[3.2] LSTM Multivariate.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"KghNzcvMl-Xd"},"source":["# **Bulding a LSTM multivariate model**"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"X8pb1f9WmNgq"},"outputs":[],"source":["!pip install tensorflow --quiet\n","!pip install yfinance   --quiet\n","\n","import math as mt\n","import numpy as np\n","import pandas as pd\n","import yfinance as yf\n","import tensorflow as tf\n","import matplotlib.pyplot as plt\n","import matplotlib.dates as mdates\n","\n","from tensorflow import keras\n","from seaborn import set_style\n","from sklearn.preprocessing import MinMaxScaler\n","\n","set_style(\"darkgrid\")\n","\n","# For reproducibility\n","np.random.seed(24)\n","tf.random.set_seed(24)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1454,"status":"ok","timestamp":1689366154408,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"6ElIU55kmpEu","outputId":"3e6095b3-182f-4f6c-8cdf-0df8c1a1426f"},"outputs":[{"name":"stdout","output_type":"stream","text":["[*********************100%***********************]  1 of 1 completed\n","[*********************100%***********************]  1 of 1 completed\n","[*********************100%***********************]  1 of 1 completed\n","[*********************100%***********************]  1 of 1 completed\n"]}],"source":["start_date = \"2020-06-24\"\n","end_date   = \"2023-06-24\"\n","\n","apple_ticker  = \"AAPL\"\n","smsg_ticker   = \"005930.KS\" # Ticker symbol for Samsung on Korea Stock Exchange (KS)\n","\n","amazon_ticker = \"AMZN\"\n","baba_ticker   = \"BABA\"  # Ticker symbol for Alibaba Group on NYSE\n","\n","AAPL = yf.download(apple_ticker, start=start_date, end=end_date)\n","SMSG = yf.download(smsg_ticker, start=start_date, end=end_date)\n","\n","AMZN = yf.download(amazon_ticker, start=start_date, end=end_date)\n","BABA = yf.download(baba_ticker, start=start_date, end=end_date)\n","\n","AAPL.index = pd.to_datetime(AAPL.index)\n","AMZN.index = pd.to_datetime(AMZN.index)\n","BABA.index = pd.to_datetime(BABA.index)\n","SMSG.index = pd.to_datetime(SMSG.index)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"executionInfo":{"elapsed":22,"status":"ok","timestamp":1689366154408,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"foiqH_6esvWk","outputId":"61a8d6ae-e2bb-47fd-89f3-db372c0cfb25"},"outputs":[{"data":{"text/html":["\n","\n","  <div id=\"df-b374d45b-0e1c-4727-9d29-b63def2be87a\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","   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<th>2023-06-21</th>\n","      <td>70700.0</td>\n","      <td>71200.0</td>\n","      <td>70400.0</td>\n","      <td>70500.0</td>\n","      <td>70500.0</td>\n","      <td>10626603</td>\n","    </tr>\n","    <tr>\n","      <th>2023-06-22</th>\n","      <td>70200.0</td>\n","      <td>71500.0</td>\n","      <td>70100.0</td>\n","      <td>71300.0</td>\n","      <td>71300.0</td>\n","      <td>11411007</td>\n","    </tr>\n","    <tr>\n","      <th>2023-06-23</th>\n","      <td>72000.0</td>\n","      <td>72200.0</td>\n","      <td>71600.0</td>\n","      <td>71600.0</td>\n","      <td>71600.0</td>\n","      <td>12329484</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b374d45b-0e1c-4727-9d29-b63def2be87a')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 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70100.0  71300.0    71300.0  11411007\n","2023-06-23  72000.0  72200.0  71600.0  71600.0    71600.0  12329484"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["SMSG.tail()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"executionInfo":{"elapsed":22,"status":"ok","timestamp":1689366154409,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"VmsJ39PGtITF","outputId":"cced8031-b96f-4544-90e3-af8877ff2076"},"outputs":[{"data":{"text/html":["\n","\n","  <div id=\"df-5ca0f2c7-dc05-4c6f-ade8-b679ff206f06\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table 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<td>87.379997</td>\n","      <td>89.160004</td>\n","      <td>86.620003</td>\n","      <td>86.769997</td>\n","      <td>86.769997</td>\n","      <td>15159900</td>\n","    </tr>\n","    <tr>\n","      <th>2023-06-22</th>\n","      <td>86.779999</td>\n","      <td>87.315002</td>\n","      <td>85.320000</td>\n","      <td>86.889999</td>\n","      <td>86.889999</td>\n","      <td>10272700</td>\n","    </tr>\n","    <tr>\n","      <th>2023-06-23</th>\n","      <td>85.809998</td>\n","      <td>85.938004</td>\n","      <td>84.370003</td>\n","      <td>84.919998</td>\n","      <td>84.919998</td>\n","      <td>14830800</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5ca0f2c7-dc05-4c6f-ade8-b679ff206f06')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 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Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n"],"text/plain":["                 Open       High        Low      Close  Adj Close    Volume\n","Date                                                                       \n","2023-06-16  94.000000  94.290001  91.519997  92.099998  92.099998  25048200\n","2023-06-20  89.830002  90.199997  87.320000  87.930000  87.930000  23382900\n","2023-06-21  87.379997  89.160004  86.620003  86.769997  86.769997  15159900\n","2023-06-22  86.779999  87.315002  85.320000  86.889999  86.889999  10272700\n","2023-06-23  85.809998  85.938004  84.370003  84.919998  84.919998  14830800"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["\n","BABA.tail()"]},{"cell_type":"markdown","metadata":{"id":"62Dv5iaXxVbm"},"source":["Before starting the analysis, it is necessary to understand that there exists a correlation (or anticorrelation) between the returns of a company and the chosen competitor."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ipWFBlDK1s44"},"outputs":[],"source":["AAPL['AAPL Close']  = AAPL['Close']\n","AAPL['AAPL Volume'] = AAPL['Volume']\n","\n","# SK WON to USD (08-07-2023):\n","WON_USD = 0.000770\n","SMSG['SMSG Close']  = SMSG['Close'] * WON_USD\n","SMSG['SMSG Volume'] = SMSG['Volume']\n","\n","AAPL = AAPL.drop(['Open','High','Low','Close','Adj Close','Volume'], axis=1)\n","SMSG = SMSG.drop(['Open','High','Low','Close','Adj Close','Volume'], axis=1)\n","\n","\n","AMZN['AMZN Close']  = AMZN['Close']\n","AMZN['AMZN Volume'] = AMZN['Volume']\n","\n","BABA['BABA Close']  = BABA['Close']\n","BABA['BABA Volume'] = BABA['Volume']\n","\n","AMZN = AMZN.drop(['Open','High','Low','Close','Adj Close','Volume'], axis=1)\n","BABA = BABA.drop(['Open','High','Low','Close','Adj Close','Volume'], axis=1)\n","\n","\n","# Merge the two DataFrames based on 'Date' column\n","AAPL_SMSG = pd.merge(AAPL, SMSG, on='Date', how='inner')\n","AMZN_BABA = pd.merge(AMZN, BABA, on='Date', how='inner')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"m4ySI94Yxb91"},"outputs":[],"source":["T = 21\n","\n","AAPL_returns = AAPL_SMSG['AAPL Close'] - AAPL_SMSG['AAPL Close'].shift(T)\n","SMSG_returns = AAPL_SMSG['SMSG Close'] - AAPL_SMSG['SMSG Close'].shift(T)\n","\n","AMZN_returns = AMZN_BABA['AMZN Close'] - AMZN_BABA['AMZN Close'].shift(T)\n","BABA_returns = AMZN_BABA['BABA Close'] - AMZN_BABA['BABA Close'].shift(T)\n","\n","AAPL_SMSG['AAPL Ret'] = AAPL_returns\n","AAPL_SMSG['SMSG Ret'] = SMSG_returns\n","\n","AMZN_BABA['AMZN Ret'] = AMZN_returns\n","AMZN_BABA['BABA Ret'] = BABA_returns\n","\n","AAPL_SMSG = AAPL_SMSG.iloc[T:]\n","AMZN_BABA = AMZN_BABA.iloc[T:]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"executionInfo":{"elapsed":21,"status":"ok","timestamp":1689366154410,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"7pKLNQsmzB8F","outputId":"ba26ad4c-8ff4-4854-a8ce-159c2ab45e0f"},"outputs":[{"data":{"text/html":["\n","\n","  <div id=\"df-bb9cc3a4-ff72-4f4f-855d-be034e82a093\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th 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<td>2.849</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-28</th>\n","      <td>93.252502</td>\n","      <td>103625600</td>\n","      <td>45.122</td>\n","      <td>48431566</td>\n","      <td>4.845001</td>\n","      <td>4.081</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-29</th>\n","      <td>95.040001</td>\n","      <td>90329200</td>\n","      <td>45.430</td>\n","      <td>36476611</td>\n","      <td>4.595001</td>\n","      <td>5.082</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-30</th>\n","      <td>96.190002</td>\n","      <td>158130000</td>\n","      <td>45.430</td>\n","      <td>19285354</td>\n","      <td>4.990005</td>\n","      <td>4.774</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bb9cc3a4-ff72-4f4f-855d-be034e82a093')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","\n","  <svg 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Visit the ' +\n","            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n","            + ' to learn more about interactive tables.';\n","          element.innerHTML = '';\n","          dataTable['output_type'] = 'display_data';\n","          await google.colab.output.renderOutput(dataTable, element);\n","          const docLink = document.createElement('div');\n","          docLink.innerHTML = docLinkHtml;\n","          element.appendChild(docLink);\n","        }\n","      </script>\n","    </div>\n","  </div>\n"],"text/plain":["            AAPL Close  AAPL Volume  SMSG Close  SMSG Volume  AAPL Ret  \\\n","Date                                                                     \n","2020-07-24   92.614998    185438800      41.734     10994535  2.599998   \n","2020-07-27   94.809998    121214000      42.812     21054421  3.599998   \n","2020-07-28   93.252502    103625600      45.122     48431566  4.845001   \n","2020-07-29   95.040001     90329200      45.430     36476611  4.595001   \n","2020-07-30   96.190002    158130000      45.430     19285354  4.990005   \n","\n","            SMSG Ret  \n","Date                  \n","2020-07-24     1.001  \n","2020-07-27     2.849  \n","2020-07-28     4.081  \n","2020-07-29     5.082  \n","2020-07-30     4.774  "]},"execution_count":8,"metadata":{},"output_type":"execute_result"}],"source":["AAPL_SMSG.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"executionInfo":{"elapsed":20,"status":"ok","timestamp":1689366154410,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"OLWBmuxkzGkG","outputId":"9742b12a-9001-4839-8b9c-6fdd8cdfc380"},"outputs":[{"data":{"text/html":["\n","\n","  <div id=\"df-414b0414-c5b4-4a62-abe0-49e5e637006f\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr 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 <th>2020-07-27</th>\n","      <td>152.760498</td>\n","      <td>83410000</td>\n","      <td>250.860001</td>\n","      <td>18966900</td>\n","      <td>15.031494</td>\n","      <td>28.699997</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-28</th>\n","      <td>150.016495</td>\n","      <td>62534000</td>\n","      <td>249.050003</td>\n","      <td>9878700</td>\n","      <td>15.373001</td>\n","      <td>33.339996</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-29</th>\n","      <td>151.676498</td>\n","      <td>59482000</td>\n","      <td>252.449997</td>\n","      <td>11493600</td>\n","      <td>17.657501</td>\n","      <td>37.429993</td>\n","    </tr>\n","    <tr>\n","      <th>2020-07-30</th>\n","      <td>152.593994</td>\n","      <td>122566000</td>\n","      <td>252.740005</td>\n","      <td>7032900</td>\n","      <td>14.653000</td>\n","      <td>37.040009</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" 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In other words, the null hypothesis assumes that the true population correlation coefficient is zero.\n","\n","If the p-value is below a chosen significance level (e.g., 0.05), the null hypothesis can be rejected in favor of the alternative hypothesis, indicating that there is a statistically significant correlation between the variables.\n","\n","AAPL-SMSG:\n","- A coefficient of `0.4131` indicates a moderate positive correlation between AAPL and SMSG stock returns. This means that, on average, when the stock returns of Apple increase, the stock returns of Samsung tend to increase as well, and vice versa.\n","- In this case, the p-value is extremely small (`5.567e-30`), which is close to zero. This suggests that the observed correlation between AAPL and SMSG stock returns is highly unlikely to occur by chance.\n","\n","AMZN-BABA:\n","- In this case, the coefficient indicates a weak positive correlation between AMZN and BABA stock returns. It suggests that there is a tendency for the stock returns of Amazon and Alibaba to move together, but the correlation is not as strong as in the AAPL-SMSG case.\n","- The p-value for the AMZN-BABA correlation is also very small (`2.384e-12`), indicating that the observed correlation is statistically significant.\n","\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":517},"executionInfo":{"elapsed":1262,"status":"ok","timestamp":1689366155656,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"x6zoUFVx-Vs7","outputId":"b2e2b2b7-8fd5-4104-e6c9-3d1541aac46d"},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["import seaborn as sn\n","corr_matrix = AAPL_SMSG.corr()\n","sn.heatmap(corr_matrix, annot=True)\n","plt.show()\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":519},"executionInfo":{"elapsed":1288,"status":"ok","timestamp":1689366156938,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"SQOY7kKbJB3N","outputId":"d4a0231b-578e-4f36-c05f-3fc945fff690"},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["corr_matrix = AMZN_BABA.corr()\n","sn.heatmap(corr_matrix, annot=True)\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"KpDA1FxTvj7X"},"source":["## **Creating train, validation and test dataset**"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238},"executionInfo":{"elapsed":11,"status":"ok","timestamp":1689366156939,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"CRg1H9MnWYZ8","outputId":"a2b920f5-d03f-49e8-d931-2df0cf3a4b7a"},"outputs":[{"data":{"text/html":["\n","\n","  <div id=\"df-f5a54632-5931-4251-89f1-da8fb9f172e4\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","   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<td>9.625002</td>\n","      <td>3.663</td>\n","    </tr>\n","    <tr>\n","      <th>2020-08-05</th>\n","      <td>110.062500</td>\n","      <td>121776800</td>\n","      <td>43.813</td>\n","      <td>17739706</td>\n","      <td>11.523574</td>\n","      <td>3.641</td>\n","    </tr>\n","    <tr>\n","      <th>2020-08-06</th>\n","      <td>113.902496</td>\n","      <td>202428800</td>\n","      <td>44.660</td>\n","      <td>21625874</td>\n","      <td>13.482859</td>\n","      <td>3.608</td>\n","    </tr>\n","    <tr>\n","      <th>2020-08-07</th>\n","      <td>111.112503</td>\n","      <td>198045600</td>\n","      <td>44.275</td>\n","      <td>18751717</td>\n","      <td>15.020716</td>\n","      <td>3.399</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f5a54632-5931-4251-89f1-da8fb9f172e4')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              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\n","2020-08-06  113.902496    202428800      44.660     21625874  13.482859   \n","2020-08-07  111.112503    198045600      44.275     18751717  15.020716   \n","\n","            SMSG Ret  \n","Date                  \n","2020-08-03     3.553  \n","2020-08-04     3.663  \n","2020-08-05     3.641  \n","2020-08-06     3.608  \n","2020-08-07     3.399  "]},"execution_count":13,"metadata":{},"output_type":"execute_result"}],"source":["\n","window_size = 7\n","\n","AAPL_SMSG['AAPL Ret'] = AAPL_SMSG['AAPL Ret'].rolling(window=window_size).mean()\n","AAPL_SMSG['SMSG Ret'] = AAPL_SMSG['SMSG Ret'].rolling(window=window_size).mean()\n","AMZN_BABA['AMZN Ret'] = AMZN_BABA['AMZN Ret'].rolling(window=window_size).mean()\n","AMZN_BABA['BABA Ret'] = AMZN_BABA['BABA Ret'].rolling(window=window_size).mean()\n","\n","AAPL_SMSG = AAPL_SMSG.dropna()\n","AMZN_BABA = AMZN_BABA.dropna()\n","\n","AAPL_SMSG.head()\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"LaXerHb1OMjy"},"outputs":[],"source":["from sklearn.preprocessing import MinMaxScaler\n","\n","AAPL_SMSG_scaled = pd.DataFrame(index=AAPL_SMSG.index)\n","AMZN_BABA_scaled = pd.DataFrame(index=AMZN_BABA.index)\n","\n","############################## Close Price ##############################\n","AAPL_Close_scaler = MinMaxScaler()\n","AMZN_Close_scaler = MinMaxScaler()\n","\n","AAPL_close_prices = AAPL_SMSG['AAPL Close'].values.reshape(-1, 1)\n","AMZN_close_prices = AMZN_BABA['AMZN Close'].values.reshape(-1, 1)\n","\n","AAPL_Close_scaler.fit(AAPL_close_prices)\n","AMZN_Close_scaler.fit(AMZN_close_prices)\n","\n","AAPL_SMSG_scaled['AAPL Close'] = AAPL_Close_scaler.transform(AAPL_close_prices)\n","AMZN_BABA_scaled['AMZN Close'] = AMZN_Close_scaler.transform(AMZN_close_prices)\n","#########################################################################\n","\n","\n","##############################   Returns   ##############################\n","AAPL_Return_scaler = MinMaxScaler()\n","SMSG_Return_scaler = MinMaxScaler()\n","AMZN_Return_scaler = MinMaxScaler()\n","BABA_Return_scaler = MinMaxScaler()\n","\n","AAPL_return = AAPL_SMSG['AAPL Ret'].values.reshape(-1, 1)\n","SMSG_return = AAPL_SMSG['SMSG Ret'].values.reshape(-1, 1)\n","AMZN_return = AMZN_BABA['AMZN Ret'].values.reshape(-1, 1)\n","BABA_return = AMZN_BABA['BABA Ret'].values.reshape(-1, 1)\n","\n","AAPL_Return_scaler.fit(AAPL_return)\n","SMSG_Return_scaler.fit(SMSG_return)\n","AMZN_Return_scaler.fit(AMZN_return)\n","BABA_Return_scaler.fit(BABA_return)\n","\n","AAPL_SMSG_scaled['AAPL Ret'] = AAPL_Return_scaler.transform(AAPL_return)\n","AAPL_SMSG_scaled['SMSG Ret'] = SMSG_Return_scaler.transform(SMSG_return)\n","AMZN_BABA_scaled['AMZN Ret'] = AMZN_Return_scaler.transform(AMZN_return)\n","AMZN_BABA_scaled['BABA Ret'] = BABA_Return_scaler.transform(BABA_return)\n","#########################################################################"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":842},"executionInfo":{"elapsed":7813,"status":"ok","timestamp":1689366164745,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"n9w8ZV5dULAU","outputId":"d6741cbf-7afd-435e-f890-6ba21039bc5c"},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1200x800 with 3 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Get the column names except for the index column\n","columns = AAPL_SMSG_scaled.columns\n","\n","# Set the number of rows and columns for subplots\n","num_rows = (len(columns) - 1) // 2 + 1\n","num_cols = 2\n","\n","# Create subplots\n","fig, axs = plt.subplots(num_rows, num_cols, figsize=(12, 8))\n","fig.suptitle('Scaled Data: AAPL vs. SMSG')\n","\n","# Flatten the axs array if there is only one row or one column\n","if num_rows == 1 or num_cols == 1:\n","    axs = [axs]\n","\n","# Iterate over columns and plot each one\n","for i, column in enumerate(columns):\n","    row = i // num_cols\n","    col = i % num_cols\n","    if row < num_rows - 1:\n","        axs[row][col].set_xticklabels([])\n","    if col % 2 == 0:\n","      axs[row][col].plot(AAPL_SMSG_scaled.index, AAPL_SMSG_scaled[column], color='blue')\n","    else:\n","      axs[row][col].plot(AAPL_SMSG_scaled.index, AAPL_SMSG_scaled[column], color='red')\n","    axs[row][col].set_title(column)\n","\n","# Remove any unused subplots\n","if len(columns) < num_rows * num_cols:\n","    for j in range(len(columns), num_rows * num_cols):\n","        row = j // num_cols\n","        col = j % num_cols\n","        fig.delaxes(axs[row][col])\n","\n","fig.tight_layout()\n","\n","# Rotate x-axis labels for better visibility\n","for ax_row in axs:\n","    for ax in ax_row:\n","        ax.tick_params(axis='x', rotation=45)\n","\n","# Display the plot\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Wumq2YHkwD9L"},"outputs":[],"source":["def create_dataset(dataset, lookback, column):\n","    X_train = []\n","    Y_train = []\n","\n","    for i in range(lookback, len(dataset)):\n","        X_train.append(dataset.iloc[i-lookback:i, dataset.columns != 'Data'].values)\n","        Y_train.append(dataset[column].iloc[i])\n","\n","    return np.array(X_train), np.array(Y_train)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"kBwim0iOKoRK"},"outputs":[],"source":["# Split the data into training, validation, and testing sets\n","AAPL_SMSG_train_size = int(len(AAPL_SMSG_scaled) * 0.7)\n","AAPL_SMSG_val_size   = int(len(AAPL_SMSG) * 0.2)\n","AAPL_SMSG_train_data = AAPL_SMSG_scaled[:AAPL_SMSG_train_size]\n","AAPL_SMSG_val_data   = AAPL_SMSG_scaled[AAPL_SMSG_train_size:AAPL_SMSG_train_size + AAPL_SMSG_val_size]\n","AAPL_SMSG_test_data  = AAPL_SMSG_scaled[AAPL_SMSG_train_size + AAPL_SMSG_val_size:]\n","\n","AMZN_BABA_train_size = int(len(AMZN_BABA_scaled) * 0.7)\n","AMZN_BABA_val_size   = int(len(AMZN_BABA_scaled) * 0.2)\n","AMZN_BABA_train_data = AMZN_BABA_scaled[:AMZN_BABA_train_size]\n","AMZN_BABA_val_data   = AMZN_BABA_scaled[AMZN_BABA_train_size:AMZN_BABA_train_size + AMZN_BABA_val_size]\n","AMZN_BABA_test_data  = AMZN_BABA_scaled[AMZN_BABA_train_size + AMZN_BABA_val_size:]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ra5CRve1MsBq"},"outputs":[],"source":["AAPL_SMSG_X_train, AAPL_SMSG_Y_train = create_dataset(AAPL_SMSG_train_data, lookback=7, column='AAPL Ret')\n","AMZN_BABA_X_train, AMZN_BABA_Y_train = create_dataset(AMZN_BABA_train_data, lookback=7, column='AMZN Ret')\n","\n","AAPL_SMSG_X_val, AAPL_SMSG_Y_val = create_dataset(AAPL_SMSG_val_data, lookback=7, column='AAPL Ret')\n","AMZN_BABA_X_val, AMZN_BABA_Y_val = create_dataset(AMZN_BABA_val_data, lookback=7, column='AMZN Ret')\n","\n","AAPL_SMSG_X_test, AAPL_SMSG_Y_test = create_dataset(AAPL_SMSG_test_data, lookback=7, column='AAPL Ret')\n","AMZN_BABA_X_test, AMZN_BABA_Y_test = create_dataset(AMZN_BABA_test_data, lookback=7, column='AMZN Ret')"]},{"cell_type":"markdown","metadata":{"id":"lj2zKb46gkdy"},"source":["## **Training and evaluating the model**"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"M4wUvFdQgtQd"},"outputs":[],"source":["from keras.models import Sequential\n","from keras.layers import Dense\n","from keras.layers import SimpleRNN\n","from keras.layers import LSTM\n","from keras.layers import Dropout\n","from keras.utils import plot_model\n","from keras.optimizers import Adam\n","from keras.callbacks import EarlyStopping"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"lTm_xwq3gnoI"},"outputs":[],"source":["def smape(actual, predicted):\n","    numerator = tf.abs(actual - predicted)\n","    denominator = (tf.abs(actual) + tf.abs(predicted)) / 2.0\n","\n","    smape_score = tf.reduce_mean(numerator / denominator) * 100.0\n","\n","    return smape_score\n","\n","\n","def compile_and_fit(model,\n","                    X_train, Y_train,\n","                    X_val, Y_val,\n","                    file='LSTM_univariate_summary.png',\n","                    _patience=10, _min_delta=0.0001, _epochs=100, _batch_size=32, _early_stopping=False, _learning_rate=0.01, _verbose=1):\n","\n","  if _early_stopping:\n","    early_stopping = EarlyStopping(monitor='val_smape',\n","                                   patience=_patience,\n","                                   min_delta=_min_delta,\n","                                   mode='min')\n","\n","  _optimizer = Adam(learning_rate=_learning_rate)\n","\n","  model.compile(loss=tf.keras.losses.MeanSquaredError(),\n","                optimizer=_optimizer,\n","                metrics=[smape])\n","\n","  if _verbose != 0:\n","    model.summary()\n","    plot_model(model, to_file=file, show_shapes=True, show_layer_names=True)\n","\n","  if _early_stopping:\n","    history = model.fit(X_train, Y_train,\n","                        batch_size=_batch_size,\n","                        epochs=_epochs,\n","                        validation_data=(X_val, Y_val),\n","                        callbacks=[early_stopping],\n","                        verbose=_verbose)\n","  else:\n","    history = model.fit(X_train, Y_train,\n","                        batch_size=_batch_size,\n","                        epochs=_epochs,\n","                        validation_data=(X_val, Y_val),\n","                        verbose=_verbose)\n","  return history"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"gfqLpVU5gx65"},"outputs":[],"source":["lookback = 7\n","features = 3\n","\n","#################### AAPL ####################\n","AAPL_regressor = Sequential()\n","\n","AAPL_regressor.add(LSTM(units=8,\n","                   input_shape=(lookback, features)))\n","\n","AAPL_regressor.add(Dense(units=1))\n","##############################################\n","\n","#################### AMZN ####################\n","AMZN_regressor = Sequential()\n","\n","AMZN_regressor.add(LSTM(units=8,\n","                   input_shape=(lookback, features)))\n","\n","AMZN_regressor.add(Dense(units=1))\n","##############################################"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":46977,"status":"ok","timestamp":1689359336238,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"olxjj8tWhqHd","outputId":"0e2159c9-d380-4418-c0af-6472562d364a"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," lstm (LSTM)                 (None, 8)                 384       \n","                                                                 \n"," dense (Dense)               (None, 1)                 9         \n","                                                                 \n","=================================================================\n","Total params: 393\n","Trainable params: 393\n","Non-trainable params: 0\n","_________________________________________________________________\n","Epoch 1/100\n","15/15 [==============================] - 10s 97ms/step - loss: 0.0920 - smape: 60.3109 - val_loss: 0.0282 - val_smape: 33.7765\n","Epoch 2/100\n","15/15 [==============================] - 0s 21ms/step - loss: 0.0263 - smape: 31.5358 - val_loss: 0.0205 - val_smape: 30.0494\n","Epoch 3/100\n","15/15 [==============================] - 0s 16ms/step - loss: 0.0161 - smape: 25.3574 - val_loss: 0.0127 - val_smape: 23.9689\n","Epoch 4/100\n","15/15 [==============================] - 0s 14ms/step - loss: 0.0109 - smape: 22.0779 - val_loss: 0.0105 - val_smape: 24.4773\n","Epoch 5/100\n","15/15 [==============================] - 0s 12ms/step - loss: 0.0074 - smape: 18.5311 - val_loss: 0.0068 - val_smape: 18.6795\n","Epoch 6/100\n","15/15 [==============================] - 0s 19ms/step - loss: 0.0057 - smape: 16.7062 - val_loss: 0.0065 - val_smape: 17.2959\n","Epoch 7/100\n","15/15 [==============================] - 0s 14ms/step - loss: 0.0052 - smape: 16.2587 - val_loss: 0.0065 - val_smape: 17.1345\n","Epoch 8/100\n","15/15 [==============================] - 0s 15ms/step - loss: 0.0050 - smape: 15.8436 - val_loss: 0.0062 - val_smape: 16.4837\n","Epoch 9/100\n","15/15 [==============================] - 0s 15ms/step - loss: 0.0049 - smape: 15.9072 - val_loss: 0.0059 - val_smape: 16.6201\n","Epoch 10/100\n","15/15 [==============================] - 0s 20ms/step - loss: 0.0048 - smape: 15.6348 - val_loss: 0.0053 - val_smape: 15.5477\n","Epoch 11/100\n","15/15 [==============================] - 0s 15ms/step - loss: 0.0043 - smape: 14.7871 - val_loss: 0.0050 - val_smape: 14.6898\n","Epoch 12/100\n","15/15 [==============================] - 0s 16ms/step - loss: 0.0041 - smape: 14.7144 - val_loss: 0.0046 - val_smape: 14.0318\n","Epoch 13/100\n","15/15 [==============================] - 0s 25ms/step - loss: 0.0037 - smape: 14.1199 - val_loss: 0.0048 - val_smape: 15.3967\n","Epoch 14/100\n","15/15 [==============================] - 0s 16ms/step - loss: 0.0035 - smape: 13.6214 - val_loss: 0.0048 - val_smape: 15.4108\n","Epoch 15/100\n","15/15 [==============================] - 0s 19ms/step - loss: 0.0031 - smape: 13.1479 - val_loss: 0.0044 - val_smape: 14.8639\n","Epoch 16/100\n","15/15 [==============================] - 0s 16ms/step - loss: 0.0029 - smape: 12.5646 - val_loss: 0.0034 - val_smape: 12.6280\n","Epoch 17/100\n","15/15 [==============================] - 0s 17ms/step - loss: 0.0025 - smape: 12.0588 - val_loss: 0.0031 - val_smape: 12.1625\n","Epoch 18/100\n","15/15 [==============================] - 0s 24ms/step - loss: 0.0022 - smape: 11.4918 - val_loss: 0.0029 - val_smape: 12.2140\n","Epoch 19/100\n","15/15 [==============================] - 0s 18ms/step - loss: 0.0020 - smape: 10.8370 - val_loss: 0.0020 - val_smape: 9.2603\n","Epoch 20/100\n","15/15 [==============================] - 0s 12ms/step - loss: 0.0018 - smape: 10.5390 - val_loss: 0.0017 - val_smape: 8.9732\n","Epoch 21/100\n","15/15 [==============================] - 0s 16ms/step - loss: 0.0015 - smape: 9.5880 - val_loss: 0.0018 - val_smape: 10.0984\n","Epoch 22/100\n","15/15 [==============================] - 0s 17ms/step - loss: 0.0011 - smape: 8.7567 - val_loss: 0.0011 - val_smape: 6.8996\n","Epoch 23/100\n","15/15 [==============================] - 0s 19ms/step - loss: 0.0010 - smape: 8.2697 - val_loss: 0.0010 - val_smape: 6.9175\n","Epoch 24/100\n","15/15 [==============================] - 0s 21ms/step - loss: 9.2087e-04 - smape: 7.8225 - val_loss: 8.7676e-04 - val_smape: 6.5082\n","Epoch 25/100\n","15/15 [==============================] - 0s 18ms/step - loss: 8.6561e-04 - smape: 7.5886 - val_loss: 7.4333e-04 - val_smape: 5.7125\n","Epoch 26/100\n","15/15 [==============================] - 0s 12ms/step - loss: 7.7216e-04 - smape: 7.4913 - val_loss: 6.4193e-04 - val_smape: 5.5886\n","Epoch 27/100\n","15/15 [==============================] - 0s 16ms/step - loss: 8.1160e-04 - smape: 7.4764 - val_loss: 9.4108e-04 - val_smape: 6.8132\n","Epoch 28/100\n","15/15 [==============================] - 0s 13ms/step - loss: 6.6475e-04 - smape: 6.9049 - val_loss: 6.4450e-04 - val_smape: 5.4927\n","Epoch 29/100\n","15/15 [==============================] - 0s 19ms/step - loss: 6.2680e-04 - smape: 6.9090 - val_loss: 5.4840e-04 - val_smape: 4.8582\n","Epoch 30/100\n","15/15 [==============================] - 0s 16ms/step - loss: 6.1692e-04 - smape: 6.8193 - val_loss: 5.7024e-04 - val_smape: 5.0761\n","Epoch 31/100\n","15/15 [==============================] - 0s 11ms/step - loss: 6.7011e-04 - smape: 7.0011 - val_loss: 6.6463e-04 - val_smape: 5.5895\n","Epoch 32/100\n","15/15 [==============================] - 0s 10ms/step - loss: 7.4146e-04 - smape: 7.1022 - val_loss: 6.0937e-04 - val_smape: 5.2921\n","Epoch 33/100\n","15/15 [==============================] - 0s 11ms/step - loss: 6.9380e-04 - smape: 6.9808 - val_loss: 0.0010 - val_smape: 7.5238\n","Epoch 34/100\n","15/15 [==============================] - 0s 10ms/step - loss: 7.0254e-04 - smape: 6.9145 - val_loss: 6.1080e-04 - val_smape: 5.4840\n","Epoch 35/100\n","15/15 [==============================] - 0s 11ms/step - loss: 6.5240e-04 - smape: 6.8168 - val_loss: 7.4291e-04 - val_smape: 6.1132\n","Epoch 36/100\n","15/15 [==============================] - 0s 9ms/step - loss: 5.8919e-04 - smape: 6.6200 - val_loss: 6.4414e-04 - val_smape: 5.7469\n","Epoch 37/100\n","15/15 [==============================] - 0s 11ms/step - loss: 5.5917e-04 - smape: 6.5076 - val_loss: 6.3886e-04 - val_smape: 5.7072\n","Epoch 38/100\n","15/15 [==============================] - 0s 13ms/step - loss: 4.9092e-04 - smape: 6.1972 - val_loss: 4.3140e-04 - val_smape: 4.3544\n","Epoch 39/100\n","15/15 [==============================] - 0s 19ms/step - loss: 4.8711e-04 - smape: 6.2660 - val_loss: 4.2473e-04 - val_smape: 4.2730\n","Epoch 40/100\n","15/15 [==============================] - 0s 18ms/step - loss: 4.9418e-04 - smape: 6.2444 - val_loss: 5.3239e-04 - val_smape: 5.0057\n","Epoch 41/100\n","15/15 [==============================] - 0s 16ms/step - loss: 5.4946e-04 - smape: 6.2329 - val_loss: 4.6885e-04 - val_smape: 4.5933\n","Epoch 42/100\n","15/15 [==============================] - 0s 13ms/step - loss: 4.9072e-04 - smape: 6.1817 - val_loss: 4.1199e-04 - val_smape: 4.2558\n","Epoch 43/100\n","15/15 [==============================] - 0s 14ms/step - loss: 5.2242e-04 - smape: 6.4674 - val_loss: 5.8342e-04 - val_smape: 5.2431\n","Epoch 44/100\n","15/15 [==============================] - 0s 13ms/step - loss: 6.9257e-04 - smape: 6.9085 - val_loss: 6.4611e-04 - val_smape: 5.5068\n","Epoch 45/100\n","15/15 [==============================] - 0s 7ms/step - loss: 6.5086e-04 - smape: 6.6064 - val_loss: 5.6585e-04 - val_smape: 5.0762\n","Epoch 46/100\n","15/15 [==============================] - 0s 7ms/step - loss: 5.3752e-04 - smape: 6.3008 - val_loss: 6.0391e-04 - val_smape: 5.3420\n","Epoch 47/100\n","15/15 [==============================] - 0s 6ms/step - loss: 5.5022e-04 - smape: 6.1713 - val_loss: 4.1809e-04 - val_smape: 4.2655\n","Epoch 48/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.1844e-04 - smape: 5.8156 - val_loss: 3.8464e-04 - val_smape: 4.1214\n","Epoch 49/100\n","15/15 [==============================] - 0s 6ms/step - loss: 4.1010e-04 - smape: 5.6720 - val_loss: 3.7890e-04 - val_smape: 4.0541\n","Epoch 50/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.2024e-04 - smape: 5.7976 - val_loss: 6.3808e-04 - val_smape: 5.9700\n","Epoch 51/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.5639e-04 - smape: 5.8690 - val_loss: 5.0987e-04 - val_smape: 5.2286\n","Epoch 52/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.3140e-04 - smape: 5.6594 - val_loss: 3.7951e-04 - val_smape: 4.2794\n","Epoch 53/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.7922e-04 - smape: 5.4565 - val_loss: 4.5245e-04 - val_smape: 4.5254\n","Epoch 54/100\n","15/15 [==============================] - 0s 8ms/step - loss: 4.4259e-04 - smape: 5.6819 - val_loss: 4.0360e-04 - val_smape: 4.2570\n","Epoch 55/100\n","15/15 [==============================] - 0s 7ms/step - loss: 5.7973e-04 - smape: 6.3516 - val_loss: 4.2302e-04 - val_smape: 4.3943\n","Epoch 56/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.7101e-04 - smape: 5.9808 - val_loss: 6.3496e-04 - val_smape: 5.4716\n","Epoch 57/100\n","15/15 [==============================] - 0s 7ms/step - loss: 5.1032e-04 - smape: 6.2435 - val_loss: 5.2432e-04 - val_smape: 4.9365\n","Epoch 58/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.1357e-04 - smape: 5.7874 - val_loss: 4.5398e-04 - val_smape: 4.5585\n","Epoch 59/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.5831e-04 - smape: 5.8855 - val_loss: 3.8771e-04 - val_smape: 4.1283\n","Epoch 60/100\n","15/15 [==============================] - 0s 7ms/step - loss: 5.0172e-04 - smape: 6.0300 - val_loss: 3.4696e-04 - val_smape: 3.8919\n","Epoch 61/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.1925e-04 - smape: 5.5703 - val_loss: 3.6750e-04 - val_smape: 3.9803\n","Epoch 62/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.7826e-04 - smape: 5.4156 - val_loss: 3.7090e-04 - val_smape: 4.0401\n","Epoch 63/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.7145e-04 - smape: 5.3579 - val_loss: 3.3103e-04 - val_smape: 3.8444\n","Epoch 64/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.5309e-04 - smape: 5.3639 - val_loss: 3.4508e-04 - val_smape: 3.8707\n","Epoch 65/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.4393e-04 - smape: 5.3775 - val_loss: 3.4555e-04 - val_smape: 4.1845\n","Epoch 66/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.5558e-04 - smape: 5.4424 - val_loss: 3.8962e-04 - val_smape: 4.6246\n","Epoch 67/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.4905e-04 - smape: 5.4278 - val_loss: 3.3014e-04 - val_smape: 3.8197\n","Epoch 68/100\n","15/15 [==============================] - 0s 8ms/step - loss: 4.3171e-04 - smape: 5.6996 - val_loss: 3.9192e-04 - val_smape: 4.1872\n","Epoch 69/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.3112e-04 - smape: 5.1990 - val_loss: 3.4178e-04 - val_smape: 4.2643\n","Epoch 70/100\n","15/15 [==============================] - 0s 7ms/step - loss: 4.1862e-04 - smape: 5.5681 - val_loss: 7.8186e-04 - val_smape: 6.9615\n","Epoch 71/100\n","15/15 [==============================] - 0s 7ms/step - loss: 5.0390e-04 - smape: 6.1008 - val_loss: 4.8511e-04 - val_smape: 5.3677\n","Epoch 72/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.5632e-04 - smape: 5.3266 - val_loss: 3.8110e-04 - val_smape: 4.6004\n","Epoch 73/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.1896e-04 - smape: 5.1786 - val_loss: 3.1791e-04 - val_smape: 3.9818\n","Epoch 74/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.6799e-04 - smape: 5.5417 - val_loss: 3.0802e-04 - val_smape: 3.7681\n","Epoch 75/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.3868e-04 - smape: 5.3586 - val_loss: 3.1393e-04 - val_smape: 3.8319\n","Epoch 76/100\n","15/15 [==============================] - 0s 8ms/step - loss: 3.1557e-04 - smape: 5.1197 - val_loss: 3.0598e-04 - val_smape: 3.8390\n","Epoch 77/100\n","15/15 [==============================] - 0s 8ms/step - loss: 2.9873e-04 - smape: 5.1347 - val_loss: 3.0484e-04 - val_smape: 3.8638\n","Epoch 78/100\n","15/15 [==============================] - 0s 8ms/step - loss: 3.1058e-04 - smape: 5.2593 - val_loss: 3.0869e-04 - val_smape: 3.8857\n","Epoch 79/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.1048e-04 - smape: 5.1683 - val_loss: 3.2180e-04 - val_smape: 3.7866\n","Epoch 80/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.1232e-04 - smape: 5.1578 - val_loss: 3.0114e-04 - val_smape: 3.7126\n","Epoch 81/100\n","15/15 [==============================] - 0s 8ms/step - loss: 3.1766e-04 - smape: 5.1651 - val_loss: 3.1081e-04 - val_smape: 3.7550\n","Epoch 82/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.8658e-04 - smape: 5.0152 - val_loss: 3.2912e-04 - val_smape: 4.2127\n","Epoch 83/100\n","15/15 [==============================] - 0s 10ms/step - loss: 3.2900e-04 - smape: 4.9851 - val_loss: 4.7342e-04 - val_smape: 5.3153\n","Epoch 84/100\n","15/15 [==============================] - 0s 10ms/step - loss: 3.2048e-04 - smape: 5.0849 - val_loss: 2.9444e-04 - val_smape: 3.7648\n","Epoch 85/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.8088e-04 - smape: 4.8723 - val_loss: 2.9059e-04 - val_smape: 3.6924\n","Epoch 86/100\n","15/15 [==============================] - 0s 11ms/step - loss: 2.9083e-04 - smape: 4.8328 - val_loss: 2.9116e-04 - val_smape: 3.8382\n","Epoch 87/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.9893e-04 - smape: 5.2950 - val_loss: 3.1637e-04 - val_smape: 4.1634\n","Epoch 88/100\n","15/15 [==============================] - 0s 10ms/step - loss: 3.6131e-04 - smape: 5.0038 - val_loss: 3.1998e-04 - val_smape: 4.2515\n","Epoch 89/100\n","15/15 [==============================] - 0s 10ms/step - loss: 4.3571e-04 - smape: 5.7397 - val_loss: 5.5288e-04 - val_smape: 5.8471\n","Epoch 90/100\n","15/15 [==============================] - 0s 9ms/step - loss: 3.4089e-04 - smape: 5.1681 - val_loss: 2.9557e-04 - val_smape: 3.8473\n","Epoch 91/100\n","15/15 [==============================] - 0s 9ms/step - loss: 3.0845e-04 - smape: 5.1576 - val_loss: 4.1627e-04 - val_smape: 4.5742\n","Epoch 92/100\n","15/15 [==============================] - 0s 15ms/step - loss: 3.1716e-04 - smape: 5.0559 - val_loss: 2.9941e-04 - val_smape: 3.7484\n","Epoch 93/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.7108e-04 - smape: 4.9230 - val_loss: 2.7762e-04 - val_smape: 3.6940\n","Epoch 94/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.8418e-04 - smape: 4.9824 - val_loss: 2.9017e-04 - val_smape: 3.7020\n","Epoch 95/100\n","15/15 [==============================] - 0s 12ms/step - loss: 2.8497e-04 - smape: 5.0333 - val_loss: 3.3253e-04 - val_smape: 3.9255\n","Epoch 96/100\n","15/15 [==============================] - 0s 10ms/step - loss: 2.7258e-04 - smape: 4.8656 - val_loss: 3.2037e-04 - val_smape: 3.8836\n","Epoch 97/100\n","15/15 [==============================] - 0s 9ms/step - loss: 2.9055e-04 - smape: 5.3610 - val_loss: 2.7577e-04 - val_smape: 3.7273\n","Epoch 98/100\n","15/15 [==============================] - 0s 7ms/step - loss: 2.6836e-04 - smape: 4.9339 - val_loss: 4.1355e-04 - val_smape: 5.0416\n","Epoch 99/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.1728e-04 - smape: 5.4148 - val_loss: 2.7226e-04 - val_smape: 3.6521\n","Epoch 100/100\n","15/15 [==============================] - 0s 7ms/step - loss: 3.1146e-04 - smape: 5.0475 - val_loss: 2.8059e-04 - val_smape: 3.7632\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["history = compile_and_fit(AAPL_regressor, X_train=AAPL_SMSG_X_train, Y_train=AAPL_SMSG_Y_train, X_val=AAPL_SMSG_X_val, Y_val=AAPL_SMSG_Y_val, _batch_size=32)\n","\n","# Plot training loss and validation loss\n","plt.plot(history.history['loss'], label='Training Loss')\n","plt.plot(history.history['val_loss'], label='Validation Loss')\n","plt.title('Training and Validation Loss')\n","plt.xlabel('Epochs')\n","plt.ylabel('Loss')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":14,"status":"ok","timestamp":1689359336238,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"Puh1pbnqllit","outputId":"9a0290ac-72ab-47de-897a-96b7d6385245"},"outputs":[{"name":"stdout","output_type":"stream","text":["2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 9ms/step - loss: 1.4277e-04 - smape: 1.6387\n"]}],"source":["AAPL_predictions = AAPL_regressor.predict(AAPL_SMSG_X_test)\n","\n","# Evaluate the model on the test dataset\n","loss = AAPL_regressor.evaluate(AAPL_SMSG_X_test, AAPL_SMSG_Y_test, batch_size=32)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"elapsed":857,"status":"ok","timestamp":1689359337085,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"-r48jp5Alwqv","outputId":"fb35862e-ea1f-4c26-b7fd-9c2bc2d08eb0"},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Plotting AAPL close price predictions\n","plt.figure(figsize=(12, 6))\n","plt.plot(AAPL_SMSG.index[-len(AAPL_SMSG_Y_test):].values, AAPL_Return_scaler.inverse_transform(AAPL_SMSG_Y_test.reshape(-1, 1)), label='Actual', color='magenta')\n","plt.plot(AAPL_SMSG.index[-len(AAPL_SMSG_Y_test):].values, AAPL_Return_scaler.inverse_transform(AAPL_predictions.reshape(-1, 1)), label='Predicted', color='blue')\n","plt.title('AAPL - Returns', fontweight='bold')\n","plt.xlabel('Time', fontweight='bold')\n","plt.ylabel('ROI [T = ' + str(T) + ' days]', fontweight='bold')\n","plt.legend()\n","plt.grid(True)\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"elapsed":14890,"status":"ok","timestamp":1689359351967,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"Bc1hawFInpXE","outputId":"a268a666-a9a4-4ac6-d86a-ddb47148e17b"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential_1\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," lstm_1 (LSTM)               (None, 8)                 384       \n","                                                                 \n"," dense_1 (Dense)             (None, 1)                 9         \n","                                                                 \n","=================================================================\n","Total params: 393\n","Trainable params: 393\n","Non-trainable params: 0\n","_________________________________________________________________\n","Epoch 1/100\n","16/16 [==============================] - 2s 35ms/step - loss: 0.0407 - smape: 32.3821 - val_loss: 0.0656 - val_smape: 51.1961\n","Epoch 2/100\n","16/16 [==============================] - 0s 7ms/step - loss: 0.0132 - smape: 19.7610 - val_loss: 0.0204 - val_smape: 24.5122\n","Epoch 3/100\n","16/16 [==============================] - 0s 7ms/step - loss: 0.0087 - smape: 17.0217 - val_loss: 0.0052 - val_smape: 12.2246\n","Epoch 4/100\n","16/16 [==============================] - 0s 7ms/step - loss: 0.0053 - smape: 14.0865 - val_loss: 0.0039 - val_smape: 8.5679\n","Epoch 5/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0045 - smape: 12.6600 - val_loss: 0.0049 - val_smape: 10.6737\n","Epoch 6/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0043 - smape: 12.2169 - val_loss: 0.0051 - val_smape: 11.1805\n","Epoch 7/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0040 - smape: 12.1553 - val_loss: 0.0033 - val_smape: 8.0965\n","Epoch 8/100\n","16/16 [==============================] - 0s 12ms/step - loss: 0.0033 - smape: 11.1461 - val_loss: 0.0035 - val_smape: 8.7587\n","Epoch 9/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0030 - smape: 10.4988 - val_loss: 0.0031 - val_smape: 7.8898\n","Epoch 10/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0028 - smape: 10.1147 - val_loss: 0.0029 - val_smape: 7.9271\n","Epoch 11/100\n","16/16 [==============================] - 0s 8ms/step - loss: 0.0023 - smape: 9.5116 - val_loss: 0.0029 - val_smape: 8.1484\n","Epoch 12/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0021 - smape: 8.9277 - val_loss: 0.0027 - val_smape: 8.0432\n","Epoch 13/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0019 - smape: 8.8381 - val_loss: 0.0025 - val_smape: 7.6836\n","Epoch 14/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0018 - smape: 8.4052 - val_loss: 0.0024 - val_smape: 7.7104\n","Epoch 15/100\n","16/16 [==============================] - 0s 9ms/step - loss: 0.0015 - smape: 8.0292 - val_loss: 0.0022 - val_smape: 7.4856\n","Epoch 16/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0014 - smape: 7.5025 - val_loss: 0.0022 - val_smape: 7.7271\n","Epoch 17/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0012 - smape: 7.3936 - val_loss: 0.0021 - val_smape: 7.7606\n","Epoch 18/100\n","16/16 [==============================] - 0s 10ms/step - loss: 0.0011 - smape: 7.0140 - val_loss: 0.0024 - val_smape: 8.1826\n","Epoch 19/100\n","16/16 [==============================] - 0s 9ms/step - loss: 9.2208e-04 - smape: 6.3752 - val_loss: 0.0017 - val_smape: 6.9795\n","Epoch 20/100\n","16/16 [==============================] - 0s 9ms/step - loss: 7.3891e-04 - smape: 6.1158 - val_loss: 0.0019 - val_smape: 7.4554\n","Epoch 21/100\n","16/16 [==============================] - 0s 6ms/step - loss: 6.5490e-04 - smape: 5.5873 - val_loss: 0.0014 - val_smape: 6.5501\n","Epoch 22/100\n","16/16 [==============================] - 0s 6ms/step - loss: 7.9049e-04 - smape: 6.0510 - val_loss: 0.0025 - val_smape: 8.8213\n","Epoch 23/100\n","16/16 [==============================] - 0s 7ms/step - loss: 6.8642e-04 - smape: 5.8939 - val_loss: 0.0012 - val_smape: 6.2467\n","Epoch 24/100\n","16/16 [==============================] - 0s 7ms/step - loss: 6.0154e-04 - smape: 5.9450 - val_loss: 0.0012 - val_smape: 6.0640\n","Epoch 25/100\n","16/16 [==============================] - 0s 7ms/step - loss: 4.0031e-04 - smape: 4.6221 - val_loss: 0.0012 - val_smape: 6.2462\n","Epoch 26/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.8389e-04 - smape: 4.8308 - val_loss: 0.0015 - val_smape: 6.9088\n","Epoch 27/100\n","16/16 [==============================] - 0s 6ms/step - loss: 4.7675e-04 - smape: 5.1075 - val_loss: 0.0012 - val_smape: 6.0273\n","Epoch 28/100\n","16/16 [==============================] - 0s 8ms/step - loss: 4.2096e-04 - smape: 4.8193 - val_loss: 9.1614e-04 - val_smape: 5.4178\n","Epoch 29/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.8574e-04 - smape: 5.0055 - val_loss: 0.0011 - val_smape: 5.9866\n","Epoch 30/100\n","16/16 [==============================] - 0s 6ms/step - loss: 3.1983e-04 - smape: 4.5705 - val_loss: 0.0011 - val_smape: 5.8695\n","Epoch 31/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.3247e-04 - smape: 4.6073 - val_loss: 0.0014 - val_smape: 6.8301\n","Epoch 32/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.9574e-04 - smape: 4.2191 - val_loss: 0.0010 - val_smape: 5.8401\n","Epoch 33/100\n","16/16 [==============================] - 0s 6ms/step - loss: 3.2898e-04 - smape: 4.6090 - val_loss: 0.0015 - val_smape: 7.0819\n","Epoch 34/100\n","16/16 [==============================] - 0s 8ms/step - loss: 4.2585e-04 - smape: 4.9682 - val_loss: 0.0014 - val_smape: 6.8778\n","Epoch 35/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.9539e-04 - smape: 4.6193 - val_loss: 0.0010 - val_smape: 5.8471\n","Epoch 36/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.1947e-04 - smape: 4.5814 - val_loss: 7.7168e-04 - val_smape: 5.0166\n","Epoch 37/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.9879e-04 - smape: 5.0256 - val_loss: 9.8231e-04 - val_smape: 5.6735\n","Epoch 38/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.3267e-04 - smape: 4.5039 - val_loss: 0.0011 - val_smape: 5.9525\n","Epoch 39/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.2048e-04 - smape: 4.7180 - val_loss: 9.6448e-04 - val_smape: 5.6385\n","Epoch 40/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.5491e-04 - smape: 4.0851 - val_loss: 8.6928e-04 - val_smape: 5.3675\n","Epoch 41/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.0284e-04 - smape: 4.6931 - val_loss: 6.8137e-04 - val_smape: 4.6973\n","Epoch 42/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.9661e-04 - smape: 4.5851 - val_loss: 0.0011 - val_smape: 5.9622\n","Epoch 43/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.4587e-04 - smape: 4.2060 - val_loss: 0.0011 - val_smape: 5.9049\n","Epoch 44/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.5112e-04 - smape: 4.1837 - val_loss: 8.8636e-04 - val_smape: 5.4121\n","Epoch 45/100\n","16/16 [==============================] - 0s 8ms/step - loss: 3.0237e-04 - smape: 4.4143 - val_loss: 7.5546e-04 - val_smape: 5.0143\n","Epoch 46/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.8321e-04 - smape: 4.4705 - val_loss: 8.3649e-04 - val_smape: 5.2544\n","Epoch 47/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.4266e-04 - smape: 4.7093 - val_loss: 8.5497e-04 - val_smape: 5.3166\n","Epoch 48/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.3690e-04 - smape: 4.3344 - val_loss: 9.5892e-04 - val_smape: 5.6322\n","Epoch 49/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2929e-04 - smape: 4.5935 - val_loss: 7.8529e-04 - val_smape: 5.0942\n","Epoch 50/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.7847e-04 - smape: 4.0877 - val_loss: 8.6431e-04 - val_smape: 5.3503\n","Epoch 51/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.2111e-04 - smape: 4.1492 - val_loss: 0.0010 - val_smape: 5.9183\n","Epoch 52/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.6209e-04 - smape: 4.4653 - val_loss: 8.0901e-04 - val_smape: 5.1653\n","Epoch 53/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.4905e-04 - smape: 4.3896 - val_loss: 0.0012 - val_smape: 6.3423\n","Epoch 54/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.3595e-04 - smape: 4.0539 - val_loss: 0.0012 - val_smape: 6.4350\n","Epoch 55/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.7090e-04 - smape: 4.8408 - val_loss: 0.0012 - val_smape: 6.2886\n","Epoch 56/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.4741e-04 - smape: 4.7621 - val_loss: 7.6359e-04 - val_smape: 5.0054\n","Epoch 57/100\n","16/16 [==============================] - 0s 7ms/step - loss: 3.5874e-04 - smape: 4.5799 - val_loss: 7.1919e-04 - val_smape: 4.8563\n","Epoch 58/100\n","16/16 [==============================] - 0s 8ms/step - loss: 3.0959e-04 - smape: 4.2764 - val_loss: 5.2529e-04 - val_smape: 4.0264\n","Epoch 59/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.8541e-04 - smape: 4.0912 - val_loss: 8.1010e-04 - val_smape: 5.1651\n","Epoch 60/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.1532e-04 - smape: 4.0123 - val_loss: 7.0805e-04 - val_smape: 4.8019\n","Epoch 61/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.3478e-04 - smape: 3.9533 - val_loss: 6.7541e-04 - val_smape: 4.6842\n","Epoch 62/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2461e-04 - smape: 4.2408 - val_loss: 8.0465e-04 - val_smape: 5.1455\n","Epoch 63/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.0682e-04 - smape: 4.0336 - val_loss: 8.8061e-04 - val_smape: 5.4222\n","Epoch 64/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.0963e-04 - smape: 4.1709 - val_loss: 6.1844e-04 - val_smape: 4.5067\n","Epoch 65/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.6319e-04 - smape: 4.8087 - val_loss: 5.7849e-04 - val_smape: 4.3422\n","Epoch 66/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.7086e-04 - smape: 4.6324 - val_loss: 5.5901e-04 - val_smape: 4.2106\n","Epoch 67/100\n","16/16 [==============================] - 0s 8ms/step - loss: 2.1689e-04 - smape: 4.2070 - val_loss: 5.5556e-04 - val_smape: 4.2854\n","Epoch 68/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.6124e-04 - smape: 4.3562 - val_loss: 4.9176e-04 - val_smape: 3.9698\n","Epoch 69/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2412e-04 - smape: 4.2456 - val_loss: 7.4253e-04 - val_smape: 4.9438\n","Epoch 70/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2061e-04 - smape: 4.5543 - val_loss: 0.0011 - val_smape: 6.1210\n","Epoch 71/100\n","16/16 [==============================] - 0s 8ms/step - loss: 2.8254e-04 - smape: 4.0462 - val_loss: 0.0011 - val_smape: 6.0456\n","Epoch 72/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.1153e-04 - smape: 4.2745 - val_loss: 5.6307e-04 - val_smape: 4.2471\n","Epoch 73/100\n","16/16 [==============================] - 0s 8ms/step - loss: 1.9416e-04 - smape: 4.0209 - val_loss: 6.9035e-04 - val_smape: 4.7468\n","Epoch 74/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2950e-04 - smape: 4.0259 - val_loss: 6.2759e-04 - val_smape: 4.5045\n","Epoch 75/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2121e-04 - smape: 3.9611 - val_loss: 7.2065e-04 - val_smape: 4.8613\n","Epoch 76/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.1508e-04 - smape: 4.1306 - val_loss: 0.0011 - val_smape: 6.1040\n","Epoch 77/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.6104e-04 - smape: 4.3395 - val_loss: 5.7454e-04 - val_smape: 4.2793\n","Epoch 78/100\n","16/16 [==============================] - 0s 7ms/step - loss: 1.8659e-04 - smape: 4.0388 - val_loss: 6.9423e-04 - val_smape: 4.7822\n","Epoch 79/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.0123e-04 - smape: 3.8202 - val_loss: 0.0010 - val_smape: 5.8212\n","Epoch 80/100\n","16/16 [==============================] - 0s 8ms/step - loss: 2.0918e-04 - smape: 4.2166 - val_loss: 5.9603e-04 - val_smape: 4.3775\n","Epoch 81/100\n","16/16 [==============================] - 0s 7ms/step - loss: 1.9560e-04 - smape: 3.7852 - val_loss: 4.4676e-04 - val_smape: 3.7628\n","Epoch 82/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.3601e-04 - smape: 4.3176 - val_loss: 4.4220e-04 - val_smape: 3.7428\n","Epoch 83/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.7097e-04 - smape: 4.4421 - val_loss: 4.3354e-04 - val_smape: 3.7333\n","Epoch 84/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.1084e-04 - smape: 3.7594 - val_loss: 8.2300e-04 - val_smape: 5.2567\n","Epoch 85/100\n","16/16 [==============================] - 0s 6ms/step - loss: 1.8998e-04 - smape: 4.2066 - val_loss: 7.3674e-04 - val_smape: 4.9318\n","Epoch 86/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.0700e-04 - smape: 4.4409 - val_loss: 5.3696e-04 - val_smape: 4.1159\n","Epoch 87/100\n","16/16 [==============================] - 0s 7ms/step - loss: 1.8871e-04 - smape: 4.0215 - val_loss: 4.2686e-04 - val_smape: 3.6916\n","Epoch 88/100\n","16/16 [==============================] - 0s 8ms/step - loss: 2.1407e-04 - smape: 4.0678 - val_loss: 5.2144e-04 - val_smape: 4.0538\n","Epoch 89/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.0900e-04 - smape: 4.0830 - val_loss: 3.8584e-04 - val_smape: 3.4632\n","Epoch 90/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.4536e-04 - smape: 4.3494 - val_loss: 4.2060e-04 - val_smape: 3.5855\n","Epoch 91/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2712e-04 - smape: 4.3720 - val_loss: 4.0240e-04 - val_smape: 3.5471\n","Epoch 92/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.1609e-04 - smape: 3.7074 - val_loss: 4.2869e-04 - val_smape: 3.6564\n","Epoch 93/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.7698e-04 - smape: 4.1100 - val_loss: 4.9373e-04 - val_smape: 3.9129\n","Epoch 94/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.6160e-04 - smape: 4.4926 - val_loss: 4.8220e-04 - val_smape: 3.8679\n","Epoch 95/100\n","16/16 [==============================] - 0s 6ms/step - loss: 1.8065e-04 - smape: 3.8714 - val_loss: 5.1000e-04 - val_smape: 4.0047\n","Epoch 96/100\n","16/16 [==============================] - 0s 6ms/step - loss: 2.5723e-04 - smape: 4.2958 - val_loss: 3.8227e-04 - val_smape: 3.3852\n","Epoch 97/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.1707e-04 - smape: 3.7936 - val_loss: 4.1227e-04 - val_smape: 3.5387\n","Epoch 98/100\n","16/16 [==============================] - 0s 8ms/step - loss: 2.6085e-04 - smape: 4.4795 - val_loss: 3.8548e-04 - val_smape: 3.4014\n","Epoch 99/100\n","16/16 [==============================] - 0s 7ms/step - loss: 2.2337e-04 - smape: 4.0283 - val_loss: 4.6969e-04 - val_smape: 3.7930\n","Epoch 100/100\n","16/16 [==============================] - 0s 7ms/step - loss: 1.8190e-04 - smape: 4.1090 - val_loss: 6.7892e-04 - val_smape: 4.7190\n"]},{"data":{"image/png":"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\n","text/plain":["<Figure size 640x480 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["history = compile_and_fit(AMZN_regressor, X_train=AMZN_BABA_X_train, Y_train=AMZN_BABA_Y_train, X_val=AMZN_BABA_X_val, Y_val=AMZN_BABA_Y_val, _batch_size=32)\n","\n","# Plot training loss and validation loss\n","plt.plot(history.history['loss'], label='Training Loss')\n","plt.plot(history.history['val_loss'], label='Validation Loss')\n","plt.title('Training and Validation Loss')\n","plt.xlabel('Epochs')\n","plt.ylabel('Loss')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":585,"status":"ok","timestamp":1689359352530,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"3mZJSikony0F","outputId":"764c4866-ec7c-4fc6-cdf9-c74c8f3be223"},"outputs":[{"name":"stdout","output_type":"stream","text":["3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 6ms/step - loss: 2.7029e-04 - smape: 1.5959\n"]}],"source":["AMZN_predictions = AMZN_regressor.predict(AMZN_BABA_X_test)\n","\n","# Evaluate the model on the test dataset\n","loss = AMZN_regressor.evaluate(AMZN_BABA_X_test, AMZN_BABA_Y_test, batch_size=32)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"elapsed":760,"status":"ok","timestamp":1689359353288,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"202jV1FMn-dI","outputId":"b262b5e9-0af0-4335-d128-b1c0407d7aca"},"outputs":[{"data":{"image/png":"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\n","text/plain":["<Figure size 1200x600 with 1 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["# Plotting AAPL close price predictions\n","plt.figure(figsize=(12, 6))\n","plt.plot(AMZN_BABA.index[-len(AMZN_BABA_Y_test):].values, AMZN_Return_scaler.inverse_transform(AMZN_BABA_Y_test.reshape(-1, 1)), label='Actual', color='magenta')\n","plt.plot(AMZN_BABA.index[-len(AMZN_BABA_Y_test):].values, AMZN_Return_scaler.inverse_transform(AMZN_predictions.reshape(-1, 1)), label='Predicted', color='blue')\n","plt.title('AMZN - Returns', fontweight='bold')\n","plt.xlabel('Time', fontweight='bold')\n","plt.ylabel('ROI [T = ' + str(T) + ' days]', fontweight='bold')\n","plt.legend()\n","plt.grid(True)\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"76wXJ8omYIl4"},"source":["# **Hyperparameter Tuning**"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"38811x2WqroH"},"outputs":[],"source":["from sklearn.metrics import mean_squared_error\n","\n","def grid_search(ticker, X_train, Y_train, X_val, Y_val, _early_stopping=True, lookback=7, features=3):\n","  # Hyperparameter grid\n","  param_grid = {\n","      'units': [4, 8, 16, 32],\n","      'batch_size': [8, 16, 32],\n","      'epochs': [100, 250],\n","      'patience': [10, 25],\n","      'learning_rate': [0.01, 0.001]\n","  }\n","\n","  # Initialize variables for best hyperparameters and best performance\n","  best_score = float('inf')\n","  best_params = {}\n","\n","  # Iterate through the hyperparameter grid\n","  for _units in param_grid['units']:\n","      for _batch_size in param_grid['batch_size']:\n","          for _epochs in param_grid['epochs']:\n","              for _patience in param_grid['patience']:\n","                  for l_rate in param_grid['learning_rate']:\n","\n","                      # For reproducibility\n","                      np.random.seed(24)\n","                      tf.random.set_seed(24)\n","\n","                      # Build the RNN model\n","                      regressor = Sequential()\n","                      regressor.add(LSTM(units=_units,\n","                                              batch_input_shape=(_batch_size, lookback, features)))\n","                      regressor.add(Dense(units=1))\n","\n","                      # Compile and fit the model\n","                      history = compile_and_fit(model=regressor,\n","                                                X_train = X_train,\n","                                                Y_train = Y_train,\n","                                                X_val   = X_val,\n","                                                Y_val   = Y_val,\n","                                                _early_stopping = _early_stopping,\n","                                                _patience       = _patience,\n","                                                _min_delta      = 1e-5,\n","                                                _epochs         = _epochs,\n","                                                _batch_size     = _batch_size,\n","                                                _learning_rate  = l_rate,\n","                                                _verbose        = 0)\n","\n","                      # Get MSE of the validation set\n","                      mse = history.history['val_loss']\n","\n","                      # Check if current model's performance is better than the best so far\n","                      if mse < best_score:\n","                          best_score = mse\n","                          best_params = {'units': _units, 'batch_size': _batch_size, 'epochs': _epochs, 'patience': _patience, 'learning_rate': l_rate}\n","                          print(\"NEW Best\", best_params)\n","                          print('\\t\\tMSE: ', mse)\n","\n","  # Print the best hyperparameters and best MSE score\n","  print(str(ticker) + \" - Best Hyperparameters:\", best_params)\n","  print(str(ticker) + \" - Best MSE Score:\", best_score)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2404941,"status":"ok","timestamp":1689364372457,"user":{"displayName":"DANIEL DEIANA","userId":"13376148660549534283"},"user_tz":-120},"id":"mz0nipu0t3VO","outputId":"f005d63d-786b-4a78-dc22-32497a55ec6d"},"outputs":[{"name":"stdout","output_type":"stream","text":["2/2 [==============================] - 0s 7ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 100, 'patience': 10, 'learning_rate': 0.01}\n","\t\tMSE:  0.001127226897595704\n","2/2 [==============================] - 1s 11ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 100, 'patience': 10, 'learning_rate': 0.001}\n","\t\tMSE:  0.00014134123989668464\n","2/2 [==============================] - 0s 9ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 250, 'patience': 10, 'learning_rate': 0.01}\n","\t\tMSE:  0.0001136234001416129\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 250, 'patience': 25, 'learning_rate': 0.01}\n","\t\tMSE:  0.00010595538433958262\n","2/2 [==============================] - 0s 6ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 250, 'patience': 25, 'learning_rate': 0.001}\n","\t\tMSE:  9.695703551989921e-05\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 5ms/step\n","2/2 [==============================] - 0s 5ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 1s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 4ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 9ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 10ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","NEW Best {'units': 8, 'batch_size': 8, 'epochs': 250, 'patience': 25, 'learning_rate': 0.001}\n","\t\tMSE:  8.797830998581046e-05\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 9ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","NEW Best {'units': 16, 'batch_size': 8, 'epochs': 250, 'patience': 25, 'learning_rate': 0.001}\n","\t\tMSE:  8.760256806245646e-05\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 5ms/step\n","2/2 [==============================] - 0s 4ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 1s 9ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 1s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 4ms/step\n","2/2 [==============================] - 0s 6ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 8ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","2/2 [==============================] - 0s 7ms/step\n","AAPL - Best Hyperparameters: {'units': 16, 'batch_size': 8, 'epochs': 250, 'patience': 25, 'learning_rate': 0.001}\n","AAPL - Best MSE Score: 8.760256806245646e-05\n"]}],"source":["grid_search(ticker='AAPL',\n","            X_train = AAPL_SMSG_X_train,\n","            Y_train = AAPL_SMSG_Y_train,\n","            X_val   = AAPL_SMSG_X_val,\n","            Y_val   = AAPL_SMSG_Y_val,\n","            _early_stopping=True)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true,"base_uri":"https://localhost:8080/"},"id":"uEdCCLffvEJR","outputId":"2b569e86-15ba-434d-81de-c114056c36dc"},"outputs":[{"name":"stdout","output_type":"stream","text":["3/3 [==============================] - 1s 5ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 100, 'patience': 10, 'learning_rate': 0.01}\n","\t\tMSE:  0.0008658264711338457\n","3/3 [==============================] - 0s 5ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 100, 'patience': 10, 'learning_rate': 0.001}\n","\t\tMSE:  0.00027671250828296945\n","3/3 [==============================] - 0s 5ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 100, 'patience': 25, 'learning_rate': 0.01}\n","\t\tMSE:  9.925989341171778e-05\n","3/3 [==============================] - 1s 4ms/step\n"]},{"name":"stderr","output_type":"stream","text":["WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_predict_function.<locals>.predict_function at 0x7b7f17e62a70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"]},{"name":"stdout","output_type":"stream","text":["3/3 [==============================] - 0s 6ms/step\n","NEW Best {'units': 4, 'batch_size': 8, 'epochs': 250, 'patience': 10, 'learning_rate': 0.01}\n","\t\tMSE:  7.203463401030566e-05\n"]},{"name":"stderr","output_type":"stream","text":["WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_predict_function.<locals>.predict_function at 0x7b7f1d427c70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"]},{"name":"stdout","output_type":"stream","text":["3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 8ms/step\n","3/3 [==============================] - 2s 7ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 1s 5ms/step\n","NEW Best {'units': 4, 'batch_size': 32, 'epochs': 250, 'patience': 25, 'learning_rate': 0.01}\n","\t\tMSE:  7.105322083230115e-05\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 9ms/step\n","3/3 [==============================] - 0s 7ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 4ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 7ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 6ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 1s 6ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 1s 5ms/step\n","3/3 [==============================] - 0s 5ms/step\n","3/3 [==============================] - 0s 4ms/step\n","3/3 [==============================] - 0s 5ms/step\n","AMZN - Best Hyperparameters: {'units': 4, 'batch_size': 32, 'epochs': 250, 'patience': 25, 'learning_rate': 0.01}\n","AMZN - Best MSE Score: 7.105322083230115e-05\n"]}],"source":["grid_search(ticker='AMZN',\n","            X_train = AMZN_BABA_X_train,\n","            Y_train = AMZN_BABA_Y_train,\n","            X_val   = AMZN_BABA_X_val,\n","            Y_val   = AMZN_BABA_Y_val,\n","            _early_stopping=True)"]}],"metadata":{"accelerator":"GPU","colab":{"provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}