Live 08 - Aplicações da Física Clássica no Mercado Financeiro.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aplicações da Física Clássica no Mercado Financeiro\n",
    "\n",
    " \n",
    "\n",
    "#### Etapas\n",
    "\n",
    "- Passo 1 - Carregar as bibliotecas\n",
    "\n",
    "- Passo 2 - Carregar a base de dados\n",
    "\n",
    "- Passo 3 - Tratamento dos dados\n",
    "\n",
    "- Passo 4 - Construçao dos alvos\n",
    "\n",
    "- Passo 5 - Construçao das Variaveis\n",
    "\n",
    "- Passo 6 - Treinamento do Modelo\n",
    "\n",
    "- Passo 7 - Avaliaçao dos Resultados\n",
    "\n",
    "- Passo 8 - Avaliaçao dos Modelos\n",
    "\n",
    "________________________________________________________\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 1 - Carregar as bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Carregando as bibliotecas\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.model_selection import train_test_split\n",
    "import statsmodels.api as sm\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import classification_report\n",
    "import sklearn.metrics as metrics\n",
    "from math import sqrt\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 2 - Carregar a base de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2627"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Carregando a base de dados e fazendo os checks iniciais\n",
    "\n",
    "# Muda o diretorio de trabalho\n",
    "import os\n",
    "os.chdir(\"C:\\\\Users\\\\engle\\\\OM Na Pratica\\\\Finanças Quantitativas\\\\Bases de Dados\")\n",
    "\n",
    "df1 = pd.read_csv(\"EURUSD_Daily_Bid_2009.09.30_2019.10.24.csv\", sep = \";\")\n",
    "\n",
    "df1.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 3 - Tratamento dos dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df1.rename(columns = {\"Time (CAT)\": \"Date\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ajustando a data - precisamos transforma-la nos indices do data frame\n",
    "\n",
    "df1[\"Data\"] = pd.to_datetime(df1[\"Date\"]).dt.normalize()\n",
    "\n",
    "df1 = df1.set_index(\"Data\")\n",
    "\n",
    "df1.drop([\"Date\"], axis=1, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2009-09-30</td>\n",
       "      <td>1.46404</td>\n",
       "      <td>1.46668</td>\n",
       "      <td>1.45154</td>\n",
       "      <td>1.45415</td>\n",
       "      <td>80746.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>1.45436</td>\n",
       "      <td>1.46467</td>\n",
       "      <td>1.44792</td>\n",
       "      <td>1.45743</td>\n",
       "      <td>80633.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-04</td>\n",
       "      <td>1.45773</td>\n",
       "      <td>1.46685</td>\n",
       "      <td>1.45772</td>\n",
       "      <td>1.46480</td>\n",
       "      <td>81029.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-05</td>\n",
       "      <td>1.46457</td>\n",
       "      <td>1.47612</td>\n",
       "      <td>1.46430</td>\n",
       "      <td>1.47212</td>\n",
       "      <td>81421.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-06</td>\n",
       "      <td>1.47200</td>\n",
       "      <td>1.47361</td>\n",
       "      <td>1.46480</td>\n",
       "      <td>1.46887</td>\n",
       "      <td>81847.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close  Volume \n",
       "Data                                                   \n",
       "2009-09-30  1.46404  1.46668  1.45154  1.45415  80746.3\n",
       "2009-10-01  1.45436  1.46467  1.44792  1.45743  80633.4\n",
       "2009-10-04  1.45773  1.46685  1.45772  1.46480  81029.8\n",
       "2009-10-05  1.46457  1.47612  1.46430  1.47212  81421.4\n",
       "2009-10-06  1.47200  1.47361  1.46480  1.46887  81847.6"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>2627.000000</td>\n",
       "      <td>2627.000000</td>\n",
       "      <td>2627.000000</td>\n",
       "      <td>2627.000000</td>\n",
       "      <td>2.627000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>1.239255</td>\n",
       "      <td>1.244429</td>\n",
       "      <td>1.234097</td>\n",
       "      <td>1.239194</td>\n",
       "      <td>2.251913e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>0.118138</td>\n",
       "      <td>0.118662</td>\n",
       "      <td>0.117213</td>\n",
       "      <td>0.118073</td>\n",
       "      <td>1.554760e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>1.038830</td>\n",
       "      <td>1.041780</td>\n",
       "      <td>1.034030</td>\n",
       "      <td>1.038820</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>1.127320</td>\n",
       "      <td>1.131965</td>\n",
       "      <td>1.122620</td>\n",
       "      <td>1.127325</td>\n",
       "      <td>1.603489e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>1.237660</td>\n",
       "      <td>1.243490</td>\n",
       "      <td>1.232310</td>\n",
       "      <td>1.237660</td>\n",
       "      <td>2.045263e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>1.338700</td>\n",
       "      <td>1.343585</td>\n",
       "      <td>1.333580</td>\n",
       "      <td>1.338740</td>\n",
       "      <td>2.504352e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>1.513320</td>\n",
       "      <td>1.514410</td>\n",
       "      <td>1.503900</td>\n",
       "      <td>1.513280</td>\n",
       "      <td>1.469805e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Open         High          Low        Close       Volume \n",
       "count  2627.000000  2627.000000  2627.000000  2627.000000  2.627000e+03\n",
       "mean      1.239255     1.244429     1.234097     1.239194  2.251913e+05\n",
       "std       0.118138     0.118662     0.117213     0.118073  1.554760e+05\n",
       "min       1.038830     1.041780     1.034030     1.038820  0.000000e+00\n",
       "25%       1.127320     1.131965     1.122620     1.127325  1.603489e+05\n",
       "50%       1.237660     1.243490     1.232310     1.237660  2.045263e+05\n",
       "75%       1.338700     1.343585     1.333580     1.338740  2.504352e+05\n",
       "max       1.513320     1.514410     1.503900     1.513280  1.469805e+06"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 4 - Construçao dos alvos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Construcao dos alvos\n",
    "\n",
    "periodos = 1\n",
    "\n",
    "# Alvo 1 - Retorno\n",
    "df1[\"Retorno\"] = df1[\"Close\"].pct_change(periodos)\n",
    "df1[\"Alvo1\"] = df1[\"Retorno\"].shift(-periodos)\n",
    "\n",
    "# Variaçao em Pips do alvo\n",
    "df1[\"Pips\"] = (df1[\"Close\"] - df1[\"Close\"].shift(periodos))*10000\n",
    "df1[\"Pips\"] = df1[\"Pips\"].shift(-periodos)\n",
    "\n",
    "# Criacao do alvo\n",
    "df1[\"Alvo_Bin\"] = np.where(df1['Alvo1'] > 0 , 1, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Retorno</th>\n",
       "      <th>Alvo1</th>\n",
       "      <th>Pips</th>\n",
       "      <th>Alvo_Bin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2009-09-30</td>\n",
       "      <td>1.46404</td>\n",
       "      <td>1.46668</td>\n",
       "      <td>1.45154</td>\n",
       "      <td>1.45415</td>\n",
       "      <td>80746.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.002256</td>\n",
       "      <td>32.8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>1.45436</td>\n",
       "      <td>1.46467</td>\n",
       "      <td>1.44792</td>\n",
       "      <td>1.45743</td>\n",
       "      <td>80633.4</td>\n",
       "      <td>0.002256</td>\n",
       "      <td>0.005057</td>\n",
       "      <td>73.7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-04</td>\n",
       "      <td>1.45773</td>\n",
       "      <td>1.46685</td>\n",
       "      <td>1.45772</td>\n",
       "      <td>1.46480</td>\n",
       "      <td>81029.8</td>\n",
       "      <td>0.005057</td>\n",
       "      <td>0.004997</td>\n",
       "      <td>73.2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-05</td>\n",
       "      <td>1.46457</td>\n",
       "      <td>1.47612</td>\n",
       "      <td>1.46430</td>\n",
       "      <td>1.47212</td>\n",
       "      <td>81421.4</td>\n",
       "      <td>0.004997</td>\n",
       "      <td>-0.002208</td>\n",
       "      <td>-32.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-06</td>\n",
       "      <td>1.47200</td>\n",
       "      <td>1.47361</td>\n",
       "      <td>1.46480</td>\n",
       "      <td>1.46887</td>\n",
       "      <td>81847.6</td>\n",
       "      <td>-0.002208</td>\n",
       "      <td>0.007046</td>\n",
       "      <td>103.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-07</td>\n",
       "      <td>1.46893</td>\n",
       "      <td>1.48160</td>\n",
       "      <td>1.46794</td>\n",
       "      <td>1.47922</td>\n",
       "      <td>80459.8</td>\n",
       "      <td>0.007046</td>\n",
       "      <td>-0.004273</td>\n",
       "      <td>-63.2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-08</td>\n",
       "      <td>1.47923</td>\n",
       "      <td>1.47973</td>\n",
       "      <td>1.46721</td>\n",
       "      <td>1.47290</td>\n",
       "      <td>81972.7</td>\n",
       "      <td>-0.004273</td>\n",
       "      <td>0.002845</td>\n",
       "      <td>41.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-11</td>\n",
       "      <td>1.47240</td>\n",
       "      <td>1.48127</td>\n",
       "      <td>1.46751</td>\n",
       "      <td>1.47709</td>\n",
       "      <td>80571.1</td>\n",
       "      <td>0.002845</td>\n",
       "      <td>0.005443</td>\n",
       "      <td>80.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-12</td>\n",
       "      <td>1.47711</td>\n",
       "      <td>1.48756</td>\n",
       "      <td>1.47575</td>\n",
       "      <td>1.48513</td>\n",
       "      <td>82395.8</td>\n",
       "      <td>0.005443</td>\n",
       "      <td>0.005084</td>\n",
       "      <td>75.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-13</td>\n",
       "      <td>1.48517</td>\n",
       "      <td>1.49443</td>\n",
       "      <td>1.48361</td>\n",
       "      <td>1.49268</td>\n",
       "      <td>81248.0</td>\n",
       "      <td>0.005084</td>\n",
       "      <td>0.001353</td>\n",
       "      <td>20.2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close  Volume    Retorno     Alvo1  \\\n",
       "Data                                                                          \n",
       "2009-09-30  1.46404  1.46668  1.45154  1.45415  80746.3       NaN  0.002256   \n",
       "2009-10-01  1.45436  1.46467  1.44792  1.45743  80633.4  0.002256  0.005057   \n",
       "2009-10-04  1.45773  1.46685  1.45772  1.46480  81029.8  0.005057  0.004997   \n",
       "2009-10-05  1.46457  1.47612  1.46430  1.47212  81421.4  0.004997 -0.002208   \n",
       "2009-10-06  1.47200  1.47361  1.46480  1.46887  81847.6 -0.002208  0.007046   \n",
       "2009-10-07  1.46893  1.48160  1.46794  1.47922  80459.8  0.007046 -0.004273   \n",
       "2009-10-08  1.47923  1.47973  1.46721  1.47290  81972.7 -0.004273  0.002845   \n",
       "2009-10-11  1.47240  1.48127  1.46751  1.47709  80571.1  0.002845  0.005443   \n",
       "2009-10-12  1.47711  1.48756  1.47575  1.48513  82395.8  0.005443  0.005084   \n",
       "2009-10-13  1.48517  1.49443  1.48361  1.49268  81248.0  0.005084  0.001353   \n",
       "\n",
       "             Pips  Alvo_Bin  \n",
       "Data                         \n",
       "2009-09-30   32.8         1  \n",
       "2009-10-01   73.7         1  \n",
       "2009-10-04   73.2         1  \n",
       "2009-10-05  -32.5         0  \n",
       "2009-10-06  103.5         1  \n",
       "2009-10-07  -63.2         0  \n",
       "2009-10-08   41.9         1  \n",
       "2009-10-11   80.4         1  \n",
       "2009-10-12   75.5         1  \n",
       "2009-10-13   20.2         1  "
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Retorno</th>\n",
       "      <th>Alvo1</th>\n",
       "      <th>Pips</th>\n",
       "      <th>Alvo_Bin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2019-10-13</td>\n",
       "      <td>1.10316</td>\n",
       "      <td>1.10426</td>\n",
       "      <td>1.10128</td>\n",
       "      <td>1.10248</td>\n",
       "      <td>154882.9700</td>\n",
       "      <td>-0.000734</td>\n",
       "      <td>0.000653</td>\n",
       "      <td>7.2</td>\n",
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       "    <tr>\n",
       "      <td>2019-10-14</td>\n",
       "      <td>1.10250</td>\n",
       "      <td>1.10459</td>\n",
       "      <td>1.09912</td>\n",
       "      <td>1.10320</td>\n",
       "      <td>225723.7900</td>\n",
       "      <td>0.000653</td>\n",
       "      <td>0.003535</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-15</td>\n",
       "      <td>1.10319</td>\n",
       "      <td>1.10855</td>\n",
       "      <td>1.10223</td>\n",
       "      <td>1.10710</td>\n",
       "      <td>233180.1260</td>\n",
       "      <td>0.003535</td>\n",
       "      <td>0.004733</td>\n",
       "      <td>52.4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-16</td>\n",
       "      <td>1.10710</td>\n",
       "      <td>1.11398</td>\n",
       "      <td>1.10650</td>\n",
       "      <td>1.11234</td>\n",
       "      <td>222120.3900</td>\n",
       "      <td>0.004733</td>\n",
       "      <td>0.004216</td>\n",
       "      <td>46.9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-17</td>\n",
       "      <td>1.11236</td>\n",
       "      <td>1.11719</td>\n",
       "      <td>1.11145</td>\n",
       "      <td>1.11703</td>\n",
       "      <td>146440.9600</td>\n",
       "      <td>0.004216</td>\n",
       "      <td>-0.001934</td>\n",
       "      <td>-21.6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-20</td>\n",
       "      <td>1.11607</td>\n",
       "      <td>1.11793</td>\n",
       "      <td>1.11386</td>\n",
       "      <td>1.11487</td>\n",
       "      <td>127017.5650</td>\n",
       "      <td>-0.001934</td>\n",
       "      <td>-0.002189</td>\n",
       "      <td>-24.4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-21</td>\n",
       "      <td>1.11487</td>\n",
       "      <td>1.11568</td>\n",
       "      <td>1.11176</td>\n",
       "      <td>1.11243</td>\n",
       "      <td>124844.3600</td>\n",
       "      <td>-0.002189</td>\n",
       "      <td>0.000485</td>\n",
       "      <td>5.4</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>2019-10-22</td>\n",
       "      <td>1.11242</td>\n",
       "      <td>1.11405</td>\n",
       "      <td>1.11061</td>\n",
       "      <td>1.11297</td>\n",
       "      <td>114032.9300</td>\n",
       "      <td>0.000485</td>\n",
       "      <td>-0.002336</td>\n",
       "      <td>-26.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-23</td>\n",
       "      <td>1.11296</td>\n",
       "      <td>1.11627</td>\n",
       "      <td>1.10930</td>\n",
       "      <td>1.11037</td>\n",
       "      <td>147677.3094</td>\n",
       "      <td>-0.002336</td>\n",
       "      <td>-0.002224</td>\n",
       "      <td>-24.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2019-10-24</td>\n",
       "      <td>1.11036</td>\n",
       "      <td>1.11229</td>\n",
       "      <td>1.10729</td>\n",
       "      <td>1.10790</td>\n",
       "      <td>104934.8200</td>\n",
       "      <td>-0.002224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close      Volume    Retorno  \\\n",
       "Data                                                                    \n",
       "2019-10-13  1.10316  1.10426  1.10128  1.10248  154882.9700 -0.000734   \n",
       "2019-10-14  1.10250  1.10459  1.09912  1.10320  225723.7900  0.000653   \n",
       "2019-10-15  1.10319  1.10855  1.10223  1.10710  233180.1260  0.003535   \n",
       "2019-10-16  1.10710  1.11398  1.10650  1.11234  222120.3900  0.004733   \n",
       "2019-10-17  1.11236  1.11719  1.11145  1.11703  146440.9600  0.004216   \n",
       "2019-10-20  1.11607  1.11793  1.11386  1.11487  127017.5650 -0.001934   \n",
       "2019-10-21  1.11487  1.11568  1.11176  1.11243  124844.3600 -0.002189   \n",
       "2019-10-22  1.11242  1.11405  1.11061  1.11297  114032.9300  0.000485   \n",
       "2019-10-23  1.11296  1.11627  1.10930  1.11037  147677.3094 -0.002336   \n",
       "2019-10-24  1.11036  1.11229  1.10729  1.10790  104934.8200 -0.002224   \n",
       "\n",
       "               Alvo1  Pips  Alvo_Bin  \n",
       "Data                                  \n",
       "2019-10-13  0.000653   7.2         1  \n",
       "2019-10-14  0.003535  39.0         1  \n",
       "2019-10-15  0.004733  52.4         1  \n",
       "2019-10-16  0.004216  46.9         1  \n",
       "2019-10-17 -0.001934 -21.6         0  \n",
       "2019-10-20 -0.002189 -24.4         0  \n",
       "2019-10-21  0.000485   5.4         1  \n",
       "2019-10-22 -0.002336 -26.0         0  \n",
       "2019-10-23 -0.002224 -24.7         0  \n",
       "2019-10-24       NaN   NaN         0  "
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    50.171298\n",
       "1    49.828702\n",
       "Name: Alvo_Bin, dtype: float64"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Analisando a proporçao dos alvos categoricos\n",
    "\n",
    "df1[\"Alvo_Bin\"].value_counts(normalize=True)*100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 5 - Construçao das Variaveis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Open</th>\n",
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       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2009-10-15</td>\n",
       "      <td>1.49453</td>\n",
       "      <td>1.49660</td>\n",
       "      <td>1.48463</td>\n",
       "      <td>1.49032</td>\n",
       "      <td>81677.9</td>\n",
       "      <td>-0.002930</td>\n",
       "      <td>0.004026</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000268</td>\n",
       "      <td>0.000315</td>\n",
       "      <td>0.011795</td>\n",
       "      <td>3.713055e-06</td>\n",
       "      <td>4.249362e-10</td>\n",
       "      <td>0.002945</td>\n",
       "      <td>3.713039e-06</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>1.093480e-08</td>\n",
       "      <td>3.166043e-06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-18</td>\n",
       "      <td>1.49047</td>\n",
       "      <td>1.49656</td>\n",
       "      <td>1.48301</td>\n",
       "      <td>1.49632</td>\n",
       "      <td>81065.4</td>\n",
       "      <td>0.004026</td>\n",
       "      <td>-0.001256</td>\n",
       "      <td>-18.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000236</td>\n",
       "      <td>0.000136</td>\n",
       "      <td>0.012976</td>\n",
       "      <td>1.761263e-06</td>\n",
       "      <td>3.621168e-10</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>1.761260e-06</td>\n",
       "      <td>0.000116</td>\n",
       "      <td>3.152579e-09</td>\n",
       "      <td>3.065531e-06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-19</td>\n",
       "      <td>1.49634</td>\n",
       "      <td>1.49940</td>\n",
       "      <td>1.48806</td>\n",
       "      <td>1.49444</td>\n",
       "      <td>79114.3</td>\n",
       "      <td>-0.001256</td>\n",
       "      <td>0.004731</td>\n",
       "      <td>70.7</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.001340</td>\n",
       "      <td>-0.000286</td>\n",
       "      <td>0.006276</td>\n",
       "      <td>-1.793846e-06</td>\n",
       "      <td>5.634027e-09</td>\n",
       "      <td>0.001507</td>\n",
       "      <td>-1.793844e-06</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>-2.702472e-09</td>\n",
       "      <td>-8.409560e-06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-20</td>\n",
       "      <td>1.49449</td>\n",
       "      <td>1.50456</td>\n",
       "      <td>1.48846</td>\n",
       "      <td>1.50151</td>\n",
       "      <td>79788.7</td>\n",
       "      <td>0.004731</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>15.9</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.000071</td>\n",
       "      <td>-0.000306</td>\n",
       "      <td>0.005923</td>\n",
       "      <td>-1.811193e-06</td>\n",
       "      <td>1.475043e-11</td>\n",
       "      <td>0.000238</td>\n",
       "      <td>-1.811193e-06</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>-4.319630e-10</td>\n",
       "      <td>-4.180239e-07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-21</td>\n",
       "      <td>1.50146</td>\n",
       "      <td>1.50383</td>\n",
       "      <td>1.49413</td>\n",
       "      <td>1.50310</td>\n",
       "      <td>80394.2</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>-0.001683</td>\n",
       "      <td>-25.3</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.000059</td>\n",
       "      <td>0.000216</td>\n",
       "      <td>0.005629</td>\n",
       "      <td>1.215558e-06</td>\n",
       "      <td>9.753286e-12</td>\n",
       "      <td>0.000914</td>\n",
       "      <td>1.215557e-06</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>1.111039e-09</td>\n",
       "      <td>-3.313650e-07</td>\n",
       "      <td>0.000032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-22</td>\n",
       "      <td>1.50298</td>\n",
       "      <td>1.50590</td>\n",
       "      <td>1.49830</td>\n",
       "      <td>1.50057</td>\n",
       "      <td>79298.1</td>\n",
       "      <td>-0.001683</td>\n",
       "      <td>-0.008757</td>\n",
       "      <td>-131.4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000249</td>\n",
       "      <td>-0.000004</td>\n",
       "      <td>0.006876</td>\n",
       "      <td>-2.613010e-08</td>\n",
       "      <td>2.139073e-10</td>\n",
       "      <td>0.001712</td>\n",
       "      <td>-2.613007e-08</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>-4.473137e-11</td>\n",
       "      <td>1.715147e-06</td>\n",
       "      <td>0.000047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-25</td>\n",
       "      <td>1.49934</td>\n",
       "      <td>1.50600</td>\n",
       "      <td>1.48420</td>\n",
       "      <td>1.48743</td>\n",
       "      <td>79935.1</td>\n",
       "      <td>-0.008757</td>\n",
       "      <td>-0.004841</td>\n",
       "      <td>-72.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.002557</td>\n",
       "      <td>-0.000559</td>\n",
       "      <td>-0.005906</td>\n",
       "      <td>3.299098e-06</td>\n",
       "      <td>-1.930191e-08</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>3.299097e-06</td>\n",
       "      <td>-0.000017</td>\n",
       "      <td>1.880617e-09</td>\n",
       "      <td>1.510008e-05</td>\n",
       "      <td>0.000035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-26</td>\n",
       "      <td>1.48750</td>\n",
       "      <td>1.49260</td>\n",
       "      <td>1.47660</td>\n",
       "      <td>1.48023</td>\n",
       "      <td>79202.0</td>\n",
       "      <td>-0.004841</td>\n",
       "      <td>-0.006648</td>\n",
       "      <td>-98.4</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>0.000125</td>\n",
       "      <td>-0.009491</td>\n",
       "      <td>-1.182684e-06</td>\n",
       "      <td>-2.438353e-09</td>\n",
       "      <td>-0.000930</td>\n",
       "      <td>-1.182684e-06</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>1.099909e-09</td>\n",
       "      <td>6.803159e-06</td>\n",
       "      <td>0.000090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-27</td>\n",
       "      <td>1.48023</td>\n",
       "      <td>1.48405</td>\n",
       "      <td>1.46888</td>\n",
       "      <td>1.47039</td>\n",
       "      <td>79406.8</td>\n",
       "      <td>-0.006648</td>\n",
       "      <td>0.007937</td>\n",
       "      <td>116.7</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.002276</td>\n",
       "      <td>-0.000441</td>\n",
       "      <td>-0.020869</td>\n",
       "      <td>9.203796e-06</td>\n",
       "      <td>-5.403843e-08</td>\n",
       "      <td>-0.002844</td>\n",
       "      <td>9.203759e-06</td>\n",
       "      <td>0.000297</td>\n",
       "      <td>-2.617823e-08</td>\n",
       "      <td>4.749176e-05</td>\n",
       "      <td>0.000436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-28</td>\n",
       "      <td>1.47029</td>\n",
       "      <td>1.48582</td>\n",
       "      <td>1.46836</td>\n",
       "      <td>1.48206</td>\n",
       "      <td>80555.4</td>\n",
       "      <td>0.007937</td>\n",
       "      <td>-0.006943</td>\n",
       "      <td>-102.9</td>\n",
       "      <td>0</td>\n",
       "      <td>0.001376</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>-0.013991</td>\n",
       "      <td>-4.013885e-06</td>\n",
       "      <td>-1.323675e-08</td>\n",
       "      <td>-0.004386</td>\n",
       "      <td>-4.013846e-06</td>\n",
       "      <td>0.000307</td>\n",
       "      <td>1.760316e-08</td>\n",
       "      <td>-1.924579e-05</td>\n",
       "      <td>0.000196</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close  Volume    Retorno     Alvo1  \\\n",
       "Data                                                                          \n",
       "2009-10-15  1.49453  1.49660  1.48463  1.49032  81677.9 -0.002930  0.004026   \n",
       "2009-10-18  1.49047  1.49656  1.48301  1.49632  81065.4  0.004026 -0.001256   \n",
       "2009-10-19  1.49634  1.49940  1.48806  1.49444  79114.3 -0.001256  0.004731   \n",
       "2009-10-20  1.49449  1.50456  1.48846  1.50151  79788.7  0.004731  0.001059   \n",
       "2009-10-21  1.50146  1.50383  1.49413  1.50310  80394.2  0.001059 -0.001683   \n",
       "2009-10-22  1.50298  1.50590  1.49830  1.50057  79298.1 -0.001683 -0.008757   \n",
       "2009-10-25  1.49934  1.50600  1.48420  1.48743  79935.1 -0.008757 -0.004841   \n",
       "2009-10-26  1.48750  1.49260  1.47660  1.48023  79202.0 -0.004841 -0.006648   \n",
       "2009-10-27  1.48023  1.48405  1.46888  1.47039  79406.8 -0.006648  0.007937   \n",
       "2009-10-28  1.47029  1.48582  1.46836  1.48206  80555.4  0.007937 -0.006943   \n",
       "\n",
       "             Pips  Alvo_Bin         v         a         m             f  \\\n",
       "Data                                                                      \n",
       "2009-10-15   60.0         1  0.000268  0.000315  0.011795  3.713055e-06   \n",
       "2009-10-18  -18.8         0  0.000236  0.000136  0.012976  1.761263e-06   \n",
       "2009-10-19   70.7         1 -0.001340 -0.000286  0.006276 -1.793846e-06   \n",
       "2009-10-20   15.9         1 -0.000071 -0.000306  0.005923 -1.811193e-06   \n",
       "2009-10-21  -25.3         0 -0.000059  0.000216  0.005629  1.215558e-06   \n",
       "2009-10-22 -131.4         0  0.000249 -0.000004  0.006876 -2.613010e-08   \n",
       "2009-10-25  -72.0         0 -0.002557 -0.000559 -0.005906  3.299098e-06   \n",
       "2009-10-26  -98.4         0 -0.000717  0.000125 -0.009491 -1.182684e-06   \n",
       "2009-10-27  116.7         1 -0.002276 -0.000441 -0.020869  9.203796e-06   \n",
       "2009-10-28 -102.9         0  0.001376  0.000287 -0.013991 -4.013885e-06   \n",
       "\n",
       "                       T       cat             w         k           tau  \\\n",
       "Data                                                                       \n",
       "2009-10-15  4.249362e-10  0.002945  3.713039e-06  0.000174  1.093480e-08   \n",
       "2009-10-18  3.621168e-10  0.001790  1.761260e-06  0.000116  3.152579e-09   \n",
       "2009-10-19  5.634027e-09  0.001507 -1.793844e-06  0.000047 -2.702472e-09   \n",
       "2009-10-20  1.475043e-11  0.000238 -1.811193e-06  0.000007 -4.319630e-10   \n",
       "2009-10-21  9.753286e-12  0.000914  1.215557e-06  0.000026  1.111039e-09   \n",
       "2009-10-22  2.139073e-10  0.001712 -2.613007e-08  0.000059 -4.473137e-11   \n",
       "2009-10-25 -1.930191e-08  0.000570  3.299097e-06 -0.000017  1.880617e-09   \n",
       "2009-10-26 -2.438353e-09 -0.000930 -1.182684e-06  0.000044  1.099909e-09   \n",
       "2009-10-27 -5.403843e-08 -0.002844  9.203759e-06  0.000297 -2.617823e-08   \n",
       "2009-10-28 -1.323675e-08 -0.004386 -4.013846e-06  0.000307  1.760316e-08   \n",
       "\n",
       "                       M         g  \n",
       "Data                                \n",
       "2009-10-15  3.166043e-06       NaN  \n",
       "2009-10-18  3.065531e-06       NaN  \n",
       "2009-10-19 -8.409560e-06       NaN  \n",
       "2009-10-20 -4.180239e-07       NaN  \n",
       "2009-10-21 -3.313650e-07  0.000032  \n",
       "2009-10-22  1.715147e-06  0.000047  \n",
       "2009-10-25  1.510008e-05  0.000035  \n",
       "2009-10-26  6.803159e-06  0.000090  \n",
       "2009-10-27  4.749176e-05  0.000436  \n",
       "2009-10-28 -1.924579e-05  0.000196  "
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Aplicando a fisica\n",
    "\n",
    "p = 5 \n",
    "\n",
    "# Velocidade de p dias\n",
    "df1[\"v\"] = (df1[\"Retorno\"] - df1[\"Retorno\"].shift(p))/p\n",
    "\n",
    "# Aceleraçao de p dias\n",
    "df1[\"a\"] = (df1[\"v\"] - df1[\"v\"].shift(p))/p\n",
    "\n",
    "# Força\n",
    "# Calculando a massa\n",
    "df1[\"m\"] = df1[\"Retorno\"].rolling(p).sum()\n",
    "df1[\"f\"] = df1[\"m\"]*df1[\"a\"]\n",
    "\n",
    "# Energia cinética\n",
    "df1[\"T\"] = 0.5*df1[\"m\"]*df1[\"v\"]*df1[\"v\"]\n",
    "\n",
    "\n",
    "# Trabalho \n",
    "# cateto_oposto\n",
    "cat_op = df1[\"Retorno\"].rolling(p).sum()-df1[\"Retorno\"].rolling(1).sum()\n",
    "cat_ad = p\n",
    "df1[\"cat\"] = cat_op/cat_ad\n",
    "df1 = df1.dropna(axis = 0)\n",
    "df1[\"w\"] = df1[\"f\"]*np.cos(np.arctan(df1[\"cat\"]))\n",
    "\n",
    "# Energia potencial\n",
    "df1[\"k\"] = cat_op*df1[\"m\"]\n",
    "\n",
    "# Torque\n",
    "df1[\"tau\"] = df1[\"f\"]*np.sin(np.arctan(df1[\"cat\"]))\n",
    "\n",
    "# Momentum\n",
    "df1[\"M\"] = df1[\"m\"]*df1[\"v\"]\n",
    "\n",
    "# Gravidade\n",
    "df1[\"g\"] = df1[\"m\"]*df1[\"Retorno\"].rolling(p).sum()/(df1[\"m\"]/df1[\"Retorno\"].rolling(p).sum())*(df1[\"m\"]/df1[\"Retorno\"].rolling(p).sum())\n",
    "\n",
    "df1.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(5,figsize=(20, 20))\n",
    "\n",
    "ax[0].plot(df1[\"v\"], color = \"red\")\n",
    "ax[1].plot(df1[\"T\"], color = \"green\");\n",
    "ax[2].plot(df1[\"g\"], color = \"blue\");\n",
    "ax[3].plot(df1[\"tau\"], color = \"black\");\n",
    "ax[4].plot(df1[\"k\"], color = \"red\");\n",
    "\n",
    "ax[0].set(ylabel = \"V\"\n",
    "          , title = \"Velocidade\")\n",
    "\n",
    "ax[1].set(ylabel = \"T\"\n",
    "          , title = \"Energia Cinética\")\n",
    "\n",
    "ax[2].set(xlabel = \"G\", ylabel = \"Fg\"\n",
    "          , title = \"Gravidade\")\n",
    "\n",
    "ax[3].set(xlabel = \"T\", ylabel = \"Fg\"\n",
    "          , title = \"Torque\")\n",
    "\n",
    "ax[4].set(xlabel = \"EP\", ylabel = \"Fg\"\n",
    "          , title = \"Energia Potencial\")\n",
    "\n",
    "# E este aqui é para afastar os graficos e melhorar a visualizaçao\n",
    "fig.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filtrando os valores missing\n",
    "\n",
    "df1_filtrado = df1.dropna(axis = 0) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:3: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:4: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  after removing the cwd from sys.path.\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:5: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:6: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:7: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  import sys\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:8: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:9: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if __name__ == '__main__':\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:10: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # Remove the CWD from sys.path while we load stuff.\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:11: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  # This is added back by InteractiveShellApp.init_path()\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\ipykernel_launcher.py:12: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if sys.path[0] == '':\n"
     ]
    }
   ],
   "source": [
    "corte = 5\n",
    "\n",
    "df1_filtrado[\"v\"] = pd.qcut(df1_filtrado[\"v\"], corte, labels = False)\n",
    "df1_filtrado[\"a\"] = pd.qcut(df1_filtrado[\"a\"], corte, labels = False)\n",
    "df1_filtrado[\"m\"] = pd.qcut(df1_filtrado[\"m\"], corte, labels = False)\n",
    "df1_filtrado[\"f\"] = pd.qcut(df1_filtrado[\"f\"], corte, labels = False)\n",
    "df1_filtrado[\"T\"] = pd.qcut(df1_filtrado[\"T\"], corte, labels = False)\n",
    "df1_filtrado[\"w\"] = pd.qcut(df1_filtrado[\"w\"], corte, labels = False)\n",
    "df1_filtrado[\"k\"] = pd.qcut(df1_filtrado[\"k\"], corte, labels = False)\n",
    "df1_filtrado[\"tau\"] = pd.qcut(df1_filtrado[\"tau\"], corte, labels = False)\n",
    "df1_filtrado[\"M\"] = pd.qcut(df1_filtrado[\"M\"], corte, labels = False)\n",
    "df1_filtrado[\"g\"] = pd.qcut(df1_filtrado[\"g\"], corte, labels = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Retorno</th>\n",
       "      <th>Alvo1</th>\n",
       "      <th>Pips</th>\n",
       "      <th>Alvo_Bin</th>\n",
       "      <th>v</th>\n",
       "      <th>a</th>\n",
       "      <th>m</th>\n",
       "      <th>f</th>\n",
       "      <th>T</th>\n",
       "      <th>cat</th>\n",
       "      <th>w</th>\n",
       "      <th>k</th>\n",
       "      <th>tau</th>\n",
       "      <th>M</th>\n",
       "      <th>g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2009-10-21</td>\n",
       "      <td>1.50146</td>\n",
       "      <td>1.50383</td>\n",
       "      <td>1.49413</td>\n",
       "      <td>1.50310</td>\n",
       "      <td>80394.2</td>\n",
       "      <td>0.001059</td>\n",
       "      <td>-0.001683</td>\n",
       "      <td>-25.3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000914</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-22</td>\n",
       "      <td>1.50298</td>\n",
       "      <td>1.50590</td>\n",
       "      <td>1.49830</td>\n",
       "      <td>1.50057</td>\n",
       "      <td>79298.1</td>\n",
       "      <td>-0.001683</td>\n",
       "      <td>-0.008757</td>\n",
       "      <td>-131.4</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.001712</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-25</td>\n",
       "      <td>1.49934</td>\n",
       "      <td>1.50600</td>\n",
       "      <td>1.48420</td>\n",
       "      <td>1.48743</td>\n",
       "      <td>79935.1</td>\n",
       "      <td>-0.008757</td>\n",
       "      <td>-0.004841</td>\n",
       "      <td>-72.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000570</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-26</td>\n",
       "      <td>1.48750</td>\n",
       "      <td>1.49260</td>\n",
       "      <td>1.47660</td>\n",
       "      <td>1.48023</td>\n",
       "      <td>79202.0</td>\n",
       "      <td>-0.004841</td>\n",
       "      <td>-0.006648</td>\n",
       "      <td>-98.4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.000930</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2009-10-27</td>\n",
       "      <td>1.48023</td>\n",
       "      <td>1.48405</td>\n",
       "      <td>1.46888</td>\n",
       "      <td>1.47039</td>\n",
       "      <td>79406.8</td>\n",
       "      <td>-0.006648</td>\n",
       "      <td>0.007937</td>\n",
       "      <td>116.7</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.002844</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close  Volume    Retorno     Alvo1  \\\n",
       "Data                                                                          \n",
       "2009-10-21  1.50146  1.50383  1.49413  1.50310  80394.2  0.001059 -0.001683   \n",
       "2009-10-22  1.50298  1.50590  1.49830  1.50057  79298.1 -0.001683 -0.008757   \n",
       "2009-10-25  1.49934  1.50600  1.48420  1.48743  79935.1 -0.008757 -0.004841   \n",
       "2009-10-26  1.48750  1.49260  1.47660  1.48023  79202.0 -0.004841 -0.006648   \n",
       "2009-10-27  1.48023  1.48405  1.46888  1.47039  79406.8 -0.006648  0.007937   \n",
       "\n",
       "             Pips  Alvo_Bin  v  a  m  f  T       cat  w  k  tau  M  g  \n",
       "Data                                                                   \n",
       "2009-10-21  -25.3         0  2  3  3  3  2  0.000914  3  2    3  1  1  \n",
       "2009-10-22 -131.4         0  2  2  3  2  3  0.001712  2  2    2  2  2  \n",
       "2009-10-25  -72.0         0  0  0  1  3  0  0.000570  3  0    3  4  2  \n",
       "2009-10-26  -98.4         0  1  3  1  1  1 -0.000930  1  2    3  3  3  \n",
       "2009-10-27  116.7         1  0  0  0  4  0 -0.002844  4  4    0  4  4  "
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_filtrado.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 6 - Treinamento do modelo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separando os dados entre treinamento e teste\n",
    "\n",
    "# Nossa base vai de 30-09-2009 a 24-10-2019\n",
    "\n",
    "# Vamos treinar o modelo de 2009 a 2013\n",
    "start_train = \"2009-09-30\"\n",
    "end_train = \"2013-12-31\"\n",
    "\n",
    "# Vamos testar o modelo de 2014 a 2019\n",
    "start_test = \"2014-01-01\"\n",
    "end_test = \"2019-10-24\"\n",
    "\n",
    "df1_train1 = df1_filtrado[start_train : end_train]\n",
    "\n",
    "df1_test1 = df1_filtrado[start_test : end_test]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1094, 20)\n",
      "(1517, 20)\n"
     ]
    }
   ],
   "source": [
    "print(df1_train1.shape)\n",
    "\n",
    "print(df1_test1.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Retorno</th>\n",
       "      <th>Alvo1</th>\n",
       "      <th>Pips</th>\n",
       "      <th>Alvo_Bin</th>\n",
       "      <th>v</th>\n",
       "      <th>a</th>\n",
       "      <th>m</th>\n",
       "      <th>f</th>\n",
       "      <th>T</th>\n",
       "      <th>cat</th>\n",
       "      <th>w</th>\n",
       "      <th>k</th>\n",
       "      <th>tau</th>\n",
       "      <th>M</th>\n",
       "      <th>g</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Data</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2013-12-25</td>\n",
       "      <td>1.36751</td>\n",
       "      <td>1.36809</td>\n",
       "      <td>1.36606</td>\n",
       "      <td>1.36800</td>\n",
       "      <td>3644.76</td>\n",
       "      <td>0.000314</td>\n",
       "      <td>0.000789</td>\n",
       "      <td>10.8</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-0.000109</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2013-12-26</td>\n",
       "      <td>1.36800</td>\n",
       "      <td>1.37015</td>\n",
       "      <td>1.36619</td>\n",
       "      <td>1.36908</td>\n",
       "      <td>60597.15</td>\n",
       "      <td>0.000789</td>\n",
       "      <td>0.004163</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2013-12-27</td>\n",
       "      <td>1.36905</td>\n",
       "      <td>1.38932</td>\n",
       "      <td>1.36869</td>\n",
       "      <td>1.37478</td>\n",
       "      <td>198522.37</td>\n",
       "      <td>0.004163</td>\n",
       "      <td>0.003957</td>\n",
       "      <td>54.4</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000300</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2013-12-30</td>\n",
       "      <td>1.37558</td>\n",
       "      <td>1.38189</td>\n",
       "      <td>1.37280</td>\n",
       "      <td>1.38022</td>\n",
       "      <td>145202.06</td>\n",
       "      <td>0.003957</td>\n",
       "      <td>-0.004434</td>\n",
       "      <td>-61.2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000761</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2013-12-31</td>\n",
       "      <td>1.37971</td>\n",
       "      <td>1.38123</td>\n",
       "      <td>1.37410</td>\n",
       "      <td>1.37410</td>\n",
       "      <td>113992.87</td>\n",
       "      <td>-0.004434</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0.001845</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open     High      Low    Close    Volume    Retorno     Alvo1  \\\n",
       "Data                                                                            \n",
       "2013-12-25  1.36751  1.36809  1.36606  1.36800    3644.76  0.000314  0.000789   \n",
       "2013-12-26  1.36800  1.37015  1.36619  1.36908   60597.15  0.000789  0.004163   \n",
       "2013-12-27  1.36905  1.38932  1.36869  1.37478  198522.37  0.004163  0.003957   \n",
       "2013-12-30  1.37558  1.38189  1.37280  1.38022  145202.06  0.003957 -0.004434   \n",
       "2013-12-31  1.37971  1.38123  1.37410  1.37410  113992.87 -0.004434  0.000000   \n",
       "\n",
       "            Pips  Alvo_Bin  v  a  m  f  T       cat  w  k  tau  M  g  \n",
       "Data                                                                  \n",
       "2013-12-25  10.8         1  4  4  2  2  2 -0.000109  2  0    2  1  0  \n",
       "2013-12-26  57.0         1  3  2  2  2  3  0.000280  2  1    2  2  0  \n",
       "2013-12-27  54.4         1  3  2  3  2  3  0.000300  2  1    2  3  1  \n",
       "2013-12-30 -61.2         0  3  2  3  2  3  0.000761  2  2    3  3  2  \n",
       "2013-12-31   0.0         0  1  2  3  2  3  0.001845  2  2    1  1  1  "
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_train1.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['v', 'a', 'm', 'f', 'T', 'cat', 'w', 'k', 'tau', 'M', 'g'], dtype='object')"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.columns[9:df1.shape[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df1.drop([\"m\",\"cat\",\"M\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separando os dados com as variaveis em x e o alvo em y\n",
    " \n",
    "x_train1 = df1_train1.iloc[:, 9:df1.shape[1]]\n",
    "y_train1 = df1_train1['Alvo_Bin']\n",
    "\n",
    "x_test1 = df1_test1.iloc[:, 9:df1.shape[1]]\n",
    "y_test1 = df1_test1['Alvo_Bin']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',\n",
       "                       max_depth=10, max_features='auto', max_leaf_nodes=None,\n",
       "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                       min_samples_leaf=1, min_samples_split=2,\n",
       "                       min_weight_fraction_leaf=0.0, n_estimators=1500,\n",
       "                       n_jobs=5, oob_score=True, random_state=42, verbose=0,\n",
       "                       warm_start=False)"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Treinando o modelo\n",
    "\n",
    "rf1 = RandomForestClassifier(bootstrap = True,\n",
    "           criterion = 'gini', max_depth = 10, max_features = 'auto',\n",
    "           min_samples_leaf = 1, min_samples_split = 2,\n",
    "           n_estimators = 1500, n_jobs = 5, oob_score = True, random_state = 42)\n",
    "\n",
    "rf1.fit(x_train1, y_train1) # essa é a linha que treina o modelo!!!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prediçoes para o teste\n",
    "\n",
    "y_pred_test1 = rf1.predict(x_test1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 7 - Avaliaçao dos Resultados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[375 403]\n",
      " [283 456]]\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.57      0.48      0.52       778\n",
      "           1       0.53      0.62      0.57       739\n",
      "\n",
      "    accuracy                           0.55      1517\n",
      "   macro avg       0.55      0.55      0.55      1517\n",
      "weighted avg       0.55      0.55      0.55      1517\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Como availar os resultados?\n",
    "\n",
    "print(confusion_matrix(y_test1, y_pred_test1))\n",
    "print()\n",
    "print(\"--------------------------------------------------------------------------------\")\n",
    "print()\n",
    "print(classification_report(y_test1, y_pred_test1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acuracia: 54.779\n"
     ]
    }
   ],
   "source": [
    "# Acuràcia do modelo\n",
    "\n",
    "print(\"Acuracia:\", round(metrics.accuracy_score(y_test1, y_pred_test1)*100,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\pandas\\core\\indexing.py:376: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[key] = _infer_fill_value(value)\n",
      "D:\\Anaconda\\envs\\R\\lib\\site-packages\\pandas\\core\\indexing.py:494: 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: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self.obj[item] = s\n"
     ]
    }
   ],
   "source": [
    "# Calculando a performance\n",
    "\n",
    "df1_test1.loc[: , \"Previsto\"] = y_pred_test1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data\n",
       "2014-01-01    0\n",
       "2014-01-02    1\n",
       "2014-01-03    1\n",
       "2014-01-06    1\n",
       "2014-01-07    0\n",
       "             ..\n",
       "2019-10-17    1\n",
       "2019-10-20    1\n",
       "2019-10-21    1\n",
       "2019-10-22    1\n",
       "2019-10-23    1\n",
       "Name: Previsto, Length: 1517, dtype: object"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_test1[\"Previsto\"].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ajustando o retorno em pips com o resultado do modelo\n",
    "\n",
    "df1_test1.loc[: , \"Ret_Pips\"] = np.where(df1_test1.loc[: , 'Previsto'] == 1 , df1_test1.loc[: , 'Pips'], '0')\n",
    "df1_test1.loc[: , \"Ret_Pips\"] = np.where(df1_test1.loc[: , 'Previsto'] == 0 , -1*df1_test1.loc[: , 'Pips'], df1_test1.loc[: , \"Ret_Pips\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convertendo para float\n",
    "\n",
    "df1_test1.loc[: , \"Ret_Pips\"] = df1_test1[\"Ret_Pips\"].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulando um stop\n",
    "\n",
    "stop = 100\n",
    "\n",
    "df1_test1.loc[: , \"Ret_Pips\"] = np.where(df1_test1.loc[: , 'Ret_Pips'] <= -stop , -stop, df1_test1.loc[: , \"Ret_Pips\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1_test1.loc[: , \"Ret_Pips_Acumulado\"] = df1_test1[\"Ret_Pips\"].cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data\n",
       "2019-10-17    7005.7\n",
       "2019-10-20    6981.3\n",
       "2019-10-21    6986.7\n",
       "2019-10-22    6960.7\n",
       "2019-10-23    6936.0\n",
       "Name: Ret_Pips_Acumulado, dtype: float64"
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_test1.loc[: , \"Ret_Pips_Acumulado\"].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24cd2246d08>"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1_test1[\"Ret_Pips_Acumulado\"].plot(figsize=(20,15)\n",
    "                                     , linewidth = 3\n",
    "                                     , fontsize = 15)\n",
    "plt.xlabel('Periodos'\n",
    "           , fontsize = 15);\n",
    "plt.ylabel('Pips'\n",
    "           , fontsize = 15);\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Passo 8 - Avaliaçao dos modelos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Comparaçao com resultados aleatorios\n",
    "\n",
    "df1_test1.loc[: , 'Resultado_Aleatorio'] = np.random.randint(0, 2, size = len(df1_test1)).astype(float)\n",
    "\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio\"] = np.where(df1_test1.loc[: , 'Resultado_Aleatorio'] == 1 , df1_test1.loc[: , 'Pips'], '0')\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio\"] = np.where(df1_test1.loc[: , 'Resultado_Aleatorio'] == 0 , -1*df1_test1.loc[: , 'Pips'], df1_test1.loc[: , \"Resultado_Aleatorio\"])\n",
    "\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio\"] = df1_test1[\"Resultado_Aleatorio\"].astype(float).cumsum()\n",
    "\n",
    "df1_test1.loc[: , 'Resultado_Aleatorio2'] = np.random.randint(0, 2, size = len(df1_test1)).astype(float)\n",
    "\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio2\"] = np.where(df1_test1.loc[: , 'Resultado_Aleatorio2'] == 1 , df1_test1.loc[: , 'Pips'], '0')\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio2\"] = np.where(df1_test1.loc[: , 'Resultado_Aleatorio2'] == 0 , -1*df1_test1.loc[: , 'Pips'], df1_test1.loc[: , \"Resultado_Aleatorio2\"])\n",
    "\n",
    "df1_test1.loc[: , \"Resultado_Aleatorio2\"] = df1_test1[\"Resultado_Aleatorio2\"].astype(float).cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Data\n",
       "2019-10-17   -1275.9\n",
       "2019-10-20   -1300.3\n",
       "2019-10-21   -1300.3\n",
       "2019-10-22   -1300.3\n",
       "2019-10-23   -1300.3\n",
       "Name: Resultado_Aleatorio, dtype: float64"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1_test1.loc[: , 'Resultado_Aleatorio'].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24cd7b52748>"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1_test1[\"Resultado_Aleatorio\"].plot(figsize=(20,15)\n",
    "                                     , linewidth = 3\n",
    "                                     , fontsize = 15)\n",
    "df1_test1[\"Resultado_Aleatorio2\"].plot(figsize=(20,15)\n",
    "                                     , linewidth = 3\n",
    "                                     , fontsize = 15)\n",
    "df1_test1[\"Ret_Pips_Acumulado\"].plot(figsize=(20,15)\n",
    "                                     , linewidth = 3\n",
    "                                     , fontsize = 15)\n",
    "plt.xlabel('Periodos'\n",
    "           , fontsize = 15);\n",
    "plt.ylabel('Pips'\n",
    "           , fontsize = 15);\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "______________________________________________________"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}