{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6a1ea458",
   "metadata": {},
   "source": [
    "# US GDP Forecasting\n",
    "\n",
    "Author: Dron Mongia\n",
    "\n",
    "Course Project, UC Irvine, Math 10, S24\n",
    "\n",
    "I would like to post my notebook on the course’s website: Yes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec8c04f0",
   "metadata": {},
   "source": [
    "# Motivation and Procedure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4017e0c",
   "metadata": {},
   "source": [
    "GDP is a very strong metric of a country's economic wellbeing and therefore, forecasts of GDP are highly sought after. Policy makers and legislators, for example, may want to have a rough forecast of the trends regarding the country's GDP prior to passing some new bill or law. My procedure for this project will be to first compile time series data from the FRED api consisting of some economic metrics closely related to GDP (GDP = Consumption + Investment + Govt. Spending + Net Export). We then will conduct a series of exploratory tests to better understand our data, and finally we will use a vairety of models (including machine learning methods) to see which one provides the most accurate forecast."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0bd734f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import fredapi as fd\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "983f6d49",
   "metadata": {},
   "source": [
    "# Feature Creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "36a3c2c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "fred = fd.Fred(api_key = 'efdb939ff3f6b3129c564ef0aa34a91e') # generally this should be hidden, however for the purposes of this project I will keep it visible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "df42df34",
   "metadata": {},
   "outputs": [],
   "source": [
    "def gen_df(category, series):\n",
    "    gen_ser = fred.get_series(series, frequency='q')\n",
    "    return pd.DataFrame({'Date': gen_ser.index, category + ' : Billions of dollars': gen_ser.values})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ad6c8814",
   "metadata": {},
   "outputs": [],
   "source": [
    "def merge_dataframes(dataframes, on_column):\n",
    "    merged_df = dataframes[0]\n",
    "\n",
    "    for df in dataframes[1:]:\n",
    "        merged_df = pd.merge(merged_df, df, on=on_column)\n",
    "\n",
    "    return merged_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9ff5a8c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataframes_list = [\n",
    "    gen_df('GDP', 'GDP'),\n",
    "    gen_df('PCE', 'PCE'),\n",
    "    gen_df('GPDI', 'GPDI'),\n",
    "    gen_df('NETEXP', 'NETEXP'),\n",
    "    gen_df('GovTotExp', 'W068RCQ027SBEA')\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f8f0d003",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>GDP : Billions of dollars</th>\n",
       "      <th>PCE : Billions of dollars</th>\n",
       "      <th>GPDI : Billions of dollars</th>\n",
       "      <th>NETEXP : Billions of dollars</th>\n",
       "      <th>GovTotExp : Billions of dollars</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1960-01-01</td>\n",
       "      <td>542.648</td>\n",
       "      <td>326.4</td>\n",
       "      <td>96.476</td>\n",
       "      <td>2.858</td>\n",
       "      <td>144.233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1960-04-01</td>\n",
       "      <td>541.080</td>\n",
       "      <td>332.2</td>\n",
       "      <td>87.096</td>\n",
       "      <td>3.395</td>\n",
       "      <td>147.417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1960-07-01</td>\n",
       "      <td>545.604</td>\n",
       "      <td>332.1</td>\n",
       "      <td>86.377</td>\n",
       "      <td>4.682</td>\n",
       "      <td>150.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1960-10-01</td>\n",
       "      <td>540.197</td>\n",
       "      <td>334.0</td>\n",
       "      <td>75.963</td>\n",
       "      <td>5.880</td>\n",
       "      <td>153.780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1961-01-01</td>\n",
       "      <td>545.018</td>\n",
       "      <td>334.5</td>\n",
       "      <td>78.378</td>\n",
       "      <td>5.902</td>\n",
       "      <td>157.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>2023-01-01</td>\n",
       "      <td>26813.601</td>\n",
       "      <td>18269.6</td>\n",
       "      <td>4725.828</td>\n",
       "      <td>-825.687</td>\n",
       "      <td>9326.383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>2023-04-01</td>\n",
       "      <td>27063.012</td>\n",
       "      <td>18419.0</td>\n",
       "      <td>4780.290</td>\n",
       "      <td>-806.093</td>\n",
       "      <td>9422.404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>2023-07-01</td>\n",
       "      <td>27610.128</td>\n",
       "      <td>18679.5</td>\n",
       "      <td>4915.033</td>\n",
       "      <td>-779.231</td>\n",
       "      <td>10007.677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>2023-10-01</td>\n",
       "      <td>27956.998</td>\n",
       "      <td>18914.5</td>\n",
       "      <td>4954.426</td>\n",
       "      <td>-783.734</td>\n",
       "      <td>9700.808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>2024-01-01</td>\n",
       "      <td>28255.928</td>\n",
       "      <td>19164.2</td>\n",
       "      <td>5004.419</td>\n",
       "      <td>-850.094</td>\n",
       "      <td>9924.229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>257 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  GDP : Billions of dollars  PCE : Billions of dollars  \\\n",
       "0   1960-01-01                    542.648                      326.4   \n",
       "1   1960-04-01                    541.080                      332.2   \n",
       "2   1960-07-01                    545.604                      332.1   \n",
       "3   1960-10-01                    540.197                      334.0   \n",
       "4   1961-01-01                    545.018                      334.5   \n",
       "..         ...                        ...                        ...   \n",
       "252 2023-01-01                  26813.601                    18269.6   \n",
       "253 2023-04-01                  27063.012                    18419.0   \n",
       "254 2023-07-01                  27610.128                    18679.5   \n",
       "255 2023-10-01                  27956.998                    18914.5   \n",
       "256 2024-01-01                  28255.928                    19164.2   \n",
       "\n",
       "     GPDI : Billions of dollars  NETEXP : Billions of dollars  \\\n",
       "0                        96.476                         2.858   \n",
       "1                        87.096                         3.395   \n",
       "2                        86.377                         4.682   \n",
       "3                        75.963                         5.880   \n",
       "4                        78.378                         5.902   \n",
       "..                          ...                           ...   \n",
       "252                    4725.828                      -825.687   \n",
       "253                    4780.290                      -806.093   \n",
       "254                    4915.033                      -779.231   \n",
       "255                    4954.426                      -783.734   \n",
       "256                    5004.419                      -850.094   \n",
       "\n",
       "     GovTotExp : Billions of dollars  \n",
       "0                            144.233  \n",
       "1                            147.417  \n",
       "2                            150.459  \n",
       "3                            153.780  \n",
       "4                            157.254  \n",
       "..                               ...  \n",
       "252                         9326.383  \n",
       "253                         9422.404  \n",
       "254                        10007.677  \n",
       "255                         9700.808  \n",
       "256                         9924.229  \n",
       "\n",
       "[257 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = merge_dataframes(dataframes_list,'Date')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "89aa3ced",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "231   2017-10-01\n",
      "232   2018-01-01\n",
      "233   2018-04-01\n",
      "234   2018-07-01\n",
      "235   2018-10-01\n",
      "236   2019-01-01\n",
      "237   2019-04-01\n",
      "238   2019-07-01\n",
      "239   2019-10-01\n",
      "240   2020-01-01\n",
      "241   2020-04-01\n",
      "242   2020-07-01\n",
      "243   2020-10-01\n",
      "244   2021-01-01\n",
      "245   2021-04-01\n",
      "246   2021-07-01\n",
      "247   2021-10-01\n",
      "248   2022-01-01\n",
      "249   2022-04-01\n",
      "250   2022-07-01\n",
      "251   2022-10-01\n",
      "252   2023-01-01\n",
      "253   2023-04-01\n",
      "254   2023-07-01\n",
      "255   2023-10-01\n",
      "256   2024-01-01\n",
      "Name: Date, dtype: datetime64[ns]\n"
     ]
    }
   ],
   "source": [
    "Date_col = data['Date'].tail(26) # to be used later on\n",
    "print(Date_col) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2cb4b67",
   "metadata": {},
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbb7f367",
   "metadata": {},
   "source": [
    "Below is a simple line plot comparing each of the time series. We notice that some of the features resemble GDP far more than others, however, we can not yet begin selecting and removing certain features prior do conducting more exploratory tests."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c7b234d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "date_column = 'Date'\n",
    "\n",
    "feature_columns = data.columns.difference([date_column])\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "fig.suptitle('Features vs Time', y=1.02)\n",
    "\n",
    "for i, feature in enumerate(feature_columns):\n",
    "    ax.plot(data[date_column], data[feature], label=feature, color=plt.cm.viridis(i / len(feature_columns)))\n",
    "\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Billions of Dollars')\n",
    "ax.legend(loc='upper left', bbox_to_anchor=(1, 1))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c852a50e",
   "metadata": {},
   "source": [
    "Here we run a test to evaluate the stationarity of out time series. Stationarity essentially means that a time series has a constant mean and varience. This is important to test for because many popular forecasting methods require stationarity to function properly. Although we can determine the stationarity for most of these time series just by looking at the graph, doing the testing is still beneficial because we will likely reuse it in later parts of the forecast."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fb2751fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADF Statistic for GDP : Billions of dollars: 7.301049607594838\n",
      "P-value for GDP : Billions of dollars: 1.0\n",
      "Critical Values:\n",
      "  1%: -3.4562572510874396\n",
      "  5%: -2.8729420379793598\n",
      "  10%: -2.5728461399461744\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for PCE : Billions of dollars: 6.798336970342141\n",
      "P-value for PCE : Billions of dollars: 1.0\n",
      "Critical Values:\n",
      "  1%: -3.4562572510874396\n",
      "  5%: -2.8729420379793598\n",
      "  10%: -2.5728461399461744\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for GPDI : Billions of dollars: 2.765116699661126\n",
      "P-value for GPDI : Billions of dollars: 1.0\n",
      "Critical Values:\n",
      "  1%: -3.4561550092339512\n",
      "  5%: -2.8728972266578676\n",
      "  10%: -2.5728222369384763\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for NETEXP : Billions of dollars: -0.009808856906310032\n",
      "P-value for NETEXP : Billions of dollars: 0.9577133440470131\n",
      "Critical Values:\n",
      "  1%: -3.4565688966099373\n",
      "  5%: -2.8730786194395455\n",
      "  10%: -2.5729189953388762\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for GovTotExp : Billions of dollars: 2.7291557866089486\n",
      "P-value for GovTotExp : Billions of dollars: 0.9990880001645039\n",
      "Critical Values:\n",
      "  1%: -3.4577787098622674\n",
      "  5%: -2.873608704758507\n",
      "  10%: -2.573201765981991\n",
      "\n",
      "========================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import adfuller\n",
    "\n",
    "for column in data.columns:\n",
    "    if column != 'Date':\n",
    "        result = adfuller(data[column])\n",
    "        print(f\"ADF Statistic for {column}: {result[0]}\")\n",
    "        print(f\"P-value for {column}: {result[1]}\")\n",
    "        print(\"Critical Values:\")\n",
    "        for key, value in result[4].items():\n",
    "            print(f\"  {key}: {value}\")\n",
    "\n",
    "        print(\"\\n\" + \"=\" * 40 + \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19293db9",
   "metadata": {},
   "source": [
    "The numbers we are interested from this test are the P-values. A P-value close to zero (equal to or less than 0.05) implies stationarity while a value closer to 1 implies nonstationarity. We can see that all of our time series are highly unstationary due to their statistically insignificant p-values, in other words we are unable to reject the null hypothesis for stationarity. Below is a simple visual representation of the test. The red dotted line represents the P-value where we would be able to determine stationarity for the time series, the blue box represents the P-value where we are at currently."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8c1d1c42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x3000 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "adf_results = []\n",
    "\n",
    "for column in data.columns:\n",
    "    if column != 'Date':  \n",
    "        result = adfuller(data[column])\n",
    "        adf_results.append({\n",
    "            'Feature': column,\n",
    "            'ADF Statistic': result[0],\n",
    "            'P-value': result[1],\n",
    "            'Critical Values': result[4]\n",
    "        })\n",
    "\n",
    "adf_df = pd.DataFrame(adf_results)\n",
    "\n",
    "fig, axes = plt.subplots(nrows=len(adf_df), figsize=(12, 6 * len(adf_df)))\n",
    "\n",
    "for idx, row in adf_df.iterrows():\n",
    "    ax = axes[idx] if len(adf_df) > 1 else axes  \n",
    "\n",
    "    ax.bar(row['Feature'] + '_P-value', row['P-value'], color='skyblue')\n",
    "    ax.text(row['Feature'] + '_P-value', row['P-value'] + 0.005, f\"{row['P-value']:.4f}\", ha='center')\n",
    "    \n",
    "    ax.set_title(f'ADF Test Results for {row[\"Feature\"]}')\n",
    "    ax.set_ylabel('Value')\n",
    "    ax.axhline(y=0.05, color='red', linestyle='--', label='Significance Level (0.05)')\n",
    "    ax.legend()\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b2e1087",
   "metadata": {},
   "source": [
    "Below is a VIF (variance inflation factor) test. The purpose is to check for multicollinearity, or the degree of correlation the predictors share with one another. High multicollineaity is not necessairly detrimental for our forecast, however, it can make it much harder for us to determine the individual effect of each feature time series for the prediction, thus hurting the interpretability of the model. Usually a score less than 5 implies no multicollinearity, implying that our features are extremely higly correlated with one another. This will play into our model selection for later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f5763592",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dronm\\AppData\\Local\\Temp\\ipykernel_49020\\2334127177.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  X['intercept'] = 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                           Feature         VIF\n",
      "0        PCE : Billions of dollars  170.028884\n",
      "1       GPDI : Billions of dollars   77.277626\n",
      "2     NETEXP : Billions of dollars    7.335556\n",
      "3  GovTotExp : Billions of dollars   52.196119\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.stats.outliers_influence import variance_inflation_factor\n",
    "\n",
    "\n",
    "X = data.iloc[:, [2, 3, 4, 5]]\n",
    "X['intercept'] = 1\n",
    "X = X[['intercept'] + [col for col in X if col != 'intercept']]\n",
    "\n",
    "vif_data = pd.DataFrame()\n",
    "vif_data[\"Feature\"] = X.columns[1:] \n",
    "vif_data[\"VIF\"] = [variance_inflation_factor(X.values, i) for i in range(1, X.shape[1])]\n",
    "\n",
    "print(vif_data)\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.bar(vif_data[\"Feature\"], vif_data[\"VIF\"], color='skyblue')\n",
    "plt.title('VIF Scores for Features')\n",
    "plt.xlabel('Features')\n",
    "plt.ylabel('VIF Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3705fa8",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "f4c296a4",
   "metadata": {},
   "source": [
    "# Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ec5f0d",
   "metadata": {},
   "source": [
    "# VAR forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "134139b7",
   "metadata": {},
   "source": [
    "To use the Vector Auto Regression (VAR) model we need to first ensure our data is stationary. we can achieve this using a technique called differencing which essentially is a tranformation of the raw data. It is defined mathematically as \n",
    "y'(t) = y(t)-y(t-1). We are taking values from our time series and calculating the change which occured following the previous point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ffb58a6a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ADF Statistic for GDP : Billions of dollars: -3.906538294382316\n",
      "P-value for GDP : Billions of dollars: 0.0019872523174590214\n",
      "Critical Values:\n",
      "  1%: -3.4566744514553016\n",
      "  5%: -2.8731248767783426\n",
      "  10%: -2.5729436702592023\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for PCE : Billions of dollars: -6.0438368049790725\n",
      "P-value for PCE : Billions of dollars: 1.3263283721705999e-07\n",
      "Critical Values:\n",
      "  1%: -3.4564641849494113\n",
      "  5%: -2.873032730098417\n",
      "  10%: -2.572894516864816\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for GPDI : Billions of dollars: -14.67874111897741\n",
      "P-value for GPDI : Billions of dollars: 3.180913951450319e-27\n",
      "Critical Values:\n",
      "  1%: -3.4562572510874396\n",
      "  5%: -2.8729420379793598\n",
      "  10%: -2.5728461399461744\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for NETEXP : Billions of dollars: -8.837398948334888\n",
      "P-value for NETEXP : Billions of dollars: 1.7044265762844e-14\n",
      "Critical Values:\n",
      "  1%: -3.4565688966099373\n",
      "  5%: -2.8730786194395455\n",
      "  10%: -2.5729189953388762\n",
      "\n",
      "========================================\n",
      "\n",
      "ADF Statistic for GovTotExp : Billions of dollars: -3.110199822877988\n",
      "P-value for GovTotExp : Billions of dollars: 0.0258075066297484\n",
      "Critical Values:\n",
      "  1%: -3.4577787098622674\n",
      "  5%: -2.873608704758507\n",
      "  10%: -2.573201765981991\n",
      "\n",
      "========================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "data_diff = data.drop('Date', axis=1).diff().dropna()\n",
    "for column in data_diff.columns:\n",
    "    result = adfuller(data_diff[column])\n",
    "    print(f\"ADF Statistic for {column}: {result[0]}\")\n",
    "    print(f\"P-value for {column}: {result[1]}\")\n",
    "    print(\"Critical Values:\")\n",
    "    for key, value in result[4].items():\n",
    "        print(f\"  {key}: {value}\")\n",
    "\n",
    "    print(\"\\n\" + \"=\" * 40 + \"\\n\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1fa0010c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "fig.suptitle('Features vs Time', y=1.02)\n",
    "\n",
    "for i, feature in enumerate(data_diff.columns):\n",
    "    ax.plot(data['Date'][1:], data_diff[feature], label=feature, color=plt.cm.viridis(i / len(data_diff.columns)))\n",
    "\n",
    "ax.set_xlabel('Date')\n",
    "ax.set_ylabel('Difference')\n",
    "ax.legend(loc='upper left', bbox_to_anchor=(1, 1))\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f411106c",
   "metadata": {},
   "source": [
    "Below is an Autocorrelation Function (ACF) plot which tells us the significance that previous lags have to the current lag. This is usually helpful in evaluating factors like seasonality which are important for certain models. We can see that for the most part, previous lags have reasonably small scores in relation to our time series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3ec3fe67",
   "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"
    },
    {
     "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"
    },
    {
     "data": {
      "image/png": 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ys7M1ty5duiA9PR0nTpwosLbs7GzMnz8fPj4+kMvlKFeuHORyOa5evapzmNJYhw4dAqC77Zo1a4a6devqrK+rqyuaNWum1ebn56ez27ggr7/+Ok6fPq11Gz9+/AvV3rBhQ1SrVk1z39raGrVq1dKqZe/evWjXrh3q1q37Qs+RX3Ftr9TUVDx58gTOzs46jwkhNIf/goKCAADe3t5o27Yttm3bhrS0NFNXS0uNGjV0fkeffPKJTj9nZ2eo1WokJycXOJYQQuvvPDs7+4VqCg0NhZWVleaW9/DlwYMH0aFDB51zvYYNG4YnT55oDhV17twZrq6uWL9+vabPL7/8gtu3bxt1+Cf3uXLHziv/e40x3nvvPZ3tfPr0aZ0LKL744gvUq1cP7dq1w+HDh7Fp0ya9h0nr1auHBg0aaLUNHDgQaWlpOHv2rMFaZs2ahezsbLRp08ao2vO+jn/99VesXbsWd+/eRfv27XWuDJTClStXcPv2bYSEhMDC4vlHsL29PXr37o0TJ07onGaS/xC3n58f0tPTcefOHQDQnALQr18/fPfdd0Zf5Srl30CumJgYpKenY9CgQVrtgYGB8PT01Hl+Hx8fnfeVYcOGQQihqc9Yjx49wtSpU/Haa6+hXLlyKFeuHOzt7fH48WO9nyv6Pu+aNWuG8PBw/Pe//8WJEyeQlZVlUg0Az7Eq1LVr13DkyBF07doVQgikpqYiNTUVffr0AQC958G8jPv376NcuXJwcnLSapfJZHB1ddWc6Hr37l0Ahq+6ye2r743L3d1d56RZW1tbODg46B0r/xj3799HdnY2li1bpvUhYWVlhS5dugCAwTel0NBQzJw5Ez179sSuXbtw8uRJnD59Gg0aNMDTp08LXM4QU9e3cuXKOv0UCoXRz69UKtGkSROtm7u7+wtUblwtd+/elfTk8+LaXrmPW1tb6zx28OBBxMfHo2/fvkhLS9O8vvr164cnT55gy5YtAABHR0fY2toiPj7euJX7l7W1tc7vyNvbW2+/vLXqEx0drfO3nvdcufyqVauGu3fv6nxIvv/++5oPcn2vq4J+H7mPA0C5cuUQEhKC7du3a86FCQ8Ph5ubGzp27FhgTfmfy5j3GmNUrVpVZzs3adJE58oxhUKBgQMHIj09HQ0bNtSE6fxcXV0LbJP6ZP+8r+PAwECMGDEC3377LS5fvozPP/9c0ucCCn/dqdVqpKSkaLXnf+3lnmOY+/faunVr7NixA9nZ2RgyZAiqVq0KX19fzevHUC1S/Q3kHRMw/DvM29eYv3djDRw4EMuXL8eoUaPwyy+/4NSpUzh9+jScnJz0vrb1PXdERASGDh2Kb775BgEBAahUqRKGDBli8D9d+TFYFWLdunUQQuCHH35AxYoVNbeuXbsCADZs2KCZhyb3zTnvJc6A4YCRX+XKlZGdna0JTrmEEEhOTtZczZP7Qsh/knH+sQAgKSlJ57Hbt2/rXBlk6MTM/I9VrFgRlpaWGDZsmN7/qZ4+fVoTsPTZtGkThgwZgvnz56Njx45o1qwZmjRp8lL/QzR1fYuSFH8L+Tk5ORn8fZuquLZX7vPknWMqV+6FFosXL9Z6fY0bN07rcUtLS3To0AFnzpyRdBvkyq3N0Dr7+/vr/I0bCtJBQUHIycnBnj17tNo9PDw0H+RyuVzrscqVKxf4+8hf3/Dhw5Geno6tW7ciJSUFO3fuxJAhQ2BpaVn4CsP49xopXbx4EbNmzULTpk1x9uxZLF68WG8/fR9iuW36Ar7U/Pz8AADnz5+XfOzCXncWFhZaRweM9eabb+LAgQNQqVQ4fPgwqlatioEDB+qcEJ+/Fqn/BnLXz9DvMG9fY//eC6NSqfDzzz/jo48+wrRp09ChQwc0bdoU9evX1/veA+j/zHN0dMSSJUtw/fp13LhxA2FhYfjxxx8LnGpEHwYrA3JycrBhwwbUqFEDhw4d0rm9//77SEpK0lztkHulzIULF7TG2blzp87Y+f/HkSv3SrzcOX1ybdu2DY8fP9Y8HhwcDEtLS3z11VcF1h8QEAAbGxudsW7evKk55PCibG1t0a5dO5w7dw5+fn56/7dq6A1QJpPpXNm1e/dunV3YBW0nfdq3bw9Ad9udPn0aly9ffqn1NVVBfwu7du164TE7d+6MQ4cO4cqVKwX2KYnbSy6Xo3r16vjrr7+02lNSUrB9+3a0bNlS7+tr0KBBOH36tGYyz+nTp0MIgdGjRyMzM1PnebKysl54+/7999+oXLkyXFxcCuxTvnx5nb/x/MEor1GjRsHFxQUfffSR3g8PfTp06ICDBw9qPlhybdy4Eba2tlqX7detWxfNmzfH+vXr8e233yIjIwPDhw836nlynwso/L0GMG1PbkEeP36Mvn37wsvLC4cOHcLEiRMxbdo0nDx5UqfvpUuXdELNt99+i/Lly6Nx48YvVYcxcifY1Xf4+mXVrl0bVapUwbfffqt15evjx4+xbds2zZWCL0qhUKBNmzZYsGABAODcuXMF9jXlb8BYLVq0gLW1tc78ccePH9c5baBDhw74/fffdQ7vbty4ETKZTOeKWUNkMhmEEDqfK998880LT8JbrVo1TJw4EUFBQYUegs6L81gZsHfvXty+fRsLFizQO1usr68vli9fjrVr16Jbt25wdXXFG2+8gbCwMFSsWBGenp44cOAAfvzxR51l69evDwBYsGABOnfuDEtLS/j5+SEoKAgdO3bE1KlTkZaWhpYtW+LChQuYPXs2GjVqhJCQEADPPrhnzJiBTz75BE+fPtVcivv777/j3r17mDt3LipUqICZM2dixowZGDJkCN5++23cv38fc+fOhbW1NWbPnv1S2+fLL7/E66+/jlatWmHcuHHw8vLCw4cPce3aNezatcvg8fFu3bohPDwcderUgZ+fH86cOYNFixbpHOqqUaMGbGxssHnzZtStWxf29vZwd3fXu6egdu3aGDNmDJYtWwYLCwt07twZ169fx8yZM+Hh4YEpU6a81PqaokuXLqhUqRJGjhyJefPmoVy5cggPD0diYuILjzlv3jzs3bsXrVu3xowZM1C/fn2kpqYiMjISoaGhqFOnTondXm3bttW53Hrz5s1IT0/HpEmT9L6+KleujM2bN2Pt2rX44osvEBAQgK+++grjx4+Hv78/xo0bh3r16iErKwvnzp3D6tWr4evri+7du5tc34kTJ9CmTRtJZ6avUKECduzYge7du6NBgwZaE4Tev38fR44cQXJyMgIDAzXLzJ49Gz///DPatWuHWbNmoVKlSti8eTN2796NhQsXak3sCQAjRozAO++8g9u3byMwMBC1a9c2uj5j32uAZ+9XW7duRUREBKpXrw5ra2vNexjw7JJ5fedUOjk5aSYgHTt2LBISEnDq1CnY2dnh888/R0xMDAYMGIBz586hQoUKmuXc3d3Ro0cPzJkzB25ubti0aROioqKwYMGCQkPHvHnzMG/ePBw4cMCo86xSU1M1tWdlZeHy5cuYP38+FAqFwXNYX5SFhQUWLlyIQYMGoVu3bnjnnXeQkZGBRYsWITU1FZ9++qnJY86aNQs3b95Ehw4dULVqVaSmpuLLL7+ElZWVwW1gyt+AsSpWrIgPPvgA//3vfzFq1Cj07dsXiYmJmDNnjs6hwClTpmDjxo3o2rUr5s2bB09PT+zevRsrV67EuHHjNHOIGcPBwQGtW7fGokWL4OjoCC8vL0RHR2Pt2rVaf1uGqFQqtGvXDgMHDkSdOnVQvnx5nD59GpGRkXjrrbeM3wgvdep7GdezZ08hl8sNXlY6YMAAUa5cOZGcnCyEeHYJcZ8+fUSlSpWEUqkUgwcPFrGxsTpXamVkZIhRo0YJJycnIZPJtK4Ue/r0qZg6darw9PQUVlZWws3NTYwbN06kpKToPP/GjRtF06ZNhbW1tbC3txeNGjXSuSLsm2++EX5+fkIulwulUinefPNNcenSJa0+hq74ACAmTJig97H4+HgxYsQIUaVKFWFlZSWcnJxEYGCg+O9//6vVJ//6p6SkiJEjRwpnZ2dha2srXn/9dXH06FG9V9ls2bJF1KlTR1hZWWldGaLvKp2cnByxYMECUatWLWFlZSUcHR3F4MGDNVMO5Mq9FD+/oUOHCk9PT73rmpenp6fo2rWrwT6nTp0SgYGBws7OTlSpUkXMnj1bM1VH/qsC9Y2lb1skJiaKESNGCFdXV2FlZSXc3d1Fv379xD///KPpUxK314EDBwQAcerUKU1bw4YNhbOzs8jIyChwuRYtWghHR0etPnFxcWLo0KGiWrVqQi6Xay4NnzVrltZrtaCa87t27ZoAILZt21Zo3xeRnJwspk+fLvz8/ISdnZ3m99a9e3exceNGnWkJfvvtN9G9e3ehVCqFXC4XDRo0KPCKWpVKJWxsbAQAsWbNGoN15L8qUAjj32uuX78ugoODRfny5QUAze+8sKsCc6/AXLNmjd6rVa9duyYcHBxEz549NW25r4cffvhB1KtXT8jlcuHl5SUWL15scP3yr6ex0y3krdfS0lJUq1ZN9OnTR5w7d07vuHm96HQLQgixY8cO0bx5c2FtbS3s7OxEhw4dxK+//qr3OfP+zoTQvbr4559/Fp07dxZVqlQRcrlcODs7iy5duuhclamPsX8Dxl4VKMSzaRzCwsKEh4eHkMvlws/PT+zatUvv9rpx44YYOHCgqFy5srCyshK1a9cWixYt0plKxJjtevPmTdG7d29RsWJFUb58edGpUydx8eJF4enpKYYOHarpl7v9Tp8+rfUc6enpYuzYscLPz084ODgIGxsbUbt2bTF79myTpk2R/VswEVGR8vPzQ8uWLQ0evjaHmTNnYuPGjfjrr79Qrhx34publ5cXfH198fPPP5u7FKIXwnOsiKhYLFy4EOHh4UVy8vmLSk1NxYoVKzB//nyGKiKSBIMVERWLTp06YdGiRSZPmVCU4uPjMX36dL1fIExE9CJ4KJCIiIhIIqVqj9WRI0fQvXt3uLu7QyaTYceOHYUuEx0dDX9/f80Xea5atUqnz7Zt2+Dj4wOFQgEfHx9s3769CKonIiKisq5UBavHjx+jQYMGWL58uVH94+Pj0aVLF7Rq1Qrnzp3DjBkzMGnSJGzbtk3TJyYmBv3790dISAjOnz+PkJAQ9OvXT+/cKkRERESGlNpDgTKZDNu3b0fPnj0L7DN16lTs3LlT6zuCxo4di/Pnz2tmo+3fvz/S0tK05tjp1KkTKlasWOjXARARERHlVaYvg4mJiUFwcLBWW8eOHbF27VpkZWXBysoKMTExOhMhduzYEUuWLClw3IyMDK2vKlGr1Xjw4AEqV64s6QSDREREVHSEEHj48CHc3d21vhT7ZZTpYJWcnKzzFRUuLi7Izs7GvXv34ObmVmAfQ1+4GBYWhrlz5xZJzURERFS8EhMTJfuS+zIdrADdL1nMPfKZt11fH0N7nqZPn47Q0FDNfZVKhWrVqiExMREODg4vVe8XUX8i/Ph15Kh1j9BaWsgwLNALU4KMn+afiIiI9EtLS4OHhwfKly8v2ZhlOli5urrq7Hm6c+cOypUrp/mC4IL6GPoyVoVCofNFj8Cz7yp62WA1pE1dbIj9BxZ6znyTyYChberCwcHupZ6DiIiInpPyNJ5SdVWgqQICAhAVFaXVtm/fPjRp0gRWVlYG++T9YtTi5O1ohwW9/WCR53dsKZPBQgYs6O0HL0eGKiIiopKqVO2xevToEa5du6a5Hx8fj7i4OFSqVAnVqlXD9OnTcevWLWzcuBHAsysAly9fjtDQUIwePRoxMTFYu3at1tV+7733Hlq3bo0FCxbgzTffxE8//YT9+/fj2LFjxb5+ufo28YBvFQd0/vJZDcNf98Lg5p4MVURERCVcqdpjFRsbi0aNGqFRo0YAgNDQUDRq1AizZs0CACQlJSEhIUHT39vbG3v27MHhw4fRsGFDfPLJJ1i6dCl69+6t6RMYGIitW7di/fr18PPzQ3h4OCIiItC8efPiXbl8PCs/D1GhQbUYqoiIiEqBUjuPVUmSlpYGpVIJlUr10udY5XqSmQ2fWb8AAH6f1xG28lK1c5GIiKjEK4rP71K1x4qIiIioJGOwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFESl2wWrlyJby9vWFtbQ1/f38cPXq0wL7Dhg2DTCbTudWrV0/TJzw8XG+f9PT04lgdIiIiKkNKVbCKiIjA5MmT8fHHH+PcuXNo1aoVOnfujISEBL39v/zySyQlJWluiYmJqFSpEvr27avVz8HBQatfUlISrK2ti2OViIiIqAwpVcFq8eLFGDlyJEaNGoW6detiyZIl8PDwwFdffaW3v1KphKurq+YWGxuLlJQUDB8+XKufTCbT6ufq6locq0NERERlTKkJVpmZmThz5gyCg4O12oODg3H8+HGjxli7di3eeOMNeHp6arU/evQInp6eqFq1Krp164Zz584ZHCcjIwNpaWlaNyIiIqJSE6zu3buHnJwcuLi4aLW7uLggOTm50OWTkpKwd+9ejBo1Squ9Tp06CA8Px86dO7FlyxZYW1ujZcuWuHr1aoFjhYWFQalUam4eHh4vtlJERERUppSaYJVLJpNp3RdC6LTpEx4ejgoVKqBnz55a7S1atMDgwYPRoEEDtGrVCt999x1q1aqFZcuWFTjW9OnToVKpNLfExMQXWhciIiIqW8qZuwBjOTo6wtLSUmfv1J07d3T2YuUnhMC6desQEhICuVxusK+FhQWaNm1qcI+VQqGAQqEwvngiIiJ6JZSaPVZyuRz+/v6IiorSao+KikJgYKDBZaOjo3Ht2jWMHDmy0OcRQiAuLg5ubm4vVS8RERG9ekrNHisACA0NRUhICJo0aYKAgACsXr0aCQkJGDt2LIBnh+hu3bqFjRs3ai23du1aNG/eHL6+vjpjzp07Fy1atEDNmjWRlpaGpUuXIi4uDitWrCiWdSIiIqKyo1QFq/79++P+/fuYN28ekpKS4Ovriz179miu8ktKStKZ00qlUmHbtm348ssv9Y6ZmpqKMWPGIDk5GUqlEo0aNcKRI0fQrFmzIl8fIiIiKltkQghh7iJKu7S0NCiVSqhUKjg4OEgy5pPMbPjM+gUA8Pu8jrCVl6oMTEREVOIVxed3qTnHioiIiKikY7AiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkURKXbBauXIlvL29YW1tDX9/fxw9erTAvocPH4ZMJtO5/fHHH1r9tm3bBh8fHygUCvj4+GD79u1FvRpERERUBpWqYBUREYHJkyfj448/xrlz59CqVSt07twZCQkJBpe7cuUKkpKSNLeaNWtqHouJiUH//v0REhKC8+fPIyQkBP369cPJkyeLenWIiIiojJEJIYS5izBW8+bN0bhxY3z11Veatrp166Jnz54ICwvT6X/48GG0a9cOKSkpqFChgt4x+/fvj7S0NOzdu1fT1qlTJ1SsWBFbtmwxqq60tDQolUqoVCo4ODiYtlIFeJKZDZ9ZvwAAfp/XEbbycpKMS0RERM8Uxed3qdljlZmZiTNnziA4OFirPTg4GMePHze4bKNGjeDm5oYOHTrg0KFDWo/FxMTojNmxY8dCxyQiIiLKr9TsBrl37x5ycnLg4uKi1e7i4oLk5GS9y7i5uWH16tXw9/dHRkYG/u///g8dOnTA4cOH0bp1awBAcnKySWMCQEZGBjIyMjT309LSXnS1iIiIqAwpNcEql0wm07ovhNBpy1W7dm3Url1bcz8gIACJiYn47LPPNMHK1DEBICwsDHPnzn2R8omIiKgMKzWHAh0dHWFpaamzJ+nOnTs6e5wMadGiBa5evaq57+rqavKY06dPh0ql0twSExONfn4iIiIqu0pNsJLL5fD390dUVJRWe1RUFAIDA40e59y5c3Bzc9PcDwgI0Blz3759BsdUKBRwcHDQuhERERGVqkOBoaGhCAkJQZMmTRAQEIDVq1cjISEBY8eOBfBsT9KtW7ewceNGAMCSJUvg5eWFevXqITMzE5s2bcK2bduwbds2zZjvvfceWrdujQULFuDNN9/ETz/9hP379+PYsWNmWUciIiIqvUpVsOrfvz/u37+PefPmISkpCb6+vtizZw88PT0BAElJSVpzWmVmZuKDDz7ArVu3YGNjg3r16mH37t3o0qWLpk9gYCC2bt2K//znP5g5cyZq1KiBiIgING/evNjXj4iIiEq3UjWPVUnFeayIiIhKn1d6HisiIiKiko7BioiIiEgiDFZEREREEmGwIiIiIpIIz4gmkkj8vcf4LjYRN1OeompFG/Rr4gFvRztzl0VERMWIwYpIAt/FJmLatguQyWSar0T6OvovLOjth75NPMxdHhERFRMeCiR6SfH3HmPatgtQCyBHLbT+nbrtAq7fe2zuEomIqJgwWBG9pO9iEwv80m6ZTIaIWH6XJBHRq4LBiugl3Ux5ioLm2RVC4GbK02KuiIiIzIXBiuglVa1oY3CPVdWKNsVcERERmQuDFdFL6tfEw+Aeq/48eZ2I6JXBYEX0krwd7bCgtx8s8uy0spTJYCEDFvT2gxenXCAiemVwugUiCfRt4gHfKg7o/OUxAMDw170wuLknQxUR0SuGwYpIIp6Vn4eo0KBasJXz5UVE9KrhoUAiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikkipC1YrV66Et7c3rK2t4e/vj6NHjxbY98cff0RQUBCcnJzg4OCAgIAA/PLLL1p9wsPDIZPJdG7p6elFvSpERERUxpgcrB4/foyZM2ciMDAQr732GqpXr651K0oRERGYPHkyPv74Y5w7dw6tWrVC586dkZCQoLf/kSNHEBQUhD179uDMmTNo164dunfvjnPnzmn1c3BwQFJSktbN2tq6SNeFiIiIyp5ypi4watQoREdHIyQkBG5ubpDJZEVRl16LFy/GyJEjMWrUKADAkiVL8Msvv+Crr75CWFiYTv8lS5Zo3Z8/fz5++ukn7Nq1C40aNdK0y2QyuLq6FmntREREVPaZHKz27t2L3bt3o2XLlkVRT4EyMzNx5swZTJs2Tas9ODgYx48fN2oMtVqNhw8folKlSlrtjx49gqenJ3JyctCwYUN88sknWsGLiIiIyBgmHwqsWLGiTjApDvfu3UNOTg5cXFy02l1cXJCcnGzUGJ9//jkeP36Mfv36adrq1KmD8PBw7Ny5E1u2bIG1tTVatmyJq1evFjhORkYG0tLStG5EREREJgerTz75BLNmzcKTJ0+Kop5C5T/0KIQw6nDkli1bMGfOHERERMDZ2VnT3qJFCwwePBgNGjRAq1at8N1336FWrVpYtmxZgWOFhYVBqVRqbh4eHi++QkRERFRmmHwo8PPPP8dff/0FFxcXeHl5wcrKSuvxs2fPSlZcXo6OjrC0tNTZO3Xnzh2dvVj5RUREYOTIkfj+++/xxhtvGOxrYWGBpk2bGtxjNX36dISGhmrup6WlMVwRERGR6cGqZ8+eRVBG4eRyOfz9/REVFYVevXpp2qOiovDmm28WuNyWLVswYsQIbNmyBV27di30eYQQiIuLQ/369Qvso1AooFAoTFsBIiIiKvNMDlazZ88uijqMEhoaipCQEDRp0gQBAQFYvXo1EhISMHbsWADP9iTdunULGzduBPAsVA0ZMgRffvklWrRoodnbZWNjA6VSCQCYO3cuWrRogZo1ayItLQ1Lly5FXFwcVqxYYZ6VJCIiolLL5GCV68yZM7h8+TJkMhl8fHyK5Sq6/v374/79+5g3bx6SkpLg6+uLPXv2wNPTEwCQlJSkNafV119/jezsbEyYMAETJkzQtA8dOhTh4eEAgNTUVIwZMwbJyclQKpVo1KgRjhw5gmbNmhX5+hAREVHZIhNCCFMWuHPnDgYMGIDDhw+jQoUKEEJApVKhXbt22Lp1K5ycnIqq1hIrLS0NSqUSKpUKDg4Okoz5JDMbPrOezRL/+7yOsJW/cAamYsLfGRFR6VIUn98mXxX47rvvIi0tDZcuXcKDBw+QkpKCixcvIi0tDZMmTZKkKCIiIqLSyOT/UkdGRmL//v2oW7eups3HxwcrVqxAcHCwpMURERERlSYm77FSq9U6UywAgJWVFdRqtSRFEREREZVGJger9u3b47333sPt27c1bbdu3cKUKVPQoUMHSYsjIiIiKk1MDlbLly/Hw4cP4eXlhRo1auC1116Dt7c3Hj58aHC2ciIiIqKyzuRzrDw8PHD27FlERUXhjz/+gBACPj4+hc5oTkRERFTWvfD14EFBQQgKCpKyFiIiIqJSzahgtXTpUowZMwbW1tZYunSpwb6ccoGIiIheVUYFqy+++AKDBg2CtbU1vvjiiwL7yWQyBisiIiLSYuJc5DpkMplElRQ9o4JVfHy83p+J6NUihIBaAGohoBYCQvPz88f09RH57ktfl4n9UfAC+sbS1zv/B4X+Pvqf3bh++sc0dlntcQrvZNQ4Rm5nY57P1DGLglTPnX99844rtNqF3nbdWkQB7fnH0z+2bn0vz5y/JwB4zdkeTuUV5i3CSCafYzVv3jx88MEHsLW11Wp/+vQpFi1ahFmzZklWHBGZJjtHjawcgcwctebnHCGgVgvtcIN8AUiN5yEIz9s1fdS5y5h7DYmISjaTg9XcuXMxduxYnWD15MkTzJ07l8GKSGJZOep/b+L5z9kCWernP+cGKTWDDxGRWZkcrIQQeo91nj9/HpUqVZKkKKKyTAiBrByBbPXzUJSVo0Z2zvOf8wYp7iUiIio9jA5WFStWhEwmg0wmQ61atbTCVU5ODh49eoSxY8cWSZFE5iY0h8n+/RnQOl9ICOBJZram/72HmShnmaV/b1NO0ZxnRERE5md0sFqyZAmEEBgxYgTmzp0LpVKpeUwul8PLywsBAQFFUiS9mnLU4vlNCK37aiGQrX5+7lDueUFCPD8XSOtnPD/HKG8YKnQ5Yfy5RelZOZqf/7r7CNZWltJvFCIiKtGMDlZDhw4FAHh7eyMwMFDvFzHTq00I3RCkVgPZavW/J1A/+1mtxr991MhRQyso5f6co+ZeHSIiKn1MPseqTZs2mp+fPn2KrKwsrccdHBxevioqNur8e4P+vYIsd29QjhDIznkedgrae5QbkIiIiF5lJgerJ0+e4KOPPsJ3332H+/fv6zyek5OjZykytzsP03EnLUMrPD0LReaujIio9ElSPcXhK3dx91EGnOwVaFvbCW5KG3OXRSWAycHqww8/xKFDh7By5UoMGTIEK1aswK1bt/D111/j008/LYoaSQIZWWo8TM8uvCMRERl0+ModrD76N2R4dkGLDMCuC7fxTuvqaFPL2czVkbmZHKx27dqFjRs3om3bthgxYgRatWqF1157DZ6enti8eTMGDRpUFHUSERGZXZLqKVYf/VtzlTDw/N+vj/yN2i4OcFVam6s8KgEsTF3gwYMH8Pb2BvDsfKoHDx4AAF5//XUcOXJE2uqIiIhKkMNX7qKgb62TATh05U5xlkMlkMnBqnr16rh+/ToAwMfHB9999x2AZ3uyKlSoIGVtREREJcrdRxkFfvee+PdxerWZHKyGDx+O8+fPAwCmT5+OlStXQqFQYMqUKfjwww8lL5CIiKikcLJXGNxj5WRfOr4omIqOyedYTZkyRfNzu3bt8McffyA2NhY1atRAgwYNJC2OiIioJGlb2wm7LtzW+5gA0K42T15/1ZkcrPKrVq0aqlWrJkUtREREJZqb0gbvtK6Or4/8rZnE2EL2LFS907o6T1wn44LV0qVLjR5w0qRJL1wMERGVDJynqWBtajnDq7Idpv34GwCgk68rguq6MlQRACOD1RdffGHUYDKZjMGKiPTiB3XpwXmaCufi8DxE9fX34HeDkoZRwSo+Pr6o6yCiMowf1KUH52kiejkmXxWYKzMzE1euXEF2NmfzJqKC5f2gVgto/fv1kb+RrEo3d4mUB+dpIno5JgerJ0+eYOTIkbC1tUW9evWQkJAA4Nm5VfxKGyLKjx/UpQvnaSJ6OSYHq+nTp+P8+fM4fPgwrK2f7w5+4403EBERIWlxRFT68YO6dOE8TUQvx+RgtWPHDixfvhyvv/46ZLLnLz8fHx/89ddfkhZHRKUfP6hLl7a1nQwGYc7TRGSYycHq7t27cHbWfWE9fvxYK2gREQH8oC5tcudpyvt2biEDZDLO00TGS1I9xZZTCVh68Cq2nEpAkuqpuUsqNiYHq6ZNm2L37t2a+7lhas2aNQgICJCuMiIqE/hBXfq0qeWMsF71Nfc7+bpicd+GvIKTjHL4yh28//15/HzhNk78fR8/X7iN978/j+g/X43zKU2eeT0sLAydOnXC77//juzsbHz55Ze4dOkSYmJiEB0dXRQ1ElEpxwkVSx/O00QvgtN1vMAeq8DAQBw/fhxPnjxBjRo1sG/fPri4uCAmJgb+/v5FUSMRlQH5P6jL+psr0auIVwGbGKyysrIwfPhw2NraYsOGDbh48SJ+//13bNq0CfXr1y98AAmsXLkS3t7esLa2hr+/P44ePWqwf3R0NPz9/WFtbY3q1atj1apVOn22bdsGHx8fKBQK+Pj4YPv27UVVPhERUZnFq4BNDFZWVlZmDR0RERGYPHkyPv74Y5w7dw6tWrVC586dNXNp5RcfH48uXbqgVatWOHfuHGbMmIFJkyZh27Ztmj4xMTHo378/QkJCcP78eYSEhKBfv344efJkca0WERFRmcCrgF/gHKtevXphx44dCA0NLYp6DFq8eDFGjhyJUaNGAQCWLFmCX375BV999RXCwsJ0+q9atQrVqlXDkiVLAAB169ZFbGwsPvvsM/Tu3VszRlBQEKZPnw7g2Txd0dHRWLJkCbZs2WJSfU8ys1EuU5qZ6J/kGeeJBGM+zcxBelbOS49DBcvIs30zuK11cPuULvx9Gcbto19AjcrYdeG23scEgMAalV/os+hpZo4kn4X5FcWYJger1157DZ988gmOHz8Of39/2NnZaT1eVF/CnJmZiTNnzmDatGla7cHBwTh+/LjeZWJiYhAcHKzV1rFjR6xduxZZWVmwsrJCTEwMpkyZotMnN4zpk5GRgYyM57sz09LSAADN/ncAFgpbU1bLKE3+e0DyMalojd181twllGjcPqULf1+GcfsYRwhoLmApKdQZTyQf0+Rg9c0336BChQo4c+YMzpw5o/WYTCYrsmB179495OTkwMXFRavdxcUFycnJepdJTk7W2z87Oxv37t2Dm5tbgX0KGhN4dmXk3LlzX3BNiIiIqKwyKVgJIXDo0CE4OzvD1lb6PTPGyD8JqRDC4MSk+vrnbzd1zOnTp2sdCk1LS4OHhwdOfdwBDg4Oha+EGdx88BS3Ul9ugraMrBzN/8xWDWoMhZkvvy5p9ZQ03D6GlbTtU9LqKWm4fQwr69unhpM9HMvLJR83LS0NbkukHdPkYFWrVi1cunQJNWvWlLaSQjg6OsLS0lJnT9KdO3d09jjlcnV11du/XLlyqFy5ssE+BY0JAAqFAgqF7gl4tvJysJWbvBOwWNjILSWdh0ZhJe14L6uk1VPScPsYVtK2T0mrpyRITkvX/Lzzwm28UdcFbkobM1ZUcpXFvx8buWWRfL5mF8GYJl0VaGFhgZo1a+L+/fuSF1IYuVwOf39/REVFabVHRUUhMDBQ7zIBAQE6/fft24cmTZrAysrKYJ+CxiQiouJ1+ModzNj+/NycyIvJr9RM3lS6mDxB6MKFC/Hhhx/i4sWLRVGPQaGhofjmm2+wbt06XL58GVOmTEFCQgLGjh0L4NkhuiFDhmj6jx07Fjdu3EBoaCguX76MdevWYe3atfjggw80fd577z3s27cPCxYswB9//IEFCxZg//79mDx5cnGvHhER5ZN3Ju9cavHsROivj/yNZFV6wQsTmYHJ+8AGDx6MJ0+eoEGDBpDL5bCx0d4V++DBA8mKy69///64f/8+5s2bh6SkJPj6+mLPnj3w9PQEACQlJWnNaeXt7Y09e/ZgypQpWLFiBdzd3bF06VLNVAvAs5nkt27div/85z+YOXMmatSogYiICDRv3rzI1oOIiIyTO5O3vkknc2fyfrtZtWKuiqhgJgcrQ9MQFIfx48dj/Pjxeh8LDw/XaWvTpg3OnjV8KWyfPn3Qp08fKcojIiIJcSZv4+Q9B+37M4k8B82MTA5WQ4cOLYo6iIheafxg1C93Ju+C9li9CjN5F+bwlTtYffRvzf3Ii8nYezEZ77Sujja1nM1Y2avphU6Hz8nJwY4dO3D58mXIZDL4+PigR48esLQsW1chEBEVB34wFqxtbSeDM3m3q/1qb5+CzkEDnp2DVtvFgV94XsxMDlbXrl1Dly5dcOvWLdSuXRtCCPz555/w8PDA7t27UaNGjaKok4ioTOIHo2FuShu807o6vj7yt2bPVe6/77Su/kpvG4DnoJVEJgerSZMmoUaNGjhx4gQqVaoEALh//z4GDx6MSZMmYffu3ZIXSURUVvGDsXBtajmjtosDDl25g7uPMuBkr0C72s6vfKgCeA5aSWRysIqOjtYKVQBQuXJlfPrpp2jZsqWkxRERFZWSck4TPxiN46q0fuUDpj48B63kMXkeK4VCgYcPH+q0P3r0CHK59NPNExFJrSRNOJn7wagPPxipMG1rOxkM5q/6OWjmYHKw6tatG8aMGYOTJ09CCAEhBE6cOIGxY8eiR48eRVEjEZFkStqEk/xgpJeRew6aTAZYyKD1L89BMw+TDwUuXboUQ4cORUBAgOZrYbKzs9GjRw98+eWXkhdIRCSlknZOE0/OppfFc9BKFpODVYUKFfDTTz/h2rVruHz5MoQQ8PHxwWuvvVYU9RERSaokntPED0Z6WTwHreR44a91fu211ximiKjUKakn+/KDkahsMPkcqz59+uDTTz/VaV+0aBH69u0rSVFEREWF5zQRUVEyOVhFR0eja9euOu2dOnXCkSNHJCmKiKio8GRfIipKJh8KLGhaBSsrK6SlpUlSFBFRUeI5TURUVEwOVr6+voiIiMCsWbO02rdu3QofHx/JCiMiKko8p4mIioLJwWrmzJno3bs3/vrrL7Rv3x4AcODAAWzZsgXff/+95AUSERERlRYmB6sePXpgx44dmD9/Pn744QfY2NjAz88P+/fvR5s2bYqiRpKAvaIcnB0UUKsFstUCOWoBtXj2s1pz39xVEhERlW4vNN1C165d9Z7ATiVXRTs5KtoZ/sohtVogR+gPXTlqgUcZ2Zq+zg4KKMpZPA9paiBbrYZaCOSogRymNCIiegW98DxWZ86cweXLlyGTyeDj44NGjRpJWReZgYWFDBaQwcpS/+P2mc+DlbejHWzlBf/5iH8DWo7IE7rUQI4QWj/n5DwPczl59qTl/LtnLfdnwZxGRESlgMnB6s6dOxgwYAAOHz6MChUqQAgBlUqFdu3aYevWrXByciqKOqmUkclkKGcpy/MHVkBaM1JOvsOXOWqBx+nPg151RztYyy2hFs9CmAD+/S5L/Hv/eXtuH/zbps77eEE/F7ScEP8+10utHhERlREmB6t3330XaWlpuHTpEurWrQsA+P333zF06FBMmjQJW7ZskbxIIksLGSwtZFptVpbP7zs5KAzuQSsOQjw7Ty0rR41stUBWthpZOWpk5qiRnSM0P2flCGT/+y8REZUtJn8SRUZGYv/+/ZpQBQA+Pj5YsWIFgoODJS2OqDSRyWSwlAGWFv/unSvkm1GEEFpBK/fnrGw1stVqZGY/C2NZDGFERKWGycFKrVbDyspKp93KygpqtVqSooheBTKZDIpyllAY8SoUQjwLXXmC1vOfn4WwbPXzx3hokojIPEwOVu3bt8d7772HLVu2wN3dHQBw69YtTJkyBR06dJC8QCJ6FsLk5WSQlyv8W6hyQ1haeqam7TVneyisLIB/zw1TC6E5Z0z97yFMke/fvH1Envv5+zDEERE9Z3KwWr58Od588014eXnBw8MDMpkMCQkJqF+/PjZt2lQUNRLpdf3+Y83Pi6P+xKDmnvB2tDNjRSVDbgjLe85ZZXt5kZ6DplY/D115A5vmpH91nqBm4timBjeTn0FPd30j6KtD33Pl76d/rMKXM5UxyxuzbYytw9hy9a3ry4z3bEwTOr8Q058gb035l9Z+TOhtN6WfMcsYIsX2e9khjP27yJX/HNuSzOR3Wg8PD5w9exZRUVH4448/IISAj48P3njjjaKoj0iv72ITMW3bBc399ceuY92xeCzo7Ye+TTzMWNmrKXeqDiKiV53JwWrjxo3o378/goKCEBQUpGnPzMzE1q1bMWTIEEkLJMov/t5jTNt2QWum+Jx///czddsFNPWqBC/uuSIiIjMo/ISNfIYPHw6VSqXT/vDhQwwfPlySoogM+S42ETKZ/r0jMpkMEbGJxVwRERHRMyYHKyGE3g+1mzdvQqlUSlIUkSE3U54WeHxeCIGbKU+LuSIiIqJnjD4U2KhRI8hkMshkMnTo0AHlyj1fNCcnB/Hx8ejUqVORFEmUV9WKNs/CvZ5wJZPJULWijRmqIiIiMiFY9ezZEwAQFxeHjh07wt7eXvOYXC6Hl5cXevfuLXmBRPn1a+KBr6P/0vuYEAL9efI6ERGZidHBavbs2QAALy8v9O/fH9bW1kVWFJEh3o52WNDbD1O3XYBMJtMcnhZCYEFvP564TkREZmPyVYFDhw4tijqITNK3iQeaelVCRGwibqY8RdWKNujfxIOhioiIzMrkYGVhYVHgFVnAs/OtiIqDl6MdpnaqY+4yiIiINEwOVj/++KNWsMrKysK5c+ewYcMGzJ07V9LiiIiIiEoTk4NV7knsefXp0wf16tVDREQERo4cKUVdRERERKWOyfNYFaR58+bYv3+/VMPpSElJQUhICJRKJZRKJUJCQpCamlpg/6ysLEydOhX169eHnZ0d3N3dMWTIENy+fVurX9u2bTXTSOTeBgwYUGTrQVRc8n+XYvy9xwZ6ExGRFCQJVk+fPsWyZctQtWpVKYbTa+DAgYiLi0NkZCQiIyMRFxeHkJCQAvs/efIEZ8+excyZM3H27Fn8+OOP+PPPP9GjRw+dvqNHj0ZSUpLm9vXXXxfZehAVh+9iE9Ft6THN/fXHrqPD54fxPWelJyIqUiYfCqxYsaLWOVZCCDx8+BA2NjbYvHmzpMXlunz5MiIjI3HixAk0b94cALBmzRoEBATgypUrqF27ts4ySqUSUVFRWm3Lli1Ds2bNkJCQgGrVqmnabW1t4erqWiS1ExU3fpciEZH5mByslixZonXfwsICTk5OaN68OW7cuCFVXVpiYmKgVCo1oQoAWrRoAaVSiePHj+sNVvqoVCrIZDJUqFBBq33z5s3YtGkTXFxc0LlzZ8yePRvly5cvcJyMjAxkZGRo7qelpZm2QkRFSPNdigXMTB8Rm8irKYmIishLz2OlUqmwefNmfPzxx4iLiyuS6RaSk5Ph7Oys0+7s7Izk5GSjxkhPT8e0adMwcOBAODg4aNoHDRoEb29vuLq64uLFi5g+fTrOnz+vs7crr7CwMF4BSSUWv0uRiMh8Xvgcq4MHD2Lw4MFwc3PDsmXL0LlzZ8TGxpo0xpw5c3ROHM9/yx1T39xZBX0hdH5ZWVkYMGAA1Go1Vq5cqfXY6NGj8cYbb8DX1xcDBgzADz/8gP379+Ps2bMFjjd9+nSoVCrNLTGR561QyaH5LkU9+F2KRERFy6Q9Vjdv3kR4eDjWrVuHx48fo1+/fsjKysK2bdvg4+Nj8pNPnDix0CvwvLy8cOHCBfzzzz86j929excuLi4Gl8/KykK/fv0QHx+PgwcPau2t0qdx48awsrLC1atX0bhxY719FAoFFAqFwXGIzIXfpUhEZD5GB6suXbrg2LFj6NatG5YtW4ZOnTrB0tISq1ateuEnd3R0hKOjY6H9AgICoFKpcOrUKTRr1gwAcPLkSahUKgQGBha4XG6ounr1Kg4dOoTKlSsX+lyXLl1CVlYW3NzcjF8RohKE36VIRGQ+Rgerffv2YdKkSRg3bhxq1qxZlDXpqFu3Ljp16oTRo0drpkIYM2YMunXrpnXiep06dRAWFoZevXohOzsbffr0wdmzZ/Hzzz8jJydHcz5WpUqVIJfL8ddff2Hz5s3o0qULHB0d8fvvv+P9999Ho0aN0LJly2JdRyIp8bsUiYjMw+hgdfToUaxbtw5NmjRBnTp1EBISgv79+xdlbVo2b96MSZMmITg4GADQo0cPLF++XKvPlStXoFKpADw7bLlz504AQMOGDbX6HTp0CG3btoVcLseBAwfw5Zdf4tGjR/Dw8EDXrl0xe/ZsWFpaFv1KERUhfpciEVHxk4mCLh8qwJMnT7B161asW7cOp06dQk5ODhYvXowRI0YYnKKgLEtLS4NSqYRKpSr0HK7S7ElmNnxm/QIA+H1eR9jKTb6olIiIqMQois9vk68KtLW1xYgRI3Ds2DH89ttveP/99/Hpp5/C2dlZ76zmRERERK+Kl/pKm9q1a2PhwoW4efMmtmzZIlVNRERERKWSJN8VaGlpiZ49e2rOaSIiIiJ6FUkSrIiIiIiIwYqIiIhIMgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKzLa9fuPNT8vjvoT8fceG+hNRET06mGwIqN8F5uIbkuPae6vP3YdHT4/jO9jE81YFRERUcnCYEWFir/3GNO2XYA6z9d15wgBtQCmbruA69xzRUREBIDBiozwXWwiZDKZ3sdkMhkiuNeKiIgIAIMVGeFmylMIIfQ+JoTAzZSnxVwRERFRycRgRYWqWtHG4B6rqhVtirkiIiKikonBigrVr4mHwT1W/Zt4FHNFREREJRODFRXK29EOC3r7wUIGWFrItP5d0NsPXo525i6RiIioRChn7gKodOjbxANNvSohIjYRN1OeompFG/Rv4sFQRURElAeDFRnNy9EOUzvVMXcZREREJRYPBRIRERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJJFSE6xSUlIQEhICpVIJpVKJkJAQpKamGlxm2LBhkMlkWrcWLVpo9cnIyMC7774LR0dH2NnZoUePHrh582YRrgkRERGVVaUmWA0cOBBxcXGIjIxEZGQk4uLiEBISUuhynTp1QlJSkua2Z88erccnT56M7du3Y+vWrTh27BgePXqEbt26IScnp6hWhYiIiMqocuYuwBiXL19GZGQkTpw4gebNmwMA1qxZg4CAAFy5cgW1a9cucFmFQgFXV1e9j6lUKqxduxb/93//hzfeeAMAsGnTJnh4eGD//v3o2LGj9CtDREREZVap2GMVExMDpVKpCVUA0KJFCyiVShw/ftzgsocPH4azszNq1aqF0aNH486dO5rHzpw5g6ysLAQHB2va3N3d4evra3DcjIwMpKWlad2IiIiISkWwSk5OhrOzs067s7MzkpOTC1yuc+fO2Lx5Mw4ePIjPP/8cp0+fRvv27ZGRkaEZVy6Xo2LFilrLubi4GBw3LCxMc66XUqmEh4fHC64ZERERlSVmDVZz5szRObk8/y02NhYAIJPJdJYXQuhtz9W/f3907doVvr6+6N69O/bu3Ys///wTu3fvNlhXYeNOnz4dKpVKc0tMTDRyjYmIiKgsM+s5VhMnTsSAAQMM9vHy8sKFCxfwzz//6Dx29+5duLi4GP18bm5u8PT0xNWrVwEArq6uyMzMREpKitZeqzt37iAwMLDAcRQKBRQKhdHPS0RERK8GswYrR0dHODo6FtovICAAKpUKp06dQrNmzQAAJ0+ehEqlMhiA8rt//z4SExPh5uYGAPD394eVlRWioqLQr18/AEBSUhIuXryIhQsXvsAaERER0ausVJxjVbduXXTq1AmjR4/GiRMncOLECYwePRrdunXTuiKwTp062L59OwDg0aNH+OCDDxATE4Pr16/j8OHD6N69OxwdHdGrVy8AgFKpxMiRI/H+++/jwIEDOHfuHAYPHoz69etrrhIkIiIiMlapmG4BADZv3oxJkyZpruDr0aMHli9frtXnypUrUKlUAABLS0v89ttv2LhxI1JTU+Hm5oZ27dohIiIC5cuX1yzzxRdfoFy5cujXrx+ePn2KDh06IDw8HJaWlsW3ckRERFQmyIQQwtxFlHZpaWlQKpVQqVRwcHAwdzlERERkhKL4/C4VhwKJiIiISgMGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJpNQEq5SUFISEhECpVEKpVCIkJASpqakGl5HJZHpvixYt0vRp27atzuMDBgwo4rUhIiKisqicuQsw1sCBA3Hz5k1ERkYCAMaMGYOQkBDs2rWrwGWSkpK07u/duxcjR45E7969tdpHjx6NefPmae7b2NhIWDkRERG9KkpFsLp8+TIiIyNx4sQJNG/eHACwZs0aBAQE4MqVK6hdu7be5VxdXbXu//TTT2jXrh2qV6+u1W5ra6vTl4iIiMhUpeJQYExMDJRKpSZUAUCLFi2gVCpx/Phxo8b4559/sHv3bowcOVLnsc2bN8PR0RH16tXDBx98gIcPH0pWOxEREb06SsUeq+TkZDg7O+u0Ozs7Izk52agxNmzYgPLly+Ott97Sah80aBC8vb3h6uqKixcvYvr06Th//jyioqIKHCsjIwMZGRma+2lpaUauCREREZVlZt1jNWfOnAJPMM+9xcbGAnh2Inp+Qgi97fqsW7cOgwYNgrW1tVb76NGj8cYbb8DX1xcDBgzADz/8gP379+Ps2bMFjhUWFqY5iV6pVMLDw8OEtSYiIqKyyqx7rCZOnFjoFXheXl64cOEC/vnnH53H7t69CxcXl0Kf5+jRo7hy5QoiIiIK7du4cWNYWVnh6tWraNy4sd4+06dPR2hoqOZ+WloawxURERGZN1g5OjrC0dGx0H4BAQFQqVQ4deoUmjVrBgA4efIkVCoVAgMDC11+7dq18Pf3R4MGDQrte+nSJWRlZcHNza3APgqFAgqFotCxiIiI6NVSKk5er1u3Ljp16oTRo0fjxIkTOHHiBEaPHo1u3bppXRFYp04dbN++XWvZtLQ0fP/99xg1apTOuH/99RfmzZuH2NhYXL9+HXv27EHfvn3RqFEjtGzZssjXi4iIiMqWUhGsgGdX7tWvXx/BwcEIDg6Gn58f/u///k+rz5UrV6BSqbTatm7dCiEE3n77bZ0x5XI5Dhw4gI4dO6J27dqYNGkSgoODsX//flhaWhbp+hAREVHZIxNCCHMXUdqlpaVBqVRCpVLBwcHB3OUQERGREYri87vU7LEiIiIiKukYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkEQYrIiIiIokwWBERERFJhMGKiIiISCIMVkREREQSYbAiIiIikgiDFREREZFEGKyIiIiIJMJgRURERCQRBisiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEmGwIiIiIpIIgxURERGRRBisiIiIiCTCYEVEREQkkVITrP73v/8hMDAQtra2qFChglHLCCEwZ84cuLu7w8bGBm3btsWlS5e0+mRkZODdd9+Fo6Mj7Ozs0KNHD9y8ebMI1oCIiIjKulITrDIzM9G3b1+MGzfO6GUWLlyIxYsXY/ny5Th9+jRcXV0RFBSEhw8favpMnjwZ27dvx9atW3Hs2DE8evQI3bp1Q05OTlGsBhEREZVhMiGEMHcRpggPD8fkyZORmppqsJ8QAu7u7pg8eTKmTp0K4NneKRcXFyxYsADvvPMOVCoVnJyc8H//93/o378/AOD27dvw8PDAnj170LFjR6NqSktLg1KphEqlgoODw0utHxERERWPovj8LjV7rEwVHx+P5ORkBAcHa9oUCgXatGmD48ePAwDOnDmDrKwsrT7u7u7w9fXV9CEiIiIyVjlzF1BUkpOTAQAuLi5a7S4uLrhx44amj1wuR8WKFXX65C6vT0ZGBjIyMjT3VSoVgGfJl4iIiEqH3M9tKQ/emTVYzZkzB3PnzjXY5/Tp02jSpMkLP4dMJtO6L4TQacuvsD5hYWF66/bw8HixIomIiMhsHj58CKVSKclYZg1WEydOxIABAwz28fLyeqGxXV1dATzbK+Xm5qZpv3PnjmYvlqurKzIzM5GSkqK11+rOnTsIDAwscOzp06cjNDRUc1+tVuPBgweoXLlyoaHNFGlpafDw8EBiYiLP3SoAt5Fh3D6GcfsYxu1jGLePYaVh+wgh8PDhQ7i7u0s2plmDlaOjIxwdHYtkbG9vb7i6uiIqKgqNGjUC8OzKwujoaCxYsAAA4O/vDysrK0RFRaFfv34AgKSkJFy8eBELFy4scGyFQgGFQqHVZuwUEC/CwcGhxP5RlhTcRoZx+xjG7WMYt49h3D6GlfTtI9Weqlyl5hyrhIQEPHjwAAkJCcjJyUFcXBwA4LXXXoO9vT0AoE6dOggLC0OvXr0gk8kwefJkzJ8/HzVr1kTNmjUxf/582NraYuDAgQCebcyRI0fi/fffR+XKlVGpUiV88MEHqF+/Pt544w1zrSoRERGVUqUmWM2aNQsbNmzQ3M/dC3Xo0CG0bdsWAHDlyhXNieQA8NFHH+Hp06cYP348UlJS0Lx5c+zbtw/ly5fX9Pniiy9Qrlw59OvXD0+fPkWHDh0QHh4OS0vL4lkxIiIiKjNKTbAKDw9HeHi4wT75z+qXyWSYM2cO5syZU+Ay1tbWWLZsGZYtWyZBldJSKBSYPXu2zmFHeo7byDBuH8O4fQzj9jGM28ewV3X7lLoJQomIiIhKqjI7QSgRERFRcWOwIiIiIpIIgxURERGRRBisiIiIiCTCYFWCrVy5Et7e3rC2toa/vz+OHj1q7pJKhLCwMDRt2hTly5eHs7MzevbsiStXrpi7rBIrLCxMM68bPXPr1i0MHjwYlStXhq2tLRo2bIgzZ86Yu6wSIzs7G//5z3/g7e0NGxsbVK9eHfPmzYNarTZ3aWZx5MgRdO/eHe7u7pDJZNixY4fW40IIzJkzB+7u7rCxsUHbtm1x6dIl8xRrBoa2T1ZWFqZOnYr69evDzs4O7u7uGDJkCG7fvm2+gosYg1UJFRERgcmTJ+Pjjz/GuXPn0KpVK3Tu3BkJCQnmLs3soqOjMWHCBJw4cQJRUVHIzs5GcHAwHj9+bO7SSpzTp09j9erV8PPzM3cpJUZKSgpatmwJKysr7N27F7///js+//zzIv32hNJmwYIFWLVqFZYvX47Lly9j4cKFWLRoUYmclqY4PH78GA0aNMDy5cv1Pr5w4UIsXrwYy5cvx+nTp+Hq6oqgoCA8fPiwmCs1D0Pb58mTJzh79ixmzpyJs2fP4scff8Sff/6JHj16mKHSYiKoRGrWrJkYO3asVludOnXEtGnTzFRRyXXnzh0BQERHR5u7lBLl4cOHombNmiIqKkq0adNGvPfee+YuqUSYOnWqeP31181dRonWtWtXMWLECK22t956SwwePNhMFZUcAMT27ds199VqtXB1dRWffvqppi09PV0olUqxatUqM1RoXvm3jz6nTp0SAMSNGzeKp6hixj1WJVBmZibOnDmD4OBgrfbg4GAcP37cTFWVXLmz7VeqVMnMlZQsEyZMQNeuXfn1TPns3LkTTZo0Qd++feHs7IxGjRphzZo15i6rRHn99ddx4MAB/PnnnwCA8+fP49ixY+jSpYuZKyt54uPjkZycrPV+rVAo0KZNG75fF0ClUkEmk5XZvcSlZub1V8m9e/eQk5MDFxcXrXYXFxckJyebqaqSSQiB0NBQvP766/D19TV3OSXG1q1bcfbsWZw+fdrcpZQ4f//9N7766iuEhoZixowZOHXqFCZNmgSFQoEhQ4aYu7wSYerUqVCpVKhTpw4sLS2Rk5OD//3vf3j77bfNXVqJk/uerO/9+saNG+YoqURLT0/HtGnTMHDgwBL9xcwvg8GqBJPJZFr3hRA6ba+6iRMn4sKFCzh27Ji5SykxEhMT8d5772Hfvn2wtrY2dzkljlqtRpMmTTB//nwAz7539NKlS/jqq68YrP4VERGBTZs24dtvv0W9evUQFxeHyZMnw93dHUOHDjV3eSUS368Ll5WVhQEDBkCtVmPlypXmLqfIMFiVQI6OjrC0tNTZO3Xnzh2d/xW9yt59913s3LkTR44cQdWqVc1dTolx5swZ3LlzB/7+/pq2nJwcHDlyBMuXL0dGRsYr/SXjbm5u8PHx0WqrW7cutm3bZqaKSp4PP/wQ06ZNw4ABAwAA9evXx40bNxAWFsZglY+rqyuAZ3uu3NzcNO18v9aWlZWFfv36IT4+HgcPHiyze6sAXhVYIsnlcvj7+yMqKkqrPSoqCoGBgWaqquQQQmDixIn48ccfcfDgQXh7e5u7pBKlQ4cO+O233xAXF6e5NWnSBIMGDUJcXNwrHaoAoGXLljrTc/z555/w9PQ0U0Ulz5MnT2Bhof3xYGlp+cpOt2CIt7c3XF1dtd6vMzMzER0dzffrf+WGqqtXr2L//v2oXLmyuUsqUtxjVUKFhoYiJCQETZo0QUBAAFavXo2EhASMHTvW3KWZ3YQJE/Dtt9/ip59+Qvny5TV79pRKJWxsbMxcnfmVL19e53wzOzs7VK5cmeehAZgyZQoCAwMxf/589OvXD6dOncLq1auxevVqc5dWYnTv3h3/+9//UK1aNdSrVw/nzp3D4sWLMWLECHOXZhaPHj3CtWvXNPfj4+MRFxeHSpUqoVq1apg8eTLmz5+PmjVrombNmpg/fz5sbW0xcOBAM1ZdfAxtH3d3d/Tp0wdnz57Fzz//jJycHM17dqVKlSCXy81VdtEx70WJZMiKFSuEp6enkMvlonHjxpxO4F8A9N7Wr19v7tJKLE63oG3Xrl3C19dXKBQKUadOHbF69Wpzl1SipKWliffee09Uq1ZNWFtbi+rVq4uPP/5YZGRkmLs0szh06JDe95yhQ4cKIZ5NuTB79mzh6uoqFAqFaN26tfjtt9/MW3QxMrR94uPjC3zPPnTokLlLLxIyIYQoziBHREREVFbxHCsiIiIiiTBYEREREUmEwYqIiIhIIgxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyJ6JQ0bNgw9e/Y0dxlEVMYwWBERERFJhMGKiCifxYsXo379+rCzs4OHhwfGjx+PR48eafVZs2YNPDw8YGtri169emHx4sWoUKGCeQomohKDwYqIKB8LCwssXboUFy9exIYNG3Dw4EF89NFHmsd//fVXjB07Fu+99x7i4uIQFBSE//3vf2asmIhKCn4JMxG9koYNG4bU1FTs2LGj0L7ff/89xo0bh3v37gEABgwYgEePHuHnn3/W9Bk8eDB+/vlnpKamFlHFRFQacI8VEVE+hw4dQlBQEKpUqYLy5ctjyJAhuH//Ph4/fgwAuHLlCpo1a6a1TP77RPRqYrAiIsrjxo0b6NKlC3x9fbFt2zacOXMGK1asAABkZWUBAIQQkMlkWstx5z8RAUA5cxdARFSSxMbGIjs7G59//jksLJ793/O7777T6lOnTh2cOnVKZzkiIgYrInplqVQqxMXFabU5OTkhOzsby5YtQ/fu3fHrr79i1apVWn3effddtG7dGosXL0b37t1x8OBB7N27V2cvFhG9enjyOhG9koYNG4YNGzbotA8dOhQNGjTAokWLkJqaitatW2PQoEEYMmQIUlJSNFMqrFmzBnPnzsWDBw/QsWNHNGnSBMuXL0dSUlIxrwkRlSQMVkREEhg9ejT++OMPHD161NylEJEZ8VAgEdEL+OyzzxAUFAQ7Ozvs3bsXGzZswMqVK81dFhGZGfdYERG9gH79+uHw4cN4+PAhqlevjnfffRdjx441d1lEZGYMVkREREQS4TxWRERERBJhsCIiIiKSCIMVERERkUQYrIiIiIgkwmBFREREJBEGKyIiIiKJMFgRERERSYTBioiIiEgiDFZEREREEvl/LxZSgN8FhpYAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.graphics.tsaplots import plot_acf\n",
    "\n",
    "for column in data_diff.columns:\n",
    "    if column != 'Date':  \n",
    "        plot_acf(data_diff[column], lags=12)\n",
    "        plt.title(f'Autocorrelation Function (ACF) - {column}')\n",
    "        plt.xlabel('Lag')\n",
    "        plt.ylabel('Autocorrelation')\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "372f0799",
   "metadata": {},
   "source": [
    "From the ADF test along with the plot we can determine that our data is now centered around the mean. Our next step is to perform a granger causality test which indicates to us if a lagged verison of a specific time series can help us predict out target time series, however not necessairly that one time series causes the other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "14b3a70c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For: PCE : Billions of dollars\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 1\n",
      "ssr based F test:         F=0.8821  , p=0.3485  , df_denom=252, df_num=1\n",
      "ssr based chi2 test:   chi2=0.8926  , p=0.3448  , df=1\n",
      "likelihood ratio test: chi2=0.8910  , p=0.3452  , df=1\n",
      "parameter F test:         F=0.8821  , p=0.3485  , df_denom=252, df_num=1\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 2\n",
      "ssr based F test:         F=0.7486  , p=0.4741  , df_denom=249, df_num=2\n",
      "ssr based chi2 test:   chi2=1.5273  , p=0.4660  , df=2\n",
      "likelihood ratio test: chi2=1.5228  , p=0.4670  , df=2\n",
      "parameter F test:         F=0.7486  , p=0.4741  , df_denom=249, df_num=2\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 3\n",
      "ssr based F test:         F=0.9103  , p=0.4366  , df_denom=246, df_num=3\n",
      "ssr based chi2 test:   chi2=2.8087  , p=0.4221  , df=3\n",
      "likelihood ratio test: chi2=2.7933  , p=0.4246  , df=3\n",
      "parameter F test:         F=0.9103  , p=0.4366  , df_denom=246, df_num=3\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 4\n",
      "ssr based F test:         F=0.8554  , p=0.4914  , df_denom=243, df_num=4\n",
      "ssr based chi2 test:   chi2=3.5483  , p=0.4706  , df=4\n",
      "likelihood ratio test: chi2=3.5235  , p=0.4743  , df=4\n",
      "parameter F test:         F=0.8554  , p=0.4914  , df_denom=243, df_num=4\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 5\n",
      "ssr based F test:         F=1.8087  , p=0.1118  , df_denom=240, df_num=5\n",
      "ssr based chi2 test:   chi2=9.4578  , p=0.0921  , df=5\n",
      "likelihood ratio test: chi2=9.2840  , p=0.0983  , df=5\n",
      "parameter F test:         F=1.8087  , p=0.1118  , df_denom=240, df_num=5\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 6\n",
      "ssr based F test:         F=2.0385  , p=0.0614  , df_denom=237, df_num=6\n",
      "ssr based chi2 test:   chi2=12.9021 , p=0.0446  , df=6\n",
      "likelihood ratio test: chi2=12.5802 , p=0.0502  , df=6\n",
      "parameter F test:         F=2.0385  , p=0.0614  , df_denom=237, df_num=6\n",
      "\n",
      "========================================\n",
      "\n",
      "For: GPDI : Billions of dollars\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 1\n",
      "ssr based F test:         F=0.3612  , p=0.5484  , df_denom=252, df_num=1\n",
      "ssr based chi2 test:   chi2=0.3655  , p=0.5454  , df=1\n",
      "likelihood ratio test: chi2=0.3653  , p=0.5456  , df=1\n",
      "parameter F test:         F=0.3612  , p=0.5484  , df_denom=252, df_num=1\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 2\n",
      "ssr based F test:         F=0.0208  , p=0.9794  , df_denom=249, df_num=2\n",
      "ssr based chi2 test:   chi2=0.0425  , p=0.9790  , df=2\n",
      "likelihood ratio test: chi2=0.0425  , p=0.9790  , df=2\n",
      "parameter F test:         F=0.0208  , p=0.9794  , df_denom=249, df_num=2\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 3\n",
      "ssr based F test:         F=1.3069  , p=0.2727  , df_denom=246, df_num=3\n",
      "ssr based chi2 test:   chi2=4.0323  , p=0.2580  , df=3\n",
      "likelihood ratio test: chi2=4.0005  , p=0.2614  , df=3\n",
      "parameter F test:         F=1.3069  , p=0.2727  , df_denom=246, df_num=3\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 4\n",
      "ssr based F test:         F=1.0861  , p=0.3640  , df_denom=243, df_num=4\n",
      "ssr based chi2 test:   chi2=4.5051  , p=0.3419  , df=4\n",
      "likelihood ratio test: chi2=4.4653  , p=0.3467  , df=4\n",
      "parameter F test:         F=1.0861  , p=0.3640  , df_denom=243, df_num=4\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 5\n",
      "ssr based F test:         F=1.0364  , p=0.3968  , df_denom=240, df_num=5\n",
      "ssr based chi2 test:   chi2=5.4197  , p=0.3668  , df=5\n",
      "likelihood ratio test: chi2=5.3620  , p=0.3733  , df=5\n",
      "parameter F test:         F=1.0364  , p=0.3968  , df_denom=240, df_num=5\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 6\n",
      "ssr based F test:         F=1.0198  , p=0.4130  , df_denom=237, df_num=6\n",
      "ssr based chi2 test:   chi2=6.4546  , p=0.3742  , df=6\n",
      "likelihood ratio test: chi2=6.3727  , p=0.3828  , df=6\n",
      "parameter F test:         F=1.0198  , p=0.4130  , df_denom=237, df_num=6\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 7\n",
      "ssr based F test:         F=1.6969  , p=0.1105  , df_denom=234, df_num=7\n",
      "ssr based chi2 test:   chi2=12.6395 , p=0.0814  , df=7\n",
      "likelihood ratio test: chi2=12.3291 , p=0.0902  , df=7\n",
      "parameter F test:         F=1.6969  , p=0.1105  , df_denom=234, df_num=7\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 8\n",
      "ssr based F test:         F=1.8874  , p=0.0628  , df_denom=231, df_num=8\n",
      "ssr based chi2 test:   chi2=16.2107 , p=0.0395  , df=8\n",
      "likelihood ratio test: chi2=15.7029 , p=0.0468  , df=8\n",
      "parameter F test:         F=1.8874  , p=0.0628  , df_denom=231, df_num=8\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 9\n",
      "ssr based F test:         F=2.3202  , p=0.0162  , df_denom=228, df_num=9\n",
      "ssr based chi2 test:   chi2=22.6221 , p=0.0071  , df=9\n",
      "likelihood ratio test: chi2=21.6454 , p=0.0101  , df=9\n",
      "parameter F test:         F=2.3202  , p=0.0162  , df_denom=228, df_num=9\n",
      "\n",
      "========================================\n",
      "\n",
      "For: NETEXP : Billions of dollars\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 1\n",
      "ssr based F test:         F=9.1682  , p=0.0027  , df_denom=252, df_num=1\n",
      "ssr based chi2 test:   chi2=9.2773  , p=0.0023  , df=1\n",
      "likelihood ratio test: chi2=9.1126  , p=0.0025  , df=1\n",
      "parameter F test:         F=9.1682  , p=0.0027  , df_denom=252, df_num=1\n",
      "\n",
      "========================================\n",
      "\n",
      "For: GovTotExp : Billions of dollars\n",
      "\n",
      "Granger Causality\n",
      "number of lags (no zero) 1\n",
      "ssr based F test:         F=57.2092 , p=0.0000  , df_denom=252, df_num=1\n",
      "ssr based chi2 test:   chi2=57.8903 , p=0.0000  , df=1\n",
      "likelihood ratio test: chi2=52.1702 , p=0.0000  , df=1\n",
      "parameter F test:         F=57.2092 , p=0.0000  , df_denom=252, df_num=1\n",
      "\n",
      "========================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.stattools import grangercausalitytests\n",
    "columns = ['PCE : Billions of dollars', 'GPDI : Billions of dollars', 'NETEXP : Billions of dollars', 'GovTotExp : Billions of dollars']\n",
    "lags = [6, 9, 1, 1] #determined from individually testing each combination\n",
    "\n",
    "for column, lag in zip(columns, lags):\n",
    "    df_new = data_diff[['GDP : Billions of dollars', column]]\n",
    "    print(f'For: {column}')\n",
    "    gc_res = grangercausalitytests(df_new, lag)\n",
    "    print(\"\\n\" + \"=\" * 40 + \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ab86794",
   "metadata": {},
   "source": [
    "here we are just looking for a single lag for each feature which has statiscally significant p-values. Personal consumption Expenditures arguably did not make this cut off, however the sixth lag is so close that I decided to keep it in. Our next step is to create our VAR model now that we have decided that all of our features are significant. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4dfc732e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dronm\\anaconda3\\Lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:473: ValueWarning: An unsupported index was provided and will be ignored when e.g. forecasting.\n",
      "  self._init_dates(dates, freq)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 328.39\n",
      "MAPE: 57.72%\n",
      "GDP Actual vs Forecast:\n",
      "          Date  Actual GDP  Forecasted GDP\n",
      "231 2017-10-01     344.493       84.479946\n",
      "232 2018-01-01     291.465      179.477634\n",
      "233 2018-04-01     252.359      155.624087\n",
      "234 2018-07-01     217.818      105.220413\n",
      "235 2018-10-01     119.137      153.221441\n",
      "236 2019-01-01     186.266      240.780124\n",
      "237 2019-04-01     280.642      216.362075\n",
      "238 2019-07-01     309.507      151.012279\n",
      "239 2019-10-01     208.108      286.572411\n",
      "240 2020-01-01    -195.877      232.309027\n",
      "241 2020-04-01   -1793.370      226.008422\n",
      "242 2020-07-01    1734.497      242.669525\n",
      "243 2020-10-01     376.862      255.241138\n",
      "244 2021-01-01     575.683      203.352525\n",
      "245 2021-04-01     692.177      247.383534\n",
      "246 2021-07-01     536.611      211.806723\n",
      "247 2021-10-01     825.630      188.329785\n",
      "248 2022-01-01     374.513      193.401142\n",
      "249 2022-04-01     515.157      220.097723\n",
      "250 2022-07-01     450.366      193.285245\n",
      "251 2022-10-01     413.766      200.739952\n",
      "252 2023-01-01     405.196      220.162682\n",
      "253 2023-04-01     249.411      174.751380\n",
      "254 2023-07-01     547.116      229.388535\n",
      "255 2023-10-01     346.870      241.182963\n",
      "256 2024-01-01     298.930      201.618804\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from statsmodels.tsa.api import VAR\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "columns = ['GDP : Billions of dollars', 'PCE : Billions of dollars', 'GPDI : Billions of dollars', 'NETEXP : Billions of dollars', 'GovTotExp : Billions of dollars']\n",
    "data_diff = data_diff[columns]\n",
    "\n",
    "split_index = int(len(data_diff) * 0.90)\n",
    "train_data = data_diff.iloc[:split_index]\n",
    "test_data = data_diff.iloc[split_index:]\n",
    "\n",
    "model = VAR(train_data)\n",
    "results = model.fit(maxlags=14)\n",
    "\n",
    "forecast_steps = len(test_data)\n",
    "forecast = results.forecast(train_data.values[-results.k_ar:], steps=forecast_steps)\n",
    "\n",
    "\n",
    "forecast_df = pd.DataFrame(forecast, index=test_data.index, columns=columns)\n",
    "\n",
    "\n",
    "gdp_forecast = forecast_df['GDP : Billions of dollars']\n",
    "gdp_actual = test_data['GDP : Billions of dollars']\n",
    "\n",
    "\n",
    "dates = data_diff.index[split_index:]\n",
    "\n",
    "\n",
    "comparison_df = pd.DataFrame({'Date': Date_col, 'Actual GDP': gdp_actual.values, 'Forecasted GDP': gdp_forecast.values})\n",
    "comparison_df.dropna(inplace=True)\n",
    "\n",
    "\n",
    "mae = mean_absolute_error(comparison_df['Actual GDP'], comparison_df['Forecasted GDP'])\n",
    "print(f\"MAE: {mae:.2f}\")\n",
    "\n",
    "def mean_absolute_percentage_error(y_true, y_pred):\n",
    "    return np.mean(np.abs((y_true - y_pred) / y_true)) * 100\n",
    "\n",
    "mape = mean_absolute_percentage_error(comparison_df['Actual GDP'], comparison_df['Forecasted GDP'])\n",
    "print(f\"MAPE: {mape:.2f}%\")\n",
    "\n",
    "\n",
    "print(\"GDP Actual vs Forecast:\")\n",
    "print(comparison_df)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(comparison_df['Date'], comparison_df['Actual GDP'], label='Actual GDP', color='blue')\n",
    "plt.plot(comparison_df['Date'], comparison_df['Forecasted GDP'], label='Forecasted GDP', color='red', linestyle='--')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('GDP : Billions of dollars')\n",
    "plt.title('Actual vs Forecasted GDP using VAR')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3cd654f",
   "metadata": {},
   "source": [
    "Looking this forecast, we can clealy see that despite missing the mark quite heavily on both evaluation metrics used (MAE and MAPE), our model visually was not too innaccurate barring the outliers caused by the pandemic. We managed to stay on the testing line for the most part from 2018-2019 and from 2022-2024, however the global events following obviously threw in some unpredictability which affected the model's ability to precisely judge the trends."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "083a9b5d",
   "metadata": {},
   "source": [
    "# VECM forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f309bcd",
   "metadata": {},
   "source": [
    "VECM (Vector Error Correction Model) is similar to, albeit a few key differences. Unlike VAR, VECM does not rely on stationarity so differencing and normalizing the time series will not be necessary. Below is a Johansen cointegration test which conpares test values to critical values in order to determine the number of relevant cointegration relationships (variables which share a long term equilibrium relationship)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cf953fd1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Johansen cointegration test using trace test statistic with 5% significance level\n",
      "=====================================\n",
      "r_0 r_1 test statistic critical value\n",
      "-------------------------------------\n",
      "  0   5          243.6          69.82\n",
      "  1   5          94.27          47.85\n",
      "  2   5          47.34          29.80\n",
      "  3   5          15.06          15.49\n",
      "-------------------------------------\n"
     ]
    }
   ],
   "source": [
    "from statsmodels.tsa.vector_ar.vecm import VECM, select_order, select_coint_rank\n",
    "columns = ['GDP : Billions of dollars', 'PCE : Billions of dollars', 'GPDI : Billions of dollars', 'NETEXP : Billions of dollars', 'GovTotExp : Billions of dollars']\n",
    "data = data[columns]\n",
    "rank_test = select_coint_rank(data, det_order=0, k_ar_diff=1)\n",
    "print(rank_test.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5ef0180a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAE: 1482.53\n",
      "GDP Actual vs Forecast:\n",
      "          Date  Actual GDP  Forecasted GDP\n",
      "231 2017-10-01   20037.088    19753.822655\n",
      "232 2018-01-01   20328.553    19886.303817\n",
      "233 2018-04-01   20580.912    20019.396912\n",
      "234 2018-07-01   20798.730    20091.444369\n",
      "235 2018-10-01   20917.867    20201.747583\n",
      "236 2019-01-01   21104.133    20397.007183\n",
      "237 2019-04-01   21384.775    20590.328595\n",
      "238 2019-07-01   21694.282    20715.361432\n",
      "239 2019-10-01   21902.390    20933.376095\n",
      "240 2020-01-01   21706.513    21102.670722\n",
      "241 2020-04-01   19913.143    21333.003367\n",
      "242 2020-07-01   21647.640    21572.994781\n",
      "243 2020-10-01   22024.502    21812.328621\n",
      "244 2021-01-01   22600.185    22030.977990\n",
      "245 2021-04-01   23292.362    22299.984264\n",
      "246 2021-07-01   23828.973    22534.530745\n",
      "247 2021-10-01   24654.603    22750.677701\n",
      "248 2022-01-01   25029.116    22985.403756\n",
      "249 2022-04-01   25544.273    23271.176604\n",
      "250 2022-07-01   25994.639    23483.148023\n",
      "251 2022-10-01   26408.405    23719.922245\n",
      "252 2023-01-01   26813.601    23977.040794\n",
      "253 2023-04-01   27063.012    24160.506343\n",
      "254 2023-07-01   27610.128    24361.691614\n",
      "255 2023-10-01   27956.998    24615.083068\n",
      "256 2024-01-01   28255.928    24786.868614\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "columns = ['GDP : Billions of dollars', 'PCE : Billions of dollars', 'GPDI : Billions of dollars', 'NETEXP : Billions of dollars', 'GovTotExp : Billions of dollars']\n",
    "data = data[columns]\n",
    "split_index1 = int(len(data) * 0.90)\n",
    "train_data1 = data.iloc[:split_index1]\n",
    "test_data1 = data.iloc[split_index1:]\n",
    "rank_test = select_coint_rank(data, det_order=0, k_ar_diff=1)\n",
    "lag_order = select_order(data, maxlags=15, deterministic=\"ci\")\n",
    "\n",
    "model = VECM(train_data1, k_ar_diff=lag_order.aic, coint_rank=rank_test.rank, deterministic='ci')\n",
    "results = model.fit()\n",
    "\n",
    "forecast_steps = len(test_data1)\n",
    "forecast = results.predict(steps=forecast_steps)\n",
    "\n",
    "forecast_df = pd.DataFrame(forecast, index=test_data1.index, columns=columns)\n",
    "\n",
    "gdp_forecast = forecast_df['GDP : Billions of dollars']\n",
    "gdp_actual = test_data1['GDP : Billions of dollars']\n",
    "\n",
    "dates = dates[:len(gdp_actual)]\n",
    "\n",
    "comparison_df = pd.DataFrame({'Date': Date_col, 'Actual GDP': gdp_actual.values, 'Forecasted GDP': gdp_forecast.values})\n",
    "comparison_df.dropna(inplace=True)\n",
    "\n",
    "mae = mean_absolute_error(comparison_df['Actual GDP'], comparison_df['Forecasted GDP'])\n",
    "print(f\"MAE: {mae:.2f}\")\n",
    "\n",
    "print(\"GDP Actual vs Forecast:\")\n",
    "print(comparison_df)\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(comparison_df['Date'], comparison_df['Actual GDP'], label='Actual GDP', color='blue')\n",
    "plt.plot(comparison_df['Date'], comparison_df['Forecasted GDP'], label='Forecasted GDP', color='red', linestyle='--')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('GDP : Billions of dollars')\n",
    "plt.title('Actual vs Forecasted GDP using VECM')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e9ee0b",
   "metadata": {},
   "source": [
    "Though it is hard to compare to our VAR model to this one given that we are now using the unstationary data, we can still deduce both by the error metric and the visualization that this model was not able to accurately capture the trends in this forecast. With this, it is fair to say that we can rule out traditional statistical methods for approaching this problem."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ebc69b4",
   "metadata": {},
   "source": [
    "# Machine Learning forecasting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "feab38cf",
   "metadata": {},
   "source": [
    "When deciding a machine learning approach to model this problem, I wanted to keep in mind the amount of data that I am working with. Prior to creating lagged columns, out dataset has a total of 1275 observations across all time series. This means that using more complex approaches, such as LSTMs or gradient boosting, are perhaps unnecessary as we can use more simple model to recieve the same amount of accuracy and far more interpretability.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c63ce6f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "def printevals(y_test,y_pred):\n",
    "    mape = mean_absolute_percentage_error(y_test, y_pred)\n",
    "    print(f\"MAPE: {mape:.2f}%\")\n",
    "    mae = mean_absolute_error(y_test, y_pred)\n",
    "    print(f\"MAE: {mae:.2f}\")\n",
    "def plotresults(title):\n",
    "    \n",
    "    comparison_df = pd.DataFrame({'Date': Date_col, 'Actual GDP': y_test.values, 'Forecasted GDP': y_pred})\n",
    "    comparison_df.dropna(inplace=True)\n",
    "\n",
    "    print(\"GDP Actual vs Forecast:\")\n",
    "    print(comparison_df)\n",
    "    \n",
    "    plt.figure(figsize=(12, 6))\n",
    "    plt.plot(comparison_df['Date'], comparison_df['Actual GDP'], label='Actual GDP', color='blue')\n",
    "    plt.plot(comparison_df['Date'], comparison_df['Forecasted GDP'], label='Forecasted GDP', color='red', linestyle='--')\n",
    "    plt.xlabel('Date')\n",
    "    plt.ylabel('GDP : Billions of dollars')\n",
    "    plt.title(title)\n",
    "    plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "953a2eda",
   "metadata": {},
   "source": [
    "# Train-Test Split "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca6095d0",
   "metadata": {},
   "source": [
    "Train-test splits for time series problems differ slightly from splits in traditional regression or classification tasks. Here it is imparative that we do not shuffle around our data, since that would mean we are training our model on data from the future which in turn will cause data leakages. Also notice that we are training over a very large portion (90%) of the data. This is because we are not actually concerned with forecasting over a large time frame. Realistically even forecasting over several years is not probable for this task. (Note we also used the train test split in our VAR and VECM models, it just felt more appropriate to talk about in the Machine Learning section)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a1218061",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "split_index = int(len(data_diff) * 0.90)\n",
    "\n",
    "train_data = data_diff.iloc[:split_index]\n",
    "test_data = data_diff.iloc[split_index:]\n",
    "\n",
    "X_train = train_data.drop('GDP : Billions of dollars', axis=1)\n",
    "y_train = train_data['GDP : Billions of dollars']\n",
    "X_test = test_data.drop('GDP : Billions of dollars', axis=1)\n",
    "y_test = test_data['GDP : Billions of dollars']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f82690c",
   "metadata": {},
   "source": [
    "# Random Forests"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7dbc2a0",
   "metadata": {},
   "source": [
    "Remembering our VIF test from earlier, we know our features are highly multicolinear. This partially plays into the decision of choosing random forests as our model. decision trees make binary choices between features, meaning that theoretically our features being highly correlated should not be detrimental to our model. In addition to this, random forests is generally a very strong model being robust to overfitting from the schocastic nature of how the trees are computed and generally being very simple to implement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "46035dba",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAPE: 44.31%\n",
      "MAE: 287.97\n",
      "GDP Actual vs Forecast:\n",
      "          Date  Actual GDP  Forecasted GDP\n",
      "231 2017-10-01     344.493       222.66964\n",
      "232 2018-01-01     291.465       232.99618\n",
      "233 2018-04-01     252.359       192.05078\n",
      "234 2018-07-01     217.818       220.23716\n",
      "235 2018-10-01     119.137       118.40956\n",
      "236 2019-01-01     186.266       115.82722\n",
      "237 2019-04-01     280.642       198.88359\n",
      "238 2019-07-01     309.507       228.12818\n",
      "239 2019-10-01     208.108       156.30033\n",
      "240 2020-01-01    -195.877       -78.69897\n",
      "241 2020-04-01   -1793.370      -161.98572\n",
      "242 2020-07-01    1734.497       233.81564\n",
      "243 2020-10-01     376.862       233.81564\n",
      "244 2021-01-01     575.683       151.72623\n",
      "245 2021-04-01     692.177       129.98664\n",
      "246 2021-07-01     536.611       233.97176\n",
      "247 2021-10-01     825.630       235.97884\n",
      "248 2022-01-01     374.513       233.81564\n",
      "249 2022-04-01     515.157       163.32067\n",
      "250 2022-07-01     450.366       167.84568\n",
      "251 2022-10-01     413.766       275.92276\n",
      "252 2023-01-01     405.196       157.41253\n",
      "253 2023-04-01     249.411       240.37866\n",
      "254 2023-07-01     547.116       296.78346\n",
      "255 2023-10-01     346.870       198.98305\n",
      "256 2024-01-01     298.930       179.61721\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "rf_model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = rf_model.predict(X_test)\n",
    "\n",
    "printevals(y_test,y_pred)\n",
    "plotresults('Actual vs Forecasted GDP using Random Forest')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e2f0594",
   "metadata": {},
   "source": [
    "We can see that Random Forests was able to produce our best forecast yet, attaining better error metrics than our attepts at VAR and VECM. Perhaps most impressively, visually we can see that our model was almost perfectly encaptualiting the data from 2017-2019, just prior to encountering the outliers. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e543f71a",
   "metadata": {},
   "source": [
    "# KNN"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42e1e2bd",
   "metadata": {},
   "source": [
    "KNN (K-Nearest-Neighbors) was one final apporach I wanted to attempt. Given that our data is fairly low dimensional (5 features), with over 1000 observations, we have a ratio which should allow this algorithm to perform very well. Notice below we test out various values of our hyperparamter k, with k=2 seemingly being the best one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5f9f8b14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for k = 1 \n",
      "MAPE: 48.93%\n",
      "MAE: 302.74\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 2 \n",
      "MAPE: 47.72%\n",
      "MAE: 303.45\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 3 \n",
      "MAPE: 48.31%\n",
      "MAE: 306.37\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 4 \n",
      "MAPE: 48.41%\n",
      "MAE: 306.15\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 5 \n",
      "MAPE: 49.35%\n",
      "MAE: 310.94\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 6 \n",
      "MAPE: 50.54%\n",
      "MAE: 315.49\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 7 \n",
      "MAPE: 50.36%\n",
      "MAE: 315.71\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 8 \n",
      "MAPE: 50.62%\n",
      "MAE: 317.13\n",
      "\n",
      "========================================\n",
      "\n",
      "for k = 9 \n",
      "MAPE: 50.04%\n",
      "MAE: 315.95\n",
      "\n",
      "========================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "for i in range (1,10):\n",
    "    knn_model = KNeighborsRegressor(n_neighbors=i)\n",
    "    knn_model.fit(X_train, y_train)\n",
    "\n",
    "    y_pred = knn_model.predict(X_test)\n",
    "\n",
    "    print(f'for k = {i} ')\n",
    "    printevals(y_test,y_pred)\n",
    "    print(\"\\n\" + \"=\" * 40 + \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "470bb6db",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MAPE: 47.72%\n",
      "MAE: 303.45\n",
      "GDP Actual vs Forecast:\n",
      "          Date  Actual GDP  Forecasted GDP\n",
      "231 2017-10-01     344.493        237.9050\n",
      "232 2018-01-01     291.465        252.8530\n",
      "233 2018-04-01     252.359        217.4445\n",
      "234 2018-07-01     217.818        206.1615\n",
      "235 2018-10-01     119.137        115.1375\n",
      "236 2019-01-01     186.266        110.2265\n",
      "237 2019-04-01     280.642        203.0175\n",
      "238 2019-07-01     309.507        264.4540\n",
      "239 2019-10-01     208.108        156.4880\n",
      "240 2020-01-01    -195.877          1.0515\n",
      "241 2020-04-01   -1793.370        -65.8135\n",
      "242 2020-07-01    1734.497        227.1580\n",
      "243 2020-10-01     376.862        129.9220\n",
      "244 2021-01-01     575.683        167.6270\n",
      "245 2021-04-01     692.177        124.7765\n",
      "246 2021-07-01     536.611        227.1580\n",
      "247 2021-10-01     825.630        227.1580\n",
      "248 2022-01-01     374.513        193.9800\n",
      "249 2022-04-01     515.157        167.6270\n",
      "250 2022-07-01     450.366        185.8210\n",
      "251 2022-10-01     413.766        167.6270\n",
      "252 2023-01-01     405.196        183.3980\n",
      "253 2023-04-01     249.411        264.4540\n",
      "254 2023-07-01     547.116        167.6270\n",
      "255 2023-10-01     346.870        221.4005\n",
      "256 2024-01-01     298.930        198.0385\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "knn_model = KNeighborsRegressor(n_neighbors=2)\n",
    "knn_model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = knn_model.predict(X_test)\n",
    "\n",
    "printevals(y_test,y_pred)\n",
    "\n",
    "plotresults('Actual vs Forecasted GDP using KNN')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fdd2287",
   "metadata": {},
   "source": [
    "We can see KNN in its own right performed very well. Despite being out performed slightly in terms of error metrics compared to Random Forests, visually the model performed about the same and arguably captured the period before the pandemic from 2018-2019 even better than Random Forests. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9aadf738",
   "metadata": {},
   "source": [
    "# Conclusions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65377f55",
   "metadata": {},
   "source": [
    "Looking at all of our models, we can see the one which performed the best was Random Forests. This is most likely due to Random Forests generally being a very strong predictive model which can be fit to a vairety of datasets. In general the machine learning algorithms far outperformed the traditional statistical methods. Perhaps this can be explained by the fact that VAR and VECM both require a great amount of historical background data to work optimally, something which we did not have much of given that our data came out in quarterly intervals. There also may be something to be said about how both the machine learning models used were nonparametric. These models often are governed by less assumptions than their counterparts and therefore may be more flexible to unique problem sets like the one here. Below is our final best prediction, removing the differencing transformation we previously used to fit the models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3218862f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rf_model = RandomForestRegressor(n_estimators=100, random_state=42)\n",
    "rf_model.fit(X_train, y_train)\n",
    "\n",
    "y_pred = rf_model.predict(X_test)\n",
    "\n",
    "comparison_df = pd.DataFrame({'Date': Date_col, 'Actual GDP': y_test.values, 'Forecasted GDP': y_pred})\n",
    "comparison_df.dropna(inplace=True)\n",
    "\n",
    "last_actual_value = data.iloc[split_index - 1]['GDP : Billions of dollars']\n",
    "\n",
    "comparison_df['Actual GDP'] = comparison_df['Actual GDP'].cumsum() + last_actual_value\n",
    "comparison_df['Forecasted GDP'] = comparison_df['Forecasted GDP'].cumsum() + last_actual_value\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(comparison_df['Date'], comparison_df['Actual GDP'], label='Actual GDP', color='blue')\n",
    "plt.plot(comparison_df['Date'], comparison_df['Forecasted GDP'], label='Forecasted GDP', color='red', linestyle='--')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('GDP : Billions of dollars')\n",
    "plt.title('Actual vs Forecasted GDP (Differencing Removed) using Random Forest')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98b81785",
   "metadata": {},
   "source": [
    "# Challenges and Areas of Improvement"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4183a14b",
   "metadata": {},
   "source": [
    "By far the greatest challenge regarding this forecasting problem was handeling the massive outlier caused by the pandemic along with the following instability caused by it. Our methods for forecasting obviously can not predict that this would occur, ultimately decreasing our accuracy for each approach. Had our goal been to forecast the previous decade, our models would most likely have a much easier time finding and predicting trends. In terms of improvement and further research, I think a possible solution would be to perform some sort of normalization and outlier smoothing technique on the time interval from 2020-2024, and then evaluating our fully trained model on new quarterly data which comes in. In addition, it may be beneficial to incorporate new features which have a heavy influence on GDP such as quarterly inflation and personal assest evaluations."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf203f5",
   "metadata": {},
   "source": [
    "# References"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6fa82ef",
   "metadata": {},
   "source": [
    "For traditional statistical methods - https://link.springer.com/book/10.1007/978-1-4842-7150-6\n",
    "For machine learning methods - https://www.statlearning.com/"
   ]
  }
 ],
 "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}