+D+QdkslzRWlwyTJY+CZEDoT8ZPvK31WpLpbLKvPy4DdyueJGKEx1iUgKRVtQSl2hcAStaT5jTVg/mTD30z/hyVg48pNxbMGbsOQozLwX+k6GzCQIiIQzzpPHIwYqS72jpG6EslwZ4tCprZL7uyfISXpHVrlOPoWilSilrlA4Aj2m7tVKpQ4w+BxjPWuHXJ79GCQsAt8guT37QQjrL/d7mP98IwZCcbqRca9oG0LAsj/A8sugPMfYv+t/UFkAZ/2f9JQUNZOsqFB0IpzVJlah6FrUVgIaePm2/ppx10HRcdj7uZGc1a3B9OF+k+DvO233hccBAgqPQfTQjkjdNamrli9hGb/DmseN/RuXQq8xMGCGHKFbdNxVEipOJ07ug+pS6DvRJR+vLHWFwhHUVsokuebGrjZFSC+Y/4pc12Pkp5ryphMRZ75GueDbRXWpXHr5wbF1xv7CVJh6h/wdhvaV5YMKxakoPC6TWd8+22UiKKWuUDiC8lxZqtZWvHwBzegH39BSbwqLUlfJcu2iukQuz7zTdn/UECNvIayfVPKqs5/iVCT/bKzryZZORil1hcLeCAGpG6DvhLZfq2ngEwgV+eDhBUHRLV/jFwL+4V035ltbJefXNyTnYOsy1nVLXe/spzPlNiNvIWqITJYrze6QqAo3R8+FAcg54BIRlFJXKOxNfjKUZMpYbHvQa9uDe8jxrK3BP0wqHWdSeLzpfvXOZN3T8PRAeOdco+KguhS+vxtemQD/nd7yy46u1H2D4dYdcNFrcM4TEL/IOKd7vFxm77H/Myjch6wd8gUQZGzdBSilrlDYm6Nr5HLAjPZd72NW6q1xvev4hUClE5V6RQEsTYAf73PeZzakslB21YscCBlb4auboeQEfHwFbPkv9BorX3SObzr1fWrK5NI3GMIHQOJimHgTeFrlEccMl8vs3Y55FsXpT02FtM6HXAC+IUqpKxRuw9E1ENJXlp61B+9AuQxpg1L3D3Wupa5bv7s+at35QsCaJyDvSPPHD/0gO7q1Fj0x8MwlMPshWTXw7BA4uhom/hX+9Lk8Xp5re93RtZD+u7FtsdS7Nf9ZfiEQFgsn9zY+VlcN+75U8fauTvYeEPWyYiJ6KOTsd4kYSqkrFPbEVA+p62HA9LZlvlvTLks91LmWenG6XOpJZgC/v2GbKGRNSaYsF/vfH233H/4JNjwHO5fBR5fAzg9bL4P+ghA5CKbeLhvy6Ey7QypiD29bpV5VAu/Pg7fOkttf3Qxf/EWut5TYGDOiaff72qfg06uaf3ZF1yBru1z2HCU9Oyf3yxe9vCNODVMppa5Q2JMTO2XW64AZ7b+HHlNvTTmbjn+oc7NtrYecpG2W1u7KO+HDhbbnHVwJ782T/dOh8TS5be/Azw/DjmVyu6qEVpN/BDRPCO0nX6ACo+T+2Q9BYKSxz/oz931he48dVi8RLSn17gnSO1BdZrtfb1ij2sh2bTK3yzyYbj0gZphsOZxzAF4aC78tdZoYqvmMQmFP9Hh6/+ntv4eP2f3eVku9qkhaBu31ELSW6lKjfC58ALx7PsTNNo7rbuiaMli+GIJijGOmett7lWTJZdpvcukX0no50n+Xbk4vH7mtmW2U0L7GOYGRtpa6dXxdn8Sm49XCRL3u8YCQbtU+4439uswuKmFSdBKydkDP0XI92vwSq89v6J7gNDGUpa5Q2JOjayAmHoKi2n8Pi6Xexpi6qU6OZHU0j/eGrW/KLN+/rIY+E+DIj8bx54bDs8Og9KTcnvWAcczUwA1ZekK6yHXqWtnqtrpUeggGWr1M6OVn3Xoa+wKjDKW+7mnbITkbnpVL/efd0stQcxnwnuaXioqC1smu6HwUHIW35spES2uqSqCupuXrq4ql56jnKLmtd3bc/YlcKqWuUJxm/HQ/rH4c0rbIeHpHsMTU2+B+t1iLRY5N2NIta5DWqn8oTPm7sS9mhPQalGYZDXT8w4zj9dXGi0d9LZTlwNhrDCu7poFruzmS3gFTLQy50Ng3+Fy5DOlj7NPd7+X5MvYNxkvG9vflz/j2ffDPky1/Zkhv+WzZe+RLTZa5Xa/uji9Rc9dPW3Z/AulbZGtg3ZtUUwFP9JFjj1vixC657GVW6v6h8v9W6QnpqQqOaf5aO6OUukLRUSoLYfNrsPYJqbQGzOjY/fxCpfUYENG2a0Bax0/2g82vdkyG5kjfYqz3GCmXA2bAoLPh6pVw00aYaS5z0130/qFybKyO3m617CQgZNOXq7+T+2oqWpahsgjW/wcGzoE+44z9M+6Bv++CUGulbna/b34F6mvgr1tg2j/g0o/gxg1w2x4ICAfvFlzvIC35nqNkxv93/4APF8j9erJgQytPcfqgh162vCq9TDXl0rMDMomzJTLNSXI9Rhn79DJI3cPjJJRSVyhaS85BWPNkY0v40A/SatTpO6ljnzPpFrjiS8Od3Br8zUp904vSFZj0TsdkaI40s1Kf8zCMukKue/nC5Z9A7BS5rSes6UrdL0SOjb3uV7mtD0bRS9K69YJ+k8EnqHXhg43PS4/E7Ids93t4yrIza4Ki5Wz7Dc/C0HkQPUQq5yHnyS/btvyMAUZfYYQI9BcQvSSutV4GRefDOu+iLFv2OdDDMx7esmuhqb55L1jWdpmwGWj1Ih5j7lDoRNc7KKWuULSO+lrZoWzNYzL+Zs3+r4z1mHhjTGp7CY5pe4tZ3VLX3YA9EzsmQ3Okb4Z+U2UJWXMT6ALNpWUWpW6WLayfXOpZ4lvflMf6mV+CfAJbVoz1dfILd8RC6NGKL0v9BUOYYGor3KgtMewiOPMu84aAnf+Dg9/KzYZZ8YrOTXEmfHKl9PyUNQi/rDcr9Il/lS/sX/0VXpkIK+9qfB+QSXK9Rtvu05PlWvP/1I6o7HeFojVY93EuyTSGqFQVQ8ovMPbPcnvanY2vdQa6pa67gPWWqfakphxO7G5ZOephA2v3u77fOxD2fCZL4g58DSMXG6VkPoEtW+rlOXJMar8prZM50CphsYcdXnQ8PGHW/TLr/8ub5D+dmtKO31/hPLa/L1/IIwbJ3A5r9N/l5L9JT9O6p2WSZ95h+UJrncRaniebMY27zvYeg+fKl4KBcxz7HA1QSl2haA16YwmwTRY7/KOM1Y5cbFvm5Gz0RLk6szKvq7b/Z2Rulx2z+rTgRdCbvpSdlHXkPmbPhaZJF33yL5CZJPdZl+15B0qFfSr0gSrB3Vsnc6BVQ5rW9tFvDcMXyKz3inz4foncp1vqB1fK30OPRKk0snfLnILoIfb7fEXH0V8293wiPXF9J0HaJpjzL/jl/+RLZnAPmasxdB5sfQOS3pZZ7tZKXR/i0rOBpe4XAuc87pxnsUIpdYWiOUqzZayte7zMePbwlq4468Yr+7+C4J6yz7gr8Q0BNMAc82ttaVhbSN8sl73Hnfo8TZPKtPSEfAmwLhW7zFzi82i0fBmyVs7W7veacngyFi5cComXGefobtJWK/UOlBaeCm8/iP+DzKrXlbqpVr5MLV8st/3DobJATturLIQrv2r+fgrno3dgLMuRfy/xi+DPP8h9J/fJ35n+fzdmGIy/Xir1hqWLWTsAzUgcdTEqpq5QNMerk+G1qTI5prJQNjXxDzMs9epSOLIKhs1re8KVvfHwAD+r3uX2tNRTN8L/LoWdH0HkGTJbvCWm3i6XelxRR9PkP72227qm3Nr9fvA7qfT12GZ9HeQeki8KAEGtVOrWrWMdQWAEjL/BaL5jHVevLIDFy2HGvbJ/wSNRsmRK0TmoLJDW9H0n4NadMqyic/FrcPmntuf7m//fV+Tb7s/cLlsV+51idoATUUpdoWgO/Y+3PFd+WfsGyVplfZjJkZ9kCduw+a6T0Ro9IQ0MN3xryDkAzw43msU0ZMcHcPh7KEhpfQLfhBvgH4fhT581fVxX6o0s9QrZM1uf/qZb2ptehFcmQfZeQGvdnHmQFvWM++Avv7bu/PZw3lMycQ8ax9XjZsPgs+V6fQ2sfqzp2e8K51NRIBW1hweE97dN/PTwbNyMSO+3UFlouz9nn9Mz3E+FUuoKRVNYtzPNOSDdwj7BsqZan9S1/yvZWKKlGLOz8LdW6m2w1De+IBunWHeFsybbajJZQ8v7VATH2Fri1uixdGv3uG83yD0A710oXdZ9Jsj2sSd2wfYPpCs/6S2p0D29m75vU8y4W07OciR6xYN1rfrij2ULW/1npnlKN29GUtP3OLkPnjD3GFAT3xxPZYFtY6SW8PKR3wEN3e8VhY4L87QDpdQViqbQrXGwUuqBMm5WekLG4dK2wICZ9k3A6gjWfdPbElOvNbu89XapNseqpKId8QfZZGbEgo5IaHDphzD7Qdvub3ryUUUeXPUtxM2S2/89U3oJdGZYNbLpLOjJgLqcF78OZ5wj1z084L4suPOw7JyX0ozX4MRuWX//wz3w7e2Ol7mrU1nYulCSNQHmPAkdU730zrRlZoGDUUpdoWiK3EPGeuY2w/2uu9lSVssmFd1HuEa+pvA7haWetgV+uK/xNZnbjDr7ptzCOftkKc+weTLRq7Vu75YIi5Wd3axdnNaDWCIHwuirjG3rF45RV9pHBnuil+XprXEbtgX1CZTJg73GyHnvTVFhniY3bL6cXlfrgGRHhYHufm8LAeG2MXW9m6BS6gpFJyf3oFz2P1NmfdeUS2tMb/m46yO5jGmDO9rR2LjfGyiEQyth88uN68CtR6U2NWVM729ujxrvlrBW6iBHWM57Sa4Pu8jY79kJi3Z0S33jCzJfIGJg0+fFzZIvUg3jsiaTfCHw8Jb/50Ba7V2Vza/CB3byCjWFEDJXJrCNiZQBEbZKXf+bUUpdoejk5B2WGdaDz5Gu+PIc+cXtHyrbQerWVvQw18ppjbWl3tDK05W83mQja6eM/1orl+omZpmf2Cnjjg0VriPQP8PDSmnHTpXW1Lhr4Y/vd96ysNA+EDVUlkVd97NMqGyKATNld7tj62z3f/wn2QzFL8T4PVZ2QaVenAm7PpYhiJRfZNWDI6gslD0R2jLeGCCsP+Qly5cwkFPcoNNkvoOqU1comib3IEQNhj4T5bYwGclQPUbK/uXeAbazwl1NQ0vdera63tSlLEdm+r4+3ZiMptOcpd4j0fEz2sH4gj3nCWNfeH+4W5977uJeACwDzjYAACAASURBVKfCNxhu3tzyeb3HymSrlNVG1URZDhwyD7SpKjJ+j13NUj/yM3zxF9uYdXlO88mWbSF1o6wI0bu7lWTKZVvGG4P01G19Q/79h/dXlrpCcVogBOQelvPCeySAl7/cr7tY9V7O/uHOUXatxeaLRdjGyHXLvdyqHaYwWxsTb5bLhkqkrlomCTqqj3xDPL3h4WIY/xfnfJ4r8DS711N+MTLcs3cbx0114KeXTnURpW4ywfFN8L9FjRPXGvZkby/vnidDTbnmnIdis1Jvy3hjMHJo0rfIF7Pt78ltpdQVik5MSZbMaI0cLL+E9XIon0C57G7uHFXdyXp9625bX71lrJUL3mKpn2zs0pz8N/kCU9XA/Z6zX3ZJ6ySdstyGuJkypKNPqzu5z/a4Kyz12kp4faacOOhstr4J75wjXzL/8LbtseZ6J7SXl8fJ//8l5q6QzYVJmiNmhOwV/+3t8MFFsMfcoEYpdYWiE6N/yUaZe3XrDVf0DGfdUteVfGdBVwb+TSh1S0w917ZBSlB3mZDm262x+92ZSXJdicjBcqm3G87eK0MPZy6Rte2uiKkn/yznG6Rvcd5n6qRbhS0iz4BznjQ6EpZl2+czfK1i3qVZ8mfv4dX2ag4vX7hmpTHQSUcpdYWiE1JZCO9eAB9dIuPNehKcPh9d/2II7g6zHmjcRtLV6G5bXSnYWOq6Uj9p28q05yi59A+VX3R6AhDIJDm/0MYzyhUdQ59iV5EvLeQjP8qpc7P+KWvb9aQrZ1rqe7+Qy8qCU5/nCKwVrrcfTLxRdgEEY4BPR6ivk0mgfSfL7cJUKDgmEzPb02MiKBqu/s42Sda38yTKOU2pa5r2tqZpOZqm7W3meIimad9omrZL07R9mqZd4yzZFApADmZIXQ9jroYb1su+3iDLkOa/LN2mOmfe2blq1AECzEpdVxrWteq6+70813ZmuT4DevgC2ThFL9UDc5LcyM6VN+AOWCv1g99JD8moPxnHPb1l/oazLPWacjj8gyGTs9EV91mPGPu8fCA8rvnue21Bf1HpbQ6jFR6HwmNyfG578QuBSbfIdc2j8zSgwrmW+rvAOac4fjOwXwgxEpgB/EfTNB8nyKVQSMpy5XLiX20Vtoen/NK17g3dGQnrD/NfMaaaVZXI2eWbrOrTm7PUEy6RbVl/ul9OHgP5xae7ihX2I8BqMMiOD6TFGDvN9pyw/rJs0lElXdYc/lG+9HkHypanzqYkEwbNhSm32u4fOEe+ZKdtht/faP/9y81/1z0SZaveIz9JSz2sf/vvCYbr3rtzheGcptSFEOuAU/l2BBCsaZoGBJnPdcL/aIXCjJ4Z3on6OLcJTYNRlxsNcZJXwefXyuEoeeYOeWU5Rkw9bjb0ny7XPTzgguekm3LVg1BXIy1Ie3WQUxh4+cqytqydcnpb4p8aT/mbcqssq8zc5nh59n0hSzMHTHeRpX6i6bK1QWfJENLbZ8PKO9s3ebAozfBCBHeH0VfAga/l//NwOyl1nybaK7uQzhRTfwkYCmQBe4C/CyFMTZ2oadr1mqYlaZqWlJub60wZFe5MWY7sBtaJkl7ahR4DX/+fxsfKcgxL/ax/STenTsxwmHQz7PwQ0jbJfafrC05nJyAcDn4r1xMXNz6ue1AKjzU+Zk/qqiH5Vxhygeyu5uyYuqkeyvOa7vcQOxW8/IztgqNtu3dZLixNhF/+T/aUCI+DC5fCjRvhzLvkPIOOoI/17T2uY/exM51JqZ8N7AR6AonAS5qmNZl9IIR4XQgxVggxNipKfeko7ER5rvxyOd1jyD6BEBgtR33GL7I9VldpxDD1untrhs6TSz0LWlnqjkGPq0cMbLpbnz7o5utb4dOr4aPFjomxH/9NDvQZNNdogerMCXFVxYBoelqat79U7Dp6X/3iDNl9z9SkzWdQmiUn+53zJNyVLKs8QIbWZt3fuD9/WwnpBZd9Ahe92rH72JnOpNSvAb4QkmTgGDDExTIpuhJlOe5jmYb3l7E+6+SjYPOXWn6yXOoletboSlxviBKolLpD0OfIN9dm2NtsodZXQ+oG2bv/8A9ywlt1qZwtf+DbjstxaKW0hmOnSsvTVCfd4c5Cb1Pc3AjUgWcZ62ufgvfnw3PD4eu/Qeq6pq+x3Nv8EhQz3HHlp4PP7lQtYqFzKfU0YDaApmkxwBlAG/0tCkU7qS6TMUz9y/Z0Z/ZDsOgdcw26OZwQ2k8udTdmU5a6rsT1GepBbvKS09nQB9ToFvup+LN5zv2KG+CDi2H3x7Ix0MeXd6wBkqke9n8tY9e+QXDGuYAGSW+3eKnd0Mv2mlPqQ86TL6cRA+HkXtkJbtx18tihH2R9/YcL4ZdHGl9reWEIbXzMjXFa73dN0z5CZrVHapqWATwEeAMIIV4DHgHe1TRtD6ABdwsh8pwln6ILYzLB+/OkhTL/ZVdLYx9ipxjrvsFQXQxh/WSjj+RVMszQVDa/t5+sTddjucpSdwwjFkr3cMKlzZ+z6D0ZEgofIBWbPvf+N/PkOs0Dfv03nGvVK3/HMpk13hrXctpm2dxl+MVyOyJONlbSmw7V1cjPcORUPF3x+jWjeEP7wr0ZMpGwqsSwistyYMur8h/IctRZ9xuhs4PfwadXnfreborTlLoQoolsEJvjWcBcJ4mjUBgUHJVZxrPut61Fdxf8ukEJti0xh81vPncgKEZaUD1GdrrMXrfB08vomtYcw63GzYbFytn2IF+4Jt0ikxn1qgaQCWdf/VWuj/iDfBmY9c/m779vhZxrMOhsY19AhJEs98FF0kKe90KrH6vNVLZgqYNRGWDt5r5wqWz40m+y7Lvw/RLb2vN9K4xzu5il3pnc7wqF86ivg1enyH873pf79AlO7sa0f8hlz9HGPr2UrSn0RhrDHTjPWtE2GpZfDV8gy8BKsox91uVoez+DXcubv5+pHvZ/BYPnGtMHQQ4pqiiQWfHpW+D4RvvI3xwtxdSbIyAcLnpZlnDqHR91DwPYeqGaCjO5MWr0qqJrUpwmY3Qgl5qnnIftjsT/QZYseVuVB0Wf4lln3CO/ICfc6HjZFK3DulVvaD/ZCTC4Jxxda+yvMFvYU/4uXdV669eGVBbCyiWyL0PDF7eAcGmp5x6USXP5KVBT4TiPjcVS74A1refBWL/UeHgb66d7NUsbUUpd0TUpMMeML/1INqMQwlbpuRsNn01PmmuKYfONWd+KzoG1Up92h1RU3XrKJirVpTJvQrd6h18sY8rVJTJfxLqxTX2tnMZWnA7T7zZKGHX8w2WZmcXqFZB7wJhUaG8q8mW+gKd3y+c2h17FYZ002NVm0VuhlLqia1KYKpc9RsoM266GI5OfFPZHd79PvV3OJgCjC1vJCYgKNmLh/mHmBkpCxputY9F63/Pzn4Vx1zb+HL2Fbep6ZL6ykFMLHaXUs3dDdAcrl738pGVebTU6uLzr5lirmLqia1J4DDx9jdrtrsLt++HWnS2fp+hc6H3KrUvg9C5s+nhSS3w63JgaZq3owHiZba4+3t+s1I+ulS5+nyCjvNHe1NXIBNU+Ezt2H02TLy5VDZR6cA+45vuO3fs0RL2uK7omRekyG7xhz213J6SXqyVQtIfwAXLcr15+BkZymR6XriiQM8J9g63GtxbbVj3opYrNjdPVLfXyHBh6gcw1ObnPbo9hQ/Zu2du9z/iO38s32Nb9Xp4LQy+U2fFdjC72jaZQmCk72fWsdMXpi6bJcb/WClpX6nr8uLJQ7tM0Y35Bea6c0ldbKbeLjkt3dVO91sH2/jEjZDe2k3sd0zo2bbNc9u2gpQ7SM1FdIl9sTPUyFBEY2fH7noYopa7ompSecJ/ucYquiZ4xrrvdKwsM97neRfD9+XJKX9I7crswVSZJNuehCo8z1rsnSKVeVWRbOmcv0jdLWezxd+gXItvoPjNIviwIk/u0fG4jSqkruh5CQOlJpdQVpzc+QdLdbu1+1633hv3If39dZsIXpjbvegfbBMqYYdA9Xq6ftHNcXQhI22IfKx2MDHhTHWx+Ra4rS12h6CJUl8hpZc25IBWK0wFNk0rcYqkXGTFx3wZKvfCYbA9cePzUSh1g1BXQrZccgqL3M8g5YFfR+ehSGbfvM8E+97N+3kMr5TKgayp1lSin6HqUnpRLZakrTnf8Qq1i6gWydztI1/PYP0PkYOh/phwE878/ymMtKfX5L1ndP0RWiVQWyGlxeUdg7DUdk9lUL13lYHSD6yjWnglhHsmq3O8KRRdBL+vppjLBFac5NpZ6oeF+9/CAC56DiTfJuPikm41rrJPhWoNfiCwXW/8f+OFeqZQ7Qk2ZXPafLl389kB/OTjjPBmSgC7rfleWuqLrkZkkp0/1GOlqSRSKjuEfJpM+a6ugtqL5HuqTb5UlXjuWwcDZbfsMvxD5wpCxTYatCo5C5KD2y6yXno1Y2P57NGTEAgjpI0v/VlwPyb8YSYNdDKXUFV2PjK2y+YZv1xr0oHBDos6AlF9l21cwYuoN0TSp8GY/0PbP8Osmm8RUF8vtk3s7qNTNlrq9//76jJPLmf+UXoAu2jVRud8VXYv6Wkj/3T4NLxQKVzNoLphqjVGjbZ121hr8QoyXBmh7h7mKAnj/IihKk9u6+71hMp+96DUaptzqmHufBiilruhaZCTJL5UBM1wtiULRcfpOlMpRH7PqKKUOsvY9akjby9u2vQtHV8Pm1+S23rq2i41EdRZKqSu6FkfXAJrMCFYoTnc8vSFuJhSkyO2w/qc+vz3oFnWv0bJuva1tY3ULXU/Qc5T7XQEopa7oahxdAz1HOcaiUShcwaCz5dK3G4T2tf/9dUu99zjZOrY43Wh40xp0pa5jcb8H20c+hQ1KqSu6DlUlMkluwAxXS6JQ2I+Bc+QyZrhMiLM31ko96gy5np8sp6xl7Wj5et2LUFMul3r2u49S6o6ga6YHKroWJpNsnpGxFUS9dFcqFO5CcAyMvlJ6oBxB+ACpgHuPhYp8uS8/GfZ+Lluy3rjBaCfbkIoCoy+EbqHrSl253x2CUuoK92fVA7DpJUi8HLz87deaUqHoLMx70XH3Hn4xDD5bto31CZLjWPOOwJ7P5PHt78N5Tzd9bfrvxrpuqVcVg6cPePk6TuYujHK/K9yfTea2lzuXyfnK6stEoWg9miYVOoCXj2wzu2+F7N0Opy5xKzgqlz7BUqmvehB+e0G1aHYgSqkr3Ju6GtvtATNcIYVC4T70SJBxcg9viJslO9o1R3mubNsa0gvKsmVZW7decMmHzpO3i6GUusK9OfSd7XZbW2QqFApbeo2Vy0FzIWoolJ2Uo1SboiJPTkvzCYJj66C+Gha+qVo0OxCl1BXuzda3bMt8ou00QEKh6KrETpHLxMukG722wmgo05DyPDlYxSdQzjoPjFI5LQ5GJcop3Jfcw5C6HmY/KMdHduvpmJIfhaIr0XMU3LpDZsXv/lTuy0iC2Gky5m5Nea5ZqZsz3YdcAB6ezpW3i6GUusJ92faOjPuNugKCol0tjULhPoQPkEs94e3DBTJf5fLPZJc7nfI8CO1nKPKhFzpTyi6Jcr8r3JcjP8kYulLoXYI9GcWUVNW6WoyuRY8EY/3oGlh5lxFfN9WbLfUoqfwDo1R7ZieglLrCfakuhaAYV0uhcAJf78riwpc28NqaFFeL0rXwC4E+E+X65Fuld2zLa1Kx/3CPbDjTdwJMvwdu3GhrxSscgnK/K9yX6jLVX7oLsP5ILv/4ZCcAO9OLyC+rJiLIl292ZVFZW8+iMb3RVC6F47jiC1mDHhAJ+Snw0wOyPv3312HSLbJ5DYBPgGvl7CIopa5wT0wmqC03mmYo3JL0ggr+umw7cVFBDIwO4tvdJxjz6M9cN7U/b244BkCovzdzh6tmJw7DJ9D4O7vgOXh+hFTo/abCWY+4VrYuiHK/K9yTWnNLSjWz2W0RQnDrcjlQ5I0rx9oo7jc3HGNApFQ0v6Xk21y3O6OI/VnNlGApOkZwjFFCOmA6eCgV42yUpa5wT07skktlqbstBeU17Egr4u5zhtAnPIDeYf5MiYvg6R8P8c2uLN64aiwPfLmX348VALD2cC57M4t5+sdDAKQ+cb4rxXdfPMxqJWqIa+XooiilrnA/KgrgXfMXtoqpuy3H8qQ3ZkgP+TvWNI2IIF8evHAYt80ZTPcQPxL7hPL6uqOk5pVz87LtlFXXuVLkrkHPUZB7ECIHuVqSLolS6gr3I++wsa4sdbflqFmp94+w/R0H+HgR4CO/2gbFBFFnEvzhtU2I5lqZtkBdvQlN0/D0UMl2reK8Z2DoPIge6mpJuiQq4KFwP3IOGOtKqbstx/LK8fLQ6B3m3+w5g6KlFZ9XVs1DFw7n7OFGiWNdvanFz6isqWfmf9bw12XbOi5wV8E3CIac52opuixKqSvci5IT8O1txraPcr+7K5mFlfQM9cfLs/mvsbgoI1Fy0djevHTZaBaM7gXImHxLLNtynPSCSn7cdxKTqX2WvkLhTJRSV7gXuz6y3VaWutuSU1pFdLDvKc/x9/HkzSvHsuneWWiahrenB3OHSWs9t6yaihoZY3921WHWH8ltdP2KHZmW9WP55XaUXqFwDEqpK04Pjv8GtZUtn3fga+g1BrzNjS58VUmbu5JbWk10t1MrdYA5w2LoEWK46COC5DWXvr6ZEQ/9yAu/HOGFX45w/fvb2JtZbDnvyMlS9mWVcMnYPgA2xxSKzorTlLqmaW9rmpajadreU5wzQ9O0nZqm7dM0ba2zZFN0YmqrZIeqd86Fz6879bmFxyFrBwybLxU7GMpd4XbklFYTFdSyUm/I4OhghnQPZnJcBINjgnl2lUysrKyt57r3krjirS38sPcEX+7MxNND45ZZAwFIy6+wq/wKhSNwZvb7u8BLwPtNHdQ0LRR4BThHCJGmaZqawqGQfaR/e0GuH/y2+fPSf4cf7pXrQ+fB6CvlvoBwx8uocDpVtfWUVtUR3c2vzdeGBHjzw21ysMimlHwWv7EZgJtnxvHy6hSyS6pYfySPXqH+TB0YSZ/wAKKDfUkvVEpd0flxmqUuhFgHFJzilMuAL4QQaebzc5wimKJzY2pQV1zTTFzz/YsgMwkCoyG8P/iHweCzHS+fwiXkllYDENVCTL0lRvUNtazPGmI7/CezqJKLR8mkur7hAaQVGEq9oLyGmjqZPV9YXsPzPx+muq6+Q7IoFPagM8XUBwNhmqat0TRtm6ZpVzZ3oqZp12ualqRpWlJubuPkFoUb0TDRbe1TTZ8XECGXo69wrDwKlyOE4OXVyYBtdnt78PP2tKz3DbcN1QT4eDLXXALXJzyA9AKZ07E3s5jRj6ziuZ8Ps/pQDqMeWcXzPx/h463pHZJFobAHnUmpewFjgPOBs4EHNE0b3NSJQojXhRBjhRBjo6KinCmjwhl89mfY8l+5bm2Zj1wMG5fKmc2l2bbX+IdCzAiYcZ/z5FS4hOd/PsLyrencMnMgY/qF2e2+EYE+NttnD+9uaWIzrEc3MosqOZpbxvM/yxj8iu2Z3PnJLsv5W46eyhGpUDiHzqTUM4AfhRDlQog8YB0w0sUyKZxNURrs/Ry+XyK3q60Gb8z9NyDkBKiGpWtVxRAzHDxVk0R3pqy6jhd/PcK8kT35x9wm3/nbzHt/Hs+N0+PwaNAx7iKz6x1gXmJPPDR4Y/0xVh+S3sHskiryrWrdVcxd0RnoTEr9K2CqpmlemqYFABOAAy1co3A3Dn5nrB9dC1VmpT7zfgiMgCu/ktuiQTewqmLwC3GOjG2gqKKG819Yz4ETaiqYPUjJKcMk4PyEHnabkT59cBT3nCuHjwT5ypfCp/6QwLSBkZZzYrr5MX1wFMu3plFvEpwXLyfCTRtknKP6yis6A04zazRN+wiYAURqmpYBPAR4AwghXhNCHNA07QdgN2AC3hRCNFv+pnBDhIDt7xvx8U+vhj4TIDwOpt8l9/WfLpd1Vt3ATCZp0XdCpZ6SW86+rBK+2ZXF0B7dXC3Oac/hk6UADIp2TP+BlbdO40hOKbOHxjQ6tmhsH4uVftfZcjLcdVMHMO7fPwNQrpS6ohPgNKUuhFjcinOeBp52gjiKzkj6FsjZDxe+AJGD4Z1z4MhP0CPBOEfTwNMH6qqMfTVl0nLvhEq9pKoWgI0NZnor2seh7FJ8PD0aJbXZi74RAfSNaPres4dGExrgTXiAD/0jA7n3XDmwpFeoP5lFlZRXq+x3hetRAUhF5yHpbfDtBiMWyk5wfSZIRe/bwML18oO6amO7ytzpqzMq9Uqp1PdkFPH5tgwignyYcYZqwdBWDmWX8sqaZFYfzGFSXMQp+707Cl8vT/59UTwNvf4b75nFsz8d4sXVyQgh7BYWUCjaQ2eKqSs6O7VV8O3tsnObvSnPh30rIOESo7XrlL/LZUNl7eUL9aeXUjcJ+Menu7j6na0uluj05LlVh/lqZxYlVXX8ZdoAl8lxfkIPzovv0Wh/oK8XQkBFTT0niitJL1BJcwrXoJS6ovXsXi6tab3Dmz3Z+SHU18DYPxv7Bp8LfSZCjwZFEJ6+zVjqoXQ2SqpknNXHy/hTG3jfSleJc1qSXVzFqgMnLduJfTvf7znQnGBXXl3HpMd/ZdpTq10skaKropS6ovWkbZHL4MaWSoc48A2selAq8Jhhxn4PD7j2RzjzTtvzvXxtY+qd3FL39fJgQn+jXW2dSSCEGuNpjckk+HJHpmXGeXZxFa+tTSG9oMKSca6jZ6h3JnSZSq2S5WrrTaw+mMP/fbOfE8WtGEakUNiBzvfXoei8FJnd7vUtz6FuE6kb5HLBf1t3/ukUU6+qpZu/N5PjIll/JM+yv7ymvlMqJ1fx4ZbjPPjVPipr67lkbB+ufW8r+7JKeOL7gwCcOTiKEH9veoS0vde7M9At9cPZpZZ9f/zvJnakFQHQzd+L2+bYp65eoTgV6ltF0XpqyuSyuvTU57WVkkyZ7R4W27rzvXzkGFYhZDZ8J1bqxZW1dPPz4k8T+7LpaD7rDuda9iulbrDTrPzqTYIvdmSyL6uEyXER/GauGrhmciwzh3TeBMNAX9lu9tNtGZZ9O9KKuHpyLJuP5rM1VXWbUzgH9a2iaD16y9ZqOzdSKTnRNpe+lx+k/AIfLoArVhhKvWGWfCegpLKOEH9vgv28+ePY3oZSr6ilV6h/C1e7P5uP5vPjvmw2H5XKu6q2npd+TWZk7xA+vHYCHh4aheU1hDVo4drZ0F/Qfj2Yg6+XB9XmYS/TBkXioWm8vfEYaw/nMn2wamutcCwqpu6urHsGfn1UWrPtoSgNsvfY7rModTtb6qUnoFuvls/T8TJP5kr5VS6risEnuFO2iC2qrCHE3xuQncv0TqTF5qz4rs57v6XyzsZUsopljsR7m1LJLqnin+cPs7Rt7ewKHQylPqR7MMuvn2jZPzgmmFtmDaSbnxefJKmBLwrHo5S6u/LrI7Duadj6ZtuuqymHz66FpYnw5lm2A1WqHeB+N9XL4Szd2mCpezYYt9lJW8QC5JXWEBkk5Q328+brW6YCUqkXlNs5N+E0JLe0mgn9w/npdjnfPL2gkrAAb8bF2m9QizOIjQjk7nOG8PbV4xjZO5TJcRH0iwigV6g/4YE+jOobRmpeuUqQVDgcpdTdFX/zl+LP/5JtVFvLvi9h72cwcDbUVULaJrlfCCOmnpEElUX2kbMsB0R929zvokHnrqqiTqnUTSZBXlm1zcxv3Wr/6Pc0Rj+yiu92n3CVeHYnvaCCS1/fxKPf7mdvZrHNMSEEr61NITWv3GZ/blk13UP8GBwTTLjZIh/Svdtp18DFw0Pjphlx9Az1x8ND439/mcjqf8yweBv6RwayL6uExW9sdrGkCndHKXV3pL5OKt1uvaCmFAqPtf7aUrOSufi/sh3r0TVyu7YSMFsZ1SXw9S32kVWXLbx/66+xznyHTmupF1XWUmcStko9QCr1tebY+qfb3Mcl+8IvR0hKLeT9TcdZ+OpvFJbXUFNnIi2/gvVH8nji+4N89HuazTW5pdVEmT0Z3fykC9tdeuRbT33T3fObjxZQ2ISH5ssdmfzh1d/4ZGs6NXVteAlXKBqglLo7UpEPCIibKbcbxsatydwmXeA6ZSfBNwQCwmWb1kPfw/sXQdpvttcd+BbyUzoua8FRuQxvQ5ew2gY1v51UqeeWypcPa6Ue5OOFl4dG925+XDyqFxuT86iua3/P8Kraep5bdZiTJVUtn+xAMgorWLEjkz9N7Me7fx5HdZ2JTUfzmfzEr5z59GqufPt3APZbTasrr66joqaeyGAjPAEwpEew8x/AwVw4sqdlfd2R3EbHb/t4J0nHC1ny+W5eXWOHvytFl0UpdXekPEcuY88EzQNONjPsLnM7vDEL1j9r7CvNhmDzhKoBMyA/GY6uhjVP2l7r4QmbXu6YnEXp8NXNcj2kb+uvs7bUayqgMNWQuRORV2ZW6kGGUvfw0HhyYQIfXDueOUNjqK0XHMpuOUchv6y6yf0PfbWPpb8c4ZtdWfYRup2s2J5JvRBcf+YARvUJw9ND46Pf08grq2bxeON3e+CE8awNfz7d/M2Wenf3sNStOaN7MCmPnUd4oA+/HsyxOdYwafLl1cmk5JY5UzyFG6GUujtSbrYEQvtAWH/IPdj4nIoCw9I+vsHYX5YDQWYF2SPR2J8hLS0m3QJT74CRi2HnMvjpfji+qX1yHrJql9qWzHXrbnL7vpDhgPg/tk8GB3LCnNEdGWyb2LdwTG8GxQST0Ft6F3ZnFDe6VufIyVKufXcrYx79mXu/2GMz3vOTrel8bM6oPtogVu1sdmcW0z8ykJ6h/vj7eDJxQLil2c61U43QSl5ZtcWDsS9LWu3dzQ1lgn298dBgUIxjxqq6Gk8PjRmDo1h7ONemQ15OAy+Ln7cH969QU6cV7UMpdXekzKzUA6MgagjkHpbbJpNU5tVl8OIYWPkPud96NnlZNgR3l+shTZSZDZwNcx6CyX+TXa6QmQAAIABJREFUyvW3F+Xcc4Cv/warHmq5jC79d0j+BXIPye3LPm3b81lb6ptfhcgzoN/ktt3DzuSVVXPde0mst3Kt/pacR2iAN/2aGRPaO8yfEH9vG5c0wN7MYsuX/q3Ld/KL2bJbvjWNs55dy7bjBezLKuaBr/YyZWAEo/qGkpLjWstuX2Yx8b2MEMjd5wwBwMfTg9gGo0wPZsvnfWP9UQZEBjLe3EJ3XP9wzhnRHT9vTydJ7XxmDommqKKWHWmFln1FDSz1G2fEseloPv/3zX5L21yForUope6OFJuTr7r1gqjBUJAC9bWwbCE81V8q4soCo2lLcbpU+NveM7uyuxvX6+gxbx+zFRV1BnTrLdcj4qQbfPv7sPF5+Plh21K4hrx1lmwcc3If9J0Eg+e27fnqrGLqJ/fCmKtpNA/Tybyx/ig/HzjJFW/9zsurk2Xf70M5zDojutkxoZqmERcVyFErV+uejGIueHEDL/2aLM8x7580IIKPr59ETmk1C1/dxPkvbCAswIell45icHQwR3LKMJlcUy51PL+crOIqG6We0DuUqyfHcubgKLw8Pbhl5kBGmQexvLw6mcmP/8KOtCKmDorE2/zzuXZqf165fIxLnsFZnDk4Ck8PjTWHjJe/ogpbpa7PCXh74zE2JOehULQFpdTdkaI0aaX7BEgr1lQnXe16s5YNz9meX5wOP94L39wqt0P7yaWfVWxz1BVyad217dofzeeFQv4RY//G5+GX/2taNmsr/uQ+iBnetmcDOPMuY93TF0Ze2vZ72JHfkvN4c/0x5g6L4cKRPXn6x0PMf2kjhRW1zBl26lh/XFQQR3ONF6As8+CP3RmyZLCsuo4zYoJ57U9jGN8/3KZV6mtXjCEyyJdpgyMpKK/h+73ZDni6llm2JQ1PD80mGQzg4XnDefOqsQDcefYZrPjrFHqE+LH5aIGl2UxMt87Zy91RhPh7Myg6yMY7U1hhmw0/rIfxclRbr+raFW1DKXV3pOg4hJqTk6LMQySythvHrWeRD7lA9lzfYjVMJbSJpLWJN8HCt6SFrhPSW2bI15QZLn6d4gyaxHp/TWn7lPqEG+DS/8n14RfLTH0XcTy/nL/+bzsDIgP5zx9H8sKliTxy0QiSc8rw8fRg2qDIU14/ICqInNJqSqqktWbtb6irN5FZVMmcYdGWUjhvT3nG4wviSewjLd9zR/QgPNDH0oLWWRzLK+dkSRUfbj7O+fE9WqWgX758NJ/fNAk/b/nV072LKXXQX+QM70yx2VLvFerPLTMH4u/jyXnx0lvWUOErFC3R+fpqKjpOUZoxgzzSrNQzthrHPX2hz3hIXS8V89ALYcUNxnHdUgdI/JO09L39If4PjT/LO0Aq9bxDoHlC9FDpEi83uw1ryuU5untcj6PrxMS37xnD48DLHyZc377r28HG5Dw+35bBYwvi8fP2pLSqlmvfSwLgzavGWkqyrpjYj3GxYeSV1lj2NUdcVCAAR3PLSewTSo05hiqArKIq6k2CPmFGTPr2OYPJK6vhvBFGsx5PD40eIX7klDqvrO1EcSUzn1kDgIcGt80Z1KrrRveVTZF8PD2oqjVZkuS6EnFRgXy/9wTZxVXsySymsKIGLw+NDXfPtDTdeXJhAiv3ZFsUvkLRWpSl7m6YTLJUTFfMvsEy9q0r9aghMO0OI24eFAPxiyBqqHEPa0v9opdPPRLVJ1Aq7tyDsoHMX36FxMsh94Ac1PJYT9jymnF+eQNrMnoo7SJ6CNybAb2cE4Otqzdx+Ztb+GJHJl+by8ce+mofx/LKeeWy0fSLCLQ5f0j3bkxtwUoHiIuWOQp6oltZlcxuF0Kw0+yCH2EVqx4UE8wnN0yyWO460cG+5JQ2XfbmCNZaxYQXju7NgKi2Zaz7eMlkuK7mfgfpnTEJuOOTnfzl/SQ++j2N0ABvmy56Qb6yn0FhRQ27M4o4/4X1Tn1pU5y+KKXubpRlg6nWVjFHDTYa0Jz9b5hxjzETPbi7rDm/ZiVc8LwsDfNpOlu7SXyCzEr9sIzfe/lC/zNlEt6Bb+Q5O5cZ51caWb+E9QffDpQvOXGAS65VnfjHW2Ui4qaj+VyQ0IPJA1tW3s3RNzwALw+No3lSqZdWGSVr248X4u/tyZDuLTdjiQ72c5pS/+eKPTz49T4AfL08uHV266x0a/42ayBAp52P7kjizC9Av6Xk4+PlQWFFraV9sI6maYQGeJNXVs1dn+5mX1YJB0/YeZCSwi1R7nd3o/C4XFq70KOGGElyeqJbvdmt52tWGAHhMPYa+a8t+ARIBV6TCUPOk/sGngVosMsc987eA0tHyjGp1kq9PfF0F6HXnI+LDWNraiHJOWVkl1QR28BCbyvenh70jQggKbWQepOg1BxbrzMJfj2Yw5h+Yc1mz1sT3c2X/LJq6k0CTw/HVQKkF1SwbIu0LD++fiK9wwJsOua1lqsmx3LV5Fj7C3gaMCDK+D9z3dT+eHl64N3E7yzE35tPkowclLxmGhApFNYoS93dKDL31g6zUup6XB0Mpe4Xat7uYEtOn0A5UMVUJy11gMAIGbPP2mGcV5gKSW83UOojOvbZTiTbrNRvODMOgFfXpCCEtLQ7yqIxfdhyrICbl20nz9wXfMvRAtIKKmy6sZ2K6GBfTKL5znMdYcvRfG7+33ZKqmr5ZrcMPXxzy1RG9Q1rl0Lv6gT6GrbUtEFR3HHWYP7WhLcjp6TafI70BCmlrmgNSqm7G7pSD+lt7LPOWNfL1M55HM5+DPpP79jneVtZqlFWLw+Dz2lwogY7/yfDA6H9YPwNkND5usA1h26pj40NY3xsOJ9vlxZUHzso9ZtmxHH/+UP5YV82/9sif3819SZ6hvhx9vDWtb+NCpZu7Pa44I/nl3Pu0vWWTm8N+XRbBt/tPsGzPx3m651ZjO4bapfn7sqEmnMi9Jr0ptCb8vznjyPx8fIgv8zIhP8tOU8l0SmaRCl1d6PouEx+8/Y39llbxLql7h8Kk27ueNMWHyulHnkKpX7RK3LQzIFvIDASzntKNq05TcgursTP24MQf2/mjzLqsWMj7aPcrps2gMcutq0EuGJSbKtc7yDd70CzivlUvLXhGAdOlDDu3z+zKSW/0XF97vv3e09wMLuUeQ3q0RVt54e/n8n6JTNtJrk1ZOniUWx/4Cyig/2ICvK15HUk55Rx2ZtbmPHMajWfXdEIpdTdDesadR3rJjI+HYsBN0K/n6ePrSs/eqgc0uLpA/NegoRLjaEt+qz304jj+RX0DgtA0zTOj5flZNMHRxEdbL9Er0VjDe9KoI8ni8f3afW10WY3eE5pFcWVtdS2ob2ov1Vb1id+ONhIURzPl81xTpZU46HB+QlKqXeU7iF+LXo7gny9LDPmI4N8LJa6Pra3sKLW0sRHodBRiXLuRlEa9BrbeP+AmXLamr3bqepjW7s3qDfXNJj7CNRWQOJlct+4P8sWsqWu6XzWHipq6vDz8uTwyVKG9ZQvR6EBPqxfMtNiHdsLb08PXrpsFLX1JsbFhhMa4NPqayPNk86O51cw8l8/sXh8Hx5fkNCqa708jf8Tu9KL+C0lnynmjH6TSZBeaLTlnRwXqeLoLiAiyJeMwgqyiiptmgwdOVlKr1D/U1yp6GooS92dMNXLjm1NdYS7/FO4J93+n6kr87Mfa3xs+EWGQgeYeLPsYDfpFvvL4QCyiiqZ8NgvzH95I2kFFQyKNjwRfcID8PWy/+CRCxJ6cvGo3vQOa5tb38/bkxB/b95YL+fTN+wZvu14AY98u9+ybTIJS6/4kkqjjC4yyIeXVydbtp9ddZiaOhPnDJd9DZTr3TVEBvlw+GQZk5/4lbWHc7koUf4ekl08yKcrkVtazf1f7qGipq7Zc/67NoUln+2yVLG4AqXU3YmSLJmF3pRS9/S2dcPbi36T4IF86Dux5XO9fODSZZC42P5yOIA31h+lus5ETmkVJgFDe3SwUsDBRAf7WnqFnxFj+7teuSebtzYcs8zuPuOB7/nbRzvYcjSfDzYft5x3/ZkD+C0ln+ScUt7ZeIyXViezeHwfnr1kJEvOOYN5iUqpuwLdE6Mzf1Qvs6LveO26EELF5lvBks928eHmNDYcaXrIzuGTpTz+/UE+ScrgBxfNYQDlfncvUn6Ryx6tc7vaDSc2gXEm6QWVxEUF8dmNk1h3OJezhnV3tUinJLqbL0dy9CY2tpZCoTnZLb2gguAe3aitF3y354QlPgsyC3/igAgAknPKeXbVYc4cHMWjF8Xj6aHx1xkDnfQkioZENFDqE/tHMMg8na+jXPHW7xzJKeXiUb25cfqANoV9uhLrzMpcTxxtyMurkwnw8aTOJFhzOJdFY1ufE2NPlKXuTuz9XNaK9xztakncgryyaiKDfAj0/f/27jtOrqps4PjvzGzvfTfZTdn0XpcUIJAgLfSOKNjgpSgWFEUURAVfLNiQFxQEURSkiqJEeigJIQ3SezbJbrb3Xue8f5w7szOb3WTrlLvP9/PZz87Mvbs5T2bvPPf0MFbOHjWsi7oMBe9Be94r0wFUWRuDFFY3eTaP6e6Oc6cx2uqfXZ9fRX1LBytnZQV93CNBWpxvoo2OcDI5M479pQ0+tez9ZQ39GiSptWbT4WpcGn7/7gH+vmEYuuhsoLi2mU6ru6qopvmY4/kVjbyypYjrlo7jgtmj+OhgZcBaPySp20nNEVNLD/De4qGstrmdDutDsbKxldTY0Km1ZHgNYKtv7a2m3uyziMnfblgMwNRM07WQGhtBRJiDN3eVAjBz9DB02Yh+825+X/X1ZQBMzoijvrWDUmuRmtrmds781bvc8eLWPv/eioY2mts7+cryiYQ7lad7Rvha7bXXQWEPSf2R1fsJdzq44dQJzB2TREVDG8W1Lfzj40Lu/fdOz/gVf7Bnu+lI1VBm5qiLAdlVXMd5D76PUynGpMRQUNXM2UHe5O7Ne1R6Qy819YLqJsrrzeOnb1jM3DFJvPnN00m2FkNRSjE6MYpDlU0oBVMyg3scwUjhntqWmxbL9FEJ1mOzhvyhykayEqMorjXJ5qXNR4kKd5IRH8k3zpzS8y+0/HntIQDGpcYSGxlGY2vvg8BGoqKaZu79905WbS9hXGoMyTERHK32TeqF1U28tPko1y4ZR3p8JHNyzAZMWwtr+dmqPZTUtZAeH8nNp/tnXQ6pqdtFa4OZPhabHuiShKy3d5ehNVx/ai4N1odbalwI1dQTfJvfvZv/qhtNDaygqslTU0+zbgImZcT59NmOSjRN8BnxkUSFD/0If9F/7laYC+d0bbmbFm/+Nt3z10u85qw//dERnvdaN74nhysbecia6TAmJYa4yLBjbgZHipb2Tl7YVHhMjfq6xz/i7d1lfOPMyfzna8uYlhXPruI6T1M8wB/ePYhScNPpEwCYPiqBMIdia2GNZ2vhS+dn+y0WSep20WCaS6WmPnAfHqhkWlY8d543nTOmZgAQ7gidSyQhqqvhrcOlaWk33QitHZ2em5SC6mbP+vDdR1S7uVfJGy3zn4NGalwkm+4606fm7a69VzWa99O9VvyVC3M4b3YWDa0d1Da18+3nt1DT1DW467kNBRRUNfHGTvOZMSoxirHupD5Ca+q/fWsftz+/xdPtBKYf/UB5I986ewrfOHMKcZFhLJ2YSl1LBzuL6nhtRwl/XXeYVduLOW/2KM/NcFS4k6lZ8Ww7WkttczsXzh3t1y2GpfndLtz7lMdlBLYcIUprbfattlZLWzEtnWc3Fgz5AjPDKaVb/399SzvREU5PLT02wklhdRMlda2EOxVJ3bb7dJtkzcePGoZ5+GLguo+AT7FGqVda4yVK6kxN/b5LZ/HgW/t4bUcp6/IreX5TISflpnBV3hhqmtr4zotbyUmOJjE6nKmZ8bx222mA2Wim8ThzsO1s+9FawAx4c/v4SA0Ai3JTPa+dPDENh4LnNxXwlw+7poJ276aak5PIq9vMtLberrPhEjrVEHF8npq6JPWBKKlroa6lwzMX/dxZo/j3V08NqcVW5uQk8X+fWcD9l5kFgeqsptSjNU0AnJSbQku7i81HqslJjul13fFJGaav9niLbIjAC3M6SIoJ9zS/l9a1kBwTTmSYk/iocDpdmkNWktp4qAro2hugsLqZHUV1nDWjq2VvpDW/7yiq5VO/XM2u4jq2FJgEfv+q3Sz7+ds8te4w//fOfhKiwnzWp0iPj+SaRWP5m7XxkltOsm+r1pycJGqb26ltbveMV/EXSep20VBmvkvz+4DsLjGLeEzL6hrtPSs7ERViMwnOnzPK02zubnI9UmWS+ikTzdKv6/Orjrvu+IQ0s57/gnGht0b/SJMaG+GZN11a1+Jp5o23umLcK85tOGS2PK6wbgBuWT6RKZlxXLqgq693pDW///qNfRwob+TyR9bS3N7pGYBYUNXM3S9vZ1dxHb+9Zv4xK0d+86wpxHQba9L9epqdneh57O95/9L8bhcNZaAcEJN64nPFMdbsqyDMoZgW5KvG9YV7Gl5FQyt1Le1876XtAJ6FZQDGHSepj0mJ4dWvLfPU2EXwSo2NpNLqUy+ta/Uk9Thrz/b95Sap51c0Ul7f6hkkeen8bO44d5rP7xppSb2s3nRXNLV1ctuZU8gbn8xn//gR1yway/Kp6YQ5FCumHtvymRoXya1nTOL+Vbs9r3WvqU/N6vocSfJzTd1vSV0p9QRwAVCmtZ51nPNOAj4EPq21fsFf5Qt5jWUQkwYO6Qftr06X5oXNhZwzM4uEKP9egMPBPbWtoqGNlzYV0txuNt2ZmNG1Q9+41OOvLT9D5qeHhPT4SLYXmf7g0roWZli1Tfff8cdHaogMc9Da4WLT4SrPIMme1l8wU9o6/VTywNJae5bYnZWdwC3WPP3fX7uAUyene26KenPDsgnMzkkk3Ongpc1HSe823iHc6SA1NoLKxjZiIvxbd/Zn8/uTwLnHO0Ep5QR+BrzujwLZSkOZ9KcPUE1TGzVN7SzKTQl0UYZEildNvdia5nTR3NE+Hy5zcpICUjYxtGbnJHK4somyuhYqGlrJtAZ2xnvNhJidnUhkmIP1+dVUNLThUD03CcdFhXlGzNtdXUsHLe0u7lw5jZduOYWIMAdKKc6dNeqECR3A6VCcPDGNk8ancP9ls3vspnvs83mMTYnxzFv3F78lda31e0DVCU77KvAiUDb8JbKZhlJJ6v10sLyBX7+x19PP2H30eKgKtwZQVTS0sre0nmlZ8Tx4zXyfc+aPlaRuBwutcQ+v7SzFpbvWKojzSup3rJzGvDFJvLevnPWHqkiJjexx6d94K5l9/+Vtfih5YJVaMwVGJ0UTETY8aXDB2GTe+84Kv08NDZo+daVUNnApsAI4KcDFCT0N5ZB2/NWjRJeqxjbOe/B9WtpdnlV17ZLUwcxB35BfTUldC8smp3le/9VVc6lpaifcKWNk7WB2diLhTsWrW4sByPIMlOvqRjppfAqLc1N48O39OBRcs6iHXRyBi+eP5iev7qKw+thlUO3GndT9OX/cX4ImqQO/Ae7QWrtONOJYKXUjcCPA2LE9/4GOKNWHob5Yaup9pLXm5qc2eRZncU9PsVNSz4iPZO2BSnLTYrnptK7lKS9bkBPAUomhFhXuZFZ2Ih/lVwIwKskkKffc6KutncKuP3UCkzLjWToh1Wc5YW8Z8VGcMS3DM4DMztyr72WG0DoUfRVMST0P+LuV0NOA85RSHVrrl7ufqLV+FHgUIC8vTzYCfvfnEBYJ868LdElCwrajtaw/VMUPL5zBJwU1vPxJEWCvpP7dldM4UtXEuTOzCJNaua0tHJvsWShlXKoZDBkbGcYHd6zw1NwTY8L7tOZCQlQY+8vsPwK+zJqvb8eaetBc7VrrXK31eK31eOAF4Ms9JXTRg4J1kHsapE0OdElCQlGNuUvPG5/CRfO6PuiSbbSP9JycJC6YM1oS+gjg7ldPi4v0GeSVkxzT7/c/MTrctju1uVzasy1taV0LidHhttzbwG9XvFLqGcxUtalKqUKl1PVKqZuVUjf7qwy21FQFlfshR4Yh9JV7sY7UuAiWTU4nOSac+MiwYRswI8Rwcif18SeYptgXCdHh1Le0+3WrUH95cu0hJn9/FR/sq6CktsWWTe/gx+Z3rfU1/Tj3C8NYFHsp3GC+j1kU2HKEEPcGGCmxEYQ7HVy7ZBxbC2sDXCohBiYjIYrpoxKYPQRTpxKjw3FpaGjr4N5XdpKbHsuXl08aglIG3tu7zaSqu/+5ndhIpy2b3iG4+tTFQBSsB+WE0fNPfK4AzAYYcZFhnuUfv3X21ACXSIjBeemWkwlzDn5JY/eiNaW1Lfzj46MsnpDil6SutfaZ611W30JBVbOnFWIo5Fc0EuF0eDZtuWKhPQeNSntjqCtcD1mzICL2xOcKwDS/22lQnBDREc4hmaaYYI2aX72nnA6X9mwWM5xe2FRI7p2vUt3Y9W9d9vBaLn9kLa0dQ7PCXV1LO0drmvn6mZOZZi3hmmXTmrok9VDm6oSjm6U/vZ8kqQvRs4Ro03j72g6zbWhFH5L64x/k8/kn1g/437z9+S0AfPO5T3hndxkdnS7PXPmdRXUD/r3e3LvVTUyP4+ufMgOKMxPtmdSl+T2Ule2EtgbIkf7046lvaWdrYS2nTEqjtaOTw5VNTJbNSoQ4xqhEs/rZxsNmV7eqxlZcLt3rNr0A9/57JwAdna5+j7ava+kaaf/OnnLe2VPuc3zzkRrmjx18E7x7p8JxqTFMzYzn11fP5Yxp9tzRUmrqoazoE/M9Jy+w5Qhy331xG5/940ccrmzkW89t4UhVk8+Wk0IIIzspGnf+jo1w4tJQ08cpbu6pov2xId935XB3LRrM+urdj/dHR6eL/311F69uK+ZwpUnqY1JicDgUl87PITE69Ddv6onU1EPV0c3w/i/N40R7DvgYKusOmtW2lj+wGq3hzpXTuGDOiRfiEGKkiQhzMDopmsLqZj41PZN/bSmisqG1T91VhyobGdvPaXUfHqgkIsxBW4eZP37rGZP47Vv7ALhsfjav7yw9YUtBb3aX1PPoewd9XuvLZi2hTmrqoeqxFVCdD1FJZjU50aOW9k7qW8wKWVrDjadN4KbTJ57gp4QYucalxqAUrJyVBcCDb+/v9VzvgWyHKhv7/W99eLCSBV6bC4U7HTx74xJevGUpJ09Kpba5nZ3FA+tXd9fO3bX/RePtsQvjidj/tsXulNyXHc8H+ypo63Rx1/nTmTEqgaUTUwNdJCGC2pnTM0mJjWTFtAwWjE3iP1uL+NFFM3usrbvXUAd4c1cZn1s6vsff2X3KGpgtj3cW1/GNT01hVGI04daUvMUTzDWanWRq/esOVjIru/9z8N396Dcsy+WGZbl02nBBnZ5IRghF2uuPs6O1l1M0/9laPGRTQkLVGztLiY8M43NLx3PypLQe9z0WQnT54im5/O6a+USFO/nhRTNxaVi9p4yapjb+8XEhL20u9Jy72hrYds7MTN7bW86+0vpjft/e0npy73yVD/ZV+Ly+7mAVWsPJk1L59dXz+PkVc32OZyVGMSEtljX7K3w+xyobWj3N9b2pbGjlZ//dDZgd6+KjwnvcQ96OJKmHoqbKrscdPQ9O2Xykmq88vZkfvbLTT4UKHu/vK+fpj47Q6dK8tbuU06emyxKwQgzArNGJhDkU+8oa+ME/d3Dbs1v45nNbPFuXPv3REeaNSeJ/L51NZJiDP609dMzveGNnKQDv7CnzeX3dwUqiw53MzUk65mfclk5M5Z095cz/8RsUVDXx7IYjLLn/LX75xp7jlvutXebfGpsy+KVzQ4180oWi6sNdj1Mm9HiKeyTqK1uK/FGioHLd4+v53j+2seFQFRUNbZw1w55TV4QYbg6HIjUugtK6FlbvKSPVaoIvrG6ipLaFPaX1nDsri9S4SC6Zl81LmwupafKd215u7YjWfcvXDw9Ukjc++bg33ItyTT94U1snlz2yljte3IbW8MaOUrTuvTm9xLrpePamJf0POsRJUg9FDebOl2Xfgs/1vJGduz+pvqXjuH/8dvbrN/YS5lAsnyr7zAsxUGlxkazeU05dSweXWVNBL3/kQ5bc/xYAp0xMA+CLp46npd3FM+sLfH7endRdXp9DFQ2t7CmtP+EYlxXTMlg2OY0rF+ZQXt/K/yzL5Y5zp3GwopHcO1/lzz20DIBJ6imxEZ559yOJJPVQcXQzlJk+Ik9Sz7seEnP4x8eFfOnJDZ6+rg/2VfCL17qap+pb7b8/spv3YJiP8qtYlJti2/moQvhDWlwkVY1tOB2Ki+d1re9w7ZKx3HHuNGZlJwAwLSuBkyem8uyGIz4/X1BtKhgNLV2fQ+f+5j0Alk44flJPiArnqesX8/Mr5vD+d1bw/fNnsGJauuf4D1/ZwX+3lxzzc6W1LbbdsOVEJKmHisdWwMOLzeMGq28qNh2XS/OzVXt4e3cZ33xuCwVVTTyxJt/nR913ypsOV3HKT9+mtsme+yUDFNU0+zyfmC4rxwkxGGlxptk8b1wyE9K79pi4c+V0blk+0Wfw6UnjUzhc1eQZyNbc1ulZ6rXBqly0dbioaGgjOyn6uP3p3pRSjLH6x72v6Xljkvj63z9m85Fqn/NL6lrIsunWqiciST3YtTfDI6d2PW+uNjX16BQIi2BdfiUldS1cNt/cQRfVNLPtaC1Kwf8sywW6kvoDr+3laE0zm44MfJWmYOfegclN1ngXYnDS4sw1tHxqBjERXbOgY3tYyCUnORqtobjW3FxvKayhw2o9c9fUG63kfsOy3AEtKqOU4tHrFvKH6xbyx8/lkZkQxTef/YSOzq4R8aV1LWTZdG33E5GkHuw2/glKt3U9f2Aq7P0vxJnBX89tKCA+KozPnTwegPf2lVNe38rPL5/DlXljgK6k7rQuoIPljdz4l42eTRvsxL1QRaQ1+Mb9gSSEGJgMqxnbu9m7N+7adPcNWdLiIj3dgO4a+2BxH22sAAAgAElEQVRWdzt7ZhbnzDQD9L533nQOVTbx7l4zvc7dEjBSm99l8Zlg1t4Ma37j+1pnK9QdhQmTqW1uZ9X2Eq7My2GcdTE9v9H0q58+Jd2zFWN+RSMdnS7arTvZn/93D22dLmIinJwzM8t/8fjBzqI6spOi6XC5KK1rJSV2ZDbBCTFUrliQw+jEKKZlmb7zH100k+ReWsByks3AtEffO0hbh4uC6iZiIpyMT43x1NTdST0+amjSj3uEfIE1OLis3ox8t+vWqiciST2YbfqzaWq/6CF484fQVAGTzoSFX4TEbN7ZXUZrh4vLF+SQFBNOhNNBWX0r00clkJEQhdaa2Agnv3pjLw+v3k9Lu0nqbZ0uUmIjOFDe/2Udg92OolpmjE5ga2ENAKlSUxdiUBJjwlk5e5Tn+eetVsGeuBPpu3vL2XCoionpcYxJjiE+KozC6ma++szHnilvPTXfD6h80eEoBVXWWCH3HHq7bq16ItL8HqxKd8BbP4bxy2DBdXDVn83rE8+A6RfA6PkUWf1WU7PizWAVq3vq9CmmmUwpxT++cgo/vnimJ6FnJ0Vz3yWzuGjuaA6WN/Q63a22qZ1thbXDG+MQa2rr4GBFIzNGJXheS5U+dSH8Jszp8KwL0dbhYtvRWnKSo4mLCmdfWQOvbCnifWtluaHaXMXpUCRFh7M+v5IrHlnLazvM7KCRWlOXpB6sdv4L2pvgskfN8/Gnwg1vw5Ive06pbGgjJsLpGbxyijXn89L5XdNOpmTGc92ScZ7nt501hWuXjGNiRhyNbZ385k2zI1KnS/OrN/Z6lmD8zB/XceFDH/DCpkKueXQdO4vquH/VLq5/ckNA1lCubGg94Xz73SX1aA0zRycwLsWM0h0pS0MKESx+edVcfnfNfO46fzpg+tlTYkxt+pRJXVPYhqr5HSA5NoJ1B6vYeLjaszOb9KmL4FK206wWl+C1RWjOQs/D13eU8PgH+Z4+LIBHrl2I1hAd4fT5Vd5TTtzLJp4/exQ/W7Wb13eWcttZU1ifX8WDb+1jT0kdoxKj2WENcHnwrX0cqWpi1fZi/vCuuVhWbS/269altc3tLLzvTW4+fSLfXTmt1/Pcg3JmjE7g4WsXsGZ/xTGrWAkhhldCVDgXzh2Ny6UprW9l5awsshKjuGR+NhpYs38tMHTN7wApMREcpJGxKTEkRodzpKqJ5JiRuT6FJPVgVbYLMqb3evjGpzYB5gJyiwp39na6xzhrv+OU2AgunZ/NU+sO88G+CjSmFuxuurr+1Fx2FNWy7qCZ/vZJQQ3ZSdEcrWlm46Fqzps1CodDUVTTTGJ0+JBeoN0dLG8A4PfvHjhuUt9RVEdidDjZSdEo5btQhhDCvxwOxR3ndl2vGfFRNLV1LUAzlHubu2v9SyakcO8ls6hqbBuxmzdJ83swqiuGqgOQOeuEpzb0cbU49wIS6XFdNddsq5Z/7eMfcdBr0NxZMzK549xpPpshfFJQ4/m3nlx7iDte3IrWmpN/+jZf/NOGPpVhoLz3af7MY+vYdLjnefY7i2qZMSphxF7MQgQ7n3nuEUOX1N0ti2dOzyQyzDkil4d1k6QejD58CFAw99M9HnZ59WlXd9s8oTf/uvUU/n7jEp/FHkYndf3hP7O+a2nHn1wyi4gwh09Sr2/poLa5ayW65zcV8uwGs8bz+kPDu5hNfoWZqvL1T01mX1kD33puyzHnvL6jhC2FtcwcnXDMMSFE8BnIwjO9uWbRWABOn3riufR2J83vwaKtEdqawOE0C87MvgJScns81T3qHfq+teDopGifJA749DntLjH7IP/yyrmexSYmZcQDkBAVRp01x3TGqATPxgx3/3O7z++ramyjoqGVKZnxfSpTX+wrrefBt/aRnRTNbWdNQWvNQ+/sp63D5bO70/ObzPz8S+ZLk7sQwezR6xay8XD1iU/sh9vOmsKtZ0zyrM0xkklSDxZPnAslW+HCB6G90WeUu9vRmmZKaptp6zBJ9fpTc7nptJ63Xu2Lk8ancOn8bDpdmn9tKSI5JpzLF+Z4jp81I5MXbl7KmJQYznhgNY1tnVx/ai6XL8xhW2Etlzy8BoCkmHA6XZrlv3iHupYOzpyewX2XzB6SZRrdzWo3n27iHJsai0ub/4vctK51qGub21mcm8Ks7MRB/5tCiOFz9swszh6GRa8koRvyvxAsSraa7ztfhqSxMGquz+FV24o577fvc81jH7GjyMwf/8zisZ5a9UBEhTv59dXzuPn0iQDHrBLldCjyxqeQmRDF7ByTLJOs2v3snERuO3MyYC6mTYerPbX5N3eV8fgHBwdcLm/ufZEvXWBuNsZbA/28+9kB6prbZTc2IcSIJ0k92Bx4G6ZfBN0Ge93yt83UNrfT1uHikdUHABg9RINBpo+KZ0J6LJnxvd8gzB1jdlNK8mqyv/WMydyyfCLVjW28vqOEcKdiWpZpeh/MYLXDlY2eneRKaluIiwzzjJR1dze4l4R0q5WkLoQQktSD0rQLfJ66ui32UtnYRlJM+DHz0QfK7HqUx32X9j7afvmUDCLDHJ4NG9xSYyPocGle+vgoSyem8fJXTiE9PpKS2pYBlUVrzem/WM1JP3mT9k4XpXUtZHptoZho3VTUt/iO+pekLoQQktSDT2w6jFnkedra0cm8H7/uef6rq0yz/FBP2ZiUEXfcvceXTkxl54/PJaNbbT7ZWrGtqrGNs2ZkEhXuJDctdsBJ/aC1dWpbp4v39pabfZG9+uYjnA7CHMpnvmtbh4umtk5J6kKIEU+SerBwWGMWp55nRsBbNh3q6qv+xRVzuHR+NnNyEj3N3P7k7GEKiruvHeCs6WbN51GJUZ6+8P5as7/C8/h/X93F1sJaxqd2DYhTShET4aSxtdPzmnuqXeIIXUFKCCHcZPR7MNAatAtSJ8HyO30OvbevK8llJEShlOK5m5biCJIFVqZkxjMhLZZOrT016tFJ0by6rZj6lnbio/qeaA9XNvKL1/YwNyeRpJgI3t1bzlV5Odx+9lSf82Ijw3xq6p6kLjV1IcQIJ0l9mLV2dOJQ6vjTLSr2maS+8AuQMMrn0Af7yz2P3TuO9WU5WH/6z9eWeZaZBVg5K4tHVh/g2Q0F3LDsxFPuXt1WzH3/3kliTAQOpXjoMwuIDHdQ19zumSvvLSbCSWPbsTX1BEnqQogRTprfh9mCH7/BdY9/dOyB0p1Qfdg8/r+TzPco3znWlQ2tbD9ax3RrK9GxqX1baMbfor12igOYk5PEkgkpPPFBPq0dncf5SePxD/Ipqm1hV3Edv7l6HmNSYsiIj+oxoYNVU/daHte9P3OSJHUhxAgnSX0YNbd10tjW6dkUxccjS+G3c+Dopq7XOlp9TllzoBKA+y+bzaGfnu+zeUuwu+m0iRTVtjD1rv/y/MYCCqubej3XPU3tngtnsGJaxgl/d/eaemWDSeppcbIjmxBiZJOkPox2Ftd5HpfVew0c894X/LEzuh5P9HoMvL+3nMTocGaH4Cppp09J9yzj+u0XtnLqz95hj7UUbXeVjW3MzUnki6f0vCxud7ERvn3q5Q3mZki2WRVCjHSS1IeRe+U3gF3FXgmt1ST716PPo3LxHbDoRri7ElInek5p73Tx9u4yTp2c1uOo82DncCje/84Kn9fe21ve47lVja2kdFvN7nhiIsPYfrSOpz48BEBFQytxkWFBN9ZACCH8TZL6MNp+tCupl3lP8aorBuDftRP4TulZcN4vwNnVJ6215sa/bKSysY1LQ3hP8MyEKMKdXTckHx6s9Dne6dK8u7ecyoY2UmL7XsuOtFoA7v7nDsA0v6fG9f2mQAgh7EpGvw+j7UfrWDQ+hfWHqiir7+ovb685SjhQopPZuKeMqXetorXDRXxkGNt+dA7v7CnjnT3lzM5OZHmIbyXY3mm6GpZOSGV9fhUdnS7CrJkAT3902JOY+5OUqxp9t5utaGiV/nQhhMCPNXWl1BNKqTKl1PZejn9WKbVVKbVNKbVWKTW3p/NCRUt7J3tL68kbn0x8ZBjlXkl9//69AHzu7KW4NLR2uACob+3g7d2lfOnJjQB8//zpngQYqq7OGwPAVSfl0NDawfaiOrYV1vLRwUrW5XcNIHSvTNcXRTXNPs9L6lo80/2EEGIk82dN/UngIeAvvRzPB07XWlcrpVYCjwKL/VS2Ibe3tJ4Ol2Z2diLpCZE+Sb2hZB8d2sGnFs/ntPztPn3Nr2wp9jweyn3JA+W+S2fx3ZXTaHeZG5cPD1Ty1q5SKhvbqG5qY1RiFBPT41g2Oa3Pv3N2diK7S+oJcyg2HqriYHkj1y4eN1whCCFEyPBbNVBr/R7Qw9wuz/G1Wutq6+k6IKe3c0PB9qNmMNys7ETS43yTenRdPoUqk+iYGB7+7AIWjE3yHHt1W1dS78/gsWAV7nSQHBthzTuP44P95WwvqiW/opGapna+u3Iaf71hcb/2Qb/3klmcMzMTDfzu7f2kxEbw6UVjhi8IIYQIEcHatns9sCrQhRiMbUdrSYgKIyc5msyEKIrrupqMk5oOURxm7lniIsNYOatrFbnWDhf3XDiDD+8845jfGeqWTkhlzf5KWtpNrd2h4LTJ/R8zEBXu5KTxKZ6Bdtefmuuz+I0QQoxUQZfUlVIrMEn9juOcc6NSaqNSamN5ec/TpAJt0+Eq5o9NRinF1Kx4CqqazXKmLhcZbQVURo31nJub1rVhiUPBRXNHD/kubMFgTo5vbXzumCSSB9gakWT1wcdHhXHdUml6F0IICLKkrpSaA/wRuFhrXdnbeVrrR7XWeVrrvPT04BsdXtXYxt7SBhblpgAwN8c0r28rrIXGMiJopzm2q7n4zBmZ/P7aBQDkjUsh1aYjud3L3bqtmHri1eN6kxJrVtf7wsnjQ2qlPSGEGE5B02aplBoLvARcp7XeG+jyDMaGQ2bowGIrqbu3J91SWMMpMXUogITRPj9z1owspmbG27pveFJG137tj163kFMm9X1wXHeLclO56fQJfdowRgghRgq/JXWl1DPAciBNKVUI3AOEA2itfw/8AEgFHlZmW9EOrXWev8o3lDbkVxEZ5jDJ3OUi8ei7TEiNZktBDbVJBSQBkcm+i8o4HYrXbjstMAX2k6hwJ19ZMZE5OUmcPTNrUL8rLjKMO1dOH6KSCSGEPfgtqWutrznB8RuAG/xUnGG14XA188YkERnmhDUPwht3c0PWd3iwcAkVqYdIArJyRmYN89vnTAt0EYQQwraCqk/dLo5UNpqm5tYGWPsgAGe2vklFXQNrPt5Oh3aQO258YAsphBDCdoKmT90uWjs6qW5qJzMhCtY9DI3lMO+zZHzyNzYk301UUzFlKpVRCfYb3S6EECKwJKkPMfciM2MjG+C938L0C+GSh2HMYpI3PUnVhBXU5l7MaBV6O68JIYQIbpLUh1hpnUnqC488Ce3N8Kl7zIGFn4eFnycFSAlY6YQQQtiZ9KkPsbK6FhJoZPTB52D2lZA2OdBFEkIIMUJIUh9iZfWtLHbswtnRZGrnQgghhJ9IUh9ilQ2tTHUUmidZswNbGCGEECOK9KkPsdTid/l82HMQFgWRob91qhBCiNAhNfUhNrXiDfOg2zKwQgghxHCTpD7EdLu1xepnngtsQYQQQow4ktSHWHJbCTujF8qodyGEEH4nSX2IpbvKaIiWpnchhBD+J0l9CLlqCkmlltY4+26fKoQQInhJUh9Cxf++lzbtpHnqpYEuihBCiBFIkvoQ+NeWIqoLd5O5/3leCTub5YtDcht4IYQQIU6S+iBVN7bxtWc+5u0/3E67dqKX3U5EmPy3CiGE8D/JPoNU1dQGwFLHDlY7lnDBKfMDXCIhhBAjlST1QapqbAM0qdSRNSaXqHBnoIskhBBihJKkPkhVjW3E0Uyk6mDahAmBLo4QQogRTJL6IFU1tpGq6gCITs4KcGmEEEKMZJLUB6mqsY1UTFInNi2whRFCCDGiSVIfhJb2Th54fQ9pqta8EJse2AIJIYQY0SSpD8K7e8vRGm4Je8W8IEldCCFEAElSH4S9JfWkU8N8x35QDojNCHSRhBBCjGCS1Adhb1kD8xLrzZNPPw3OsMAWSAghxIgmSX0Q9pbUMy+h0TxJzAlsYYQQQox4ktQHqL3TxcGKBqZG15gXEmVnNiGEEIElSX2ADlc2Et9Zy5lHHjQvRCUGtkBCCCFGPEnq/dXWCKt/xoEjR7nM+b55bcxiUCqw5RJCCDHiyciu/tr3Oqz+XyaFv0CaU+PKnIPj+tcDXSohhBBCknq/VewDYGL7XtPOMfOuwJZHCCGEsEjze09KtsFr34eO1mOPle/xfT79Yv+USQghhDgBSeo92fEP+PAhePkWcLm6Xu9og6KPadKRABxxjoP0KQEqpBBCCOFLknpP6ksBBdtfhNX3d72+8QmoOsD9HdfQgYPEvKsCVkQhhBCiO0nqPWkohVFzYNblsPZBaLF2YSvcQHvcaJ7qPJv3T3+OxLO+HdhyCiGEEF4kqfekoQTismDxLdDRArv/A0BjwSe8W5sJQHzuQgiLDGQphRBCCB+S1HvSUAbxmZCTB5GJUPARtLcQVXuQXXocAHPHJAW4kEIIIYQvSerduTqhsRwdl2kWlBk9D4o2Q/kunLjY5RrLrSsmEe6U/zohhBDBRTJTd7UFoF38fG0DtU3tMHo+lO6AgvUAjJuxmNvPmRrgQgohhBDHkqTe3dFNALzXmMMTa/Jh8lng6sD13gM06kiSciShCyGECE5+S+pKqSeUUmVKqe29HFdKqQeVUvuVUluVUgv8VTa3+vyN8MKXANijx/DEmnxq0/MgNgNHYxl79BgmZyX4u1hCCCFEn/izpv4kcO5xjq8EJltfNwKP+KFMPva8/VcAXu48maS4GOpbOvjzugLaRp8EwC7XOCalx/u7WEIIIUSf+G3td631e0qp8cc55WLgL1prDaxTSiUppUZprYv9UkAgsXgNG1xT+Eb7rZwzJZnmdhcvbi4kubaV68KgzJFGdnK0v4ojhBBC9Esw9alnAwVezwut146hlLpRKbVRKbWxvLx8SP7xzs5OauIn837EMgCcDsWCsUkcrmxilWsRAEcST8LpkC1WhRBCBKdgSup9prV+VGudp7XOS09PH5Lf6XQ6OenrT3PS1XcCUFTTwpRM09S+1jWLaS1/wpWdNyT/lhBCCDEcgimpHwXGeD3PsV7zK/eiMjeeNoHJGXGe11uIZHSSNL0LIYQIXsG0n/q/gFuVUn8HFgO1/uxPd0uICufQT88HoNOlWZybwkf5VQDERwXTf5cQQgjhy29ZSin1DLAcSFNKFQL3AOEAWuvfA68C5wH7gSbgi/4qW2+cDsWzNy2lpqmN+1/dzbVLxgW6SEIIIUSvlBlsHrry8vL0xo0bA10MIYQQwi+UUpu01j0O8gqmPnUhhBBCDIIkdSGEEMImJKkLIYQQNiFJXQghhLAJSepCCCGETUhSF0IIIWxCkroQQghhE5LUhRBCCJuQpC6EEELYhCR1IYQQwiYkqQshhBA2EfJrvyul6oE9gS7HMEkDKgJdiGEisYUeu8YFElsos2t8x4trnNY6vacDdthLdE9vC9uHOqXURokt9Ng1NrvGBRJbKLNrfAONS5rfhRBCCJuQpC6EEELYhB2S+qOBLsAwkthCk11js2tcILGFMrvGN6C4Qn6gnBBCCCEMO9TUhRBCCIEkdSGEEMI2QiKpK6VUoMsg+k/et9Aj71lokvctNA3H+xYSSR2IA1BKOQNdkKGmlLpIKTUx0OUYJp73Sz50QkYSgFLKDmtY+FBKfUYpNdd6bLe/xyj3AxvGZmdDfr0FbVJXRoZSajXwRwCtdWdgSzV0lFJnKqU+BB4HRgW6PENJKXW+UupN4FdKqdMAtE1GZCqlLlFK3Rvocgw1pVSiUuo14L8AWuuOABdpyFjX2vvAb4D5YKu/x7OVUmuBh5RSnwX7xAZyvQ1E0CZ16w+zxfqao5RaCaCUCtoyn4h1oxKnlHoFuMv6WgeMs46HbGxuSqnxwE+A3wG7gBuVUjdYx0IyPut9c1pxPAB8Vym1LNDlGmLNQA0wSyl1JYR2y5j1nkUrpZ7DXGf3AS8AMdbxkI3NTSmVDvwY+DnwN+BqpdSd1rGQvNZArrfBCto33vqjzAE+Ab4L/ABAa+0KZLkGQxsNwF+11su11m8BrwEXW8dDNjYvE4EPtNb/BP6EaWX5qlIqWWvtCsWmQet96wT2Y2p6XwZsU3uwPkySMTeYV2NuyNBad4bi+wWe96wZ+Jt1rb0GrAWus46HdKuf9b5kAlu01i9rrd/GfE5+WymVFqrXGsj1NtjfHzRJXSn1NaXUT5VSl4MnwRUBU4A1QLFS6mal1ORAlnMgvGK7EkBr/az1ugOoBgqUUpGBLONAKaWuUEot9nqpELhcKRWptW7RWq/GfJj+ICAFHATrfXvM3dIAvKu1rtdaPwbEKqWut84LmuuoL7zi+pJSSlkfoHXA+VrrfwNblVI/UErN0lrrUEoOXrH9D4B1c+n+IM0HdiilxgSyjAOllPq8Uuos8LRkNgAnK6VSrNd2As9hJYlQI9fbEF1vWuuAfgEKuA2TuK/ANNl+AUgB8oB7rPNuBxqBV6znYYEu+yBiS/c652Rgd6DLOoDYMoB3MTdeLwMOr2N/AX7j9X8wF9P0mRnocvcjvi9g7qTPteK8E5jodXwlsANIDnRZBxnX9zCtKxnAfdY5XwI6gI3W8/BAl3sQsU3wOj4b2ADEB7qs/Ywr2bp+ioGtgNPr2F+Ap7qd+xGQG+hyD/K9k+ttgF8Bv+PRJooVwF1a6xcwSXAecBZQAixTSr0KfBGTHA9aPxr0zWe9xDYX8wa7z1kLFCqlLgpMKQdGa10G/BMTSzFwk9fhHwEXKKVmWv8HLUA9pmYRKj4F/Exr/V/gW5jRxZ91H9Rar6JrzEC8uxUmBHSPKxK4EtPHt1Ip9TrwNeBt4LD1M6EyaK57bBHAte6DWuttmL/FTwemeAOjta4GXgemA5vwbfW6FThXKXWS9bwR2AK0+bWQgyfX2xBdbwFN6l7NKBuBZQBW8HswyW8+pjl3g9Z6JuZiXK6UyraSRdA6Tmx7gZlKqWnWeQnAbqA9EOUcCK/YfgfsxHzgnK+UGgWgtT6AGdX/sFLqVMwHawYQ9GMGvGL7GLgAQGu9EfgQyFZKneJ1+h3A/cA+IMuf5eyvE8Q1ATgVeANYr7Wep7U+G3Ot5YbQtdY9tnWY9+xU6zyFGcMSFSpdCl7l/IvWugZ4GLhMKTUOQGtdh7mJvlsp9XnMoMCZhMgNtFxvQ3+9+TWpu0f3uf9QddfAsP1AvFJqtvX8PSAeKANu1lrfY51fBZyitT7qz3L3RT9iexdIxJp7b12UOZhBL0Gpt9i01u3aTMVYi7kx+br7Z7TW92MS+/XAVOB6bQYuBR3vPjqv920N4FDWlDxgO6ZFYrT1M5MwH7AvAwu01kHXj9nHuHZgbpzjgR9ore/y+hVjtdb5filsP/XjPSvCmjJqfVhmAI3BfKPSLTZtfW+xvm8AVmFmmLjPeQgzXW8hZibNlVrrWn+Wua+630zZ5XrrR1zDfr35JakrpU5RSv0ZuEspleL+Q1VKhVunrMc0OZytlArTWu/A/HHO11q3KDO9wZ1QguoOdACx7QSyMeMF3D6ttX7Sn+Xui+PE5uz2R1wB/AuYopTKUWZ9gWSt9V+Am7TWV2mtSwIQQq+UUouUUl8D31kHXh+o+zAX4NVKKafWuhBz4zXeOl4L3Kq1vkxrXeS/kh/fAOIqwHxwjtNat1nvrcP6+UY/F/+4BvieZdH1ngHcrrV+wk9F7rPjxKZ6GBj2EDBJKTVTKZWplJqkzej327TWnw+mv0c3K77HgDuUmYrnft09jSuUr7f+xDXs19uwJ3Wl1ATMHdY7mER9r1LqPDA1Pev7fkwz9UTMtAyAVuCQdbwzGO+shyI265wW/5W6b04QW6fWWiulIpUZ5d6ptX4P88e7HdMakWadG3R9e0qpbwD/wNysuNc/cILPB2o98D6mD+wB6yYtGai0zivXWu/zd9mPZxBxJdEVV6cOwqmVQ/GeWeeG2t+j1mZ6WrRSyt26d8Q6fxvmWkuwXg+6cUZW0rofs43oGmABcI9SKhN8yhxS19sg4xrW680fNfVFwC6rJno7Zt75hcrqf1VK3aeUehwzAORBYJFSahNQhemrDWYjObYfY+agu5/fjBks9wdgTjBdgD3Ix/Rz3YJ1o+X9gaiU+hHwNKZ2cDfmw+V96/mf/V3YfrBrXDCyY7sHs7jMBOv5NZi52w8As7XWm/1d4H46ClxlfZbcBiwBot0HQ/i9C8649NAP4b8QMyJzifV8AuZOZqz1fAbwU+s/4VQr6ElePx8HJA11uSS2YY/tTO/nwfTVQ2xO6ysKeBX4mvW6AzPt6Wl8p9M4CMJpUHaNS2I7YWxLCOIpa17xnWQ9T7G+R1rfXwbyrMdzQuW9C5W4hjLgUcArmDuRuzHTD86xjj0AfMt67MSs6nQPkOgdcKDfNIltQLE5/V3mIYpNWd8/hZkClNbDzwfl+2bXuCS2E8YWtNfaceI7u9s58VZ8o0PlvQu1uIay+T0PeF9rvUxrfS/wW+BG69j7wGyl1GJtmpWOAqdpa4SmUsqhg7Afz4vE1ntsQdeP56V7bL8BbgafTS/ewUx9+iqYgS/WdxXE75td4wKJ7XixBfO1Bj3H9+Vu5ywCdmiti5TZB2MyBP17F1JxDSqpK6U+p5RarswSp28BT3kdrsTMyQazwtHHmF274jDzKA8rpWIgONc8l9gA+8VWhbnL9oyYtmK4DzN6tRZYYF2IQTUw065xgcRmnRdysUGf4ttpneeeDZSMWRb7i5jV/eZB8O0sF8px9XsPV6WUwkwTeRqzmMgB4H+Ar2uti5VS4dqM/B6FCRRtpjP9VpkFE57AjKb+nNa6aWjCGBoS2/BQ3nQAAAQxSURBVIiKzb3hxUTMxjNrgG9os+pYULBrXCCxhWpsMOD43ItrXYxZKe7PwNVa663+Ln9vbBNXf9rqsfp0MJus/NX9GmZlsZe6nfMKcKb1OMP6HkYQDoCQ2EZkbO5BLhnAikDHMVLikthCN7ZBxpdmfb8GuCLQcdg5rj7V1JWZM3kv4FRmHfYErLXXtdku7utAkVLqdK31u0qpCKAc2KuU+glmHfDl2qxhXN+Xf9NfJLYRHdsKbdawLwtQGMewa1wgsRGiscGQxXea1vqZQMXQEzvGdcI+daXU6Zh51smYJU/vxaxTvkJZgzi06Qf6IWYNYjBTM76A6YuIx9zVVA9x2QdNYhvxsVX5teAnYNe4QGIL1dhgSOMLqqVr7RpXX5ollgHXeT1/GLNIwheATdZrDkxfxHOYdcwXYbYEnBfopgiJTWILldjsGpfEFrqx2Tk+28bVh8BjMEvcufsTPgvcbz3+BPiq9TgP+HugA+rnmyqxSWxB82XXuCS20I3NzvHZNa4TNr9rrZu01q26a47kWZg+BTB7nE9XSv0beAbTlHHMjjXBSmKT2IKJXeMCiS1UYwP7xmfXuPo8pc0aUKAxO+f8y3q5HvgeMAvI19aWqNq6vQkVEpvEFkzsGhdIbKEaG9g3PrvF1Z/FZ1xAOGabzTnWHczdgEtr/YEOwj3O+0FiC012jc2ucYHEFsrsGp+94upPWz1mIwEX8AFwfaD7DobyS2ILzS+7xmbXuCS20P6ya3x2isu9iUCfKKVyMJt6/Epr3dqfm4dgJ7GFJrvGZte4QGILZXaNz05x9SupCyGEECJ4DeUubUIIIYQIIEnqQgghhE1IUhdCCCFsQpK6EEIIYROS1IUQHkqpTqXUJ0qpHUqpLUqpbymljvs5oZQar5T6jL/KKITonSR1IYS3Zq31PK31TMyymSuBe07wM+MBSepCBAGZ0iaE8FBKNWit47yeTwA2AGnAOOApINY6fKvWeq1Sah0wHcgH/gw8CPwUWI7ZMOP/tNZ/8FsQQoxgktSFEB7dk7r1Wg0wFbMetktr3aKUmgw8o7XOU0otB27XWl9gnX8jkKG1vk8pFQmsAa7UWuf7NRghRqA+b+gihBjxwoGHlFLzgE5gSi/nnY1ZQ/sK63kiMBlTkxdCDCNJ6kKIXlnN751AGaZvvRSYixmP09Lbj2H2on7NL4UUQnjIQDkhRI+UUunA74GHtOmnSwSKtdYuzDrZTuvUeiDe60dfA25RSoVbv2eKUioWIcSwk5q6EMJbtFLqE0xTewdmYNyvrGMPAy8qpT4H/BdotF7fCnQqpbYATwK/xYyI36yUUkA5cIm/AhBiJJOBckIIIYRNSPO7EEIIYROS1IUQQgibkKQuhBBC2IQkdSGEEMImJKkLIYQQNiFJXQghhLAJSepCCCGETUhSF0IIIWzi/wGIrP2ZtREkgQAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "z89rLDN7HR9F"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "uA-oTur5EmUz"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4. Funções para análise rápida"
      ],
      "metadata": {
        "id": "o9rEtVcu0xy4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Parâmetros da função\n",
        "\n",
        "* data_aporte: a data em que o novo aporte foi feito (considerando a premissa de que o aporte é feito no final do pregão)\n",
        "* dic_aportes: um dicionário contendo os aportes feitos, com o ticker e a quantidade comprada (em R$)\n",
        "* precos: um data frame contendo as cotações dos ativos no período analisado\n",
        "* carteira_anterior: um data frame contendo a variação da posição dos ativos dia após dia, sem os novos aportes"
      ],
      "metadata": {
        "id": "DeHXpmZvJinZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def configuraaportes(data_aporte, dic_aportes, precos, carteira_anterior):\n",
        "  \n",
        "  # Novos aportes em formato de dataframe                  \n",
        "  nova_compra_df = pd.Series(data=dic_aportes, index=list(dic_aportes.keys()))\n",
        "\n",
        "  # Preço dos ativos no dia do novo aporte\n",
        "  precos_novo_aporte = precos.loc[data_aporte]\n",
        "\n",
        "  # Quantidade de papéis comprados no novo aporte\n",
        "  qtd_acoes_nova_compra = nova_compra_df/precos_novo_aporte\n",
        "\n",
        "  # Configura novo dataframe que vai conter informações exclusivamente do novo aporte\n",
        "  novos_PL = pd.DataFrame(data= None, index = precos.index, columns= precos.columns)\n",
        "\n",
        "  # Oscilação do patrimônio dos ativos comprados no novo aporte\n",
        "  novos_PL = precos*qtd_acoes_nova_compra\n",
        "\n",
        "  novos_PL = novos_PL.fillna(0)\n",
        "\n",
        "  # Configura como zero os valores dos ativos antes do segundo aporte\n",
        "  # Ou seja: os papéis do segundo aporte na prática não existiam, portanto\n",
        "  # precisam ser configurados como zero. Lembrando que o patrimônio da carteira \n",
        "  # inicial está descrito pelo data frame \"carteira_anterior\".\n",
        "  novos_PL[novos_PL.index < data_aporte] = 0\n",
        "\n",
        "  # Carteira original + novo aporte\n",
        "  carteira_full = pd.concat([carteira_anterior, novos_PL], axis = 1)\n",
        "\n",
        "  # Somando colunas de mesmo nome, para agrupar os patrimônios antes e depois do aporte\n",
        "  carteira_full = carteira_full.groupby(lambda x:x, axis=1).sum()\n",
        "\n",
        "  # Rentabilidade antes e depois do aporte\n",
        "  antes_aporte = carteira_full[carteira_full.index<data_aporte]\n",
        "  depois_aporte = carteira_full[carteira_full.index>=data_aporte]\n",
        "\n",
        "  # Variação de patrimônio antes e depois do aporte\n",
        "  antes_aporte['PL Total'] = antes_aporte.sum(axis = 1)\n",
        "  depois_aporte['PL Total'] = depois_aporte.sum(axis = 1)\n",
        "\n",
        "  # Encontrando o dia imediatamente antes do aporte\n",
        "  dia_antes_aporte = (datetime.strptime(data_aporte, '%Y-%m-%d')- timedelta(1)).strftime('%Y-%m-%d')\n",
        "\n",
        "  # Configurando momento logo após o aporte\n",
        "  # A ideia é que a rentabilidade do dia do aporte seja calculada com relação à posição logo antes do aporte\n",
        "  # somada dos valores aportados. Perceba que isto é diferente de calcular a rentabilidade com relação à posição \n",
        "  # do dia anterior ao aporte. Isto geraria uma distorção considerável no cálculo de rentabilidade.\n",
        "  posicao_original = pd.DataFrame(antes_aporte.loc[dia_antes_aporte]).T\n",
        "\n",
        "  aportes = (pd.DataFrame(nova_compra_df,columns = [dia_antes_aporte])).T.apply(pd.to_numeric)\n",
        "  aportes.index =  pd.to_datetime(aportes.index)\n",
        "\n",
        "  # Posição logo antes do aporte\n",
        "  operations = pd.concat([posicao_original,aportes], axis = 1)\n",
        "  operations = operations.groupby(lambda x:x, axis=1).sum()\n",
        "  operations.drop(['PL Total'], axis=1, inplace=True)\n",
        "  operations['PL Total'] = operations.iloc[:].sum(axis = 1)\n",
        "\n",
        "  # Agora sim, vamos juntar a linha contendo a operação de aporte com o data frame da carteira após o aporte\n",
        "  depois_aporte = pd.concat([operations, depois_aporte], axis = 0)\n",
        "\n",
        "  # Retorno diário da carteira antes e depois do aporte\n",
        "  rentabilidade_antes_aporte = antes_aporte.pct_change()\n",
        "  rentabilidade_depois_aporte = depois_aporte.pct_change()\n",
        "\n",
        "  rentabilidade_antes_aporte = rentabilidade_antes_aporte.dropna()\n",
        "  rentabilidade_depois_aporte = rentabilidade_depois_aporte.dropna()\n",
        "\n",
        "  # Juntando tudo num data frame só\n",
        "  rentabilidade_total = pd.concat([rentabilidade_antes_aporte, rentabilidade_depois_aporte], axis = 0)\n",
        "\n",
        "  # Calculando a rentabilidade acumulada e fazendo alguns ajustes\n",
        "  cum_daily_return = (1 + rentabilidade_total).cumprod()\n",
        "  cum_daily_return['Date'] = pd.to_datetime(cum_daily_return.index)\n",
        "  cum_daily_return.index = cum_daily_return['Date']\n",
        "  cum_daily_return.drop(['Date'], axis = 1, inplace = True)\n",
        "\n",
        "  return cum_daily_return;"
      ],
      "metadata": {
        "id": "49jtxTkv0n0N"
      },
      "execution_count": 111,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "novos_aportes = {'VALE3.SA' : 1000000, 'AAPL34.SA' : 200000}"
      ],
      "metadata": {
        "id": "E_TIbHi2Jz40"
      },
      "execution_count": 114,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "PL.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "6XkGiJ5LKRHy",
        "outputId": "8ee7116d-72d6-4bb6-e1d9-163f1f8a06dc"
      },
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              AAPL34.SA   IVVB11.SA     OIBR3.SA     PETR4.SA     RADL3.SA  \\\n",
              "Date                                                                         \n",
              "2020-05-04  1100.000000  900.000000  1500.000000  2500.000000  1700.000000   \n",
              "2020-05-05  1132.653031  916.170259  1544.117605  2580.552703  1692.683606   \n",
              "2020-05-06  1175.442177  928.989346  1544.117605  2485.615938  1683.090923   \n",
              "2020-05-07  1210.000116  973.404273  1477.941198  2508.630876  1685.854897   \n",
              "2020-05-08  1221.059801  961.436188  1522.058802  2658.228053  1701.951059   \n",
              "\n",
              "               VALE3.SA     WEGE3.SA      PL Total  \n",
              "Date                                                \n",
              "2020-05-04  2300.000000  2000.000000  12000.000000  \n",
              "2020-05-05  2287.958586  1958.333240  12112.469028  \n",
              "2020-05-06  2320.942650  1949.297353  12087.495991  \n",
              "2020-05-07  2410.995130  1962.349037  12229.175526  \n",
              "2020-05-08  2557.591901  1919.678768  12542.004572  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>AAPL34.SA</th>\n",
              "      <th>IVVB11.SA</th>\n",
              "      <th>OIBR3.SA</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th>2020-05-04</th>\n",
              "      <td>1100.000000</td>\n",
              "      <td>900.000000</td>\n",
              "      <td>1500.000000</td>\n",
              "      <td>2500.000000</td>\n",
              "      <td>1700.000000</td>\n",
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              "      <td>2000.000000</td>\n",
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              "    <tr>\n",
              "      <th>2020-05-05</th>\n",
              "      <td>1132.653031</td>\n",
              "      <td>916.170259</td>\n",
              "      <td>1544.117605</td>\n",
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              "      <td>1958.333240</td>\n",
              "      <td>12112.469028</td>\n",
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              "      <th>2020-05-06</th>\n",
              "      <td>1175.442177</td>\n",
              "      <td>928.989346</td>\n",
              "      <td>1544.117605</td>\n",
              "      <td>2485.615938</td>\n",
              "      <td>1683.090923</td>\n",
              "      <td>2320.942650</td>\n",
              "      <td>1949.297353</td>\n",
              "      <td>12087.495991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-07</th>\n",
              "      <td>1210.000116</td>\n",
              "      <td>973.404273</td>\n",
              "      <td>1477.941198</td>\n",
              "      <td>2508.630876</td>\n",
              "      <td>1685.854897</td>\n",
              "      <td>2410.995130</td>\n",
              "      <td>1962.349037</td>\n",
              "      <td>12229.175526</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>1221.059801</td>\n",
              "      <td>961.436188</td>\n",
              "      <td>1522.058802</td>\n",
              "      <td>2658.228053</td>\n",
              "      <td>1701.951059</td>\n",
              "      <td>2557.591901</td>\n",
              "      <td>1919.678768</td>\n",
              "      <td>12542.004572</td>\n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PL.drop('PL Total', axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "nwDedvWvKVdL"
      },
      "execution_count": 116,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "aporte_vale_apple = configuraaportes(data_aporte, novos_aportes, precos, PL)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mXYH0vodJh8k",
        "outputId": "260c4853-45fb-480c-d260-0ee96b40b5eb"
      },
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:37: 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",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:38: 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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "comparaacao('VALE3', inicio, fim, 'VALE3')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "wFOVArnPLRU-",
        "outputId": "361f1760-4205-4b7e-c45e-7ec02e629028"
      },
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "comparaibov(inicio, fim, aporte_vale_apple, 8, 6, 'Novo aporte em Vale e Apple')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "id": "ZBc31B8yMMKt",
        "outputId": "f32317f9-1c4c-4687-da9b-d794b8ae09d8"
      },
      "execution_count": 128,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PL['PL Total'] = PL.sum(axis = 1)\n",
        "comparaibov(inicio, fim, PL, 8, 6, 'Carteira com apenas um aporte')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "id": "dejrtIThKuU6",
        "outputId": "b90f8941-4a45-4c7b-f006-3591a7ef41c4"
      },
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x432 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Compara algum papel ao IBOV"
      ],
      "metadata": {
        "id": "hWlN6PYrK08T"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Compara ação com o IBOV\n",
        "\n",
        "def comparaacao(papel, i, f, nome):\n",
        "  ativo = papel + '.SA'\n",
        "  data = yf.download(ativo, start = i, end = f)\n",
        "  data.rename(columns = {'Adj Close':'PL Total'}, inplace = True)\n",
        "  return comparaibov(inicio, fim, data,8,6,nome);"
      ],
      "metadata": {
        "id": "IRJusAbSLMvM"
      },
      "execution_count": 121,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "lS0Bax_SLU0M"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}