stock_RNN_many_to_one.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "source": [
    "import pandas as pd\r\n",
    "import numpy as np\r\n",
    "import matplotlib.pyplot as plt\r\n",
    "%matplotlib inline"
   ],
   "outputs": [],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T11:10:55.631046Z",
     "start_time": "2020-12-04T11:10:55.615174Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "source": [
    "from FinMind.data import DataLoader\r\n",
    "dl=DataLoader()\r\n",
    "data = dl.taiwan_stock_daily_adj(\"2330\", \"2018-01-01\", \"2021-07-02\")\r\n",
    "\r\n",
    "fig=plt.figure(figsize=(20,8))\r\n",
    "plt.xticks(rotation = 90)  \r\n",
    "ax1 = plt.subplot(111)\r\n",
    "ax1.plot(data.close,color='red',label='close')\r\n",
    "ax1.plot(data.open,color='green',label='open')\r\n",
    "plt.legend()\r\n",
    "# twin 為共享x軸\r\n",
    "ax2= ax1.twinx()\r\n",
    "plt.bar(data.date,data.Trading_Volume.astype('int')//1000)\r\n",
    "ax3 = ax1.twinx()"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "C:\\Users\\desse\\AppData\\Local\\Programs\\Python\\Python36\\lib\\site-packages\\ipykernel_launcher.py:7: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance.  In a future version, a new instance will always be created and returned.  Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance.\n",
      "  import sys\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1440x576 with 3 Axes>"
      ],
      "image/png": "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"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T11:11:09.316755Z",
     "start_time": "2020-12-04T11:10:55.754708Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "source": [
    "# train, test split\r\n",
    "train_size = int(len(data) * 0.7)\r\n",
    "test_size = len(data) - train_size\r\n",
    "train, test = data[0:train_size], data[train_size:len(data)]\r\n",
    "\r\n",
    "print('Training size: ', train_size)\r\n",
    "print('Test size: ', test_size)\r\n",
    "\r\n",
    "#只要Volume\r\n",
    "train_set = train['Trading_Volume']\r\n",
    "test_set = test['Trading_Volume']\r\n",
    "\r\n",
    "# MinMaxScale\r\n",
    "from sklearn.preprocessing import MinMaxScaler \r\n",
    "sc = MinMaxScaler(feature_range = (0, 1))\r\n",
    "train_set = train_set.values.reshape(-1, 1)\r\n",
    "training_set_scaled = sc.fit_transform(train_set)\r\n",
    "\r\n",
    "print('training_set_scaled:\\n',training_set_scaled[0:5])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Training size:  500\n",
      "Test size:  215\n",
      "training_set_scaled:\n",
      " [[0.1144334 ]\n",
      " [0.22252775]\n",
      " [0.20252178]\n",
      " [0.15929965]\n",
      " [0.14445588]]\n"
     ]
    }
   ],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T11:11:09.870357Z",
     "start_time": "2020-12-04T11:11:09.348996Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "source": [
    "look_back=11\n",
    "X_train = [] \n",
    "y_train = []\n",
    "for i in range(look_back,len(train_set)):\n",
    "    X_train.append(training_set_scaled[i-look_back:i-1, 0]) \n",
    "    y_train.append(training_set_scaled[i, 0])\n",
    "\n",
    "X_train, y_train = np.array(X_train), np.array(y_train) \n",
    "X_train = np.reshape(X_train, (X_train.shape[0], X_train.shape[1], 1))\n",
    "\n",
    "print('用第',look_back-1,'天之前的股價:')\n",
    "print(X_train[0])\n",
    "print('預測第',look_back-1,'天的股價:')\n",
    "print(y_train[0])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "用第 10 天之前的股價:\n",
      "[[0.1144334 ]\n",
      " [0.22252775]\n",
      " [0.20252178]\n",
      " [0.15929965]\n",
      " [0.14445588]\n",
      " [0.12225575]\n",
      " [0.17509682]\n",
      " [0.22541205]\n",
      " [0.15470719]\n",
      " [0.19774628]]\n",
      "預測第 10 天的股價:\n",
      "0.2733015470616637\n"
     ]
    }
   ],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T11:12:14.270695Z",
     "start_time": "2020-12-04T11:12:14.257798Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "source": [
    "from tensorflow.keras import layers\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, SimpleRNN\n",
    "\n",
    "model = Sequential()\n",
    "model.add(SimpleRNN(units = 100, input_shape = (X_train.shape[1], 1)))\n",
    "model.add(Dense(units = 1))\n",
    "model.compile(optimizer = 'adam', loss = 'mean_squared_error')\n",
    "history = model.fit(X_train, y_train, epochs = 100, batch_size = 16)\n",
    "\n",
    "plt.title('train_loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.plot(history.history[\"loss\"])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Epoch 1/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0293\n",
      "Epoch 2/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0163\n",
      "Epoch 3/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0156\n",
      "Epoch 4/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0146\n",
      "Epoch 5/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0147\n",
      "Epoch 6/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0146\n",
      "Epoch 7/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0152\n",
      "Epoch 8/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0159\n",
      "Epoch 9/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0140\n",
      "Epoch 10/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0141\n",
      "Epoch 11/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0143\n",
      "Epoch 12/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0143\n",
      "Epoch 13/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0142\n",
      "Epoch 14/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0141\n",
      "Epoch 15/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 16/100\n",
      "30/30 [==============================] - 0s 4ms/step - loss: 0.0139\n",
      "Epoch 17/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0140\n",
      "Epoch 18/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 19/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 20/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 21/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0140\n",
      "Epoch 22/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 23/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 24/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 25/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 26/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 27/100\n",
      "30/30 [==============================] - 0s 4ms/step - loss: 0.0137\n",
      "Epoch 28/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 29/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 30/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 31/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0142\n",
      "Epoch 32/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 33/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 34/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 35/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 36/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 37/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 38/100\n",
      "30/30 [==============================] - 0s 4ms/step - loss: 0.0138\n",
      "Epoch 39/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 40/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 41/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 42/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 43/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 44/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 45/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 46/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 47/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 48/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 49/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 50/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 51/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 52/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 53/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 54/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 55/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 56/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 57/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 58/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 59/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 60/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 61/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0146\n",
      "Epoch 62/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 63/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 64/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 65/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 66/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 67/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 68/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 69/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 70/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 71/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 72/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 73/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 74/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 75/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 76/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 77/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 78/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 79/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 80/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 81/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 82/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 83/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 84/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 85/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0135\n",
      "Epoch 86/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n",
      "Epoch 87/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 88/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 89/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 90/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0140\n",
      "Epoch 91/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 92/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0136\n",
      "Epoch 93/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 94/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 95/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 96/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 97/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 98/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0137\n",
      "Epoch 99/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0138\n",
      "Epoch 100/100\n",
      "30/30 [==============================] - 0s 3ms/step - loss: 0.0139\n"
     ]
    },
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x23c8366c080>]"
      ]
     },
     "metadata": {},
     "execution_count": 21
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T10:08:55.254072Z",
     "start_time": "2020-12-04T10:08:45.890967Z"
    },
    "scrolled": true
   }
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "source": [
    "dataset_total = pd.concat((train['Trading_Volume'], test['Trading_Volume']), axis = 0)\n",
    "inputs = dataset_total[len(dataset_total) - len(test) - look_back:].values\n",
    "inputs = inputs.reshape(-1,1)\n",
    "inputs = sc.transform(inputs)\n",
    "X_test = []\n",
    "for i in range(look_back, len(inputs)):\n",
    "    X_test.append(inputs[i-look_back:i-1, 0])\n",
    "\n",
    "X_test = np.array(X_test)\n",
    "X_test = np.reshape(X_test, (X_test.shape[0], X_test.shape[1], 1))\n",
    "\n",
    "predicted_stock_price = model.predict(X_test)\n",
    "# inverse_transform將股價轉為歸一化前\n",
    "predicted_stock_price = sc.inverse_transform(predicted_stock_price)\n"
   ],
   "outputs": [],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T10:08:55.438403Z",
     "start_time": "2020-12-04T10:08:55.347632Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "source": [
    "# Plot prediction vs Real\n",
    "plt.plot(test['Trading_Volume'].values, color = 'black', label = 'Real TSMC Stock Price')\n",
    "plt.plot(predicted_stock_price, color = 'green', label = 'Predicted TSMC Stock Price')\n",
    "plt.title('TSMC Stock Price Prediction')\n",
    "plt.xlabel('Time',size=14)\n",
    "plt.ylabel('Stock Price',size=14)\n",
    "plt.legend(fontsize=14)\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "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"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-04T10:08:55.653770Z",
     "start_time": "2020-12-04T10:08:55.532141Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
 "metadata": {
  "hide_input": false,
  "kernelspec": {
   "display_name": "Python 3.6.8 64-bit",
   "language": "python",
   "name": "python36864bit6992c404cc394c739b38c1f8a470111b"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}