notebooks/7.2_AG_ARIMA.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a6ab4558-8edf-4b23-8a50-6da80b136a5b",
   "metadata": {},
   "source": [
    "# Deterministic forecasting of the silver price using ARIMA method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbfe300f-a15c-4363-82a5-45b708a194df",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5ba52249-cd78-40b5-b0c5-098977d635e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pmdarima as pm\n",
    "import seaborn as sns\n",
    "from sklearn.metrics import mean_absolute_error, mean_squared_error\n",
    "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "from statsmodels.tsa.stattools import adfuller"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7f65294a-4f78-4456-b5fb-9d52a25870cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get silver price df and set date as index\n",
    "df_ag = pd.read_csv(\"../data/AG.csv\", index_col=\"date\", parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "07a37a6d-ccbc-4b2e-b084-f6c4adfcb341",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set charts theme\n",
    "sns.set_theme(style=\"darkgrid\", rc={\"grid.alpha\": 0.33})\n",
    "plt.style.use(\"dark_background\")\n",
    "\n",
    "# Save chart as png function\n",
    "def save_chart_as_png(filename: str) -> None:\n",
    "    plt.savefig(\n",
    "        f\"../images/{filename}.png\",\n",
    "        format=\"png\",\n",
    "        dpi=300,\n",
    "        orientation=\"landscape\",\n",
    "        bbox_inches=\"tight\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb7e5fee-2a79-4fc4-b787-b01167512bd2",
   "metadata": {},
   "source": [
    "## Preparing the time series to fit the ARIMA models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5a49797-1adb-4d36-b54b-caf64fa5875b",
   "metadata": {},
   "source": [
    "### Resample to weekly prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0f292ff6-2109-41d7-8363-9b2dae92885a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Resample to weekly prices (taking the mean of the week)\n",
    "df_ag = df_ag.resample(\"W\").mean()\n",
    "df_ag = df_ag.asfreq(\"W\")\n",
    "# Front fill missing values\n",
    "df_ag.ffill(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a68a3980-140e-4fc8-b6a6-eb17b3226695",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert data type to more memory-efficient\n",
    "df_ag = df_ag.astype({\"price\": \"float32\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70369fe4-dfbe-440c-9a14-7cd98beff1b2",
   "metadata": {},
   "source": [
    "### Split data into train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "512cc910-9934-40b5-aff6-62b1948fd348",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the data into train and test sets based on date\n",
    "split_date = pd.Timestamp(\"2022-01-01\")\n",
    "df_ag_train = df_ag.loc[df_ag.index < split_date].copy()\n",
    "df_ag_test = df_ag.loc[df_ag.index >= split_date].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c67e0210-a839-4eed-898d-ac84ee17aa29",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "price    0\n",
      "dtype: int64\n",
      "price    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Check for missing values\n",
    "print(df_ag_train.isnull().sum())\n",
    "print(df_ag_test.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f3a3378-4c75-4f58-a81a-275c4714df69",
   "metadata": {},
   "source": [
    "### Check if the time series is stationary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c958dc56-a9b6-498c-b336-170e0936b2b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='date'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the df\n",
    "df_ag_train.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11f9845d-01d6-49c5-96d8-84fe8b79ad8e",
   "metadata": {},
   "source": [
    "The plot clearly shows an upward trend, indicating the series is not stationary. Let's confirm this with other methods."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74cd66d7-9f52-4372-bcf9-599d60798d64",
   "metadata": {},
   "source": [
    "#### Autocorrelation function (ACF) and partial autocorrelation function (PACF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c2207c57-b692-4341-b9e3-f346c7ff0e43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the acf and pacf\n",
    "acf = plot_acf(df_ag_train)\n",
    "pacf = plot_pacf(df_ag_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e16e8af2-2be7-4cdd-b750-a8d80f0f01eb",
   "metadata": {},
   "source": [
    "- The autocorrelation function (ACF) plot shows that the correlations decline slowly, indicating a strong and persistent correlation over time. This slow decay suggests that the time series data is non-stationary.\n",
    "- The partial autocorrelation function (PACF) plot reveals that only the lag 1 value is significantly different from zero, indicating a strong correlation at lag 1 but not beyond. This pattern is typical of an autoregressive process.\n",
    "- Together, these observations suggest that the time series data is non-stationary and shows a high degree of autocorrelation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c867536-e683-48cd-bbcd-0971e9c373cf",
   "metadata": {},
   "source": [
    "#### Augmented Dickey–Fuller (ADF) test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "020048bd-d0da-47f9-929c-ecd3e421d8df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value: 0.3885401449080233\n"
     ]
    }
   ],
   "source": [
    "# Perform ADF test\n",
    "adf_test  = adfuller(df_ag_train)\n",
    "print(f\"p-value: {adf_test[1]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5b7b4d-fbc1-4ef4-9135-c17ea4a28ef1",
   "metadata": {},
   "source": [
    "- The ADF test results in a p-value close to 0.4, which is greater than the 0.05 threshold.\n",
    "- A high p-value indicates that we fail to reject the null hypothesis of the ADF test, which states that the time series has a unit root (non-stationary)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a08c032f-1066-4c86-9e5e-52ca25191a33",
   "metadata": {},
   "source": [
    "### Transform time series into stationary using differencing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "600adfd2-0de1-4add-91c8-cc4b6eabdb41",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create diff from df\n",
    "df_ag_train_diff = df_ag_train.diff().dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "101f2723-d948-4063-a257-a23b4aa823da",
   "metadata": {},
   "source": [
    "### Check again for stationarity and determine ARIMA parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ee7b9ffb-fd4b-40d7-a224-ffe11c1dfd7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the acf and pacf\n",
    "acf = plot_acf(df_ag_train_diff)\n",
    "pacf = plot_pacf(df_ag_train_diff)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e2172276-231f-4b2c-874f-288ce000f09f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p-value: 7.47350030323111e-23\n"
     ]
    }
   ],
   "source": [
    "# Perform ADF test\n",
    "adf_test  = adfuller(df_ag_train_diff)\n",
    "print(f\"p-value: {adf_test[1]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fcfef9b-2728-41a2-9e30-51c1211786bf",
   "metadata": {},
   "source": [
    "- After differencing, we can conclude that the time series is stationary with \"d\" = 1.\n",
    "- Based on the ACF and PACF plots, \"q\" is 3 and \"p\" is 2.\n",
    "- Let's use the pmdarima module to obtain the \"auto\" parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db91b101-7aa3-4612-bee2-239c196871ec",
   "metadata": {},
   "source": [
    "### Determine the ARIMA parameters using pmdarima"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "532d0a6d-175a-497e-9cc1-bb0c5536c848",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Performing stepwise search to minimize aic\n",
      " ARIMA(2,1,2)(1,0,1)[52] intercept   : AIC=4335.397, Time=34.92 sec\n",
      " ARIMA(0,1,0)(0,0,0)[52] intercept   : AIC=4431.306, Time=0.15 sec\n",
      " ARIMA(1,1,0)(1,0,0)[52] intercept   : AIC=4358.666, Time=5.05 sec\n",
      " ARIMA(0,1,1)(0,0,1)[52] intercept   : AIC=4350.756, Time=5.89 sec\n",
      " ARIMA(0,1,0)(0,0,0)[52]             : AIC=4429.476, Time=0.07 sec\n",
      " ARIMA(2,1,2)(0,0,1)[52] intercept   : AIC=4333.590, Time=22.93 sec\n",
      " ARIMA(2,1,2)(0,0,0)[52] intercept   : AIC=4332.279, Time=0.60 sec\n",
      " ARIMA(2,1,2)(1,0,0)[52] intercept   : AIC=4333.571, Time=22.55 sec\n",
      " ARIMA(1,1,2)(0,0,0)[52] intercept   : AIC=4350.233, Time=0.63 sec\n",
      " ARIMA(2,1,1)(0,0,0)[52] intercept   : AIC=4350.185, Time=0.97 sec\n",
      " ARIMA(3,1,2)(0,0,0)[52] intercept   : AIC=4311.488, Time=1.15 sec\n",
      " ARIMA(3,1,2)(1,0,0)[52] intercept   : AIC=4313.354, Time=44.10 sec\n",
      " ARIMA(3,1,2)(0,0,1)[52] intercept   : AIC=4313.361, Time=39.13 sec\n",
      " ARIMA(3,1,2)(1,0,1)[52] intercept   : AIC=4315.369, Time=46.42 sec\n",
      " ARIMA(3,1,1)(0,0,0)[52] intercept   : AIC=4347.285, Time=0.46 sec\n",
      " ARIMA(4,1,2)(0,0,0)[52] intercept   : AIC=4305.097, Time=1.85 sec\n",
      " ARIMA(4,1,2)(1,0,0)[52] intercept   : AIC=4306.269, Time=58.22 sec\n",
      " ARIMA(4,1,2)(0,0,1)[52] intercept   : AIC=4306.293, Time=47.00 sec\n",
      " ARIMA(4,1,2)(1,0,1)[52] intercept   : AIC=4308.201, Time=61.11 sec\n",
      " ARIMA(4,1,1)(0,0,0)[52] intercept   : AIC=4341.177, Time=0.97 sec\n",
      " ARIMA(5,1,2)(0,0,0)[52] intercept   : AIC=4305.651, Time=1.26 sec\n",
      " ARIMA(4,1,3)(0,0,0)[52] intercept   : AIC=4307.295, Time=2.07 sec\n",
      " ARIMA(3,1,3)(0,0,0)[52] intercept   : AIC=4305.407, Time=1.74 sec\n",
      " ARIMA(5,1,1)(0,0,0)[52] intercept   : AIC=4330.660, Time=1.01 sec\n",
      " ARIMA(5,1,3)(0,0,0)[52] intercept   : AIC=4307.351, Time=3.63 sec\n",
      " ARIMA(4,1,2)(0,0,0)[52]             : AIC=4303.225, Time=1.11 sec\n",
      " ARIMA(4,1,2)(1,0,0)[52]             : AIC=4304.390, Time=22.69 sec\n",
      " ARIMA(4,1,2)(0,0,1)[52]             : AIC=4304.413, Time=17.25 sec\n",
      " ARIMA(4,1,2)(1,0,1)[52]             : AIC=4306.304, Time=28.13 sec\n",
      " ARIMA(3,1,2)(0,0,0)[52]             : AIC=4309.600, Time=0.82 sec\n",
      " ARIMA(4,1,1)(0,0,0)[52]             : AIC=4339.295, Time=0.57 sec\n",
      " ARIMA(5,1,2)(0,0,0)[52]             : AIC=4303.781, Time=0.85 sec\n",
      " ARIMA(4,1,3)(0,0,0)[52]             : AIC=4305.399, Time=1.20 sec\n",
      " ARIMA(3,1,1)(0,0,0)[52]             : AIC=4345.409, Time=0.28 sec\n",
      " ARIMA(3,1,3)(0,0,0)[52]             : AIC=4303.503, Time=1.05 sec\n",
      " ARIMA(5,1,1)(0,0,0)[52]             : AIC=4328.798, Time=0.48 sec\n",
      " ARIMA(5,1,3)(0,0,0)[52]             : AIC=4305.485, Time=1.42 sec\n",
      "\n",
      "Best model:  ARIMA(4,1,2)(0,0,0)[52]          \n",
      "Total fit time: 479.788 seconds\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>y</td>        <th>  No. Observations:  </th>   <td>2191</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>SARIMAX(4, 1, 2)</td> <th>  Log Likelihood     </th> <td>-2144.612</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Fri, 21 Jun 2024</td> <th>  AIC                </th> <td>4303.225</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>20:41:55</td>     <th>  BIC                </th> <td>4343.066</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>             <td>01-06-1980</td>    <th>  HQIC               </th> <td>4317.786</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                   <td>- 12-26-2021</td>   <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "     <td></td>       <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>  <td>   -0.5189</td> <td>    0.012</td> <td>  -43.651</td> <td> 0.000</td> <td>   -0.542</td> <td>   -0.496</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>  <td>   -0.8334</td> <td>    0.009</td> <td>  -94.346</td> <td> 0.000</td> <td>   -0.851</td> <td>   -0.816</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L3</th>  <td>    0.1858</td> <td>    0.008</td> <td>   22.460</td> <td> 0.000</td> <td>    0.170</td> <td>    0.202</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L4</th>  <td>    0.0163</td> <td>    0.009</td> <td>    1.846</td> <td> 0.065</td> <td>   -0.001</td> <td>    0.034</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>  <td>    0.7293</td> <td>    0.010</td> <td>   73.715</td> <td> 0.000</td> <td>    0.710</td> <td>    0.749</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L2</th>  <td>    0.9149</td> <td>    0.007</td> <td>  128.203</td> <td> 0.000</td> <td>    0.901</td> <td>    0.929</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th> <td>    0.4149</td> <td>    0.003</td> <td>  142.788</td> <td> 0.000</td> <td>    0.409</td> <td>    0.421</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.02</td> <th>  Jarque-Bera (JB):  </th> <td>193594.00</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.88</td> <th>  Prob(JB):          </th>   <td>0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.47</td> <th>  Skew:              </th>   <td>-1.15</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td> <th>  Kurtosis:          </th>   <td>49.00</td>  \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}          &        y         & \\textbf{  No. Observations:  } &    2191     \\\\\n",
       "\\textbf{Model:}                  & SARIMAX(4, 1, 2) & \\textbf{  Log Likelihood     } & -2144.612   \\\\\n",
       "\\textbf{Date:}                   & Fri, 21 Jun 2024 & \\textbf{  AIC                } &  4303.225   \\\\\n",
       "\\textbf{Time:}                   &     20:41:55     & \\textbf{  BIC                } &  4343.066   \\\\\n",
       "\\textbf{Sample:}                 &    01-06-1980    & \\textbf{  HQIC               } &  4317.786   \\\\\n",
       "\\textbf{}                        &   - 12-26-2021   & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}        &       opg        & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{ar.L1}  &      -0.5189  &        0.012     &   -43.651  &         0.000        &       -0.542    &       -0.496     \\\\\n",
       "\\textbf{ar.L2}  &      -0.8334  &        0.009     &   -94.346  &         0.000        &       -0.851    &       -0.816     \\\\\n",
       "\\textbf{ar.L3}  &       0.1858  &        0.008     &    22.460  &         0.000        &        0.170    &        0.202     \\\\\n",
       "\\textbf{ar.L4}  &       0.0163  &        0.009     &     1.846  &         0.065        &       -0.001    &        0.034     \\\\\n",
       "\\textbf{ma.L1}  &       0.7293  &        0.010     &    73.715  &         0.000        &        0.710    &        0.749     \\\\\n",
       "\\textbf{ma.L2}  &       0.9149  &        0.007     &   128.203  &         0.000        &        0.901    &        0.929     \\\\\n",
       "\\textbf{sigma2} &       0.4149  &        0.003     &   142.788  &         0.000        &        0.409    &        0.421     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Ljung-Box (L1) (Q):}     & 0.02 & \\textbf{  Jarque-Bera (JB):  } & 193594.00  \\\\\n",
       "\\textbf{Prob(Q):}                & 0.88 & \\textbf{  Prob(JB):          } &    0.00    \\\\\n",
       "\\textbf{Heteroskedasticity (H):} & 1.47 & \\textbf{  Skew:              } &   -1.15    \\\\\n",
       "\\textbf{Prob(H) (two-sided):}    & 0.00 & \\textbf{  Kurtosis:          } &   49.00    \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{SARIMAX Results}\n",
       "\\end{center}\n",
       "\n",
       "Warnings: \\newline\n",
       " [1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                               SARIMAX Results                                \n",
       "==============================================================================\n",
       "Dep. Variable:                      y   No. Observations:                 2191\n",
       "Model:               SARIMAX(4, 1, 2)   Log Likelihood               -2144.612\n",
       "Date:                Fri, 21 Jun 2024   AIC                           4303.225\n",
       "Time:                        20:41:55   BIC                           4343.066\n",
       "Sample:                    01-06-1980   HQIC                          4317.786\n",
       "                         - 12-26-2021                                         \n",
       "Covariance Type:                  opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1         -0.5189      0.012    -43.651      0.000      -0.542      -0.496\n",
       "ar.L2         -0.8334      0.009    -94.346      0.000      -0.851      -0.816\n",
       "ar.L3          0.1858      0.008     22.460      0.000       0.170       0.202\n",
       "ar.L4          0.0163      0.009      1.846      0.065      -0.001       0.034\n",
       "ma.L1          0.7293      0.010     73.715      0.000       0.710       0.749\n",
       "ma.L2          0.9149      0.007    128.203      0.000       0.901       0.929\n",
       "sigma2         0.4149      0.003    142.788      0.000       0.409       0.421\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.02   Jarque-Bera (JB):            193594.00\n",
       "Prob(Q):                              0.88   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               1.47   Skew:                            -1.15\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                        49.00\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Shorten the train df to avoid huge RAM consumption\n",
    "df_ag_train_short = df_ag_train[\"1980\":]\n",
    "model_auto = pm.auto_arima(df_ag_train_short, seasonal=True, m=52, trace=True, error_action=\"ignore\", suppress_warnings=True, stepwise=True)\n",
    "model_auto.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a02733f4-fb10-4ad0-b7c1-d7182a9a6266",
   "metadata": {},
   "source": [
    "## Fit the ARIMA models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c75892f-2445-4f4f-9f51-dbfae017bb4c",
   "metadata": {},
   "source": [
    "### Train the ARIMA models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a030641-1d4a-42ff-b1d9-b442adbdaa7d",
   "metadata": {},
   "source": [
    "#### Manual model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2ab46e92-0894-477e-82e0-6e58d2e2883c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>price</td>      <th>  No. Observations:  </th>   <td>2817</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>            <td>ARIMA(2, 1, 3)</td>  <th>  Log Likelihood     </th> <td>-2579.349</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Fri, 21 Jun 2024</td> <th>  AIC                </th> <td>5170.697</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>20:41:55</td>     <th>  BIC                </th> <td>5206.356</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>             <td>01-07-1968</td>    <th>  HQIC               </th> <td>5183.565</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                   <td>- 12-26-2021</td>   <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "     <td></td>       <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>  <td>    0.4493</td> <td>    0.030</td> <td>   15.184</td> <td> 0.000</td> <td>    0.391</td> <td>    0.507</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>  <td>   -0.6774</td> <td>    0.023</td> <td>  -29.022</td> <td> 0.000</td> <td>   -0.723</td> <td>   -0.632</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>  <td>   -0.2596</td> <td>    0.029</td> <td>   -8.841</td> <td> 0.000</td> <td>   -0.317</td> <td>   -0.202</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L2</th>  <td>    0.6955</td> <td>    0.020</td> <td>   34.204</td> <td> 0.000</td> <td>    0.656</td> <td>    0.735</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L3</th>  <td>    0.1737</td> <td>    0.006</td> <td>   28.091</td> <td> 0.000</td> <td>    0.162</td> <td>    0.186</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th> <td>    0.3657</td> <td>    0.002</td> <td>  181.244</td> <td> 0.000</td> <td>    0.362</td> <td>    0.370</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.02</td> <th>  Jarque-Bera (JB):  </th> <td>452862.06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.88</td> <th>  Prob(JB):          </th>   <td>0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.13</td> <th>  Skew:              </th>   <td>-0.79</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.06</td> <th>  Kurtosis:          </th>   <td>65.11</td>  \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}          &      price       & \\textbf{  No. Observations:  } &    2817     \\\\\n",
       "\\textbf{Model:}                  &  ARIMA(2, 1, 3)  & \\textbf{  Log Likelihood     } & -2579.349   \\\\\n",
       "\\textbf{Date:}                   & Fri, 21 Jun 2024 & \\textbf{  AIC                } &  5170.697   \\\\\n",
       "\\textbf{Time:}                   &     20:41:55     & \\textbf{  BIC                } &  5206.356   \\\\\n",
       "\\textbf{Sample:}                 &    01-07-1968    & \\textbf{  HQIC               } &  5183.565   \\\\\n",
       "\\textbf{}                        &   - 12-26-2021   & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}        &       opg        & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{ar.L1}  &       0.4493  &        0.030     &    15.184  &         0.000        &        0.391    &        0.507     \\\\\n",
       "\\textbf{ar.L2}  &      -0.6774  &        0.023     &   -29.022  &         0.000        &       -0.723    &       -0.632     \\\\\n",
       "\\textbf{ma.L1}  &      -0.2596  &        0.029     &    -8.841  &         0.000        &       -0.317    &       -0.202     \\\\\n",
       "\\textbf{ma.L2}  &       0.6955  &        0.020     &    34.204  &         0.000        &        0.656    &        0.735     \\\\\n",
       "\\textbf{ma.L3}  &       0.1737  &        0.006     &    28.091  &         0.000        &        0.162    &        0.186     \\\\\n",
       "\\textbf{sigma2} &       0.3657  &        0.002     &   181.244  &         0.000        &        0.362    &        0.370     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Ljung-Box (L1) (Q):}     & 0.02 & \\textbf{  Jarque-Bera (JB):  } & 452862.06  \\\\\n",
       "\\textbf{Prob(Q):}                & 0.88 & \\textbf{  Prob(JB):          } &    0.00    \\\\\n",
       "\\textbf{Heteroskedasticity (H):} & 1.13 & \\textbf{  Skew:              } &   -0.79    \\\\\n",
       "\\textbf{Prob(H) (two-sided):}    & 0.06 & \\textbf{  Kurtosis:          } &   65.11    \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{SARIMAX Results}\n",
       "\\end{center}\n",
       "\n",
       "Warnings: \\newline\n",
       " [1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                               SARIMAX Results                                \n",
       "==============================================================================\n",
       "Dep. Variable:                  price   No. Observations:                 2817\n",
       "Model:                 ARIMA(2, 1, 3)   Log Likelihood               -2579.349\n",
       "Date:                Fri, 21 Jun 2024   AIC                           5170.697\n",
       "Time:                        20:41:55   BIC                           5206.356\n",
       "Sample:                    01-07-1968   HQIC                          5183.565\n",
       "                         - 12-26-2021                                         \n",
       "Covariance Type:                  opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.4493      0.030     15.184      0.000       0.391       0.507\n",
       "ar.L2         -0.6774      0.023    -29.022      0.000      -0.723      -0.632\n",
       "ma.L1         -0.2596      0.029     -8.841      0.000      -0.317      -0.202\n",
       "ma.L2          0.6955      0.020     34.204      0.000       0.656       0.735\n",
       "ma.L3          0.1737      0.006     28.091      0.000       0.162       0.186\n",
       "sigma2         0.3657      0.002    181.244      0.000       0.362       0.370\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.02   Jarque-Bera (JB):            452862.06\n",
       "Prob(Q):                              0.88   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               1.13   Skew:                            -0.79\n",
       "Prob(H) (two-sided):                  0.06   Kurtosis:                        65.11\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "manual_model = ARIMA(df_ag_train, order=(2, 1, 3))\n",
    "manual_model_fit = manual_model.fit()\n",
    "manual_model_fit.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ecb42a3-d582-4d36-84c5-045a5e59e3d9",
   "metadata": {},
   "source": [
    "#### Auto model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8f72ab30-4ddc-42ed-881a-f19d038a3b07",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tm/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.12/site-packages/statsmodels/tsa/statespace/sarimax.py:966: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n",
      "  warn('Non-stationary starting autoregressive parameters'\n",
      "/home/tm/.var/app/org.jupyter.JupyterLab/config/jupyterlab-desktop/jlab_server/lib/python3.12/site-packages/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
      "  warn('Non-invertible starting MA parameters found.'\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>price</td>      <th>  No. Observations:  </th>   <td>2817</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>            <td>ARIMA(4, 1, 2)</td>  <th>  Log Likelihood     </th> <td>-2578.441</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Fri, 21 Jun 2024</td> <th>  AIC                </th> <td>5170.883</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>20:41:57</td>     <th>  BIC                </th> <td>5212.484</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>             <td>01-07-1968</td>    <th>  HQIC               </th> <td>5185.895</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                   <td>- 12-26-2021</td>   <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>        <td>opg</td>       <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "     <td></td>       <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>  <td>    0.6190</td> <td>    0.025</td> <td>   24.688</td> <td> 0.000</td> <td>    0.570</td> <td>    0.668</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>  <td>   -0.8360</td> <td>    0.025</td> <td>  -33.944</td> <td> 0.000</td> <td>   -0.884</td> <td>   -0.788</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L3</th>  <td>    0.1910</td> <td>    0.006</td> <td>   30.796</td> <td> 0.000</td> <td>    0.179</td> <td>    0.203</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L4</th>  <td>   -0.0250</td> <td>    0.005</td> <td>   -4.608</td> <td> 0.000</td> <td>   -0.036</td> <td>   -0.014</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L1</th>  <td>   -0.4253</td> <td>    0.025</td> <td>  -17.359</td> <td> 0.000</td> <td>   -0.473</td> <td>   -0.377</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.L2</th>  <td>    0.8205</td> <td>    0.022</td> <td>   36.669</td> <td> 0.000</td> <td>    0.777</td> <td>    0.864</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th> <td>    0.3654</td> <td>    0.002</td> <td>  177.736</td> <td> 0.000</td> <td>    0.361</td> <td>    0.369</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.00</td> <th>  Jarque-Bera (JB):  </th> <td>448570.10</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.98</td> <th>  Prob(JB):          </th>   <td>0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.13</td> <th>  Skew:              </th>   <td>-0.81</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.06</td> <th>  Kurtosis:          </th>   <td>64.81</td>  \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}          &      price       & \\textbf{  No. Observations:  } &    2817     \\\\\n",
       "\\textbf{Model:}                  &  ARIMA(4, 1, 2)  & \\textbf{  Log Likelihood     } & -2578.441   \\\\\n",
       "\\textbf{Date:}                   & Fri, 21 Jun 2024 & \\textbf{  AIC                } &  5170.883   \\\\\n",
       "\\textbf{Time:}                   &     20:41:57     & \\textbf{  BIC                } &  5212.484   \\\\\n",
       "\\textbf{Sample:}                 &    01-07-1968    & \\textbf{  HQIC               } &  5185.895   \\\\\n",
       "\\textbf{}                        &   - 12-26-2021   & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}        &       opg        & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{ar.L1}  &       0.6190  &        0.025     &    24.688  &         0.000        &        0.570    &        0.668     \\\\\n",
       "\\textbf{ar.L2}  &      -0.8360  &        0.025     &   -33.944  &         0.000        &       -0.884    &       -0.788     \\\\\n",
       "\\textbf{ar.L3}  &       0.1910  &        0.006     &    30.796  &         0.000        &        0.179    &        0.203     \\\\\n",
       "\\textbf{ar.L4}  &      -0.0250  &        0.005     &    -4.608  &         0.000        &       -0.036    &       -0.014     \\\\\n",
       "\\textbf{ma.L1}  &      -0.4253  &        0.025     &   -17.359  &         0.000        &       -0.473    &       -0.377     \\\\\n",
       "\\textbf{ma.L2}  &       0.8205  &        0.022     &    36.669  &         0.000        &        0.777    &        0.864     \\\\\n",
       "\\textbf{sigma2} &       0.3654  &        0.002     &   177.736  &         0.000        &        0.361    &        0.369     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Ljung-Box (L1) (Q):}     & 0.00 & \\textbf{  Jarque-Bera (JB):  } & 448570.10  \\\\\n",
       "\\textbf{Prob(Q):}                & 0.98 & \\textbf{  Prob(JB):          } &    0.00    \\\\\n",
       "\\textbf{Heteroskedasticity (H):} & 1.13 & \\textbf{  Skew:              } &   -0.81    \\\\\n",
       "\\textbf{Prob(H) (two-sided):}    & 0.06 & \\textbf{  Kurtosis:          } &   64.81    \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{SARIMAX Results}\n",
       "\\end{center}\n",
       "\n",
       "Warnings: \\newline\n",
       " [1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                               SARIMAX Results                                \n",
       "==============================================================================\n",
       "Dep. Variable:                  price   No. Observations:                 2817\n",
       "Model:                 ARIMA(4, 1, 2)   Log Likelihood               -2578.441\n",
       "Date:                Fri, 21 Jun 2024   AIC                           5170.883\n",
       "Time:                        20:41:57   BIC                           5212.484\n",
       "Sample:                    01-07-1968   HQIC                          5185.895\n",
       "                         - 12-26-2021                                         \n",
       "Covariance Type:                  opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.6190      0.025     24.688      0.000       0.570       0.668\n",
       "ar.L2         -0.8360      0.025    -33.944      0.000      -0.884      -0.788\n",
       "ar.L3          0.1910      0.006     30.796      0.000       0.179       0.203\n",
       "ar.L4         -0.0250      0.005     -4.608      0.000      -0.036      -0.014\n",
       "ma.L1         -0.4253      0.025    -17.359      0.000      -0.473      -0.377\n",
       "ma.L2          0.8205      0.022     36.669      0.000       0.777       0.864\n",
       "sigma2         0.3654      0.002    177.736      0.000       0.361       0.369\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.00   Jarque-Bera (JB):            448570.10\n",
       "Prob(Q):                              0.98   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               1.13   Skew:                            -0.81\n",
       "Prob(H) (two-sided):                  0.06   Kurtosis:                        64.81\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Auto model is seasonal\n",
    "auto_model = ARIMA(df_ag_train, order=model_auto.order, seasonal_order=model_auto.seasonal_order)\n",
    "auto_model_fit = auto_model.fit()\n",
    "auto_model_fit.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "224b420d-c027-4aa0-8f20-c6ee61a7281d",
   "metadata": {},
   "source": [
    "### Check models residuals"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08b0626b-22ea-4b53-81c2-81fda5f7a635",
   "metadata": {},
   "source": [
    "#### Manual model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ccae6cb5-ff00-46e6-87ff-7f9cbd3d9ded",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Density'}, ylabel='Density'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residuals = manual_model_fit.resid[1:]\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
    "\n",
    "plot_acf(residuals)\n",
    "plot_pacf(residuals)\n",
    "residuals.plot(title=\"Residuals\", ax=axes[0])\n",
    "residuals.plot(title=\"Density\", ax=axes[1], kind=\"kde\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "463a4b77-ccbc-41e3-b4a5-8f53fa24bd46",
   "metadata": {},
   "source": [
    "#### Auto model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a28f0122-d7ec-40ef-8ff8-15b0bbf69743",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Density'}, ylabel='Density'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "residuals = auto_model_fit.resid[1:]\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n",
    "\n",
    "plot_acf(residuals)\n",
    "plot_pacf(residuals)\n",
    "residuals.plot(title=\"Residuals\", ax=axes[0])\n",
    "residuals.plot(title=\"Density\", ax=axes[1], kind=\"kde\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "378b2cf4-44ba-4772-9abc-c7e266260c88",
   "metadata": {},
   "source": [
    "- Residuals resemble white noise in both models.\n",
    "- Their density is normally distributed.\n",
    "- ACF and PACF plots show no significant spikes for both models.\n",
    "- Therefore, the models appear to be well-fitted and meet the necessary diagnostic criteria."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fff35ee-aaf3-470d-b7bc-08ddb17ba73d",
   "metadata": {},
   "source": [
    "### Forecast on the training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c287324b-5c9d-4e4e-8596-89d13b89a703",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get number of periods to forecast from test\n",
    "n_forecast = len(df_ag_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4a63e96-3922-43df-a4a8-9e44e4f181c9",
   "metadata": {},
   "source": [
    "#### Manual model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6dd69dd4-bc29-4d20-86ff-62f91d65d8db",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get forecast values\n",
    "manual_forecast = manual_model_fit.get_forecast(steps=n_forecast)\n",
    "manual_forecast_values = manual_forecast.predicted_mean\n",
    "manual_conf_int = manual_forecast.conf_int()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c351532b-58eb-4357-ae30-c408ea59038c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1b29772d20>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plot the training data\n",
    "plt.plot(df_ag_train.loc[\"2020-01-01\":].index, df_ag_train.loc[\"2020-01-01\":].values, label=\"Train\")\n",
    "\n",
    "# Plot the test data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, df_ag_test.loc[\"2020-01-01\":].values, label=\"Test\")\n",
    "\n",
    "# Plot the forecast data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, manual_forecast_values, label=\"Forecast\")\n",
    "\n",
    "# Fill the confidence interval\n",
    "plt.fill_between(df_ag_test.loc[\"2020-01-01\":].index, manual_conf_int.iloc[:, 0], manual_conf_int.iloc[:, 1], color=\"pink\", alpha=0.3)\n",
    "\n",
    "plt.title(\"ARIMA forecast of the silver price\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"\")\n",
    "plt.legend(loc=\"upper left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71c61ff0-d26a-452f-8e16-a8a22680f5c6",
   "metadata": {},
   "source": [
    "#### Auto model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a7547588-c4d3-4931-b236-73b6803024d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get forecast values\n",
    "auto_forecast = auto_model_fit.get_forecast(steps=n_forecast)\n",
    "auto_forecast_values = auto_forecast.predicted_mean\n",
    "auto_conf_int = auto_forecast.conf_int()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2b2ba966-2e3a-4b61-9fe0-cb17b0ecc876",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1b29b19d60>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plot the training data\n",
    "plt.plot(df_ag_train.loc[\"2020-01-01\":].index, df_ag_train.loc[\"2020-01-01\":].values, label=\"Train\")\n",
    "\n",
    "# Plot the test data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, df_ag_test.loc[\"2020-01-01\":].values, label=\"Test\")\n",
    "\n",
    "# Plot the forecast data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, auto_forecast_values, label=\"Forecast\")\n",
    "\n",
    "# Fill the confidence interval\n",
    "plt.fill_between(df_ag_test.loc[\"2020-01-01\":].index, auto_conf_int.iloc[:, 0], auto_conf_int.iloc[:, 1], color=\"pink\", alpha=0.3)\n",
    "\n",
    "plt.title(\"SARIMA forecast of the silver price\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"\")\n",
    "plt.legend(loc=\"upper left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4a4cc7b-7506-4fc9-88db-693d14bd0a42",
   "metadata": {},
   "source": [
    "### Evaluate both models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "528e095b-b27f-4de0-99a4-d60e329d1be0",
   "metadata": {},
   "source": [
    "#### Manual model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d93e2c53-1dfc-44ca-a80e-d73c9e89237e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 1.5896277154168992\n",
      "RMSE: 2.1356731426093454\n"
     ]
    }
   ],
   "source": [
    "# Evaluate model\n",
    "mae = mean_absolute_error(df_ag_test, manual_forecast_values)\n",
    "rmse = np.sqrt(mean_squared_error(df_ag_test, manual_forecast_values))\n",
    "\n",
    "print(f\"MAE: {mae}\")\n",
    "print(f\"RMSE: {rmse}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7eb87f3a-a191-4224-b298-3b6faa23b62e",
   "metadata": {},
   "source": [
    "#### Auto model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "bb82567e-a747-44b1-a0eb-4e78c59e09ff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 1.5899169296855227\n",
      "RMSE: 2.1354464879485078\n"
     ]
    }
   ],
   "source": [
    "# Evaluate model\n",
    "mae = mean_absolute_error(df_ag_test, auto_forecast_values)\n",
    "rmse = np.sqrt(mean_squared_error(df_ag_test, auto_forecast_values))\n",
    "\n",
    "print(f\"MAE: {mae}\")\n",
    "print(f\"RMSE: {rmse}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "885dbe3a-ec4d-4bc3-bfef-e94e7fd23d9d",
   "metadata": {},
   "source": [
    "**Both models seem to be accurate. The manual model is slightly more. Let's also try a fine tuned.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fd03008-39f6-4bcd-9b44-d95dfd462765",
   "metadata": {},
   "source": [
    "### Fine tune a model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4dc97baf-68bb-45f9-a6d1-8b0445013d2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                <td>price</td>             <th>  No. Observations:  </th>   <td>2817</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>ARIMA(3, 1, 0)x(0, 1, [1], 52)</td> <th>  Log Likelihood     </th> <td>-2659.547</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Fri, 21 Jun 2024</td>        <th>  AIC                </th> <td>5329.093</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>20:43:45</td>            <th>  BIC                </th> <td>5358.715</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>01-07-1968</td>           <th>  HQIC               </th> <td>5339.793</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 12-26-2021</td>          <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>    <td>    0.1929</td> <td>    0.005</td> <td>   40.438</td> <td> 0.000</td> <td>    0.184</td> <td>    0.202</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>    <td>    0.0562</td> <td>    0.004</td> <td>   14.125</td> <td> 0.000</td> <td>    0.048</td> <td>    0.064</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L3</th>    <td>    0.0275</td> <td>    0.005</td> <td>    5.139</td> <td> 0.000</td> <td>    0.017</td> <td>    0.038</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L52</th> <td>   -0.9764</td> <td>    0.013</td> <td>  -77.428</td> <td> 0.000</td> <td>   -1.001</td> <td>   -0.952</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>   <td>    0.3792</td> <td>    0.004</td> <td>  100.057</td> <td> 0.000</td> <td>    0.372</td> <td>    0.387</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.00</td> <th>  Jarque-Bera (JB):  </th> <td>394010.22</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.99</td> <th>  Prob(JB):          </th>   <td>0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.13</td> <th>  Skew:              </th>   <td>-1.20</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.06</td> <th>  Kurtosis:          </th>   <td>61.44</td>  \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}          &             price              & \\textbf{  No. Observations:  } &    2817     \\\\\n",
       "\\textbf{Model:}                  & ARIMA(3, 1, 0)x(0, 1, [1], 52) & \\textbf{  Log Likelihood     } & -2659.547   \\\\\n",
       "\\textbf{Date:}                   &        Fri, 21 Jun 2024        & \\textbf{  AIC                } &  5329.093   \\\\\n",
       "\\textbf{Time:}                   &            20:43:45            & \\textbf{  BIC                } &  5358.715   \\\\\n",
       "\\textbf{Sample:}                 &           01-07-1968           & \\textbf{  HQIC               } &  5339.793   \\\\\n",
       "\\textbf{}                        &          - 12-26-2021          & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}        &              opg               & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                  & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{ar.L1}    &       0.1929  &        0.005     &    40.438  &         0.000        &        0.184    &        0.202     \\\\\n",
       "\\textbf{ar.L2}    &       0.0562  &        0.004     &    14.125  &         0.000        &        0.048    &        0.064     \\\\\n",
       "\\textbf{ar.L3}    &       0.0275  &        0.005     &     5.139  &         0.000        &        0.017    &        0.038     \\\\\n",
       "\\textbf{ma.S.L52} &      -0.9764  &        0.013     &   -77.428  &         0.000        &       -1.001    &       -0.952     \\\\\n",
       "\\textbf{sigma2}   &       0.3792  &        0.004     &   100.057  &         0.000        &        0.372    &        0.387     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Ljung-Box (L1) (Q):}     & 0.00 & \\textbf{  Jarque-Bera (JB):  } & 394010.22  \\\\\n",
       "\\textbf{Prob(Q):}                & 0.99 & \\textbf{  Prob(JB):          } &    0.00    \\\\\n",
       "\\textbf{Heteroskedasticity (H):} & 1.13 & \\textbf{  Skew:              } &   -1.20    \\\\\n",
       "\\textbf{Prob(H) (two-sided):}    & 0.06 & \\textbf{  Kurtosis:          } &   61.44    \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{SARIMAX Results}\n",
       "\\end{center}\n",
       "\n",
       "Warnings: \\newline\n",
       " [1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                     SARIMAX Results                                      \n",
       "==========================================================================================\n",
       "Dep. Variable:                              price   No. Observations:                 2817\n",
       "Model:             ARIMA(3, 1, 0)x(0, 1, [1], 52)   Log Likelihood               -2659.547\n",
       "Date:                            Fri, 21 Jun 2024   AIC                           5329.093\n",
       "Time:                                    20:43:45   BIC                           5358.715\n",
       "Sample:                                01-07-1968   HQIC                          5339.793\n",
       "                                     - 12-26-2021                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.1929      0.005     40.438      0.000       0.184       0.202\n",
       "ar.L2          0.0562      0.004     14.125      0.000       0.048       0.064\n",
       "ar.L3          0.0275      0.005      5.139      0.000       0.017       0.038\n",
       "ma.S.L52      -0.9764      0.013    -77.428      0.000      -1.001      -0.952\n",
       "sigma2         0.3792      0.004    100.057      0.000       0.372       0.387\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.00   Jarque-Bera (JB):            394010.22\n",
       "Prob(Q):                              0.99   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               1.13   Skew:                            -1.20\n",
       "Prob(H) (two-sided):                  0.06   Kurtosis:                        61.44\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit tuned model (the exact same parameters of gold are also the best for silver)\n",
    "tuned_model = ARIMA(df_ag_train, order=(3, 1, 0), seasonal_order=(0, 1, 1, 52))\n",
    "tuned_model_fit = tuned_model.fit()\n",
    "tuned_model_fit.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0e571899-6c38-4d20-994f-0e9a073c56d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get forecast values\n",
    "tuned_forecast = tuned_model_fit.get_forecast(steps=n_forecast)\n",
    "tuned_forecast_values = tuned_forecast.predicted_mean\n",
    "tuned_conf_int = tuned_forecast.conf_int()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "037cc52a-cd4d-4fb3-a7ed-02ccfde1911b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1b29c98890>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plot the training data\n",
    "plt.plot(df_ag_train.loc[\"2020-01-01\":].index, df_ag_train.loc[\"2020-01-01\":].values, label=\"Train\")\n",
    "\n",
    "# Plot the test data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, df_ag_test.loc[\"2020-01-01\":].values, label=\"Test\")\n",
    "\n",
    "# Plot the forecast data\n",
    "plt.plot(df_ag_test.loc[\"2020-01-01\":].index, tuned_forecast_values, label=\"Forecast\")\n",
    "\n",
    "# Fill the confidence interval\n",
    "plt.fill_between(df_ag_test.loc[\"2020-01-01\":].index, tuned_conf_int.iloc[:, 0], tuned_conf_int.iloc[:, 1], color=\"pink\", alpha=0.3)\n",
    "\n",
    "plt.title(\"SARIMA forecast of the silver price\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"\")\n",
    "plt.legend(loc=\"upper left\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "79defa7e-1a19-460e-83bb-87d2ad4c217d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 1.5539507160676809\n",
      "RMSE: 2.0574974703351177\n"
     ]
    }
   ],
   "source": [
    "# Evaluate model\n",
    "mae = mean_absolute_error(df_ag_test, tuned_forecast_values)\n",
    "rmse = np.sqrt(mean_squared_error(df_ag_test, tuned_forecast_values))\n",
    "\n",
    "print(f\"MAE: {mae}\")\n",
    "print(f\"RMSE: {rmse}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "446006ff-5e97-45b2-8f76-f7949169b6a6",
   "metadata": {},
   "source": [
    "**This model has provided better results. Just like gold's, this one is the best performing. Therefore it'll be used for the forecast.**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69e1a407-92d1-4d45-bab6-972fd1ae7610",
   "metadata": {},
   "source": [
    "## The forecast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d2b89423-10ba-4b4b-af15-a2a4252bf09d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>SARIMAX Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>                <td>price</td>             <th>  No. Observations:  </th>   <td>2942</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>           <td>ARIMA(3, 1, 0)x(0, 1, [1], 52)</td> <th>  Log Likelihood     </th> <td>-2803.351</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>                   <td>Fri, 21 Jun 2024</td>        <th>  AIC                </th> <td>5616.703</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                       <td>20:45:45</td>            <th>  BIC                </th> <td>5646.546</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Sample:</th>                    <td>01-07-1968</td>           <th>  HQIC               </th> <td>5627.458</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th></th>                          <td>- 05-19-2024</td>          <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>               <td>opg</td>              <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>        <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L1</th>    <td>    0.1990</td> <td>    0.005</td> <td>   41.032</td> <td> 0.000</td> <td>    0.190</td> <td>    0.209</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L2</th>    <td>    0.0377</td> <td>    0.004</td> <td>    9.202</td> <td> 0.000</td> <td>    0.030</td> <td>    0.046</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ar.L3</th>    <td>    0.0286</td> <td>    0.005</td> <td>    5.264</td> <td> 0.000</td> <td>    0.018</td> <td>    0.039</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>ma.S.L52</th> <td>   -0.9805</td> <td>    0.014</td> <td>  -71.849</td> <td> 0.000</td> <td>   -1.007</td> <td>   -0.954</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>sigma2</th>   <td>    0.3853</td> <td>    0.004</td> <td>   89.107</td> <td> 0.000</td> <td>    0.377</td> <td>    0.394</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Ljung-Box (L1) (Q):</th>     <td>0.00</td> <th>  Jarque-Bera (JB):  </th> <td>358493.43</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Q):</th>                <td>0.99</td> <th>  Prob(JB):          </th>   <td>0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Heteroskedasticity (H):</th> <td>1.25</td> <th>  Skew:              </th>   <td>-1.02</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(H) (two-sided):</th>    <td>0.00</td> <th>  Kurtosis:          </th>   <td>57.53</td>  \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}          &             price              & \\textbf{  No. Observations:  } &    2942     \\\\\n",
       "\\textbf{Model:}                  & ARIMA(3, 1, 0)x(0, 1, [1], 52) & \\textbf{  Log Likelihood     } & -2803.351   \\\\\n",
       "\\textbf{Date:}                   &        Fri, 21 Jun 2024        & \\textbf{  AIC                } &  5616.703   \\\\\n",
       "\\textbf{Time:}                   &            20:45:45            & \\textbf{  BIC                } &  5646.546   \\\\\n",
       "\\textbf{Sample:}                 &           01-07-1968           & \\textbf{  HQIC               } &  5627.458   \\\\\n",
       "\\textbf{}                        &          - 05-19-2024          & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}        &              opg               & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                  & \\textbf{coef} & \\textbf{std err} & \\textbf{z} & \\textbf{P$> |$z$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{ar.L1}    &       0.1990  &        0.005     &    41.032  &         0.000        &        0.190    &        0.209     \\\\\n",
       "\\textbf{ar.L2}    &       0.0377  &        0.004     &     9.202  &         0.000        &        0.030    &        0.046     \\\\\n",
       "\\textbf{ar.L3}    &       0.0286  &        0.005     &     5.264  &         0.000        &        0.018    &        0.039     \\\\\n",
       "\\textbf{ma.S.L52} &      -0.9805  &        0.014     &   -71.849  &         0.000        &       -1.007    &       -0.954     \\\\\n",
       "\\textbf{sigma2}   &       0.3853  &        0.004     &    89.107  &         0.000        &        0.377    &        0.394     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Ljung-Box (L1) (Q):}     & 0.00 & \\textbf{  Jarque-Bera (JB):  } & 358493.43  \\\\\n",
       "\\textbf{Prob(Q):}                & 0.99 & \\textbf{  Prob(JB):          } &    0.00    \\\\\n",
       "\\textbf{Heteroskedasticity (H):} & 1.25 & \\textbf{  Skew:              } &   -1.02    \\\\\n",
       "\\textbf{Prob(H) (two-sided):}    & 0.00 & \\textbf{  Kurtosis:          } &   57.53    \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{SARIMAX Results}\n",
       "\\end{center}\n",
       "\n",
       "Warnings: \\newline\n",
       " [1] Covariance matrix calculated using the outer product of gradients (complex-step)."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                                     SARIMAX Results                                      \n",
       "==========================================================================================\n",
       "Dep. Variable:                              price   No. Observations:                 2942\n",
       "Model:             ARIMA(3, 1, 0)x(0, 1, [1], 52)   Log Likelihood               -2803.351\n",
       "Date:                            Fri, 21 Jun 2024   AIC                           5616.703\n",
       "Time:                                    20:45:45   BIC                           5646.546\n",
       "Sample:                                01-07-1968   HQIC                          5627.458\n",
       "                                     - 05-19-2024                                         \n",
       "Covariance Type:                              opg                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "ar.L1          0.1990      0.005     41.032      0.000       0.190       0.209\n",
       "ar.L2          0.0377      0.004      9.202      0.000       0.030       0.046\n",
       "ar.L3          0.0286      0.005      5.264      0.000       0.018       0.039\n",
       "ma.S.L52      -0.9805      0.014    -71.849      0.000      -1.007      -0.954\n",
       "sigma2         0.3853      0.004     89.107      0.000       0.377       0.394\n",
       "===================================================================================\n",
       "Ljung-Box (L1) (Q):                   0.00   Jarque-Bera (JB):            358493.43\n",
       "Prob(Q):                              0.99   Prob(JB):                         0.00\n",
       "Heteroskedasticity (H):               1.25   Skew:                            -1.02\n",
       "Prob(H) (two-sided):                  0.00   Kurtosis:                        57.53\n",
       "===================================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
       "\"\"\""
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit model\n",
    "model = ARIMA(df_ag, order=(3, 1, 0), seasonal_order=(0, 1, 1, 52))\n",
    "model_fit = model.fit()\n",
    "model_fit.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "97fc48b8-c9b7-4fbb-9bcf-e4c1e30ecf45",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get number of periods (weeks) to forecast\n",
    "n_forecast = 26"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "189d4e3c-e2a3-474b-a67b-4b1d56252d32",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get forecast values\n",
    "forecast = model_fit.get_forecast(steps=n_forecast)\n",
    "forecast_values = forecast.predicted_mean\n",
    "conf_int = forecast.conf_int()\n",
    "forecast_index = pd.date_range(start=df_ag.index[-1], periods=n_forecast + 1, freq=\"W\")[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "41d8da21-d8d3-4788-8925-178372b38915",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plot the original data\n",
    "sns.lineplot(x=df_ag.loc[\"2022-01-01\":].index, y=df_ag.loc[\"2022-01-01\":][\"price\"], label=\"Historic\", color=\"lightgrey\")\n",
    "\n",
    "# Plot the forecast data\n",
    "sns.lineplot(x=forecast_index, y=forecast_values, label=\"Forecast\", color=\"aqua\")\n",
    "\n",
    "# Fill the confidence interval\n",
    "plt.fill_between(forecast_index, conf_int.iloc[:, 0], conf_int.iloc[:, 1], label=\"Confidence interval\", color=\"aquamarine\", alpha=0.2)\n",
    "\n",
    "plt.title(\"SARIMA forecast of the silver price for the next 6 months\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"\")\n",
    "plt.legend(loc=\"upper left\")\n",
    "\n",
    "save_chart_as_png(\"7.2_AG_ARIMA\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25cf147f-f9e5-4d71-bcc9-b73845a1234d",
   "metadata": {},
   "source": [
    "**Silver prices are expected to rise steadily over the next six months, much like gold. Although the model parameters are the same to those used for gold, the confidence interval for silver is significantly wider.**"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}