ARMA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yfinance as yf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "sp500 = yf.Ticker(\"^GSPC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "msft = yf.Ticker(\"MSFT\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 4415.53\n"
     ]
    }
   ],
   "source": [
    "warnings.filterwarnings(\"ignore\")  # To ignore warnings from ARIMA\n",
    "\n",
    "# Step 1: Download Microsoft stock data\n",
    "msft = yf.download('MSFT', start='2010-01-01', end='2024-01-01')\n",
    "\n",
    "# Step 2: Extract the 'Close' prices to use as our time series\n",
    "msft_close = msft['Close']\n",
    "\n",
    "# Step 3: Ensure all datetimes are timezone-naive\n",
    "msft_close.index = msft_close.index.tz_localize(None)\n",
    "\n",
    "# Step 4: Plot the data to visualize the time series\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(msft_close, label='Microsoft Closing Price')\n",
    "plt.title('Microsoft Stock Closing Price')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Price (USD)')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# Step 5: Train an ARIMA model\n",
    "# Split data into train and test sets\n",
    "train_size = int(len(msft_close) * 0.8)\n",
    "train, test = msft_close[:train_size], msft_close[train_size:]\n",
    "\n",
    "# Fit the ARIMA model on the training data\n",
    "order = (5, 1, 0)  # You might need to adjust (p, d, q) after checking model performance\n",
    "model = ARIMA(train, order=order)\n",
    "model_fit = model.fit()\n",
    "\n",
    "# Step 6: Make predictions using integer index positions\n",
    "start_index = len(train)\n",
    "end_index = len(train) + len(test) - 1\n",
    "predictions = model_fit.predict(start=start_index, end=end_index, typ='levels')\n",
    "\n",
    "# Step 7: Plot the predictions against the actual values\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(train, label='Training Data')\n",
    "plt.plot(test, label='Actual Stock Price', color='blue')\n",
    "plt.plot(test.index, predictions, label='Predicted Stock Price', color='red')\n",
    "plt.title('ARIMA Model Predictions')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Price (USD)')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "# Step 8: Evaluate the model\n",
    "from sklearn.metrics import mean_squared_error\n",
    "mse = mean_squared_error(test, predictions)\n",
    "print(f'Mean Squared Error: {mse:.2f}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicted=117.225645, expected=117.940002\n",
      "predicted=117.718810, expected=119.019997\n",
      "predicted=118.853950, expected=119.190002\n",
      "predicted=119.202696, expected=119.970001\n",
      "predicted=119.861228, expected=119.360001\n",
      "predicted=119.251011, expected=119.889999\n",
      "predicted=119.820906, expected=119.930000\n",
      "predicted=119.818475, expected=119.279999\n",
      "predicted=119.331251, expected=120.190002\n",
      "predicted=120.169465, expected=120.330002\n",
      "predicted=120.177238, expected=120.949997\n",
      "predicted=120.928011, expected=121.050003\n",
      "predicted=121.009003, expected=120.769997\n",
      "predicted=120.741454, expected=121.769997\n",
      "predicted=121.652872, expected=123.370003\n",
      "predicted=123.059341, expected=123.760002\n",
      "predicted=123.634436, expected=125.440002\n",
      "predicted=125.277521, expected=125.010002\n",
      "predicted=124.806753, expected=129.149994\n",
      "predicted=128.681373, expected=129.889999\n",
      "predicted=129.416590, expected=129.770004\n",
      "predicted=129.804402, expected=130.600006\n",
      "predicted=130.450923, expected=127.879997\n",
      "predicted=127.787087, expected=126.209999\n",
      "predicted=126.559468, expected=128.899994\n",
      "predicted=128.601474, expected=128.149994\n",
      "predicted=128.005624, expected=125.519997\n",
      "predicted=126.234398, expected=125.510002\n",
      "predicted=125.702114, expected=125.500000\n",
      "predicted=125.219153, expected=127.129997\n",
      "predicted=127.109970, expected=123.349998\n",
      "predicted=123.799993, expected=124.730003\n",
      "predicted=124.942211, expected=126.019997\n",
      "predicted=125.554061, expected=128.929993\n",
      "predicted=128.569430, expected=128.070007\n",
      "predicted=128.202244, expected=126.220001\n",
      "predicted=126.465620, expected=126.900002\n",
      "predicted=126.783824, expected=127.669998\n",
      "predicted=127.309156, expected=126.180000\n",
      "predicted=126.404905, expected=126.239998\n",
      "predicted=126.484414, expected=126.160004\n",
      "predicted=126.046177, expected=124.940002\n",
      "predicted=125.070555, expected=125.730003\n",
      "predicted=125.835120, expected=123.680000\n",
      "predicted=123.790963, expected=119.839996\n",
      "predicted=120.476246, expected=123.160004\n",
      "predicted=123.093560, expected=125.830002\n",
      "predicted=125.108280, expected=127.820000\n",
      "predicted=127.744027, expected=131.399994\n",
      "predicted=131.127892, expected=132.600006\n",
      "predicted=131.959642, expected=132.100006\n",
      "predicted=131.942284, expected=131.490005\n",
      "predicted=131.359199, expected=132.320007\n",
      "predicted=131.978736, expected=132.449997\n",
      "predicted=132.282662, expected=132.850006\n",
      "predicted=132.892695, expected=135.160004\n",
      "predicted=134.934538, expected=135.690002\n",
      "predicted=135.417622, expected=136.949997\n",
      "predicted=136.873436, expected=136.970001\n",
      "predicted=136.787645, expected=137.779999\n",
      "predicted=137.586091, expected=133.429993\n",
      "predicted=133.687272, expected=133.929993\n",
      "predicted=134.148447, expected=134.149994\n",
      "predicted=133.887087, expected=133.960007\n",
      "predicted=134.075359, expected=135.679993\n",
      "predicted=135.843221, expected=136.580002\n",
      "predicted=136.314360, expected=137.460007\n",
      "predicted=137.373287, expected=137.059998\n",
      "predicted=137.014597, expected=136.960007\n",
      "predicted=136.869828, expected=136.460007\n",
      "predicted=136.394920, expected=137.850006\n",
      "predicted=137.704914, expected=138.399994\n",
      "predicted=138.260330, expected=138.899994\n",
      "predicted=138.895162, expected=138.899994\n",
      "predicted=138.868033, expected=137.080002\n",
      "predicted=137.140383, expected=136.270004\n",
      "predicted=136.417169, expected=136.419998\n",
      "predicted=136.359608, expected=136.619995\n",
      "predicted=136.633911, expected=138.429993\n",
      "predicted=138.428176, expected=139.289993\n",
      "predicted=139.140935, expected=140.720001\n",
      "predicted=140.578743, expected=140.190002\n",
      "predicted=140.071567, expected=141.339996\n",
      "predicted=141.155673, expected=141.029999\n",
      "predicted=140.829915, expected=140.350006\n",
      "predicted=140.388878, expected=136.270004\n",
      "predicted=136.660925, expected=138.059998\n",
      "predicted=138.086720, expected=136.899994\n",
      "predicted=136.791510, expected=132.210007\n",
      "predicted=133.000058, expected=134.690002\n",
      "predicted=135.006535, expected=135.279999\n",
      "predicted=134.725986, expected=138.889999\n",
      "predicted=138.905688, expected=137.710007\n",
      "predicted=137.845976, expected=135.789993\n",
      "predicted=135.975032, expected=138.600006\n",
      "predicted=138.241754, expected=133.979996\n",
      "predicted=133.965641, expected=133.679993\n",
      "predicted=134.343908, expected=136.130005\n",
      "predicted=135.700997, expected=138.410004\n",
      "predicted=137.999592, expected=137.259995\n",
      "predicted=137.646624, expected=138.789993\n",
      "predicted=138.721888, expected=137.779999\n",
      "predicted=137.418626, expected=133.389999\n",
      "predicted=133.831944, expected=135.449997\n",
      "predicted=135.568375, expected=135.740005\n",
      "predicted=135.300064, expected=135.559998\n",
      "predicted=135.955690, expected=138.119995\n",
      "predicted=138.129612, expected=137.860001\n",
      "predicted=137.483699, expected=136.039993\n",
      "predicted=136.335856, expected=137.630005\n",
      "predicted=137.468939, expected=140.050003\n",
      "predicted=139.394830, expected=139.100006\n",
      "predicted=139.181097, expected=137.520004\n",
      "predicted=137.924562, expected=136.080002\n",
      "predicted=136.055804, expected=136.119995\n",
      "predicted=136.036544, expected=137.520004\n",
      "predicted=137.491047, expected=137.320007\n",
      "predicted=137.427349, expected=136.330002\n",
      "predicted=136.610506, expected=137.389999\n",
      "predicted=137.281893, expected=138.520004\n",
      "predicted=138.174883, expected=141.070007\n",
      "predicted=140.830905, expected=139.440002\n",
      "predicted=139.433444, expected=139.139999\n",
      "predicted=139.261713, expected=137.380005\n",
      "predicted=137.293081, expected=139.360001\n",
      "predicted=139.196793, expected=139.539993\n",
      "predicted=139.431962, expected=137.729996\n",
      "predicted=138.080268, expected=139.029999\n",
      "predicted=139.092040, expected=137.070007\n",
      "predicted=136.938026, expected=134.649994\n",
      "predicted=135.206590, expected=136.279999\n",
      "predicted=136.326820, expected=138.119995\n",
      "predicted=137.710739, expected=137.119995\n",
      "predicted=137.395436, expected=135.669998\n",
      "predicted=136.068379, expected=138.240005\n",
      "predicted=137.854740, expected=139.100006\n",
      "predicted=138.622940, expected=139.679993\n",
      "predicted=139.779715, expected=139.550003\n",
      "predicted=139.512745, expected=141.570007\n",
      "predicted=141.156942, expected=140.410004\n",
      "predicted=140.235306, expected=139.690002\n",
      "predicted=139.904907, expected=137.410004\n",
      "predicted=137.578908, expected=138.429993\n",
      "predicted=138.415292, expected=136.369995\n",
      "predicted=136.543151, expected=137.240005\n",
      "predicted=137.541361, expected=139.940002\n",
      "predicted=139.651259, expected=140.729996\n",
      "predicted=140.443685, expected=144.190002\n",
      "predicted=143.991280, expected=142.830002\n",
      "predicted=142.462850, expected=144.610001\n",
      "predicted=144.401085, expected=143.369995\n",
      "predicted=143.058152, expected=143.720001\n",
      "predicted=143.628876, expected=144.550003\n",
      "predicted=144.413179, expected=144.460007\n",
      "predicted=144.329670, expected=144.059998\n",
      "predicted=144.217698, expected=144.259995\n",
      "predicted=144.199916, expected=145.960007\n",
      "predicted=145.692466, expected=146.110001\n",
      "predicted=145.982656, expected=147.070007\n",
      "predicted=147.035056, expected=147.309998\n",
      "predicted=147.106910, expected=148.059998\n",
      "predicted=147.850252, expected=149.970001\n",
      "predicted=149.662505, expected=150.339996\n",
      "predicted=150.081884, expected=150.389999\n",
      "predicted=150.363860, expected=149.619995\n",
      "predicted=149.553021, expected=149.479996\n",
      "predicted=149.392171, expected=149.589996\n",
      "predicted=149.533609, expected=151.229996\n",
      "predicted=151.085112, expected=152.029999\n",
      "predicted=151.883500, expected=152.320007\n",
      "predicted=152.283615, expected=151.380005\n",
      "predicted=151.384969, expected=149.550003\n",
      "predicted=149.649904, expected=149.309998\n",
      "predicted=149.380154, expected=149.850006\n",
      "predicted=149.786225, expected=149.929993\n",
      "predicted=150.037346, expected=151.750000\n",
      "predicted=151.737747, expected=151.360001\n",
      "predicted=151.238402, expected=151.130005\n",
      "predicted=151.193576, expected=151.699997\n",
      "predicted=151.547937, expected=153.240005\n",
      "predicted=152.909989, expected=154.529999\n",
      "predicted=154.334710, expected=155.529999\n",
      "predicted=155.362542, expected=154.690002\n",
      "predicted=154.602889, expected=154.369995\n",
      "predicted=154.314406, expected=155.710007\n",
      "predicted=155.430906, expected=157.410004\n",
      "predicted=157.091906, expected=157.410004\n",
      "predicted=157.387140, expected=157.380005\n",
      "predicted=157.390800, expected=158.669998\n",
      "predicted=158.364510, expected=158.960007\n",
      "predicted=158.697000, expected=157.589996\n",
      "predicted=157.738511, expected=157.699997\n",
      "predicted=157.752951, expected=160.619995\n",
      "predicted=160.177291, expected=158.619995\n",
      "predicted=158.610317, expected=159.029999\n",
      "predicted=159.355659, expected=157.580002\n",
      "predicted=157.478629, expected=160.089996\n",
      "predicted=159.841202, expected=162.089996\n",
      "predicted=161.762881, expected=161.339996\n",
      "predicted=161.352337, expected=163.279999\n",
      "predicted=163.198973, expected=162.130005\n",
      "predicted=161.783714, expected=163.179993\n",
      "predicted=163.126208, expected=166.169998\n",
      "predicted=165.706412, expected=167.100006\n",
      "predicted=166.720664, expected=166.500000\n",
      "predicted=166.604140, expected=165.699997\n",
      "predicted=165.646042, expected=166.720001\n",
      "predicted=166.432438, expected=165.039993\n",
      "predicted=165.057651, expected=162.279999\n",
      "predicted=162.796599, expected=165.460007\n",
      "predicted=165.337823, expected=168.039993\n",
      "predicted=167.425808, expected=172.779999\n",
      "predicted=172.481335, expected=170.229996\n",
      "predicted=170.149288, expected=174.380005\n",
      "predicted=173.966686, expected=180.119995\n",
      "predicted=178.874859, expected=179.899994\n",
      "predicted=179.441307, expected=183.630005\n",
      "predicted=183.629830, expected=183.889999\n",
      "predicted=183.214435, expected=188.699997\n",
      "predicted=188.280876, expected=184.440002\n",
      "predicted=184.495854, expected=184.710007\n",
      "predicted=184.975196, expected=183.710007\n",
      "predicted=183.500435, expected=185.350006\n",
      "predicted=185.076139, expected=187.229996\n",
      "predicted=187.122476, expected=187.279999\n",
      "predicted=187.239151, expected=184.419998\n",
      "predicted=184.769163, expected=178.589996\n",
      "predicted=179.128599, expected=170.889999\n",
      "predicted=171.438107, expected=168.070007\n",
      "predicted=168.349464, expected=170.169998\n",
      "predicted=170.253840, expected=158.179993\n",
      "predicted=158.809913, expected=162.009995\n",
      "predicted=162.577389, expected=172.789993\n",
      "predicted=171.092730, expected=164.509995\n",
      "predicted=164.880237, expected=170.550003\n",
      "predicted=172.268338, expected=166.270004\n",
      "predicted=164.977952, expected=161.570007\n",
      "predicted=162.949912, expected=150.619995\n",
      "predicted=151.978288, expected=160.919998\n",
      "predicted=159.234584, expected=153.630005\n",
      "predicted=154.232052, expected=139.059998\n",
      "predicted=142.755840, expected=158.830002\n",
      "predicted=156.735669, expected=135.419998\n",
      "predicted=137.789712, expected=146.570007\n",
      "predicted=148.189049, expected=140.399994\n",
      "predicted=138.985965, expected=142.710007\n",
      "predicted=142.789203, expected=137.350006\n",
      "predicted=140.204551, expected=135.979996\n",
      "predicted=135.971736, expected=148.339996\n",
      "predicted=143.707918, expected=146.919998\n",
      "predicted=147.364395, expected=156.110001\n",
      "predicted=154.885060, expected=149.699997\n",
      "predicted=151.579359, expected=160.229996\n",
      "predicted=157.232776, expected=157.710007\n",
      "predicted=158.273492, expected=152.110001\n",
      "predicted=155.033620, expected=155.259995\n",
      "predicted=153.724924, expected=153.830002\n",
      "predicted=153.552992, expected=165.270004\n",
      "predicted=161.804541, expected=163.490005\n",
      "predicted=164.245653, expected=165.130005\n",
      "predicted=165.741889, expected=165.139999\n",
      "predicted=164.800799, expected=165.509995\n",
      "predicted=165.612501, expected=173.699997\n",
      "predicted=170.970333, expected=171.880005\n",
      "predicted=172.846571, expected=177.039993\n",
      "predicted=176.149532, expected=178.600006\n",
      "predicted=178.048608, expected=175.059998\n",
      "predicted=177.040421, expected=167.820007\n",
      "predicted=170.022576, expected=173.520004\n",
      "predicted=171.061034, expected=171.419998\n",
      "predicted=171.638906, expected=174.550003\n",
      "predicted=174.120751, expected=174.050003\n",
      "predicted=173.963857, expected=169.809998\n",
      "predicted=171.584284, expected=177.429993\n",
      "predicted=174.623993, expected=179.210007\n",
      "predicted=178.511210, expected=174.570007\n",
      "predicted=176.960657, expected=178.839996\n",
      "predicted=177.295165, expected=180.759995\n",
      "predicted=179.820724, expected=182.539993\n",
      "predicted=182.530323, expected=183.600006\n",
      "predicted=183.360568, expected=184.679993\n",
      "predicted=184.593805, expected=186.740005\n",
      "predicted=186.231411, expected=182.509995\n",
      "predicted=184.076041, expected=179.750000\n",
      "predicted=180.752334, expected=180.529999\n",
      "predicted=179.765167, expected=183.160004\n",
      "predicted=182.144438, expected=184.910004\n",
      "predicted=184.449884, expected=183.630005\n",
      "predicted=184.269143, expected=185.660004\n",
      "predicted=185.122200, expected=183.429993\n",
      "predicted=184.087881, expected=183.509995\n",
      "predicted=183.681765, expected=181.570007\n",
      "predicted=181.928295, expected=181.809998\n",
      "predicted=181.765860, expected=181.399994\n",
      "predicted=181.313669, expected=183.250000\n",
      "predicted=182.701287, expected=182.830002\n",
      "predicted=182.935186, expected=184.910004\n",
      "predicted=184.417010, expected=185.360001\n",
      "predicted=185.186884, expected=182.919998\n",
      "predicted=183.949742, expected=187.199997\n",
      "predicted=185.758736, expected=188.360001\n",
      "predicted=187.870572, expected=189.800003\n",
      "predicted=189.826593, expected=196.839996\n",
      "predicted=194.643275, expected=186.270004\n",
      "predicted=190.098289, expected=187.740005\n",
      "predicted=187.710069, expected=188.940002\n",
      "predicted=187.397173, expected=193.570007\n",
      "predicted=192.559977, expected=194.240005\n",
      "predicted=193.928570, expected=196.320007\n",
      "predicted=196.063083, expected=195.149994\n",
      "predicted=195.535031, expected=200.570007\n",
      "predicted=199.056126, expected=201.910004\n",
      "predicted=201.467711, expected=197.839996\n",
      "predicted=199.725817, expected=200.339996\n",
      "predicted=199.463292, expected=196.330002\n",
      "predicted=197.401502, expected=198.440002\n",
      "predicted=198.015897, expected=203.509995\n",
      "predicted=201.396713, expected=204.699997\n",
      "predicted=204.741326, expected=206.259995\n",
      "predicted=206.088692, expected=210.699997\n",
      "predicted=209.357136, expected=208.250000\n",
      "predicted=209.329622, expected=212.830002\n",
      "predicted=211.718273, expected=214.320007\n",
      "predicted=213.665306, expected=213.669998\n",
      "predicted=214.503224, expected=207.070007\n",
      "predicted=209.147735, expected=208.350006\n",
      "predicted=207.790196, expected=208.039993\n",
      "predicted=207.612746, expected=203.919998\n",
      "predicted=205.458965, expected=202.880005\n",
      "predicted=202.948872, expected=211.600006\n",
      "predicted=208.435399, expected=208.750000\n",
      "predicted=209.760640, expected=211.750000\n",
      "predicted=211.545729, expected=202.539993\n",
      "predicted=205.138775, expected=201.300003\n",
      "predicted=201.962164, expected=203.850006\n",
      "predicted=202.180890, expected=202.020004\n",
      "predicted=202.823113, expected=204.059998\n",
      "predicted=203.468803, expected=203.899994\n",
      "predicted=203.745335, expected=205.009995\n",
      "predicted=204.905905, expected=216.539993\n",
      "predicted=212.831273, expected=213.289993\n",
      "predicted=214.630045, expected=212.940002\n",
      "predicted=213.891535, expected=216.350006\n",
      "predicted=214.709713, expected=212.479996\n",
      "predicted=214.019431, expected=208.250000\n",
      "predicted=209.806613, expected=203.380005\n",
      "predicted=204.368985, expected=209.190002\n",
      "predicted=207.152740, expected=208.699997\n",
      "predicted=208.609205, expected=208.899994\n",
      "predicted=209.378728, expected=210.279999\n",
      "predicted=209.574829, expected=211.490005\n",
      "predicted=211.218447, expected=209.699997\n",
      "predicted=210.363001, expected=214.580002\n",
      "predicted=213.098282, expected=213.020004\n",
      "predicted=213.387066, expected=213.690002\n",
      "predicted=213.916165, expected=216.470001\n",
      "predicted=215.321143, expected=221.149994\n",
      "predicted=219.872986, expected=226.580002\n",
      "predicted=225.205618, expected=228.910004\n",
      "predicted=228.665042, expected=225.529999\n",
      "predicted=226.921569, expected=227.270004\n",
      "predicted=226.784267, expected=231.649994\n",
      "predicted=230.125461, expected=217.300003\n",
      "predicted=222.059367, expected=214.250000\n",
      "predicted=215.330905, expected=202.660004\n",
      "predicted=204.417018, expected=211.289993\n",
      "predicted=208.708011, expected=205.369995\n",
      "predicted=206.476163, expected=204.029999\n",
      "predicted=205.053453, expected=205.410004\n",
      "predicted=204.159412, expected=208.779999\n",
      "predicted=207.900643, expected=205.050003\n",
      "predicted=206.336827, expected=202.910004\n",
      "predicted=203.661510, expected=200.389999\n",
      "predicted=200.761498, expected=202.539993\n",
      "predicted=201.762939, expected=207.419998\n",
      "predicted=205.859643, expected=200.589996\n",
      "predicted=202.870328, expected=203.190002\n",
      "predicted=202.541924, expected=207.820007\n",
      "predicted=205.979810, expected=209.440002\n",
      "predicted=209.373915, expected=207.259995\n",
      "predicted=208.132999, expected=210.330002\n",
      "predicted=209.520124, expected=212.460007\n",
      "predicted=211.801539, expected=206.190002\n",
      "predicted=208.344012, expected=210.380005\n",
      "predicted=209.152046, expected=205.910004\n",
      "predicted=206.883017, expected=209.830002\n",
      "predicted=208.928467, expected=210.580002\n",
      "predicted=209.982536, expected=215.809998\n",
      "predicted=214.604185, expected=221.399994\n",
      "predicted=219.862019, expected=222.860001\n",
      "predicted=223.034409, expected=220.860001\n",
      "predicted=221.862052, expected=219.660004\n",
      "predicted=220.054822, expected=219.660004\n",
      "predicted=219.521600, expected=214.220001\n",
      "predicted=215.740682, expected=214.649994\n",
      "predicted=214.382256, expected=214.800003\n",
      "predicted=214.366872, expected=214.889999\n",
      "predicted=214.967379, expected=216.229996\n",
      "predicted=215.832489, expected=210.080002\n",
      "predicted=211.907732, expected=213.250000\n",
      "predicted=212.260284, expected=202.679993\n",
      "predicted=205.423629, expected=204.720001\n",
      "predicted=204.083603, expected=202.470001\n",
      "predicted=202.344091, expected=202.330002\n",
      "predicted=202.588567, expected=206.429993\n",
      "predicted=204.953599, expected=216.389999\n",
      "predicted=213.716568, expected=223.289993\n",
      "predicted=222.209840, expected=223.720001\n",
      "predicted=224.564495, expected=218.389999\n",
      "predicted=219.908909, expected=211.009995\n",
      "predicted=212.230440, expected=216.550003\n",
      "predicted=214.462710, expected=215.440002\n",
      "predicted=215.817567, expected=216.509995\n",
      "predicted=216.795290, expected=217.229996\n",
      "predicted=216.855576, expected=214.460007\n",
      "predicted=215.281559, expected=211.080002\n",
      "predicted=211.871581, expected=212.419998\n",
      "predicted=211.777499, expected=210.389999\n",
      "predicted=210.941656, expected=210.110001\n",
      "predicted=210.350339, expected=213.860001\n",
      "predicted=212.740387, expected=213.869995\n",
      "predicted=214.065466, expected=215.229996\n",
      "predicted=215.078887, expected=214.070007\n",
      "predicted=214.255929, expected=216.210007\n",
      "predicted=215.615082, expected=215.369995\n",
      "predicted=215.556527, expected=214.240005\n",
      "predicted=214.642686, expected=214.360001\n",
      "predicted=214.165764, expected=214.289993\n",
      "predicted=214.273766, expected=216.009995\n",
      "predicted=215.618297, expected=211.800003\n",
      "predicted=212.986926, expected=210.520004\n",
      "predicted=210.788168, expected=213.259995\n",
      "predicted=212.222335, expected=214.199997\n",
      "predicted=214.156504, expected=214.130005\n",
      "predicted=214.401997, expected=219.279999\n",
      "predicted=217.846956, expected=219.419998\n",
      "predicted=219.480293, expected=218.589996\n",
      "predicted=219.040565, expected=222.589996\n",
      "predicted=221.279214, expected=223.940002\n",
      "predicted=223.609342, expected=221.020004\n",
      "predicted=222.067362, expected=222.750000\n",
      "predicted=222.100437, expected=224.960007\n",
      "predicted=224.170059, expected=224.149994\n",
      "predicted=224.623957, expected=221.679993\n",
      "predicted=222.391062, expected=222.419998\n",
      "predicted=221.990228, expected=217.690002\n",
      "predicted=218.838660, expected=217.899994\n",
      "predicted=217.840378, expected=212.250000\n",
      "predicted=213.511783, expected=218.289993\n",
      "predicted=216.667030, expected=219.619995\n",
      "predicted=219.279694, expected=217.490005\n",
      "predicted=218.622974, expected=214.929993\n",
      "predicted=215.450248, expected=216.339996\n",
      "predicted=215.640780, expected=213.020004\n",
      "predicted=213.886761, expected=212.649994\n",
      "predicted=212.848727, expected=216.440002\n",
      "predicted=215.258119, expected=224.339996\n",
      "predicted=222.480837, expected=224.970001\n",
      "predicted=225.315023, expected=225.949997\n",
      "predicted=225.910938, expected=229.529999\n",
      "predicted=228.276800, expected=232.330002\n",
      "predicted=231.618648, expected=232.899994\n",
      "predicted=232.990423, expected=238.929993\n",
      "predicted=237.437994, expected=231.960007\n",
      "predicted=233.849083, expected=239.649994\n",
      "predicted=237.605972, expected=239.509995\n",
      "predicted=239.273295, expected=243.000000\n",
      "predicted=242.611697, expected=242.009995\n",
      "predicted=242.281963, expected=242.199997\n",
      "predicted=242.185669, expected=242.470001\n",
      "predicted=242.256206, expected=243.770004\n",
      "predicted=243.433551, expected=242.820007\n",
      "predicted=243.144900, expected=244.490005\n",
      "predicted=244.071557, expected=244.990005\n",
      "predicted=244.840350, expected=243.699997\n",
      "predicted=244.153567, expected=244.199997\n",
      "predicted=244.006820, expected=243.789993\n",
      "predicted=243.812796, expected=240.970001\n",
      "predicted=241.743816, expected=234.509995\n",
      "predicted=236.037556, expected=233.270004\n",
      "predicted=233.151669, expected=234.550003\n",
      "predicted=233.919076, expected=228.990005\n",
      "predicted=230.606435, expected=232.380005\n",
      "predicted=231.456989, expected=236.940002\n",
      "predicted=235.586914, expected=233.869995\n",
      "predicted=235.178945, expected=227.559998\n",
      "predicted=229.333343, expected=226.729996\n",
      "predicted=226.370938, expected=231.600006\n",
      "predicted=230.020989, expected=227.389999\n",
      "predicted=228.761134, expected=233.779999\n",
      "predicted=232.367071, expected=232.419998\n",
      "predicted=232.670965, expected=237.130005\n",
      "predicted=236.194866, expected=235.750000\n",
      "predicted=236.147680, expected=234.809998\n",
      "predicted=235.156732, expected=237.710007\n",
      "predicted=236.763574, expected=237.039993\n",
      "predicted=237.229567, expected=230.720001\n",
      "predicted=232.534581, expected=230.350006\n",
      "predicted=230.138168, expected=235.990005\n",
      "predicted=234.159161, expected=237.580002\n",
      "predicted=237.470741, expected=235.460007\n",
      "predicted=236.431905, expected=232.339996\n",
      "predicted=233.049348, expected=236.479996\n",
      "predicted=235.136411, expected=235.240005\n",
      "predicted=235.539348, expected=231.850006\n",
      "predicted=232.962471, expected=235.770004\n",
      "predicted=234.592459, expected=242.350006\n",
      "predicted=240.535582, expected=249.070007\n",
      "predicted=247.806181, expected=247.860001\n",
      "predicted=248.604770, expected=249.899994\n",
      "predicted=249.520362, expected=253.250000\n",
      "predicted=252.287711, expected=255.850006\n",
      "predicted=255.368537, expected=255.910004\n",
      "predicted=256.129829, expected=258.489990\n",
      "predicted=257.958215, expected=255.589996\n",
      "predicted=256.343387, expected=259.500000\n",
      "predicted=258.558150, expected=260.739990\n",
      "predicted=260.392719, expected=258.739990\n",
      "predicted=259.469427, expected=258.260010\n",
      "predicted=258.379393, expected=260.579987\n",
      "predicted=259.864353, expected=257.170013\n",
      "predicted=258.056454, expected=261.149994\n",
      "predicted=260.195398, expected=261.549988\n",
      "predicted=261.381821, expected=261.970001\n",
      "predicted=262.081308, expected=254.559998\n",
      "predicted=256.450915, expected=252.509995\n",
      "predicted=252.791430, expected=252.179993\n",
      "predicted=251.845496, expected=251.860001\n",
      "predicted=251.866262, expected=247.789993\n",
      "predicted=248.815866, expected=246.470001\n",
      "predicted=246.665940, expected=249.729996\n",
      "predicted=248.698339, expected=252.460007\n",
      "predicted=251.828040, expected=247.179993\n",
      "predicted=248.716456, expected=246.229996\n",
      "predicted=246.473451, expected=239.000000\n",
      "predicted=240.472532, expected=243.029999\n",
      "predicted=241.804179, expected=248.149994\n",
      "predicted=246.720318, expected=245.179993\n",
      "predicted=246.203360, expected=243.080002\n",
      "predicted=243.720108, expected=243.119995\n",
      "predicted=242.954462, expected=246.479996\n",
      "predicted=245.602756, expected=245.169998\n",
      "predicted=245.536769, expected=250.779999\n",
      "predicted=249.514832, expected=251.720001\n",
      "predicted=251.555268, expected=251.490005\n",
      "predicted=251.790473, expected=249.309998\n",
      "predicted=249.863710, expected=249.679993\n",
      "predicted=249.539552, expected=247.399994\n",
      "predicted=247.875645, expected=247.300003\n",
      "predicted=247.294436, expected=245.710007\n",
      "predicted=246.007004, expected=250.789993\n",
      "predicted=249.524553, expected=253.809998\n",
      "predicted=253.136081, expected=252.570007\n",
      "predicted=253.116656, expected=253.589996\n",
      "predicted=253.421136, expected=257.239990\n",
      "predicted=256.324724, expected=257.890015\n",
      "predicted=257.842575, expected=259.890015\n",
      "predicted=259.568357, expected=258.359985\n",
      "predicted=258.793791, expected=257.380005\n",
      "predicted=257.655318, expected=260.899994\n",
      "predicted=259.979269, expected=259.429993\n",
      "predicted=259.816098, expected=262.630005\n",
      "predicted=261.964314, expected=265.510010\n",
      "predicted=264.829855, expected=265.269989\n",
      "predicted=265.517025, expected=266.690002\n",
      "predicted=266.459744, expected=265.019989\n",
      "predicted=265.440689, expected=268.720001\n",
      "predicted=267.860392, expected=271.399994\n",
      "predicted=270.775836, expected=270.899994\n",
      "predicted=271.229406, expected=271.600006\n",
      "predicted=271.527900, expected=277.649994\n",
      "predicted=276.226547, expected=277.660004\n",
      "predicted=277.830789, expected=279.929993\n",
      "predicted=279.656624, expected=277.420013\n",
      "predicted=278.094723, expected=277.940002\n",
      "predicted=277.878303, expected=277.320007\n",
      "predicted=277.383141, expected=280.980011\n",
      "predicted=280.117179, expected=282.510010\n",
      "predicted=282.200258, expected=281.029999\n",
      "predicted=281.563860, expected=280.750000\n",
      "predicted=280.854777, expected=277.010010\n",
      "predicted=277.848452, expected=279.320007\n",
      "predicted=278.680780, expected=281.399994\n",
      "predicted=280.806234, expected=286.140015\n",
      "predicted=285.156022, expected=289.670013\n",
      "predicted=289.031778, expected=289.049988\n",
      "predicted=289.468771, expected=286.540009\n",
      "predicted=287.228873, expected=286.220001\n",
      "predicted=286.216557, expected=286.500000\n",
      "predicted=286.353140, expected=284.910004\n",
      "predicted=285.278642, expected=284.820007\n",
      "predicted=284.806497, expected=287.119995\n",
      "predicted=286.527531, expected=286.510010\n",
      "predicted=286.707372, expected=289.519989\n",
      "predicted=288.886411, expected=289.459991\n",
      "predicted=289.517990, expected=288.329987\n",
      "predicted=288.703299, expected=286.440002\n",
      "predicted=286.835910, expected=286.950012\n",
      "predicted=286.751916, expected=289.809998\n",
      "predicted=289.099937, expected=292.850006\n",
      "predicted=292.240610, expected=294.600006\n",
      "predicted=294.363405, expected=293.079987\n",
      "predicted=293.556980, expected=290.730011\n",
      "predicted=291.273927, expected=296.769989\n",
      "predicted=295.281518, expected=304.359985\n",
      "predicted=302.718476, expected=304.649994\n",
      "predicted=304.929227, expected=302.619995\n",
      "predicted=303.267860, expected=302.010010\n",
      "predicted=302.148370, expected=299.089996\n",
      "predicted=299.718078, expected=299.720001\n",
      "predicted=299.517113, expected=303.589996\n",
      "predicted=302.655584, expected=301.880005\n",
      "predicted=302.366350, expected=301.829987\n",
      "predicted=301.888385, expected=301.149994\n",
      "predicted=301.236083, expected=301.140015\n",
      "predicted=301.164127, expected=300.179993\n",
      "predicted=300.366211, expected=300.209991\n",
      "predicted=300.188912, expected=297.250000\n",
      "predicted=297.881473, expected=295.709991\n",
      "predicted=296.001512, expected=296.989990\n",
      "predicted=296.592043, expected=299.790009\n",
      "predicted=299.171748, expected=304.820007\n",
      "predicted=303.793365, expected=305.220001\n",
      "predicted=305.281010, expected=299.869995\n",
      "predicted=301.142602, expected=294.299988\n",
      "predicted=295.370593, expected=294.799988\n",
      "predicted=294.525132, expected=298.579987\n",
      "predicted=297.766577, expected=299.559998\n",
      "predicted=299.453020, expected=299.350006\n",
      "predicted=299.411496, expected=294.170013\n",
      "predicted=295.241482, expected=283.519989\n",
      "predicted=285.676815, expected=284.000000\n",
      "predicted=283.705846, expected=281.920013\n",
      "predicted=282.360056, expected=289.100006\n",
      "predicted=287.817909, expected=283.109985\n",
      "predicted=284.369326, expected=288.760010\n",
      "predicted=287.500093, expected=293.109985\n",
      "predicted=292.100041, expected=294.850006\n",
      "predicted=294.744102, expected=294.850006\n",
      "predicted=294.759909, expected=294.230011\n",
      "predicted=294.310728, expected=292.880005\n",
      "predicted=293.133418, expected=296.309998\n",
      "predicted=295.576624, expected=302.750000\n",
      "predicted=301.488673, expected=304.209991\n",
      "predicted=304.064318, expected=307.290009\n",
      "predicted=306.640904, expected=308.230011\n",
      "predicted=308.013920, expected=307.410004\n",
      "predicted=307.626546, expected=310.760010\n",
      "predicted=310.020985, expected=309.160004\n",
      "predicted=309.564776, expected=308.130005\n",
      "predicted=308.348243, expected=310.109985\n",
      "predicted=309.601998, expected=323.170013\n",
      "predicted=320.626823, expected=324.350006\n",
      "predicted=324.415150, expected=331.619995\n",
      "predicted=330.309889, expected=329.369995\n",
      "predicted=329.841586, expected=333.130005\n",
      "predicted=332.490983, expected=334.000000\n",
      "predicted=333.869784, expected=336.440002\n",
      "predicted=336.142907, expected=336.059998\n",
      "predicted=336.163153, expected=336.989990\n",
      "predicted=336.856294, expected=335.950012\n",
      "predicted=336.167955, expected=330.799988\n",
      "predicted=331.798083, expected=332.429993\n",
      "predicted=331.911902, expected=336.720001\n",
      "predicted=335.924220, expected=336.070007\n",
      "predicted=336.388947, expected=339.510010\n",
      "predicted=338.785315, expected=339.119995\n",
      "predicted=339.270912, expected=341.269989\n",
      "predicted=340.924950, expected=343.109985\n",
      "predicted=342.780875, expected=339.829987\n",
      "predicted=340.590491, expected=337.679993\n",
      "predicted=337.969043, expected=337.910004\n",
      "predicted=337.767247, expected=329.679993\n",
      "predicted=331.307035, expected=336.630005\n",
      "predicted=334.982425, expected=330.589996\n",
      "predicted=331.940266, expected=330.079987\n",
      "predicted=330.157146, expected=329.489990\n",
      "predicted=329.331076, expected=323.010010\n",
      "predicted=324.465028, expected=326.190002\n",
      "predicted=325.211481, expected=334.920013\n",
      "predicted=333.229524, expected=334.970001\n",
      "predicted=335.403014, expected=333.100006\n",
      "predicted=333.431481, expected=342.540009\n",
      "predicted=340.508506, expected=339.399994\n",
      "predicted=340.334084, expected=328.339996\n",
      "predicted=330.669966, expected=334.649994\n",
      "predicted=332.927566, expected=324.899994\n",
      "predicted=326.815816, expected=323.799988\n",
      "predicted=324.202763, expected=319.910004\n",
      "predicted=320.335476, expected=327.290009\n",
      "predicted=325.727626, expected=333.200012\n",
      "predicted=332.265422, expected=334.690002\n",
      "predicted=334.814729, expected=342.450012\n",
      "predicted=340.985366, expected=341.250000\n",
      "predicted=341.548354, expected=341.950012\n",
      "predicted=341.850176, expected=339.320007\n",
      "predicted=339.604619, expected=336.320007\n",
      "predicted=336.745458, expected=334.750000\n",
      "predicted=334.884596, expected=329.010010\n",
      "predicted=330.050340, expected=316.380005\n",
      "predicted=318.554029, expected=313.880005\n",
      "predicted=313.652765, expected=314.040009\n",
      "predicted=313.678257, expected=314.269989\n",
      "predicted=314.558899, expected=314.980011\n",
      "predicted=315.121441, expected=318.269989\n",
      "predicted=317.760184, expected=304.799988\n",
      "predicted=307.433624, expected=310.200012\n",
      "predicted=308.666499, expected=302.649994\n",
      "predicted=303.860112, expected=303.329987\n",
      "predicted=303.286026, expected=301.600006\n",
      "predicted=301.828872, expected=296.029999\n",
      "predicted=297.146140, expected=296.369995\n",
      "predicted=296.020980, expected=288.489990\n",
      "predicted=289.829077, expected=296.709991\n",
      "predicted=294.875227, expected=299.839996\n",
      "predicted=299.478628, expected=308.260010\n",
      "predicted=307.335860, expected=310.980011\n",
      "predicted=310.892039, expected=308.760010\n",
      "predicted=309.347733, expected=313.459991\n",
      "predicted=312.249261, expected=301.250000\n",
      "predicted=303.549782, expected=305.940002\n",
      "predicted=304.482006, expected=300.950012\n",
      "predicted=301.729667, expected=304.559998\n",
      "predicted=304.094117, expected=311.209991\n",
      "predicted=309.963239, expected=302.380005\n",
      "predicted=304.812139, expected=295.040009\n",
      "predicted=295.921998, expected=295.000000\n",
      "predicted=294.088999, expected=300.470001\n",
      "predicted=299.688506, expected=299.500000\n",
      "predicted=300.279437, expected=290.730011\n",
      "predicted=292.358713, expected=287.929993\n",
      "predicted=287.828618, expected=287.720001\n",
      "predicted=287.592814, expected=280.269989\n",
      "predicted=281.850126, expected=294.589996\n",
      "predicted=291.583965, expected=297.309998\n",
      "predicted=297.375113, expected=298.790009\n",
      "predicted=299.183712, expected=294.950012\n",
      "predicted=295.127227, expected=300.190002\n",
      "predicted=298.918697, expected=295.920013\n",
      "predicted=296.848942, expected=289.859985\n",
      "predicted=291.005036, expected=278.910004\n",
      "predicted=280.368426, expected=275.850006\n",
      "predicted=275.879759, expected=288.500000\n",
      "predicted=286.371091, expected=285.589996\n",
      "predicted=287.087714, expected=280.070007\n",
      "predicted=281.082668, expected=276.440002\n",
      "predicted=276.447771, expected=287.149994\n",
      "predicted=285.281515, expected=294.390015\n",
      "predicted=293.529153, expected=295.220001\n",
      "predicted=295.193064, expected=300.429993\n",
      "predicted=299.199858, expected=299.160004\n",
      "predicted=299.473853, expected=304.059998\n",
      "predicted=303.265518, expected=299.489990\n",
      "predicted=300.328614, expected=304.100006\n",
      "predicted=303.232656, expected=303.679993\n",
      "predicted=303.792410, expected=310.700012\n",
      "predicted=309.611966, expected=315.410004\n",
      "predicted=314.682202, expected=313.859985\n",
      "predicted=314.354484, expected=308.309998\n",
      "predicted=308.998508, expected=309.420013\n",
      "predicted=309.056660, expected=314.970001\n",
      "predicted=314.224272, expected=310.880005\n",
      "predicted=311.826993, expected=299.500000\n",
      "predicted=301.148565, expected=301.369995\n",
      "predicted=300.743186, expected=296.970001\n",
      "predicted=298.013884, expected=285.260010\n",
      "predicted=287.147487, expected=282.059998\n",
      "predicted=281.982420, expected=287.619995\n",
      "predicted=286.648933, expected=279.829987\n",
      "predicted=281.236115, expected=280.519989\n",
      "predicted=280.116075, expected=285.299988\n",
      "predicted=284.388909, expected=286.359985\n",
      "predicted=286.378961, expected=280.809998\n",
      "predicted=281.764570, expected=274.029999\n",
      "predicted=275.019310, expected=280.720001\n",
      "predicted=279.484497, expected=270.220001\n",
      "predicted=272.083829, expected=283.220001\n",
      "predicted=280.672105, expected=289.630005\n",
      "predicted=288.656722, expected=277.519989\n",
      "predicted=280.121379, expected=284.470001\n",
      "predicted=282.885746, expected=281.779999\n",
      "predicted=282.163166, expected=289.980011\n",
      "predicted=288.787044, expected=277.350006\n",
      "predicted=279.654994, expected=274.730011\n",
      "predicted=275.221103, expected=264.579987\n",
      "predicted=266.196858, expected=269.500000\n",
      "predicted=268.505855, expected=260.549988\n",
      "predicted=262.155176, expected=255.350006\n",
      "predicted=255.996048, expected=261.119995\n",
      "predicted=259.708296, expected=261.500000\n",
      "predicted=261.549283, expected=266.820007\n",
      "predicted=265.796915, expected=254.080002\n",
      "predicted=256.489564, expected=253.139999\n",
      "predicted=253.167738, expected=252.559998\n",
      "predicted=252.621606, expected=260.649994\n",
      "predicted=259.220021, expected=259.619995\n",
      "predicted=259.688784, expected=262.519989\n",
      "predicted=261.919285, expected=265.899994\n",
      "predicted=265.371457, expected=273.239990\n",
      "predicted=272.159937, expected=271.869995\n",
      "predicted=272.301944, expected=272.420013\n",
      "predicted=272.369846, expected=274.579987\n",
      "predicted=274.339010, expected=270.019989\n",
      "predicted=271.036145, expected=268.750000\n",
      "predicted=268.845740, expected=272.500000\n",
      "predicted=271.811003, expected=270.410004\n",
      "predicted=270.885674, expected=264.790009\n",
      "predicted=265.675623, expected=252.990005\n",
      "predicted=254.935768, expected=242.259995\n",
      "predicted=243.723386, expected=244.490005\n",
      "predicted=243.699996, expected=251.759995\n",
      "predicted=250.544246, expected=244.970001\n",
      "predicted=245.913604, expected=247.649994\n",
      "predicted=246.793361, expected=253.740005\n",
      "predicted=252.862131, expected=253.130005\n",
      "predicted=253.442500, expected=258.859985\n",
      "predicted=257.774723, expected=267.700012\n",
      "predicted=266.471797, expected=264.890015\n",
      "predicted=265.688112, expected=256.480011\n",
      "predicted=257.848700, expected=260.260010\n",
      "predicted=259.598952, expected=256.829987\n",
      "predicted=257.522440, expected=259.579987\n",
      "predicted=258.988226, expected=262.850006\n",
      "predicted=262.275738, expected=266.209991\n",
      "predicted=265.747044, expected=268.399994\n",
      "predicted=268.095948, expected=267.660004\n",
      "predicted=267.869322, expected=264.510010\n",
      "predicted=265.049796, expected=253.669998\n",
      "predicted=255.377096, expected=252.720001\n",
      "predicted=252.648121, expected=254.080002\n",
      "predicted=253.851939, expected=256.720001\n",
      "predicted=256.341273, expected=254.250000\n",
      "predicted=254.637116, expected=259.529999\n",
      "predicted=258.617401, expected=262.269989\n",
      "predicted=261.942207, expected=264.839996\n",
      "predicted=264.489591, expected=260.359985\n",
      "predicted=261.113702, expected=258.829987\n",
      "predicted=258.980832, expected=251.899994\n",
      "predicted=252.975872, expected=268.739990\n",
      "predicted=265.847458, expected=276.410004\n",
      "predicted=275.552478, expected=280.739990\n",
      "predicted=280.059207, expected=278.010010\n",
      "predicted=278.306167, expected=274.820007\n",
      "predicted=275.181538, expected=282.470001\n",
      "predicted=281.354969, expected=283.649994\n",
      "predicted=283.715747, expected=282.910004\n",
      "predicted=282.896979, expected=280.320007\n",
      "predicted=280.627970, expected=282.299988\n",
      "predicted=282.064324, expected=289.160004\n",
      "predicted=288.209184, expected=287.019989\n",
      "predicted=287.407931, expected=291.910004\n",
      "predicted=290.971312, expected=293.470001\n",
      "predicted=293.378233, expected=292.709991\n",
      "predicted=292.887005, expected=291.320007\n",
      "predicted=291.461062, expected=290.170013\n",
      "predicted=290.405608, expected=286.149994\n",
      "predicted=286.785179, expected=277.750000\n",
      "predicted=278.942462, expected=276.440002\n",
      "predicted=276.512181, expected=275.790009\n",
      "predicted=275.965252, expected=278.850006\n",
      "predicted=278.365123, expected=268.089996\n",
      "predicted=269.634455, expected=265.230011\n",
      "predicted=265.376831, expected=262.970001\n",
      "predicted=263.398186, expected=261.470001\n",
      "predicted=261.684426, expected=260.399994\n",
      "predicted=260.338369, expected=256.059998\n",
      "predicted=256.612356, expected=253.250000\n",
      "predicted=253.512952, expected=258.089996\n",
      "predicted=257.336207, expected=258.519989\n",
      "predicted=258.540583, expected=264.459991\n",
      "predicted=263.437883, expected=266.649994\n",
      "predicted=266.430257, expected=251.990005\n",
      "predicted=254.203151, expected=252.220001\n",
      "predicted=251.911602, expected=245.380005\n",
      "predicted=246.715008, expected=244.740005\n",
      "predicted=244.746195, expected=244.520004\n",
      "predicted=244.340656, expected=242.449997\n",
      "predicted=242.767640, expected=238.949997\n",
      "predicted=239.259217, expected=240.979996\n",
      "predicted=240.619163, expected=237.919998\n",
      "predicted=238.447427, expected=237.449997\n",
      "predicted=237.377767, expected=236.410004\n",
      "predicted=236.511469, expected=241.070007\n",
      "predicted=240.419813, expected=237.500000\n",
      "predicted=238.079336, expected=232.899994\n",
      "predicted=233.412940, expected=240.740005\n",
      "predicted=239.518820, expected=248.880005\n",
      "predicted=248.010001, expected=249.199997\n",
      "predicted=249.122820, expected=246.789993\n",
      "predicted=246.954062, expected=234.240005\n",
      "predicted=236.115226, expected=229.250000\n",
      "predicted=229.900647, expected=225.410004\n",
      "predicted=226.088030, expected=225.750000\n",
      "predicted=225.754180, expected=234.240005\n",
      "predicted=233.064519, expected=228.559998\n",
      "predicted=229.440377, expected=237.529999\n",
      "predicted=235.901532, expected=238.500000\n",
      "predicted=238.589952, expected=236.479996\n",
      "predicted=236.813783, expected=236.149994\n",
      "predicted=235.913481, expected=242.119995\n",
      "predicted=241.454809, expected=247.250000\n",
      "predicted=246.731554, expected=250.660004\n",
      "predicted=250.166916, expected=231.320007\n",
      "predicted=233.827615, expected=226.750000\n",
      "predicted=226.985417, expected=235.869995\n",
      "predicted=235.276360, expected=232.130005\n",
      "predicted=233.098726, expected=228.169998\n",
      "predicted=228.068368, expected=220.100006\n",
      "predicted=221.089399, expected=214.250000\n",
      "predicted=215.351042, expected=221.389999\n",
      "predicted=220.547221, expected=227.869995\n",
      "predicted=227.188017, expected=228.869995\n",
      "predicted=228.326357, expected=224.509995\n",
      "predicted=224.593410, expected=242.979996\n",
      "predicted=240.681220, expected=247.110001\n",
      "predicted=246.965357, expected=241.550003\n",
      "predicted=241.794780, expected=241.970001\n",
      "predicted=241.715706, expected=241.729996\n",
      "predicted=242.456593, expected=241.679993\n",
      "predicted=241.789254, expected=241.220001\n",
      "predicted=241.126420, expected=242.050003\n",
      "predicted=241.957180, expected=245.029999\n",
      "predicted=244.649753, expected=247.580002\n",
      "predicted=247.223148, expected=247.490005\n",
      "predicted=247.406585, expected=241.759995\n",
      "predicted=242.452074, expected=240.330002\n",
      "predicted=240.617774, expected=255.139999\n",
      "predicted=253.475024, expected=254.690002\n",
      "predicted=254.659029, expected=255.020004\n",
      "predicted=254.384814, expected=250.199997\n",
      "predicted=250.821676, expected=245.119995\n",
      "predicted=246.266569, expected=244.369995\n",
      "predicted=244.638165, expected=247.399994\n",
      "predicted=247.206160, expected=245.419998\n",
      "predicted=245.531676, expected=252.509995\n",
      "predicted=251.378429, expected=256.920013\n",
      "predicted=256.346545, expected=257.220001\n",
      "predicted=257.019035, expected=249.009995\n",
      "predicted=249.811484, expected=244.690002\n",
      "predicted=245.449480, expected=240.449997\n",
      "predicted=241.398648, expected=241.800003\n",
      "predicted=241.881563, expected=244.429993\n",
      "predicted=244.088210, expected=238.190002\n",
      "predicted=238.799211, expected=238.729996\n",
      "predicted=238.495954, expected=236.960007\n",
      "predicted=237.417325, expected=234.529999\n",
      "predicted=234.933550, expected=241.009995\n",
      "predicted=240.112188, expected=239.820007\n",
      "predicted=240.031171, expected=239.580002\n",
      "predicted=239.364255, expected=229.100006\n",
      "predicted=230.325699, expected=222.309998\n",
      "predicted=223.405572, expected=224.929993\n",
      "predicted=225.032992, expected=227.119995\n",
      "predicted=227.195857, expected=228.850006\n",
      "predicted=228.282065, expected=235.770004\n",
      "predicted=234.638612, expected=238.509995\n",
      "predicted=238.105935, expected=239.229996\n",
      "predicted=238.892638, expected=240.350006\n",
      "predicted=240.064380, expected=235.809998\n",
      "predicted=236.436052, expected=231.929993\n",
      "predicted=232.421707, expected=240.220001\n",
      "predicted=239.447504, expected=242.580002\n",
      "predicted=242.471140, expected=242.039993\n",
      "predicted=241.705027, expected=240.610001\n",
      "predicted=240.477757, expected=248.000000\n",
      "predicted=247.326165, expected=248.160004\n",
      "predicted=248.183485, expected=242.710007\n",
      "predicted=243.070191, expected=247.809998\n",
      "predicted=247.146684, expected=252.750000\n",
      "predicted=252.461362, expected=264.600006\n",
      "predicted=263.047498, expected=258.350006\n",
      "predicted=258.560371, expected=256.769989\n",
      "predicted=256.642078, expected=267.559998\n",
      "predicted=266.624327, expected=266.730011\n",
      "predicted=267.102896, expected=263.619995\n",
      "predicted=263.456842, expected=263.100006\n",
      "predicted=263.159101, expected=271.320007\n",
      "predicted=270.769878, expected=272.170013\n",
      "predicted=271.912962, expected=269.320007\n",
      "predicted=269.260533, expected=262.149994\n",
      "predicted=263.003072, expected=258.059998\n",
      "predicted=259.018804, expected=252.669998\n",
      "predicted=253.642508, expected=251.509995\n",
      "predicted=251.804221, expected=254.770004\n",
      "predicted=254.437712, expected=249.220001\n",
      "predicted=249.726151, expected=250.160004\n",
      "predicted=249.874693, expected=249.419998\n",
      "predicted=249.650910, expected=246.270004\n",
      "predicted=246.708931, expected=251.110001\n",
      "predicted=250.467723, expected=255.289993\n",
      "predicted=254.870417, expected=256.869995\n",
      "predicted=256.437341, expected=254.149994\n",
      "predicted=254.182269, expected=253.699997\n",
      "predicted=253.869458, expected=252.320007\n",
      "predicted=252.694947, expected=248.589996\n",
      "predicted=249.101439, expected=253.919998\n",
      "predicted=253.354286, expected=260.790009\n",
      "predicted=260.049406, expected=265.440002\n",
      "predicted=264.590319, expected=276.200012\n",
      "predicted=274.626355, expected=279.429993\n",
      "predicted=278.923534, expected=272.230011\n",
      "predicted=272.699759, expected=273.779999\n",
      "predicted=273.647732, expected=272.290009\n",
      "predicted=272.891412, expected=277.660004\n",
      "predicted=277.182351, expected=280.570007\n",
      "predicted=280.040363, expected=276.380005\n",
      "predicted=276.646916, expected=275.230011\n",
      "predicted=275.231725, expected=280.510010\n",
      "predicted=280.234514, expected=284.049988\n",
      "predicted=283.733437, expected=288.299988\n",
      "predicted=287.501314, expected=287.230011\n",
      "predicted=287.082298, expected=287.179993\n",
      "predicted=287.174630, expected=284.339996\n",
      "predicted=284.743648, expected=291.600006\n",
      "predicted=291.005142, expected=289.390015\n",
      "predicted=289.587709, expected=282.829987\n",
      "predicted=283.317879, expected=283.489990\n",
      "predicted=283.491020, expected=289.839996\n",
      "predicted=289.604353, expected=286.140015\n",
      "predicted=286.351091, expected=288.799988\n",
      "predicted=288.184065, expected=288.369995\n",
      "predicted=288.486943, expected=288.450012\n",
      "predicted=288.538919, expected=286.109985\n",
      "predicted=286.269314, expected=285.760010\n",
      "predicted=285.909386, expected=281.769989\n",
      "predicted=282.275732, expected=275.420013\n",
      "predicted=276.187512, expected=295.369995\n",
      "predicted=293.365474, expected=304.829987\n",
      "predicted=303.626069, expected=307.260010\n",
      "predicted=305.988278, expected=305.559998\n",
      "predicted=305.014297, expected=305.410004\n",
      "predicted=305.778758, expected=304.399994\n",
      "predicted=304.765685, expected=305.410004\n",
      "predicted=305.404430, expected=310.649994\n",
      "predicted=310.105212, expected=308.649994\n",
      "predicted=308.699499, expected=307.000000\n",
      "predicted=306.972553, expected=312.309998\n",
      "predicted=311.875108, expected=310.109985\n",
      "predicted=310.410298, expected=308.970001\n",
      "predicted=308.901454, expected=309.459991\n",
      "predicted=309.442279, expected=311.739990\n",
      "predicted=311.677176, expected=314.000000\n",
      "predicted=313.658359, expected=318.519989\n",
      "predicted=317.899987, expected=318.339996\n",
      "predicted=318.163897, expected=321.179993\n",
      "predicted=320.765874, expected=315.260010\n",
      "predicted=315.814551, expected=313.850006\n",
      "predicted=314.113551, expected=325.920013\n",
      "predicted=324.928346, expected=332.890015\n",
      "predicted=332.071173, expected=331.209991\n",
      "predicted=330.581870, expected=328.390015\n",
      "predicted=328.307072, expected=332.579987\n",
      "predicted=332.577709, expected=335.399994\n",
      "predicted=335.310608, expected=335.940002\n",
      "predicted=335.611440, expected=333.679993\n",
      "predicted=333.683996, expected=323.380005\n",
      "predicted=324.512393, expected=325.260010\n",
      "predicted=325.533765, expected=326.790009\n",
      "predicted=327.041870, expected=331.850006\n",
      "predicted=331.234487, expected=334.290009\n",
      "predicted=333.552700, expected=337.339996\n",
      "predicted=336.803394, expected=348.100006\n",
      "predicted=346.932129, expected=342.329987\n",
      "predicted=342.590214, expected=338.049988\n",
      "predicted=338.207637, expected=333.559998\n",
      "predicted=334.337998, expected=339.709991\n",
      "predicted=339.759062, expected=335.019989\n",
      "predicted=335.383746, expected=328.600006\n",
      "predicted=328.988009, expected=334.570007\n",
      "predicted=334.249341, expected=335.850006\n",
      "predicted=335.978476, expected=335.049988\n",
      "predicted=334.752238, expected=340.540009\n",
      "predicted=339.807489, expected=337.989990\n",
      "predicted=338.228473, expected=338.149994\n",
      "predicted=338.024474, expected=341.269989\n",
      "predicted=341.013059, expected=337.220001\n",
      "predicted=337.654511, expected=331.829987\n",
      "predicted=332.298511, expected=332.470001\n",
      "predicted=332.724056, expected=337.200012\n",
      "predicted=337.032572, expected=342.660004\n",
      "predicted=341.904703, expected=345.239990\n",
      "predicted=344.501889, expected=345.730011\n",
      "predicted=345.353286, expected=359.489990\n",
      "predicted=358.173489, expected=355.079987\n",
      "predicted=355.172077, expected=346.869995\n",
      "predicted=347.312515, expected=343.769989\n",
      "predicted=344.438980, expected=345.109985\n",
      "predicted=345.716806, expected=350.980011\n",
      "predicted=350.481691, expected=337.769989\n",
      "predicted=338.577498, expected=330.720001\n",
      "predicted=331.535327, expected=338.369995\n",
      "predicted=338.498451, expected=335.920013\n",
      "predicted=336.285022, expected=336.339996\n",
      "predicted=335.767535, expected=327.500000\n",
      "predicted=328.211701, expected=326.660004\n",
      "predicted=327.313034, expected=327.779999\n",
      "predicted=327.987742, expected=330.109985\n",
      "predicted=329.886616, expected=326.049988\n",
      "predicted=326.013980, expected=322.230011\n",
      "predicted=322.632724, expected=322.929993\n",
      "predicted=323.228271, expected=321.010010\n",
      "predicted=321.385407, expected=324.040009\n",
      "predicted=323.661291, expected=321.859985\n",
      "predicted=321.897985, expected=320.399994\n",
      "predicted=320.520493, expected=316.880005\n",
      "predicted=317.302804, expected=316.480011\n",
      "predicted=316.814814, expected=321.880005\n",
      "predicted=321.457251, expected=322.459991\n",
      "predicted=322.147496, expected=327.000000\n",
      "predicted=326.205102, expected=319.970001\n",
      "predicted=320.424139, expected=322.980011\n",
      "predicted=322.959935, expected=323.700012\n",
      "predicted=323.843014, expected=328.410004\n",
      "predicted=327.940129, expected=328.790009\n",
      "predicted=328.297904, expected=327.760010\n",
      "predicted=327.742376, expected=328.660004\n",
      "predicted=328.633423, expected=333.549988\n",
      "predicted=333.263341, expected=332.880005\n",
      "predicted=332.722577, expected=329.910004\n",
      "predicted=329.970428, expected=334.269989\n",
      "predicted=334.048733, expected=337.940002\n",
      "predicted=337.714733, expected=331.769989\n",
      "predicted=331.988417, expected=336.059998\n",
      "predicted=335.657122, expected=338.700012\n",
      "predicted=338.687026, expected=330.220001\n",
      "predicted=330.862430, expected=329.059998\n",
      "predicted=329.251242, expected=328.649994\n",
      "predicted=329.226148, expected=320.769989\n",
      "predicted=321.650369, expected=319.529999\n",
      "predicted=319.734448, expected=317.010010\n",
      "predicted=317.553891, expected=317.540009\n",
      "predicted=317.597057, expected=312.140015\n",
      "predicted=312.468484, expected=312.790009\n",
      "predicted=312.874893, expected=313.640015\n",
      "predicted=313.651173, expected=315.750000\n",
      "predicted=315.477091, expected=321.799988\n",
      "predicted=320.940501, expected=313.390015\n",
      "predicted=313.902636, expected=318.959991\n",
      "predicted=318.564712, expected=319.359985\n",
      "predicted=319.496371, expected=327.260010\n",
      "predicted=326.409084, expected=329.820007\n",
      "predicted=328.985467, expected=328.390015\n",
      "predicted=328.327682, expected=332.420013\n",
      "predicted=332.044326, expected=331.160004\n",
      "predicted=331.478912, expected=327.730011\n",
      "predicted=328.048657, expected=332.640015\n",
      "predicted=332.304177, expected=332.059998\n",
      "predicted=332.185124, expected=330.109985\n",
      "predicted=330.090765, expected=331.320007\n",
      "predicted=331.199100, expected=326.670013\n",
      "predicted=327.321291, expected=329.320007\n",
      "predicted=329.169888, expected=330.529999\n",
      "predicted=330.405057, expected=340.670013\n",
      "predicted=339.556600, expected=327.890015\n",
      "predicted=328.612179, expected=329.809998\n",
      "predicted=329.817477, expected=337.309998\n",
      "predicted=337.013485, expected=338.109985\n",
      "predicted=337.915928, expected=346.070007\n",
      "predicted=344.471229, expected=348.320007\n",
      "predicted=347.841897, expected=352.799988\n",
      "predicted=352.276525, expected=356.529999\n",
      "predicted=355.990205, expected=360.529999\n",
      "predicted=360.181318, expected=363.200012\n",
      "predicted=362.801294, expected=360.690002\n",
      "predicted=360.917637, expected=369.670013\n",
      "predicted=368.974284, expected=366.679993\n",
      "predicted=366.926874, expected=370.269989\n",
      "predicted=369.829331, expected=369.670013\n",
      "predicted=369.670294, expected=376.170013\n",
      "predicted=375.764254, expected=369.850006\n",
      "predicted=370.222134, expected=377.440002\n",
      "predicted=376.776483, expected=373.070007\n",
      "predicted=373.555235, expected=377.850006\n",
      "predicted=377.387075, expected=377.429993\n",
      "predicted=377.338005, expected=378.609985\n",
      "predicted=378.565627, expected=382.700012\n",
      "predicted=382.141386, expected=378.850006\n",
      "predicted=379.280764, expected=378.910004\n",
      "predicted=378.879906, expected=374.510010\n",
      "predicted=375.195569, expected=369.140015\n",
      "predicted=369.941061, expected=372.519989\n",
      "predicted=372.314382, expected=368.799988\n",
      "predicted=369.224026, expected=370.950012\n",
      "predicted=370.487535, expected=374.230011\n",
      "predicted=373.764434, expected=371.299988\n",
      "predicted=371.546494, expected=374.380005\n",
      "predicted=373.904124, expected=374.369995\n",
      "predicted=374.490272, expected=365.929993\n",
      "predicted=366.836152, expected=370.730011\n",
      "predicted=370.371533, expected=372.649994\n",
      "predicted=372.675773, expected=373.260010\n",
      "predicted=372.925743, expected=370.619995\n",
      "predicted=370.532799, expected=373.540009\n",
      "predicted=373.489326, expected=374.579987\n",
      "predicted=374.540020, expected=374.660004\n",
      "predicted=374.530448, expected=374.070007\n",
      "predicted=374.023187, expected=375.279999\n",
      "predicted=375.287671, expected=376.040009\n",
      "Test RMSE: 4.503\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "import yfinance as yf\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from math import sqrt\n",
    "\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")  # To ignore warnings from ARIMA\n",
    "\n",
    "\n",
    "# Step 1: Download Microsoft stock data\n",
    "msft = yf.download('MSFT', start='2010-01-01', end='2024-01-01')\n",
    "\n",
    "\n",
    "# Step 2: Extract the 'Close' prices to use as our time series\n",
    "msft_close = msft['Close']\n",
    "\n",
    "\n",
    "# Step 3: Ensure all datetimes are timezone-naive\n",
    "msft_close.index = msft_close.index.tz_localize(None)\n",
    "\n",
    "\n",
    "# Step 4: Plot the data to visualize the time series\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(msft_close, label='Microsoft Closing Price')\n",
    "plt.title('Microsoft Stock Closing Price')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Price (USD)')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# Step 5: Walk-forward validation for ARIMA model\n",
    "# Split data into train and test sets\n",
    "X = msft_close.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",
    "\n",
    "\n",
    "# Walk-forward validation\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)\n",
    "    print('predicted=%f, expected=%f' % (yhat, obs))\n",
    "\n",
    "\n",
    "# Evaluate forecasts\n",
    "rmse = sqrt(mean_squared_error(test, predictions))\n",
    "print('Test RMSE: %.3f' % rmse)\n",
    "\n",
    "\n",
    "# Step 6: Plot the predictions against the actual values\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(msft_close.index[size:], test, label='Actual Stock Price', color='blue')\n",
    "plt.plot(msft_close.index[size:], predictions, label='Predicted Stock Price', color='red')\n",
    "plt.title('ARIMA Model Walk-Forward Validation Predictions')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Price (USD)')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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