20220517_Stock_Screener_Python_Twitter.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Trading-com-Dados/tutoriais_publicos/blob/main/20220517_Stock_Screener_Python_Twitter.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "<img src=\"https://tradingcomdados.com/images/logotipo/logotipo-trading-com-dados.svg\" width=\"300\" align=\"left\"/>"
      ],
      "metadata": {
        "id": "8zYfFn__TyAH"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xEGXWNa-_rcq"
      },
      "source": [
        "# **Stock Screener com Python - modelo simplificado Twitter**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5LYsJ_x8_waa"
      },
      "source": [
        "### **1. Bibliotecas utilizadas**"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para um Screening em tempo real intraday, a melhor biblioteca seria MetaTrader5 (integra o código com o software MetaTrader 5 - MT5).<p>\n",
        "Como a maioria do público talvez não tenha acesso ao MT5, vamos fazer um modelo de Screening usando o Yahoo Finance, mas que tem um delay de alguns minutos e, nesse caso, não indicado para screening intraday. "
      ],
      "metadata": {
        "id": "HKQ2l8HCUoLX"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wRVARobC6jIH",
        "outputId": "f1dcc4f3-7ec6-4c8a-c3d3-4603e1544fd4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.70)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.6)\n",
            "Requirement already satisfied: lxml>=4.5.1 in /usr/local/lib/python3.7/dist-packages (from yfinance) (4.8.0)\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: requests>=2.26 in /usr/local/lib/python3.7/dist-packages (from yfinance) (2.27.1)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2022.1)\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: 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",
            "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: ta in /usr/local/lib/python3.7/dist-packages (0.10.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from ta) (1.21.6)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from ta) (1.3.5)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (2022.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->ta) (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->ta) (1.15.0)\n"
          ]
        }
      ],
      "source": [
        "!pip install yfinance\n",
        "!pip install ta"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "id": "RddjS8RF6ltL"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from datetime import datetime, timedelta\n",
        "import pytz\n",
        "import plotly.graph_objects as go\n",
        "from plotly.subplots import make_subplots\n",
        "import yfinance as yf\n",
        "import ta as ta"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LzlBKluaAKi7"
      },
      "source": [
        "### **2. Organizando o dataset**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XHTnJaU6BowJ"
      },
      "source": [
        "#### 2.1. Baixar dados de cotações"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "metadata": {
        "id": "wZqbQUsc6opb"
      },
      "outputs": [],
      "source": [
        "ativos_IBOV = ['WEGE3', 'EMBR3', 'AZUL4', 'CCRO3', 'ECOR3', 'GOLL4', 'RAIL3', 'POSI3', 'BRFS3', 'JBSS3',\n",
        "               'MRFG3', 'BEEF3', 'ABEV3', 'ASAI3', 'CRFB3', 'PCAR3', 'NTCO3', 'AMER3', 'SOMA3', 'LREN3',\n",
        "               'MGLU3', 'PETZ3', 'VIIA3', 'ALPA4', 'CYRE3', 'EZTC3', 'JHSF3', 'MRVE3', 'CVCB3', 'COGN3',\n",
        "               'RENT3', 'LCAM3', 'YDUQ3', 'BRML3', 'IGTI11', 'MULT3', 'BIDI11', 'BPAN4', 'BBDC3', 'BBDC4',\n",
        "               'BBAS3', 'BPAC11', 'ITSA4', 'ITUB4', 'SANB11', 'BBSE3', 'IRBR3', 'SULA11', 'B3SA3', 'CIEL3',\n",
        "               'DXCO3', 'KLBN11', 'SUZB3', 'BRAP4', 'CMIN3', 'VALE3', 'BRKM5', 'GGBR4', 'GOAU4', 'CSNA3',\n",
        "               'USIM5', 'RRRP3', 'CSAN3', 'PETR3', 'PETR4', 'PRIO3', 'UGPA3', 'VBBR3', 'HYPE3', 'RADL3',\n",
        "               'FLRY3', 'HAPV3', 'QUAL3', 'RDOR3', 'LWSA3', 'CASH3', 'TOTS3', 'VIVT3', 'TIMS3', 'SBSP3',\n",
        "               'CMIG4', 'CPLE6', 'CPFE3', 'ELET3', 'ELET6', 'ENBR3', 'ENGI11', 'ENEV3', 'EGIE3', 'EQTL3',\n",
        "               'TAEE11']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 80,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SEHpC18e6rET",
        "outputId": "ec909a1a-f94b-4d88-ca43-bb54907088b2"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['ABEV3.SA', 'ALPA4.SA', 'AMER3.SA', 'ASAI3.SA', 'AZUL4.SA']"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ],
      "source": [
        "tickers_IBOV_yf = [ativos_IBOV + '.SA' for ativos_IBOV in ativos_IBOV]\n",
        "tickers_IBOV_yf.sort()\n",
        "tickers_IBOV_yf[0:5]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "SZV_vCb26wVz",
        "outputId": "b98ce203-d433-43da-d982-c7ea83790257"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2022-05-18'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 81
        }
      ],
      "source": [
        "data_fim = datetime.now(pytz.timezone(\"America/Sao_Paulo\"))\n",
        "data_fim = data_fim.strftime('%Y-%m-%d')\n",
        "data_fim"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data_inicio = datetime.now(pytz.timezone(\"America/Sao_Paulo\")) - timedelta(days=5)\n",
        "data_inicio = data_inicio.strftime('%Y-%m-%d')\n",
        "data_inicio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "dTDjLaL_YQ0M",
        "outputId": "04a0257c-bcb6-4a12-f9be-50a552395829"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2022-05-13'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E0bZW_6L7BUa",
        "outputId": "a420a302-bd7f-47c3-ab4b-6f65ab3d4dee"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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          ]
        }
      ],
      "source": [
        "lista_OHLC = []\n",
        "\n",
        "for i in tickers_IBOV_yf:\n",
        "  cotacoes_IBOV = yf.download([i], start=data_inicio, end=data_fim, interval = \"5m\")\n",
        "  cotacoes_IBOV['Ativo'] = i\n",
        "  lista_OHLC.append(cotacoes_IBOV)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lista_OHLC[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "IMGOz4hITREs",
        "outputId": "dc993485-d699-494d-b627-737628988a94"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Open   High    Low  Close  Adj Close  Volume  \\\n",
              "Datetime                                                                   \n",
              "2022-05-13 10:00:00-03:00  14.55  14.55  14.51  14.52      14.52       0   \n",
              "2022-05-13 10:05:00-03:00  14.52  14.56  14.51  14.53      14.53  150000   \n",
              "2022-05-13 10:10:00-03:00  14.53  14.54  14.45  14.52      14.52  136800   \n",
              "2022-05-13 10:15:00-03:00  14.51  14.54  14.48  14.49      14.49   78000   \n",
              "2022-05-13 10:20:00-03:00  14.50  14.53  14.47  14.47      14.47   70000   \n",
              "...                          ...    ...    ...    ...        ...     ...   \n",
              "2022-05-17 16:30:00-03:00  14.73  14.74  14.72  14.73      14.73  166400   \n",
              "2022-05-17 16:35:00-03:00  14.73  14.75  14.72  14.72      14.72  191000   \n",
              "2022-05-17 16:40:00-03:00  14.72  14.75  14.71  14.74      14.74  262800   \n",
              "2022-05-17 16:45:00-03:00  14.74  14.75  14.71  14.72      14.72  238200   \n",
              "2022-05-17 16:50:00-03:00  14.72  14.74  14.70  14.70      14.70  172000   \n",
              "\n",
              "                              Ativo  \n",
              "Datetime                             \n",
              "2022-05-13 10:00:00-03:00  ABEV3.SA  \n",
              "2022-05-13 10:05:00-03:00  ABEV3.SA  \n",
              "2022-05-13 10:10:00-03:00  ABEV3.SA  \n",
              "2022-05-13 10:15:00-03:00  ABEV3.SA  \n",
              "2022-05-13 10:20:00-03:00  ABEV3.SA  \n",
              "...                             ...  \n",
              "2022-05-17 16:30:00-03:00  ABEV3.SA  \n",
              "2022-05-17 16:35:00-03:00  ABEV3.SA  \n",
              "2022-05-17 16:40:00-03:00  ABEV3.SA  \n",
              "2022-05-17 16:45:00-03:00  ABEV3.SA  \n",
              "2022-05-17 16:50:00-03:00  ABEV3.SA  \n",
              "\n",
              "[248 rows x 7 columns]"
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              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
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              "      <th>Ativo</th>\n",
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              "      <th>2022-05-13 10:00:00-03:00</th>\n",
              "      <td>14.55</td>\n",
              "      <td>14.55</td>\n",
              "      <td>14.51</td>\n",
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              "      <th>2022-05-13 10:05:00-03:00</th>\n",
              "      <td>14.52</td>\n",
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              "      <td>14.51</td>\n",
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              "      <th>2022-05-13 10:10:00-03:00</th>\n",
              "      <td>14.53</td>\n",
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              "      <td>14.52</td>\n",
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              "      <th>2022-05-13 10:15:00-03:00</th>\n",
              "      <td>14.51</td>\n",
              "      <td>14.54</td>\n",
              "      <td>14.48</td>\n",
              "      <td>14.49</td>\n",
              "      <td>14.49</td>\n",
              "      <td>78000</td>\n",
              "      <td>ABEV3.SA</td>\n",
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              "      <th>2022-05-13 10:20:00-03:00</th>\n",
              "      <td>14.50</td>\n",
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              "      <td>14.47</td>\n",
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              "      <td>ABEV3.SA</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:30:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.73</td>\n",
              "      <td>14.73</td>\n",
              "      <td>166400</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:35:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>191000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:40:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.74</td>\n",
              "      <td>262800</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:45:00-03:00</th>\n",
              "      <td>14.74</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>238200</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:50:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>172000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>248 rows × 7 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2e2fd216-dd3a-490e-a209-45028968fba4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      fill: #1967D2;\n",
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              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2e2fd216-dd3a-490e-a209-45028968fba4');\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",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S9s1v48fF4MC"
      },
      "source": [
        "#### 2.2. Calcular indicadores de Análise Técnica"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "metadata": {
        "id": "JH_p8GeWIi8p"
      },
      "outputs": [],
      "source": [
        "for i in range(0,len(lista_OHLC)):\n",
        "  MM9p = ta.trend.SMAIndicator(lista_OHLC[i]['Close'], window=9)\n",
        "  MM20p = ta.trend.SMAIndicator(lista_OHLC[i]['Close'], window=20)\n",
        "  MM200p = ta.trend.SMAIndicator(lista_OHLC[i]['Close'], window=200)\n",
        "  IFR14p = ta.momentum.RSIIndicator(close=lista_OHLC[i]['Close'], window=14)\n",
        "  lista_OHLC[i]['SMA_9p'] = MM20p.sma_indicator()\n",
        "  lista_OHLC[i]['SMA_20p'] = MM20p.sma_indicator()\n",
        "  lista_OHLC[i]['SMA_200p'] = MM200p.sma_indicator()\n",
        "  lista_OHLC[i]['IFR14p'] = IFR14p.rsi()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lista_OHLC[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "KRBRzcA8D9uL",
        "outputId": "40d8cf19-ca85-4226-e38b-05320cfcf185"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Open   High    Low  Close  Adj Close  Volume  \\\n",
              "Datetime                                                                   \n",
              "2022-05-13 10:00:00-03:00  14.55  14.55  14.51  14.52      14.52       0   \n",
              "2022-05-13 10:05:00-03:00  14.52  14.56  14.51  14.53      14.53  150000   \n",
              "2022-05-13 10:10:00-03:00  14.53  14.54  14.45  14.52      14.52  136800   \n",
              "2022-05-13 10:15:00-03:00  14.51  14.54  14.48  14.49      14.49   78000   \n",
              "2022-05-13 10:20:00-03:00  14.50  14.53  14.47  14.47      14.47   70000   \n",
              "...                          ...    ...    ...    ...        ...     ...   \n",
              "2022-05-17 16:30:00-03:00  14.73  14.74  14.72  14.73      14.73  166400   \n",
              "2022-05-17 16:35:00-03:00  14.73  14.75  14.72  14.72      14.72  191000   \n",
              "2022-05-17 16:40:00-03:00  14.72  14.75  14.71  14.74      14.74  262800   \n",
              "2022-05-17 16:45:00-03:00  14.74  14.75  14.71  14.72      14.72  238200   \n",
              "2022-05-17 16:50:00-03:00  14.72  14.74  14.70  14.70      14.70  172000   \n",
              "\n",
              "                              Ativo   SMA_9p  SMA_20p  SMA_200p     IFR14p  \n",
              "Datetime                                                                    \n",
              "2022-05-13 10:00:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:05:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:10:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:15:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:20:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "...                             ...      ...      ...       ...        ...  \n",
              "2022-05-17 16:30:00-03:00  ABEV3.SA  14.7325  14.7325  14.71025  45.358220  \n",
              "2022-05-17 16:35:00-03:00  ABEV3.SA  14.7290  14.7290  14.71100  42.994737  \n",
              "2022-05-17 16:40:00-03:00  ABEV3.SA  14.7275  14.7275  14.71190  48.747147  \n",
              "2022-05-17 16:45:00-03:00  ABEV3.SA  14.7230  14.7230  14.71280  43.968934  \n",
              "2022-05-17 16:50:00-03:00  ABEV3.SA  14.7220  14.7220  14.71340  39.770541  \n",
              "\n",
              "[248 rows x 11 columns]"
            ],
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
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              "      <th>Ativo</th>\n",
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              "      <th>SMA_20p</th>\n",
              "      <th>SMA_200p</th>\n",
              "      <th>IFR14p</th>\n",
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              "      <th>Datetime</th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2022-05-13 10:00:00-03:00</th>\n",
              "      <td>14.55</td>\n",
              "      <td>14.55</td>\n",
              "      <td>14.51</td>\n",
              "      <td>14.52</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:05:00-03:00</th>\n",
              "      <td>14.52</td>\n",
              "      <td>14.56</td>\n",
              "      <td>14.51</td>\n",
              "      <td>14.53</td>\n",
              "      <td>14.53</td>\n",
              "      <td>150000</td>\n",
              "      <td>ABEV3.SA</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <th>2022-05-13 10:10:00-03:00</th>\n",
              "      <td>14.53</td>\n",
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              "      <td>14.45</td>\n",
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              "      <th>2022-05-13 10:15:00-03:00</th>\n",
              "      <td>14.51</td>\n",
              "      <td>14.54</td>\n",
              "      <td>14.48</td>\n",
              "      <td>14.49</td>\n",
              "      <td>14.49</td>\n",
              "      <td>78000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:20:00-03:00</th>\n",
              "      <td>14.50</td>\n",
              "      <td>14.53</td>\n",
              "      <td>14.47</td>\n",
              "      <td>14.47</td>\n",
              "      <td>14.47</td>\n",
              "      <td>70000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-17 16:30:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.73</td>\n",
              "      <td>14.73</td>\n",
              "      <td>166400</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7325</td>\n",
              "      <td>14.7325</td>\n",
              "      <td>14.71025</td>\n",
              "      <td>45.358220</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:35:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
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              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7290</td>\n",
              "      <td>14.7290</td>\n",
              "      <td>14.71100</td>\n",
              "      <td>42.994737</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-17 16:40:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.74</td>\n",
              "      <td>262800</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7275</td>\n",
              "      <td>14.7275</td>\n",
              "      <td>14.71190</td>\n",
              "      <td>48.747147</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-17 16:45:00-03:00</th>\n",
              "      <td>14.74</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>238200</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7230</td>\n",
              "      <td>14.7230</td>\n",
              "      <td>14.71280</td>\n",
              "      <td>43.968934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:50:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>172000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7220</td>\n",
              "      <td>14.7220</td>\n",
              "      <td>14.71340</td>\n",
              "      <td>39.770541</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "<p>248 rows × 11 columns</p>\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b2d6909b-83f3-4296-b208-e19cbd13a492 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-b2d6909b-83f3-4296-b208-e19cbd13a492');\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",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lgj4sba5OuCJ"
      },
      "source": [
        "## 2.3. Visualização gráficos candlesticks e indicadores"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M-25wYqlQB1C",
        "outputId": "7888acdb-3430-4b1e-ed7c-545000ab0db1"
      },
      "outputs": [
        {
          "output_type": "execute_result",
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          "metadata": {},
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      ],
      "source": [
        "list(enumerate(tickers_IBOV_yf))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "metadata": {
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          "height": 1000
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        "id": "MoPS6eCEO4NR",
        "outputId": "fa08a3b9-99a7-4668-c616-586910a3980c"
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      "outputs": [
        {
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              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Como exemplo, vamos produzir os gráficos de candlestick (com suas MMs), OBV e IFR do ticker 'MGLU3.SA' (número 59 na lista)\n",
        "\n",
        "df_figure = lista_OHLC[0]\n",
        "\n",
        "fig = make_subplots(rows=2, cols=1)\n",
        "\n",
        "fig.add_trace(go.Candlestick(name='ABEV3', x=df_figure.index, open=df_figure['Open'], high = df_figure['High'], low=df_figure['Low'], close=df_figure['Close']), row=1,col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_9p', x=df_figure.index, y=df_figure['SMA_9p'],marker_color='red'), row=1, col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_20p', x=df_figure.index, y=df_figure['SMA_20p'],marker_color='blue'), row=1, col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_200p', x=df_figure.index, y=df_figure['SMA_200p'],marker_color='black'), row=1, col=1)\n",
        "\n",
        "fig.add_trace(go.Scatter(name='IFR14p', x=df_figure.index, y=df_figure['IFR14p'],marker_color='orange'), row=2, col=1)\n",
        "\n",
        "fig.update_xaxes(title_text=\"<b> Data\",rangebreaks=[dict(bounds=[\"sat\", \"mon\"]),dict(bounds=[17, 10], pattern=\"hour\")])\n",
        "\n",
        "fig.update_layout(xaxis_rangeslider_visible=False, title_text='Price, OBV e IFR',width=1000,height=1000)\n",
        "fig.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "l-uJwX6RS3gB"
      },
      "source": [
        "# 3. Screening dos ativos listados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jzHH_D5FdVkx"
      },
      "source": [
        "Vamos determinar algumas regras e fazer a varredura de quantos e quais ativos se encaixam nesse momento. Estaremos buscando ativos que apresentaram:\n",
        "\n",
        "* Regra 01: Fechamento com preço acima da MM20p e MM200p;\n",
        "* Regra 02: MM9p > MM20p > MM200p;\n",
        "* Regra 03: IFR14p < 50"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lista_OHLC[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "hI82zpzqvWpu",
        "outputId": "8c62fd30-52d4-4092-bb58-bc3503f0656e"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                            Open   High    Low  Close  Adj Close  Volume  \\\n",
              "Datetime                                                                   \n",
              "2022-05-13 10:00:00-03:00  14.55  14.55  14.51  14.52      14.52       0   \n",
              "2022-05-13 10:05:00-03:00  14.52  14.56  14.51  14.53      14.53  150000   \n",
              "2022-05-13 10:10:00-03:00  14.53  14.54  14.45  14.52      14.52  136800   \n",
              "2022-05-13 10:15:00-03:00  14.51  14.54  14.48  14.49      14.49   78000   \n",
              "2022-05-13 10:20:00-03:00  14.50  14.53  14.47  14.47      14.47   70000   \n",
              "...                          ...    ...    ...    ...        ...     ...   \n",
              "2022-05-17 16:30:00-03:00  14.73  14.74  14.72  14.73      14.73  166400   \n",
              "2022-05-17 16:35:00-03:00  14.73  14.75  14.72  14.72      14.72  191000   \n",
              "2022-05-17 16:40:00-03:00  14.72  14.75  14.71  14.74      14.74  262800   \n",
              "2022-05-17 16:45:00-03:00  14.74  14.75  14.71  14.72      14.72  238200   \n",
              "2022-05-17 16:50:00-03:00  14.72  14.74  14.70  14.70      14.70  172000   \n",
              "\n",
              "                              Ativo   SMA_9p  SMA_20p  SMA_200p     IFR14p  \n",
              "Datetime                                                                    \n",
              "2022-05-13 10:00:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:05:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:10:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:15:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "2022-05-13 10:20:00-03:00  ABEV3.SA      NaN      NaN       NaN        NaN  \n",
              "...                             ...      ...      ...       ...        ...  \n",
              "2022-05-17 16:30:00-03:00  ABEV3.SA  14.7325  14.7325  14.71025  45.358220  \n",
              "2022-05-17 16:35:00-03:00  ABEV3.SA  14.7290  14.7290  14.71100  42.994737  \n",
              "2022-05-17 16:40:00-03:00  ABEV3.SA  14.7275  14.7275  14.71190  48.747147  \n",
              "2022-05-17 16:45:00-03:00  ABEV3.SA  14.7230  14.7230  14.71280  43.968934  \n",
              "2022-05-17 16:50:00-03:00  ABEV3.SA  14.7220  14.7220  14.71340  39.770541  \n",
              "\n",
              "[248 rows x 11 columns]"
            ],
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Ativo</th>\n",
              "      <th>SMA_9p</th>\n",
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              "      <th>SMA_200p</th>\n",
              "      <th>IFR14p</th>\n",
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              "    <tr>\n",
              "      <th>Datetime</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2022-05-13 10:00:00-03:00</th>\n",
              "      <td>14.55</td>\n",
              "      <td>14.55</td>\n",
              "      <td>14.51</td>\n",
              "      <td>14.52</td>\n",
              "      <td>14.52</td>\n",
              "      <td>0</td>\n",
              "      <td>ABEV3.SA</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:05:00-03:00</th>\n",
              "      <td>14.52</td>\n",
              "      <td>14.56</td>\n",
              "      <td>14.51</td>\n",
              "      <td>14.53</td>\n",
              "      <td>14.53</td>\n",
              "      <td>150000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:10:00-03:00</th>\n",
              "      <td>14.53</td>\n",
              "      <td>14.54</td>\n",
              "      <td>14.45</td>\n",
              "      <td>14.52</td>\n",
              "      <td>14.52</td>\n",
              "      <td>136800</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:15:00-03:00</th>\n",
              "      <td>14.51</td>\n",
              "      <td>14.54</td>\n",
              "      <td>14.48</td>\n",
              "      <td>14.49</td>\n",
              "      <td>14.49</td>\n",
              "      <td>78000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-13 10:20:00-03:00</th>\n",
              "      <td>14.50</td>\n",
              "      <td>14.53</td>\n",
              "      <td>14.47</td>\n",
              "      <td>14.47</td>\n",
              "      <td>14.47</td>\n",
              "      <td>70000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2022-05-17 16:30:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.73</td>\n",
              "      <td>14.73</td>\n",
              "      <td>166400</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7325</td>\n",
              "      <td>14.7325</td>\n",
              "      <td>14.71025</td>\n",
              "      <td>45.358220</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:35:00-03:00</th>\n",
              "      <td>14.73</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>191000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7290</td>\n",
              "      <td>14.7290</td>\n",
              "      <td>14.71100</td>\n",
              "      <td>42.994737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:40:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.74</td>\n",
              "      <td>262800</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7275</td>\n",
              "      <td>14.7275</td>\n",
              "      <td>14.71190</td>\n",
              "      <td>48.747147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:45:00-03:00</th>\n",
              "      <td>14.74</td>\n",
              "      <td>14.75</td>\n",
              "      <td>14.71</td>\n",
              "      <td>14.72</td>\n",
              "      <td>14.72</td>\n",
              "      <td>238200</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7230</td>\n",
              "      <td>14.7230</td>\n",
              "      <td>14.71280</td>\n",
              "      <td>43.968934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-05-17 16:50:00-03:00</th>\n",
              "      <td>14.72</td>\n",
              "      <td>14.74</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>14.70</td>\n",
              "      <td>172000</td>\n",
              "      <td>ABEV3.SA</td>\n",
              "      <td>14.7220</td>\n",
              "      <td>14.7220</td>\n",
              "      <td>14.71340</td>\n",
              "      <td>39.770541</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>248 rows × 11 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5bd69a6a-971c-4237-bd9e-4b8a86b3d7ed')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border-radius: 50%;\n",
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              "        buttonEl.style.display =\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 93
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ls_screening = []\n",
        "\n",
        "for i in range(0,len(lista_OHLC)):\n",
        "  if (lista_OHLC[i].iloc[-1]['Close'] >= lista_OHLC[i].iloc[-1]['SMA_20p']) and (lista_OHLC[i].iloc[-1]['Close'] >= lista_OHLC[i].iloc[-1]['SMA_200p']) and (lista_OHLC[i].iloc[-1]['SMA_9p'] >= lista_OHLC[i].iloc[-1]['SMA_20p']) and (lista_OHLC[i].iloc[-1]['SMA_20p'] >= lista_OHLC[i].iloc[-1]['SMA_200p']) and (lista_OHLC[i].iloc[-1]['IFR14p'] < 50):\n",
        "    ls_screening.append((tickers_IBOV_yf[i],i))"
      ],
      "metadata": {
        "id": "xMfwbCE0zI2T"
      },
      "execution_count": 94,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ls_screening"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MehyN_-yw40e",
        "outputId": "8c872397-d5ff-460a-d67c-3900b0665064"
      },
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('CPFE3.SA', 24),\n",
              " ('DXCO3.SA', 31),\n",
              " ('ECOR3.SA', 32),\n",
              " ('KLBN11.SA', 54),\n",
              " ('LCAM3.SA', 55),\n",
              " ('RAIL3.SA', 71),\n",
              " ('VIVT3.SA', 88)]"
            ]
          },
          "metadata": {},
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ls_screening = []\n",
        "\n",
        "for i in range(0,len(lista_OHLC)):\n",
        "  if (lista_OHLC[i].iloc[-1]['Close'] >= lista_OHLC[i].iloc[-1]['SMA_20p']) and (lista_OHLC[i].iloc[-1]['Close'] >= lista_OHLC[i].iloc[-1]['SMA_200p']) and (lista_OHLC[i].iloc[-1]['SMA_9p'] >= lista_OHLC[i].iloc[-1]['SMA_20p']) and (lista_OHLC[i].iloc[-1]['SMA_20p'] >= lista_OHLC[i].iloc[-1]['SMA_200p']) and (lista_OHLC[i].iloc[-1]['IFR14p'] < 50):\n",
        "    ls_screening.append((tickers_IBOV_yf[i],i))\n",
        "    print(\"O ativo indexado como\",i,\"(\"+tickers_IBOV_yf[i]+\") atende a todas as regras estabelecidas\")\n",
        "  else:\n",
        "    print(tickers_IBOV_yf[i],\"não atende\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8SnWZv3PvRmu",
        "outputId": "985afc1f-9a64-4b2b-84c2-cd3d8a91b379"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ABEV3.SA não atende\n",
            "ALPA4.SA não atende\n",
            "AMER3.SA não atende\n",
            "ASAI3.SA não atende\n",
            "AZUL4.SA não atende\n",
            "B3SA3.SA não atende\n",
            "BBAS3.SA não atende\n",
            "BBDC3.SA não atende\n",
            "BBDC4.SA não atende\n",
            "BBSE3.SA não atende\n",
            "BEEF3.SA não atende\n",
            "BIDI11.SA não atende\n",
            "BPAC11.SA não atende\n",
            "BPAN4.SA não atende\n",
            "BRAP4.SA não atende\n",
            "BRFS3.SA não atende\n",
            "BRKM5.SA não atende\n",
            "BRML3.SA não atende\n",
            "CASH3.SA não atende\n",
            "CCRO3.SA não atende\n",
            "CIEL3.SA não atende\n",
            "CMIG4.SA não atende\n",
            "CMIN3.SA não atende\n",
            "COGN3.SA não atende\n",
            "O ativo indexado como 24 (CPFE3.SA) atende a todas as regras estabelecidas\n",
            "CPLE6.SA não atende\n",
            "CRFB3.SA não atende\n",
            "CSAN3.SA não atende\n",
            "CSNA3.SA não atende\n",
            "CVCB3.SA não atende\n",
            "CYRE3.SA não atende\n",
            "O ativo indexado como 31 (DXCO3.SA) atende a todas as regras estabelecidas\n",
            "O ativo indexado como 32 (ECOR3.SA) atende a todas as regras estabelecidas\n",
            "EGIE3.SA não atende\n",
            "ELET3.SA não atende\n",
            "ELET6.SA não atende\n",
            "EMBR3.SA não atende\n",
            "ENBR3.SA não atende\n",
            "ENEV3.SA não atende\n",
            "ENGI11.SA não atende\n",
            "EQTL3.SA não atende\n",
            "EZTC3.SA não atende\n",
            "FLRY3.SA não atende\n",
            "GGBR4.SA não atende\n",
            "GOAU4.SA não atende\n",
            "GOLL4.SA não atende\n",
            "HAPV3.SA não atende\n",
            "HYPE3.SA não atende\n",
            "IGTI11.SA não atende\n",
            "IRBR3.SA não atende\n",
            "ITSA4.SA não atende\n",
            "ITUB4.SA não atende\n",
            "JBSS3.SA não atende\n",
            "JHSF3.SA não atende\n",
            "O ativo indexado como 54 (KLBN11.SA) atende a todas as regras estabelecidas\n",
            "O ativo indexado como 55 (LCAM3.SA) atende a todas as regras estabelecidas\n",
            "LREN3.SA não atende\n",
            "LWSA3.SA não atende\n",
            "MGLU3.SA não atende\n",
            "MRFG3.SA não atende\n",
            "MRVE3.SA não atende\n",
            "MULT3.SA não atende\n",
            "NTCO3.SA não atende\n",
            "PCAR3.SA não atende\n",
            "PETR3.SA não atende\n",
            "PETR4.SA não atende\n",
            "PETZ3.SA não atende\n",
            "POSI3.SA não atende\n",
            "PRIO3.SA não atende\n",
            "QUAL3.SA não atende\n",
            "RADL3.SA não atende\n",
            "O ativo indexado como 71 (RAIL3.SA) atende a todas as regras estabelecidas\n",
            "RDOR3.SA não atende\n",
            "RENT3.SA não atende\n",
            "RRRP3.SA não atende\n",
            "SANB11.SA não atende\n",
            "SBSP3.SA não atende\n",
            "SOMA3.SA não atende\n",
            "SULA11.SA não atende\n",
            "SUZB3.SA não atende\n",
            "TAEE11.SA não atende\n",
            "TIMS3.SA não atende\n",
            "TOTS3.SA não atende\n",
            "UGPA3.SA não atende\n",
            "USIM5.SA não atende\n",
            "VALE3.SA não atende\n",
            "VBBR3.SA não atende\n",
            "VIIA3.SA não atende\n",
            "O ativo indexado como 88 (VIVT3.SA) atende a todas as regras estabelecidas\n",
            "WEGE3.SA não atende\n",
            "YDUQ3.SA não atende\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "i4-0TaczfwJo",
        "outputId": "b9a34f5f-3ca1-4cdb-c963-1d2791de68f5"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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      ],
      "source": [
        "# Checagem gráfica de um ativo que atende a todas as regras do Screening de Compra\n",
        "# Cheque todas as regras nos gráficos e veja que realmente funcionou\n",
        "\n",
        "df_figure = lista_OHLC[88]\n",
        "\n",
        "fig = make_subplots(rows=2, cols=1)\n",
        "\n",
        "fig.add_trace(go.Candlestick(name='VIVT3', x=df_figure.index, open=df_figure['Open'], high = df_figure['High'], low=df_figure['Low'], close=df_figure['Close']), row=1,col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_9p', x=df_figure.index, y=df_figure['SMA_9p'],marker_color='red'), row=1, col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_20p', x=df_figure.index, y=df_figure['SMA_20p'],marker_color='blue'), row=1, col=1)\n",
        "fig.add_trace(go.Scatter(name='SMA_200p', x=df_figure.index, y=df_figure['SMA_200p'],marker_color='black'), row=1, col=1)\n",
        "\n",
        "fig.add_trace(go.Scatter(name='IFR14p', x=df_figure.index, y=df_figure['IFR14p'],marker_color='orange'), row=2, col=1)\n",
        "\n",
        "fig.update_xaxes(title_text=\"<b> Data\",rangebreaks=[dict(bounds=[\"sat\", \"mon\"]),dict(bounds=[17, 10], pattern=\"hour\")])\n",
        "\n",
        "fig.update_layout(xaxis_rangeslider_visible=False, title_text='Price, OBV e IFR',width=1000,height=1000)\n",
        "fig.show()"
      ]
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