Stockpred.ipynb

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  "metadata": {
    "colab": {
      "name": "Stockpred.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "Z1B3ZSJhjjVs"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0iFgPgKquJsX",
        "outputId": "efd634c6-d01c-4ba3-da96-f781c6686af9"
      },
      "source": [
        "!pip install utils"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: utils in /usr/local/lib/python3.7/dist-packages (1.0.1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        },
        "id": "Z8Bk_g4ouO-p",
        "outputId": "1271507e-ebec-4668-f2a2-58bbd2ab50da"
      },
      "source": [
        "!pip install mxnet"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: mxnet in /usr/local/lib/python3.7/dist-packages (1.8.0.post0)\n",
            "Requirement already satisfied: numpy<2.0.0,>1.16.0 in /usr/local/lib/python3.7/dist-packages (from mxnet) (1.19.5)\n",
            "Requirement already satisfied: graphviz<0.9.0,>=0.8.1 in /usr/local/lib/python3.7/dist-packages (from mxnet) (0.8.4)\n",
            "Requirement already satisfied: requests<3,>=2.20.0 in /usr/local/lib/python3.7/dist-packages (from mxnet) (2.25.1)\n",
            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.20.0->mxnet) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.20.0->mxnet) (2021.5.30)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.20.0->mxnet) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.20.0->mxnet) (2.10)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1tFIlqoYuWh6"
      },
      "source": [
        "from utils import *\n",
        "\n",
        "import time\n",
        "import numpy as np\n",
        "\n",
        "from mxnet import nd, autograd, gluon\n",
        "from mxnet.gluon import nn, rnn\n",
        "import mxnet as mx\n",
        "import datetime\n",
        "import seaborn as sns\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "from sklearn.decomposition import PCA\n",
        "\n",
        "import math\n",
        "\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "import xgboost as xgb\n",
        "from sklearn.metrics import accuracy_score\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kxtlnmosucz0"
      },
      "source": [
        "context = mx.cpu(); model_ctx=mx.cpu()\n",
        "mx.random.seed(1719)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rT-Y9wllugEG"
      },
      "source": [
        "def parser(x):\n",
        "    return datetime.datetime.strptime(x,'%d-%m-%Y')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "828b26XrujJy"
      },
      "source": [
        "import pandas as pd\n",
        "dataset_ex_df = pd.read_csv('GS.csv', header=0, parse_dates=[0], date_parser=parser)\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LTZBOCtwupIr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "642091c4-cd9a-445c-891e-11e071a0814a"
      },
      "source": [
        "dataset_ex_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    }\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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MS</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2001-07-09</td>\n",
              "      <td>82.599998</td>\n",
              "      <td>82.900002</td>\n",
              "      <td>81.250000</td>\n",
              "      <td>81.910004</td>\n",
              "      <td>64.095253</td>\n",
              "      <td>2765400</td>\n",
              "      <td>43.990002</td>\n",
              "      <td>60.730000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2001-07-10</td>\n",
              "      <td>82.250000</td>\n",
              "      <td>82.849998</td>\n",
              "      <td>81.139999</td>\n",
              "      <td>81.599998</td>\n",
              "      <td>63.852703</td>\n",
              "      <td>2444600</td>\n",
              "      <td>42.009998</td>\n",
              "      <td>58.459999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2001-07-11</td>\n",
              "      <td>81.250000</td>\n",
              "      <td>81.949997</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>81.599998</td>\n",
              "      <td>63.852703</td>\n",
              "      <td>2863700</td>\n",
              "      <td>42.049999</td>\n",
              "      <td>57.820000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2001-07-12</td>\n",
              "      <td>83.500000</td>\n",
              "      <td>86.849998</td>\n",
              "      <td>83.080002</td>\n",
              "      <td>86.550003</td>\n",
              "      <td>67.726112</td>\n",
              "      <td>3151600</td>\n",
              "      <td>42.540001</td>\n",
              "      <td>61.820000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2001-07-13</td>\n",
              "      <td>86.000000</td>\n",
              "      <td>88.000000</td>\n",
              "      <td>85.620003</td>\n",
              "      <td>86.150002</td>\n",
              "      <td>67.413109</td>\n",
              "      <td>1880300</td>\n",
              "      <td>42.549999</td>\n",
              "      <td>61.419998</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Date       Open       High  ...   Volume        JPM         MS\n",
              "0 2001-07-09  82.599998  82.900002  ...  2765400  43.990002  60.730000\n",
              "1 2001-07-10  82.250000  82.849998  ...  2444600  42.009998  58.459999\n",
              "2 2001-07-11  81.250000  81.949997  ...  2863700  42.049999  57.820000\n",
              "3 2001-07-12  83.500000  86.849998  ...  3151600  42.540001  61.820000\n",
              "4 2001-07-13  86.000000  88.000000  ...  1880300  42.549999  61.419998\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "1Lrw6IqzxEmY",
        "outputId": "6d5f2da6-0e7c-4b50-ac5c-1f1e2996b96c"
      },
      "source": [
        "dataset_ex_df[['Date', 'Open']].head(3)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2001-07-09</td>\n",
              "      <td>82.599998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2001-07-10</td>\n",
              "      <td>82.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2001-07-11</td>\n",
              "      <td>81.250000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Date       Open\n",
              "0 2001-07-09  82.599998\n",
              "1 2001-07-10  82.250000\n",
              "2 2001-07-11  81.250000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I_vtbsXfyJIN",
        "outputId": "ab8ab6c0-e18d-499d-8d0a-de9607c6a7a3"
      },
      "source": [
        "print('There are {} days in the dataset.'.format(dataset_ex_df.shape[0]))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "There are 5030 days in the dataset.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 480
        },
        "id": "ERy0EdxryPEI",
        "outputId": "37e142c2-1a47-4045-aef0-802b8f310a8f"
      },
      "source": [
        "plt.figure(figsize=(10, 5), dpi=100)\n",
        "plt.plot(dataset_ex_df['Date'], dataset_ex_df['Open'], label='Goldman Sachs stock opening price')\n",
        "plt.vlines(datetime.date(2016,7,6), 0, 270, linestyles='--', colors='gray', label='Train/Test data cut-off')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('USD')\n",
        "plt.title('Goldman Sachs GS stock price')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hmlLPggBy9Sd",
        "outputId": "cae77ec4-e9f3-4fff-9d34-515b420b663c"
      },
      "source": [
        "dataset_ex_df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5030, 9)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6am88WkTzvie"
      },
      "source": [
        "num_training_days=dataset_ex_df.shape[0]*.8"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iJ8qOZfM0K8V"
      },
      "source": [
        "num_test_days=dataset_ex_df.shape[0]*.2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m9Y_U3FK45vX",
        "outputId": "e3b20b44-bc03-452b-bf51-c5a3d95849ac"
      },
      "source": [
        "print(num_training_days)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4024.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2kkI7bsM4_CQ",
        "outputId": "65b5457f-a361-43ea-f1f0-b0a06b31b687"
      },
      "source": [
        "print(num_test_days)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1006.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RzCiy1N2B1RM",
        "outputId": "be22e17f-36e1-4606-8c00-c6737f40d695"
      },
      "source": [
        "pip install universal-portfolios"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: universal-portfolios in /usr/local/lib/python3.7/dist-packages (0.4.3)\n",
            "Requirement already satisfied: cvxopt<2.0.0,>=1.2.5 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (1.2.6)\n",
            "Requirement already satisfied: matplotlib<4.0.0,>=3.3.1 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (3.4.2)\n",
            "Requirement already satisfied: scikit-learn<0.24.0,>=0.23.2 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (0.23.2)\n",
            "Requirement already satisfied: statsmodels<0.13.0,>=0.12.0 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (0.12.2)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.24.0 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (2.25.1)\n",
            "Requirement already satisfied: scipy<2.0.0,>=1.5.2 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (1.7.0)\n",
            "Requirement already satisfied: pandas-datareader<0.10.0,>=0.9.0 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (0.9.0)\n",
            "Requirement already satisfied: seaborn<0.11.0,>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (0.10.1)\n",
            "Requirement already satisfied: plotly<5.0.0,>=4.9.0 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (4.14.3)\n",
            "Requirement already satisfied: pandas<2.0.0,>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from universal-portfolios) (1.1.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (2.8.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (1.3.1)\n",
            "Requirement already satisfied: pyparsing>=2.2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (2.4.7)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (7.1.2)\n",
            "Requirement already satisfied: numpy>=1.16 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (1.19.5)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib<4.0.0,>=3.3.1->universal-portfolios) (0.10.0)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn<0.24.0,>=0.23.2->universal-portfolios) (2.2.0)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn<0.24.0,>=0.23.2->universal-portfolios) (1.0.1)\n",
            "Requirement already satisfied: patsy>=0.5 in /usr/local/lib/python3.7/dist-packages (from statsmodels<0.13.0,>=0.12.0->universal-portfolios) (0.5.1)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.24.0->universal-portfolios) (2.10)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.24.0->universal-portfolios) (1.24.3)\n",
            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.24.0->universal-portfolios) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0,>=2.24.0->universal-portfolios) (2021.5.30)\n",
            "Requirement already satisfied: lxml in /usr/local/lib/python3.7/dist-packages (from pandas-datareader<0.10.0,>=0.9.0->universal-portfolios) (4.2.6)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from plotly<5.0.0,>=4.9.0->universal-portfolios) (1.15.0)\n",
            "Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.7/dist-packages (from plotly<5.0.0,>=4.9.0->universal-portfolios) (1.3.3)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas<2.0.0,>=1.1.1->universal-portfolios) (2018.9)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PUjFmJ465D3i"
      },
      "source": [
        "def get_technical_indicators(dataset):\n",
        "    # Create 7 and 21 days Moving Average\n",
        "    dataset['ma7'] = dataset['price'].rolling(window=7).mean()\n",
        "    dataset['ma21'] = dataset['price'].rolling(window=21).mean()\n",
        "    \n",
        "    # Create MACD\n",
        "    dataset['26ema'] = dataset['price'].ewm(span=26).mean()\n",
        "    dataset['12ema'] = dataset['price'].ewm( span=12).mean()\n",
        "    dataset['MACD'] = (dataset['12ema']-dataset['26ema'])\n",
        "\n",
        "    # Create Bollinger Bands\n",
        "    dataset['20sd'] = dataset['price'].rolling(window=20).std()\n",
        "    dataset['upper_band'] = dataset['ma21'] + (dataset['20sd']*2)\n",
        "    dataset['lower_band'] = dataset['ma21'] - (dataset['20sd']*2)\n",
        "    \n",
        "    # Create Exponential moving average\n",
        "    dataset['ema'] = dataset['price'].ewm(com=0.5).mean()\n",
        "    \n",
        "    # Create Momentum\n",
        "    dataset['momentum'] = dataset['price']-1\n",
        "    \n",
        "    return dataset"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "7p2iDiQh5pWz",
        "outputId": "7aa04a01-3a76-4e21-a1b3-e7dfc37566cb"
      },
      "source": [
        "(dataset_ex_df[['Open']])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>2</th>\n",
              "      <td>81.250000</td>\n",
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              "      <td>83.500000</td>\n",
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              "      <th>4</th>\n",
              "      <td>86.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <th>5025</th>\n",
              "      <td>374.859985</td>\n",
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              "      <th>5026</th>\n",
              "      <td>370.899994</td>\n",
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              "    <tr>\n",
              "      <th>5029</th>\n",
              "      <td>373.230011</td>\n",
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              "  </tbody>\n",
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              "<p>5030 rows × 1 columns</p>\n",
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            "text/plain": [
              "            Open\n",
              "0      82.599998\n",
              "1      82.250000\n",
              "2      81.250000\n",
              "3      83.500000\n",
              "4      86.000000\n",
              "...          ...\n",
              "5025  374.859985\n",
              "5026  370.899994\n",
              "5027  380.700012\n",
              "5028  376.309998\n",
              "5029  373.230011\n",
              "\n",
              "[5030 rows x 1 columns]"
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          "execution_count": 19
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      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MIBjWNW55utM"
      },
      "source": [
        "dataset_ex_df.rename(columns = {'Open':'price'}, inplace = True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "wwqZjH6b81W0",
        "outputId": "93416309-9158-456e-f485-2376597c4d8b"
      },
      "source": [
        "(dataset_ex_df[['price']])"
      ],
      "execution_count": null,
      "outputs": [
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              "  </tbody>\n",
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              "<p>5030 rows × 1 columns</p>\n",
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            "text/plain": [
              "           price\n",
              "0      82.599998\n",
              "1      82.250000\n",
              "2      81.250000\n",
              "3      83.500000\n",
              "4      86.000000\n",
              "...          ...\n",
              "5025  374.859985\n",
              "5026  370.899994\n",
              "5027  380.700012\n",
              "5028  376.309998\n",
              "5029  373.230011\n",
              "\n",
              "[5030 rows x 1 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "WHrlmaVJD9Rq",
        "outputId": "7171f6d1-614a-4c54-9d05-60f76f734643"
      },
      "source": [
        "dataset_ex_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>price</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>JPM</th>\n",
              "      <th>MS</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2001-07-09</td>\n",
              "      <td>82.599998</td>\n",
              "      <td>82.900002</td>\n",
              "      <td>81.250000</td>\n",
              "      <td>81.910004</td>\n",
              "      <td>64.095253</td>\n",
              "      <td>2765400</td>\n",
              "      <td>43.990002</td>\n",
              "      <td>60.730000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2001-07-10</td>\n",
              "      <td>82.250000</td>\n",
              "      <td>82.849998</td>\n",
              "      <td>81.139999</td>\n",
              "      <td>81.599998</td>\n",
              "      <td>63.852703</td>\n",
              "      <td>2444600</td>\n",
              "      <td>42.009998</td>\n",
              "      <td>58.459999</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2001-07-11</td>\n",
              "      <td>81.250000</td>\n",
              "      <td>81.949997</td>\n",
              "      <td>80.000000</td>\n",
              "      <td>81.599998</td>\n",
              "      <td>63.852703</td>\n",
              "      <td>2863700</td>\n",
              "      <td>42.049999</td>\n",
              "      <td>57.820000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2001-07-12</td>\n",
              "      <td>83.500000</td>\n",
              "      <td>86.849998</td>\n",
              "      <td>83.080002</td>\n",
              "      <td>86.550003</td>\n",
              "      <td>67.726112</td>\n",
              "      <td>3151600</td>\n",
              "      <td>42.540001</td>\n",
              "      <td>61.820000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2001-07-13</td>\n",
              "      <td>86.000000</td>\n",
              "      <td>88.000000</td>\n",
              "      <td>85.620003</td>\n",
              "      <td>86.150002</td>\n",
              "      <td>67.413109</td>\n",
              "      <td>1880300</td>\n",
              "      <td>42.549999</td>\n",
              "      <td>61.419998</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Date      price       High  ...   Volume        JPM         MS\n",
              "0 2001-07-09  82.599998  82.900002  ...  2765400  43.990002  60.730000\n",
              "1 2001-07-10  82.250000  82.849998  ...  2444600  42.009998  58.459999\n",
              "2 2001-07-11  81.250000  81.949997  ...  2863700  42.049999  57.820000\n",
              "3 2001-07-12  83.500000  86.849998  ...  3151600  42.540001  61.820000\n",
              "4 2001-07-13  86.000000  88.000000  ...  1880300  42.549999  61.419998\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zd-NzK5Q84UN",
        "outputId": "c2c31965-b78c-48ee-d56c-3eed616b2879"
      },
      "source": [
        "dataset_TI_df = get_technical_indicators(dataset_ex_df[['price']])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  after removing the cwd from sys.path.\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  import sys\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:8: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if __name__ == '__main__':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  if sys.path[0] == '':\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:13: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  del sys.path[0]\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 707
        },
        "id": "ydVRuDsJ8_fx",
        "outputId": "38a7501e-c8bf-460e-c5e9-caae466ddfc5"
      },
      "source": [
        "dataset_TI_df.head(21)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th>12ema</th>\n",
              "      <th>MACD</th>\n",
              "      <th>20sd</th>\n",
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              "      <th>ema</th>\n",
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              "      <th>1</th>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.418268</td>\n",
              "      <td>82.410416</td>\n",
              "      <td>-0.007853</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.337499</td>\n",
              "      <td>81.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>81.250000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>81.998521</td>\n",
              "      <td>81.957505</td>\n",
              "      <td>-0.041016</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>81.584615</td>\n",
              "      <td>80.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>83.500000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.418269</td>\n",
              "      <td>82.444411</td>\n",
              "      <td>0.026142</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.877500</td>\n",
              "      <td>82.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>86.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.248887</td>\n",
              "      <td>83.410451</td>\n",
              "      <td>0.161564</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>84.967769</td>\n",
              "      <td>85.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>85.900002</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.779884</td>\n",
              "      <td>84.015543</td>\n",
              "      <td>0.235659</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>85.590111</td>\n",
              "      <td>84.900002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>82.900002</td>\n",
              "      <td>83.485715</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.623402</td>\n",
              "      <td>83.766614</td>\n",
              "      <td>0.143212</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.795885</td>\n",
              "      <td>81.900002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>83.849998</td>\n",
              "      <td>83.664286</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.659912</td>\n",
              "      <td>83.784015</td>\n",
              "      <td>0.124103</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.831966</td>\n",
              "      <td>82.849998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>85.000000</td>\n",
              "      <td>84.057143</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.858542</td>\n",
              "      <td>84.024580</td>\n",
              "      <td>0.166038</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>84.610695</td>\n",
              "      <td>84.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>82.849998</td>\n",
              "      <td>84.285714</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.719373</td>\n",
              "      <td>83.801997</td>\n",
              "      <td>0.082624</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.436877</td>\n",
              "      <td>81.849998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>83.750000</td>\n",
              "      <td>84.321429</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.723345</td>\n",
              "      <td>83.792483</td>\n",
              "      <td>0.069138</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.645627</td>\n",
              "      <td>82.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>81.300003</td>\n",
              "      <td>83.650000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.425600</td>\n",
              "      <td>83.349328</td>\n",
              "      <td>-0.076271</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.081875</td>\n",
              "      <td>80.300003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>81.949997</td>\n",
              "      <td>83.085714</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.252733</td>\n",
              "      <td>83.106351</td>\n",
              "      <td>-0.146382</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>81.993956</td>\n",
              "      <td>80.949997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>82.800003</td>\n",
              "      <td>83.071428</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.201886</td>\n",
              "      <td>83.054190</td>\n",
              "      <td>-0.147696</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.531321</td>\n",
              "      <td>81.800003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>84.519997</td>\n",
              "      <td>83.167143</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.344473</td>\n",
              "      <td>83.299738</td>\n",
              "      <td>-0.044736</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.857105</td>\n",
              "      <td>83.519997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>83.849998</td>\n",
              "      <td>83.002857</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.397355</td>\n",
              "      <td>83.390673</td>\n",
              "      <td>-0.006683</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.852367</td>\n",
              "      <td>82.849998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>82.449997</td>\n",
              "      <td>82.945714</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.301190</td>\n",
              "      <td>83.236972</td>\n",
              "      <td>-0.064218</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>82.917454</td>\n",
              "      <td>81.449997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>83.500000</td>\n",
              "      <td>82.909999</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.320832</td>\n",
              "      <td>83.279543</td>\n",
              "      <td>-0.041289</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.305818</td>\n",
              "      <td>82.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>85.949997</td>\n",
              "      <td>83.574284</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.574322</td>\n",
              "      <td>83.708320</td>\n",
              "      <td>0.133998</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>85.068604</td>\n",
              "      <td>84.949997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>86.099998</td>\n",
              "      <td>84.167141</td>\n",
              "      <td>NaN</td>\n",
              "      <td>83.812512</td>\n",
              "      <td>84.089773</td>\n",
              "      <td>0.277261</td>\n",
              "      <td>1.541790</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>85.756200</td>\n",
              "      <td>85.099998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>84.849998</td>\n",
              "      <td>84.459998</td>\n",
              "      <td>83.67238</td>\n",
              "      <td>83.908415</td>\n",
              "      <td>84.210342</td>\n",
              "      <td>0.301928</td>\n",
              "      <td>1.546028</td>\n",
              "      <td>86.764436</td>\n",
              "      <td>80.580324</td>\n",
              "      <td>85.152065</td>\n",
              "      <td>83.849998</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        price        ma7      ma21  ...  lower_band        ema   momentum\n",
              "0   82.599998        NaN       NaN  ...         NaN  82.599998  81.599998\n",
              "1   82.250000        NaN       NaN  ...         NaN  82.337499  81.250000\n",
              "2   81.250000        NaN       NaN  ...         NaN  81.584615  80.250000\n",
              "3   83.500000        NaN       NaN  ...         NaN  82.877500  82.500000\n",
              "4   86.000000        NaN       NaN  ...         NaN  84.967769  85.000000\n",
              "5   85.900002        NaN       NaN  ...         NaN  85.590111  84.900002\n",
              "6   82.900002  83.485715       NaN  ...         NaN  83.795885  81.900002\n",
              "7   83.849998  83.664286       NaN  ...         NaN  83.831966  82.849998\n",
              "8   85.000000  84.057143       NaN  ...         NaN  84.610695  84.000000\n",
              "9   82.849998  84.285714       NaN  ...         NaN  83.436877  81.849998\n",
              "10  83.750000  84.321429       NaN  ...         NaN  83.645627  82.750000\n",
              "11  81.300003  83.650000       NaN  ...         NaN  82.081875  80.300003\n",
              "12  81.949997  83.085714       NaN  ...         NaN  81.993956  80.949997\n",
              "13  82.800003  83.071428       NaN  ...         NaN  82.531321  81.800003\n",
              "14  84.519997  83.167143       NaN  ...         NaN  83.857105  83.519997\n",
              "15  83.849998  83.002857       NaN  ...         NaN  83.852367  82.849998\n",
              "16  82.449997  82.945714       NaN  ...         NaN  82.917454  81.449997\n",
              "17  83.500000  82.909999       NaN  ...         NaN  83.305818  82.500000\n",
              "18  85.949997  83.574284       NaN  ...         NaN  85.068604  84.949997\n",
              "19  86.099998  84.167141       NaN  ...         NaN  85.756200  85.099998\n",
              "20  84.849998  84.459998  83.67238  ...   80.580324  85.152065  83.849998\n",
              "\n",
              "[21 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JnCYWZ92Fg3b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "outputId": "254c5a5c-4faf-4fef-c7f6-269850300323"
      },
      "source": [
        "dataset_TI_df.tail(20)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>price</th>\n",
              "      <th>ma7</th>\n",
              "      <th>ma21</th>\n",
              "      <th>26ema</th>\n",
              "      <th>12ema</th>\n",
              "      <th>MACD</th>\n",
              "      <th>20sd</th>\n",
              "      <th>upper_band</th>\n",
              "      <th>lower_band</th>\n",
              "      <th>ema</th>\n",
              "      <th>momentum</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>5010</th>\n",
              "      <td>385.790009</td>\n",
              "      <td>383.392857</td>\n",
              "      <td>371.036191</td>\n",
              "      <td>368.697382</td>\n",
              "      <td>378.650828</td>\n",
              "      <td>9.953446</td>\n",
              "      <td>11.041158</td>\n",
              "      <td>393.118507</td>\n",
              "      <td>348.953875</td>\n",
              "      <td>387.530510</td>\n",
              "      <td>384.790009</td>\n",
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              "    <tr>\n",
              "      <th>5011</th>\n",
              "      <td>383.160004</td>\n",
              "      <td>384.987144</td>\n",
              "      <td>371.496191</td>\n",
              "      <td>369.768687</td>\n",
              "      <td>379.344547</td>\n",
              "      <td>9.575860</td>\n",
              "      <td>11.199832</td>\n",
              "      <td>393.895855</td>\n",
              "      <td>349.096527</td>\n",
              "      <td>384.616839</td>\n",
              "      <td>382.160004</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5012</th>\n",
              "      <td>389.640015</td>\n",
              "      <td>386.692858</td>\n",
              "      <td>372.764763</td>\n",
              "      <td>371.240637</td>\n",
              "      <td>380.928465</td>\n",
              "      <td>9.687828</td>\n",
              "      <td>11.661032</td>\n",
              "      <td>396.086827</td>\n",
              "      <td>349.442700</td>\n",
              "      <td>387.965623</td>\n",
              "      <td>388.640015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5013</th>\n",
              "      <td>375.700012</td>\n",
              "      <td>385.602862</td>\n",
              "      <td>373.366192</td>\n",
              "      <td>371.570961</td>\n",
              "      <td>380.124088</td>\n",
              "      <td>8.553126</td>\n",
              "      <td>10.673229</td>\n",
              "      <td>394.712649</td>\n",
              "      <td>352.019735</td>\n",
              "      <td>379.788549</td>\n",
              "      <td>374.700012</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5014</th>\n",
              "      <td>377.429993</td>\n",
              "      <td>384.914289</td>\n",
              "      <td>374.517620</td>\n",
              "      <td>372.004964</td>\n",
              "      <td>379.709612</td>\n",
              "      <td>7.704648</td>\n",
              "      <td>10.282379</td>\n",
              "      <td>395.082378</td>\n",
              "      <td>353.952863</td>\n",
              "      <td>378.216178</td>\n",
              "      <td>376.429993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5015</th>\n",
              "      <td>373.500000</td>\n",
              "      <td>382.602862</td>\n",
              "      <td>375.065239</td>\n",
              "      <td>372.115707</td>\n",
              "      <td>378.754287</td>\n",
              "      <td>6.638580</td>\n",
              "      <td>10.145424</td>\n",
              "      <td>395.356088</td>\n",
              "      <td>354.774391</td>\n",
              "      <td>375.072059</td>\n",
              "      <td>372.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5016</th>\n",
              "      <td>370.989990</td>\n",
              "      <td>379.458575</td>\n",
              "      <td>375.218096</td>\n",
              "      <td>372.032321</td>\n",
              "      <td>377.559780</td>\n",
              "      <td>5.527459</td>\n",
              "      <td>10.153989</td>\n",
              "      <td>395.526074</td>\n",
              "      <td>354.910119</td>\n",
              "      <td>372.350680</td>\n",
              "      <td>369.989990</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5017</th>\n",
              "      <td>373.519989</td>\n",
              "      <td>377.705715</td>\n",
              "      <td>375.320000</td>\n",
              "      <td>372.142518</td>\n",
              "      <td>376.938273</td>\n",
              "      <td>4.795755</td>\n",
              "      <td>9.503270</td>\n",
              "      <td>394.326541</td>\n",
              "      <td>356.313460</td>\n",
              "      <td>373.130219</td>\n",
              "      <td>372.519989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5018</th>\n",
              "      <td>356.519989</td>\n",
              "      <td>373.899998</td>\n",
              "      <td>375.154285</td>\n",
              "      <td>370.985294</td>\n",
              "      <td>373.796999</td>\n",
              "      <td>2.811705</td>\n",
              "      <td>9.749068</td>\n",
              "      <td>394.652421</td>\n",
              "      <td>355.656150</td>\n",
              "      <td>362.056732</td>\n",
              "      <td>355.519989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5019</th>\n",
              "      <td>352.890015</td>\n",
              "      <td>368.649998</td>\n",
              "      <td>374.864286</td>\n",
              "      <td>369.644903</td>\n",
              "      <td>370.580540</td>\n",
              "      <td>0.935637</td>\n",
              "      <td>10.575639</td>\n",
              "      <td>396.015564</td>\n",
              "      <td>353.713007</td>\n",
              "      <td>355.945587</td>\n",
              "      <td>351.890015</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5020</th>\n",
              "      <td>357.000000</td>\n",
              "      <td>365.978568</td>\n",
              "      <td>374.650476</td>\n",
              "      <td>368.708244</td>\n",
              "      <td>368.491226</td>\n",
              "      <td>-0.217018</td>\n",
              "      <td>11.229033</td>\n",
              "      <td>397.108542</td>\n",
              "      <td>352.192411</td>\n",
              "      <td>356.648529</td>\n",
              "      <td>356.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5021</th>\n",
              "      <td>358.790009</td>\n",
              "      <td>363.315713</td>\n",
              "      <td>374.244286</td>\n",
              "      <td>367.973559</td>\n",
              "      <td>366.998731</td>\n",
              "      <td>-0.974828</td>\n",
              "      <td>11.758051</td>\n",
              "      <td>397.760388</td>\n",
              "      <td>350.728184</td>\n",
              "      <td>358.076182</td>\n",
              "      <td>357.790009</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5022</th>\n",
              "      <td>363.000000</td>\n",
              "      <td>361.815713</td>\n",
              "      <td>373.915238</td>\n",
              "      <td>367.605148</td>\n",
              "      <td>366.383542</td>\n",
              "      <td>-1.221606</td>\n",
              "      <td>11.850888</td>\n",
              "      <td>397.617015</td>\n",
              "      <td>350.213461</td>\n",
              "      <td>361.358727</td>\n",
              "      <td>362.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5023</th>\n",
              "      <td>368.820007</td>\n",
              "      <td>361.505716</td>\n",
              "      <td>374.097143</td>\n",
              "      <td>367.695137</td>\n",
              "      <td>366.758382</td>\n",
              "      <td>-0.936755</td>\n",
              "      <td>11.897873</td>\n",
              "      <td>397.892889</td>\n",
              "      <td>350.301398</td>\n",
              "      <td>366.332914</td>\n",
              "      <td>367.820007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5024</th>\n",
              "      <td>367.799988</td>\n",
              "      <td>360.688573</td>\n",
              "      <td>373.929048</td>\n",
              "      <td>367.702904</td>\n",
              "      <td>366.918629</td>\n",
              "      <td>-0.784274</td>\n",
              "      <td>11.976214</td>\n",
              "      <td>397.881477</td>\n",
              "      <td>349.976619</td>\n",
              "      <td>367.310963</td>\n",
              "      <td>366.799988</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5025</th>\n",
              "      <td>374.859985</td>\n",
              "      <td>363.308572</td>\n",
              "      <td>374.065238</td>\n",
              "      <td>368.233058</td>\n",
              "      <td>368.140376</td>\n",
              "      <td>-0.092682</td>\n",
              "      <td>11.947155</td>\n",
              "      <td>397.959547</td>\n",
              "      <td>350.170929</td>\n",
              "      <td>372.343644</td>\n",
              "      <td>373.859985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5026</th>\n",
              "      <td>370.899994</td>\n",
              "      <td>365.881426</td>\n",
              "      <td>373.741428</td>\n",
              "      <td>368.430609</td>\n",
              "      <td>368.564933</td>\n",
              "      <td>0.134324</td>\n",
              "      <td>11.751585</td>\n",
              "      <td>397.244599</td>\n",
              "      <td>350.238257</td>\n",
              "      <td>371.381211</td>\n",
              "      <td>369.899994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5027</th>\n",
              "      <td>380.700012</td>\n",
              "      <td>369.267142</td>\n",
              "      <td>373.616191</td>\n",
              "      <td>369.339454</td>\n",
              "      <td>370.431868</td>\n",
              "      <td>1.092415</td>\n",
              "      <td>11.694162</td>\n",
              "      <td>397.004515</td>\n",
              "      <td>350.227866</td>\n",
              "      <td>377.593745</td>\n",
              "      <td>379.700012</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5028</th>\n",
              "      <td>376.309998</td>\n",
              "      <td>371.769998</td>\n",
              "      <td>373.333333</td>\n",
              "      <td>369.855790</td>\n",
              "      <td>371.336196</td>\n",
              "      <td>1.480406</td>\n",
              "      <td>11.066890</td>\n",
              "      <td>395.467113</td>\n",
              "      <td>351.199554</td>\n",
              "      <td>376.737914</td>\n",
              "      <td>375.309998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5029</th>\n",
              "      <td>373.230011</td>\n",
              "      <td>373.231428</td>\n",
              "      <td>372.550001</td>\n",
              "      <td>370.105732</td>\n",
              "      <td>371.627552</td>\n",
              "      <td>1.521820</td>\n",
              "      <td>9.969474</td>\n",
              "      <td>392.488949</td>\n",
              "      <td>352.611053</td>\n",
              "      <td>374.399312</td>\n",
              "      <td>372.230011</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           price         ma7        ma21  ...  lower_band         ema    momentum\n",
              "5010  385.790009  383.392857  371.036191  ...  348.953875  387.530510  384.790009\n",
              "5011  383.160004  384.987144  371.496191  ...  349.096527  384.616839  382.160004\n",
              "5012  389.640015  386.692858  372.764763  ...  349.442700  387.965623  388.640015\n",
              "5013  375.700012  385.602862  373.366192  ...  352.019735  379.788549  374.700012\n",
              "5014  377.429993  384.914289  374.517620  ...  353.952863  378.216178  376.429993\n",
              "5015  373.500000  382.602862  375.065239  ...  354.774391  375.072059  372.500000\n",
              "5016  370.989990  379.458575  375.218096  ...  354.910119  372.350680  369.989990\n",
              "5017  373.519989  377.705715  375.320000  ...  356.313460  373.130219  372.519989\n",
              "5018  356.519989  373.899998  375.154285  ...  355.656150  362.056732  355.519989\n",
              "5019  352.890015  368.649998  374.864286  ...  353.713007  355.945587  351.890015\n",
              "5020  357.000000  365.978568  374.650476  ...  352.192411  356.648529  356.000000\n",
              "5021  358.790009  363.315713  374.244286  ...  350.728184  358.076182  357.790009\n",
              "5022  363.000000  361.815713  373.915238  ...  350.213461  361.358727  362.000000\n",
              "5023  368.820007  361.505716  374.097143  ...  350.301398  366.332914  367.820007\n",
              "5024  367.799988  360.688573  373.929048  ...  349.976619  367.310963  366.799988\n",
              "5025  374.859985  363.308572  374.065238  ...  350.170929  372.343644  373.859985\n",
              "5026  370.899994  365.881426  373.741428  ...  350.238257  371.381211  369.899994\n",
              "5027  380.700012  369.267142  373.616191  ...  350.227866  377.593745  379.700012\n",
              "5028  376.309998  371.769998  373.333333  ...  351.199554  376.737914  375.309998\n",
              "5029  373.230011  373.231428  372.550001  ...  352.611053  374.399312  372.230011\n",
              "\n",
              "[20 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7BFoE5d1Ce83"
      },
      "source": [
        "dataset_TI_df=dataset_TI_df.drop(dataset_TI_df.index[range(19)],axis=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PvYGv1r3GJ2R"
      },
      "source": [
        "dataset_TI_df=dataset_TI_df.drop(labels=[19],axis=0)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "QssvvXpxcspg",
        "outputId": "51e8f7e0-610c-40cc-d6d1-267f178dfc04"
      },
      "source": [
        "dataset_TI_df.reset_index()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>price</th>\n",
              "      <th>ma7</th>\n",
              "      <th>ma21</th>\n",
              "      <th>26ema</th>\n",
              "      <th>12ema</th>\n",
              "      <th>MACD</th>\n",
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              "      <th>lower_band</th>\n",
              "      <th>ema</th>\n",
              "      <th>momentum</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20</td>\n",
              "      <td>84.849998</td>\n",
              "      <td>84.459998</td>\n",
              "      <td>83.672380</td>\n",
              "      <td>83.908415</td>\n",
              "      <td>84.210342</td>\n",
              "      <td>0.301928</td>\n",
              "      <td>1.546028</td>\n",
              "      <td>86.764436</td>\n",
              "      <td>80.580324</td>\n",
              "      <td>85.152065</td>\n",
              "      <td>83.849998</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>21</td>\n",
              "      <td>83.680000</td>\n",
              "      <td>84.339998</td>\n",
              "      <td>83.723809</td>\n",
              "      <td>83.887681</td>\n",
              "      <td>84.126629</td>\n",
              "      <td>0.238948</td>\n",
              "      <td>1.506742</td>\n",
              "      <td>86.737293</td>\n",
              "      <td>80.710325</td>\n",
              "      <td>84.170688</td>\n",
              "      <td>82.680000</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>22</td>\n",
              "      <td>82.900002</td>\n",
              "      <td>84.204285</td>\n",
              "      <td>83.754761</td>\n",
              "      <td>83.799502</td>\n",
              "      <td>83.933782</td>\n",
              "      <td>0.134280</td>\n",
              "      <td>1.401405</td>\n",
              "      <td>86.557571</td>\n",
              "      <td>80.951952</td>\n",
              "      <td>83.323564</td>\n",
              "      <td>81.900002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>23</td>\n",
              "      <td>80.599998</td>\n",
              "      <td>83.939999</td>\n",
              "      <td>83.723809</td>\n",
              "      <td>83.518129</td>\n",
              "      <td>83.411413</td>\n",
              "      <td>-0.106716</td>\n",
              "      <td>1.581277</td>\n",
              "      <td>86.886362</td>\n",
              "      <td>80.561256</td>\n",
              "      <td>81.507853</td>\n",
              "      <td>79.599998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>24</td>\n",
              "      <td>79.809998</td>\n",
              "      <td>83.412856</td>\n",
              "      <td>83.548095</td>\n",
              "      <td>83.196487</td>\n",
              "      <td>82.848709</td>\n",
              "      <td>-0.347778</td>\n",
              "      <td>1.714764</td>\n",
              "      <td>86.977622</td>\n",
              "      <td>80.118567</td>\n",
              "      <td>80.375950</td>\n",
              "      <td>78.809998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>5005</th>\n",
              "      <td>5025</td>\n",
              "      <td>374.859985</td>\n",
              "      <td>363.308572</td>\n",
              "      <td>374.065238</td>\n",
              "      <td>368.233058</td>\n",
              "      <td>368.140376</td>\n",
              "      <td>-0.092682</td>\n",
              "      <td>11.947155</td>\n",
              "      <td>397.959547</td>\n",
              "      <td>350.170929</td>\n",
              "      <td>372.343644</td>\n",
              "      <td>373.859985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5006</th>\n",
              "      <td>5026</td>\n",
              "      <td>370.899994</td>\n",
              "      <td>365.881426</td>\n",
              "      <td>373.741428</td>\n",
              "      <td>368.430609</td>\n",
              "      <td>368.564933</td>\n",
              "      <td>0.134324</td>\n",
              "      <td>11.751585</td>\n",
              "      <td>397.244599</td>\n",
              "      <td>350.238257</td>\n",
              "      <td>371.381211</td>\n",
              "      <td>369.899994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5007</th>\n",
              "      <td>5027</td>\n",
              "      <td>380.700012</td>\n",
              "      <td>369.267142</td>\n",
              "      <td>373.616191</td>\n",
              "      <td>369.339454</td>\n",
              "      <td>370.431868</td>\n",
              "      <td>1.092415</td>\n",
              "      <td>11.694162</td>\n",
              "      <td>397.004515</td>\n",
              "      <td>350.227866</td>\n",
              "      <td>377.593745</td>\n",
              "      <td>379.700012</td>\n",
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              "    <tr>\n",
              "      <th>5008</th>\n",
              "      <td>5028</td>\n",
              "      <td>376.309998</td>\n",
              "      <td>371.769998</td>\n",
              "      <td>373.333333</td>\n",
              "      <td>369.855790</td>\n",
              "      <td>371.336196</td>\n",
              "      <td>1.480406</td>\n",
              "      <td>11.066890</td>\n",
              "      <td>395.467113</td>\n",
              "      <td>351.199554</td>\n",
              "      <td>376.737914</td>\n",
              "      <td>375.309998</td>\n",
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              "    <tr>\n",
              "      <th>5009</th>\n",
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              "      <td>373.230011</td>\n",
              "      <td>373.231428</td>\n",
              "      <td>372.550001</td>\n",
              "      <td>370.105732</td>\n",
              "      <td>371.627552</td>\n",
              "      <td>1.521820</td>\n",
              "      <td>9.969474</td>\n",
              "      <td>392.488949</td>\n",
              "      <td>352.611053</td>\n",
              "      <td>374.399312</td>\n",
              "      <td>372.230011</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5010 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      index       price         ma7  ...  lower_band         ema    momentum\n",
              "0        20   84.849998   84.459998  ...   80.580324   85.152065   83.849998\n",
              "1        21   83.680000   84.339998  ...   80.710325   84.170688   82.680000\n",
              "2        22   82.900002   84.204285  ...   80.951952   83.323564   81.900002\n",
              "3        23   80.599998   83.939999  ...   80.561256   81.507853   79.599998\n",
              "4        24   79.809998   83.412856  ...   80.118567   80.375950   78.809998\n",
              "...     ...         ...         ...  ...         ...         ...         ...\n",
              "5005   5025  374.859985  363.308572  ...  350.170929  372.343644  373.859985\n",
              "5006   5026  370.899994  365.881426  ...  350.238257  371.381211  369.899994\n",
              "5007   5027  380.700012  369.267142  ...  350.227866  377.593745  379.700012\n",
              "5008   5028  376.309998  371.769998  ...  351.199554  376.737914  375.309998\n",
              "5009   5029  373.230011  373.231428  ...  352.611053  374.399312  372.230011\n",
              "\n",
              "[5010 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KdwLMV1Ti9gr"
      },
      "source": [
        "dataset_TI_df['log_momentum'] = np.log(dataset_TI_df['momentum'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "KvXegrrqjXw5",
        "outputId": "c99cf60c-cd0e-4e73-ecf6-537b8124a7bd"
      },
      "source": [
        "dataset_TI_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th>price</th>\n",
              "      <th>ma7</th>\n",
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              "      <th>lower_band</th>\n",
              "      <th>ema</th>\n",
              "      <th>momentum</th>\n",
              "      <th>log_momentum</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>84.849998</td>\n",
              "      <td>84.459998</td>\n",
              "      <td>83.672380</td>\n",
              "      <td>83.908415</td>\n",
              "      <td>84.210342</td>\n",
              "      <td>0.301928</td>\n",
              "      <td>1.546028</td>\n",
              "      <td>86.764436</td>\n",
              "      <td>80.580324</td>\n",
              "      <td>85.152065</td>\n",
              "      <td>83.849998</td>\n",
              "      <td>4.429029</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>83.680000</td>\n",
              "      <td>84.339998</td>\n",
              "      <td>83.723809</td>\n",
              "      <td>83.887681</td>\n",
              "      <td>84.126629</td>\n",
              "      <td>0.238948</td>\n",
              "      <td>1.506742</td>\n",
              "      <td>86.737293</td>\n",
              "      <td>80.710325</td>\n",
              "      <td>84.170688</td>\n",
              "      <td>82.680000</td>\n",
              "      <td>4.414978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>82.900002</td>\n",
              "      <td>84.204285</td>\n",
              "      <td>83.754761</td>\n",
              "      <td>83.799502</td>\n",
              "      <td>83.933782</td>\n",
              "      <td>0.134280</td>\n",
              "      <td>1.401405</td>\n",
              "      <td>86.557571</td>\n",
              "      <td>80.951952</td>\n",
              "      <td>83.323564</td>\n",
              "      <td>81.900002</td>\n",
              "      <td>4.405499</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>80.599998</td>\n",
              "      <td>83.939999</td>\n",
              "      <td>83.723809</td>\n",
              "      <td>83.518129</td>\n",
              "      <td>83.411413</td>\n",
              "      <td>-0.106716</td>\n",
              "      <td>1.581277</td>\n",
              "      <td>86.886362</td>\n",
              "      <td>80.561256</td>\n",
              "      <td>81.507853</td>\n",
              "      <td>79.599998</td>\n",
              "      <td>4.377014</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>79.809998</td>\n",
              "      <td>83.412856</td>\n",
              "      <td>83.548095</td>\n",
              "      <td>83.196487</td>\n",
              "      <td>82.848709</td>\n",
              "      <td>-0.347778</td>\n",
              "      <td>1.714764</td>\n",
              "      <td>86.977622</td>\n",
              "      <td>80.118567</td>\n",
              "      <td>80.375950</td>\n",
              "      <td>78.809998</td>\n",
              "      <td>4.367040</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        price        ma7       ma21  ...        ema   momentum  log_momentum\n",
              "20  84.849998  84.459998  83.672380  ...  85.152065  83.849998      4.429029\n",
              "21  83.680000  84.339998  83.723809  ...  84.170688  82.680000      4.414978\n",
              "22  82.900002  84.204285  83.754761  ...  83.323564  81.900002      4.405499\n",
              "23  80.599998  83.939999  83.723809  ...  81.507853  79.599998      4.377014\n",
              "24  79.809998  83.412856  83.548095  ...  80.375950  78.809998      4.367040\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aN2ZUZrdiUXy"
      },
      "source": [
        "def plot_technical_indicators(dataset, last_days):\n",
        "    plt.figure(figsize=(16, 10), dpi=100)\n",
        "    shape_0 = dataset.shape[0]\n",
        "    xmacd_ = shape_0-last_days\n",
        "    \n",
        "    dataset = dataset.iloc[-last_days:, :]\n",
        "    x_ = range(3, dataset.shape[0])\n",
        "    x_ =list(dataset.index)\n",
        "    \n",
        "    # Plot first subplot\n",
        "    plt.subplot(2, 1, 1)\n",
        "    plt.plot(dataset['ma7'],label='MA 7', color='g',linestyle='--')\n",
        "    plt.plot(dataset['price'],label='Closing Price', color='b')\n",
        "    plt.plot(dataset['ma21'],label='MA 21', color='r',linestyle='--')\n",
        "    plt.plot(dataset['upper_band'],label='Upper Band', color='c')\n",
        "    plt.plot(dataset['lower_band'],label='Lower Band', color='c')\n",
        "    plt.fill_between(x_, dataset['lower_band'], dataset['upper_band'], alpha=0.35)\n",
        "    plt.title('Technical indicators for Goldman Sachs - last {} days.'.format(last_days))\n",
        "    plt.ylabel('USD')\n",
        "    plt.legend()\n",
        "\n",
        "    # Plot second subplot\n",
        "    plt.subplot(2, 1, 2)\n",
        "    plt.title('MACD')\n",
        "    plt.plot(dataset['MACD'],label='MACD', linestyle='-.')\n",
        "    plt.hlines(15, xmacd_, shape_0, colors='g', linestyles='--')\n",
        "    plt.hlines(-15, xmacd_, shape_0, colors='g', linestyles='--')\n",
        "    plt.plot(dataset['log_momentum'],label='Momentum', color='b',linestyle='-')\n",
        "\n",
        "    plt.legend()\n",
        "    plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 740
        },
        "id": "UOSc1Z5vij3R",
        "outputId": "e527b3bb-8ef4-4dc8-9531-cdc499cb3ed9"
      },
      "source": [
        "plot_technical_indicators(dataset_TI_df, 600)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1600x1000 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z1B3ZSJhjjVs"
      },
      "source": [
        "# **Sentiment Analysis**\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "inuJeqf9imeo",
        "outputId": "0ed92bbd-4b41-4a1c-fcff-f927c0b5e98e"
      },
      "source": [
        "pip install bert"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting bert\n",
            "  Downloading https://files.pythonhosted.org/packages/e8/e6/55ed98ef52b168a38192da1aff7265c640f214009790220664ee3b4cb52a/bert-2.2.0.tar.gz\n",
            "Collecting erlastic\n",
            "  Downloading https://files.pythonhosted.org/packages/f3/30/f40d99fe35c38c2e0415b1e746c89569f2483e64ef65d054b9f0f382f234/erlastic-2.0.0.tar.gz\n",
            "Building wheels for collected packages: bert, erlastic\n",
            "  Building wheel for bert (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for bert: filename=bert-2.2.0-cp37-none-any.whl size=3767 sha256=370e5a928b473fa6c765929e855fb91fd61c7e01940ad48aa9e7e5492ac0ab8d\n",
            "  Stored in directory: /root/.cache/pip/wheels/fe/71/b7/941459453bd38e5d97a8c886361dee19325e9933c9cf88ad46\n",
            "  Building wheel for erlastic (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for erlastic: filename=erlastic-2.0.0-cp37-none-any.whl size=6795 sha256=c417fbc76d3220c2ab6213bd9f8ca0180915c92a8a24e342c6f84e19fcb20707\n",
            "  Stored in directory: /root/.cache/pip/wheels/02/62/46/93c713a5f061aeeb4f16eb6bf5ee798816e6ddda70faa78e69\n",
            "Successfully built bert erlastic\n",
            "Installing collected packages: erlastic, bert\n",
            "Successfully installed bert-2.2.0 erlastic-2.0.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7eIXKXcKjqbu"
      },
      "source": [
        "data_FT = dataset_ex_df[['Date', 'price']]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FdOqHo27kqxh"
      },
      "source": [
        "close_fft = np.fft.fft(np.asarray(data_FT['price'].tolist()))\n",
        "fft_df = pd.DataFrame({'fft':close_fft})\n",
        "fft_df['absolute'] = fft_df['fft'].apply(lambda x: np.abs(x))\n",
        "fft_df['angle'] = fft_df['fft'].apply(lambda x: np.angle(x))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 769
        },
        "id": "AV6UW_Gpk1Ou",
        "outputId": "d1fde3d0-a08c-466d-9f5a-b7a1565909d9"
      },
      "source": [
        "plt.figure(figsize=(14, 7), dpi=100)\n",
        "fft_list = np.asarray(fft_df['fft'].tolist())\n",
        "for num_ in [3, 6, 9, 100]:\n",
        "    fft_list_m10= np.copy(fft_list); fft_list_m10[num_:-num_]=0\n",
        "    plt.plot(np.fft.ifft(fft_list_m10), label='Fourier transform with {} components'.format(num_))\n",
        "plt.plot(data_FT['price'],  label='Real')\n",
        "plt.xlabel('Days')\n",
        "plt.ylabel('USD')\n",
        "plt.title('Figure 3: Goldman Sachs (close) stock prices & Fourier transforms')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n",
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n",
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n",
            "/usr/local/lib/python3.7/dist-packages/numpy/core/_asarray.py:83: ComplexWarning: Casting complex values to real discards the imaginary part\n",
            "  return array(a, dtype, copy=False, order=order)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1400x700 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ueiOKEGOlF3Z"
      },
      "source": [
        "ARIMA\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3_G0ndd0k8yZ",
        "outputId": "40d45fd7-eeb7-47ff-a978-a35e00772112"
      },
      "source": [
        "from statsmodels.tsa.arima_model import ARIMA\n",
        "from pandas import DataFrame\n",
        "from pandas import datetime\n",
        "\n",
        "series = data_FT['price']\n",
        "model = ARIMA(series, order=(5, 1, 0))\n",
        "model_fit = model.fit(disp=0)\n",
        "print(model_fit.summary())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:3: FutureWarning: The pandas.datetime class is deprecated and will be removed from pandas in a future version. Import from datetime module instead.\n",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n",
            "/usr/local/lib/python3.7/dist-packages/statsmodels/tsa/arima_model.py:472: FutureWarning: \n",
            "statsmodels.tsa.arima_model.ARMA and statsmodels.tsa.arima_model.ARIMA have\n",
            "been deprecated in favor of statsmodels.tsa.arima.model.ARIMA (note the .\n",
            "between arima and model) and\n",
            "statsmodels.tsa.SARIMAX. These will be removed after the 0.12 release.\n",
            "\n",
            "statsmodels.tsa.arima.model.ARIMA makes use of the statespace framework and\n",
            "is both well tested and maintained.\n",
            "\n",
            "To silence this warning and continue using ARMA and ARIMA until they are\n",
            "removed, use:\n",
            "\n",
            "import warnings\n",
            "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARMA',\n",
            "                        FutureWarning)\n",
            "warnings.filterwarnings('ignore', 'statsmodels.tsa.arima_model.ARIMA',\n",
            "                        FutureWarning)\n",
            "\n",
            "  warnings.warn(ARIMA_DEPRECATION_WARN, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "                             ARIMA Model Results                              \n",
            "==============================================================================\n",
            "Dep. Variable:                D.price   No. Observations:                 5029\n",
            "Model:                 ARIMA(5, 1, 0)   Log Likelihood              -13167.565\n",
            "Method:                       css-mle   S.D. of innovations              3.318\n",
            "Date:                Sat, 10 Jul 2021   AIC                          26349.130\n",
            "Time:                        13:00:50   BIC                          26394.791\n",
            "Sample:                             1   HQIC                         26365.129\n",
            "                                                                              \n",
            "=================================================================================\n",
            "                    coef    std err          z      P>|z|      [0.025      0.975]\n",
            "---------------------------------------------------------------------------------\n",
            "const             0.0579      0.043      1.344      0.179      -0.027       0.142\n",
            "ar.L1.D.price    -0.0758      0.014     -5.375      0.000      -0.103      -0.048\n",
            "ar.L2.D.price    -0.0114      0.014     -0.805      0.421      -0.039       0.016\n",
            "ar.L3.D.price     0.0062      0.014      0.439      0.661      -0.022       0.034\n",
            "ar.L4.D.price    -0.0173      0.014     -1.221      0.222      -0.045       0.010\n",
            "ar.L5.D.price     0.0117      0.014      0.827      0.408      -0.016       0.039\n",
            "                                    Roots                                    \n",
            "=============================================================================\n",
            "                  Real          Imaginary           Modulus         Frequency\n",
            "-----------------------------------------------------------------------------\n",
            "AR.1           -1.6661           -1.3595j            2.1504           -0.3911\n",
            "AR.2           -1.6661           +1.3595j            2.1504            0.3911\n",
            "AR.3            0.9579           -2.3404j            2.5288           -0.1882\n",
            "AR.4            0.9579           +2.3404j            2.5288            0.1882\n",
            "AR.5            2.8965           -0.0000j            2.8965           -0.0000\n",
            "-----------------------------------------------------------------------------\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1WvI-kMTlit2",
        "outputId": "1da08c5b-8f5e-4219-d903-7c2d0714faca"
      },
      "source": [
        "pip install pandas.tools"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[31mERROR: Could not find a version that satisfies the requirement pandas.tools (from versions: none)\u001b[0m\n",
            "\u001b[31mERROR: No matching distribution found for pandas.tools\u001b[0m\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "RJlFpd5wlX0n",
        "outputId": "24b39a4c-3107-4565-90b7-7a3ad0f71097"
      },
      "source": [
        "from pandas.plotting import autocorrelation_plot\n",
        "autocorrelation_plot(series)\n",
        "plt.figure(figsize=(10, 7), dpi=80)\n",
        "plt.show() "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/pandas/plotting/_matplotlib/misc.py:411: MatplotlibDeprecationWarning: Calling gca() with keyword arguments was deprecated in Matplotlib 3.4. Starting two minor releases later, gca() will take no keyword arguments. The gca() function should only be used to get the current axes, or if no axes exist, create new axes with default keyword arguments. To create a new axes with non-default arguments, use plt.axes() or plt.subplot().\n",
            "  ax = plt.gca(xlim=(1, n), ylim=(-1.0, 1.0))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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MBRZ4ziAiI4EXgMtVNcOjPE5EQp3hRGAcHvd62pKgwACemjaCyNAg7njtG44Xlfo7JGOMqabWZONcukJE7vVognyrx3ijqGoZcCfwCbAZmK+qG0XkURGpaMb8OBAJvCEi6SJSkYwGAqtEZC2wBPc9mzaZbAA6RIXx1NSR7M48wT3z0nG5rB82Y0zzUtdltHbOz5quy3jlr5mqfgh8WKXsIY/hC2pZbhkw1BsxtBbj+iTy0GWDeOi9jcxevoebxvX0d0jGGPOdWpONqr7gDC5S1S89pzmNBEwz86OzurN061H+/NEWzu6dSP+Odv/GGNM8NOThjGcaWGb8TET4y1XDiA4L4p55ayguK/d3SMYYA9R9z2asiPwcaF9xn8b5/A539zKmGUqMDOUvPxjGlsPHefzjrf4OxxhjgLrPbEJw35wPwn3fpuKTB1zl+9DM6Tp/YBLXn9WNWV/sZum2o/4Oxxhj6rxnsxRYKiKvVHR+aVqOBy8exMrd2dz7ejof3vM9kqLD/B2SMaYNa8g9mwLnfTYfisinFR+fR2YaJTwkkL9fN5KCknLunruGcmsObYzxo4Ykm9eALUBP4BFgD+4HMk0z16dDFH+4Yghf7c7imU/ttdTGGP9pSLJJUNUXgVJVXaqqN2MvTmsxfjAqmStHduHpxdv5eneWv8MxxrRRDUk2Ff2fHBKRS5wuZOJ9GJPxst9fMYRu8RHcM28NOQUl/g7H1ODo8WJ+++4GrvrHMh55f2Otrw83pqVqSLL5g9MJ58+BXwCzgJ/5NCrjVZGhQTwz7Qwy84v59Tvrqe+1Ei1VQUkZGw7kklvQsvqHW/NtNpc98wWvr9yHS5VXV+zlwr99xso9diZqWo+GvBb6A2cwF/DZK6KNbw1NjuHeif35y8dbiC0NaVW/SFVl1ue7eXrxdo4XlxEYINx1Xh/uPq9vs35tdrlLeXrxdp5dsoPOsWG8c8fZDO4cw86j+fx49ipufOlrXr9tbKNetmdMc1FrshGRZ6ijDzRVvdsnERmfuW18L9Z8m83cTUe4eHsm5/RN9HdIjeZyKX/8cDMvfrGb8wZ04IqRXVi8+Qh/W7SdDQfyePLa4Q165bY//G7BRv61Yi9TRnbh4csGExPhjrN3+0jmzjiLKc8t46ZXVvLuHePoEhvu52iNaZy6LqOtAlbX8TEtTECA8OS1I+gcKdw59xv2ZRX4O6RGKSgp42fz03nxi93ceHYPZt2QwuXDO/O3a0fwu8sGsWRrBj/4xzIy84vrX1kTe2PVPv61Yi8zxvfir9cM/y7RVEiKDuOVm0ZTWFLOT177xroeMi1erclGVWd7foA3qoybFqhdaBB3jwzD5VJm/Gs1hSUt849Y9okSpv3zKxasPcgvL+rPw5cN+u6SmYhw47iezLl5DN9mFXDdP7/iWDNKOPuyCnjovY2c3TuBX13UH5GaL/X1TYri/64extp9OfzxP5ubOEpjvKveBgJOH2mbcD9rg4gMF5HnfB6Z8ZmkdgE8NW0kWw7ncd9b61pcg4HDuUVc88JyNh/K44XrR3HHhD41/sEe1yeRl6aPZs+xE1w36yuyTvi/JZ6q8ut31hMg8H9XDycosO6v4KQhnbj1nJ7MWb6XuV9/20RRGuN9DWmN9jfgIuAYgPOWzvE+jMk0gQn9O/Dzif1YsPYgH2847O9wGmxP5gmuen4Zh3KLmH3TGC4c3LHO+c/uk8iL00ezO/MEP/znCg7lFjZRpDV7Y9V+Pt+eyX3fH0DnBt6Hue/7Azi3X3t+/c56nlq0nbJyl4+jNMb76m2NBqCq+6r859gir70cO3aMV1555aSywYMHM3r0aEpLS3nttdeqLTNixAhGjBhBQUEB8+fPrzY9JSWFIUOGkJubyzvvvFNt+tixY+nfvz+ZmZl88MEH1aaPHz+eXr16cfjwYT7++ONq088//3y6du3Kvn37WLx4cbXpkyZNomPHjuzatYvPPvus2vRLL72UxMREtm7dyvLlywHIyclhz549hCv0SuzOYx9voaMrk7Vrqt+Ku+aaa4iIiCA9PZ309PRq06+77jqCg4NZuXIlGzdurDb9xhtvBGDZsmVs27btpGnBwcFcd911ACxdupTdu3efND0iIoJrrrkGgEWLFrFwcwYLDkWBwPXJuRxauxR6TwHg448/5vDhk5NmQkICl112Gef0TeTH/cuYuTmXCx9fyA+Tc+kUVk7Hjh0JC3P3Gff222+Tl5d30vLJyclccIH7/X3z58+noODke1w9e/bk3HPPBeC1116jtPTkJtf9+vXj7LPPBuCVV14hrzSAv++Oo3t4GWVb0lgZ1LBjr7S4iHPYRHZUFE8u2sarn23i/PYnmHbuUIYPG+qVYy89PZ09e/acNN0Xx56nK6+8kpiYGDZs2MCqVauqTffXsZeTk0NGRsZJx97+/ftPWj46OpopU+o/9gDef/99jh07dtL0jh07MmnSJKBpjr2qGvp3r7S0tMblT4fUdwlFRN4EngCeBc4E7gFSVHWqVyJoQsnJyXrnnXeeVNauXTuioqJQVY4cOVJtmcjISCIjI3G5XGRkZFSbHhUVRbt27SgrKyMzM7Pa9OjoaCIiIigtLa12wAHExsYSFhZGSUkJWVnVn6uIi4sjNDSU4uJisrOzq02Pj48nJCSEoqIicnJyqk1PSEggODiYgoKC7w7osrIygoLc/2fkhndh7qF4JsRm0Z8D1Zbv0KEDAQEB5Ofnk5+fX216UlISIsLx48c5ceJEtekdO7rPPPLy8qp9YUSEpKQkwP0FLyo6+UHGwMBAYhLaszU/lFWZgewtaUdiYCEXRHxLbGAJQUFBJCa6W9RlZWVRUnLyZbLg4GASEhIA9z8ah4sC+TC/OyUayPcj99IjopSAgABiY2PJzMykrKzspOVDQ0OJi4sD4OjRo5SXn/w/VlhYGLGxsQAcOXKk2uXIiIgIoqOjATh06DAfn+jOgbJIroraTmxgySkfe6qwuzSaFUUdyXOFEhtUyiUdT9AzrLDRx15GRsZ3x0QFXxx7nhITEwkKCuLEiRMcP3682nR/HXtlZWWEhobSvn17ALKzsykuPvme36kee1WTQUhICPHx7mfjfX3sVU2E0PC/exX7/sADD6xW1ZRqM56ChiSbROAp4AJAgP8C96hq9aP3VDcuMslZdyAwS1UfqzI9FJgDjMJ9Ge9aVd3jTHsAuAX3WdbdqvpJfdvr2bOnPvzww40Nu8XLycn57kAF+Ne+GA4UBnFP7yzCA5vH/ZsTZcKio+3YkBdGqQpRQeWMiSvk7PhCAhvx6ExuaQD/2hdDTmkgU7vkklh29KS68JV1uaG8fSiaCzvkc3Z84y7llStsPh5KWmYEmSVBDIsu4pKkfEIb8bureky0ZVYXlSrq4qabbmp0skFVa/3gTgKv1TXP6X6cde8EeuF+d85aYFCVeX4CPO8MTwVed4YHOfOH4u4gdCcQWN82R40apUZ1yZIlJ42v35+j3e/7QJ9bssM/AXlwuVz69jf7dMQjn2ifX/9H739rnS7fmanl5S6vbSPzeJF+/2+fad9ff6h/m7/Qa+utzdHjRTrikU908rNfaJkX96OotEz/+t+t2vP+DzT18SW6em+Wulynt/6qx0RbZnVRqaIugFXayL/5DTmz+QI4T1W92pRHRMYCv1PVi5zxBwBU9c8e83zizLNcRIKAw0B74H7PeT3nq2ubUVFROmrUKG/uRotU039uhwdcTWlEIslrXkC0aW5AVxx5FScqZSHRHOs1kcLYXoQeP0jCro8JKWz0CXSNygNDOTLwGkrCE+iw7V0icvf4ZDsKHO03mYLYXnReP8cn+1MUlczRvpdSHhJFUFEOIQUZBBccI/LoeoKLcxu0DvtvvpLVRaXsvBMUj5nO1hfuavSZTUMaCOwCvhSRBcB3F0ZV9YnGbBjoAuzzGN+P+55QjfOoapmI5AIJTvmKKst2qWkjIjIDmAHu66g1XVtua8rLy6vVQ+COpRSlTOdoWDIhh9b5dPuukHYU9xpPSafhaGgUlBYSUHwcV3gcqIvwTe8T8u1XFKD48rHTsK9mUZZyMxn9pxC++QNC933t9W0Udx9LYXw/wrZ8RMGhnb7Zn5wc2h3aQWmnoZQm9qMoIoGCzr3J7TiKsB2LCd3zJVJ7ZyBAzcdEW2V1Uamwz0RKYnt6ZV0NSTY7nU8A7tdCtyiqOhOYCZCSkqI1tXppa9LS0khNTT2pzOVSLnhiKVGXzODdO8bV+qBhY207cpzrZn1FwYkSvj84iT7tI8krKuNwbhHR4UHcc0E/usRO8cm2a/LhwiW8sb8dSwImk3LFLXSMDqOozEWAwBnd4hjbO4G+HSJPqT5Ulf3Zhbyxej9PL97OxEFJvPCnZ5q0n7aDOYU89N4GFgV9n4nX3sJfrx5OSFDtTzrUdEy0VVYXbpsO5nHpM59zzahkHvfC+upMNiISCPRT1eu8sK2qDgBdPcaTnbKa5tnvXEaLwd1QoCHLVlNT0+e2qKLpc1UDAsP4cH8Uf3j+NbqGl1VfsJFOlAmz9sZR6oIfd8slqTQDDrrfV9EDIB8WvrvG69utS05ODt+LiUUTI1i7p5y1CkGilKrwXvpBAGKDyxkQWczQ6GK61FIvmcWBfJ0TxoHCYI6VBFLkcv9hHxZdxJllG5gzZ0OT7VOFcQraPpz31x5ky47dXNslj9ryTW3HRFtkdQEuhVl7YwkToUduulfWWWeyUdVyEekuIiHevmeD+22ffUWkJ+5EMRX4YZV5FgDTgeXAVcCnqqrOJb1/i8gTQGegL1DvNZDS0tJqzQArmgDW1rS5oglgeXk5R48erTa9sU2fY2JiCA8Pr7Xpc0Xz1Nqal1Y0Py0sLCQ3t/r1+dqaPlc09fRsftqpKIMQBpB2UJjYzl1P7du3JzAwsNbmpxXNU+trfpqVk8sbRzuSVy5cHrkLzSnkSAOaPvu6+WlAQAABAkP4lgHtKhOJKhQHt+NYUHu2HA/h6+wwVmRHkBBYSHJQPgEoocGBhISGcagoiO0nQghESQoqoFdQMfGBRfRsV07vRPeDm3U1P/Xlsfe9BAjWMj7OjOXtPQGMjzj43XTPYy8/P79a/fvi2PNUX9Nnbx17ubm5FBae3AKwvqbPpaWlLbrpc3h4ODEx7t7CT+fY26qdOVgUzKTog+Qd9c59Rr/ds3HuwdwJfIK7ZdpLqrpRRB7F3fJhAfAi8C8R2QFk4U5IOPPNBzYBZcAdqlrvg6bBwcHfHYAV2upDnRUHatUH60YFFrMiK4bwhHJigl1eebBOVbnxuUUcKi9hSqc8hsXEADGn/FCnLx6sCwsLIzU1td4H62b/ez5fHXGRnhvGuqJEBHAVC3ICeiS0Y3zEMcbE5BMZVPGlD/Hag3WNPfYuzczk+EtL+DIrgYGJwQyNdv/h9Dz25s2bV+2meFt+qLNz585t9qHO7JIAlu1NZEL/RKZ0CebgQe/0mt6Q1mg1Ppiiqo94JYImZPds3Oq6Jr0vq4BzH1/Cbef25r5JAxq9LVXlkfc38cqyPdx9fl/undiv0ev0ptO5Pq+qiAjFZeUEitTbv1lzUFruYurMFWw6mMe8GWcxvGvsSdPtPkWltlwXqsoNL33NN3uzWXjvuWxL/4rU1FREpNGt0er9lqjqI05i+SvwV49x0wp1jY/gwkEdmfv1t17pEfrJhdt4ZdkebjmnJz+7oK8XIvS/isYCoUGBLSLRAAQHBvD89aNIjArh1jmr7LXTpkYvfbmHz7dncv/FAxvcd19DNaTX5yEisgbYCGwUkdUiMtirUZhm5aZxPcgpKOXd9HrbXNTpo/WHePrTHVw9KpnfXDLQZy3cTMO0jwpl1g2jyS8q4yevfUOpdehpPKzak8WfP9zMRYOTuP7Mbl5ff0P+LZsJ3Kuq3VW1O/Bz4J9ej8Q0G2N6xjO4czQvf7n7tF8/sPXwcX7+xlpGdovlD1cOsUTTTPTvGMVjPxjKqr3ZPLN4u7/DMc3EV7uOcfMrK0mOC+fxq4f75PvakGTTTlWXVIyoahrQzuuRmGZDRLhpXE+2Hcnnyx2n3hIlp6CEH89ZRbvQIJ6/fhShQYE+iNKcrskjujBlZBeeS9vJ9iPVW4GZtuW99AP86MWvaR8Vyr9uOZNoH71GvSHJZpeI/FZEejif3+BuoWZascuGdyIxMoSXv9xd/8weyl3KXXPXcCi3kOevH0VSdJiPIjSN8eAlA2kXGsRv3t3Q4l6eZ7xjf3YBP3s9nXvmpTOiWyxv3z6OrvERPtteQ5o+3ww8AryNu6unz50y04qFBgVy3ZndeWrxdlbuyWJ0j/gGLfe/n2zh8+2Z/HnKUEZ1j/NxlOZ0JUSG8qtJ/XnwnQ28m34AX/6msk6U8P7ag2w4kEtuYSntQoO4cFASFw7uSGAT9qrQ1qkqGw7ksWLXMVbtzWLJlqOIwF3n9eHu8/sS7OPGLvUmG1XNBu72aRSmWbppXA/eTT/AdbO+4lcX9Wf62T1qPSBVlScXbuOFpbu47sxuTBvj/RuMxrumje7G/FX7+eN/NvPImQ16j+JJ8opK+dfyvSzafIScglLKXUpQgFBYWk5RaTntQoMQgX1Z7gcq20eFEhMeTNaJEt5Zc4CBnaL5/eTBpDTwHxlz+r7ckclfPt7Cuv3uh2+7xUdwzehkfpLax+utzmpT7xEmIguBq1U1xxmPA+ZV9NZsWq/YiBDevv1sfvHGWv7wn8289tW33HN+Xy4f3vm7fr5Ky11sOXScFz7byQfrDnFtSlceudwaK7YEAQHCH68YwuXPfsFb211cMrHhy+49doLrX/yKfVmFjOwWy5AuMQQKlLmU8OBAQoMDKCgup6TcxbUpXTlvQBKDOrtf5lVW7uKjDYd57KMtTPvnCv545VAuG9aZ9H05fJt1grG9EumW4LvLOW3Juv05/O/HW/liRyZdYsP505VDOX9gB79c3m7IvzOJFYkG3Gc6ItLBdyGZ5iQhMpSXbhzNos0ZPLFwGz99PZ1ZX+xiXO9E1u7PYc23ORSXuQgKEH55UX9+ktrbWp61IEO6xHDD2B7MXraHtftyqj3sWZOSMhe3zF7F8aIy3rp9LKO6n9qZSVBgAJcN78y5/dszY84qfvXmOn71ZmVP4yGBAdwxoQ//k9rLGpecBlXl691ZvPDZLj7dkkF8uxB+e+kgrj+rm1/rsyHJxiUi3VT1WwAR6Q719FduWhURYeKgJM4f0IF30w/wj7SdzPx8F4M6RfPDM7sxslscY3rE0zHGGgO0RPde2I93V+/l52+sZcGd44gIqfvPwstf7mZHRj4vTk855UTjKTosmNduPYu3v9nP4dwiBnaKpmt8BM8u2cGTi7axck8W/7whhfAQSzj1KS4rZ9WebLYePs7ba/az4UAe8e1CuHdiP24a14MoH7UwOxUNSTYPAl+IyFLc77n6Hs77YUzbEhAgTDkjmSlnJFNW7moxT8+bukWHBTNjWCiPr8rn0fc38dgPhtU67+HcIp5avJ0LBnbg/IFJjd52YIBwdUrXk8qemTaS8X0T+dVb67h1zkpm3TDaEk4tVJX5q/bx2EdbyC5w9482oGMUf7hiCFeNSiYsuPnUW0MaCHwsImcAZzlFP1XV6l3MmjbFEk3rMighkNvP7c1zaTsZ1yeRy4Z3rnG+P364mTKX8tClvr0vd3VKVwIDhJ+/sZZbZq9k1vSUes+42poDOYXc/9Y6Pt+eyZie8dw2vheDOkfTMTqsWV7Kbuhv72xgvMd49e6LjTEt2s8m9mP5rmP8+u31jOgaW+2Zi2U7Mnl/7UHuOb9vk9zAn3JGMgC/eGMt1836ipemjyauXYjPt9vcuVzKvJX7+NOHm3Gp8vvJg7nuzO5N+nK+09GQvtEeA+7B3Z3/JuAeEfmTrwMzxjSt4MAAnp46EoC75q6hqLSyI9YTxWX8+p31dI0P5/bU3k0W05QzknnuulFsPJjHD55fxoGcwvoXaqVyC0t5+5v9XPPCcn79znqGdonhk5+O50djezT7RAMNO7O5GBihqi4AEZkNrAF+7cvAjDFNr2t8BH+5ahg/ee0bps5cwR+vHEJiZCj3v7WOvVkFzP3xWU1+H2DSkI68esuZ3DJ7JTe+9DXv3DGOyNCWdUmt3KV8tesYOzNPkFdYSkhgAB2iQ2kfFYogFJWWc6KkjOyCUvIKS3G5FMXdlPxIbhFbjxxn48FcSsuVjtFhPDZlKNeO7tosL5fVpqG/sVjcLy8D96uZjTGt1MVDO/H3H57BQ+9t4JKnv0AEAkT4/eQhnNUrwS8xjekZz/PXj+KGl77m3tfTef76US3iv/mychfvph/kubQd7Dpa/W2iDZEYGUrv9u245ZxeXDQ4ieHJsS1i36tqSLL5M7BGRJbgbo02HnjAp1EZY/zqkmGdOKdPIi8vc/eNN2Vkst8ftBzXJ5FfXzyQ33+wiWeX7ODu85v3+5F2Hc3n52+sZc23OQzsFM3T00Yypkc8sRHBFJe5OHq8iIy8YhAIDw6kXWgQseHBRIcHExggBIgg0CITS00a0hptroikAaOdovtUtfpLrY0xrUpMRDA/vaB5vVn15nE92HgglycWbmNgp2gmDmp882tvc7mUOcv38NjHWwgNCuSpqSO4fHjnky55hQUHEhMeTJ8OUX6MtGk1pIHAYlU9pKoLnM9hEan+QvJTICLxIrJQRLY7P6v1AygiI0RkuYhsFJF1InKtx7RXRGS3iKQ7nxGNiccY0zKICH+aMpShXWL42evp7MhoXq9IOJBTyPUvfsXv3t/EWb0S+O/PxjN5RJcWdW/FV2pNNiISJiLxQKKIxDkJIl5EegBdGrnd+4HFqtoXWOyMV1UA3KCqg4FJwN9EJNZj+i9VdYTzSW9kPMaYFiIsOJAXfjSK0KAAfjxnNbmFpf4OCZdL+dfyPUx68jPW7svhz1OG8vKNo+0VGx7qOrO5DVgNDAC+cYZXA+8BzzZyu5OB2c7wbOCKqjOo6jZV3e4MHwQygPaN3K4xphXoHBvOc9edwb6sAn48exXZJ0r8FsvmQ+5m2b99byPDusbw0T3jmTamm53NVCH1vThJRO5S1We8ulGRHFWNdYYFyK4Yr2X+MbiT0mBVdYnIK8BYoBjnzEhVi2tZdgZO9zpJSUmj5s2b58U9aZny8/OJjIz0dxjNgtWFW0uthxWHypi1rpiYUOHKvsGc1SmIoEbeUG9IXagqO3Jc/HdvKasOlxMZDNMGhjK2U2CrSjIVdTFhwoTVqprSmHU1JNncUFO5qs6pZ7lFQMcaJj0IzPZMLiKSrao1vr9JRDoBacB0VV3hUXYYCAFmAjtV9dE6dwRISUnRVatW1Tdbq5eWlkZqaqq/w2gWrC7cWnI9rN6bzW/f3cCmQ3kkx4Vz36QBXDqs02n/0a+tLlSVnUfzWbLlKG+vOcDmQ3lEhQVxw9ju/Ph7vYiNaH29G1TUhYg0Otk0pOnzaI/hMOB83JfV6kw2qnpBbdNE5IiIdFLVQ07iyKhlvmjgP8CDFYnGWfchZ7BYRF4GftGA/TDGtEKjusfxn7vPYcnWDB7/ZBt3zV3Dy1/u5jeXDuKMbo17B2lJmYuPNhxi8eYMVuw6RsZx9wWUwZ2j+fOUoUwe0dn6bGughjR9vstz3LlJ39hrUQuA6cBjzs/3qs4gIiHAO8AcVX2zyrSKRCW47/dsaGQ8xpgWTEQ4b0AS5/brwFur9/P4f7cy5bllXDqsE/dNGlCtn7f6ZJ0oYe7X3zJn+R6O5BXTPiqUsb0SOKtXAuP7JZIcZy93O1Wnk5JPAL0aud3HgPkicguwF7gGQERSgP9R1VudsvFAgojc6Cx3o9Py7DURaY/7IdN04H8aGY8xphUIDBCuGd2VS4Z14oXPdjHzs52kbT3K09NGcN6A2p/JcbmUDQdzWbr1KO+tLGTXJwtxKXyvbyKP/WAY5/Zt32oervSXhrwW+n0qX5YWCAwE5jdmo6p6DPfluKrlq4BbneFXgVdrWf68xmzfGNO6tQsN4t6J/bgmJZn/eXU1t8xexX2TBvDj7/UiMEBQVfZlFbJi1zGW7czkix2ZZOaXIAI9ogO4c0IfLhnWmf4d285Dl77WkDOb//MYLsOdcK6tZV5jjGk2kuMieOO2s/nFm2t57KMtzF62h+4JEew8eoKjzv2XxMhQxvVJ5Nx+7Rnfrz0bVi0nNbW/nyNvfRpyz2apiIwEfghcDewG3vJ1YMYY4w3hIYE8O20klwztxHvpBziWX8I5fRI5o3scZ/aMp2+HyFbVXLm5qjXZiEg/YJrzyQRex91UekITxWaMMV4hIlw8tBMXD+3k71DarLrObLYAnwOXquoOABH5WZNEZYwxplWpq7uaKcAhYImI/FNEzsfd+ssYY4w5JbUmG1V9V1Wn4u4bbQnwU6CDiPxDRC5soviMMca0AvW+YkBVT6jqv1X1MiAZ9yuh7/N5ZMYYY1qNepONJ1XNVtWZqlrtGRljjDGmNqeUbIwxxpjTYcnGGGOMz1myMcYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz/kl2YhIvIgsFJHtzs+4WuYrF5F057PAo7yniHwlIjtE5HURCWm66I0xxpwqf53Z3A8sVtW+wGJnvCaFqjrC+VzuUf4X4ElV7QNkA7f4NlxjjDGN4a9kMxmY7QzPBq5o6ILifn/recCbp7O8McaYpieq2vQbFclR1VhnWIDsivEq85UB6UAZ8JiqvisiicAK56wGEekKfKSqQ2rZ1gxgBkBSUtKoefPmeX+HWpj8/HwiIyP9HUazYHXhZvVQyeqiUkVdTJgwYbWqpjRmXXW9FrpRRGQR0LGGSQ96jqiqikhtGa+7qh4QkV7ApyKyHsg9lThUdSYwEyAlJUVTU1NPZfFWKS0tDasHN6sLN6uHSlYXlbxZFz5LNqp6QW3TROSIiHRS1UMi0gnIqGUdB5yfu0QkDRgJvAXEikiQqpbhfqHbAa/vgDHGGK/x1z2bBcB0Z3g68F7VGUQkTkRCneFEYBywSd3X/ZYAV9W1vDHGmObDX8nmMWCiiGwHLnDGEZEUEZnlzDMQWCUia3Enl8dUdZMz7T7gXhHZASQALzZp9MYYY06Jzy6j1UVVjwHVXi2tqquAW53hZcDQWpbfBYzxZYzGGGO8x3oQMMYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicX5KNiMSLyEIR2e78jKthngkiku7xKRKRK5xpr4jIbo9pI5p6H4wxxjScv85s7gcWq2pfYLEzfhJVXaKqI1R1BHAeUAD812OWX1ZMV9X0JojZGGPMafJXspkMzHaGZwNX1DP/VcBHqlrgy6CMMcb4hr+STZKqHnKGDwNJ9cw/FZhbpeyPIrJORJ4UkVCvR2iMMcZrRFV9s2KRRUDHGiY9CMxW1ViPebNVtdp9G2daJ2Ad0FlVSz3KDgMhwExgp6o+WsvyM4AZAElJSaPmzZt32vvUWuTn5xMZGenvMJoFqws3q4dKVheVKupiwoQJq1U1pTHrCvJWUFWp6gW1TRORIyLSSVUPOYkjo45VXQO8U5FonHVXnBUVi8jLwC/qiGMm7oRESkqKpqamnsJetE5paWlYPbhZXbhZPVSyuqjkzbrw12W0BcB0Z3g68F4d806jyiU0J0EhIoL7fs8G74dojDHGW/yVbB4DJorIduACZxwRSRGRWRUziUgPoCuwtMryr4nIemA9kAj8oSmCNsYYc3p8dhmtLqp6DDi/hvJVwK0e43uALjXMd54v4zPGGONd1oOAMcYYn7NkY4wxxucs2RhjjPE5SzbGGGN8zpKNMcYYn7NkY4wxxucs2RhjjPE5SzbGGGN8zpKNMcYYn7NkY4wxxucs2RhjjPE5SzbGGGN8zpKNMcYYn7NkY4wxxucs2RhjjPE5SzbGGGN8zpKNMcYYn7NkY4wxxucs2RhjjPE5vyQbEblaRDaKiEtEUuqYb5KIbBWRHSJyv0d5TxH5yil/XURCmiZyY4wxp8NfZzYbgCnAZ7XNICKBwN+B7wODgGkiMsiZ/BfgSVXtA2QDt/g2XGOMMY3hl2SjqptVdWs9s40BdqjqLlUtAeYBk0VEgPOAN535ZgNX+CxYY4wxjRbk7wDq0AXY5zG+HzgTSAByVLXMo7xLbSsRkRnADGc0X0TqS3JtQSKQ6e8gmgmrCzerh0pWF5Uq6qJ7Y1fks2QjIouAjjVMelBV3/PVdqtS1ZnAzKbaXksgIqtUtdZ7ZW2J1YWb1UMlq4tK3qwLnyUbVb2gkas4AHT1GE92yo4BsSIS5JzdVJQbY4xppppz0+eVQF+n5VkIMBVYoKoKLAGucuabDjTZmZIxxphT56+mz1eKyH5gLPAfEfnEKe8sIh8COGctdwKfAJuB+aq60VnFfcC9IrID9z2cF5t6H1o4u6xYyerCzeqhktVFJa/VhbhPFIwxxhjfac6X0YwxxrQSlmyMMcb4nCWbVkJEXhKRDBHZ4FEWLyILRWS78zPOKRcRedrp7mediJzhscx0Z/7tIjLdH/vSGCLSVUSWiMgmp0uke5zytlgXYSLytYisderiEae8xu6eRCTUGd/hTO/hsa4HnPKtInKRn3apUUQkUETWiMgHznhbrYc9IrJeRNJFZJVT5vvvh6rapxV8gPHAGcAGj7L/Be53hu8H/uIMXwx8BAhwFvCVUx4P7HJ+xjnDcf7et1Osh07AGc5wFLANd3dHbbEuBIh0hoOBr5x9nA9MdcqfB253hn8CPO8MTwVed4YHAWuBUKAnsBMI9Pf+nUZ93Av8G/jAGW+r9bAHSKxS5vPvh53ZtBKq+hmQVaV4Mu7ufODkbn0mA3PUbQXu55Y6ARcBC1U1S1WzgYXAJJ8H70WqekhVv3GGj+NuydiFtlkXqqr5zmiw81Fq7+7Js47eBM53uoeaDMxT1WJV3Q3swN2dVIshIsnAJcAsZ7yubq9abT3UweffD0s2rVuSqh5yhg8DSc5wTV0BdamjvEVyLn+MxP0ffZusC+fSUTqQgfsPwk5q7+7pu312pufifrSgNdTF34BfAS5nvK5ur1pzPYD7H47/ishqcXfnBU3w/WjOfaMZL1JVFZE2085dRCKBt4Cfqmqe+x9Tt7ZUF6paDowQkVjgHWCAfyNqeiJyKZChqqtFJNXP4TQH56jqARHpACwUkS2eE331/bAzm9btiHPKi/MzwymvrSug2spbFBEJxp1oXlPVt53iNlkXFVQ1B3fPG2NxuntyJnnu13f77EyPwd09VEuvi3HA5SKyB3fv8ecBT9H26gEAVT3g/MzA/Q/IGJrg+2HJpnVbgLs7Hzi5W58FwA1OS5OzgFznFPoT4EIRiXNao1zolLUYzrX1F4HNqvqEx6S2WBftnTMaRCQcmIj7HlZt3T151tFVwKfqvhu8AJjqtNLqCfQFvm6SnfACVX1AVZNVtQfuG/6fqup1tLF6ABCRdiISVTGM+7jeQFN8P/zdMsI+XmthMhc4BJTivn56C+7rzIuB7cAiIN6ZV3C/mG4nsB5I8VjPzbhvfO4AbvL3fp1GPZyD+5r0OiDd+VzcRutiGLDGqYsNwENOeS/cfyR3AG8AoU55mDO+w5ney2NdDzp1tBX4vr/3rRF1kkpla7Q2Vw/OPq91Phtx98JPU3w/rLsaY4wxPmeX0YwxxvicJRtjjDE+Z8nGGGOMz1myMcYY43OWbIwxxvicJRtjmoCI5Nc/lzGtlyUbY4wxPmfJxhg/EZHLnPelrBGRRSKS5JS3d94pslFEZonIXhFJ9He8xjSGJRtj/OcL4CxVHYm7z65fOeUP4+4iZTDuLu67+Sk+Y7zGen02xn+Sgdedjg9DgN1O+TnAlQCq+rGIZPspPmO8xs5sjPGfZ4BnVXUocBvuPrmMaZUs2RjjPzFUdsvu+Q73L4FrAETkQtyv3TWmRbOOOI1pAiLiAg56FD2BuyfdJ4Fs4FNgtKqmOi+1mov7bYnLgUuBHqpa3LRRG+M9lmyMaWZEJBQoV9UyERkL/ENVR/g5LGMaxRoIGNP8dAPmi0gAUAL82M/xGNNodmZjjDHG56yBgDHGGJ+zZGOMMcbnLNkYY4zxOUs2xhhjfM6SjTHGGJ/7f/ZMjF6LyOdVAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x560 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d2dVLthumvw8"
      },
      "source": [
        "import sklearn"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vRYCoDjqlg7b",
        "outputId": "47d20154-db78-4dc8-e421-c889a41654fb"
      },
      "source": [
        "from pandas import read_csv\n",
        "from pandas import datetime\n",
        "from statsmodels.tsa.arima.model import ARIMA\n",
        "from sklearn.metrics import mean_squared_error\n",
        "\n",
        "X = series.values\n",
        "size = int(len(X) * 0.66)\n",
        "train, test = X[0:size], X[size:len(X)]\n",
        "history = [x for x in train]\n",
        "predictions = list()\n",
        "for t in range(len(test)):\n",
        "    model = ARIMA(history, order=(5,1,0))\n",
        "    model_fit = model.fit()\n",
        "    output = model_fit.forecast()\n",
        "    yhat = output[0]\n",
        "    predictions.append(yhat)\n",
        "    obs = test[t]\n",
        "    history.append(obs)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: FutureWarning: The pandas.datetime class is deprecated and will be removed from pandas in a future version. Import from datetime module instead.\n",
            "  \n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G90E2s3Vm0E-",
        "outputId": "2f41174d-d7f4-4fd4-cbb0-933a8cf90809"
      },
      "source": [
        "error = mean_squared_error(test, predictions)\n",
        "print('Test MSE: %.3f' % error)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Test MSE: 13.740\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B64ExupKs7JP",
        "outputId": "3bc886c6-0fc5-4693-c448-f0e9326d0c89"
      },
      "source": [
        "plt.figure(figsize=(12, 6), dpi=100)\n",
        "plt.plot(test, label='Real')\n",
        "plt.plot(predictions, color='red', label='Predicted')\n",
        "plt.xlabel('Days')\n",
        "plt.ylabel('USD')\n",
        "plt.title('Figure 5: ARIMA model on GS stock')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S-JE91dzxjlQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 131
        },
        "outputId": "1b85a9d7-3363-43ee-a264-4b43fb7a1235"
      },
      "source": [
        "dataset_total_df="
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "SyntaxError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-44-436cb25ad4d7>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    dataset_total_df=\u001b[0m\n\u001b[0m                     ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Sx-hC_lis_Ls"
      },
      "source": [
        "print('Total dataset has {} samples, and {} features.'.format(dataset_total_df.shape[0], \\\n",
        "                                                              dataset_total_df.shape[1]))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jisN0wyAxiPA"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}