carlleston/4-Models_comparison.ipynb

## 4-Models_comparison.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Models_comparison"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The propose of this notebook is identify what regression model is the best for our use case. We'll compare the regression models, such as Linear Regression, Ridge Regression, Sarimax and Deep Learning LSTM Model.\n",
    "\n",
    "If you arrived here, it means that you are really interested in the forecasting models, but unfortunately I will not explain it in detail, so I will leave some interesting links below that helped me a lot.\n",
    "\n",
    "https://medium.com/datadriveninvestor/warm-up-in-regression-analysis-ed330cf08a6e\n",
    "\n",
    "https://medium.com/@josemarcialportilla/using-python-and-auto-arima-to-forecast-seasonal-time-series-90877adff03c\n",
    "\n",
    "https://towardsdatascience.com/how-to-reshape-data-and-do-regression-for-time-series-using-lstm-133dad96cd00\n",
    "\n",
    "https://towardsdatascience.com/regression-an-explanation-of-regression-metrics-and-what-can-go-wrong-a39a9793d914#:~:text=Root%20Mean%20Squared%20Error%3A%20RMSE,value%20predicted%20by%20the%20model.&text=Mean%20Absolute%20Error%3A%20MAE%20is,value%20predicted%20by%20the%20model.\n",
    "\n",
    "At the request of the advanced data science capstone course, the version of each model was created with and without PCA, so to facilitate the creation of the same and not waste a lot of time with it, I used a pipeline on all scikitlearn models.\n",
    "\n",
    "\n",
    "Due to the objective of the model to fully hit the closing value of the stock, I chose to use the r² and the rmse metrics. Where the r² is the coefficient of determination and it's proportion of the variance in the dependent variable, so the closer to 1 more is the forecast get closer of the real value. The RMSE is the root mean squared error, thus it's get the difference between the real value and the predict value of whole test set.\n",
    "\n",
    "The train_test_split used is 0.8 and 0.2.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns; sns.set()\n",
    "import matplotlib.patches as mpatches\n",
    "import datetime\n",
    "import h5py\n",
    "from joblib import dump, load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vol</th>\n",
       "      <th>Var</th>\n",
       "      <th>Open_Dollar</th>\n",
       "      <th>Open_IBOVESPA</th>\n",
       "      <th>DayofWeek</th>\n",
       "      <th>Weekofyear</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Month</th>\n",
       "      <th>News_N</th>\n",
       "      <th>News_NN</th>\n",
       "      <th>News_P</th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_2</th>\n",
       "      <th>lag_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3739</th>\n",
       "      <td>2020-05-11</td>\n",
       "      <td>22.38</td>\n",
       "      <td>0.925370</td>\n",
       "      <td>0.996860</td>\n",
       "      <td>0.961333</td>\n",
       "      <td>0.839752</td>\n",
       "      <td>0.089790</td>\n",
       "      <td>3.750932</td>\n",
       "      <td>1.124428</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.858274</td>\n",
       "      <td>0.856584</td>\n",
       "      <td>0.971692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3740</th>\n",
       "      <td>2020-05-12</td>\n",
       "      <td>21.61</td>\n",
       "      <td>0.966678</td>\n",
       "      <td>0.952362</td>\n",
       "      <td>0.890030</td>\n",
       "      <td>1.061032</td>\n",
       "      <td>-1.545238</td>\n",
       "      <td>3.793713</td>\n",
       "      <td>1.058628</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.857057</td>\n",
       "      <td>0.972148</td>\n",
       "      <td>0.859766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3741</th>\n",
       "      <td>2020-05-13</td>\n",
       "      <td>21.60</td>\n",
       "      <td>0.873128</td>\n",
       "      <td>0.865772</td>\n",
       "      <td>0.842085</td>\n",
       "      <td>0.690609</td>\n",
       "      <td>-0.051237</td>\n",
       "      <td>3.872595</td>\n",
       "      <td>0.993438</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.972609</td>\n",
       "      <td>0.860234</td>\n",
       "      <td>0.986292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3742</th>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>22.55</td>\n",
       "      <td>0.820885</td>\n",
       "      <td>0.943944</td>\n",
       "      <td>0.784305</td>\n",
       "      <td>1.885962</td>\n",
       "      <td>1.909915</td>\n",
       "      <td>3.917720</td>\n",
       "      <td>0.987598</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.860706</td>\n",
       "      <td>0.986745</td>\n",
       "      <td>0.867066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3743</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>21.63</td>\n",
       "      <td>0.965464</td>\n",
       "      <td>0.965591</td>\n",
       "      <td>0.894947</td>\n",
       "      <td>0.827360</td>\n",
       "      <td>-1.827291</td>\n",
       "      <td>3.784337</td>\n",
       "      <td>1.055664</td>\n",
       "      <td>4</td>\n",
       "      <td>20</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.987204</td>\n",
       "      <td>0.867532</td>\n",
       "      <td>0.856116</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Date  Close      Open      High       Low       Vol       Var  \\\n",
       "3739  2020-05-11  22.38  0.925370  0.996860  0.961333  0.839752  0.089790   \n",
       "3740  2020-05-12  21.61  0.966678  0.952362  0.890030  1.061032 -1.545238   \n",
       "3741  2020-05-13  21.60  0.873128  0.865772  0.842085  0.690609 -0.051237   \n",
       "3742  2020-05-14  22.55  0.820885  0.943944  0.784305  1.885962  1.909915   \n",
       "3743  2020-05-15  21.63  0.965464  0.965591  0.894947  0.827360 -1.827291   \n",
       "\n",
       "      Open_Dollar  Open_IBOVESPA  DayofWeek  Weekofyear  Quarter  Month  \\\n",
       "3739     3.750932       1.124428          0          20        2      5   \n",
       "3740     3.793713       1.058628          1          20        2      5   \n",
       "3741     3.872595       0.993438          2          20        2      5   \n",
       "3742     3.917720       0.987598          3          20        2      5   \n",
       "3743     3.784337       1.055664          4          20        2      5   \n",
       "\n",
       "      News_N  News_NN  News_P     lag_1     lag_2     lag_3  \n",
       "3739       1        0       0  0.858274  0.856584  0.971692  \n",
       "3740       1        0       0  0.857057  0.972148  0.859766  \n",
       "3741       1        0       0  0.972609  0.860234  0.986292  \n",
       "3742       0        0       1  0.860706  0.986745  0.867066  \n",
       "3743       0        0       1  0.987204  0.867532  0.856116  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_completed = pd.read_csv(\"Data//Normalized_data.csv\",sep=\";\",index_col=0)\n",
    "df_completed = df_completed.sort_index(ascending = False).reset_index(drop=True)\n",
    "df_completed.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df_completed[['Open','lag_1','lag_2','lag_3','Open_Dollar','Open_IBOVESPA','News_N','News_NN','News_P']]\n",
    "y = df_completed['Close']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((2995, 9), (749, 9), (2995,), (749,))"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, X_test.shape,y_train.shape,y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "range_df = df_completed.Date\n",
    "df=pd.DataFrame(index = df_completed.Date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "regr = LinearRegression()\n",
    "pipe = Pipeline([\n",
    "        ('reduce_dim', PCA()),\n",
    "        ('regressor', regr)\n",
    "        ])\n",
    "pipe.fit(X_train,y_train)\n",
    "ypipe=pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Models//Linear_reg_model.joblib']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dump(pipe, 'Models//Linear_reg_model.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((749,), (749,))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape, ypipe.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train = y_train.reset_index()\n",
    "del y_train['index']\n",
    "y_trainValue = y_train['Close'].values\n",
    "y_test = y_test.reset_index()\n",
    "del y_test['index']\n",
    "y_testValue = y_test['Close'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions_series = pd.Series(ypipe, index=df.index[X_train.shape[0]:])\n",
    "train_series = pd.Series(y_trainValue, index=df.index[:X_train.shape[0]])\n",
    "test_series = pd.Series(y_testValue, index=df.index[X_train.shape[0]:])\n",
    "## Convert index to datetime\n",
    "predictions_series.index = pd.to_datetime(predictions_series.index)\n",
    "train_series.index = pd.to_datetime(train_series.index)\n",
    "test_series.index = pd.to_datetime(test_series.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/anthony/anaconda3/lib/python3.7/site-packages/pandas/plotting/_converter.py:129: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
      "\n",
      "To register the converters:\n",
      "\t>>> from pandas.plotting import register_matplotlib_converters\n",
      "\t>>> register_matplotlib_converters()\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x700 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7), dpi=100)\n",
    "plt.plot(test_series, label='actual',color = 'orange')\n",
    "plt.plot(predictions_series, label='forecast',color='darkblue')\n",
    "plt.plot(train_series, label='training', color='orange' )\n",
    "#plt.fill_between(train_labels.index, train_labels, test_labels, color='k', alpha=.15)\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "#plt.plot(train_labels, label='training')\n",
    "plt.plot(test_series, label='actual',color ='orange')\n",
    "plt.plot(predictions_series, label='forecast', color = 'darkblue')\n",
    "#plt.fill_between(train_labels.index, train_labels, test_labels, \n",
    "                 #color='k', alpha=.15)\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'mape': 0.009578395180942329,\n",
       " 'me': 0.007667403213300014,\n",
       " 'mae': 0.2714920500406397,\n",
       " 'mpe': 0.0004237518107448875,\n",
       " 'rmse': 0.35748632696611576,\n",
       " 'corr': 0.9968149736215822,\n",
       " 'r_squared': 0.9936400916361957,\n",
       " 'minmax': 0.009488361649634847}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def forecast_accuracy(predictions, test_labels):\n",
    "    forecast = predictions\n",
    "    actual = test_labels\n",
    "    mape = np.mean(np.abs(forecast - actual)/np.abs(actual))  # MAPE\n",
    "    me = np.mean(forecast - actual)             # ME\n",
    "    mae = np.mean(np.abs(forecast - actual))    # MAE\n",
    "    mpe = np.mean((forecast - actual)/actual)   # MPE\n",
    "    rmse = np.mean((forecast - actual)**2)**.5  # RMSE\n",
    "    corr = np.corrcoef(forecast, actual)[0,1]   # corr\n",
    "    mins = np.amin(np.hstack([forecast[:,None], \n",
    "                              actual[:,None]]), axis=1)\n",
    "    maxs = np.amax(np.hstack([forecast[:,None], \n",
    "                              actual[:,None]]), axis=1)\n",
    "    minmax = 1 - np.mean(mins/maxs)             # minmax\n",
    "    r_squared = corr**2\n",
    "\n",
    "    return({'mape':mape, 'me':me, 'mae': mae, \n",
    "            'mpe': mpe, 'rmse':rmse, \n",
    "            'corr':corr,'r_squared':r_squared,\n",
    "            'minmax':minmax,\n",
    "           })\n",
    "\n",
    "Linear_model_perf = forecast_accuracy(predictions_series, test_series)\n",
    "Linear_model_perf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Linear Reg wout/ PCA\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)\n",
    "regr = LinearRegression()\n",
    "pipe = Pipeline([\n",
    "        ('regressor', regr)\n",
    "        ])\n",
    "pipe.fit(X_train,y_train)\n",
    "ypipe=pipe.predict(X_test)\n",
    "predictions_series = pd.Series(ypipe, index=df.index[int(X_train.shape[0]):])\n",
    "train_series = pd.Series(y_trainValue, index=df.index[:X_train.shape[0]])\n",
    "test_series = pd.Series(y_testValue, index=df.index[X_train.shape[0]:])\n",
    "## Convert index to datetime\n",
    "predictions_series.index = pd.to_datetime(predictions_series.index)\n",
    "train_series.index = pd.to_datetime(train_series.index)\n",
    "test_series.index = pd.to_datetime(test_series.index)\n",
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "plt.plot(test_series, label='actual',color ='orange')\n",
    "plt.plot(predictions_series, label='forecast', color = 'darkblue')\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "Linear_model_perf = forecast_accuracy(predictions_series, test_series)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ridge Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)\n",
    "df=pd.DataFrame(index = df_completed.Date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "regr = Ridge()\n",
    "pipe = Pipeline([\n",
    "        ('reduce_dim', PCA()),\n",
    "        ('regressor', regr)\n",
    "        ])\n",
    "pipe.fit(X_train,y_train)\n",
    "ypipe=pipe.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Models//Ridge_reg_model.joblib']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dump(pipe, 'Models//Ridge_reg_model.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions_series = pd.Series(ypipe, index=df.index[int(X_train.shape[0]):])\n",
    "train_series = pd.Series(y_trainValue, index=df.index[:X_train.shape[0]])\n",
    "test_series = pd.Series(y_testValue, index=df.index[X_train.shape[0]:])\n",
    "## Convert index to datetime\n",
    "predictions_series.index = pd.to_datetime(predictions_series.index)\n",
    "train_series.index = pd.to_datetime(train_series.index)\n",
    "test_series.index = pd.to_datetime(test_series.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "plt.plot(test_series, label='actual',color ='orange')\n",
    "plt.plot(predictions_series, label='forecast', color = 'darkblue')\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "Ridge_model_perf = forecast_accuracy(predictions_series, test_series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Ridge wout/ PCA\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)\n",
    "regr = Ridge()\n",
    "pipe = Pipeline([\n",
    "        ('regressor', regr)\n",
    "        ])\n",
    "pipe.fit(X_train,y_train)\n",
    "ypipe=pipe.predict(X_test)\n",
    "predictions_series = pd.Series(ypipe, index=df.index[int(X_train.shape[0]):])\n",
    "train_series = pd.Series(y_trainValue, index=df.index[:X_train.shape[0]])\n",
    "test_series = pd.Series(y_testValue, index=df.index[X_train.shape[0]:])\n",
    "## Convert index to datetime\n",
    "predictions_series.index = pd.to_datetime(predictions_series.index)\n",
    "train_series.index = pd.to_datetime(train_series.index)\n",
    "test_series.index = pd.to_datetime(test_series.index)\n",
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "plt.plot(test_series, label='actual',color ='orange')\n",
    "plt.plot(predictions_series, label='forecast', color = 'darkblue')\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'mape': 0.009745813803335293,\n",
       " 'me': 0.0022525270749515825,\n",
       " 'mae': 0.2760455663457984,\n",
       " 'mpe': 0.0002634125430914938,\n",
       " 'rmse': 0.3651808822057498,\n",
       " 'corr': 0.9966745378200191,\n",
       " 'r_squared': 0.9933601343387487,\n",
       " 'minmax': 0.009651042800311926}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast_accuracy(predictions_series, test_series)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Statistical models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the previous step, Data_analysis, we could got that this time series has trends and seasonality, and the most important it isn't non-stationary. I'm using a powerful lib called pmdarima with has auto_arima, what is that? it will iterate our data and pick the best combination about (p,q,i) and the ARIMA, Sarima, MA or AR (that has the smallest AIC). Knowing that the exogenous variables have a high correlation, it's a little bit obvious that will pick a ARIMAX or SARIMAX, this also applies to seasonality. So it has a high probability to get a SARIMAX with the smallest AIC."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Preparing data\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing stepwise search to minimize aic\n",
      "Fit ARIMA(1,1,1)x(0,0,0,0) [intercept=True]; AIC=-3216.332, BIC=-3138.276, Time=17.263 seconds\n",
      "Fit ARIMA(0,1,0)x(0,0,0,0) [intercept=True]; AIC=-470.449, BIC=-404.401, Time=1.297 seconds\n",
      "Fit ARIMA(1,1,0)x(0,0,0,0) [intercept=True]; AIC=-1722.195, BIC=-1650.142, Time=16.244 seconds\n",
      "Fit ARIMA(0,1,1)x(0,0,0,0) [intercept=True]; AIC=-2678.078, BIC=-2606.026, Time=20.085 seconds\n",
      "Near non-invertible roots for order (0, 1, 1)(0, 0, 0, 0); setting score to inf (at least one inverse root too close to the border of the unit circle: 0.996)\n",
      "Fit ARIMA(0,1,0)x(0,0,0,0) [intercept=False]; AIC=-470.826, BIC=-410.782, Time=6.134 seconds\n",
      "Fit ARIMA(2,1,1)x(0,0,0,0) [intercept=True]; AIC=-3275.783, BIC=-3191.722, Time=23.991 seconds\n",
      "Fit ARIMA(2,1,0)x(0,0,0,0) [intercept=True]; AIC=-2822.628, BIC=-2744.571, Time=18.959 seconds\n",
      "Fit ARIMA(3,1,1)x(0,0,0,0) [intercept=True]; AIC=-3354.748, BIC=-3264.682, Time=24.416 seconds\n",
      "Fit ARIMA(3,1,0)x(0,0,0,0) [intercept=True]; AIC=-2794.704, BIC=-2710.643, Time=21.343 seconds\n",
      "Fit ARIMA(4,1,1)x(0,0,0,0) [intercept=True]; AIC=-3255.206, BIC=-3159.136, Time=28.797 seconds\n",
      "Fit ARIMA(3,1,2)x(0,0,0,0) [intercept=True]; AIC=-3318.534, BIC=-3222.464, Time=25.471 seconds\n",
      "Fit ARIMA(2,1,2)x(0,0,0,0) [intercept=True]; AIC=-3102.743, BIC=-3012.678, Time=25.628 seconds\n",
      "Fit ARIMA(4,1,0)x(0,0,0,0) [intercept=True]; AIC=-3021.730, BIC=-2931.664, Time=27.535 seconds\n",
      "Fit ARIMA(4,1,2)x(0,0,0,0) [intercept=True]; AIC=-3282.829, BIC=-3180.754, Time=31.949 seconds\n",
      "Total fit time: 289.132 seconds\n"
     ]
    }
   ],
   "source": [
    "from pmdarima.arima import auto_arima\n",
    "step_wise=auto_arima(y_train, \n",
    "                     exogenous= X_train,\n",
    "                     start_p=1, start_q=1, \n",
    "                     max_p=7, max_q=7, \n",
    "                     d=1, max_d=7,\n",
    "                     trace=True, \n",
    "                     error_action='ignore', \n",
    "                     suppress_warnings=True, \n",
    "                     stepwise=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>y</td>        <th>  No. Observations:  </th>   <td>2995</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(3, 1, 1)</td> <th>  Log Likelihood     </th> <td>1692.374</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Thu, 16 Jul 2020</td> <th>  AIC                </th> <td>-3354.748</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>15:27:10</td>     <th>  BIC                </th> <td>-3264.682</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                  <td>0</td>        <th>  HQIC               </th> <td>-3322.348</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                      <td> - 2995</td>     <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>           <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>intercept</th>     <td>   -0.0003</td> <td>    0.000</td> <td>   -1.196</td> <td> 0.232</td> <td>   -0.001</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Open</th>          <td>    4.9021</td> <td>    0.045</td> <td>  108.489</td> <td> 0.000</td> <td>    4.814</td> <td>    4.991</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>lag_1</th>         <td>    3.9287</td> <td>    0.093</td> <td>   42.180</td> <td> 0.000</td> <td>    3.746</td> <td>    4.111</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>lag_2</th>         <td>    0.4053</td> <td>    0.108</td> <td>    3.748</td> <td> 0.000</td> <td>    0.193</td> <td>    0.617</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>lag_3</th>         <td>   -0.9100</td> <td>    0.060</td> <td>  -15.261</td> <td> 0.000</td> <td>   -1.027</td> <td>   -0.793</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Open_Dollar</th>   <td>    0.0396</td> <td>    0.018</td> <td>    2.173</td> <td> 0.030</td> <td>    0.004</td> <td>    0.075</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Open_IBOVESPA</th> <td>   -0.0167</td> <td>    0.018</td> <td>   -0.918</td> <td> 0.358</td> <td>   -0.052</td> <td>    0.019</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>News_N</th>        <td>         0</td> <td> 2.95e-12</td> <td>        0</td> <td> 1.000</td> <td>-5.79e-12</td> <td> 5.79e-12</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>News_NN</th>       <td>         0</td> <td> 2.95e-12</td> <td>        0</td> <td> 1.000</td> <td>-5.78e-12</td> <td> 5.78e-12</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>News_P</th>        <td>  1.08e-09</td> <td> 1.22e-12</td> <td>  885.030</td> <td> 0.000</td> <td> 1.08e-09</td> <td> 1.08e-09</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>         <td>   -0.6316</td> <td>    0.014</td> <td>  -44.265</td> <td> 0.000</td> <td>   -0.660</td> <td>   -0.604</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>         <td>   -0.4499</td> <td>    0.016</td> <td>  -27.433</td> <td> 0.000</td> <td>   -0.482</td> <td>   -0.418</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L3</th>         <td>   -0.1555</td> <td>    0.015</td> <td>  -10.194</td> <td> 0.000</td> <td>   -0.185</td> <td>   -0.126</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>         <td>   -0.8929</td> <td>    0.008</td> <td> -113.747</td> <td> 0.000</td> <td>   -0.908</td> <td>   -0.877</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>        <td>    0.0183</td> <td>    0.000</td> <td>   54.692</td> <td> 0.000</td> <td>    0.018</td> <td>    0.019</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (Q):</th>          <td>76.15</td> <th>  Jarque-Bera (JB):  </th> <td>728.13</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.00</td>  <th>  Prob(JB):          </th>  <td>0.00</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>2.29</td>  <th>  Skew:              </th>  <td>-0.06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td>  <th>  Kurtosis:          </th>  <td>5.41</td> \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step).<br/>[2] Covariance matrix is singular or near-singular, with condition number 1.96e+19. Standard errors may be unstable."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                               SARIMAX Results                                \n",
       "==============================================================================\n",
       "Dep. Variable:                      y   No. Observations:                 2995\n",
       "Model:               SARIMAX(3, 1, 1)   Log Likelihood                1692.374\n",
       "Date:                Thu, 16 Jul 2020   AIC                          -3354.748\n",
       "Time:                        15:27:10   BIC                          -3264.682\n",
       "Sample:                             0   HQIC                         -3322.348\n",
       "                               - 2995                                         \n",
       "Covariance Type:                  opg                                         \n",
       "=================================================================================\n",
       "                    coef    std err          z      P>|z|      [0.025      0.975]\n",
       "---------------------------------------------------------------------------------\n",
       "intercept        -0.0003      0.000     -1.196      0.232      -0.001       0.000\n",
       "Open              4.9021      0.045    108.489      0.000       4.814       4.991\n",
       "lag_1             3.9287      0.093     42.180      0.000       3.746       4.111\n",
       "lag_2             0.4053      0.108      3.748      0.000       0.193       0.617\n",
       "lag_3            -0.9100      0.060    -15.261      0.000      -1.027      -0.793\n",
       "Open_Dollar       0.0396      0.018      2.173      0.030       0.004       0.075\n",
       "Open_IBOVESPA    -0.0167      0.018     -0.918      0.358      -0.052       0.019\n",
       "News_N                 0   2.95e-12          0      1.000   -5.79e-12    5.79e-12\n",
       "News_NN                0   2.95e-12          0      1.000   -5.78e-12    5.78e-12\n",
       "News_P          1.08e-09   1.22e-12    885.030      0.000    1.08e-09    1.08e-09\n",
       "ar.L1            -0.6316      0.014    -44.265      0.000      -0.660      -0.604\n",
       "ar.L2            -0.4499      0.016    -27.433      0.000      -0.482      -0.418\n",
       "ar.L3            -0.1555      0.015    -10.194      0.000      -0.185      -0.126\n",
       "ma.L1            -0.8929      0.008   -113.747      0.000      -0.908      -0.877\n",
       "sigma2            0.0183      0.000     54.692      0.000       0.018       0.019\n",
       "===================================================================================\n",
       "Ljung-Box (Q):                       76.15   Jarque-Bera (JB):               728.13\n",
       "Prob(Q):                              0.00   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               2.29   Skew:                            -0.06\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                         5.41\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "[2] Covariance matrix is singular or near-singular, with condition number 1.96e+19. Standard errors may be unstable.\n",
       "\"\"\""
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "step_wise.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best statistical forecast model was the SARIMAX(3, 1, 1), let's apply it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
    "model= SARIMAX(y_train, \n",
    " exog=X_train,\n",
    " order=(3,1,1),\n",
    " enforce_invertibility=False, enforce_stationarity=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/anthony/anaconda3/lib/python3.7/site-packages/statsmodels/base/model.py:568: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    }
   ],
   "source": [
    "results= model.fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Models//SARIMAX_Reg_model.joblib']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dump(model, 'Models//SARIMAX_Reg_model.joblib') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((2995, 9), (749, 9), (2995,), (749,))"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.shape, X_test.shape, y_train.shape, y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "steps=-1\n",
    "train_size = X_train.shape[0]\n",
    "test_size = y_test.shape[0]\n",
    "predictions= np.asarray(results.predict(start =train_size, end=train_size+test_size+(steps),exog=X_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictions_series.index = pd.to_datetime(predictions_series.index)\n",
    "train_series.index = pd.to_datetime(train_series.index)\n",
    "test_series.index = pd.to_datetime(test_series.index)\n",
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "plt.plot(test_series, label='actual',color ='orange')\n",
    "plt.plot(predictions_series, label='forecast', color = 'darkblue')\n",
    "plt.title('Forecast vs Actuals')\n",
    "plt.legend(loc='upper left', fontsize=8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'mape': 0.00966928198646825,\n",
       " 'me': 0.005750663357897148,\n",
       " 'mae': 0.27398713787487566,\n",
       " 'mpe': 0.0003468954061160584,\n",
       " 'rmse': 0.36079425007877897,\n",
       " 'corr': 0.9967553787416672,\n",
       " 'r_squared': 0.9935212850504445,\n",
       " 'minmax': 0.009579413490939936}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SARIMAX_Model_perf = forecast_accuracy(predictions, test_series)\n",
    "SARIMAX_Model_perf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LSTM Regressor model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As the requeriment of the project have a Deep learning model, it was chosen the most famous for regressions. The model is using Keras lib that is a very simplest way to create deep learning model using TensorFlow in backend, there's some disadvantages compared to pytorch, but to gain some velocity I opted for it.  \n",
    "\n",
    "The model has not been tuned, so I basically picked a LSTM model in the IBM course and ajusted it to my data, calculing the batch_size and time_steps for my time serie, the hyperparameter stateful was chose, due the sequences related as we saw with ACF in the previous step that represented a high interconnection "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,  random_state=0, shuffle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 64\n",
    "epochs = 120\n",
    "timesteps = 10\n",
    "\n",
    "def get_train_length(dataset, batch_size, test_percent):\n",
    "    # substract test_percent to be excluded from training, reserved for testset\n",
    "    length = len(dataset)\n",
    "    length *= 1 - test_percent\n",
    "    train_length_values = []\n",
    "    for x in range(int(length) - 100,int(length)): \n",
    "        modulo=x%batch_size\n",
    "        if (modulo == 0):\n",
    "            train_length_values.append(x)\n",
    "            print(x)\n",
    "    return (max(train_length_values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>Date</th>\n",
       "      <th>Close</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Vol</th>\n",
       "      <th>Var</th>\n",
       "      <th>Open_Dollar</th>\n",
       "      <th>Open_IBOVESPA</th>\n",
       "      <th>DayofWeek</th>\n",
       "      <th>Weekofyear</th>\n",
       "      <th>Quarter</th>\n",
       "      <th>Month</th>\n",
       "      <th>News_N</th>\n",
       "      <th>News_NN</th>\n",
       "      <th>News_P</th>\n",
       "      <th>lag_1</th>\n",
       "      <th>lag_2</th>\n",
       "      <th>lag_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2005-04-05</td>\n",
       "      <td>4.32</td>\n",
       "      <td>-1.244518</td>\n",
       "      <td>-1.244864</td>\n",
       "      <td>-1.236755</td>\n",
       "      <td>2.285151</td>\n",
       "      <td>-0.029202</td>\n",
       "      <td>0.061785</td>\n",
       "      <td>-1.831555</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.245974</td>\n",
       "      <td>-1.244239</td>\n",
       "      <td>-1.248585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2005-04-06</td>\n",
       "      <td>4.31</td>\n",
       "      <td>-1.243303</td>\n",
       "      <td>-1.248472</td>\n",
       "      <td>-1.236755</td>\n",
       "      <td>2.175839</td>\n",
       "      <td>-0.130565</td>\n",
       "      <td>0.052995</td>\n",
       "      <td>-1.851831</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.243541</td>\n",
       "      <td>-1.247888</td>\n",
       "      <td>-1.243719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2005-04-07</td>\n",
       "      <td>4.33</td>\n",
       "      <td>-1.244518</td>\n",
       "      <td>-1.252080</td>\n",
       "      <td>-1.236755</td>\n",
       "      <td>2.178052</td>\n",
       "      <td>0.173524</td>\n",
       "      <td>0.013495</td>\n",
       "      <td>-1.870653</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.247190</td>\n",
       "      <td>-1.243022</td>\n",
       "      <td>-1.247369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2005-04-08</td>\n",
       "      <td>4.30</td>\n",
       "      <td>-1.243303</td>\n",
       "      <td>-1.253282</td>\n",
       "      <td>-1.237984</td>\n",
       "      <td>0.612276</td>\n",
       "      <td>-0.333290</td>\n",
       "      <td>0.013730</td>\n",
       "      <td>-1.837179</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.242325</td>\n",
       "      <td>-1.246672</td>\n",
       "      <td>-1.247369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2005-04-11</td>\n",
       "      <td>4.34</td>\n",
       "      <td>-1.244518</td>\n",
       "      <td>-1.249674</td>\n",
       "      <td>-1.236755</td>\n",
       "      <td>0.175913</td>\n",
       "      <td>0.380657</td>\n",
       "      <td>0.003181</td>\n",
       "      <td>-1.860300</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>-1.245974</td>\n",
       "      <td>-1.246672</td>\n",
       "      <td>-1.259534</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Close      Open      High       Low       Vol       Var  \\\n",
       "0  2005-04-05   4.32 -1.244518 -1.244864 -1.236755  2.285151 -0.029202   \n",
       "1  2005-04-06   4.31 -1.243303 -1.248472 -1.236755  2.175839 -0.130565   \n",
       "2  2005-04-07   4.33 -1.244518 -1.252080 -1.236755  2.178052  0.173524   \n",
       "3  2005-04-08   4.30 -1.243303 -1.253282 -1.237984  0.612276 -0.333290   \n",
       "4  2005-04-11   4.34 -1.244518 -1.249674 -1.236755  0.175913  0.380657   \n",
       "\n",
       "   Open_Dollar  Open_IBOVESPA  DayofWeek  Weekofyear  Quarter  Month  News_N  \\\n",
       "0     0.061785      -1.831555          1          14        2      4       0   \n",
       "1     0.052995      -1.851831          2          14        2      4       0   \n",
       "2     0.013495      -1.870653          3          14        2      4       0   \n",
       "3     0.013730      -1.837179          4          14        2      4       0   \n",
       "4     0.003181      -1.860300          0          15        2      4       0   \n",
       "\n",
       "   News_NN  News_P     lag_1     lag_2     lag_3  \n",
       "0        0       1 -1.245974 -1.244239 -1.248585  \n",
       "1        0       1 -1.243541 -1.247888 -1.243719  \n",
       "2        0       1 -1.247190 -1.243022 -1.247369  \n",
       "3        0       1 -1.242325 -1.246672 -1.247369  \n",
       "4        0       1 -1.245974 -1.246672 -1.259534  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_completed.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2944\n",
      "2944\n"
     ]
    }
   ],
   "source": [
    "y = df_completed.iloc[:,1:2].values.astype(float)  \n",
    "length = get_train_length(y, batch_size, 0.2)\n",
    "print(length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2964, 1)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Adding timesteps * 2\n",
    "upper_train = length + timesteps*2\n",
    "df_data_1_train = pd.DataFrame(y[0:upper_train])\n",
    "training_set = df_data_1_train.values\n",
    "training_set.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2964, 1)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Feature Scaling\n",
    "#scale between 0 and 1. the weights are esier to find.\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "sc = MinMaxScaler(feature_range = (0, 1))\n",
    "training_set_scaled = sc.fit_transform(np.float64(training_set))\n",
    "training_set_scaled.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2964\n",
      "2964\n",
      "[array([0.0091001 , 0.00859454, 0.00960566, 0.00808898, 0.01011122]), array([0.00859454, 0.00960566, 0.00808898, 0.01011122, 0.00859454])]\n",
      "(2964,)\n",
      "[array([0.00859454, 0.00859454, 0.00353893, 0.        , 0.00252781]), array([0.00859454, 0.00353893, 0.        , 0.00252781, 0.00758342])]\n",
      "(2964,)\n"
     ]
    }
   ],
   "source": [
    "### Creating Lags \n",
    "\n",
    "length = len(training_set_scaled)\n",
    "timesteps = 5\n",
    "\n",
    "X_train = []\n",
    "y_train = []\n",
    "\n",
    "# Creating a data structure with n timesteps\n",
    "for i in range(timesteps, length + timesteps): \n",
    "    \n",
    "    X_train.append(training_set_scaled[i-timesteps:i,0])\n",
    "    y_train.append(training_set_scaled[i:i+timesteps,0])\n",
    "\n",
    "print(len(X_train))\n",
    "print(len(y_train))\n",
    "print(X_train[0:2])\n",
    "print(np.array(X_train).shape)\n",
    "print(y_train[0:2])\n",
    "print(np.array(y_train).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = np.vstack(X_train[:2944])\n",
    "y_train = np.vstack(y_train[:2944])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, y_train = np.array(X_train), np.array(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2944, 5, 1)\n",
      "(2944, 5, 1)\n"
     ]
    }
   ],
   "source": [
    "X_train, y_train = np.array(X_train), np.array(y_train)\n",
    "X_train = np.reshape(X_train, (X_train.shape[0], X_train.shape[1], 1))\n",
    "y_train = np.reshape(y_train, (y_train.shape[0], y_train.shape[1], 1))\n",
    "print(X_train.shape)\n",
    "print(y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "# Building the LSTM\n",
    "# Importing the Keras libraries and packages\n",
    "from keras.layers import Dense\n",
    "from keras.layers import Input, LSTM\n",
    "from keras.models import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         (64, 5, 1)                0         \n",
      "_________________________________________________________________\n",
      "lstm_1 (LSTM)                (64, 5, 10)               480       \n",
      "_________________________________________________________________\n",
      "lstm_2 (LSTM)                (64, 5, 10)               840       \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (64, 5, 1)                11        \n",
      "=================================================================\n",
      "Total params: 1,331\n",
      "Trainable params: 1,331\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "# Initialising the LSTM Model with MAE Loss-Function\n",
    "# Using Functional API\n",
    "\n",
    "inputs_1_mae = Input(batch_shape=(batch_size,timesteps,1))\n",
    "#each layer is the input of the next layer\n",
    "lstm_1_mae = LSTM(10, stateful=True, return_sequences=True)(inputs_1_mae)\n",
    "lstm_2_mae = LSTM(10, stateful=True, return_sequences=True)(lstm_1_mae)\n",
    "\n",
    "output_1_mae = Dense(units = 1)(lstm_2_mae)\n",
    "\n",
    "regressor_mae = Model(inputs=inputs_1_mae, outputs = output_1_mae)\n",
    "\n",
    "#adam is fast starting off and then gets slower and more precise\n",
    "#mae -> mean absolute error loss function\n",
    "regressor_mae.compile(optimizer='adam', loss = 'mae')   ### mae\n",
    "regressor_mae.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 0\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 156us/step - loss: 0.0964\n",
      "Epoch: 1\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 41us/step - loss: 0.1082\n",
      "Epoch: 2\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 42us/step - loss: 0.0871\n",
      "Epoch: 3\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0651\n",
      "Epoch: 4\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0729\n",
      "Epoch: 5\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0654\n",
      "Epoch: 6\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0621\n",
      "Epoch: 7\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0569\n",
      "Epoch: 8\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 55us/step - loss: 0.0528\n",
      "Epoch: 9\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0486\n",
      "Epoch: 10\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 47us/step - loss: 0.0445\n",
      "Epoch: 11\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 47us/step - loss: 0.0407\n",
      "Epoch: 12\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0391\n",
      "Epoch: 13\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0382\n",
      "Epoch: 14\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0377\n",
      "Epoch: 15\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0372\n",
      "Epoch: 16\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0368\n",
      "Epoch: 17\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0363\n",
      "Epoch: 18\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0358\n",
      "Epoch: 19\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0353\n",
      "Epoch: 20\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0348\n",
      "Epoch: 21\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0343\n",
      "Epoch: 22\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0338\n",
      "Epoch: 23\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0333\n",
      "Epoch: 24\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0330\n",
      "Epoch: 25\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0327\n",
      "Epoch: 26\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0326\n",
      "Epoch: 27\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0326\n",
      "Epoch: 28\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0327\n",
      "Epoch: 29\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0321\n",
      "Epoch: 30\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0315\n",
      "Epoch: 31\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0313\n",
      "Epoch: 32\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0312\n",
      "Epoch: 33\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0311\n",
      "Epoch: 34\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0311\n",
      "Epoch: 35\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0307\n",
      "Epoch: 36\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0307\n",
      "Epoch: 37\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 41us/step - loss: 0.0311\n",
      "Epoch: 38\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0311\n",
      "Epoch: 39\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 42us/step - loss: 0.0304\n",
      "Epoch: 40\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0305\n",
      "Epoch: 41\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0307\n",
      "Epoch: 42\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0304\n",
      "Epoch: 43\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0303\n",
      "Epoch: 44\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 55us/step - loss: 0.0301\n",
      "Epoch: 45\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 55us/step - loss: 0.0298\n",
      "Epoch: 46\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 49us/step - loss: 0.0302\n",
      "Epoch: 47\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 47us/step - loss: 0.0312\n",
      "Epoch: 48\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0314\n",
      "Epoch: 49\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 56us/step - loss: 0.0294\n",
      "Epoch: 50\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 47us/step - loss: 0.0316\n",
      "Epoch: 51\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 48us/step - loss: 0.0314\n",
      "Epoch: 52\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 57us/step - loss: 0.0303\n",
      "Epoch: 53\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 59us/step - loss: 0.0279\n",
      "Epoch: 54\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 49us/step - loss: 0.0293\n",
      "Epoch: 55\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 51us/step - loss: 0.0304\n",
      "Epoch: 56\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 53us/step - loss: 0.0285\n",
      "Epoch: 57\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 58us/step - loss: 0.0290\n",
      "Epoch: 58\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 61us/step - loss: 0.0294\n",
      "Epoch: 59\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 51us/step - loss: 0.0305\n",
      "Epoch: 60\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 65us/step - loss: 0.0348\n",
      "Epoch: 61\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 60us/step - loss: 0.0398\n",
      "Epoch: 62\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 62us/step - loss: 0.0294\n",
      "Epoch: 63\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 72us/step - loss: 0.0277\n",
      "Epoch: 64\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 78us/step - loss: 0.0265\n",
      "Epoch: 65\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 68us/step - loss: 0.0266\n",
      "Epoch: 66\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 49us/step - loss: 0.0266\n",
      "Epoch: 67\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 49us/step - loss: 0.0266\n",
      "Epoch: 68\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 48us/step - loss: 0.0265\n",
      "Epoch: 69\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 42us/step - loss: 0.0266\n",
      "Epoch: 70\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0266\n",
      "Epoch: 71\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0268\n",
      "Epoch: 72\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 85us/step - loss: 0.0268\n",
      "Epoch: 73\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 67us/step - loss: 0.0266\n",
      "Epoch: 74\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 52us/step - loss: 0.0263\n",
      "Epoch: 75\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 53us/step - loss: 0.0262\n",
      "Epoch: 76\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 53us/step - loss: 0.0260\n",
      "Epoch: 77\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 53us/step - loss: 0.0259\n",
      "Epoch: 78\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0258\n",
      "Epoch: 79\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 42us/step - loss: 0.0256\n",
      "Epoch: 80\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 41us/step - loss: 0.0255\n",
      "Epoch: 81\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0254\n",
      "Epoch: 82\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0254\n",
      "Epoch: 83\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0253\n",
      "Epoch: 84\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0253\n",
      "Epoch: 85\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0253\n",
      "Epoch: 86\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0252\n",
      "Epoch: 87\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0251\n",
      "Epoch: 88\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0251\n",
      "Epoch: 89\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0250\n",
      "Epoch: 90\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0250\n",
      "Epoch: 91\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0249\n",
      "Epoch: 92\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0249\n",
      "Epoch: 93\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0249\n",
      "Epoch: 94\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0248\n",
      "Epoch: 95\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0248\n",
      "Epoch: 96\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0246\n",
      "Epoch: 97\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0245\n",
      "Epoch: 98\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0244\n",
      "Epoch: 99\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0243\n",
      "Epoch: 100\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0243\n",
      "Epoch: 101\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0242\n",
      "Epoch: 102\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0241\n",
      "Epoch: 103\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0240\n",
      "Epoch: 104\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0240\n",
      "Epoch: 105\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0239\n",
      "Epoch: 106\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0239\n",
      "Epoch: 107\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0238\n",
      "Epoch: 108\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0237\n",
      "Epoch: 109\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0237\n",
      "Epoch: 110\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0237\n",
      "Epoch: 111\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 43us/step - loss: 0.0236\n",
      "Epoch: 112\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0236\n",
      "Epoch: 113\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 44us/step - loss: 0.0235\n",
      "Epoch: 114\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 46us/step - loss: 0.0235\n",
      "Epoch: 115\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 48us/step - loss: 0.0235\n",
      "Epoch: 116\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 45us/step - loss: 0.0235\n",
      "Epoch: 117\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 53us/step - loss: 0.0234\n",
      "Epoch: 118\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 67us/step - loss: 0.0234\n",
      "Epoch: 119\n",
      "Epoch 1/1\n",
      "2944/2944 [==============================] - 0s 61us/step - loss: 0.0232\n"
     ]
    }
   ],
   "source": [
    "#Statefull\n",
    "for i in range(epochs):\n",
    "    print(\"Epoch: \" + str(i))\n",
    "    #run through all data but the cell, hidden state are used for the next batch.\n",
    "    regressor_mae.fit(X_train, y_train, shuffle=False, epochs = 1, batch_size = batch_size)\n",
    "    #resets only the states but the weights, cell and hidden are kept.\n",
    "    regressor_mae.reset_states()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "regressor_mae.save(filepath=\"Models//LSTM_reg_model.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_test_length(dataset, batch_size):\n",
    "    \n",
    "    test_length_values = []\n",
    "    for x in range(len(dataset) - 200, len(dataset) - timesteps*2): \n",
    "        modulo=(x-upper_train)%batch_size\n",
    "        if (modulo == 0):\n",
    "            test_length_values.append(x)\n",
    "            print(x)\n",
    "    return (max(test_length_values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3604\n",
      "3668\n",
      "3732\n",
      "3732\n",
      "768\n"
     ]
    }
   ],
   "source": [
    "test_length = get_test_length(y, batch_size)\n",
    "print(test_length)\n",
    "upper_test = test_length + timesteps*2\n",
    "testset_length = test_length - upper_train\n",
    "print(testset_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2964 3742 3744\n"
     ]
    }
   ],
   "source": [
    "print(upper_train, upper_test, len(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# construct test set\n",
    "\n",
    "#subsetting\n",
    "df_data_1_test = y[upper_train:upper_test] \n",
    "test_set = df_data_1_test #df_data_1_test.iloc[:,1:2].values\n",
    "\n",
    "#scaling\n",
    "scaled_real_bcg_values_test = sc.fit_transform(np.float64(test_set))\n",
    "\n",
    "#creating input data\n",
    "X_test = []\n",
    "for i in range(timesteps, testset_length + timesteps):\n",
    "    X_test.append(scaled_real_bcg_values_test[i-timesteps:i, 0])\n",
    "X_test = np.array(X_test)\n",
    "\n",
    "\n",
    "#reshaping\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], X_test.shape[1], 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(749,)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(768, 5, 1)\n",
      "(768, 5)\n",
      "(763, 1)\n"
     ]
    }
   ],
   "source": [
    "#prediction\n",
    "predicted_bcg_values_test_mae = regressor_mae.predict(X_test, batch_size=batch_size)\n",
    "regressor_mae.reset_states()\n",
    "\n",
    "print(predicted_bcg_values_test_mae.shape)\n",
    "\n",
    "#reshaping\n",
    "predicted_bcg_values_test_mae = np.reshape(predicted_bcg_values_test_mae, \n",
    "                                       (predicted_bcg_values_test_mae.shape[0], \n",
    "                                        predicted_bcg_values_test_mae.shape[1]))\n",
    "\n",
    "print(predicted_bcg_values_test_mae.shape)\n",
    "#inverse transform\n",
    "predicted_bcg_values_test_mae = sc.inverse_transform(predicted_bcg_values_test_mae)\n",
    "\n",
    "\n",
    "#creating y_test data\n",
    "y_test = []\n",
    "for j in range(0, testset_length - timesteps):\n",
    "    y_test = np.append(y_test, predicted_bcg_values_test_mae[j, timesteps-1])\n",
    "\n",
    "# reshaping\n",
    "y_test = np.reshape(y_test, (y_test.shape[0], 1))\n",
    "\n",
    "print(y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the results\n",
    "plt.figure(figsize=(12,5), dpi=100)\n",
    "plt.plot(test_set[timesteps:len(y_test)].astype(float), color = 'orange', label = 'Real ITUB4 shares Prices')\n",
    "plt.plot(y_test[0:len(y_test) - timesteps].astype(float), color = 'darkblue', label = 'Predicted ITUB4 shares Prices')\n",
    "\n",
    "plt.title('ITUB4 Prices Prediction - MAE')\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('ITUB4 Prices')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictions_series = pd.DataFrame(y_test[0:len(y_test) - timesteps].astype(float), columns=['pred'])\n",
    "test_series = pd.DataFrame(test_set[timesteps:len(y_test)].astype(float),columns=['values'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "LSTM_Model_perf = forecast_accuracy(predictions_series['pred'], test_series['values'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison Regressor models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Linear Model RMSE:  0.3574863269661155 \n",
      " Ridge Model RMSE:  0.36518088220574996 \n",
      " SARIMAX Model RMSE:  0.36079425007877897 \n",
      " LSTM Model RMSE:  0.7259566315152011\n"
     ]
    }
   ],
   "source": [
    "print(\" Linear Model RMSE: \",Linear_model_perf['rmse'], \"\\n\",\n",
    "      \"Ridge Model RMSE: \",Ridge_model_perf['rmse'],\"\\n\",\n",
    "      \"SARIMAX Model RMSE: \",SARIMAX_Model_perf['rmse'],\"\\n\",\n",
    "      \"LSTM Model RMSE: \",LSTM_Model_perf['rmse'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Linear Model r_Squared:  0.9936400916361953 \n",
      " Ridge Model r_Squared:  0.9933601343387491 \n",
      " SARIMAX Model r_Squared:  0.9935212850504445 \n",
      " LSTM Model r_Squared:  0.9752139129837185\n"
     ]
    }
   ],
   "source": [
    "print(\" Linear Model r_Squared: \",Linear_model_perf['r_squared'],\"\\n\",\n",
    "      \"Ridge Model r_Squared: \",Ridge_model_perf['r_squared'],\"\\n\",\n",
    "      \"SARIMAX Model r_Squared: \",SARIMAX_Model_perf['r_squared'],\"\\n\",\n",
    "      \"LSTM Model r_Squared: \",LSTM_Model_perf['r_squared'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Linear Model Correlation:  0.996814973621582 \n",
      " Ridge Model Correlation:  0.9966745378200194 \n",
      " SARIMAX Model Correlation:  0.9967553787416672 \n",
      " LSTM Model Correlation:  0.9875291960158538\n"
     ]
    }
   ],
   "source": [
    "print(\" Linear Model Correlation: \",Linear_model_perf['corr'],\"\\n\",\n",
    "      \"Ridge Model Correlation: \",Ridge_model_perf['corr'],\"\\n\",\n",
    "      \"SARIMAX Model Correlation: \",SARIMAX_Model_perf['corr'],\"\\n\",\n",
    "      \"LSTM Model Correlation: \",LSTM_Model_perf['corr'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The best regression model for our goal is the Linear Model. Fortunately or unfortunately, due it will required to be implemented using Pyspark in the next steps and it's very simple to do. The main goal is hit the nail on the head the Close value, thus Linear Model has the smallest RMSE. Of course, maybe if we spend more time to tune the LSTM we could get a best model, but as the purpose is learning how everything fits together we will proceed with the simple linear model."
   ]
  }
 ],
 "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}