VolCalculation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "#from brapi_wrapper import BrAPIWrapper\n",
    "import os\n",
    "from utils import *\n",
    "import yfinance as yf\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import yfinance as yf\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Options chain for last day\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from oplab_api import *\n",
    "OPT=fetch_options_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>symbol</th>\n",
       "      <th>block_date</th>\n",
       "      <th>category</th>\n",
       "      <th>contract_size</th>\n",
       "      <th>days_to_maturity</th>\n",
       "      <th>due_date</th>\n",
       "      <th>exchange_id</th>\n",
       "      <th>isin</th>\n",
       "      <th>market_maker</th>\n",
       "      <th>maturity_type</th>\n",
       "      <th>...</th>\n",
       "      <th>security_category</th>\n",
       "      <th>spot_price</th>\n",
       "      <th>trades</th>\n",
       "      <th>bid_volume</th>\n",
       "      <th>ask_volume</th>\n",
       "      <th>time</th>\n",
       "      <th>type</th>\n",
       "      <th>last_trade_at</th>\n",
       "      <th>strike_eod</th>\n",
       "      <th>quotation_form</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IBOVK10</td>\n",
       "      <td>2024-11-12</td>\n",
       "      <td>CALL</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>2024-11-13</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9K0DF2</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>CALL</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>10000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IBOVW10</td>\n",
       "      <td>2024-11-12</td>\n",
       "      <td>PUT</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>2024-11-13</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9W0DF8</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>PUT</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>10000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IBOVK700</td>\n",
       "      <td>2024-11-12</td>\n",
       "      <td>CALL</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>2024-11-13</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9K0G25</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>CALL</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>70000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IBOVW700</td>\n",
       "      <td>2024-11-12</td>\n",
       "      <td>PUT</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>2024-11-13</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9W0G20</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>PUT</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>70000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBOVK780</td>\n",
       "      <td>2024-11-12</td>\n",
       "      <td>CALL</td>\n",
       "      <td>100</td>\n",
       "      <td>15</td>\n",
       "      <td>2024-11-13</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9K0FL5</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>CALL</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>78000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1105</th>\n",
       "      <td>IBOVX140</td>\n",
       "      <td>2026-12-15</td>\n",
       "      <td>PUT</td>\n",
       "      <td>100</td>\n",
       "      <td>540</td>\n",
       "      <td>2026-12-16</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9X10V4</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>PUT</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>140000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1106</th>\n",
       "      <td>IBOVL150</td>\n",
       "      <td>2026-12-15</td>\n",
       "      <td>CALL</td>\n",
       "      <td>100</td>\n",
       "      <td>540</td>\n",
       "      <td>2026-12-16</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9L11L8</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>CALL</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>150000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1107</th>\n",
       "      <td>IBOVX150</td>\n",
       "      <td>2026-12-15</td>\n",
       "      <td>PUT</td>\n",
       "      <td>100</td>\n",
       "      <td>540</td>\n",
       "      <td>2026-12-16</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9X1129</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>PUT</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>150000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1108</th>\n",
       "      <td>IBOVL7</td>\n",
       "      <td>2026-12-15</td>\n",
       "      <td>CALL</td>\n",
       "      <td>100</td>\n",
       "      <td>540</td>\n",
       "      <td>2026-12-16</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9L11M6</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>CALL</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>170000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1109</th>\n",
       "      <td>IBOVX7</td>\n",
       "      <td>2026-12-15</td>\n",
       "      <td>PUT</td>\n",
       "      <td>100</td>\n",
       "      <td>540</td>\n",
       "      <td>2026-12-16</td>\n",
       "      <td>BOVESPA</td>\n",
       "      <td>BRIBOV9X1137</td>\n",
       "      <td>False</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>129951.37</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2024-10-23 13:00:00</td>\n",
       "      <td>PUT</td>\n",
       "      <td>-62167294412000</td>\n",
       "      <td>170000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1110 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        symbol  block_date category  contract_size  days_to_maturity  \\\n",
       "0      IBOVK10  2024-11-12     CALL            100                15   \n",
       "1      IBOVW10  2024-11-12      PUT            100                15   \n",
       "2     IBOVK700  2024-11-12     CALL            100                15   \n",
       "3     IBOVW700  2024-11-12      PUT            100                15   \n",
       "4     IBOVK780  2024-11-12     CALL            100                15   \n",
       "...        ...         ...      ...            ...               ...   \n",
       "1105  IBOVX140  2026-12-15      PUT            100               540   \n",
       "1106  IBOVL150  2026-12-15     CALL            100               540   \n",
       "1107  IBOVX150  2026-12-15      PUT            100               540   \n",
       "1108    IBOVL7  2026-12-15     CALL            100               540   \n",
       "1109    IBOVX7  2026-12-15      PUT            100               540   \n",
       "\n",
       "        due_date exchange_id          isin  market_maker maturity_type  ...  \\\n",
       "0     2024-11-13     BOVESPA  BRIBOV9K0DF2         False      EUROPEAN  ...   \n",
       "1     2024-11-13     BOVESPA  BRIBOV9W0DF8         False      EUROPEAN  ...   \n",
       "2     2024-11-13     BOVESPA  BRIBOV9K0G25         False      EUROPEAN  ...   \n",
       "3     2024-11-13     BOVESPA  BRIBOV9W0G20         False      EUROPEAN  ...   \n",
       "4     2024-11-13     BOVESPA  BRIBOV9K0FL5         False      EUROPEAN  ...   \n",
       "...          ...         ...           ...           ...           ...  ...   \n",
       "1105  2026-12-16     BOVESPA  BRIBOV9X10V4         False      EUROPEAN  ...   \n",
       "1106  2026-12-16     BOVESPA  BRIBOV9L11L8         False      EUROPEAN  ...   \n",
       "1107  2026-12-16     BOVESPA  BRIBOV9X1129         False      EUROPEAN  ...   \n",
       "1108  2026-12-16     BOVESPA  BRIBOV9L11M6         False      EUROPEAN  ...   \n",
       "1109  2026-12-16     BOVESPA  BRIBOV9X1137         False      EUROPEAN  ...   \n",
       "\n",
       "     security_category  spot_price trades  bid_volume ask_volume  \\\n",
       "0                    8   129951.37      0           0          0   \n",
       "1                    8   129951.37      0           0          0   \n",
       "2                    8   129951.37      0           0          0   \n",
       "3                    8   129951.37      0           0          0   \n",
       "4                    8   129951.37      0           0          0   \n",
       "...                ...         ...    ...         ...        ...   \n",
       "1105                 8   129951.37      0           0          0   \n",
       "1106                 8   129951.37      0           0          0   \n",
       "1107                 8   129951.37      0           0          0   \n",
       "1108                 8   129951.37      0           0          0   \n",
       "1109                 8   129951.37      0           0          0   \n",
       "\n",
       "                    time  type   last_trade_at  strike_eod  quotation_form  \n",
       "0    2024-10-23 13:00:00  CALL -62167294412000       10000             NaN  \n",
       "1    2024-10-23 13:00:00   PUT -62167294412000       10000             NaN  \n",
       "2    2024-10-23 13:00:00  CALL -62167294412000       70000             NaN  \n",
       "3    2024-10-23 13:00:00   PUT -62167294412000       70000             NaN  \n",
       "4    2024-10-23 13:00:00  CALL -62167294412000       78000             NaN  \n",
       "...                  ...   ...             ...         ...             ...  \n",
       "1105 2024-10-23 13:00:00   PUT -62167294412000      140000             NaN  \n",
       "1106 2024-10-23 13:00:00  CALL -62167294412000      150000             NaN  \n",
       "1107 2024-10-23 13:00:00   PUT -62167294412000      150000             NaN  \n",
       "1108 2024-10-23 13:00:00  CALL -62167294412000      170000             NaN  \n",
       "1109 2024-10-23 13:00:00   PUT -62167294412000      170000             NaN  \n",
       "\n",
       "[1110 rows x 35 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "OPT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_variance(options):\n",
    "    \"\"\"\n",
    "    Calculate the variance for a given set of options for a specific maturity.\n",
    "\n",
    "    Parameters:\n",
    "    - options: DataFrame containing options data for a specific maturity date.\n",
    "\n",
    "    Returns:\n",
    "    - sigma_squared: The variance for the given options.\n",
    "    - F: The forward index level.\n",
    "    - K0: The strike price closest to the forward index level.\n",
    "    \"\"\"\n",
    "    import numpy as np\n",
    "\n",
    "    # Ensure necessary columns are present\n",
    "    required_columns = ['type', 'moneyness', 'strike', 'premium', 'spot_price', 'due_date', 'time', 'rate']\n",
    "    for col in required_columns:\n",
    "        if col not in options.columns:\n",
    "            raise ValueError(f\"Missing required column: {col}\")\n",
    "\n",
    "    # Extract parameters\n",
    "    spot_price = options['spot_price'].iloc[0]\n",
    "    R = options['rate'].iloc[0]\n",
    "    T = (options['due_date'].iloc[0] - options['time'].iloc[0]).total_seconds() / (365.0 * 24 * 60 * 60)\n",
    "\n",
    "    # Use 'premium' as the mid-price\n",
    "    options = options.copy()\n",
    "    options['mid_price'] = options['premium']\n",
    "\n",
    "    # Select OTM and ATM options\n",
    "    otm_calls = options[(options['type'] == 'CALL') & (options['moneyness'].isin(['OTM', 'ATM']))]\n",
    "    otm_puts = options[(options['type'] == 'PUT') & (options['moneyness'].isin(['OTM', 'ATM']))]\n",
    "    otm_options = pd.concat([otm_calls, otm_puts], ignore_index=True)\n",
    "\n",
    "    # Ensure there are enough options\n",
    "    if otm_options.empty:\n",
    "        print(f\"No OTM/ATM options available for maturity {options['due_date'].iloc[0]}\")\n",
    "        return None, None, None\n",
    "\n",
    "    # Sort options by strike price\n",
    "    otm_options = otm_options.sort_values('strike').reset_index(drop=True)\n",
    "\n",
    "    # Calculate ΔK\n",
    "    strikes = otm_options['strike'].values\n",
    "    delta_K = np.zeros_like(strikes)\n",
    "\n",
    "    # For options not at the edges\n",
    "    delta_K[1:-1] = (strikes[2:] - strikes[:-2]) / 2\n",
    "\n",
    "    # For the lowest strike price\n",
    "    delta_K[0] = strikes[1] - strikes[0] if len(strikes) > 1 else strikes[0] * 0.01  # Approximate if only one strike\n",
    "\n",
    "    # For the highest strike price\n",
    "    delta_K[-1] = strikes[-1] - strikes[-2] if len(strikes) > 1 else strikes[-1] * 0.01  # Approximate if only one strike\n",
    "\n",
    "    otm_options['delta_K'] = delta_K\n",
    "\n",
    "    # Calculate contribution to variance\n",
    "    otm_options['contribution'] = (otm_options['delta_K'] / (otm_options['strike'] ** 2)) * \\\n",
    "                                  np.exp(R * T) * otm_options['mid_price']\n",
    "\n",
    "    # Sum contributions\n",
    "    sigma_squared = (2 / T) * otm_options['contribution'].sum()\n",
    "\n",
    "    # Calculate the forward index level (F)\n",
    "    # Identify K0 (the strike price closest to the spot price)\n",
    "    K0_row = otm_options.iloc[(otm_options['strike'] - spot_price).abs().argsort()[:1]]\n",
    "    K0 = K0_row['strike'].values[0]\n",
    "\n",
    "    # Find the call and put prices at K0\n",
    "    call_at_K0 = options[(options['type'] == 'CALL') & (options['strike'] == K0)]\n",
    "    put_at_K0 = options[(options['type'] == 'PUT') & (options['strike'] == K0)]\n",
    "\n",
    "    if not call_at_K0.empty and not put_at_K0.empty:\n",
    "        call_price = call_at_K0['mid_price'].values[0]\n",
    "        put_price = put_at_K0['mid_price'].values[0]\n",
    "        F = K0 + np.exp(R * T) * (call_price - put_price)\n",
    "    else:\n",
    "        # If missing data, approximate F\n",
    "        F = spot_price * np.exp(R * T)\n",
    "\n",
    "    return sigma_squared, F, K0\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VIX DAILY\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_daily_vix(options_data):\n",
    "    \"\"\"\n",
    "    Calculate the daily VIX values given options data.\n",
    "\n",
    "    Parameters:\n",
    "    - options_data: DataFrame containing options data for multiple dates.\n",
    "\n",
    "    Returns:\n",
    "    - vix_df: DataFrame containing dates and corresponding VIX values.\n",
    "    \"\"\"\n",
    "    import pandas as pd\n",
    "    from datetime import timedelta\n",
    "\n",
    "    # Ensure the data has necessary columns\n",
    "    required_columns = [\n",
    "        'symbol', 'time', 'spot_price', 'type', 'due_date', 'strike', 'premium',\n",
    "        'maturity_type', 'moneyness', 'rate'\n",
    "    ]\n",
    "    for col in required_columns:\n",
    "        if col not in options_data.columns:\n",
    "            raise ValueError(f\"Missing required column: {col}\")\n",
    "\n",
    "    # Convert 'time' and 'due_date' to datetime\n",
    "    options_data['time'] = pd.to_datetime(options_data['time'])\n",
    "    options_data['due_date'] = pd.to_datetime(options_data['due_date']).dt.tz_localize(None)\n",
    "\n",
    "    # Add 'date' column\n",
    "    options_data['date'] = options_data['time'].dt.normalize()\n",
    "\n",
    "    # Get unique dates\n",
    "    unique_dates = options_data['date'].unique()\n",
    "    vix_results = []\n",
    "\n",
    "    # Iterate over each date to calculate VIX\n",
    "    for current_date in sorted(unique_dates):\n",
    "        daily_data = options_data[options_data['date'] == current_date]\n",
    "\n",
    "        # Extract the spot price for the current date\n",
    "        spot_price = daily_data['spot_price'].iloc[-1]\n",
    "\n",
    "        # Calculate 'days_to_maturity'\n",
    "        daily_data['days_to_maturity'] = (daily_data['due_date'] - daily_data['time']).dt.days\n",
    "\n",
    "        # Filter options within a specific maturity range\n",
    "        options_in_range = daily_data[(daily_data['days_to_maturity'] >= 23) & (daily_data['days_to_maturity'] <= 37)]\n",
    "        if options_in_range.empty:\n",
    "            options_in_range = daily_data[(daily_data['days_to_maturity'] >= 7) & (daily_data['days_to_maturity'] <= 180)]\n",
    "            if options_in_range.empty:\n",
    "                print(f\"{current_date.date()}: Not enough options with suitable maturities.\")\n",
    "                vix_results.append({'date': current_date.date(), 'VIX': None})\n",
    "                continue\n",
    "\n",
    "        # Identify maturities bracketing 30 days\n",
    "        options_in_range = options_in_range.sort_values('due_date')\n",
    "        unique_maturities = options_in_range['due_date'].unique()\n",
    "        target_date = current_date + timedelta(days=30)\n",
    "        maturities_before = unique_maturities[unique_maturities <= target_date]\n",
    "        maturities_after = unique_maturities[unique_maturities > target_date]\n",
    "\n",
    "        if len(maturities_before) >= 1 and len(maturities_after) >= 1:\n",
    "            T1_date = maturities_before[-1]\n",
    "            T2_date = maturities_after[0]\n",
    "            options_T1 = options_in_range[options_in_range['due_date'] == T1_date]\n",
    "            options_T2 = options_in_range[options_in_range['due_date'] == T2_date]\n",
    "\n",
    "            sigma1_sq, F1, K01 = calculate_variance(options_T1)\n",
    "            sigma2_sq, F2, K02 = calculate_variance(options_T2)\n",
    "\n",
    "            if sigma1_sq is None or sigma2_sq is None:\n",
    "                print(f\"{current_date.date()}: Failed to calculate variances.\")\n",
    "                vix_results.append({'date': current_date.date(), 'VIX': None})\n",
    "                continue\n",
    "\n",
    "            # Calculate times to expiration\n",
    "            T1 = (T1_date - current_date).days / 365.0\n",
    "            T2 = (T2_date - current_date).days / 365.0\n",
    "\n",
    "            # Interpolate to 30 days\n",
    "            T_30 = 30 / 365.0\n",
    "            weight1 = (T2 - T_30) / (T2 - T1)\n",
    "            weight2 = 1 - weight1\n",
    "            sigma_30_sq = weight1 * sigma1_sq + weight2 * sigma2_sq\n",
    "            VIX = 100 * np.sqrt(sigma_30_sq)\n",
    "            vix_results.append({'date': current_date.date(), 'VIX': VIX})\n",
    "        else:\n",
    "            # Use the closest maturity\n",
    "            closest_maturity_date = min(unique_maturities, key=lambda x: abs((x - target_date).days))\n",
    "            options_T = options_in_range[options_in_range['due_date'] == closest_maturity_date]\n",
    "\n",
    "            sigma_sq, F, K0 = calculate_variance(options_T)\n",
    "            if sigma_sq is None:\n",
    "                print(f\"{current_date.date()}: Failed to calculate variance.\")\n",
    "                vix_results.append({'date': current_date.date(), 'VIX': None})\n",
    "                continue\n",
    "\n",
    "            # Calculate time to expiration\n",
    "            T = (closest_maturity_date - current_date).days / 365.0\n",
    "\n",
    "            # Adjust variance to 30 days\n",
    "            T_30 = 30 / 365.0\n",
    "            sigma_30_sq = sigma_sq * (T_30 / T)\n",
    "            VIX = 100 * np.sqrt(sigma_30_sq)\n",
    "            vix_results.append({'date': current_date.date(), 'VIX': VIX})\n",
    "\n",
    "    # Create a DataFrame with the results\n",
    "    vix_df = pd.DataFrame(vix_results)\n",
    "    return vix_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = calculate_daily_vix(hist)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HISTORICAL VIX\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>symbol</th>\n",
       "      <th>time</th>\n",
       "      <th>spot_price</th>\n",
       "      <th>type</th>\n",
       "      <th>due_date</th>\n",
       "      <th>strike</th>\n",
       "      <th>premium</th>\n",
       "      <th>maturity_type</th>\n",
       "      <th>days_to_maturity</th>\n",
       "      <th>moneyness</th>\n",
       "      <th>delta</th>\n",
       "      <th>gamma</th>\n",
       "      <th>vega</th>\n",
       "      <th>theta</th>\n",
       "      <th>rho</th>\n",
       "      <th>volatility</th>\n",
       "      <th>poe</th>\n",
       "      <th>bs</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IBOVA100</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>100000</td>\n",
       "      <td>6500</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.665250</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>58.402813</td>\n",
       "      <td>-332.596873</td>\n",
       "      <td>14.913124</td>\n",
       "      <td>67.319</td>\n",
       "      <td>62.66</td>\n",
       "      <td>6499.9711</td>\n",
       "      <td>2022-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IBOVA103</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>103000</td>\n",
       "      <td>2182</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.600429</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>61.934977</td>\n",
       "      <td>-138.656526</td>\n",
       "      <td>14.337311</td>\n",
       "      <td>25.940</td>\n",
       "      <td>58.49</td>\n",
       "      <td>2182.0328</td>\n",
       "      <td>2022-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IBOVA104</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>104000</td>\n",
       "      <td>1609</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.504977</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>63.967812</td>\n",
       "      <td>-139.295521</td>\n",
       "      <td>12.111909</td>\n",
       "      <td>25.374</td>\n",
       "      <td>48.94</td>\n",
       "      <td>1609.0103</td>\n",
       "      <td>2022-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IBOVA105</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>105000</td>\n",
       "      <td>1101</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.403624</td>\n",
       "      <td>0.000099</td>\n",
       "      <td>62.096937</td>\n",
       "      <td>-128.941412</td>\n",
       "      <td>9.725037</td>\n",
       "      <td>24.292</td>\n",
       "      <td>38.92</td>\n",
       "      <td>1100.9075</td>\n",
       "      <td>2022-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBOVA106</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>106000</td>\n",
       "      <td>900</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.327248</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>57.877006</td>\n",
       "      <td>-131.655558</td>\n",
       "      <td>7.883030</td>\n",
       "      <td>26.753</td>\n",
       "      <td>31.25</td>\n",
       "      <td>900.0683</td>\n",
       "      <td>2022-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61855</th>\n",
       "      <td>IBOVV126</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-10-16T00:00:00.000Z</td>\n",
       "      <td>126000</td>\n",
       "      <td>4605</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>98</td>\n",
       "      <td>ATM</td>\n",
       "      <td>-0.644807</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>283.523712</td>\n",
       "      <td>-7.088144</td>\n",
       "      <td>-324.079149</td>\n",
       "      <td>9.472</td>\n",
       "      <td>66.66</td>\n",
       "      <td>4604.9114</td>\n",
       "      <td>2024-05-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61856</th>\n",
       "      <td>IBOVV127</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-10-16T00:00:00.000Z</td>\n",
       "      <td>127000</td>\n",
       "      <td>5095</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>98</td>\n",
       "      <td>ATM</td>\n",
       "      <td>-0.709757</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>260.737593</td>\n",
       "      <td>-4.336379</td>\n",
       "      <td>-356.824848</td>\n",
       "      <td>8.734</td>\n",
       "      <td>72.81</td>\n",
       "      <td>5094.9607</td>\n",
       "      <td>2024-05-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61857</th>\n",
       "      <td>IBOVX10</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>100000</td>\n",
       "      <td>1085</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>OTM</td>\n",
       "      <td>-0.099093</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>160.346170</td>\n",
       "      <td>-12.054379</td>\n",
       "      <td>-74.814599</td>\n",
       "      <td>23.367</td>\n",
       "      <td>13.33</td>\n",
       "      <td>1085.0525</td>\n",
       "      <td>2024-05-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61858</th>\n",
       "      <td>IBOVX11</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>110000</td>\n",
       "      <td>1895</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>OTM</td>\n",
       "      <td>-0.187079</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>247.218818</td>\n",
       "      <td>-14.266330</td>\n",
       "      <td>-140.372219</td>\n",
       "      <td>18.776</td>\n",
       "      <td>22.74</td>\n",
       "      <td>1894.9478</td>\n",
       "      <td>2024-05-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61859</th>\n",
       "      <td>IBOVX130</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>130000</td>\n",
       "      <td>6960</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>ITM</td>\n",
       "      <td>-0.836826</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>226.674045</td>\n",
       "      <td>3.295265</td>\n",
       "      <td>-619.296797</td>\n",
       "      <td>6.771</td>\n",
       "      <td>84.91</td>\n",
       "      <td>6960.0250</td>\n",
       "      <td>2024-05-31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61860 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         symbol       time  spot_price  type                  due_date  \\\n",
       "0      IBOVA100 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "1      IBOVA103 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "2      IBOVA104 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "3      IBOVA105 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "4      IBOVA106 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "...         ...        ...         ...   ...                       ...   \n",
       "61855  IBOVV126 2024-05-31   122098.09   PUT  2024-10-16T00:00:00.000Z   \n",
       "61856  IBOVV127 2024-05-31   122098.09   PUT  2024-10-16T00:00:00.000Z   \n",
       "61857   IBOVX10 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "61858   IBOVX11 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "61859  IBOVX130 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "\n",
       "       strike  premium maturity_type  days_to_maturity moneyness     delta  \\\n",
       "0      100000     6500      EUROPEAN                 6       ATM  0.665250   \n",
       "1      103000     2182      EUROPEAN                 6       ATM  0.600429   \n",
       "2      104000     1609      EUROPEAN                 6       ATM  0.504977   \n",
       "3      105000     1101      EUROPEAN                 6       ATM  0.403624   \n",
       "4      106000      900      EUROPEAN                 6       ATM  0.327248   \n",
       "...       ...      ...           ...               ...       ...       ...   \n",
       "61855  126000     4605      EUROPEAN                98       ATM -0.644807   \n",
       "61856  127000     5095      EUROPEAN                98       ATM -0.709757   \n",
       "61857  100000     1085      EUROPEAN               143       OTM -0.099093   \n",
       "61858  110000     1895      EUROPEAN               143       OTM -0.187079   \n",
       "61859  130000     6960      EUROPEAN               143       ITM -0.836826   \n",
       "\n",
       "          gamma        vega       theta         rho  volatility    poe  \\\n",
       "0      0.000034   58.402813 -332.596873   14.913124      67.319  62.66   \n",
       "1      0.000093   61.934977 -138.656526   14.337311      25.940  58.49   \n",
       "2      0.000098   63.967812 -139.295521   12.111909      25.374  48.94   \n",
       "3      0.000099   62.096937 -128.941412    9.725037      24.292  38.92   \n",
       "4      0.000084   57.877006 -131.655558    7.883030      26.753  31.25   \n",
       "...         ...         ...         ...         ...         ...    ...   \n",
       "61855  0.000052  283.523712   -7.088144 -324.079149       9.472  66.66   \n",
       "61856  0.000051  260.737593   -4.336379 -356.824848       8.734  72.81   \n",
       "61857  0.000008  160.346170  -12.054379  -74.814599      23.367  13.33   \n",
       "61858  0.000016  247.218818  -14.266330 -140.372219      18.776  22.74   \n",
       "61859  0.000040  226.674045    3.295265 -619.296797       6.771  84.91   \n",
       "\n",
       "              bs       date  \n",
       "0      6499.9711 2022-01-03  \n",
       "1      2182.0328 2022-01-03  \n",
       "2      1609.0103 2022-01-03  \n",
       "3      1100.9075 2022-01-03  \n",
       "4       900.0683 2022-01-03  \n",
       "...          ...        ...  \n",
       "61855  4604.9114 2024-05-31  \n",
       "61856  5094.9607 2024-05-31  \n",
       "61857  1085.0525 2024-05-31  \n",
       "61858  1894.9478 2024-05-31  \n",
       "61859  6960.0250 2024-05-31  \n",
       "\n",
       "[61860 rows x 19 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist = get_historical_options(spot='ibov', start='2022-01-01', end='2024-06-01')\n",
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Formatting date: 01/01/2022\n",
      "Formatting date: 01/06/2024\n"
     ]
    },
    {
     "ename": "KeyError",
     "evalue": "'date'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[0;32m~/Documents/code/quant/env/lib/python3.12/site-packages/pandas/core/indexes/base.py:3805\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3804\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3805\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcasted_key\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3806\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
      "File \u001b[0;32mindex.pyx:167\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mindex.pyx:196\u001b[0m, in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7081\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32mpandas/_libs/hashtable_class_helper.pxi:7089\u001b[0m, in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'date'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[27], line 7\u001b[0m\n\u001b[1;32m      4\u001b[0m hist \u001b[38;5;241m=\u001b[39m get_historical_options(spot\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mibov\u001b[39m\u001b[38;5;124m'\u001b[39m, start\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m2022-01-01\u001b[39m\u001b[38;5;124m'\u001b[39m, end\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m2024-06-01\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m      6\u001b[0m api \u001b[38;5;241m=\u001b[39m BrAPIWrapper()  \u001b[38;5;66;03m# Will use BRAPI_API_KEY from environment variables\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m rates \u001b[38;5;241m=\u001b[39m \u001b[43mapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_prime_rate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m01/01/2022\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m01/06/2024\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# rates['date'] = pd.to_datetime(rates.index)\u001b[39;00m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m# rates.reset_index(drop=True, inplace=True)  # Drop the index to avoid conflict\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;03m# rates.rename(columns={'prime_rate': 'rate'}, inplace=True)\u001b[39;00m\n\u001b[1;32m     11\u001b[0m \n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;03m# hist['time'] = pd.to_datetime(hist['time'])\u001b[39;00m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;66;03m# hist['date'] = hist['time'].dt.normalize()\u001b[39;00m\n\u001b[1;32m     14\u001b[0m hist \u001b[38;5;241m=\u001b[39m hist\u001b[38;5;241m.\u001b[39mmerge(rates, on\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m, how\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mleft\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[0;32m~/Documents/code/quant/BrAPIWrapper.py:291\u001b[0m, in \u001b[0;36mBrAPIWrapper.get_prime_rate\u001b[0;34m(self, country, historical, start, end, sort_by, sort_order)\u001b[0m\n\u001b[1;32m    289\u001b[0m raw \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_request(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mv2/prime-rate\u001b[39m\u001b[38;5;124m\"\u001b[39m, params)\n\u001b[1;32m    290\u001b[0m raw_df \u001b[38;5;241m=\u001b[39m prime_rate_to_dataframe(raw)\n\u001b[0;32m--> 291\u001b[0m raw_df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_datetime(\u001b[43mraw_df\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdate\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m)\u001b[38;5;241m.\u001b[39mdt\u001b[38;5;241m.\u001b[39mdate\n\u001b[1;32m    292\u001b[0m raw_df\u001b[38;5;241m.\u001b[39mreset_index(drop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, inplace\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)  \u001b[38;5;66;03m# Drop the index to avoid conflict\u001b[39;00m\n\u001b[1;32m    293\u001b[0m raw_df\u001b[38;5;241m.\u001b[39mrename(columns\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mprime_rate\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrate\u001b[39m\u001b[38;5;124m'\u001b[39m}, inplace\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
      "File \u001b[0;32m~/Documents/code/quant/env/lib/python3.12/site-packages/pandas/core/frame.py:4102\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   4100\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcolumns\u001b[38;5;241m.\u001b[39mnlevels \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   4101\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_getitem_multilevel(key)\n\u001b[0;32m-> 4102\u001b[0m indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_loc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   4103\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_integer(indexer):\n\u001b[1;32m   4104\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m [indexer]\n",
      "File \u001b[0;32m~/Documents/code/quant/env/lib/python3.12/site-packages/pandas/core/indexes/base.py:3812\u001b[0m, in \u001b[0;36mIndex.get_loc\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3807\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(casted_key, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m (\n\u001b[1;32m   3808\u001b[0m         \u001b[38;5;28misinstance\u001b[39m(casted_key, abc\u001b[38;5;241m.\u001b[39mIterable)\n\u001b[1;32m   3809\u001b[0m         \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28many\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(x, \u001b[38;5;28mslice\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m casted_key)\n\u001b[1;32m   3810\u001b[0m     ):\n\u001b[1;32m   3811\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(key)\n\u001b[0;32m-> 3812\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n\u001b[1;32m   3813\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m   3814\u001b[0m     \u001b[38;5;66;03m# If we have a listlike key, _check_indexing_error will raise\u001b[39;00m\n\u001b[1;32m   3815\u001b[0m     \u001b[38;5;66;03m#  InvalidIndexError. Otherwise we fall through and re-raise\u001b[39;00m\n\u001b[1;32m   3816\u001b[0m     \u001b[38;5;66;03m#  the TypeError.\u001b[39;00m\n\u001b[1;32m   3817\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_error(key)\n",
      "\u001b[0;31mKeyError\u001b[0m: 'date'"
     ]
    }
   ],
   "source": [
    "from oplab_api import *\n",
    "from BrAPIWrapper import BrAPIWrapper\n",
    "\n",
    "hist = get_historical_options(spot='ibov', start='2022-01-01', end='2024-06-01')\n",
    "\n",
    "api = BrAPIWrapper()  # Will use BRAPI_API_KEY from environment variables\n",
    "rates = api.get_prime_rate(start='01/01/2022', end='01/06/2024')\n",
    "rates['date'] = pd.to_datetime(rates.index)\n",
    "# rates.reset_index(drop=True, inplace=True)  # Drop the index to avoid conflict\n",
    "# rates.rename(columns={'prime_rate': 'rate'}, inplace=True)\n",
    "\n",
    "# hist['time'] = pd.to_datetime(hist['time'])\n",
    "# hist['date'] = hist['time'].dt.normalize()\n",
    "    hist = hist.merge(rates, on='date', how='left')\n",
    "    hist['rate'] = hist['rate'] / 100\n",
    "\n",
    "    # Check for missing risk-free rates\n",
    "    if hist['rate'].isnull().any():\n",
    "        missing_dates = hist[hist['rate'].isnull()]['date'].unique()\n",
    "        raise ValueError(f\"Missing risk-free rates for dates: {missing_dates}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>symbol</th>\n",
       "      <th>time</th>\n",
       "      <th>spot_price</th>\n",
       "      <th>type</th>\n",
       "      <th>due_date</th>\n",
       "      <th>strike</th>\n",
       "      <th>premium</th>\n",
       "      <th>maturity_type</th>\n",
       "      <th>days_to_maturity</th>\n",
       "      <th>moneyness</th>\n",
       "      <th>delta</th>\n",
       "      <th>gamma</th>\n",
       "      <th>vega</th>\n",
       "      <th>theta</th>\n",
       "      <th>rho</th>\n",
       "      <th>volatility</th>\n",
       "      <th>poe</th>\n",
       "      <th>bs</th>\n",
       "      <th>date</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IBOVA100</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>100000</td>\n",
       "      <td>6500</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.665250</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>58.402813</td>\n",
       "      <td>-332.596873</td>\n",
       "      <td>14.913124</td>\n",
       "      <td>67.319</td>\n",
       "      <td>62.66</td>\n",
       "      <td>6499.9711</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0.000925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IBOVA103</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>103000</td>\n",
       "      <td>2182</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.600429</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>61.934977</td>\n",
       "      <td>-138.656526</td>\n",
       "      <td>14.337311</td>\n",
       "      <td>25.940</td>\n",
       "      <td>58.49</td>\n",
       "      <td>2182.0328</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0.000925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>IBOVA104</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>104000</td>\n",
       "      <td>1609</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.504977</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>63.967812</td>\n",
       "      <td>-139.295521</td>\n",
       "      <td>12.111909</td>\n",
       "      <td>25.374</td>\n",
       "      <td>48.94</td>\n",
       "      <td>1609.0103</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0.000925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>IBOVA105</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>105000</td>\n",
       "      <td>1101</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.403624</td>\n",
       "      <td>0.000099</td>\n",
       "      <td>62.096937</td>\n",
       "      <td>-128.941412</td>\n",
       "      <td>9.725037</td>\n",
       "      <td>24.292</td>\n",
       "      <td>38.92</td>\n",
       "      <td>1100.9075</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0.000925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IBOVA106</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>103921.59</td>\n",
       "      <td>CALL</td>\n",
       "      <td>2022-01-12T00:00:00.000Z</td>\n",
       "      <td>106000</td>\n",
       "      <td>900</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>6</td>\n",
       "      <td>ATM</td>\n",
       "      <td>0.327248</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>57.877006</td>\n",
       "      <td>-131.655558</td>\n",
       "      <td>7.883030</td>\n",
       "      <td>26.753</td>\n",
       "      <td>31.25</td>\n",
       "      <td>900.0683</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>0.000925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61855</th>\n",
       "      <td>IBOVV126</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-10-16T00:00:00.000Z</td>\n",
       "      <td>126000</td>\n",
       "      <td>4605</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>98</td>\n",
       "      <td>ATM</td>\n",
       "      <td>-0.644807</td>\n",
       "      <td>0.000052</td>\n",
       "      <td>283.523712</td>\n",
       "      <td>-7.088144</td>\n",
       "      <td>-324.079149</td>\n",
       "      <td>9.472</td>\n",
       "      <td>66.66</td>\n",
       "      <td>4604.9114</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>0.001050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61856</th>\n",
       "      <td>IBOVV127</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-10-16T00:00:00.000Z</td>\n",
       "      <td>127000</td>\n",
       "      <td>5095</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>98</td>\n",
       "      <td>ATM</td>\n",
       "      <td>-0.709757</td>\n",
       "      <td>0.000051</td>\n",
       "      <td>260.737593</td>\n",
       "      <td>-4.336379</td>\n",
       "      <td>-356.824848</td>\n",
       "      <td>8.734</td>\n",
       "      <td>72.81</td>\n",
       "      <td>5094.9607</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>0.001050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61857</th>\n",
       "      <td>IBOVX10</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>100000</td>\n",
       "      <td>1085</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>OTM</td>\n",
       "      <td>-0.099093</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>160.346170</td>\n",
       "      <td>-12.054379</td>\n",
       "      <td>-74.814599</td>\n",
       "      <td>23.367</td>\n",
       "      <td>13.33</td>\n",
       "      <td>1085.0525</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>0.001050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61858</th>\n",
       "      <td>IBOVX11</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>110000</td>\n",
       "      <td>1895</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>OTM</td>\n",
       "      <td>-0.187079</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>247.218818</td>\n",
       "      <td>-14.266330</td>\n",
       "      <td>-140.372219</td>\n",
       "      <td>18.776</td>\n",
       "      <td>22.74</td>\n",
       "      <td>1894.9478</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>0.001050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61859</th>\n",
       "      <td>IBOVX130</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>122098.09</td>\n",
       "      <td>PUT</td>\n",
       "      <td>2024-12-18T00:00:00.000Z</td>\n",
       "      <td>130000</td>\n",
       "      <td>6960</td>\n",
       "      <td>EUROPEAN</td>\n",
       "      <td>143</td>\n",
       "      <td>ITM</td>\n",
       "      <td>-0.836826</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>226.674045</td>\n",
       "      <td>3.295265</td>\n",
       "      <td>-619.296797</td>\n",
       "      <td>6.771</td>\n",
       "      <td>84.91</td>\n",
       "      <td>6960.0250</td>\n",
       "      <td>2024-05-31</td>\n",
       "      <td>0.001050</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>61860 rows × 20 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         symbol       time  spot_price  type                  due_date  \\\n",
       "0      IBOVA100 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "1      IBOVA103 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "2      IBOVA104 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "3      IBOVA105 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "4      IBOVA106 2022-01-03   103921.59  CALL  2022-01-12T00:00:00.000Z   \n",
       "...         ...        ...         ...   ...                       ...   \n",
       "61855  IBOVV126 2024-05-31   122098.09   PUT  2024-10-16T00:00:00.000Z   \n",
       "61856  IBOVV127 2024-05-31   122098.09   PUT  2024-10-16T00:00:00.000Z   \n",
       "61857   IBOVX10 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "61858   IBOVX11 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "61859  IBOVX130 2024-05-31   122098.09   PUT  2024-12-18T00:00:00.000Z   \n",
       "\n",
       "       strike  premium maturity_type  days_to_maturity moneyness     delta  \\\n",
       "0      100000     6500      EUROPEAN                 6       ATM  0.665250   \n",
       "1      103000     2182      EUROPEAN                 6       ATM  0.600429   \n",
       "2      104000     1609      EUROPEAN                 6       ATM  0.504977   \n",
       "3      105000     1101      EUROPEAN                 6       ATM  0.403624   \n",
       "4      106000      900      EUROPEAN                 6       ATM  0.327248   \n",
       "...       ...      ...           ...               ...       ...       ...   \n",
       "61855  126000     4605      EUROPEAN                98       ATM -0.644807   \n",
       "61856  127000     5095      EUROPEAN                98       ATM -0.709757   \n",
       "61857  100000     1085      EUROPEAN               143       OTM -0.099093   \n",
       "61858  110000     1895      EUROPEAN               143       OTM -0.187079   \n",
       "61859  130000     6960      EUROPEAN               143       ITM -0.836826   \n",
       "\n",
       "          gamma        vega       theta         rho  volatility    poe  \\\n",
       "0      0.000034   58.402813 -332.596873   14.913124      67.319  62.66   \n",
       "1      0.000093   61.934977 -138.656526   14.337311      25.940  58.49   \n",
       "2      0.000098   63.967812 -139.295521   12.111909      25.374  48.94   \n",
       "3      0.000099   62.096937 -128.941412    9.725037      24.292  38.92   \n",
       "4      0.000084   57.877006 -131.655558    7.883030      26.753  31.25   \n",
       "...         ...         ...         ...         ...         ...    ...   \n",
       "61855  0.000052  283.523712   -7.088144 -324.079149       9.472  66.66   \n",
       "61856  0.000051  260.737593   -4.336379 -356.824848       8.734  72.81   \n",
       "61857  0.000008  160.346170  -12.054379  -74.814599      23.367  13.33   \n",
       "61858  0.000016  247.218818  -14.266330 -140.372219      18.776  22.74   \n",
       "61859  0.000040  226.674045    3.295265 -619.296797       6.771  84.91   \n",
       "\n",
       "              bs       date      rate  \n",
       "0      6499.9711 2022-01-03  0.000925  \n",
       "1      2182.0328 2022-01-03  0.000925  \n",
       "2      1609.0103 2022-01-03  0.000925  \n",
       "3      1100.9075 2022-01-03  0.000925  \n",
       "4       900.0683 2022-01-03  0.000925  \n",
       "...          ...        ...       ...  \n",
       "61855  4604.9114 2024-05-31  0.001050  \n",
       "61856  5094.9607 2024-05-31  0.001050  \n",
       "61857  1085.0525 2024-05-31  0.001050  \n",
       "61858  1894.9478 2024-05-31  0.001050  \n",
       "61859  6960.0250 2024-05-31  0.001050  \n",
       "\n",
       "[61860 rows x 20 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F: 104.1948495790438, K0: 104.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=120.0: 1000\n",
      "Contribution to sigma_squared at K=120.0: 0.34813523556506176\n",
      "F: 105.26437350859649, K0: 105.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 8000\n",
      "Contribution to sigma_squared at K=125.0: 1.555846842886105\n",
      "Date 2022-01-03: The calculated VIX-equivalent index is 2111.02\n",
      "F: 103.75554858697583, K0: 103.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=115.0: 100\n",
      "Contribution to sigma_squared at K=115.0: 0.015158215093382053\n",
      "F: 104.82056324447535, K0: 104.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 8000\n",
      "Contribution to sigma_squared at K=122.0: 2.1771042490235524\n",
      "Date 2022-01-04: The calculated VIX-equivalent index is 2238.41\n",
      "F: 101.21215138502717, K0: 101.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=120.0: 1000\n",
      "Contribution to sigma_squared at K=120.0: 0.556691418337449\n",
      "F: 102.25105895392458, K0: 102.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=128.0: 500\n",
      "Contribution to sigma_squared at K=128.0: 0.18536319437154444\n",
      "Date 2022-01-05: The calculated VIX-equivalent index is 2297.31\n",
      "F: 101.73900712784241, K0: 101.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=113.0: 1000\n",
      "Contribution to sigma_squared at K=113.0: 0.15690378546088832\n",
      "F: 102.7833226878895, K0: 102.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=122.0: 3500\n",
      "Contribution to sigma_squared at K=122.0: 1.1899092981109667\n",
      "Date 2022-01-06: The calculated VIX-equivalent index is 2209.45\n",
      "F: 102.86943722421846, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 500\n",
      "Contribution to sigma_squared at K=115.0: 0.0378623806740227\n",
      "F: 103.9253562564491, K0: 103.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=125.0: 1500\n",
      "Contribution to sigma_squared at K=125.0: 0.3885080092652002\n",
      "Date 2022-01-07: The calculated VIX-equivalent index is 2112.23\n",
      "F: 102.00470867029311, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 1000\n",
      "Contribution to sigma_squared at K=115.0: 0.07565850525134654\n",
      "F: 103.0517515643583, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 8400\n",
      "Contribution to sigma_squared at K=117.0: 0.6202919688107349\n",
      "Date 2022-01-10: The calculated VIX-equivalent index is 2266.54\n",
      "F: 103.80926513417799, K0: 103.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=124.0: 700\n",
      "Contribution to sigma_squared at K=124.0: 0.45538779681052133\n",
      "F: 104.8748311733713, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 15500\n",
      "Contribution to sigma_squared at K=116.0: 1.164065978524052\n",
      "Date 2022-01-11: The calculated VIX-equivalent index is 2190.99\n",
      "F: 106.77048658055782, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=118.0: 17600\n",
      "Contribution to sigma_squared at K=118.0: 2.5539583287948737\n",
      "F: 107.64635984030575, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=114.0: 114900\n",
      "Contribution to sigma_squared at K=114.0: 18.01041027608873\n",
      "Date 2022-01-12: The calculated VIX-equivalent index is 2224.52\n",
      "F: 106.58162064213136, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 9000\n",
      "Contribution to sigma_squared at K=120.0: 1.2624623996386242\n",
      "F: 107.45594457274869, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=116.0: 73200\n",
      "Contribution to sigma_squared at K=116.0: 11.078517904668834\n",
      "Date 2022-01-13: The calculated VIX-equivalent index is 2372.29\n",
      "F: 107.96234554305443, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 5000\n",
      "Contribution to sigma_squared at K=122.0: 0.6783628546397852\n",
      "F: 108.84799601210499, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 98000\n",
      "Contribution to sigma_squared at K=116.0: 7.413784262029136\n",
      "Date 2022-01-14: The calculated VIX-equivalent index is 2204.87\n",
      "F: 107.30909288653206, K0: 107.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.08953773798008902\n",
      "F: 108.18938451015603, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 66800\n",
      "Contribution to sigma_squared at K=117.0: 4.963116041235524\n",
      "Date 2022-01-17: The calculated VIX-equivalent index is 2109.04\n",
      "F: 107.57407321236914, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 2000\n",
      "Contribution to sigma_squared at K=127.0: 0.25010789130946137\n",
      "F: 108.45653855636468, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 65300\n",
      "Contribution to sigma_squared at K=117.0: 4.8502534073292285\n",
      "Date 2022-01-18: The calculated VIX-equivalent index is 2151.13\n",
      "F: 108.89953985970983, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 6000\n",
      "Contribution to sigma_squared at K=122.0: 0.8128486918158913\n",
      "F: 109.79287844059199, K0: 109.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=125.0: 14400\n",
      "Contribution to sigma_squared at K=125.0: 6.55747674244654\n",
      "Date 2022-01-19: The calculated VIX-equivalent index is 2222.39\n",
      "F: 109.96489901560764, K0: 109.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.29819798696247335\n",
      "F: 110.8669770864609, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 40200\n",
      "Contribution to sigma_squared at K=122.0: 8.233740597403932\n",
      "Date 2022-01-20: The calculated VIX-equivalent index is 2197.00\n",
      "F: 109.77128726278579, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 11500\n",
      "Contribution to sigma_squared at K=121.0: 0.7914469112759337\n",
      "F: 110.67177707303914, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 39100\n",
      "Contribution to sigma_squared at K=122.0: 8.006102869660682\n",
      "Date 2022-01-21: The calculated VIX-equivalent index is 2343.39\n",
      "F: 108.66390753590808, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 12100\n",
      "Contribution to sigma_squared at K=120.0: 0.8459358115936471\n",
      "F: 109.55531314768841, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 34800\n",
      "Contribution to sigma_squared at K=122.0: 7.119401670723285\n",
      "Date 2022-01-24: The calculated VIX-equivalent index is 2535.83\n",
      "F: 110.91346301091245, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 7000\n",
      "Contribution to sigma_squared at K=130.0: 0.41686856663484423\n",
      "F: 111.8233224627939, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 54100\n",
      "Contribution to sigma_squared at K=122.0: 7.376384379051647\n",
      "Date 2022-01-25: The calculated VIX-equivalent index is 2432.96\n",
      "F: 111.97318646621997, K0: 111.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 10400\n",
      "Contribution to sigma_squared at K=130.0: 2.4766675893165755\n",
      "F: 112.8917391765753, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 29700\n",
      "Contribution to sigma_squared at K=126.0: 1.8976869905216713\n",
      "Date 2022-01-26: The calculated VIX-equivalent index is 2334.04\n",
      "F: 113.27072959336503, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 11900\n",
      "Contribution to sigma_squared at K=126.0: 1.5078920199208088\n",
      "F: 114.19992647482827, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 39400\n",
      "Contribution to sigma_squared at K=125.0: 2.5571646858822064\n",
      "Date 2022-01-27: The calculated VIX-equivalent index is 2210.55\n",
      "F: 112.53223410944203, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 9500\n",
      "Contribution to sigma_squared at K=122.0: 0.641817568902506\n",
      "F: 113.4553728706557, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 34000\n",
      "Contribution to sigma_squared at K=125.0: 11.030232810378456\n",
      "Date 2022-01-28: The calculated VIX-equivalent index is 2237.12\n",
      "F: 112.66827518657146, K0: 112.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 4000\n",
      "Contribution to sigma_squared at K=125.0: 1.2859896416548\n",
      "F: 113.59252993728278, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 47100\n",
      "Contribution to sigma_squared at K=123.0: 3.1534526294326923\n",
      "Date 2022-01-31: The calculated VIX-equivalent index is 2142.61\n",
      "F: 113.72496380294503, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 3000\n",
      "Contribution to sigma_squared at K=126.0: 0.5693799909991913\n",
      "F: 114.65788691635287, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 32500\n",
      "Contribution to sigma_squared at K=125.0: 2.1062612767603257\n",
      "Date 2022-02-01: The calculated VIX-equivalent index is 2123.36\n",
      "F: 112.35237564096799, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 7500\n",
      "Contribution to sigma_squared at K=120.0: 0.522965253235321\n",
      "F: 113.27403896427626, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 25700\n",
      "Contribution to sigma_squared at K=125.0: 1.66508070012145\n",
      "Date 2022-02-02: The calculated VIX-equivalent index is 2193.31\n",
      "F: 112.12042408841441, K0: 112.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 2000\n",
      "Contribution to sigma_squared at K=122.0: 0.5395325739239953\n",
      "F: 113.04018463719254, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 20100\n",
      "Contribution to sigma_squared at K=125.0: 2.6037632794403174\n",
      "Date 2022-02-03: The calculated VIX-equivalent index is 2195.35\n",
      "F: 112.63863989244446, K0: 112.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 1500\n",
      "Contribution to sigma_squared at K=122.0: 0.4045313787230447\n",
      "F: 113.562651535135, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 27100\n",
      "Contribution to sigma_squared at K=123.0: 1.8122905256266464\n",
      "Date 2022-02-04: The calculated VIX-equivalent index is 2125.21\n",
      "F: 112.29089211774398, K0: 112.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 1500\n",
      "Contribution to sigma_squared at K=122.0: 0.4041774301642211\n",
      "F: 113.21205107158059, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 14400\n",
      "Contribution to sigma_squared at K=125.0: 0.9316033932123593\n",
      "Date 2022-02-07: The calculated VIX-equivalent index is 2103.72\n",
      "F: 112.49674890828878, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 5300\n",
      "Contribution to sigma_squared at K=117.0: 0.38807699299908016\n",
      "F: 113.41959657277897, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 9000\n",
      "Contribution to sigma_squared at K=126.0: 1.7186385568377929\n",
      "Date 2022-02-08: The calculated VIX-equivalent index is 2068.63\n",
      "F: 112.69132327314178, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 1500\n",
      "Contribution to sigma_squared at K=122.0: 0.2019708182627132\n",
      "F: 113.61576709485354, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 4400\n",
      "Contribution to sigma_squared at K=130.0: 0.2630274835069513\n",
      "Date 2022-02-09: The calculated VIX-equivalent index is 1953.91\n",
      "F: 113.56641507839471, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=151.0: 800\n",
      "Contribution to sigma_squared at K=151.0: 0.17573829538617458\n",
      "F: 114.49803756470371, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 3800\n",
      "Contribution to sigma_squared at K=131.0: 0.2236399798905319\n",
      "Date 2022-02-10: The calculated VIX-equivalent index is 2029.78\n",
      "F: 113.7381620907114, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 13100\n",
      "Contribution to sigma_squared at K=118.0: 0.9421951732006246\n",
      "F: 114.6711934739951, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 18000\n",
      "Contribution to sigma_squared at K=127.0: 1.126799858095692\n",
      "Date 2022-02-11: The calculated VIX-equivalent index is 2354.79\n",
      "F: 113.96567659617483, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=122.0: 500\n",
      "Contribution to sigma_squared at K=122.0: 0.1680636475324271\n",
      "F: 114.90057435543864, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=129.0: 5000\n",
      "Contribution to sigma_squared at K=129.0: 0.6062086700973517\n",
      "Date 2022-02-14: The calculated VIX-equivalent index is 2271.24\n",
      "F: 115.80393759611022, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 11000\n",
      "Contribution to sigma_squared at K=126.0: 0.6987574321024396\n",
      "F: 116.75391521223192, K0: 116.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=130.0: 37000\n",
      "Contribution to sigma_squared at K=130.0: 3.3390986512478626\n",
      "Date 2022-02-15: The calculated VIX-equivalent index is 2088.99\n",
      "F: 116.1258170448949, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 13100\n",
      "Contribution to sigma_squared at K=126.0: 0.8319138063205427\n",
      "F: 117.07843514352335, K0: 117.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=130.0: 105300\n",
      "Contribution to sigma_squared at K=130.0: 22.166951127561173\n",
      "Date 2022-02-16: The calculated VIX-equivalent index is 2036.02\n",
      "F: 114.42639899231382, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 13000\n",
      "Contribution to sigma_squared at K=127.0: 0.8123764366750003\n",
      "F: 115.36507620824088, K0: 115.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=130.0: 31700\n",
      "Contribution to sigma_squared at K=130.0: 2.8591263675268603\n",
      "Date 2022-02-17: The calculated VIX-equivalent index is 2106.37\n",
      "F: 113.73944701908556, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 8500\n",
      "Contribution to sigma_squared at K=126.0: 1.078952982767788\n",
      "F: 114.6724889430574, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 29600\n",
      "Contribution to sigma_squared at K=128.0: 1.8353317894592418\n",
      "Date 2022-02-18: The calculated VIX-equivalent index is 2054.59\n",
      "F: 112.47760541876275, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 9400\n",
      "Contribution to sigma_squared at K=125.0: 0.6056508903527461\n",
      "F: 113.40029604294048, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=129.0: 19000\n",
      "Contribution to sigma_squared at K=129.0: 2.317751308133908\n",
      "Date 2022-02-21: The calculated VIX-equivalent index is 2299.03\n",
      "F: 113.61880345414069, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 8000\n",
      "Contribution to sigma_squared at K=124.0: 0.5236419485750607\n",
      "F: 114.55085569944872, K0: 114.0\n",
      "deltaK: 9.0\n",
      "Q_K at K=135.0: 1200\n",
      "Contribution to sigma_squared at K=135.0: 0.6013013218199752\n",
      "Date 2022-02-22: The calculated VIX-equivalent index is 2194.48\n",
      "F: 112.69603208654827, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 7500\n",
      "Contribution to sigma_squared at K=124.0: 0.9815422165971567\n",
      "F: 113.62051453619812, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 15000\n",
      "Contribution to sigma_squared at K=129.0: 0.9143680862929533\n",
      "Date 2022-02-23: The calculated VIX-equivalent index is 2159.78\n",
      "F: 112.24498115059981, K0: 112.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=130.0: 5000\n",
      "Contribution to sigma_squared at K=130.0: 1.3391529720946547\n",
      "F: 113.16576348174097, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 18400\n",
      "Contribution to sigma_squared at K=127.0: 1.1568921748465408\n",
      "Date 2022-02-24: The calculated VIX-equivalent index is 2391.00\n",
      "F: 113.77092219269257, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 8400\n",
      "Contribution to sigma_squared at K=122.0: 0.5675018503980053\n",
      "F: 114.70422231781899, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 25600\n",
      "Contribution to sigma_squared at K=126.0: 1.6347624694883074\n",
      "Date 2022-02-25: The calculated VIX-equivalent index is 2181.36\n",
      "F: 115.64504854977808, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 20000\n",
      "Contribution to sigma_squared at K=122.0: 1.3492250553773395\n",
      "F: 116.59372274702994, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 34000\n",
      "Contribution to sigma_squared at K=128.0: 2.1007828695441706\n",
      "Date 2022-03-02: The calculated VIX-equivalent index is 2328.53\n",
      "F: 115.60321983391243, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 3900\n",
      "Contribution to sigma_squared at K=126.0: 0.24658738849608303\n",
      "F: 116.5515508965127, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 35700\n",
      "Contribution to sigma_squared at K=127.0: 4.480084864020163\n",
      "Date 2022-03-03: The calculated VIX-equivalent index is 2379.06\n",
      "F: 114.87529756394285, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 5000\n",
      "Contribution to sigma_squared at K=125.0: 0.9633672065462077\n",
      "F: 115.81765724182941, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 15900\n",
      "Contribution to sigma_squared at K=127.0: 0.9973748997853058\n",
      "Date 2022-03-04: The calculated VIX-equivalent index is 2586.29\n",
      "F: 111.88689259570647, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 700\n",
      "Contribution to sigma_squared at K=125.0: 0.04491780063354653\n",
      "F: 112.80473740918804, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 19900\n",
      "Contribution to sigma_squared at K=127.0: 2.494389247774609\n",
      "Date 2022-03-07: The calculated VIX-equivalent index is 2709.06\n",
      "F: 111.4633294657046, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 2100\n",
      "Contribution to sigma_squared at K=123.0: 0.13913065261449967\n",
      "F: 112.37769965214957, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 19300\n",
      "Contribution to sigma_squared at K=130.0: 1.1540708756460358\n",
      "Date 2022-03-08: The calculated VIX-equivalent index is 2491.07\n",
      "F: 114.1332152826918, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 1000\n",
      "Contribution to sigma_squared at K=123.0: 0.06623336327631753\n",
      "F: 115.06948741665589, K0: 115.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 6000\n",
      "Contribution to sigma_squared at K=130.0: 1.076021523437528\n",
      "Date 2022-03-09: The calculated VIX-equivalent index is 2320.53\n",
      "F: 111.87616759986906, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 1000\n",
      "Contribution to sigma_squared at K=124.0: 0.19539411462563092\n",
      "F: 112.79392443269826, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 9000\n",
      "Contribution to sigma_squared at K=128.0: 0.5546311923591741\n",
      "Date 2022-03-11: The calculated VIX-equivalent index is 2416.85\n",
      "F: 109.99178826387791, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 500\n",
      "Contribution to sigma_squared at K=120.0: 0.034742490692675626\n",
      "F: 110.89408691603867, K0: 110.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 5500\n",
      "Contribution to sigma_squared at K=130.0: 1.3132201570413056\n",
      "Date 2022-03-14: The calculated VIX-equivalent index is 2772.67\n",
      "F: 108.99109687274283, K0: 108.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=127.0: 500\n",
      "Contribution to sigma_squared at K=127.0: 0.34110019397777\n",
      "F: 109.88518652578011, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 4500\n",
      "Contribution to sigma_squared at K=128.0: 0.27699212349222346\n",
      "Date 2022-03-15: The calculated VIX-equivalent index is 2525.25\n",
      "F: 112.0239216432378, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 17500\n",
      "Contribution to sigma_squared at K=123.0: 2.3324156559949456\n",
      "F: 113.17380827740284, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 96100\n",
      "Contribution to sigma_squared at K=122.0: 6.576381678951845\n",
      "Date 2022-03-16: The calculated VIX-equivalent index is 2352.85\n",
      "F: 113.97067284937265, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 3000\n",
      "Contribution to sigma_squared at K=128.0: 0.18455368577877684\n",
      "F: 115.14054220829095, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 44900\n",
      "Contribution to sigma_squared at K=126.0: 2.8797966119007654\n",
      "Date 2022-03-17: The calculated VIX-equivalent index is 2197.48\n",
      "F: 116.18901990627684, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 7500\n",
      "Contribution to sigma_squared at K=126.0: 0.9520173377362834\n",
      "F: 117.38165982699351, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 60000\n",
      "Contribution to sigma_squared at K=127.0: 3.7868112208785067\n",
      "Date 2022-03-18: The calculated VIX-equivalent index is 2007.93\n",
      "F: 116.93665976230844, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=129.0: 10000\n",
      "Contribution to sigma_squared at K=129.0: 1.2099435464779578\n",
      "F: 118.1369739463879, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 73000\n",
      "Contribution to sigma_squared at K=127.0: 4.603255796044964\n",
      "Date 2022-03-21: The calculated VIX-equivalent index is 1853.19\n",
      "F: 118.02765400983515, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 12800\n",
      "Contribution to sigma_squared at K=126.0: 0.8114405241914976\n",
      "F: 119.23916687081129, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 42000\n",
      "Contribution to sigma_squared at K=130.0: 2.5268854658091935\n",
      "Date 2022-03-22: The calculated VIX-equivalent index is 1972.07\n",
      "F: 118.1792572615433, K0: 118.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=130.0: 6700\n",
      "Contribution to sigma_squared at K=130.0: 0.5983295498228745\n",
      "F: 119.39232627722528, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 47000\n",
      "Contribution to sigma_squared at K=130.0: 2.826880214340999\n",
      "Date 2022-03-23: The calculated VIX-equivalent index is 1801.80\n",
      "F: 119.7496882064442, K0: 119.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=130.0: 9200\n",
      "Contribution to sigma_squared at K=130.0: 0.8213471562180549\n",
      "F: 120.97887715014632, K0: 120.0\n",
      "deltaK: 9.0\n",
      "Q_K at K=140.0: 3300\n",
      "Contribution to sigma_squared at K=140.0: 1.539819843400885\n",
      "Date 2022-03-24: The calculated VIX-equivalent index is 1937.26\n",
      "F: 119.7431295225087, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 8600\n",
      "Contribution to sigma_squared at K=129.0: 0.5196688532868162\n",
      "F: 120.97225114359898, K0: 120.0\n",
      "deltaK: 18.0\n",
      "Q_K at K=150.0: 2000\n",
      "Contribution to sigma_squared at K=150.0: 1.6254095155946064\n",
      "Date 2022-03-25: The calculated VIX-equivalent index is 1915.72\n",
      "F: 119.29340246334881, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 4500\n",
      "Contribution to sigma_squared at K=129.0: 0.2716818300548438\n",
      "F: 120.51790779242961, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 35000\n",
      "Contribution to sigma_squared at K=131.0: 2.0700846827613604\n",
      "Date 2022-03-28: The calculated VIX-equivalent index is 2059.61\n",
      "F: 120.54058864863823, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 4500\n",
      "Contribution to sigma_squared at K=129.0: 0.2716025700710042\n",
      "F: 121.77789591058966, K0: 121.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=140.0: 3500\n",
      "Contribution to sigma_squared at K=140.0: 1.4495656865302973\n",
      "Date 2022-03-29: The calculated VIX-equivalent index is 1995.79\n",
      "F: 120.75201761744432, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 3900\n",
      "Contribution to sigma_squared at K=129.0: 0.23532022211562303\n",
      "Date 2022-03-30: Not enough data to calculate variance.\n",
      "F: 120.45526952799878, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 4000\n",
      "Contribution to sigma_squared at K=128.0: 0.24506844574843586\n",
      "F: 121.69170101882004, K0: 121.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=134.0: 18000\n",
      "Contribution to sigma_squared at K=134.0: 4.066356044071467\n",
      "Date 2022-03-31: The calculated VIX-equivalent index is 1850.76\n",
      "F: 121.99655813010776, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 15900\n",
      "Contribution to sigma_squared at K=126.0: 1.0050245249698644\n",
      "F: 123.24881041292558, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 32500\n",
      "Contribution to sigma_squared at K=132.0: 1.8909989260993318\n",
      "Date 2022-04-01: The calculated VIX-equivalent index is 1755.02\n",
      "F: 121.59841185522795, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 3800\n",
      "Contribution to sigma_squared at K=129.0: 0.22895210732672533\n",
      "F: 122.84657730486575, K0: 122.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 48000\n",
      "Contribution to sigma_squared at K=130.0: 2.8769357301888037\n",
      "Date 2022-04-04: The calculated VIX-equivalent index is 1593.19\n",
      "F: 119.16298139158192, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 500\n",
      "Contribution to sigma_squared at K=128.0: 0.030588896882625987\n",
      "F: 120.38614799367444, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 17000\n",
      "Contribution to sigma_squared at K=132.0: 0.9879841273565402\n",
      "Date 2022-04-05: The calculated VIX-equivalent index is 1911.09\n",
      "F: 118.46947290182159, K0: 118.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=135.0: 1500\n",
      "Contribution to sigma_squared at K=135.0: 0.5773096190166136\n",
      "F: 119.68552088021873, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=140.0: 5000\n",
      "Contribution to sigma_squared at K=140.0: 1.291237490043956\n",
      "Date 2022-04-06: The calculated VIX-equivalent index is 2114.87\n",
      "F: 119.07039237887417, K0: 119.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=130.0: 1500\n",
      "Contribution to sigma_squared at K=130.0: 0.22228229695452106\n",
      "F: 120.2926085869203, K0: 120.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=132.0: 21500\n",
      "Contribution to sigma_squared at K=132.0: 4.9951215381253835\n",
      "Date 2022-04-07: The calculated VIX-equivalent index is 1972.57\n",
      "F: 118.49500681124674, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 100\n",
      "Contribution to sigma_squared at K=126.0: 0.0063080118973790665\n",
      "F: 119.71131688635268, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=140.0: 500\n",
      "Contribution to sigma_squared at K=140.0: 0.12904841931906363\n",
      "Date 2022-04-08: The calculated VIX-equivalent index is 2043.18\n",
      "F: 117.0211191150784, K0: 117.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 500\n",
      "Contribution to sigma_squared at K=130.0: 0.08880920697772704\n",
      "F: 118.22230024506953, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 15500\n",
      "Contribution to sigma_squared at K=132.0: 0.8992334040914921\n",
      "Date 2022-04-11: The calculated VIX-equivalent index is 2150.58\n",
      "F: 116.1807543708972, K0: 116.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=128.0: 100\n",
      "Contribution to sigma_squared at K=128.0: 0.021368538707759326\n",
      "F: 117.373309448765, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 10000\n",
      "Contribution to sigma_squared at K=132.0: 0.5799813311642689\n",
      "Date 2022-04-12: The calculated VIX-equivalent index is 2138.98\n",
      "F: 117.98068624476812, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 30500\n",
      "Contribution to sigma_squared at K=127.0: 1.9104142788210123\n",
      "F: 118.94852044275632, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 22700\n",
      "Contribution to sigma_squared at K=134.0: 1.2876550781469092\n",
      "Date 2022-04-13: The calculated VIX-equivalent index is 1858.30\n",
      "F: 117.33993132358303, K0: 117.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=131.0: 6500\n",
      "Contribution to sigma_squared at K=131.0: 1.1476262125961503\n",
      "F: 118.30250919915954, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 37000\n",
      "Contribution to sigma_squared at K=130.0: 4.4586315082559596\n",
      "Date 2022-04-14: The calculated VIX-equivalent index is 1988.17\n",
      "F: 116.70435470701081, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 2000\n",
      "Contribution to sigma_squared at K=132.0: 0.23158674194421555\n",
      "F: 117.66171873950387, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 35200\n",
      "Contribution to sigma_squared at K=130.0: 2.118388691133342\n",
      "Date 2022-04-18: The calculated VIX-equivalent index is 2018.51\n",
      "F: 116.03435911513074, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 2500\n",
      "Contribution to sigma_squared at K=130.0: 0.29837205465460814\n",
      "F: 116.98622695441657, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 15000\n",
      "Contribution to sigma_squared at K=132.0: 1.7506380514633089\n",
      "Date 2022-04-19: The calculated VIX-equivalent index is 1795.59\n",
      "F: 115.28177946528236, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 7800\n",
      "Contribution to sigma_squared at K=126.0: 0.49533799154963615\n",
      "F: 116.22747364729412, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 15000\n",
      "Contribution to sigma_squared at K=130.0: 2.706587439262658\n",
      "Date 2022-04-20: The calculated VIX-equivalent index is 1839.68\n",
      "F: 111.92338192916579, K0: 111.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.2384887929609662\n",
      "F: 112.84152607659689, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 11000\n",
      "Contribution to sigma_squared at K=132.0: 1.2826779636952386\n",
      "Date 2022-04-22: The calculated VIX-equivalent index is 2060.59\n",
      "F: 111.43025019306712, K0: 111.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=125.0: 9100\n",
      "Contribution to sigma_squared at K=125.0: 0.879482409927126\n",
      "F: 112.344349019408, K0: 112.0\n",
      "deltaK: 18.0\n",
      "Q_K at K=150.0: 1500\n",
      "Contribution to sigma_squared at K=150.0: 1.217990511115464\n",
      "Date 2022-04-25: The calculated VIX-equivalent index is 2394.68\n",
      "F: 108.90973189860064, K0: 108.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=150.0: 100\n",
      "Contribution to sigma_squared at K=150.0: 0.05367679067526756\n",
      "F: 109.80315408811487, K0: 109.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=130.0: 7600\n",
      "Contribution to sigma_squared at K=130.0: 2.737877912073792\n",
      "Date 2022-04-26: The calculated VIX-equivalent index is 2525.11\n",
      "F: 110.02145399016939, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 2000\n",
      "Contribution to sigma_squared at K=128.0: 0.122820582050764\n",
      "F: 110.92399599999594, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 8900\n",
      "Contribution to sigma_squared at K=130.0: 1.068421254308554\n",
      "Date 2022-04-27: The calculated VIX-equivalent index is 2240.55\n",
      "F: 110.56229020755138, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 5000\n",
      "Contribution to sigma_squared at K=123.0: 0.3324253674458863\n",
      "F: 111.46926887394737, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 15900\n",
      "Contribution to sigma_squared at K=130.0: 1.9081957217699237\n",
      "Date 2022-04-28: The calculated VIX-equivalent index is 2148.44\n",
      "F: 108.4758685046982, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 8000\n",
      "Contribution to sigma_squared at K=121.0: 0.549448388011742\n",
      "F: 109.36573157073859, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 26100\n",
      "Contribution to sigma_squared at K=125.0: 1.6934651550051627\n",
      "Date 2022-04-29: The calculated VIX-equivalent index is 2534.35\n",
      "F: 107.13764565637126, K0: 107.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 1000\n",
      "Contribution to sigma_squared at K=125.0: 0.19289844624822\n",
      "F: 108.01653084223172, K0: 108.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=130.0: 5300\n",
      "Contribution to sigma_squared at K=130.0: 2.2236315747917628\n",
      "Date 2022-05-02: The calculated VIX-equivalent index is 2777.02\n",
      "F: 106.99535460033688, K0: 106.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=125.0: 5000\n",
      "Contribution to sigma_squared at K=125.0: 1.446316277936506\n",
      "F: 107.87307252607638, K0: 107.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=127.0: 13000\n",
      "Contribution to sigma_squared at K=127.0: 4.080889385501902\n",
      "Date 2022-05-03: The calculated VIX-equivalent index is 2412.41\n",
      "F: 108.7872219370786, K0: 108.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=125.0: 4000\n",
      "Contribution to sigma_squared at K=125.0: 0.8996675844457873\n",
      "F: 109.67963913726676, K0: 109.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=130.0: 3500\n",
      "Contribution to sigma_squared at K=130.0: 1.677233454523368\n",
      "Date 2022-05-04: The calculated VIX-equivalent index is 2448.42\n",
      "F: 105.70438317710534, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 1000\n",
      "Contribution to sigma_squared at K=120.0: 0.06970835790177732\n",
      "F: 106.57151084157583, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 1500\n",
      "Contribution to sigma_squared at K=130.0: 0.1796511580025389\n",
      "Date 2022-05-05: The calculated VIX-equivalent index is 2791.44\n",
      "F: 105.50349078238517, K0: 105.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 900\n",
      "Contribution to sigma_squared at K=125.0: 0.17340609717831737\n",
      "F: 106.36897046076645, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 10000\n",
      "Contribution to sigma_squared at K=125.0: 1.9425400463260012\n",
      "Date 2022-05-06: The calculated VIX-equivalent index is 2655.19\n",
      "F: 103.52151370021635, K0: 103.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 1900\n",
      "Contribution to sigma_squared at K=119.0: 0.26904823232992275\n",
      "F: 104.3707345716623, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 1000\n",
      "Contribution to sigma_squared at K=129.0: 0.0607448095856916\n",
      "Date 2022-05-09: The calculated VIX-equivalent index is 2790.91\n",
      "F: 103.35090515095561, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 700\n",
      "Contribution to sigma_squared at K=121.0: 0.04792267475820789\n",
      "F: 104.19872646461207, K0: 104.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=121.0: 7000\n",
      "Contribution to sigma_squared at K=121.0: 1.449474004496487\n",
      "Date 2022-05-10: The calculated VIX-equivalent index is 2598.55\n",
      "F: 104.61034499585907, K0: 104.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=125.0: 1500\n",
      "Contribution to sigma_squared at K=125.0: 0.14429441563306677\n",
      "F: 105.46849790692356, K0: 105.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=132.0: 2500\n",
      "Contribution to sigma_squared at K=132.0: 1.4495303210525574\n",
      "Date 2022-05-11: The calculated VIX-equivalent index is 2554.29\n",
      "F: 105.87282781425402, K0: 105.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 2000\n",
      "Contribution to sigma_squared at K=125.0: 0.25644856787841064\n",
      "F: 106.74133728523444, K0: 106.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=126.0: 5200\n",
      "Contribution to sigma_squared at K=126.0: 1.3232158182153382\n",
      "Date 2022-05-12: The calculated VIX-equivalent index is 2505.70\n",
      "F: 107.08028596974881, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 10000\n",
      "Contribution to sigma_squared at K=125.0: 0.6409343800498563\n",
      "F: 107.95870061531946, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 8000\n",
      "Contribution to sigma_squared at K=122.0: 1.0853805674236565\n",
      "Date 2022-05-13: The calculated VIX-equivalent index is 2401.29\n",
      "F: 108.2959189082721, K0: 108.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=125.0: 500\n",
      "Contribution to sigma_squared at K=125.0: 0.08004669855592464\n",
      "F: 109.18430578885467, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 7000\n",
      "Contribution to sigma_squared at K=123.0: 0.4667554323063666\n",
      "Date 2022-05-16: The calculated VIX-equivalent index is 2345.29\n",
      "F: 109.71377219810192, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 3500\n",
      "Contribution to sigma_squared at K=127.0: 0.4376888097915574\n",
      "Date 2022-05-17: Not enough data to calculate variance.\n",
      "F: 107.11873015842902, K0: 107.0\n",
      "deltaK: 5.5\n",
      "Q_K at K=130.0: 7500\n",
      "Contribution to sigma_squared at K=130.0: 2.4608513169168824\n",
      "F: 107.99746017426662, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 52200\n",
      "Contribution to sigma_squared at K=120.0: 3.684718066618413\n",
      "Date 2022-05-18: The calculated VIX-equivalent index is 2441.89\n",
      "F: 107.85154525085088, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 2000\n",
      "Contribution to sigma_squared at K=124.0: 0.26220322474848073\n",
      "F: 108.73628678882673, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 38300\n",
      "Contribution to sigma_squared at K=120.0: 2.702749625991808\n",
      "Date 2022-05-19: The calculated VIX-equivalent index is 2233.62\n",
      "F: 109.31403150759778, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 4500\n",
      "Contribution to sigma_squared at K=125.0: 0.5803863265498074\n",
      "F: 110.21077029917862, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 54600\n",
      "Contribution to sigma_squared at K=120.0: 7.703763849953603\n",
      "Date 2022-05-20: The calculated VIX-equivalent index is 2202.18\n",
      "F: 111.08883665176839, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 10100\n",
      "Contribution to sigma_squared at K=123.0: 1.344174582755575\n",
      "F: 112.00013475104585, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 56700\n",
      "Contribution to sigma_squared at K=121.0: 3.9307459634045268\n",
      "Date 2022-05-23: The calculated VIX-equivalent index is 2053.78\n",
      "F: 111.29291095379475, K0: 111.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.7146318285168758\n",
      "Date 2022-05-24: Not enough data to calculate variance.\n",
      "F: 111.25945653053762, K0: 111.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=130.0: 1100\n",
      "Contribution to sigma_squared at K=130.0: 0.7858656773792979\n",
      "F: 112.17215428054419, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 23500\n",
      "Contribution to sigma_squared at K=125.0: 3.0513150644396743\n",
      "Date 2022-05-25: The calculated VIX-equivalent index is 1941.08\n",
      "F: 112.54473530681828, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 7700\n",
      "Contribution to sigma_squared at K=123.0: 0.511935065866665\n",
      "F: 113.46797661944709, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 37900\n",
      "Contribution to sigma_squared at K=123.0: 5.08090980149687\n",
      "Date 2022-05-26: The calculated VIX-equivalent index is 1910.49\n",
      "F: 112.56398966996048, K0: 112.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.178501638658578\n",
      "F: 113.48738893243433, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 53300\n",
      "Contribution to sigma_squared at K=122.0: 3.630474003823018\n",
      "Date 2022-05-27: The calculated VIX-equivalent index is 1875.06\n",
      "F: 111.55167449302839, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 7700\n",
      "Contribution to sigma_squared at K=122.0: 1.0395097336844472\n",
      "F: 112.46676940265803, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 38500\n",
      "Contribution to sigma_squared at K=123.0: 5.155325954698881\n",
      "Date 2022-05-30: The calculated VIX-equivalent index is 1833.96\n",
      "F: 111.83892720106367, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 1100\n",
      "Contribution to sigma_squared at K=130.0: 0.19612276944405282\n",
      "Date 2022-05-31: Not enough data to calculate variance.\n",
      "F: 111.81576810695069, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=119.0: 10500\n",
      "Contribution to sigma_squared at K=119.0: 0.7445081212643224\n",
      "F: 112.7330294629637, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 62600\n",
      "Contribution to sigma_squared at K=120.0: 13.20247292320277\n",
      "Date 2022-06-01: The calculated VIX-equivalent index is 1750.58\n",
      "F: 112.82004282099234, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 4500\n",
      "Contribution to sigma_squared at K=122.0: 0.6069741456644947\n",
      "F: 113.74554257129992, K0: 112.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=130.0: 3000\n",
      "Contribution to sigma_squared at K=130.0: 1.796511580025389\n",
      "Date 2022-06-02: The calculated VIX-equivalent index is 1768.39\n",
      "F: 111.49201214500297, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 2400\n",
      "Contribution to sigma_squared at K=121.0: 0.16449819113213024\n",
      "F: 112.40661762485739, K0: 112.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 12000\n",
      "Contribution to sigma_squared at K=125.0: 3.8850800926520024\n",
      "Date 2022-06-03: The calculated VIX-equivalent index is 1817.11\n",
      "F: 110.47564147334602, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 7800\n",
      "Contribution to sigma_squared at K=118.0: 0.5616568465766697\n",
      "F: 111.38190933180516, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 16600\n",
      "Contribution to sigma_squared at K=122.0: 1.1273973828834454\n",
      "Date 2022-06-06: The calculated VIX-equivalent index is 1825.35\n",
      "F: 110.32699006272766, K0: 110.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=126.0: 1500\n",
      "Contribution to sigma_squared at K=126.0: 0.37881215912694194\n",
      "F: 111.23203848499472, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 5000\n",
      "Contribution to sigma_squared at K=125.0: 0.6467580617091981\n",
      "Date 2022-06-07: The calculated VIX-equivalent index is 1758.58\n",
      "F: 108.58923344560431, K0: 108.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 500\n",
      "Contribution to sigma_squared at K=122.0: 0.13464721217514217\n",
      "F: 109.48002648137239, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 13000\n",
      "Contribution to sigma_squared at K=124.0: 1.7083039130190265\n",
      "Date 2022-06-08: The calculated VIX-equivalent index is 2042.76\n",
      "F: 107.281361555804, K0: 107.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=120.0: 100\n",
      "Contribution to sigma_squared at K=120.0: 0.010434918940365018\n",
      "F: 108.16142569024234, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 4500\n",
      "Contribution to sigma_squared at K=128.0: 0.8321895700742884\n",
      "Date 2022-06-09: The calculated VIX-equivalent index is 2113.74\n",
      "F: 105.6352293077286, K0: 105.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=126.0: 100\n",
      "Contribution to sigma_squared at K=126.0: 0.025232047589516266\n",
      "F: 106.50178968036654, K0: 106.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 3000\n",
      "Contribution to sigma_squared at K=125.0: 0.19385765238640446\n",
      "Date 2022-06-10: The calculated VIX-equivalent index is 2059.98\n",
      "F: 102.6580698355812, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 100\n",
      "Contribution to sigma_squared at K=120.0: 0.01389699627707025\n",
      "F: 103.50020759430052, K0: 103.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 4000\n",
      "Contribution to sigma_squared at K=125.0: 1.291253565323524\n",
      "Date 2022-06-13: The calculated VIX-equivalent index is 2583.83\n",
      "F: 102.09303444402606, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 1000\n",
      "Contribution to sigma_squared at K=123.0: 0.13223502193060774\n",
      "F: 102.93053703242703, K0: 102.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=124.0: 3000\n",
      "Contribution to sigma_squared at K=124.0: 0.8854524488742045\n",
      "Date 2022-06-14: The calculated VIX-equivalent index is 2574.26\n",
      "F: 103.65017800502117, K0: 103.0\n",
      "deltaK: 5.5\n",
      "Q_K at K=124.0: 21200\n",
      "Contribution to sigma_squared at K=124.0: 7.645454472988038\n",
      "F: 104.7141110701068, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 35000\n",
      "Contribution to sigma_squared at K=120.0: 2.4756476701303427\n",
      "Date 2022-06-15: The calculated VIX-equivalent index is 2283.88\n",
      "F: 100.5851219178037, K0: 100.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=118.0: 3500\n",
      "Contribution to sigma_squared at K=118.0: 0.506557458476054\n",
      "F: 101.61759324707468, K0: 101.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=121.0: 14000\n",
      "Contribution to sigma_squared at K=121.0: 2.920171759243536\n",
      "Date 2022-06-17: The calculated VIX-equivalent index is 2588.27\n",
      "F: 100.5250307340408, K0: 100.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=130.0: 500\n",
      "Contribution to sigma_squared at K=130.0: 0.3574201874012964\n",
      "F: 101.55688524818851, K0: 101.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=136.0: 4000\n",
      "Contribution to sigma_squared at K=136.0: 2.4194940041193695\n",
      "Date 2022-06-20: The calculated VIX-equivalent index is 2565.78\n",
      "F: 100.32645075128829, K0: 100.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 1600\n",
      "Contribution to sigma_squared at K=115.0: 0.12176209604975627\n",
      "F: 101.35626691090752, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 9000\n",
      "Contribution to sigma_squared at K=121.0: 0.6250211886216112\n",
      "Date 2022-06-21: The calculated VIX-equivalent index is 2330.81\n",
      "F: 100.13400489527207, K0: 100.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=118.0: 3000\n",
      "Contribution to sigma_squared at K=118.0: 0.8671182489168561\n",
      "F: 101.1618456650425, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=114.0: 35400\n",
      "Contribution to sigma_squared at K=114.0: 2.7687886895340066\n",
      "Date 2022-06-22: The calculated VIX-equivalent index is 2238.49\n",
      "F: 98.65437253219629, K0: 98.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=115.0: 400\n",
      "Contribution to sigma_squared at K=115.0: 0.1521138263618545\n",
      "F: 99.66702538984205, K0: 99.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=124.0: 29000\n",
      "Contribution to sigma_squared at K=124.0: 9.58283843233172\n",
      "Date 2022-06-23: The calculated VIX-equivalent index is 2330.25\n",
      "F: 99.22080189748496, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=116.0: 100\n",
      "Contribution to sigma_squared at K=116.0: 0.014945886312574158\n",
      "F: 100.23926895576565, K0: 100.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 11000\n",
      "Contribution to sigma_squared at K=120.0: 2.3280605041068583\n",
      "Date 2022-06-24: The calculated VIX-equivalent index is 2327.85\n",
      "F: 101.23511394988095, K0: 101.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=115.0: 1500\n",
      "Contribution to sigma_squared at K=115.0: 0.5697614787577387\n",
      "F: 102.2742572215285, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 24400\n",
      "Contribution to sigma_squared at K=115.0: 1.8726508173419862\n",
      "Date 2022-06-27: The calculated VIX-equivalent index is 2264.31\n",
      "F: 101.0326345163785, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=111.0: 400\n",
      "Contribution to sigma_squared at K=111.0: 0.03260729824275866\n",
      "F: 102.06969940699044, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 21000\n",
      "Contribution to sigma_squared at K=115.0: 1.611237473874886\n",
      "Date 2022-06-28: The calculated VIX-equivalent index is 2235.25\n",
      "F: 100.02935963981335, K0: 100.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=115.0: 500\n",
      "Contribution to sigma_squared at K=115.0: 0.1898096949360711\n",
      "F: 101.05612626239436, K0: 101.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 20000\n",
      "Contribution to sigma_squared at K=123.0: 4.023002002512007\n",
      "Date 2022-06-29: The calculated VIX-equivalent index is 2206.65\n",
      "F: 98.91644427272225, K0: 98.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=119.0: 4500\n",
      "Contribution to sigma_squared at K=119.0: 1.4354182023980133\n",
      "F: 99.93178720573053, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 20800\n",
      "Contribution to sigma_squared at K=120.0: 2.929633823010847\n",
      "Date 2022-06-30: The calculated VIX-equivalent index is 2381.38\n",
      "F: 99.3009814790133, K0: 99.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=124.0: 100\n",
      "Contribution to sigma_squared at K=124.0: 0.04568517525840767\n",
      "F: 100.32027155284085, K0: 100.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=122.0: 17500\n",
      "Contribution to sigma_squared at K=122.0: 5.3639742551794125\n",
      "Date 2022-07-01: The calculated VIX-equivalent index is 2319.71\n",
      "F: 98.86804960717048, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 100\n",
      "Contribution to sigma_squared at K=125.0: 0.006416828661935218\n",
      "F: 99.88289578575106, K0: 99.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=123.0: 6000\n",
      "Contribution to sigma_squared at K=123.0: 2.008568553778785\n",
      "Date 2022-07-04: The calculated VIX-equivalent index is 2407.10\n",
      "F: 98.52435192462848, K0: 98.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 100\n",
      "Contribution to sigma_squared at K=124.0: 0.01955652262714402\n",
      "F: 99.53567016591182, K0: 99.0\n",
      "deltaK: 37.0\n",
      "Q_K at K=150.0: 1000\n",
      "Contribution to sigma_squared at K=150.0: 1.6652065649600867\n",
      "Date 2022-07-05: The calculated VIX-equivalent index is 2541.60\n",
      "F: 98.92081618744726, K0: 98.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=124.0: 100\n",
      "Contribution to sigma_squared at K=124.0: 0.039101634482599165\n",
      "F: 99.9362039966412, K0: 99.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 3000\n",
      "Contribution to sigma_squared at K=120.0: 0.21090212337384615\n",
      "Date 2022-07-06: The calculated VIX-equivalent index is 2276.81\n",
      "F: 100.90622045622382, K0: 100.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 100\n",
      "Contribution to sigma_squared at K=120.0: 0.020869837880730036\n",
      "F: 101.94198775042946, K0: 101.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=122.0: 7600\n",
      "Contribution to sigma_squared at K=122.0: 1.8086621331286694\n",
      "Date 2022-07-07: The calculated VIX-equivalent index is 2320.32\n",
      "F: 100.43535872618318, K0: 100.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=117.0: 300\n",
      "Contribution to sigma_squared at K=117.0: 0.08778960936470746\n",
      "F: 101.4662927883258, K0: 101.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 22600\n",
      "Contribution to sigma_squared at K=122.0: 4.608703667420513\n",
      "Date 2022-07-08: The calculated VIX-equivalent index is 2209.13\n",
      "F: 98.2697897506976, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=119.0: 500\n",
      "Contribution to sigma_squared at K=119.0: 0.035328851491739914\n",
      "F: 99.27849499971042, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 4500\n",
      "Contribution to sigma_squared at K=120.0: 0.6317839851971838\n",
      "Date 2022-07-11: The calculated VIX-equivalent index is 2344.15\n",
      "F: 98.29988783804278, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 1300\n",
      "Contribution to sigma_squared at K=124.0: 0.08457201940766824\n",
      "F: 99.30890203346496, K0: 99.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=124.0: 4000\n",
      "Contribution to sigma_squared at K=124.0: 1.183017071121956\n",
      "Date 2022-07-12: The calculated VIX-equivalent index is 2328.35\n",
      "F: 98.88587609964713, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 3000\n",
      "Contribution to sigma_squared at K=118.0: 0.21766690302229036\n",
      "F: 99.69706931807535, K0: 99.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 35800\n",
      "Contribution to sigma_squared at K=115.0: 2.7572149865635307\n",
      "Date 2022-07-13: The calculated VIX-equivalent index is 2236.42\n",
      "F: 97.0791671570434, K0: 97.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=113.0: 10000\n",
      "Contribution to sigma_squared at K=113.0: 0.7909545929288897\n",
      "F: 97.87553935047065, K0: 97.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=116.0: 16700\n",
      "Contribution to sigma_squared at K=116.0: 2.527476079343846\n",
      "Date 2022-07-14: The calculated VIX-equivalent index is 2229.91\n",
      "F: 97.48515726854029, K0: 97.0\n",
      "deltaK: 6.5\n",
      "Q_K at K=128.0: 11100\n",
      "Contribution to sigma_squared at K=128.0: 4.446293392079379\n",
      "F: 98.28485993177965, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 31200\n",
      "Contribution to sigma_squared at K=112.0: 2.531910766454536\n",
      "Date 2022-07-15: The calculated VIX-equivalent index is 2070.83\n",
      "F: 97.76820187488917, K0: 97.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=123.0: 14000\n",
      "Contribution to sigma_squared at K=123.0: 3.2672880261445667\n",
      "F: 98.57022644570766, K0: 98.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=111.0: 50500\n",
      "Contribution to sigma_squared at K=111.0: 4.168646906537413\n",
      "Date 2022-07-18: The calculated VIX-equivalent index is 2079.15\n",
      "F: 99.07963958274293, K0: 99.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=108.0: 20100\n",
      "Contribution to sigma_squared at K=108.0: 1.737894431509325\n",
      "F: 99.89242230646417, K0: 99.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=113.0: 29900\n",
      "Contribution to sigma_squared at K=113.0: 2.3808787180411706\n",
      "Date 2022-07-19: The calculated VIX-equivalent index is 2066.63\n",
      "F: 99.09310904713573, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=112.0: 10000\n",
      "Contribution to sigma_squared at K=112.0: 1.6074670398846362\n",
      "F: 99.90600226528349, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=115.0: 26100\n",
      "Contribution to sigma_squared at K=115.0: 4.012093773860503\n",
      "Date 2022-07-20: The calculated VIX-equivalent index is 2061.52\n",
      "F: 99.81644274541193, K0: 99.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=114.0: 2000\n",
      "Contribution to sigma_squared at K=114.0: 0.31022135916686977\n",
      "F: 100.63526970671742, K0: 100.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=113.0: 41200\n",
      "Contribution to sigma_squared at K=113.0: 3.27876177374835\n",
      "Date 2022-07-21: The calculated VIX-equivalent index is 2066.51\n",
      "F: 99.67814736875161, K0: 99.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=116.0: 3000\n",
      "Contribution to sigma_squared at K=116.0: 0.8985866381629747\n",
      "F: 100.49583984780229, K0: 100.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=114.0: 36600\n",
      "Contribution to sigma_squared at K=114.0: 5.721951780428842\n",
      "Date 2022-07-22: The calculated VIX-equivalent index is 2052.34\n",
      "F: 100.945019827188, K0: 100.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 3000\n",
      "Contribution to sigma_squared at K=115.0: 0.22837055452105515\n",
      "F: 101.77310487580911, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 30800\n",
      "Contribution to sigma_squared at K=115.0: 2.363837916972671\n",
      "Date 2022-07-25: The calculated VIX-equivalent index is 2124.93\n",
      "F: 100.41420223964411, K0: 100.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=122.0: 10500\n",
      "Contribution to sigma_squared at K=122.0: 1.0649977994013673\n",
      "F: 101.2379328177966, K0: 101.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=115.0: 27000\n",
      "Contribution to sigma_squared at K=115.0: 8.286364151356558\n",
      "Date 2022-07-26: The calculated VIX-equivalent index is 2073.97\n",
      "F: 102.06141881747142, K0: 102.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=120.0: 1000\n",
      "Contribution to sigma_squared at K=120.0: 0.6987126445554573\n",
      "F: 102.89866205253628, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 22100\n",
      "Contribution to sigma_squared at K=115.0: 1.695140945484173\n",
      "Date 2022-07-27: The calculated VIX-equivalent index is 2001.52\n",
      "F: 103.19712509356191, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 5600\n",
      "Contribution to sigma_squared at K=112.0: 0.4490413735793584\n",
      "F: 104.04368489905755, K0: 104.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=115.0: 27500\n",
      "Contribution to sigma_squared at K=115.0: 6.3261687177128225\n",
      "Date 2022-07-28: The calculated VIX-equivalent index is 2000.29\n",
      "F: 103.73820635410043, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 9900\n",
      "Contribution to sigma_squared at K=112.0: 0.7936094059302372\n",
      "F: 104.58920482633475, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=113.0: 65600\n",
      "Contribution to sigma_squared at K=113.0: 5.2083808813799575\n",
      "Date 2022-07-29: The calculated VIX-equivalent index is 1884.92\n",
      "F: 102.70343281041661, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=110.0: 9500\n",
      "Contribution to sigma_squared at K=110.0: 0.7887978819551008\n",
      "F: 103.54594269647104, K0: 103.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=115.0: 31500\n",
      "Contribution to sigma_squared at K=115.0: 7.237886275831803\n",
      "Date 2022-08-01: The calculated VIX-equivalent index is 2077.61\n",
      "F: 103.81507585082622, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 3600\n",
      "Contribution to sigma_squared at K=112.0: 0.2882486204433406\n",
      "F: 104.66670490871047, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 31400\n",
      "Contribution to sigma_squared at K=115.0: 2.4042679980469033\n",
      "Date 2022-08-02: The calculated VIX-equivalent index is 2051.06\n",
      "F: 104.19945946677963, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=110.0: 10500\n",
      "Contribution to sigma_squared at K=110.0: 0.8713206202664522\n",
      "F: 105.05424174931872, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=113.0: 48500\n",
      "Contribution to sigma_squared at K=113.0: 3.8450947076068114\n",
      "Date 2022-08-03: The calculated VIX-equivalent index is 2000.58\n",
      "F: 106.29464789914188, K0: 106.0\n",
      "deltaK: 7.5\n",
      "Q_K at K=128.0: 5000\n",
      "Contribution to sigma_squared at K=128.0: 2.2975166788915864\n",
      "F: 107.16661769838913, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 56500\n",
      "Contribution to sigma_squared at K=115.0: 4.323627176275344\n",
      "Date 2022-08-04: The calculated VIX-equivalent index is 1969.93\n",
      "F: 106.84537098542843, K0: 106.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 2500\n",
      "Contribution to sigma_squared at K=115.0: 0.18969896159148697\n",
      "F: 107.72185854646784, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 31400\n",
      "Contribution to sigma_squared at K=118.0: 2.281573087782951\n",
      "Date 2022-08-05: The calculated VIX-equivalent index is 2019.72\n",
      "F: 108.6873114304438, K0: 108.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=122.0: 9000\n",
      "Contribution to sigma_squared at K=122.0: 2.121931508362161\n",
      "F: 109.57890903203379, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 18000\n",
      "Contribution to sigma_squared at K=123.0: 3.6080465543682116\n",
      "Date 2022-08-08: The calculated VIX-equivalent index is 2189.10\n",
      "F: 108.90496457569206, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 1000\n",
      "Contribution to sigma_squared at K=123.0: 0.19875807516357097\n",
      "F: 109.79834765729558, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 20000\n",
      "Contribution to sigma_squared at K=123.0: 4.007771054612818\n",
      "Date 2022-08-09: The calculated VIX-equivalent index is 2178.23\n",
      "F: 110.4611428546319, K0: 110.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=119.0: 6000\n",
      "Contribution to sigma_squared at K=119.0: 0.6368477492455811\n",
      "F: 111.36729177617467, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 14000\n",
      "Contribution to sigma_squared at K=124.0: 0.9198559531640912\n",
      "Date 2022-08-10: The calculated VIX-equivalent index is 2216.30\n",
      "F: 109.91018977956792, K0: 109.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=129.0: 1000\n",
      "Contribution to sigma_squared at K=129.0: 0.3611870265999789\n",
      "F: 110.81181905264526, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 9500\n",
      "Contribution to sigma_squared at K=125.0: 1.2281234223684536\n",
      "Date 2022-08-11: The calculated VIX-equivalent index is 2118.43\n",
      "F: 112.92889230450126, K0: 112.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=122.0: 2900\n",
      "Contribution to sigma_squared at K=122.0: 0.4878113930396586\n",
      "F: 113.85528498276109, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 6900\n",
      "Contribution to sigma_squared at K=128.0: 1.2756517424261005\n",
      "Date 2022-08-12: The calculated VIX-equivalent index is 2109.75\n",
      "F: 113.09796037799128, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=129.0: 1000\n",
      "Contribution to sigma_squared at K=129.0: 0.3006381022622012\n",
      "F: 114.02573997701346, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 9500\n",
      "Contribution to sigma_squared at K=128.0: 1.1698635931561925\n",
      "Date 2022-08-15: The calculated VIX-equivalent index is 2261.62\n",
      "F: 114.47695652675111, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 8500\n",
      "Contribution to sigma_squared at K=128.0: 1.5696220331225998\n",
      "F: 115.44972958568628, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 50000\n",
      "Contribution to sigma_squared at K=130.0: 6.0181496907197225\n",
      "Date 2022-08-16: The calculated VIX-equivalent index is 2205.66\n",
      "F: 114.64054198497945, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 5500\n",
      "Contribution to sigma_squared at K=128.0: 1.0153414857396317\n",
      "F: 115.61470511866352, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 36000\n",
      "Contribution to sigma_squared at K=132.0: 4.201531323511941\n",
      "Date 2022-08-17: The calculated VIX-equivalent index is 2158.82\n",
      "F: 114.71303828854523, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 5500\n",
      "Contribution to sigma_squared at K=128.0: 1.0150452717832725\n",
      "F: 115.68781746281181, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 64500\n",
      "Contribution to sigma_squared at K=128.0: 4.0016216880537385\n",
      "Date 2022-08-18: The calculated VIX-equivalent index is 2069.04\n",
      "F: 112.34527039257969, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 10200\n",
      "Contribution to sigma_squared at K=124.0: 0.6684231615929267\n",
      "F: 113.29992935323392, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 75500\n",
      "Contribution to sigma_squared at K=126.0: 9.665078619675507\n",
      "Date 2022-08-19: The calculated VIX-equivalent index is 2237.30\n",
      "F: 111.24458839586158, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 5500\n",
      "Contribution to sigma_squared at K=125.0: 1.063110605406416\n",
      "F: 112.18989426201237, K0: 112.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 41800\n",
      "Contribution to sigma_squared at K=128.0: 7.7708222470470885\n",
      "Date 2022-08-22: The calculated VIX-equivalent index is 2390.69\n",
      "F: 113.5838799922076, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 15000\n",
      "Contribution to sigma_squared at K=123.0: 0.9978582442606253\n",
      "F: 114.54906409334087, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 80000\n",
      "Contribution to sigma_squared at K=126.0: 5.114598602147746\n",
      "Date 2022-08-23: The calculated VIX-equivalent index is 2275.81\n",
      "F: 113.59173362543842, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 27900\n",
      "Contribution to sigma_squared at K=122.0: 1.886017146443164\n",
      "F: 114.55698446317136, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 46100\n",
      "Contribution to sigma_squared at K=130.0: 5.535797006429904\n",
      "Date 2022-08-24: The calculated VIX-equivalent index is 2361.45\n",
      "F: 114.19618446572476, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 24100\n",
      "Contribution to sigma_squared at K=122.0: 1.6286649765727013\n",
      "F: 115.16657165151167, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 39800\n",
      "Contribution to sigma_squared at K=130.0: 4.7778838114022975\n",
      "Date 2022-08-25: The calculated VIX-equivalent index is 2352.65\n",
      "F: 112.92315531612836, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 6600\n",
      "Contribution to sigma_squared at K=124.0: 0.8632532421079515\n",
      "F: 113.88272487977073, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 37000\n",
      "Contribution to sigma_squared at K=130.0: 4.440455453175294\n",
      "Date 2022-08-26: The calculated VIX-equivalent index is 2404.18\n",
      "F: 112.84872565496022, K0: 112.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=128.0: 3500\n",
      "Contribution to sigma_squared at K=128.0: 1.2877360570311929\n",
      "F: 113.80766274922738, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 32500\n",
      "Contribution to sigma_squared at K=130.0: 3.8969873682704037\n",
      "Date 2022-08-29: The calculated VIX-equivalent index is 2521.82\n",
      "F: 110.91502237149044, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 12000\n",
      "Contribution to sigma_squared at K=120.0: 1.6739771735376228\n",
      "F: 111.85752773560678, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 29000\n",
      "Contribution to sigma_squared at K=130.0: 3.476297340644804\n",
      "Date 2022-08-30: The calculated VIX-equivalent index is 2595.67\n",
      "F: 109.97118849458239, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 6100\n",
      "Contribution to sigma_squared at K=122.0: 0.8230272837801771\n",
      "F: 110.9056735881096, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 38500\n",
      "Contribution to sigma_squared at K=128.0: 7.1385655759904605\n",
      "Date 2022-08-31: The calculated VIX-equivalent index is 2637.87\n",
      "F: 110.82487919980456, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 4100\n",
      "Contribution to sigma_squared at K=120.0: 0.571608534794574\n",
      "F: 111.76661856828717, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 12900\n",
      "Contribution to sigma_squared at K=130.0: 1.5454508259536748\n",
      "Date 2022-09-01: The calculated VIX-equivalent index is 2657.17\n",
      "F: 111.25309707777953, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 5300\n",
      "Contribution to sigma_squared at K=122.0: 0.7146721024107123\n",
      "F: 112.19847524683553, K0: 112.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 20200\n",
      "Contribution to sigma_squared at K=130.0: 6.048255652752143\n",
      "Date 2022-09-02: The calculated VIX-equivalent index is 2619.32\n",
      "F: 112.49838628830453, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 2700\n",
      "Contribution to sigma_squared at K=122.0: 0.363759687147799\n",
      "F: 113.45434635813196, K0: 113.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 23000\n",
      "Contribution to sigma_squared at K=130.0: 5.50448176265605\n",
      "Date 2022-09-05: The calculated VIX-equivalent index is 2626.74\n",
      "F: 110.02028497234414, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 3700\n",
      "Contribution to sigma_squared at K=120.0: 0.2575449166864296\n",
      "F: 110.95518726538734, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 11500\n",
      "Contribution to sigma_squared at K=130.0: 1.3757189736838085\n",
      "Date 2022-09-06: The calculated VIX-equivalent index is 2823.22\n",
      "F: 110.10823619312089, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 100\n",
      "Contribution to sigma_squared at K=123.0: 0.006621404047029159\n",
      "F: 111.04388585559691, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 8500\n",
      "Contribution to sigma_squared at K=130.0: 1.016242549913221\n",
      "Date 2022-09-08: The calculated VIX-equivalent index is 2828.29\n",
      "F: 112.46436509796044, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 1000\n",
      "Contribution to sigma_squared at K=125.0: 0.06409343800498563\n",
      "F: 113.42003607120108, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=131.0: 16000\n",
      "Contribution to sigma_squared at K=131.0: 1.8832840411834262\n",
      "Date 2022-09-09: The calculated VIX-equivalent index is 2772.23\n",
      "F: 113.47274902646745, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 100\n",
      "Contribution to sigma_squared at K=126.0: 0.006302492642662246\n",
      "F: 114.43698878724815, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 18000\n",
      "Contribution to sigma_squared at K=132.0: 1.0424444596797335\n",
      "Date 2022-09-12: The calculated VIX-equivalent index is 2799.78\n",
      "F: 110.82629226945103, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 1000\n",
      "Contribution to sigma_squared at K=117.0: 0.07307267319702553\n",
      "F: 111.76804364555618, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 15000\n",
      "Contribution to sigma_squared at K=132.0: 1.7369005645816167\n",
      "Date 2022-09-13: The calculated VIX-equivalent index is 2797.42\n",
      "F: 111.48604527336225, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 13700\n",
      "Contribution to sigma_squared at K=128.0: 1.6865742630415386\n",
      "F: 112.59755219362336, K0: 112.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 32700\n",
      "Contribution to sigma_squared at K=138.0: 13.991454075205999\n",
      "Date 2022-09-14: The calculated VIX-equivalent index is 2702.48\n",
      "F: 110.8556357914951, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 3400\n",
      "Contribution to sigma_squared at K=130.0: 0.4056676110311467\n",
      "F: 111.96085757983701, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 72400\n",
      "Contribution to sigma_squared at K=130.0: 4.362228664834208\n",
      "Date 2022-09-15: The calculated VIX-equivalent index is 2587.21\n",
      "F: 112.60971183844262, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 48500\n",
      "Contribution to sigma_squared at K=122.0: 3.281431391946913\n",
      "F: 113.73242162413939, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 73000\n",
      "Contribution to sigma_squared at K=130.0: 4.393249274225398\n",
      "Date 2022-09-19: The calculated VIX-equivalent index is 2562.77\n",
      "F: 113.27454574674171, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 4500\n",
      "Contribution to sigma_squared at K=130.0: 1.3403257027548614\n",
      "F: 114.40388387312532, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 62100\n",
      "Contribution to sigma_squared at K=130.0: 3.7361806530178794\n",
      "Date 2022-09-20: The calculated VIX-equivalent index is 2553.32\n",
      "F: 112.65670736767603, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 21100\n",
      "Contribution to sigma_squared at K=125.0: 2.7181926797955493\n",
      "F: 113.77988569502604, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 70800\n",
      "Contribution to sigma_squared at K=130.0: 4.258364237773249\n",
      "Date 2022-09-21: The calculated VIX-equivalent index is 2602.70\n",
      "F: 114.77158091497499, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 5100\n",
      "Contribution to sigma_squared at K=130.0: 0.6072598416112757\n",
      "F: 115.91584436179023, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 81500\n",
      "Contribution to sigma_squared at K=130.0: 4.900500503752662\n",
      "Date 2022-09-22: The calculated VIX-equivalent index is 2568.53\n",
      "F: 112.3698376433732, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 300\n",
      "Contribution to sigma_squared at K=126.0: 0.019007042267909353\n",
      "F: 113.4901559026044, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 60000\n",
      "Contribution to sigma_squared at K=130.0: 3.6066779192188014\n",
      "Date 2022-09-23: The calculated VIX-equivalent index is 2730.26\n",
      "F: 109.65674068984215, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 28700\n",
      "Contribution to sigma_squared at K=123.0: 1.906452080076532\n",
      "F: 110.75000959027878, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 39300\n",
      "Contribution to sigma_squared at K=130.0: 2.3603070555639913\n",
      "Date 2022-09-26: The calculated VIX-equivalent index is 2896.00\n",
      "F: 108.88348710965249, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 10000\n",
      "Contribution to sigma_squared at K=126.0: 1.898487164668958\n",
      "F: 109.96904673397846, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 32000\n",
      "Contribution to sigma_squared at K=130.0: 1.9213178330342402\n",
      "Date 2022-09-27: The calculated VIX-equivalent index is 2980.66\n",
      "F: 108.92689994565805, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 600\n",
      "Contribution to sigma_squared at K=123.0: 0.03983288931677864\n",
      "F: 110.0128923924734, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 70000\n",
      "Contribution to sigma_squared at K=126.0: 4.472662940623468\n",
      "Date 2022-09-28: The calculated VIX-equivalent index is 3068.64\n",
      "F: 108.10505099935915, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 16700\n",
      "Contribution to sigma_squared at K=122.0: 2.253205842480157\n",
      "F: 109.18284967816543, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 31200\n",
      "Contribution to sigma_squared at K=129.0: 5.703992300075202\n",
      "Date 2022-09-29: The calculated VIX-equivalent index is 3125.76\n",
      "F: 110.45496873143102, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 8000\n",
      "Contribution to sigma_squared at K=126.0: 0.5058202840945294\n",
      "F: 111.55619590135329, K0: 111.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 20400\n",
      "Contribution to sigma_squared at K=138.0: 8.687959050392607\n",
      "Date 2022-09-30: The calculated VIX-equivalent index is 3109.63\n",
      "F: 116.47381292453433, K0: 116.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.29672250567005315\n",
      "F: 117.63504748781423, K0: 117.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 17000\n",
      "Contribution to sigma_squared at K=138.0: 7.2336311986561235\n",
      "Date 2022-10-03: The calculated VIX-equivalent index is 2609.55\n",
      "F: 116.53574459315155, K0: 116.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=133.0: 100\n",
      "Contribution to sigma_squared at K=133.0: 0.02834047934952168\n",
      "F: 117.69759661019513, K0: 117.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 11000\n",
      "Contribution to sigma_squared at K=138.0: 4.679219387564745\n",
      "Date 2022-10-04: The calculated VIX-equivalent index is 2582.73\n",
      "F: 117.47170814684567, K0: 117.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=133.0: 3400\n",
      "Contribution to sigma_squared at K=133.0: 0.96329518581311\n",
      "F: 118.6428916453719, K0: 118.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=145.0: 5500\n",
      "Contribution to sigma_squared at K=145.0: 1.8537318620445549\n",
      "Date 2022-10-05: The calculated VIX-equivalent index is 2434.32\n",
      "F: 117.80118934852987, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 100\n",
      "Contribution to sigma_squared at K=133.0: 0.0056647891514919335\n",
      "F: 118.97565774818317, K0: 118.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 8000\n",
      "Contribution to sigma_squared at K=145.0: 1.1552359839212014\n",
      "Date 2022-10-06: The calculated VIX-equivalent index is 2352.59\n",
      "F: 116.57916483981252, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.017782583756361686\n",
      "F: 117.74144975322913, K0: 117.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 9500\n",
      "Contribution to sigma_squared at K=138.0: 4.037608179325293\n",
      "Date 2022-10-07: The calculated VIX-equivalent index is 2491.52\n",
      "F: 116.04217219693741, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=132.0: 100\n",
      "Contribution to sigma_squared at K=132.0: 0.017232708775650463\n",
      "F: 117.19910333681922, K0: 117.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=142.0: 6500\n",
      "Contribution to sigma_squared at K=142.0: 1.3034226236958364\n",
      "Date 2022-10-10: The calculated VIX-equivalent index is 2619.12\n",
      "F: 114.89414825856231, K0: 114.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.023682455194060544\n",
      "F: 116.03963369195233, K0: 116.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 9000\n",
      "Contribution to sigma_squared at K=138.0: 3.8206407237074558\n",
      "Date 2022-10-11: The calculated VIX-equivalent index is 2700.49\n",
      "F: 115.43965272024856, K0: 115.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=142.0: 3900\n",
      "Contribution to sigma_squared at K=142.0: 0.7813693090403704\n",
      "F: 116.38664198826098, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 23400\n",
      "Contribution to sigma_squared at K=136.0: 1.288233552510186\n",
      "Date 2022-10-13: The calculated VIX-equivalent index is 2727.90\n",
      "F: 113.15667046797358, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 12900\n",
      "Contribution to sigma_squared at K=135.0: 3.5733363565738134\n",
      "F: 114.08493168508649, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 25000\n",
      "Contribution to sigma_squared at K=138.0: 2.6726474734627454\n",
      "Date 2022-10-14: The calculated VIX-equivalent index is 2784.90\n",
      "F: 114.62294475097559, K0: 114.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=135.0: 10300\n",
      "Contribution to sigma_squared at K=135.0: 3.4207591879712695\n",
      "F: 115.56323429611311, K0: 115.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 50000\n",
      "Contribution to sigma_squared at K=135.0: 8.370924261165705\n",
      "Date 2022-10-17: The calculated VIX-equivalent index is 2688.89\n",
      "F: 116.72660191481062, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 25200\n",
      "Contribution to sigma_squared at K=130.0: 1.503795155459225\n",
      "F: 117.68414844843335, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 43800\n",
      "Contribution to sigma_squared at K=135.0: 2.4435967855526575\n",
      "Date 2022-10-18: The calculated VIX-equivalent index is 2704.26\n",
      "F: 117.22807566072517, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 40000\n",
      "Contribution to sigma_squared at K=130.0: 2.3862800648890983\n",
      "F: 118.18973594767597, K0: 118.0\n",
      "deltaK: 9.0\n",
      "Q_K at K=145.0: 5700\n",
      "Contribution to sigma_squared at K=145.0: 2.480148090598543\n",
      "Date 2022-10-19: The calculated VIX-equivalent index is 2805.29\n",
      "F: 118.09783926669583, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 52600\n",
      "Contribution to sigma_squared at K=130.0: 3.137042822845219\n",
      "F: 119.06663450928062, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 27200\n",
      "Contribution to sigma_squared at K=138.0: 1.4513770960919843\n",
      "Date 2022-10-20: The calculated VIX-equivalent index is 2856.48\n",
      "F: 120.84206575635984, K0: 120.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=142.0: 3900\n",
      "Contribution to sigma_squared at K=142.0: 1.3642081730857096\n",
      "F: 121.83337278734204, K0: 121.0\n",
      "deltaK: 19.0\n",
      "Q_K at K=158.0: 5500\n",
      "Contribution to sigma_squared at K=158.0: 4.252505968084951\n",
      "Date 2022-10-21: The calculated VIX-equivalent index is 2822.68\n",
      "F: 116.7938747460539, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=138.0: 8000\n",
      "Contribution to sigma_squared at K=138.0: 1.268725302894751\n",
      "F: 117.7519731407375, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 19300\n",
      "Contribution to sigma_squared at K=138.0: 1.0286361786970724\n",
      "Date 2022-10-24: The calculated VIX-equivalent index is 2832.93\n",
      "F: 115.36375875860705, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 24000\n",
      "Contribution to sigma_squared at K=130.0: 1.4292636570337516\n",
      "F: 116.31012544360327, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 20000\n",
      "Contribution to sigma_squared at K=137.0: 2.1624934318742777\n",
      "Date 2022-10-25: The calculated VIX-equivalent index is 2886.11\n",
      "F: 113.45685972623458, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 18100\n",
      "Contribution to sigma_squared at K=130.0: 1.0775885424670675\n",
      "F: 114.38758349411965, K0: 114.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 22500\n",
      "Contribution to sigma_squared at K=135.0: 6.261728116872854\n",
      "Date 2022-10-26: The calculated VIX-equivalent index is 3189.06\n",
      "F: 115.31171531842273, K0: 115.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=142.0: 2200\n",
      "Contribution to sigma_squared at K=142.0: 0.4389755780597259\n",
      "F: 116.25765507403926, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 28400\n",
      "Contribution to sigma_squared at K=135.0: 1.58027731383681\n",
      "Date 2022-10-27: The calculated VIX-equivalent index is 3091.63\n",
      "F: 115.17579905006865, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 25000\n",
      "Contribution to sigma_squared at K=130.0: 1.48751365548815\n",
      "F: 116.12062384003478, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 22000\n",
      "Contribution to sigma_squared at K=136.0: 1.20587043575959\n",
      "Date 2022-10-28: The calculated VIX-equivalent index is 3021.17\n",
      "F: 116.58006478739794, K0: 116.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 2400\n",
      "Contribution to sigma_squared at K=135.0: 0.6615173053779835\n",
      "F: 117.53640922898595, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 26500\n",
      "Contribution to sigma_squared at K=132.0: 3.081084679094581\n",
      "Date 2022-10-31: The calculated VIX-equivalent index is 2415.84\n",
      "F: 117.44154466340501, K0: 117.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=142.0: 100\n",
      "Contribution to sigma_squared at K=142.0: 0.059773039324890316\n",
      "F: 118.40495610647791, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 19100\n",
      "Contribution to sigma_squared at K=134.0: 1.0771413022999123\n",
      "Date 2022-11-01: The calculated VIX-equivalent index is 2425.82\n",
      "F: 117.34060752424807, K0: 117.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 2200\n",
      "Contribution to sigma_squared at K=135.0: 0.6058602958376695\n",
      "F: 118.30319094692007, K0: 118.0\n",
      "deltaK: 69.0\n",
      "Q_K at K=200.0: 1000\n",
      "Contribution to sigma_squared at K=200.0: 1.7457601278896717\n",
      "Date 2022-11-03: The calculated VIX-equivalent index is 2494.71\n",
      "F: 118.56989108164811, K0: 118.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 1000\n",
      "Contribution to sigma_squared at K=138.0: 0.42155324798108224\n",
      "F: 119.54255871982811, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 19700\n",
      "Contribution to sigma_squared at K=134.0: 1.1100061409551538\n",
      "Date 2022-11-04: The calculated VIX-equivalent index is 2296.08\n",
      "F: 115.645690352562, K0: 115.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 5000\n",
      "Contribution to sigma_squared at K=130.0: 1.4831797018156478\n",
      "F: 116.59436981473223, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 6500\n",
      "Contribution to sigma_squared at K=138.0: 0.34501960964349454\n",
      "Date 2022-11-07: The calculated VIX-equivalent index is 2614.28\n",
      "F: 116.4318136074156, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 2500\n",
      "Contribution to sigma_squared at K=128.0: 0.3058889688262599\n",
      "F: 117.38694189603447, K0: 117.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=138.0: 4500\n",
      "Contribution to sigma_squared at K=138.0: 1.432740271390296\n",
      "Date 2022-11-08: The calculated VIX-equivalent index is 2508.74\n",
      "F: 113.81231051459118, K0: 113.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=138.0: 100\n",
      "Contribution to sigma_squared at K=138.0: 0.04209386906143281\n",
      "F: 114.74595016167329, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 19700\n",
      "Contribution to sigma_squared at K=132.0: 1.1422298929894152\n",
      "Date 2022-11-09: The calculated VIX-equivalent index is 2661.87\n",
      "F: 109.9678105671631, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 900\n",
      "Contribution to sigma_squared at K=130.0: 0.05334775126908506\n",
      "F: 110.86991252242706, K0: 110.0\n",
      "deltaK: 35.0\n",
      "Q_K at K=170.0: 100\n",
      "Contribution to sigma_squared at K=170.0: 0.12231469615875944\n",
      "Date 2022-11-10: The calculated VIX-equivalent index is 2865.25\n",
      "F: 112.41737659622304, K0: 112.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=142.0: 100\n",
      "Contribution to sigma_squared at K=142.0: 0.019866295751396555\n",
      "F: 113.33957314364962, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 3500\n",
      "Contribution to sigma_squared at K=135.0: 0.9695098641866935\n",
      "Date 2022-11-11: The calculated VIX-equivalent index is 2790.42\n",
      "F: 113.22733585453231, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 1500\n",
      "Contribution to sigma_squared at K=126.0: 0.283612168919801\n",
      "F: 114.1561767629481, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 1500\n",
      "Contribution to sigma_squared at K=143.0: 0.07399813056205705\n",
      "Date 2022-11-14: The calculated VIX-equivalent index is 2719.32\n",
      "F: 111.14769213138088, K0: 111.0\n",
      "deltaK: 36.0\n",
      "Q_K at K=170.0: 200\n",
      "Contribution to sigma_squared at K=170.0: 0.251178683646804\n",
      "F: 112.2885845740432, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 50000\n",
      "Contribution to sigma_squared at K=130.0: 3.0134680008349064\n",
      "Date 2022-11-16: The calculated VIX-equivalent index is 2823.32\n",
      "F: 110.57044078143234, K0: 110.0\n",
      "deltaK: 20.0\n",
      "Q_K at K=155.0: 1600\n",
      "Contribution to sigma_squared at K=155.0: 1.3424805107122213\n",
      "F: 111.70540793954719, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=132.0: 25000\n",
      "Contribution to sigma_squared at K=132.0: 4.3829848211184546\n",
      "Date 2022-11-17: The calculated VIX-equivalent index is 2748.79\n",
      "F: 109.6992327033907, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 10000\n",
      "Contribution to sigma_squared at K=125.0: 1.2897473923329055\n",
      "F: 110.82525721327629, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 31000\n",
      "Contribution to sigma_squared at K=130.0: 1.867260181092734\n",
      "Date 2022-11-18: The calculated VIX-equivalent index is 2660.93\n",
      "F: 110.48717242618591, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 6000\n",
      "Contribution to sigma_squared at K=126.0: 0.3804737444622014\n",
      "F: 111.62128486356485, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 40000\n",
      "Contribution to sigma_squared at K=127.0: 2.522331943038336\n",
      "Date 2022-11-21: The calculated VIX-equivalent index is 2514.34\n",
      "F: 109.73871625378945, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 20000\n",
      "Contribution to sigma_squared at K=125.0: 1.2882429762064214\n",
      "F: 110.86514604860177, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 34500\n",
      "Contribution to sigma_squared at K=128.0: 6.423080753174048\n",
      "Date 2022-11-22: The calculated VIX-equivalent index is 2543.61\n",
      "F: 109.5101103642584, K0: 109.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 6000\n",
      "Contribution to sigma_squared at K=130.0: 1.7860583576802225\n",
      "F: 110.6341935990413, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 39500\n",
      "Contribution to sigma_squared at K=125.0: 2.5696461441134755\n",
      "Date 2022-11-23: The calculated VIX-equivalent index is 2441.25\n",
      "F: 112.48567163763553, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 9900\n",
      "Contribution to sigma_squared at K=126.0: 1.2544647896820174\n",
      "F: 113.64029797506299, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 48800\n",
      "Contribution to sigma_squared at K=128.0: 3.0267002787808064\n",
      "Date 2022-11-24: The calculated VIX-equivalent index is 2421.38\n",
      "F: 109.58252666090398, K0: 109.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 2000\n",
      "Contribution to sigma_squared at K=130.0: 0.5950054621952601\n",
      "F: 110.70735322381171, K0: 110.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=131.0: 23100\n",
      "Contribution to sigma_squared at K=131.0: 8.204714136028365\n",
      "Date 2022-11-25: The calculated VIX-equivalent index is 2569.41\n",
      "F: 109.29118601323334, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 5400\n",
      "Contribution to sigma_squared at K=123.0: 1.0758018641148497\n",
      "F: 110.41302206561589, K0: 110.0\n",
      "deltaK: 21.0\n",
      "Q_K at K=144.0: 4100\n",
      "Contribution to sigma_squared at K=144.0: 4.214449227070531\n",
      "Date 2022-11-28: The calculated VIX-equivalent index is 2407.41\n",
      "F: 111.39609327957602, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 11300\n",
      "Contribution to sigma_squared at K=126.0: 0.714888210921207\n",
      "F: 112.53953547372028, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 61700\n",
      "Contribution to sigma_squared at K=125.0: 4.006831488079587\n",
      "Date 2022-11-29: The calculated VIX-equivalent index is 2397.11\n",
      "F: 112.94644743375521, K0: 112.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=130.0: 500\n",
      "Contribution to sigma_squared at K=130.0: 0.2079483137125063\n",
      "F: 114.10580347463825, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=132.0: 15100\n",
      "Contribution to sigma_squared at K=132.0: 2.6373001583151474\n",
      "Date 2022-11-30: The calculated VIX-equivalent index is 2479.43\n",
      "F: 111.3471565238792, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 300\n",
      "Contribution to sigma_squared at K=131.0: 0.01754793462710087\n",
      "F: 112.49009639922878, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 23400\n",
      "Contribution to sigma_squared at K=130.0: 2.80828804335951\n",
      "Date 2022-12-01: The calculated VIX-equivalent index is 2345.07\n",
      "F: 112.3165039476805, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 12400\n",
      "Contribution to sigma_squared at K=123.0: 0.8224927678336427\n",
      "F: 113.46939383754608, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=136.0: 7000\n",
      "Contribution to sigma_squared at K=136.0: 1.9184302387084387\n",
      "Date 2022-12-02: The calculated VIX-equivalent index is 2357.32\n",
      "F: 109.68907864751972, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 3000\n",
      "Contribution to sigma_squared at K=125.0: 0.38500971971611314\n",
      "F: 110.81499892954972, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 31600\n",
      "Contribution to sigma_squared at K=128.0: 1.9536320461909342\n",
      "Date 2022-12-05: The calculated VIX-equivalent index is 2394.51\n",
      "F: 110.44607771849574, K0: 110.0\n",
      "deltaK: 17.0\n",
      "Q_K at K=145.0: 1000\n",
      "Contribution to sigma_squared at K=145.0: 0.8104508224422403\n",
      "F: 111.57976833297815, K0: 111.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=136.0: 5500\n",
      "Contribution to sigma_squared at K=136.0: 3.011159643192549\n",
      "Date 2022-12-06: The calculated VIX-equivalent index is 2405.86\n",
      "F: 109.29154643191613, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 1000\n",
      "Contribution to sigma_squared at K=128.0: 0.061159945862268555\n",
      "F: 110.41338618387122, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 3500\n",
      "Contribution to sigma_squared at K=134.0: 0.3946486603564954\n",
      "Date 2022-12-07: The calculated VIX-equivalent index is 2473.30\n",
      "F: 107.43696372786866, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 500\n",
      "Contribution to sigma_squared at K=139.0: 0.02592392263017032\n",
      "F: 108.53976683272145, K0: 108.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=131.0: 11800\n",
      "Contribution to sigma_squared at K=131.0: 4.175285114954409\n",
      "Date 2022-12-08: The calculated VIX-equivalent index is 2433.09\n",
      "F: 107.67653520598957, K0: 107.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=139.0: 500\n",
      "Contribution to sigma_squared at K=139.0: 0.10366543852056316\n",
      "F: 108.78179742882877, K0: 108.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 12000\n",
      "Contribution to sigma_squared at K=130.0: 3.59197493773299\n",
      "Date 2022-12-09: The calculated VIX-equivalent index is 2349.10\n",
      "F: 105.40482226734117, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 500\n",
      "Contribution to sigma_squared at K=129.0: 0.03006381022622012\n",
      "F: 106.48676614614727, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=132.0: 200\n",
      "Contribution to sigma_squared at K=132.0: 0.03480903499709002\n",
      "Date 2022-12-12: The calculated VIX-equivalent index is 2555.27\n",
      "F: 103.56988529792156, K0: 103.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=143.0: 1000\n",
      "Contribution to sigma_squared at K=143.0: 0.39133134075762427\n",
      "F: 104.63299418626565, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 10000\n",
      "Contribution to sigma_squared at K=130.0: 1.195928368545115\n",
      "Date 2022-12-13: The calculated VIX-equivalent index is 2472.39\n",
      "F: 104.81068428370168, K0: 104.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=125.0: 4500\n",
      "Contribution to sigma_squared at K=125.0: 1.1638248797500303\n",
      "F: 105.67048064353857, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 42300\n",
      "Contribution to sigma_squared at K=122.0: 2.894702861807107\n",
      "Date 2022-12-14: The calculated VIX-equivalent index is 2529.51\n",
      "F: 104.77194644029416, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 1700\n",
      "Contribution to sigma_squared at K=120.0: 0.2384651199317401\n",
      "F: 105.6314250209182, K0: 105.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 10000\n",
      "Contribution to sigma_squared at K=135.0: 1.676139973073645\n",
      "Date 2022-12-15: The calculated VIX-equivalent index is 2410.97\n",
      "F: 103.85085696125155, K0: 103.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=122.0: 10000\n",
      "Contribution to sigma_squared at K=122.0: 2.7134514185591407\n",
      "F: 104.7027795432999, K0: 104.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 5000\n",
      "Contribution to sigma_squared at K=135.0: 0.83782548945884\n",
      "Date 2022-12-16: The calculated VIX-equivalent index is 2453.06\n",
      "F: 105.660605952027, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 15000\n",
      "Contribution to sigma_squared at K=120.0: 1.0508248415718782\n",
      "F: 106.52737449758682, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 27000\n",
      "Contribution to sigma_squared at K=124.0: 3.5719064826683264\n",
      "Date 2022-12-19: The calculated VIX-equivalent index is 2366.55\n",
      "F: 107.77219255503186, K0: 107.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=125.0: 5500\n",
      "Contribution to sigma_squared at K=125.0: 1.4199645429834662\n",
      "F: 108.65628313686263, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 31000\n",
      "Contribution to sigma_squared at K=124.0: 2.0499406860683265\n",
      "Date 2022-12-20: The calculated VIX-equivalent index is 2223.62\n",
      "F: 108.3144492227107, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 12000\n",
      "Contribution to sigma_squared at K=120.0: 2.5205083185391097\n",
      "F: 109.20298811352974, K0: 109.0\n",
      "deltaK: 95.0\n",
      "Q_K at K=220.0: 100\n",
      "Contribution to sigma_squared at K=220.0: 0.19951451486392094\n",
      "Date 2022-12-21: The calculated VIX-equivalent index is 2182.70\n",
      "F: 108.40216604458917, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 16200\n",
      "Contribution to sigma_squared at K=120.0: 1.1338978454248048\n",
      "F: 109.29142450521793, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 27900\n",
      "Contribution to sigma_squared at K=125.0: 1.8144863744977022\n",
      "Date 2022-12-22: The calculated VIX-equivalent index is 2195.82\n",
      "F: 110.5329334787159, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 15200\n",
      "Contribution to sigma_squared at K=122.0: 1.0290076783091406\n",
      "F: 111.4396713222534, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 54500\n",
      "Contribution to sigma_squared at K=123.0: 3.659561876194149\n",
      "Date 2022-12-23: The calculated VIX-equivalent index is 2174.52\n",
      "F: 109.46993866764349, K0: 109.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=125.0: 7000\n",
      "Contribution to sigma_squared at K=125.0: 1.8040664819017966\n",
      "F: 110.36795641670464, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 46400\n",
      "Contribution to sigma_squared at K=123.0: 3.112937609654611\n",
      "Date 2022-12-26: The calculated VIX-equivalent index is 2185.85\n",
      "F: 109.27742462432505, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 12900\n",
      "Contribution to sigma_squared at K=121.0: 0.8867614059545346\n",
      "F: 110.17386311765675, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 31200\n",
      "Contribution to sigma_squared at K=125.0: 4.052289868009177\n",
      "Date 2022-12-27: The calculated VIX-equivalent index is 2184.92\n",
      "F: 110.91424776651797, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 13400\n",
      "Contribution to sigma_squared at K=122.0: 0.9058290237397275\n",
      "F: 111.82411365600655, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 60000\n",
      "Contribution to sigma_squared at K=123.0: 4.023002002512006\n",
      "Date 2022-12-28: The calculated VIX-equivalent index is 2252.06\n",
      "F: 110.37684114952648, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 13400\n",
      "Contribution to sigma_squared at K=122.0: 0.9055647587582654\n",
      "F: 111.28229851658057, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 31100\n",
      "Contribution to sigma_squared at K=126.0: 5.959681573497995\n",
      "Date 2022-12-29: The calculated VIX-equivalent index is 2213.70\n",
      "F: 106.87379675036239, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 7500\n",
      "Contribution to sigma_squared at K=120.0: 1.046541049523763\n",
      "F: 107.75051749725858, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 36000\n",
      "Contribution to sigma_squared at K=123.0: 2.410282264534542\n",
      "Date 2023-01-02: The calculated VIX-equivalent index is 2537.75\n",
      "F: 104.62264261479292, K0: 104.0\n",
      "deltaK: 22.0\n",
      "Q_K at K=150.0: 1000\n",
      "Contribution to sigma_squared at K=150.0: 0.9820666084754053\n",
      "F: 105.48089640725199, K0: 105.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=129.0: 11000\n",
      "Contribution to sigma_squared at K=129.0: 2.6774549010511093\n",
      "Date 2023-01-03: The calculated VIX-equivalent index is 2647.91\n",
      "F: 105.7656240927471, K0: 105.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=128.0: 1700\n",
      "Contribution to sigma_squared at K=128.0: 0.8334758723437927\n",
      "F: 106.63325413649981, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 21300\n",
      "Contribution to sigma_squared at K=123.0: 4.2757551246761905\n",
      "Date 2023-01-04: The calculated VIX-equivalent index is 2428.12\n",
      "F: 108.05039509794827, K0: 108.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=129.0: 2200\n",
      "Contribution to sigma_squared at K=129.0: 0.7962360837671913\n",
      "F: 108.93676786632643, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 26900\n",
      "Contribution to sigma_squared at K=123.0: 1.799440653480825\n",
      "Date 2023-01-05: The calculated VIX-equivalent index is 2395.42\n",
      "F: 109.3458909207698, K0: 109.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=129.0: 1600\n",
      "Contribution to sigma_squared at K=129.0: 1.0613383883188394\n",
      "F: 110.24289106554816, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 39000\n",
      "Contribution to sigma_squared at K=120.0: 2.7401281035414513\n",
      "Date 2023-01-06: The calculated VIX-equivalent index is 2279.55\n",
      "F: 109.41652385010403, K0: 109.0\n",
      "deltaK: 14.0\n",
      "Q_K at K=130.0: 1900\n",
      "Contribution to sigma_squared at K=130.0: 1.5781032027318493\n",
      "F: 110.31410341992805, K0: 110.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=134.0: 6300\n",
      "Contribution to sigma_squared at K=134.0: 4.255991916320524\n",
      "Date 2023-01-09: The calculated VIX-equivalent index is 2415.76\n",
      "F: 111.0756856647473, K0: 111.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 700\n",
      "Contribution to sigma_squared at K=125.0: 0.22452348196317498\n",
      "F: 111.98687588217237, K0: 111.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=132.0: 10000\n",
      "Contribution to sigma_squared at K=132.0: 4.0598693181498815\n",
      "Date 2023-01-10: The calculated VIX-equivalent index is 2298.94\n",
      "F: 112.74712713429878, K0: 112.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.17787773130309018\n",
      "F: 113.67202873335467, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 13700\n",
      "Contribution to sigma_squared at K=128.0: 0.8447647546437272\n",
      "Date 2023-01-11: The calculated VIX-equivalent index is 2229.23\n",
      "F: 112.04620599955143, K0: 112.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=129.0: 100\n",
      "Contribution to sigma_squared at K=129.0: 0.009029675664999475\n",
      "F: 112.96535771304643, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 8000\n",
      "Contribution to sigma_squared at K=131.0: 0.47082101029585655\n",
      "Date 2023-01-12: The calculated VIX-equivalent index is 2266.09\n",
      "F: 111.07801401931292, K0: 111.0\n",
      "deltaK: 4.5\n",
      "Q_K at K=125.0: 8000\n",
      "Contribution to sigma_squared at K=125.0: 2.3073637681794827\n",
      "F: 111.98922333699285, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 10000\n",
      "Contribution to sigma_squared at K=128.0: 1.2325137607981647\n",
      "Date 2023-01-13: The calculated VIX-equivalent index is 2154.68\n",
      "F: 109.27641091888361, K0: 109.0\n",
      "deltaK: 27.0\n",
      "Q_K at K=150.0: 100\n",
      "Contribution to sigma_squared at K=150.0: 0.12007004783388696\n",
      "F: 110.17284109645766, K0: 110.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=134.0: 5000\n",
      "Contribution to sigma_squared at K=134.0: 2.247252947001566\n",
      "Date 2023-01-16: The calculated VIX-equivalent index is 2315.21\n",
      "F: 112.38607890715883, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=131.0: 8000\n",
      "Contribution to sigma_squared at K=131.0: 0.9402692567869709\n",
      "F: 113.30801870939466, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 112800\n",
      "Contribution to sigma_squared at K=121.0: 7.833598897390859\n",
      "Date 2023-01-17: The calculated VIX-equivalent index is 2192.84\n",
      "F: 113.14903622850058, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 15000\n",
      "Contribution to sigma_squared at K=126.0: 0.9525730606723771\n",
      "F: 114.07723481944753, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 39600\n",
      "Contribution to sigma_squared at K=127.0: 2.4956518318999477\n",
      "Date 2023-01-18: The calculated VIX-equivalent index is 2135.76\n",
      "F: 113.81500127406076, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 22000\n",
      "Contribution to sigma_squared at K=123.0: 1.4656621264148004\n",
      "F: 114.74866299432382, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=127.0: 42400\n",
      "Contribution to sigma_squared at K=127.0: 8.013997515359883\n",
      "Date 2023-01-19: The calculated VIX-equivalent index is 2027.24\n",
      "F: 112.89384630883579, K0: 112.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=128.0: 8000\n",
      "Contribution to sigma_squared at K=128.0: 2.951997510527585\n",
      "F: 113.81995149331856, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 27300\n",
      "Contribution to sigma_squared at K=128.0: 5.078164647186213\n",
      "Date 2023-01-20: The calculated VIX-equivalent index is 1943.48\n",
      "F: 112.48966608642634, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 12400\n",
      "Contribution to sigma_squared at K=123.0: 0.8251368725826301\n",
      "F: 113.41245564820977, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 60500\n",
      "Contribution to sigma_squared at K=124.0: 11.981078616429107\n",
      "Date 2023-01-23: The calculated VIX-equivalent index is 1966.26\n",
      "F: 113.75603152430142, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 13600\n",
      "Contribution to sigma_squared at K=123.0: 0.9047248081296335\n",
      "F: 114.6892094963996, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 38400\n",
      "Contribution to sigma_squared at K=126.0: 2.4542911094692865\n",
      "Date 2023-01-24: The calculated VIX-equivalent index is 1969.39\n",
      "F: 114.97239763666163, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 9000\n",
      "Contribution to sigma_squared at K=126.0: 1.7111330070745896\n",
      "F: 115.91555385823675, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 77500\n",
      "Contribution to sigma_squared at K=124.0: 10.225805997312525\n",
      "Date 2023-01-25: The calculated VIX-equivalent index is 1983.45\n",
      "F: 114.84579429999397, K0: 114.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=128.0: 5000\n",
      "Contribution to sigma_squared at K=128.0: 1.2278475058810583\n",
      "F: 115.7879119529465, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 69500\n",
      "Contribution to sigma_squared at K=124.0: 9.167563617091997\n",
      "Date 2023-01-26: The calculated VIX-equivalent index is 1877.35\n",
      "F: 112.94055149082655, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 8100\n",
      "Contribution to sigma_squared at K=125.0: 1.042563810814837\n",
      "F: 113.8670398132092, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 85800\n",
      "Contribution to sigma_squared at K=122.0: 11.688355329381423\n",
      "Date 2023-01-27: The calculated VIX-equivalent index is 1998.56\n",
      "F: 112.79838116984826, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 8100\n",
      "Contribution to sigma_squared at K=125.0: 1.0416516097403878\n",
      "F: 113.72370322253913, K0: 113.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=132.0: 15000\n",
      "Contribution to sigma_squared at K=132.0: 8.720050978569569\n",
      "Date 2023-01-30: The calculated VIX-equivalent index is 2126.62\n",
      "F: 113.92808084522774, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 8700\n",
      "Contribution to sigma_squared at K=123.0: 0.5775768950932904\n",
      "F: 114.86267019423711, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 33100\n",
      "Contribution to sigma_squared at K=126.0: 4.222462562065551\n",
      "Date 2023-01-31: The calculated VIX-equivalent index is 1962.17\n",
      "F: 112.53229911692428, K0: 112.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=126.0: 4000\n",
      "Contribution to sigma_squared at K=126.0: 1.0119357885732592\n",
      "F: 113.45543841141557, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 32500\n",
      "Contribution to sigma_squared at K=124.0: 2.1397457886524456\n",
      "Date 2023-02-01: The calculated VIX-equivalent index is 2036.48\n",
      "F: 110.55921339817168, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 2000\n",
      "Contribution to sigma_squared at K=125.0: 0.3854593358536678\n",
      "F: 111.46616682449293, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 22500\n",
      "Contribution to sigma_squared at K=124.0: 1.4809302989608355\n",
      "Date 2023-02-02: The calculated VIX-equivalent index is 2138.56\n",
      "F: 108.90411681104288, K0: 108.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=125.0: 3000\n",
      "Contribution to sigma_squared at K=125.0: 0.48168360327310383\n",
      "F: 109.79749293815541, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 10000\n",
      "Contribution to sigma_squared at K=125.0: 1.2950266975506675\n",
      "Date 2023-02-03: The calculated VIX-equivalent index is 2147.00\n",
      "F: 109.00746104920044, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 2500\n",
      "Contribution to sigma_squared at K=122.0: 0.5052217877052764\n",
      "F: 109.90168494293509, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 5800\n",
      "Contribution to sigma_squared at K=126.0: 1.1078902839436633\n",
      "Date 2023-02-06: The calculated VIX-equivalent index is 2074.51\n",
      "F: 108.08172517298674, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 2100\n",
      "Contribution to sigma_squared at K=119.0: 0.29728234494806377\n",
      "F: 108.9683549522284, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 6000\n",
      "Contribution to sigma_squared at K=130.0: 1.0763355316906034\n",
      "Date 2023-02-07: The calculated VIX-equivalent index is 2125.94\n",
      "F: 110.1762916495485, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 3000\n",
      "Contribution to sigma_squared at K=120.0: 0.20875928187654336\n",
      "F: 111.08010384339121, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 9000\n",
      "Contribution to sigma_squared at K=125.0: 0.5819124398750152\n",
      "Date 2023-02-08: The calculated VIX-equivalent index is 1998.81\n",
      "F: 108.1973036790616, K0: 108.0\n",
      "deltaK: 37.0\n",
      "Q_K at K=168.0: 1000\n",
      "Contribution to sigma_squared at K=168.0: 1.3132380979370941\n",
      "F: 109.0848815866308, K0: 109.0\n",
      "deltaK: 43.0\n",
      "Q_K at K=174.0: 1000\n",
      "Contribution to sigma_squared at K=174.0: 1.4344268247974854\n",
      "Date 2023-02-09: The calculated VIX-equivalent index is 2176.67\n",
      "F: 108.23606090517342, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 100\n",
      "Contribution to sigma_squared at K=125.0: 0.012818687600997124\n",
      "F: 109.12395675095814, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 10000\n",
      "Contribution to sigma_squared at K=125.0: 0.6461921746213481\n",
      "Date 2023-02-10: The calculated VIX-equivalent index is 2092.17\n",
      "F: 108.9000013247617, K0: 108.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=129.0: 100\n",
      "Contribution to sigma_squared at K=129.0: 0.021044667158354083\n",
      "F: 109.79334369119277, K0: 109.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 8600\n",
      "Contribution to sigma_squared at K=130.0: 2.053398791010042\n",
      "Date 2023-02-13: The calculated VIX-equivalent index is 2047.36\n",
      "F: 108.76526008733003, K0: 108.0\n",
      "deltaK: 26.0\n",
      "Q_K at K=150.0: 1000\n",
      "Contribution to sigma_squared at K=150.0: 1.1653749405798648\n",
      "F: 109.65749712727408, K0: 109.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 5000\n",
      "Contribution to sigma_squared at K=135.0: 0.836848214230362\n",
      "Date 2023-02-14: The calculated VIX-equivalent index is 2112.79\n",
      "F: 110.49922583322041, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 11400\n",
      "Contribution to sigma_squared at K=123.0: 0.7597010993812109\n",
      "F: 111.40568716190549, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 29700\n",
      "Contribution to sigma_squared at K=125.0: 1.932113683042284\n",
      "Date 2023-02-15: The calculated VIX-equivalent index is 2018.61\n",
      "F: 110.81100854831766, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 6500\n",
      "Contribution to sigma_squared at K=124.0: 1.2782407206488433\n",
      "F: 111.72002753269723, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 37800\n",
      "Contribution to sigma_squared at K=124.0: 2.4981468464975105\n",
      "Date 2023-02-16: The calculated VIX-equivalent index is 1972.67\n",
      "F: 110.00831865073297, K0: 110.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=135.0: 1400\n",
      "Contribution to sigma_squared at K=135.0: 0.8514278910290957\n",
      "F: 110.91075290706944, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 24900\n",
      "Contribution to sigma_squared at K=124.0: 4.935373748655254\n",
      "Date 2023-02-17: The calculated VIX-equivalent index is 1867.99\n",
      "F: 107.81062880405558, K0: 107.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=124.0: 4500\n",
      "Contribution to sigma_squared at K=124.0: 1.4723133248957347\n",
      "F: 108.69503469102169, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 10000\n",
      "Contribution to sigma_squared at K=133.0: 0.5734637090470929\n",
      "Date 2023-02-22: The calculated VIX-equivalent index is 2113.09\n",
      "F: 108.22257629600557, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 14000\n",
      "Contribution to sigma_squared at K=117.0: 1.0287046150521355\n",
      "F: 109.1103615231262, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 10000\n",
      "Contribution to sigma_squared at K=133.0: 0.57329640774357\n",
      "Date 2023-02-23: The calculated VIX-equivalent index is 2023.43\n",
      "F: 106.38658792344404, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 8100\n",
      "Contribution to sigma_squared at K=122.0: 1.6417017815085153\n",
      "F: 107.25931193681325, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 20000\n",
      "Contribution to sigma_squared at K=120.0: 1.4080668926647333\n",
      "Date 2023-02-24: The calculated VIX-equivalent index is 2068.34\n",
      "F: 106.20571508472862, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=118.0: 5200\n",
      "Contribution to sigma_squared at K=118.0: 0.7504069116952923\n",
      "F: 107.07695533898125, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=119.0: 25500\n",
      "Contribution to sigma_squared at K=119.0: 1.8239876140527753\n",
      "Date 2023-02-27: The calculated VIX-equivalent index is 1996.48\n",
      "F: 105.3921933571486, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 5300\n",
      "Contribution to sigma_squared at K=117.0: 0.38887043698222223\n",
      "F: 106.25676002631016, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=133.0: 3700\n",
      "Contribution to sigma_squared at K=133.0: 0.6354313027011468\n",
      "Date 2023-02-28: The calculated VIX-equivalent index is 2035.88\n",
      "F: 104.81194633043597, K0: 104.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=121.0: 100\n",
      "Contribution to sigma_squared at K=121.0: 0.03429046124622007\n",
      "F: 105.67175304325544, K0: 105.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 2000\n",
      "Contribution to sigma_squared at K=135.0: 0.33327742952904077\n",
      "Date 2023-03-01: The calculated VIX-equivalent index is 2057.30\n",
      "F: 103.71828387311223, K0: 103.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=123.0: 700\n",
      "Contribution to sigma_squared at K=123.0: 0.13933377903032226\n",
      "F: 104.56911891471208, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=135.0: 500\n",
      "Contribution to sigma_squared at K=135.0: 0.05553003329205135\n",
      "Date 2023-03-02: The calculated VIX-equivalent index is 2058.89\n",
      "F: 104.23030066818369, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 1500\n",
      "Contribution to sigma_squared at K=119.0: 0.21259250903586605\n",
      "F: 105.08533595119582, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 15000\n",
      "Contribution to sigma_squared at K=120.0: 1.0538954244390197\n",
      "Date 2023-03-03: The calculated VIX-equivalent index is 1883.31\n",
      "F: 104.97562723277957, K0: 104.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=121.0: 100\n",
      "Contribution to sigma_squared at K=121.0: 0.0342404712255781\n",
      "F: 105.83677667363266, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 4000\n",
      "Contribution to sigma_squared at K=122.0: 0.2716620199719145\n",
      "Date 2023-03-06: The calculated VIX-equivalent index is 2016.05\n",
      "F: 104.47150786345563, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 1500\n",
      "Contribution to sigma_squared at K=115.0: 0.1136866132003654\n",
      "F: 105.32852184806559, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 8500\n",
      "Contribution to sigma_squared at K=118.0: 0.6169028660640109\n",
      "Date 2023-03-07: The calculated VIX-equivalent index is 1999.66\n",
      "F: 106.75814733166622, K0: 106.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 200\n",
      "Contribution to sigma_squared at K=116.0: 0.014893646745056598\n",
      "F: 107.63391936851544, K0: 107.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 3500\n",
      "Contribution to sigma_squared at K=125.0: 0.6788978465208512\n",
      "Date 2023-03-08: The calculated VIX-equivalent index is 2022.66\n",
      "F: 105.25529765929836, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 2600\n",
      "Contribution to sigma_squared at K=115.0: 0.196941834972787\n",
      "F: 106.11874132822865, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 15900\n",
      "Contribution to sigma_squared at K=119.0: 2.267992616821312\n",
      "Date 2023-03-09: The calculated VIX-equivalent index is 2060.53\n",
      "F: 103.76947934200315, K0: 103.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=131.0: 500\n",
      "Contribution to sigma_squared at K=131.0: 0.20424858055460937\n",
      "F: 104.62073435679652, K0: 104.0\n",
      "deltaK: 6.5\n",
      "Q_K at K=131.0: 5000\n",
      "Contribution to sigma_squared at K=131.0: 1.912152343540023\n",
      "Date 2023-03-10: The calculated VIX-equivalent index is 2172.20\n",
      "F: 103.18155523246232, K0: 103.0\n",
      "deltaK: 5.5\n",
      "Q_K at K=125.0: 100\n",
      "Contribution to sigma_squared at K=125.0: 0.03522054736460684\n",
      "F: 104.02798731328954, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 1000\n",
      "Contribution to sigma_squared at K=132.0: 0.05789668548605389\n",
      "Date 2023-03-13: The calculated VIX-equivalent index is 2281.31\n",
      "F: 102.96241807649258, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.059188865289590664\n",
      "F: 103.80705250348046, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 1000\n",
      "Contribution to sigma_squared at K=131.0: 0.05876682854918568\n",
      "Date 2023-03-14: The calculated VIX-equivalent index is 2145.95\n",
      "F: 103.51773033389857, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 1000\n",
      "Contribution to sigma_squared at K=129.0: 0.06058550131696676\n",
      "F: 104.58030386965764, K0: 104.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=127.0: 7500\n",
      "Contribution to sigma_squared at K=127.0: 2.8417662776798887\n",
      "Date 2023-03-15: The calculated VIX-equivalent index is 2216.06\n",
      "F: 104.25274499221977, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.11927919478498933\n",
      "F: 105.32286319807359, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 15700\n",
      "Contribution to sigma_squared at K=121.0: 1.0919065656842535\n",
      "Date 2023-03-16: The calculated VIX-equivalent index is 2220.12\n",
      "F: 102.75813467470309, K0: 102.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=128.0: 1000\n",
      "Contribution to sigma_squared at K=128.0: 0.7379993776318963\n",
      "F: 103.8129112249338, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 45000\n",
      "Contribution to sigma_squared at K=116.0: 3.404288691748073\n",
      "Date 2023-03-17: The calculated VIX-equivalent index is 2298.29\n",
      "F: 101.60245709021319, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 8500\n",
      "Contribution to sigma_squared at K=115.0: 0.6470499044763229\n",
      "F: 102.64537101156685, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=118.0: 20100\n",
      "Contribution to sigma_squared at K=118.0: 2.936376426947117\n",
      "Date 2023-03-20: The calculated VIX-equivalent index is 2386.78\n",
      "F: 101.6485402988149, K0: 101.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=122.0: 5100\n",
      "Contribution to sigma_squared at K=122.0: 0.8621410757058688\n",
      "F: 102.69192724829374, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 25100\n",
      "Contribution to sigma_squared at K=116.0: 1.8966216977761765\n",
      "Date 2023-03-21: The calculated VIX-equivalent index is 2212.73\n",
      "F: 100.83660685389218, K0: 100.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.1190705571786815\n",
      "F: 101.87165958865637, K0: 101.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=118.0: 17500\n",
      "Contribution to sigma_squared at K=118.0: 6.387637932601833\n",
      "Date 2023-03-22: The calculated VIX-equivalent index is 2201.75\n",
      "F: 98.49947121996637, K0: 98.0\n",
      "deltaK: 3.5\n",
      "Q_K at K=118.0: 2500\n",
      "Contribution to sigma_squared at K=118.0: 0.6320892647339432\n",
      "F: 99.51053406946087, K0: 99.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=126.0: 17000\n",
      "Contribution to sigma_squared at K=126.0: 11.969335774035228\n",
      "Date 2023-03-23: The calculated VIX-equivalent index is 2409.86\n",
      "F: 99.37868475236155, K0: 99.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=119.0: 100\n",
      "Contribution to sigma_squared at K=119.0: 0.02130271656895677\n",
      "F: 100.39877242329287, K0: 100.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 25900\n",
      "Contribution to sigma_squared at K=115.0: 1.989513537518918\n",
      "Date 2023-03-24: The calculated VIX-equivalent index is 2339.30\n",
      "F: 100.13686874911366, K0: 100.0\n",
      "deltaK: 14.0\n",
      "Q_K at K=131.0: 500\n",
      "Contribution to sigma_squared at K=131.0: 0.40981037543264887\n",
      "F: 101.16473891534878, K0: 101.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=119.0: 18000\n",
      "Contribution to sigma_squared at K=119.0: 5.160612291994058\n",
      "Date 2023-03-27: The calculated VIX-equivalent index is 2271.37\n",
      "F: 101.62891857740998, K0: 101.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=140.0: 100\n",
      "Contribution to sigma_squared at K=140.0: 0.025622099594963612\n",
      "F: 102.67210411673595, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 35000\n",
      "Contribution to sigma_squared at K=115.0: 2.685395789791477\n",
      "Date 2023-03-28: The calculated VIX-equivalent index is 2266.49\n",
      "F: 102.20918591858204, K0: 102.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=124.0: 1000\n",
      "Contribution to sigma_squared at K=124.0: 0.7836315969395027\n",
      "F: 103.25832770055747, K0: 103.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=127.0: 10000\n",
      "Contribution to sigma_squared at K=127.0: 7.547150759006032\n",
      "Date 2023-03-29: The calculated VIX-equivalent index is 2279.65\n",
      "F: 104.10759780232443, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 2000\n",
      "Contribution to sigma_squared at K=119.0: 0.2835393980045458\n",
      "F: 105.1762261227038, K0: 105.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=119.0: 24000\n",
      "Contribution to sigma_squared at K=119.0: 3.4373979769482976\n",
      "Date 2023-03-30: The calculated VIX-equivalent index is 2206.03\n",
      "F: 102.23955251123128, K0: 102.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=119.0: 6000\n",
      "Contribution to sigma_squared at K=119.0: 1.2755550542151963\n",
      "F: 103.28900599572975, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 14000\n",
      "Contribution to sigma_squared at K=120.0: 0.9856468248653133\n",
      "Date 2023-03-31: The calculated VIX-equivalent index is 2163.52\n",
      "F: 101.77308831055552, K0: 101.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 3400\n",
      "Contribution to sigma_squared at K=112.0: 0.2717586277625227\n",
      "F: 102.817753702102, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 25000\n",
      "Contribution to sigma_squared at K=116.0: 1.8819134989421842\n",
      "Date 2023-04-03: The calculated VIX-equivalent index is 2181.88\n",
      "F: 102.10751615925695, K0: 102.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=115.0: 1000\n",
      "Contribution to sigma_squared at K=115.0: 0.37895537733455137\n",
      "F: 103.155614336477, K0: 103.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=115.0: 22900\n",
      "Contribution to sigma_squared at K=115.0: 3.5068622391894326\n",
      "Date 2023-04-04: The calculated VIX-equivalent index is 2061.97\n",
      "F: 101.1843045668991, K0: 101.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=112.0: 2000\n",
      "Contribution to sigma_squared at K=112.0: 0.31952951307634186\n",
      "F: 102.2229262978835, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=115.0: 20000\n",
      "Contribution to sigma_squared at K=115.0: 3.0618682561647224\n",
      "Date 2023-04-05: The calculated VIX-equivalent index is 2077.70\n",
      "F: 100.99839167782731, K0: 100.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=131.0: 500\n",
      "Contribution to sigma_squared at K=131.0: 0.11674753432492763\n",
      "F: 102.03510507759881, K0: 102.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=131.0: 6000\n",
      "Contribution to sigma_squared at K=131.0: 1.0615131648189176\n",
      "Date 2023-04-06: The calculated VIX-equivalent index is 2090.43\n",
      "F: 101.9060911376722, K0: 101.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 100\n",
      "Contribution to sigma_squared at K=120.0: 0.02084549441560538\n",
      "F: 102.95212175702864, K0: 102.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=120.0: 7000\n",
      "Contribution to sigma_squared at K=120.0: 1.9655501761690162\n",
      "Date 2023-04-10: The calculated VIX-equivalent index is 2088.06\n",
      "F: 106.24475565994143, K0: 106.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=130.0: 700\n",
      "Contribution to sigma_squared at K=130.0: 0.2485932342162808\n",
      "F: 107.33532116319681, K0: 107.0\n",
      "deltaK: 5.5\n",
      "Q_K at K=133.0: 4900\n",
      "Contribution to sigma_squared at K=133.0: 1.539633543715629\n",
      "Date 2023-04-11: The calculated VIX-equivalent index is 2118.02\n",
      "F: 107.98689573547365, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 31100\n",
      "Contribution to sigma_squared at K=118.0: 2.2564802279977436\n",
      "F: 108.87274759779073, K0: 108.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 23300\n",
      "Contribution to sigma_squared at K=126.0: 4.484555157553896\n",
      "Date 2023-04-12: The calculated VIX-equivalent index is 1928.59\n",
      "F: 107.51922621709497, K0: 107.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=124.0: 12000\n",
      "Contribution to sigma_squared at K=124.0: 4.729307636523462\n",
      "F: 108.40124163323048, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 23300\n",
      "Contribution to sigma_squared at K=126.0: 1.4944156137480586\n",
      "Date 2023-04-13: The calculated VIX-equivalent index is 1822.43\n",
      "F: 107.30765190263573, K0: 107.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=122.0: 6000\n",
      "Contribution to sigma_squared at K=122.0: 2.035088563919356\n",
      "F: 108.18793170539699, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 23600\n",
      "Contribution to sigma_squared at K=122.0: 3.228138683786989\n",
      "Date 2023-04-14: The calculated VIX-equivalent index is 1978.87\n",
      "F: 106.94774364661106, K0: 106.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 7500\n",
      "Contribution to sigma_squared at K=120.0: 1.5762372623578171\n",
      "F: 107.82507100410857, K0: 107.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 30800\n",
      "Contribution to sigma_squared at K=120.0: 6.526181827111312\n",
      "Date 2023-04-17: The calculated VIX-equivalent index is 1861.52\n",
      "F: 107.0653567958797, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 5000\n",
      "Contribution to sigma_squared at K=122.0: 0.6775715834000103\n",
      "F: 107.94364897254904, K0: 107.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 27000\n",
      "Contribution to sigma_squared at K=120.0: 1.9064448380435435\n",
      "Date 2023-04-18: The calculated VIX-equivalent index is 1852.82\n",
      "F: 104.76537186954216, K0: 104.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 11000\n",
      "Contribution to sigma_squared at K=116.0: 0.8241852409016114\n",
      "F: 105.62479651680971, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 22500\n",
      "Contribution to sigma_squared at K=120.0: 1.5882405459562126\n",
      "Date 2023-04-19: The calculated VIX-equivalent index is 1907.70\n",
      "F: 105.19227762830083, K0: 105.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=118.0: 8800\n",
      "Contribution to sigma_squared at K=118.0: 1.2740018563935374\n",
      "F: 106.0552043232831, K0: 106.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 20300\n",
      "Contribution to sigma_squared at K=120.0: 2.8650557393020213\n",
      "Date 2023-04-20: The calculated VIX-equivalent index is 1758.09\n",
      "F: 104.64650719102885, K0: 104.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=118.0: 6900\n",
      "Contribution to sigma_squared at K=118.0: 1.4966521133605708\n",
      "F: 105.5049567524204, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=117.0: 27000\n",
      "Contribution to sigma_squared at K=117.0: 2.001956790130612\n",
      "Date 2023-04-24: The calculated VIX-equivalent index is 1814.33\n",
      "F: 103.88480933273021, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 8500\n",
      "Contribution to sigma_squared at K=115.0: 0.6468611352643301\n",
      "F: 104.73701043719835, K0: 104.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 10500\n",
      "Contribution to sigma_squared at K=120.0: 1.479764971666345\n",
      "Date 2023-04-25: The calculated VIX-equivalent index is 1952.34\n",
      "F: 102.94093146387227, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=117.0: 3300\n",
      "Contribution to sigma_squared at K=117.0: 0.48510226998722095\n",
      "F: 103.78538962914176, K0: 103.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=116.0: 21800\n",
      "Contribution to sigma_squared at K=116.0: 4.930273264911157\n",
      "Date 2023-04-26: The calculated VIX-equivalent index is 1959.29\n",
      "F: 103.52568687044443, K0: 103.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=111.0: 15200\n",
      "Contribution to sigma_squared at K=111.0: 1.2408863475066956\n",
      "F: 104.37494197577212, K0: 104.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=118.0: 22300\n",
      "Contribution to sigma_squared at K=118.0: 4.872418748024526\n",
      "Date 2023-04-27: The calculated VIX-equivalent index is 1747.92\n",
      "F: 105.0121895663629, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=112.0: 16000\n",
      "Contribution to sigma_squared at K=112.0: 1.2826010600892723\n",
      "F: 105.87363894000946, K0: 105.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 26200\n",
      "Contribution to sigma_squared at K=116.0: 1.9739724928082287\n",
      "Date 2023-04-28: The calculated VIX-equivalent index is 1774.42\n",
      "F: 102.37403260098634, K0: 102.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=115.0: 4300\n",
      "Contribution to sigma_squared at K=115.0: 0.32656794765422054\n",
      "F: 103.21384030927206, K0: 103.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=120.0: 9500\n",
      "Contribution to sigma_squared at K=120.0: 2.6722064809325716\n",
      "Date 2023-05-02: The calculated VIX-equivalent index is 2059.18\n",
      "F: 102.21377462490001, K0: 102.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=114.0: 10000\n",
      "Contribution to sigma_squared at K=114.0: 2.3178515378850784\n",
      "F: 103.05226768453689, K0: 103.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=115.0: 20000\n",
      "Contribution to sigma_squared at K=115.0: 3.0618682561647224\n",
      "Date 2023-05-03: The calculated VIX-equivalent index is 1958.80\n",
      "F: 102.56263863980949, K0: 102.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=112.0: 6000\n",
      "Contribution to sigma_squared at K=112.0: 0.9602681955857078\n",
      "F: 103.40399354518424, K0: 103.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=120.0: 8000\n",
      "Contribution to sigma_squared at K=120.0: 2.8112079354100996\n",
      "Date 2023-05-04: The calculated VIX-equivalent index is 2116.34\n",
      "F: 105.51728901060393, K0: 105.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=120.0: 5000\n",
      "Contribution to sigma_squared at K=120.0: 2.7875208522749064\n",
      "F: 106.38288188036906, K0: 106.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=116.0: 25000\n",
      "Contribution to sigma_squared at K=116.0: 1.8797183551231027\n",
      "Date 2023-05-05: The calculated VIX-equivalent index is 1797.00\n",
      "F: 107.36398173669491, K0: 107.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=114.0: 6700\n",
      "Contribution to sigma_squared at K=114.0: 1.033496109485111\n",
      "F: 108.24472363152825, K0: 108.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=123.0: 7900\n",
      "Contribution to sigma_squared at K=123.0: 2.110759422096084\n",
      "Date 2023-05-09: The calculated VIX-equivalent index is 1949.96\n",
      "F: 107.66789356089612, K0: 107.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=120.0: 800\n",
      "Contribution to sigma_squared at K=120.0: 0.2783457091687245\n",
      "F: 108.55112854392884, K0: 108.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=123.0: 7900\n",
      "Contribution to sigma_squared at K=123.0: 2.110143632819154\n",
      "Date 2023-05-10: The calculated VIX-equivalent index is 1953.74\n",
      "F: 108.4460888424702, K0: 108.0\n",
      "deltaK: 6.5\n",
      "Q_K at K=131.0: 1500\n",
      "Contribution to sigma_squared at K=131.0: 0.5691442298340222\n",
      "F: 109.335707616191, K0: 109.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=134.0: 20000\n",
      "Contribution to sigma_squared at K=134.0: 7.874570547979834\n",
      "Date 2023-05-11: The calculated VIX-equivalent index is 1993.61\n",
      "F: 108.62219382535437, K0: 108.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 700\n",
      "Contribution to sigma_squared at K=124.0: 0.04559196007931389\n",
      "F: 109.51325724590932, K0: 109.0\n",
      "deltaK: 29.0\n",
      "Q_K at K=155.0: 1200\n",
      "Contribution to sigma_squared at K=155.0: 1.462505702186714\n",
      "Date 2023-05-12: The calculated VIX-equivalent index is 2091.75\n",
      "F: 109.09276378072167, K0: 109.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=133.0: 800\n",
      "Contribution to sigma_squared at K=133.0: 0.3167657244001767\n",
      "F: 109.98768744069243, K0: 109.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 20000\n",
      "Contribution to sigma_squared at K=125.0: 2.582507130647048\n",
      "Date 2023-05-15: The calculated VIX-equivalent index is 1960.29\n",
      "F: 109.11306063558195, K0: 109.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=128.0: 5000\n",
      "Contribution to sigma_squared at K=128.0: 1.5388451305123527\n",
      "F: 110.00815079729864, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 63100\n",
      "Contribution to sigma_squared at K=120.0: 4.455432195575837\n",
      "Date 2023-05-16: The calculated VIX-equivalent index is 2068.75\n",
      "F: 110.35788580875, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=119.0: 22500\n",
      "Contribution to sigma_squared at K=119.0: 1.6019048701964542\n",
      "F: 111.26318767893743, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 54000\n",
      "Contribution to sigma_squared at K=121.0: 3.7490330761728505\n",
      "Date 2023-05-17: The calculated VIX-equivalent index is 1957.95\n",
      "F: 110.97932938403851, K0: 110.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=125.0: 4000\n",
      "Contribution to sigma_squared at K=125.0: 1.2901237707944446\n",
      "Date 2023-05-18: Not enough data to calculate variance.\n",
      "F: 111.58784608412918, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=121.0: 16500\n",
      "Contribution to sigma_squared at K=121.0: 2.271108528009201\n",
      "F: 112.50323772116377, K0: 112.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=126.0: 25500\n",
      "Contribution to sigma_squared at K=126.0: 13.053647848218214\n",
      "Date 2023-05-19: The calculated VIX-equivalent index is 1892.59\n",
      "F: 110.95524311262308, K0: 110.0\n",
      "deltaK: 30.0\n",
      "Q_K at K=155.0: 1200\n",
      "Contribution to sigma_squared at K=155.0: 1.50852890749184\n",
      "F: 111.86544530035832, K0: 111.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=123.0: 35000\n",
      "Contribution to sigma_squared at K=123.0: 9.392484167061326\n",
      "Date 2023-05-22: The calculated VIX-equivalent index is 1938.69\n",
      "F: 110.63645051343507, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=122.0: 6000\n",
      "Contribution to sigma_squared at K=122.0: 0.405713447390997\n",
      "F: 111.54403754110146, K0: 111.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 39000\n",
      "Contribution to sigma_squared at K=123.0: 5.2314288111940135\n",
      "Date 2023-05-23: The calculated VIX-equivalent index is 1909.56\n",
      "F: 109.46824462053686, K0: 109.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 7800\n",
      "Contribution to sigma_squared at K=120.0: 0.5449958627532567\n",
      "F: 110.3662484727749, K0: 110.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=120.0: 42600\n",
      "Contribution to sigma_squared at K=120.0: 9.002799600033946\n",
      "Date 2023-05-24: The calculated VIX-equivalent index is 1959.29\n",
      "F: 110.69849271851928, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 5600\n",
      "Contribution to sigma_squared at K=121.0: 0.38472611093364334\n",
      "F: 111.60658869870757, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 40000\n",
      "Contribution to sigma_squared at K=121.0: 2.770586751335567\n",
      "Date 2023-05-25: The calculated VIX-equivalent index is 1768.83\n",
      "F: 111.52205936146125, K0: 111.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=120.0: 7000\n",
      "Contribution to sigma_squared at K=120.0: 0.48881351512291155\n",
      "F: 112.43691132847019, K0: 112.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=123.0: 27400\n",
      "Contribution to sigma_squared at K=123.0: 3.672198249519447\n",
      "Date 2023-05-26: The calculated VIX-equivalent index is 1760.95\n",
      "F: 110.84969494418415, K0: 110.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=122.0: 3500\n",
      "Contribution to sigma_squared at K=122.0: 0.4725044244020214\n",
      "F: 111.75903128573553, K0: 111.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=122.0: 29500\n",
      "Contribution to sigma_squared at K=122.0: 6.022811023102106\n",
      "Date 2023-05-29: The calculated VIX-equivalent index is 1845.41\n",
      "F: 109.44499253291359, K0: 109.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=128.0: 600\n",
      "Contribution to sigma_squared at K=128.0: 0.29425380003591023\n",
      "F: 110.3428056406638, K0: 110.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 13700\n",
      "Contribution to sigma_squared at K=123.0: 0.9169787103860791\n",
      "Date 2023-05-30: The calculated VIX-equivalent index is 1949.67\n",
      "F: 108.77851644828714, K0: 108.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=120.0: 1800\n",
      "Contribution to sigma_squared at K=120.0: 0.25102332155295404\n",
      "F: 109.67086223450043, K0: 109.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=129.0: 6000\n",
      "Contribution to sigma_squared at K=129.0: 2.1900058241091647\n",
      "Date 2023-05-31: The calculated VIX-equivalent index is 2061.97\n",
      "F: 112.95294847865523, K0: 112.0\n",
      "deltaK: 19.0\n",
      "Q_K at K=140.0: 1000\n",
      "Contribution to sigma_squared at K=140.0: 0.9727878892632837\n",
      "F: 113.879538497588, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 9700\n",
      "Contribution to sigma_squared at K=126.0: 1.2363157208838689\n",
      "Date 2023-06-02: The calculated VIX-equivalent index is 1787.74\n",
      "F: 112.99265254228489, K0: 112.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=118.0: 9000\n",
      "Contribution to sigma_squared at K=118.0: 0.6480655922038496\n",
      "F: 113.91956826665134, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 13700\n",
      "Contribution to sigma_squared at K=125.0: 0.8863171171534251\n",
      "Date 2023-06-05: The calculated VIX-equivalent index is 1739.40\n",
      "F: 114.87794071494501, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=119.0: 10000\n",
      "Contribution to sigma_squared at K=119.0: 0.7078151070191995\n",
      "F: 115.82032207546465, K0: 115.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 10000\n",
      "Contribution to sigma_squared at K=129.0: 1.8218126400227548\n",
      "Date 2023-06-06: The calculated VIX-equivalent index is 1813.35\n",
      "F: 115.72428166484802, K0: 115.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=134.0: 10200\n",
      "Contribution to sigma_squared at K=134.0: 4.553733321753425\n",
      "F: 116.67360583728497, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 17300\n",
      "Contribution to sigma_squared at K=127.0: 1.0836120335607708\n",
      "Date 2023-06-07: The calculated VIX-equivalent index is 1801.90\n",
      "F: 117.19032479305712, K0: 117.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 1500\n",
      "Contribution to sigma_squared at K=126.0: 0.28386053538205797\n",
      "F: 118.15167539728024, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 10500\n",
      "Contribution to sigma_squared at K=130.0: 0.6273130393421001\n",
      "Date 2023-06-09: The calculated VIX-equivalent index is 1793.73\n",
      "F: 117.40483297044352, K0: 117.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=128.0: 600\n",
      "Contribution to sigma_squared at K=128.0: 0.25649729456701925\n",
      "F: 118.36794325547906, K0: 118.0\n",
      "deltaK: 10.5\n",
      "Q_K at K=151.0: 4000\n",
      "Contribution to sigma_squared at K=151.0: 1.8582192716187067\n",
      "Date 2023-06-12: The calculated VIX-equivalent index is 1892.98\n",
      "F: 116.77677825386657, K0: 116.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.4143220570271347\n",
      "F: 117.73473640042708, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 6800\n",
      "Contribution to sigma_squared at K=132.0: 0.7871652093872261\n",
      "Date 2023-06-13: The calculated VIX-equivalent index is 1864.74\n",
      "F: 120.045530105288, K0: 120.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 15000\n",
      "Contribution to sigma_squared at K=130.0: 1.7897100486668234\n",
      "F: 121.27775576329468, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 10500\n",
      "Contribution to sigma_squared at K=138.0: 0.5615835924681307\n",
      "Date 2023-06-14: The calculated VIX-equivalent index is 1849.37\n",
      "F: 120.16394224834725, K0: 120.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=135.0: 5500\n",
      "Contribution to sigma_squared at K=135.0: 1.216680510865817\n",
      "F: 121.39738336586142, K0: 121.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=136.0: 22400\n",
      "Contribution to sigma_squared at K=136.0: 2.4663616731818947\n",
      "Date 2023-06-15: The calculated VIX-equivalent index is 1786.65\n",
      "F: 119.66278321294996, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 9500\n",
      "Contribution to sigma_squared at K=130.0: 0.5664108832822947\n",
      "F: 120.89108010708806, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 67300\n",
      "Contribution to sigma_squared at K=130.0: 4.053761618952936\n",
      "Date 2023-06-16: The calculated VIX-equivalent index is 1772.03\n",
      "F: 120.66482556463723, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 11500\n",
      "Contribution to sigma_squared at K=130.0: 0.6850553591858182\n",
      "F: 121.90340807536661, K0: 121.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=133.0: 42000\n",
      "Contribution to sigma_squared at K=133.0: 4.829761603790897\n",
      "Date 2023-06-19: The calculated VIX-equivalent index is 1732.31\n",
      "F: 120.3927473413711, K0: 120.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=140.0: 13200\n",
      "Contribution to sigma_squared at K=140.0: 5.422451302909682\n",
      "F: 121.62853706366933, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 9500\n",
      "Contribution to sigma_squared at K=139.0: 0.4999389530952825\n",
      "Date 2023-06-20: The calculated VIX-equivalent index is 1840.53\n",
      "F: 121.16038798462431, K0: 121.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 15000\n",
      "Contribution to sigma_squared at K=130.0: 1.7860583576802225\n",
      "F: 122.404057271417, K0: 122.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 14800\n",
      "Contribution to sigma_squared at K=137.0: 1.6030491183650963\n",
      "Date 2023-06-21: The calculated VIX-equivalent index is 1857.69\n",
      "F: 119.63028343517918, K0: 119.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=131.0: 10500\n",
      "Contribution to sigma_squared at K=131.0: 1.8463002925097332\n",
      "F: 120.85824673039015, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 23000\n",
      "Contribution to sigma_squared at K=135.0: 1.2824186730683498\n",
      "Date 2023-06-22: The calculated VIX-equivalent index is 1906.62\n",
      "F: 119.63852119569633, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 11300\n",
      "Contribution to sigma_squared at K=128.0: 0.6935314521205371\n",
      "F: 120.86656904865691, K0: 120.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=132.0: 38500\n",
      "Contribution to sigma_squared at K=132.0: 11.223432182333339\n",
      "Date 2023-06-23: The calculated VIX-equivalent index is 1865.10\n",
      "F: 118.79625695211439, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=127.0: 15500\n",
      "Contribution to sigma_squared at K=127.0: 0.9654988416463262\n",
      "F: 120.01565925525023, K0: 120.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 15400\n",
      "Contribution to sigma_squared at K=134.0: 1.741020074179304\n",
      "Date 2023-06-26: The calculated VIX-equivalent index is 1893.84\n",
      "F: 118.03836104917768, K0: 118.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 4100\n",
      "Contribution to sigma_squared at K=130.0: 0.731003049746015\n",
      "F: 119.24998381419262, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 9700\n",
      "Contribution to sigma_squared at K=134.0: 0.5481483076153219\n",
      "Date 2023-06-27: The calculated VIX-equivalent index is 1915.45\n",
      "F: 117.15893003833253, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 4000\n",
      "Contribution to sigma_squared at K=128.0: 0.24513996245405667\n",
      "F: 118.36152574956992, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 16900\n",
      "Contribution to sigma_squared at K=133.0: 0.9691536682895868\n",
      "Date 2023-06-28: The calculated VIX-equivalent index is 1907.71\n",
      "F: 118.50119095773127, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=129.0: 3000\n",
      "Contribution to sigma_squared at K=129.0: 0.7236398102173905\n",
      "F: 119.71756451095226, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 29100\n",
      "Contribution to sigma_squared at K=132.0: 1.693171346138171\n",
      "Date 2023-06-30: The calculated VIX-equivalent index is 1854.40\n",
      "F: 119.98745699335434, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 16500\n",
      "Contribution to sigma_squared at K=125.0: 1.058776729219311\n",
      "F: 121.21908655104389, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 38000\n",
      "Contribution to sigma_squared at K=131.0: 2.2429347137978186\n",
      "Date 2023-07-03: The calculated VIX-equivalent index is 1842.98\n",
      "F: 119.35464826756854, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=129.0: 900\n",
      "Contribution to sigma_squared at K=129.0: 0.10841935890209717\n",
      "F: 120.57978226355046, K0: 120.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 10000\n",
      "Contribution to sigma_squared at K=135.0: 1.6668734383984851\n",
      "Date 2023-07-04: The calculated VIX-equivalent index is 1792.10\n",
      "F: 119.79363469683875, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 900\n",
      "Contribution to sigma_squared at K=130.0: 0.053363319390927054\n",
      "F: 121.02327473599603, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 8500\n",
      "Contribution to sigma_squared at K=136.0: 0.46522527214819004\n",
      "Date 2023-07-05: The calculated VIX-equivalent index is 1836.10\n",
      "F: 117.63145545749954, K0: 117.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 500\n",
      "Contribution to sigma_squared at K=129.0: 0.09029675664999473\n",
      "F: 118.83890147799085, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=135.0: 7000\n",
      "Contribution to sigma_squared at K=135.0: 0.7774204660887188\n",
      "Date 2023-07-06: The calculated VIX-equivalent index is 1925.70\n",
      "F: 119.07157735910003, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 6900\n",
      "Contribution to sigma_squared at K=125.0: 0.4422447222344008\n",
      "F: 120.29380573055647, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 9000\n",
      "Contribution to sigma_squared at K=135.0: 0.4996244975118315\n",
      "Date 2023-07-07: The calculated VIX-equivalent index is 1853.71\n",
      "F: 118.01128677037786, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.005920613798515136\n",
      "F: 119.22263162732757, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 6000\n",
      "Contribution to sigma_squared at K=135.0: 0.3327915642190927\n",
      "Date 2023-07-10: The calculated VIX-equivalent index is 1778.66\n",
      "F: 117.58982545083951, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.005918886528959067\n",
      "F: 118.79684415377636, K0: 118.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 6000\n",
      "Contribution to sigma_squared at K=135.0: 0.9980834285635775\n",
      "Date 2023-07-11: The calculated VIX-equivalent index is 1931.44\n",
      "F: 118.87429563789772, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 7800\n",
      "Contribution to sigma_squared at K=133.0: 0.4454782231880923\n",
      "F: 119.84946040631945, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=133.0: 32800\n",
      "Contribution to sigma_squared at K=133.0: 3.7773205545204487\n",
      "Date 2023-07-12: The calculated VIX-equivalent index is 1742.22\n",
      "F: 120.45294140770953, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 14800\n",
      "Contribution to sigma_squared at K=137.0: 0.7963959087709154\n",
      "F: 121.44105632425433, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 51800\n",
      "Contribution to sigma_squared at K=132.0: 6.054363032904958\n",
      "Date 2023-07-13: The calculated VIX-equivalent index is 2004.31\n",
      "F: 118.8494215913331, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 4500\n",
      "Contribution to sigma_squared at K=133.0: 0.25685673174325024\n",
      "Date 2023-07-14: Not enough data to calculate variance.\n",
      "F: 118.84255078336493, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 13400\n",
      "Contribution to sigma_squared at K=129.0: 0.8120826332201497\n",
      "F: 119.81745513835116, K0: 119.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=131.0: 34000\n",
      "Contribution to sigma_squared at K=131.0: 8.0578520435537\n",
      "Date 2023-07-18: The calculated VIX-equivalent index is 1581.72\n",
      "F: 118.5163881185967, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=133.0: 2500\n",
      "Contribution to sigma_squared at K=133.0: 0.28498030623993553\n",
      "F: 119.48861685445307, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=135.0: 12300\n",
      "Contribution to sigma_squared at K=135.0: 3.430076701719426\n",
      "Date 2023-07-19: The calculated VIX-equivalent index is 1729.20\n",
      "F: 119.01684079245572, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 5200\n",
      "Contribution to sigma_squared at K=132.0: 0.6015986936240164\n",
      "F: 119.9931749054518, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 37500\n",
      "Contribution to sigma_squared at K=130.0: 9.019326080526373\n",
      "Date 2023-07-20: The calculated VIX-equivalent index is 1681.47\n",
      "F: 121.13223876733177, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 34900\n",
      "Contribution to sigma_squared at K=133.0: 1.988002077227479\n",
      "F: 122.12592618253015, K0: 122.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 13900\n",
      "Contribution to sigma_squared at K=137.0: 0.7523440336047814\n",
      "Date 2023-07-21: The calculated VIX-equivalent index is 1552.82\n",
      "F: 122.1587476486152, K0: 122.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 10000\n",
      "Contribution to sigma_squared at K=132.0: 0.5777855416936323\n",
      "F: 123.16085585226183, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 29600\n",
      "Contribution to sigma_squared at K=134.0: 1.6731881232372532\n",
      "Date 2023-07-24: The calculated VIX-equivalent index is 1611.01\n",
      "F: 122.79347870711605, K0: 122.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=136.0: 2800\n",
      "Contribution to sigma_squared at K=136.0: 0.6094358802879644\n",
      "F: 123.80079381745644, K0: 123.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=141.0: 7900\n",
      "Contribution to sigma_squared at K=141.0: 1.6128159039308978\n",
      "Date 2023-07-25: The calculated VIX-equivalent index is 1628.98\n",
      "F: 123.31366160763139, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 23500\n",
      "Contribution to sigma_squared at K=130.0: 1.3990790468495076\n",
      "Date 2023-07-26: Not enough data to calculate variance.\n",
      "F: 120.69190058439972, K0: 120.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 6000\n",
      "Contribution to sigma_squared at K=132.0: 0.6927360033180185\n",
      "F: 121.68197576130989, K0: 121.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=134.0: 30200\n",
      "Contribution to sigma_squared at K=134.0: 6.822441807275462\n",
      "Date 2023-07-27: The calculated VIX-equivalent index is 1747.78\n",
      "F: 120.85525792093173, K0: 120.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 4900\n",
      "Contribution to sigma_squared at K=132.0: 0.5655693563405588\n",
      "F: 121.84667317155923, K0: 121.0\n",
      "deltaK: 68.0\n",
      "Q_K at K=200.0: 700\n",
      "Contribution to sigma_squared at K=200.0: 1.2064317136351435\n",
      "Date 2023-07-28: The calculated VIX-equivalent index is 1932.01\n",
      "F: 122.51360090040502, K0: 122.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 4900\n",
      "Contribution to sigma_squared at K=132.0: 0.28253725303947325\n",
      "F: 123.51862008146057, K0: 123.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=137.0: 13000\n",
      "Contribution to sigma_squared at K=137.0: 2.8063241689420506\n",
      "Date 2023-07-31: The calculated VIX-equivalent index is 1604.03\n",
      "F: 121.78022231291241, K0: 121.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=136.0: 1500\n",
      "Contribution to sigma_squared at K=136.0: 0.3258173564411463\n",
      "F: 122.77922534929516, K0: 122.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=139.0: 8100\n",
      "Contribution to sigma_squared at K=139.0: 4.245260323999454\n",
      "Date 2023-08-01: The calculated VIX-equivalent index is 1844.03\n",
      "F: 121.35342933215375, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 11100\n",
      "Contribution to sigma_squared at K=129.0: 0.6697575552521579\n",
      "F: 122.3489312459766, K0: 122.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=139.0: 7600\n",
      "Contribution to sigma_squared at K=139.0: 2.3892270981868142\n",
      "Date 2023-08-02: The calculated VIX-equivalent index is 1718.01\n",
      "F: 121.0440385875082, K0: 121.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 7300\n",
      "Contribution to sigma_squared at K=130.0: 0.8671884713177315\n",
      "F: 122.03700246775337, K0: 122.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=138.0: 5700\n",
      "Contribution to sigma_squared at K=138.0: 1.2116359343544474\n",
      "Date 2023-08-03: The calculated VIX-equivalent index is 1611.84\n",
      "F: 119.92685400251884, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 3000\n",
      "Contribution to sigma_squared at K=131.0: 0.1754281522322067\n",
      "F: 120.91065325182963, K0: 120.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=136.0: 12200\n",
      "Contribution to sigma_squared at K=136.0: 5.338764364632265\n",
      "Date 2023-08-04: The calculated VIX-equivalent index is 1841.24\n",
      "F: 119.69340581992115, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=132.0: 2000\n",
      "Contribution to sigma_squared at K=132.0: 0.5754301414298542\n",
      "F: 120.67529001735551, K0: 120.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=141.0: 7200\n",
      "Contribution to sigma_squared at K=141.0: 3.6608578589968097\n",
      "Date 2023-08-07: The calculated VIX-equivalent index is 1737.17\n",
      "F: 119.36855068138475, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=132.0: 1000\n",
      "Contribution to sigma_squared at K=132.0: 0.28763113322138667\n",
      "F: 120.34776998575504, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 10000\n",
      "Contribution to sigma_squared at K=132.0: 0.5799813311642689\n",
      "Date 2023-08-08: The calculated VIX-equivalent index is 1721.94\n",
      "F: 118.65086300680699, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 100\n",
      "Contribution to sigma_squared at K=136.0: 0.005417628422401644\n",
      "F: 119.62419488420053, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 6600\n",
      "Contribution to sigma_squared at K=134.0: 0.7426761758633567\n",
      "Date 2023-08-09: The calculated VIX-equivalent index is 1771.28\n",
      "F: 118.55697433196387, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 100\n",
      "Contribution to sigma_squared at K=132.0: 0.011498533267619852\n",
      "F: 119.52953600981706, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 6000\n",
      "Contribution to sigma_squared at K=134.0: 0.674963189826843\n",
      "Date 2023-08-10: The calculated VIX-equivalent index is 1665.18\n",
      "F: 118.23751142406171, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.023703194528471017\n",
      "F: 119.20745244308424, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 5700\n",
      "Contribution to sigma_squared at K=133.0: 0.325351860208117\n",
      "Date 2023-08-11: The calculated VIX-equivalent index is 1664.58\n",
      "F: 116.87773546629009, K0: 116.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=127.0: 1500\n",
      "Contribution to sigma_squared at K=127.0: 0.2326361829505219\n",
      "F: 117.83652179791909, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=131.0: 8400\n",
      "Contribution to sigma_squared at K=131.0: 0.9875708318204797\n",
      "Date 2023-08-14: The calculated VIX-equivalent index is 1786.15\n",
      "F: 116.20532153807976, K0: 116.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=131.0: 100\n",
      "Contribution to sigma_squared at K=131.0: 0.03497320051491459\n",
      "F: 117.15859183809681, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 12900\n",
      "Contribution to sigma_squared at K=128.0: 0.794044087344374\n",
      "Date 2023-08-15: The calculated VIX-equivalent index is 1934.09\n",
      "F: 116.53975508503196, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 8700\n",
      "Contribution to sigma_squared at K=128.0: 1.0707237485981569\n",
      "F: 117.73599518049942, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 26000\n",
      "Contribution to sigma_squared at K=132.0: 3.039756289180114\n",
      "Date 2023-08-16: The calculated VIX-equivalent index is 1786.25\n",
      "F: 115.89171753954538, K0: 115.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=132.0: 5000\n",
      "Contribution to sigma_squared at K=132.0: 1.15692056466157\n",
      "F: 117.08130575476207, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 16700\n",
      "Contribution to sigma_squared at K=132.0: 1.951889240338085\n",
      "Date 2023-08-17: The calculated VIX-equivalent index is 1789.08\n",
      "F: 116.28737322109373, K0: 116.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 30400\n",
      "Contribution to sigma_squared at K=130.0: 7.250059306013374\n",
      "Date 2023-08-18: Not enough data to calculate variance.\n",
      "F: 115.19986321473738, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 8000\n",
      "Contribution to sigma_squared at K=125.0: 0.5154475662576563\n",
      "F: 116.38234978568724, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 12900\n",
      "Contribution to sigma_squared at K=132.0: 0.7529940392985575\n",
      "Date 2023-08-21: The calculated VIX-equivalent index is 1764.21\n",
      "F: 116.90403439583035, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 9800\n",
      "Contribution to sigma_squared at K=126.0: 1.2425183026682307\n",
      "F: 118.10401369185824, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 15400\n",
      "Contribution to sigma_squared at K=132.0: 1.7973217328356639\n",
      "Date 2023-08-22: The calculated VIX-equivalent index is 1668.43\n",
      "F: 118.86066978101957, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=129.0: 6000\n",
      "Contribution to sigma_squared at K=129.0: 0.725542605487549\n",
      "F: 120.08073325946454, K0: 120.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=138.0: 5000\n",
      "Contribution to sigma_squared at K=138.0: 1.6012507079583744\n",
      "Date 2023-08-23: The calculated VIX-equivalent index is 1603.56\n",
      "F: 117.71051301620481, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 11500\n",
      "Contribution to sigma_squared at K=126.0: 0.7286032869365252\n",
      "F: 118.91877053506852, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 18900\n",
      "Contribution to sigma_squared at K=132.0: 1.1022585488907746\n",
      "Date 2023-08-24: The calculated VIX-equivalent index is 1428.83\n",
      "F: 116.48116576593407, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 8800\n",
      "Contribution to sigma_squared at K=125.0: 0.5663309589611459\n",
      "F: 117.67680446239721, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 14600\n",
      "Contribution to sigma_squared at K=131.0: 0.8642772466523387\n",
      "Date 2023-08-25: The calculated VIX-equivalent index is 1603.60\n",
      "F: 117.66903679723359, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 5400\n",
      "Contribution to sigma_squared at K=125.0: 0.34721720324679595\n",
      "F: 118.87686857712005, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 12600\n",
      "Contribution to sigma_squared at K=132.0: 1.4679637702837895\n",
      "Date 2023-08-28: The calculated VIX-equivalent index is 1688.52\n",
      "F: 118.92296424267059, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 7000\n",
      "Contribution to sigma_squared at K=128.0: 0.4291201250523691\n",
      "F: 120.14366715212091, K0: 120.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=138.0: 5500\n",
      "Contribution to sigma_squared at K=138.0: 0.8791474311817336\n",
      "Date 2023-08-29: The calculated VIX-equivalent index is 1627.26\n",
      "F: 118.01620480423443, K0: 118.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 1400\n",
      "Contribution to sigma_squared at K=129.0: 0.2534217776629787\n",
      "F: 119.22760014309294, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 16500\n",
      "Contribution to sigma_squared at K=131.0: 0.9753277347707674\n",
      "Date 2023-08-30: The calculated VIX-equivalent index is 1697.63\n",
      "F: 116.18166982578492, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 3500\n",
      "Contribution to sigma_squared at K=126.0: 0.22129637429135657\n",
      "F: 117.37423430047907, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 9400\n",
      "Contribution to sigma_squared at K=132.0: 0.5470946824599087\n",
      "Date 2023-08-31: The calculated VIX-equivalent index is 1686.33\n",
      "F: 118.30647036110813, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=125.0: 6200\n",
      "Contribution to sigma_squared at K=125.0: 0.7963835574115317\n",
      "F: 119.52084517505834, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 19000\n",
      "Contribution to sigma_squared at K=130.0: 1.1397843249499142\n",
      "Date 2023-09-01: The calculated VIX-equivalent index is 1647.62\n",
      "F: 118.08631108153948, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 9800\n",
      "Contribution to sigma_squared at K=124.0: 0.6390328361464818\n",
      "F: 119.29842603697688, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 12500\n",
      "Contribution to sigma_squared at K=132.0: 1.4533418297615952\n",
      "Date 2023-09-04: The calculated VIX-equivalent index is 1688.19\n",
      "F: 117.60550008600836, K0: 117.0\n",
      "deltaK: 11.0\n",
      "Q_K at K=140.0: 1400\n",
      "Contribution to sigma_squared at K=140.0: 0.7875504788249122\n",
      "F: 118.81267968362924, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 9500\n",
      "Contribution to sigma_squared at K=133.0: 0.5438376014108914\n",
      "Date 2023-09-05: The calculated VIX-equivalent index is 1746.29\n",
      "F: 116.22247817571224, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 2000\n",
      "Contribution to sigma_squared at K=132.0: 0.23003777617249954\n",
      "F: 117.41546153393995, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 8800\n",
      "Contribution to sigma_squared at K=132.0: 1.0225557496913753\n",
      "Date 2023-09-06: The calculated VIX-equivalent index is 1612.97\n",
      "F: 115.4817539694392, K0: 115.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.023703194528471017\n",
      "F: 116.66713405104618, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 6700\n",
      "Contribution to sigma_squared at K=132.0: 0.7780825723131054\n",
      "Date 2023-09-08: The calculated VIX-equivalent index is 1619.48\n",
      "F: 116.9515685398706, K0: 116.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=131.0: 100\n",
      "Contribution to sigma_squared at K=131.0: 0.03498340651299078\n",
      "F: 118.15203575737182, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 9000\n",
      "Contribution to sigma_squared at K=133.0: 0.5143133804533578\n",
      "Date 2023-09-11: The calculated VIX-equivalent index is 1762.47\n",
      "F: 118.00254585717191, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 2500\n",
      "Contribution to sigma_squared at K=127.0: 0.3100910854343364\n",
      "F: 119.21380099168451, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 8500\n",
      "Contribution to sigma_squared at K=131.0: 0.5005393337844699\n",
      "Date 2023-09-12: The calculated VIX-equivalent index is 1673.30\n",
      "F: 119.3890052730844, K0: 119.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=134.0: 6000\n",
      "Contribution to sigma_squared at K=134.0: 1.012740239813668\n",
      "F: 120.4035186859701, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 103600\n",
      "Contribution to sigma_squared at K=128.0: 6.442431645609261\n",
      "Date 2023-09-13: The calculated VIX-equivalent index is 1723.87\n",
      "F: 120.58187416765983, K0: 120.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=133.0: 6600\n",
      "Contribution to sigma_squared at K=133.0: 0.7536662864030681\n",
      "F: 121.6065240373373, K0: 121.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 42600\n",
      "Contribution to sigma_squared at K=132.0: 2.4902618830590937\n",
      "Date 2023-09-14: The calculated VIX-equivalent index is 1753.55\n",
      "F: 119.90654150524999, K0: 119.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=138.0: 2500\n",
      "Contribution to sigma_squared at K=138.0: 0.6627253156150602\n",
      "F: 120.92545270541925, K0: 120.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=132.0: 39500\n",
      "Contribution to sigma_squared at K=132.0: 9.23348802315621\n",
      "Date 2023-09-15: The calculated VIX-equivalent index is 1749.69\n",
      "F: 119.32818195174822, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 6400\n",
      "Contribution to sigma_squared at K=132.0: 0.3705387871107449\n",
      "Date 2023-09-18: Not enough data to calculate variance.\n",
      "F: 118.84717978709526, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 5400\n",
      "Contribution to sigma_squared at K=132.0: 0.6251017839251501\n",
      "F: 119.85708901367653, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 24900\n",
      "Contribution to sigma_squared at K=132.0: 1.453453610739076\n",
      "Date 2023-09-19: The calculated VIX-equivalent index is 1603.03\n",
      "F: 119.66901657266463, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 8600\n",
      "Contribution to sigma_squared at K=130.0: 1.0261004279023123\n",
      "F: 120.68590939409418, K0: 120.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=131.0: 41000\n",
      "Contribution to sigma_squared at K=131.0: 12.1460269774155\n",
      "Date 2023-09-20: The calculated VIX-equivalent index is 1577.51\n",
      "F: 117.06366395711665, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 3200\n",
      "Contribution to sigma_squared at K=130.0: 0.19084671165598294\n",
      "F: 118.05841767815143, K0: 118.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=136.0: 8100\n",
      "Contribution to sigma_squared at K=136.0: 0.8902940084598839\n",
      "Date 2023-09-21: The calculated VIX-equivalent index is 1710.72\n",
      "F: 116.8920632250678, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 1000\n",
      "Contribution to sigma_squared at K=132.0: 0.11565830466713525\n",
      "F: 117.88535876120584, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 19000\n",
      "Contribution to sigma_squared at K=131.0: 1.125072588799028\n",
      "Date 2023-09-22: The calculated VIX-equivalent index is 1655.59\n",
      "F: 116.70519158958587, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 1000\n",
      "Contribution to sigma_squared at K=129.0: 0.18149153197169368\n",
      "F: 117.69689917564217, K0: 117.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=129.0: 27000\n",
      "Contribution to sigma_squared at K=129.0: 11.531127156142029\n",
      "Date 2023-09-25: The calculated VIX-equivalent index is 1634.35\n",
      "F: 114.92881572376534, K0: 114.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 700\n",
      "Contribution to sigma_squared at K=130.0: 0.16674742665393766\n",
      "F: 115.90542847643998, K0: 114.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=132.0: 10000\n",
      "Contribution to sigma_squared at K=132.0: 3.4951518340090226\n",
      "Date 2023-09-26: The calculated VIX-equivalent index is 1653.92\n",
      "F: 115.02972784760257, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 1500\n",
      "Contribution to sigma_squared at K=132.0: 0.17323453997242744\n",
      "F: 116.00719810556355, K0: 116.0\n",
      "deltaK: 9.0\n",
      "Q_K at K=136.0: 8200\n",
      "Contribution to sigma_squared at K=136.0: 4.0486896283604645\n",
      "Date 2023-09-27: The calculated VIX-equivalent index is 1773.97\n",
      "F: 116.40809473615407, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 2000\n",
      "Contribution to sigma_squared at K=132.0: 0.23091200110600618\n",
      "F: 117.3972777284084, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 27500\n",
      "Contribution to sigma_squared at K=127.0: 3.4591107645444317\n",
      "Date 2023-09-28: The calculated VIX-equivalent index is 1655.97\n",
      "F: 117.21318271940521, K0: 117.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=132.0: 600\n",
      "Contribution to sigma_squared at K=132.0: 0.1731334764307833\n",
      "F: 118.2092069828109, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=128.0: 30000\n",
      "Contribution to sigma_squared at K=128.0: 7.427519645929694\n",
      "Date 2023-09-29: The calculated VIX-equivalent index is 1464.86\n",
      "F: 115.59525793853632, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 6000\n",
      "Contribution to sigma_squared at K=124.0: 0.39204451386946376\n",
      "F: 116.57753381374263, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=121.0: 106200\n",
      "Contribution to sigma_squared at K=121.0: 14.698943407237534\n",
      "Date 2023-10-02: The calculated VIX-equivalent index is 1538.87\n",
      "F: 113.91653040273033, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 1000\n",
      "Contribution to sigma_squared at K=127.0: 0.12454415079950074\n",
      "F: 114.88454121560733, K0: 114.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=126.0: 26500\n",
      "Contribution to sigma_squared at K=126.0: 6.763015803545477\n",
      "Date 2023-10-03: The calculated VIX-equivalent index is 1784.85\n",
      "F: 114.07247780864459, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=124.0: 1800\n",
      "Contribution to sigma_squared at K=124.0: 0.23508947908185085\n",
      "F: 115.04181379157927, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 8700\n",
      "Contribution to sigma_squared at K=129.0: 0.5294058554351057\n",
      "Date 2023-10-04: The calculated VIX-equivalent index is 1697.05\n",
      "F: 113.71459958227545, K0: 113.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=132.0: 100\n",
      "Contribution to sigma_squared at K=132.0: 0.02880510657098236\n",
      "F: 114.68089447897275, K0: 114.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=127.0: 12500\n",
      "Contribution to sigma_squared at K=127.0: 2.353672404196931\n",
      "Date 2023-10-05: The calculated VIX-equivalent index is 1586.18\n",
      "F: 114.57008075574386, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 2000\n",
      "Contribution to sigma_squared at K=124.0: 0.1305290721668791\n",
      "F: 115.54364514198058, K0: 115.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 5000\n",
      "Contribution to sigma_squared at K=130.0: 1.4970929833544908\n",
      "Date 2023-10-06: The calculated VIX-equivalent index is 1769.98\n",
      "F: 115.45887040184664, K0: 115.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=124.0: 1000\n",
      "Contribution to sigma_squared at K=124.0: 0.19562229677953522\n",
      "F: 116.43998731785896, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=128.0: 13000\n",
      "Contribution to sigma_squared at K=128.0: 2.4069107253143325\n",
      "Date 2023-10-09: The calculated VIX-equivalent index is 1748.59\n",
      "F: 117.00976110607616, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 2500\n",
      "Contribution to sigma_squared at K=125.0: 0.16037391568798215\n",
      "F: 118.004056785223, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=130.0: 10000\n",
      "Contribution to sigma_squared at K=130.0: 2.392554736841406\n",
      "Date 2023-10-10: The calculated VIX-equivalent index is 1627.99\n",
      "F: 117.29005644248635, K0: 117.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=130.0: 500\n",
      "Contribution to sigma_squared at K=130.0: 0.20752401985360522\n",
      "F: 118.28673394379267, K0: 118.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 9600\n",
      "Contribution to sigma_squared at K=130.0: 0.5740456169016551\n",
      "Date 2023-10-11: The calculated VIX-equivalent index is 1671.73\n",
      "F: 115.9230773485023, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 100\n",
      "Contribution to sigma_squared at K=130.0: 0.011851597264235509\n",
      "F: 116.90813888380902, K0: 116.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 3500\n",
      "Contribution to sigma_squared at K=132.0: 0.40575008252848344\n",
      "Date 2023-10-13: The calculated VIX-equivalent index is 1664.71\n",
      "F: 116.60187453139174, K0: 116.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=132.0: 100\n",
      "Contribution to sigma_squared at K=132.0: 0.04019792311549246\n",
      "F: 117.59270417612437, K0: 117.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 6000\n",
      "Contribution to sigma_squared at K=130.0: 0.35825546874673925\n",
      "Date 2023-10-16: The calculated VIX-equivalent index is 1767.78\n",
      "F: 116.92747928793132, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 4400\n",
      "Contribution to sigma_squared at K=130.0: 0.26264403140826115\n",
      "F: 117.85228163159007, K0: 117.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 24000\n",
      "Contribution to sigma_squared at K=130.0: 2.8878691037819357\n",
      "Date 2023-10-17: The calculated VIX-equivalent index is 1766.25\n",
      "F: 115.02886689308146, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 6900\n",
      "Contribution to sigma_squared at K=128.0: 0.42472125602140937\n",
      "F: 115.93865273930821, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 18000\n",
      "Contribution to sigma_squared at K=130.0: 2.1652699514101266\n",
      "Date 2023-10-18: The calculated VIX-equivalent index is 1863.81\n",
      "F: 114.9395145996913, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 8600\n",
      "Contribution to sigma_squared at K=126.0: 1.0922837762376592\n",
      "F: 115.84859374112254, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 15700\n",
      "Contribution to sigma_squared at K=130.0: 0.944022796428427\n",
      "Date 2023-10-19: The calculated VIX-equivalent index is 1807.59\n",
      "F: 114.05024728039157, K0: 114.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 4000\n",
      "Contribution to sigma_squared at K=127.0: 0.4999239610307694\n",
      "F: 114.95229303235755, K0: 114.0\n",
      "deltaK: 10.0\n",
      "Q_K at K=138.0: 1500\n",
      "Contribution to sigma_squared at K=138.0: 0.800158276029166\n",
      "Date 2023-10-20: The calculated VIX-equivalent index is 1871.68\n",
      "F: 113.57709248924418, K0: 113.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=126.0: 7100\n",
      "Contribution to sigma_squared at K=126.0: 0.9007173022572849\n",
      "F: 114.47539596726024, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=126.0: 25000\n",
      "Contribution to sigma_squared at K=126.0: 1.5983120631711707\n",
      "Date 2023-10-23: The calculated VIX-equivalent index is 1797.10\n",
      "F: 114.5279189215759, K0: 114.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=131.0: 2500\n",
      "Contribution to sigma_squared at K=131.0: 0.8799605452890142\n",
      "F: 115.43374267214372, K0: 115.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=128.0: 18500\n",
      "Contribution to sigma_squared at K=128.0: 2.2914887256551943\n",
      "Date 2023-10-24: The calculated VIX-equivalent index is 1770.48\n",
      "F: 113.55657527975097, K0: 113.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=126.0: 5300\n",
      "Contribution to sigma_squared at K=126.0: 1.0079612761441257\n",
      "F: 114.45471648313715, K0: 114.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=129.0: 12000\n",
      "Contribution to sigma_squared at K=129.0: 2.9259778761374506\n",
      "Date 2023-10-25: The calculated VIX-equivalent index is 1755.88\n",
      "F: 115.48230247349495, K0: 115.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=125.0: 6200\n",
      "Contribution to sigma_squared at K=125.0: 1.197716446193496\n",
      "F: 116.39567463057027, K0: 116.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 10000\n",
      "Contribution to sigma_squared at K=131.0: 0.5909352693069173\n",
      "Date 2023-10-26: The calculated VIX-equivalent index is 1722.52\n",
      "F: 113.96446618456625, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 8400\n",
      "Contribution to sigma_squared at K=123.0: 0.558474617309089\n",
      "F: 114.86583347703795, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 8400\n",
      "Contribution to sigma_squared at K=133.0: 0.4814284904085198\n",
      "Date 2023-10-27: The calculated VIX-equivalent index is 1907.38\n",
      "F: 113.0910938422088, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 6900\n",
      "Contribution to sigma_squared at K=123.0: 0.4583456220393056\n",
      "F: 113.98555346170221, K0: 112.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 13500\n",
      "Contribution to sigma_squared at K=130.0: 4.045690870578006\n",
      "Date 2023-10-30: The calculated VIX-equivalent index is 2054.29\n",
      "F: 113.67311534281949, K0: 113.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=121.0: 11000\n",
      "Contribution to sigma_squared at K=121.0: 0.7548305090479431\n",
      "F: 114.57217828439855, K0: 114.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=124.0: 33200\n",
      "Contribution to sigma_squared at K=124.0: 2.186470498117784\n",
      "Date 2023-10-31: The calculated VIX-equivalent index is 1915.46\n",
      "F: 115.5576172727623, K0: 115.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=123.0: 5500\n",
      "Contribution to sigma_squared at K=123.0: 0.36513481873713755\n",
      "F: 116.47158510934169, K0: 116.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 12300\n",
      "Contribution to sigma_squared at K=130.0: 2.2103540882825814\n",
      "Date 2023-11-01: The calculated VIX-equivalent index is 1793.38\n",
      "F: 118.6090196892951, K0: 118.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=130.0: 3500\n",
      "Contribution to sigma_squared at K=130.0: 1.0394382361685137\n",
      "F: 119.54712166545775, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 13500\n",
      "Contribution to sigma_squared at K=132.0: 0.783889158673651\n",
      "Date 2023-11-03: The calculated VIX-equivalent index is 1646.91\n",
      "F: 118.7773143037713, K0: 118.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=129.0: 1500\n",
      "Contribution to sigma_squared at K=129.0: 0.27120661686446174\n",
      "F: 119.71674735501436, K0: 118.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=141.0: 5000\n",
      "Contribution to sigma_squared at K=141.0: 1.016904960832447\n",
      "Date 2023-11-06: The calculated VIX-equivalent index is 1759.24\n",
      "F: 119.5816727908452, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=125.0: 7500\n",
      "Contribution to sigma_squared at K=125.0: 0.4812621496451414\n",
      "F: 120.52746767096303, K0: 120.0\n",
      "deltaK: 28.0\n",
      "Q_K at K=162.0: 3200\n",
      "Contribution to sigma_squared at K=162.0: 3.450164938244465\n",
      "Date 2023-11-07: The calculated VIX-equivalent index is 1910.28\n",
      "F: 119.45518266596544, K0: 119.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.059309880062123566\n",
      "F: 120.39997711090197, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 9000\n",
      "Contribution to sigma_squared at K=135.0: 0.4988961247213779\n",
      "Date 2023-11-08: The calculated VIX-equivalent index is 1588.41\n",
      "F: 119.27751160892122, K0: 119.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=127.0: 300\n",
      "Contribution to sigma_squared at K=127.0: 0.03727613192413943\n",
      "F: 120.22090081865595, K0: 120.0\n",
      "deltaK: 14.0\n",
      "Q_K at K=148.0: 2000\n",
      "Contribution to sigma_squared at K=148.0: 1.291049933889024\n",
      "Date 2023-11-09: The calculated VIX-equivalent index is 1723.54\n",
      "F: 120.77940169829577, K0: 120.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=130.0: 1000\n",
      "Contribution to sigma_squared at K=130.0: 0.17782583756361683\n",
      "F: 121.73466965101741, K0: 121.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 9000\n",
      "Contribution to sigma_squared at K=134.0: 1.0121494158624091\n",
      "Date 2023-11-10: The calculated VIX-equivalent index is 1686.52\n",
      "F: 120.51561627917964, K0: 120.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=129.0: 500\n",
      "Contribution to sigma_squared at K=129.0: 0.03007258354935938\n",
      "F: 121.46879790133718, K0: 121.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=137.0: 15000\n",
      "Contribution to sigma_squared at K=137.0: 2.418649536784332\n",
      "Date 2023-11-13: The calculated VIX-equivalent index is 1715.66\n",
      "F: 123.23765578914201, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=128.0: 1000\n",
      "Contribution to sigma_squared at K=128.0: 0.06107078442071887\n",
      "F: 124.21236655512165, K0: 124.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 13100\n",
      "Contribution to sigma_squared at K=135.0: 0.7249008414813025\n",
      "Date 2023-11-14: The calculated VIX-equivalent index is 1588.00\n",
      "F: 125.62503617012014, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 13600\n",
      "Contribution to sigma_squared at K=135.0: 0.7521297703534142\n",
      "F: 126.91453351934315, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 47600\n",
      "Contribution to sigma_squared at K=137.0: 2.582393286875731\n",
      "Date 2023-11-16: The calculated VIX-equivalent index is 1582.03\n",
      "F: 125.72337674258281, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 9100\n",
      "Contribution to sigma_squared at K=137.0: 0.48853417163230584\n",
      "F: 127.01388352361477, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 109000\n",
      "Contribution to sigma_squared at K=133.0: 6.272678992395357\n",
      "Date 2023-11-17: The calculated VIX-equivalent index is 1585.70\n",
      "F: 126.43503966890405, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 9000\n",
      "Contribution to sigma_squared at K=136.0: 0.4897252609456856\n",
      "F: 127.73285142261511, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 22000\n",
      "Contribution to sigma_squared at K=140.0: 3.42381930097616\n",
      "Date 2023-11-21: The calculated VIX-equivalent index is 1538.35\n",
      "F: 126.80993918929025, K0: 126.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=140.0: 3500\n",
      "Contribution to sigma_squared at K=140.0: 0.8983448287141595\n",
      "F: 128.11159915632325, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=138.0: 45500\n",
      "Contribution to sigma_squared at K=138.0: 9.714254294947471\n",
      "Date 2023-11-22: The calculated VIX-equivalent index is 1467.21\n",
      "F: 127.31655695771596, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 20000\n",
      "Contribution to sigma_squared at K=134.0: 1.120352725348366\n",
      "F: 128.62341718012297, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=139.0: 31000\n",
      "Contribution to sigma_squared at K=139.0: 6.521712035039961\n",
      "Date 2023-11-23: The calculated VIX-equivalent index is 1501.53\n",
      "F: 126.21504951222495, K0: 126.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 1500\n",
      "Contribution to sigma_squared at K=140.0: 0.230868190816069\n",
      "F: 127.5106031434109, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 26500\n",
      "Contribution to sigma_squared at K=140.0: 1.3735125052059016\n",
      "Date 2023-11-24: The calculated VIX-equivalent index is 1697.64\n",
      "F: 126.31979869549875, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 2000\n",
      "Contribution to sigma_squared at K=137.0: 0.10705731872159545\n",
      "F: 127.61642754065701, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=139.0: 22500\n",
      "Contribution to sigma_squared at K=139.0: 2.3639896572035557\n",
      "Date 2023-11-27: The calculated VIX-equivalent index is 1600.26\n",
      "F: 127.09335555467955, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=133.0: 16500\n",
      "Contribution to sigma_squared at K=133.0: 1.8737491116538487\n",
      "F: 128.39792469223332, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 43500\n",
      "Contribution to sigma_squared at K=137.0: 4.703423214326555\n",
      "Date 2023-11-28: The calculated VIX-equivalent index is 1530.44\n",
      "F: 126.68207207461695, K0: 126.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 1500\n",
      "Contribution to sigma_squared at K=137.0: 0.16049229360303952\n",
      "F: 127.98241953014387, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 17500\n",
      "Contribution to sigma_squared at K=140.0: 1.8114284909525045\n",
      "Date 2023-11-29: The calculated VIX-equivalent index is 1476.51\n",
      "F: 127.81502330391584, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 10500\n",
      "Contribution to sigma_squared at K=134.0: 0.5869850587407401\n",
      "F: 129.12700011017986, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 22500\n",
      "Contribution to sigma_squared at K=140.0: 2.3283000359485735\n",
      "Date 2023-11-30: The calculated VIX-equivalent index is 1562.85\n",
      "F: 128.63451944591358, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=133.0: 16000\n",
      "Contribution to sigma_squared at K=133.0: 0.9076895307311584\n",
      "F: 129.9549080953501, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 43500\n",
      "Contribution to sigma_squared at K=138.0: 2.3157243792406765\n",
      "Date 2023-12-01: The calculated VIX-equivalent index is 1487.04\n",
      "F: 127.13621520083632, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 5000\n",
      "Contribution to sigma_squared at K=134.0: 0.2791906544963739\n",
      "F: 128.44122427776676, K0: 128.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=143.0: 9500\n",
      "Contribution to sigma_squared at K=143.0: 2.3528658261702513\n",
      "Date 2023-12-04: The calculated VIX-equivalent index is 1633.84\n",
      "F: 127.19981947519324, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 2500\n",
      "Contribution to sigma_squared at K=134.0: 0.2791092039011719\n",
      "F: 128.50548142790134, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 17500\n",
      "Contribution to sigma_squared at K=140.0: 1.808260024691214\n",
      "Date 2023-12-05: The calculated VIX-equivalent index is 1523.94\n",
      "F: 125.87949216685605, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 4000\n",
      "Contribution to sigma_squared at K=132.0: 0.23003777617249954\n",
      "F: 127.17160141847755, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 9000\n",
      "Contribution to sigma_squared at K=141.0: 0.45827532466928994\n",
      "Date 2023-12-06: The calculated VIX-equivalent index is 1527.34\n",
      "F: 126.23036627138414, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=131.0: 3500\n",
      "Contribution to sigma_squared at K=131.0: 0.20430818506862336\n",
      "F: 127.5260771237812, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 10500\n",
      "Contribution to sigma_squared at K=140.0: 0.5421615304005192\n",
      "Date 2023-12-07: The calculated VIX-equivalent index is 1643.61\n",
      "F: 127.2791226504266, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=135.0: 3000\n",
      "Contribution to sigma_squared at K=135.0: 0.49454813275451875\n",
      "F: 128.58559862267546, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 14000\n",
      "Contribution to sigma_squared at K=140.0: 0.7226711481867564\n",
      "Date 2023-12-08: The calculated VIX-equivalent index is 1423.33\n",
      "F: 126.99049516337675, K0: 126.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=132.0: 500\n",
      "Contribution to sigma_squared at K=132.0: 0.057425604450703514\n",
      "F: 128.29400847475154, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=143.0: 5000\n",
      "Contribution to sigma_squared at K=143.0: 0.4943294910829351\n",
      "Date 2023-12-11: The calculated VIX-equivalent index is 1566.20\n",
      "F: 126.43991736123688, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=130.0: 500\n",
      "Contribution to sigma_squared at K=130.0: 0.029594432644795332\n",
      "F: 127.73777918276504, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=142.0: 4500\n",
      "Contribution to sigma_squared at K=142.0: 0.6765796897529458\n",
      "Date 2023-12-12: The calculated VIX-equivalent index is 1451.52\n",
      "F: 130.79399406495492, K0: 130.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=146.0: 4500\n",
      "Contribution to sigma_squared at K=146.0: 0.8531039475555557\n",
      "F: 131.86694002226955, K0: 131.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 87000\n",
      "Contribution to sigma_squared at K=140.0: 13.563373474370088\n",
      "Date 2023-12-13: The calculated VIX-equivalent index is 1510.98\n",
      "F: 132.14657513210625, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=146.0: 4500\n",
      "Contribution to sigma_squared at K=146.0: 0.21321376612399356\n",
      "F: 133.2306167547709, K0: 133.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=147.0: 20500\n",
      "Contribution to sigma_squared at K=147.0: 0.9659969544942342\n",
      "Date 2023-12-14: The calculated VIX-equivalent index is 1412.36\n",
      "F: 131.45679246623925, K0: 131.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=146.0: 3500\n",
      "Contribution to sigma_squared at K=146.0: 0.9947072963859536\n",
      "F: 132.53517557585016, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=148.0: 16500\n",
      "Contribution to sigma_squared at K=148.0: 1.533629154485582\n",
      "Date 2023-12-15: The calculated VIX-equivalent index is 1386.32\n",
      "F: 132.23628900877114, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 4500\n",
      "Contribution to sigma_squared at K=144.0: 0.21892184199414125\n",
      "F: 133.3210665837398, K0: 133.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 27000\n",
      "Contribution to sigma_squared at K=145.0: 1.3061030696196951\n",
      "Date 2023-12-18: The calculated VIX-equivalent index is 1383.42\n",
      "F: 132.97130892078033, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=146.0: 3500\n",
      "Contribution to sigma_squared at K=146.0: 0.33118234251867273\n",
      "F: 134.06211610474423, K0: 134.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=146.0: 20500\n",
      "Contribution to sigma_squared at K=146.0: 0.9778474805752836\n",
      "Date 2023-12-19: The calculated VIX-equivalent index is 1423.57\n",
      "F: 131.87719943384155, K0: 131.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 3000\n",
      "Contribution to sigma_squared at K=144.0: 0.14586274991545775\n",
      "F: 132.95903127945553, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 71000\n",
      "Contribution to sigma_squared at K=140.0: 3.682125020829097\n",
      "Date 2023-12-20: The calculated VIX-equivalent index is 1321.56\n",
      "F: 133.22746341592892, K0: 133.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=146.0: 2000\n",
      "Contribution to sigma_squared at K=146.0: 0.5674099432913265\n",
      "F: 134.32037191908552, K0: 134.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 27000\n",
      "Contribution to sigma_squared at K=145.0: 1.304960282376277\n",
      "Date 2023-12-21: The calculated VIX-equivalent index is 1368.20\n",
      "F: 133.76386350941618, K0: 133.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=146.0: 1500\n",
      "Contribution to sigma_squared at K=146.0: 0.07090555101286\n",
      "F: 134.86117227816544, K0: 134.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=146.0: 20000\n",
      "Contribution to sigma_squared at K=146.0: 0.9531628328454016\n",
      "Date 2023-12-22: The calculated VIX-equivalent index is 1354.50\n",
      "F: 134.39284865807343, K0: 134.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=146.0: 4500\n",
      "Contribution to sigma_squared at K=146.0: 0.4249370626032746\n",
      "F: 135.4953171979367, K0: 135.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=148.0: 15500\n",
      "Contribution to sigma_squared at K=148.0: 0.7180326743450387\n",
      "Date 2023-12-26: The calculated VIX-equivalent index is 1431.45\n",
      "F: 135.0185025368658, K0: 135.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 18500\n",
      "Contribution to sigma_squared at K=141.0: 0.9362559655428492\n",
      "F: 136.12610352034562, K0: 136.0\n",
      "deltaK: 150.0\n",
      "Q_K at K=300.0: 1000\n",
      "Contribution to sigma_squared at K=300.0: 1.6906665915556707\n",
      "Date 2023-12-27: The calculated VIX-equivalent index is 1450.14\n",
      "F: 134.97058284343396, K0: 134.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=144.0: 7000\n",
      "Contribution to sigma_squared at K=144.0: 1.0186586715457668\n",
      "F: 136.07779072597893, K0: 136.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 37000\n",
      "Contribution to sigma_squared at K=145.0: 1.7846301345698565\n",
      "Date 2023-12-28: The calculated VIX-equivalent index is 1427.88\n",
      "F: 133.27867777522061, K0: 133.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 3500\n",
      "Contribution to sigma_squared at K=144.0: 0.16952893829229396\n",
      "F: 134.3720064065349, K0: 134.0\n",
      "deltaK: 15.0\n",
      "Q_K at K=160.0: 3000\n",
      "Contribution to sigma_squared at K=160.0: 1.7800059618054136\n",
      "Date 2024-01-02: The calculated VIX-equivalent index is 1706.25\n",
      "F: 133.3776773759961, K0: 133.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=145.0: 9000\n",
      "Contribution to sigma_squared at K=145.0: 1.0745350268616343\n",
      "F: 134.4718181334495, K0: 134.0\n",
      "deltaK: 153.0\n",
      "Q_K at K=300.0: 1000\n",
      "Contribution to sigma_squared at K=300.0: 1.7209613267305843\n",
      "Date 2024-01-03: The calculated VIX-equivalent index is 1788.16\n",
      "F: 131.7246148838364, K0: 131.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 7000\n",
      "Contribution to sigma_squared at K=145.0: 1.002606774292388\n",
      "F: 132.80519502842816, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=150.0: 10000\n",
      "Contribution to sigma_squared at K=150.0: 0.8995865393312319\n",
      "Date 2024-01-04: The calculated VIX-equivalent index is 1574.75\n",
      "F: 132.48599129215984, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 3500\n",
      "Contribution to sigma_squared at K=140.0: 0.1791977690748154\n",
      "F: 133.57281725671558, K0: 133.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=148.0: 5000\n",
      "Contribution to sigma_squared at K=148.0: 0.4618971911347055\n",
      "Date 2024-01-05: The calculated VIX-equivalent index is 1505.72\n",
      "F: 132.77475273014232, K0: 132.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=145.0: 500\n",
      "Contribution to sigma_squared at K=145.0: 0.059609362569998686\n",
      "F: 133.86394749931884, K0: 133.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=146.0: 9500\n",
      "Contribution to sigma_squared at K=146.0: 0.9010242611181454\n",
      "Date 2024-01-08: The calculated VIX-equivalent index is 1580.73\n",
      "F: 131.7537771383297, K0: 131.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=141.0: 1500\n",
      "Contribution to sigma_squared at K=141.0: 0.15125048635127333\n",
      "F: 132.83459651044322, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=146.0: 6000\n",
      "Contribution to sigma_squared at K=146.0: 0.5689019354966911\n",
      "Date 2024-01-09: The calculated VIX-equivalent index is 1470.26\n",
      "F: 131.10860154405205, K0: 131.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 500\n",
      "Contribution to sigma_squared at K=140.0: 0.02556236104610735\n",
      "F: 132.1841283295251, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=146.0: 4500\n",
      "Contribution to sigma_squared at K=146.0: 0.42655197377777787\n",
      "Date 2024-01-10: The calculated VIX-equivalent index is 1592.02\n",
      "F: 130.87767512736136, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 1500\n",
      "Contribution to sigma_squared at K=137.0: 0.08005905095703353\n",
      "F: 131.95130754782937, K0: 131.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=148.0: 13000\n",
      "Contribution to sigma_squared at K=148.0: 1.1988320814683793\n",
      "Date 2024-01-11: The calculated VIX-equivalent index is 1562.09\n",
      "F: 131.17890791503933, K0: 131.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 2000\n",
      "Contribution to sigma_squared at K=137.0: 0.2134285191172466\n",
      "F: 132.255011446693, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 10500\n",
      "Contribution to sigma_squared at K=143.0: 0.518440528381901\n",
      "Date 2024-01-12: The calculated VIX-equivalent index is 1489.45\n",
      "F: 131.59768295713621, K0: 131.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 1000\n",
      "Contribution to sigma_squared at K=137.0: 0.05331044445357014\n",
      "F: 132.67722183757368, K0: 132.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=149.0: 2500\n",
      "Contribution to sigma_squared at K=149.0: 0.4543902742709801\n",
      "Date 2024-01-15: The calculated VIX-equivalent index is 1530.09\n",
      "F: 130.3927218885554, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 4000\n",
      "Contribution to sigma_squared at K=144.0: 0.194540421437611\n",
      "F: 131.46237607882424, K0: 131.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=145.0: 23000\n",
      "Contribution to sigma_squared at K=145.0: 5.561408643678351\n",
      "Date 2024-01-16: The calculated VIX-equivalent index is 1529.32\n",
      "F: 129.57815305820256, K0: 129.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=146.0: 500\n",
      "Contribution to sigma_squared at K=146.0: 0.09459592113113566\n",
      "F: 130.64112507365343, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 52500\n",
      "Contribution to sigma_squared at K=139.0: 2.7620145098146445\n",
      "Date 2024-01-17: The calculated VIX-equivalent index is 1533.01\n",
      "F: 128.32270513303524, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 3500\n",
      "Contribution to sigma_squared at K=140.0: 0.17998378498806428\n",
      "F: 129.37537829810267, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 28000\n",
      "Contribution to sigma_squared at K=141.0: 1.4311637916620825\n",
      "Date 2024-01-18: The calculated VIX-equivalent index is 1449.86\n",
      "F: 128.60761465329327, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 4500\n",
      "Contribution to sigma_squared at K=139.0: 0.23468082274056054\n",
      "F: 129.6626250244392, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 23000\n",
      "Contribution to sigma_squared at K=140.0: 2.38421038639515\n",
      "Date 2024-01-19: The calculated VIX-equivalent index is 1428.88\n",
      "F: 127.45402506239645, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=141.0: 1000\n",
      "Contribution to sigma_squared at K=141.0: 0.1012759446553981\n",
      "F: 128.499572160425, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 29500\n",
      "Contribution to sigma_squared at K=138.0: 3.1445354685558176\n",
      "Date 2024-01-22: The calculated VIX-equivalent index is 1359.64\n",
      "F: 129.08850820354348, K0: 129.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=147.0: 1000\n",
      "Contribution to sigma_squared at K=147.0: 0.32602521061265527\n",
      "F: 130.1474635019342, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 23000\n",
      "Contribution to sigma_squared at K=139.0: 1.2079088842781318\n",
      "Date 2024-01-23: The calculated VIX-equivalent index is 1434.24\n",
      "F: 128.60128189829803, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 3500\n",
      "Contribution to sigma_squared at K=140.0: 0.17966896574283192\n",
      "F: 129.65624031978126, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 19000\n",
      "Contribution to sigma_squared at K=141.0: 0.969448173820967\n",
      "Date 2024-01-24: The calculated VIX-equivalent index is 1452.52\n",
      "F: 128.91886015483308, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=138.0: 6000\n",
      "Contribution to sigma_squared at K=138.0: 0.9507114147615907\n",
      "F: 129.9764237747348, K0: 129.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=139.0: 31000\n",
      "Contribution to sigma_squared at K=139.0: 6.508405255501398\n",
      "Date 2024-01-25: The calculated VIX-equivalent index is 1443.32\n",
      "F: 129.68427913751597, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=139.0: 5000\n",
      "Contribution to sigma_squared at K=139.0: 0.5204488541535063\n",
      "F: 130.74812173994277, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 33000\n",
      "Contribution to sigma_squared at K=139.0: 1.73157027947384\n",
      "Date 2024-01-26: The calculated VIX-equivalent index is 1193.75\n",
      "F: 129.10397631647547, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 8500\n",
      "Contribution to sigma_squared at K=136.0: 0.46170928655460136\n",
      "F: 130.16305850486106, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 21000\n",
      "Contribution to sigma_squared at K=140.0: 1.0852726303614013\n",
      "Date 2024-01-29: The calculated VIX-equivalent index is 1439.75\n",
      "F: 127.96063308442633, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 4000\n",
      "Contribution to sigma_squared at K=138.0: 0.2109612064949745\n",
      "F: 129.01033605393098, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=141.0: 12500\n",
      "Contribution to sigma_squared at K=141.0: 1.2733585003609975\n",
      "Date 2024-01-30: The calculated VIX-equivalent index is 1504.13\n",
      "F: 128.2752066462521, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 500\n",
      "Contribution to sigma_squared at K=140.0: 0.051229249296521236\n",
      "F: 129.32749016568064, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 17000\n",
      "Contribution to sigma_squared at K=140.0: 0.8780414932298901\n",
      "Date 2024-01-31: The calculated VIX-equivalent index is 1481.28\n",
      "F: 128.96929333073388, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 4000\n",
      "Contribution to sigma_squared at K=136.0: 0.2170848515972304\n",
      "F: 130.02727067049014, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 11000\n",
      "Contribution to sigma_squared at K=141.0: 0.5599508789408981\n",
      "Date 2024-02-01: The calculated VIX-equivalent index is 1596.99\n",
      "F: 127.62834260912646, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 2000\n",
      "Contribution to sigma_squared at K=138.0: 0.10538831199527056\n",
      "F: 128.6753196910651, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=142.0: 5000\n",
      "Contribution to sigma_squared at K=142.0: 0.2508777046869319\n",
      "Date 2024-02-02: The calculated VIX-equivalent index is 1597.56\n",
      "F: 127.92899432942886, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 3500\n",
      "Contribution to sigma_squared at K=135.0: 0.19254887102857737\n",
      "F: 128.97843775586722, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 9000\n",
      "Contribution to sigma_squared at K=140.0: 0.46416782585915545\n",
      "Date 2024-02-05: The calculated VIX-equivalent index is 1541.80\n",
      "F: 130.7210894017359, K0: 130.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=142.0: 500\n",
      "Contribution to sigma_squared at K=142.0: 0.17398231529828453\n",
      "F: 131.793437298228, K0: 131.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 7000\n",
      "Contribution to sigma_squared at K=145.0: 1.0093578549266617\n",
      "Date 2024-02-06: The calculated VIX-equivalent index is 1508.77\n",
      "F: 130.21558945885735, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 14000\n",
      "Contribution to sigma_squared at K=135.0: 0.7697461586888182\n",
      "F: 131.28379057380943, K0: 131.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=150.0: 1500\n",
      "Contribution to sigma_squared at K=150.0: 0.5388078146990882\n",
      "Date 2024-02-07: The calculated VIX-equivalent index is 1505.57\n",
      "F: 128.44158403039353, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 4000\n",
      "Contribution to sigma_squared at K=135.0: 0.21986331265295836\n",
      "F: 129.49523239797878, K0: 129.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=148.0: 2500\n",
      "Contribution to sigma_squared at K=148.0: 0.34581694657741713\n",
      "Date 2024-02-08: The calculated VIX-equivalent index is 1577.27\n",
      "F: 128.21261353117015, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=146.0: 1000\n",
      "Contribution to sigma_squared at K=146.0: 0.14094482578737574\n",
      "F: 129.26438357878177, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 7500\n",
      "Contribution to sigma_squared at K=141.0: 0.380894549889036\n",
      "Date 2024-02-09: The calculated VIX-equivalent index is 1561.87\n",
      "F: 128.0602626206452, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 7000\n",
      "Contribution to sigma_squared at K=141.0: 0.3549833153216391\n",
      "F: 129.3747567232897, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 36000\n",
      "Contribution to sigma_squared at K=140.0: 1.8708101343958745\n",
      "Date 2024-02-14: The calculated VIX-equivalent index is 1575.21\n",
      "F: 128.81495790523704, K0: 128.0\n",
      "deltaK: 9.0\n",
      "Q_K at K=150.0: 1000\n",
      "Contribution to sigma_squared at K=150.0: 0.40316367837326395\n",
      "F: 130.13719869276713, K0: 130.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=145.0: 12000\n",
      "Contribution to sigma_squared at K=145.0: 2.32467260950428\n",
      "Date 2024-02-15: The calculated VIX-equivalent index is 1447.15\n",
      "F: 129.70614691856133, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 5500\n",
      "Contribution to sigma_squared at K=141.0: 0.2787527451551961\n",
      "F: 131.0375354516792, K0: 131.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 12500\n",
      "Contribution to sigma_squared at K=145.0: 0.6052068785329908\n",
      "Date 2024-02-16: The calculated VIX-equivalent index is 1451.17\n",
      "F: 129.90460574854632, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 12500\n",
      "Contribution to sigma_squared at K=137.0: 0.6704762692784545\n",
      "F: 131.23803139260158, K0: 131.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 30000\n",
      "Contribution to sigma_squared at K=141.0: 1.5347326056007744\n",
      "Date 2024-02-19: The calculated VIX-equivalent index is 1317.65\n",
      "F: 130.7527470340319, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 19000\n",
      "Contribution to sigma_squared at K=137.0: 1.0188266118633953\n",
      "F: 132.09487855370517, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 40500\n",
      "Contribution to sigma_squared at K=141.0: 2.071284568268223\n",
      "Date 2024-02-20: The calculated VIX-equivalent index is 1352.88\n",
      "F: 130.8307811580353, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 15500\n",
      "Contribution to sigma_squared at K=137.0: 0.8309055477903888\n",
      "F: 132.17371367087932, K0: 132.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=142.0: 28000\n",
      "Contribution to sigma_squared at K=142.0: 2.8229786335583547\n",
      "Date 2024-02-21: The calculated VIX-equivalent index is 1375.63\n",
      "F: 131.0028058477177, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 9000\n",
      "Contribution to sigma_squared at K=139.0: 0.4685406599741145\n",
      "F: 132.34750413423316, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 14500\n",
      "Contribution to sigma_squared at K=145.0: 0.700812003498371\n",
      "Date 2024-02-22: The calculated VIX-equivalent index is 1425.73\n",
      "F: 130.1381986300313, K0: 130.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=139.0: 5500\n",
      "Contribution to sigma_squared at K=139.0: 0.5724937395688569\n",
      "F: 131.4740220238557, K0: 131.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 9500\n",
      "Contribution to sigma_squared at K=145.0: 1.3770562186220654\n",
      "Date 2024-02-23: The calculated VIX-equivalent index is 1356.96\n",
      "F: 132.26699962653012, K0: 132.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 6000\n",
      "Contribution to sigma_squared at K=140.0: 0.30746519513956333\n",
      "F: 133.62467442295463, K0: 133.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=145.0: 20000\n",
      "Contribution to sigma_squared at K=145.0: 1.930456086699088\n",
      "Date 2024-02-27: The calculated VIX-equivalent index is 1458.24\n",
      "F: 130.688193427012, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 8500\n",
      "Contribution to sigma_squared at K=137.0: 0.4547281652086119\n",
      "F: 132.02966232633761, K0: 132.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 14500\n",
      "Contribution to sigma_squared at K=145.0: 2.098758527448419\n",
      "Date 2024-02-28: The calculated VIX-equivalent index is 1475.98\n",
      "F: 129.51034172142434, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 4000\n",
      "Contribution to sigma_squared at K=137.0: 0.2139272958145012\n",
      "F: 130.839720382224, K0: 130.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=150.0: 2000\n",
      "Contribution to sigma_squared at K=150.0: 0.7211406333565162\n",
      "Date 2024-02-29: The calculated VIX-equivalent index is 1467.62\n",
      "F: 129.63347102865157, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 13500\n",
      "Contribution to sigma_squared at K=135.0: 0.743338893939975\n",
      "F: 130.96411356900995, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 23000\n",
      "Contribution to sigma_squared at K=141.0: 1.172857891581308\n",
      "Date 2024-03-01: The calculated VIX-equivalent index is 1449.94\n",
      "F: 128.67800868128805, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 2000\n",
      "Contribution to sigma_squared at K=137.0: 0.10683888096620789\n",
      "F: 129.99884373261582, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 21000\n",
      "Contribution to sigma_squared at K=141.0: 1.0699332807747834\n",
      "Date 2024-03-04: The calculated VIX-equivalent index is 1481.47\n",
      "F: 128.3974718308116, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=141.0: 500\n",
      "Contribution to sigma_squared at K=141.0: 0.10083365756751556\n",
      "F: 129.71542726883877, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=144.0: 9500\n",
      "Contribution to sigma_squared at K=144.0: 0.9278494725460318\n",
      "Date 2024-03-05: The calculated VIX-equivalent index is 1536.43\n",
      "F: 129.15375290737202, K0: 129.0\n",
      "deltaK: 12.5\n",
      "Q_K at K=160.0: 1000\n",
      "Contribution to sigma_squared at K=160.0: 0.48927956689814844\n",
      "F: 130.47947130788833, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=146.0: 6500\n",
      "Contribution to sigma_squared at K=146.0: 0.30869517026008625\n",
      "Date 2024-03-06: The calculated VIX-equivalent index is 1465.18\n",
      "F: 128.56463927288644, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 500\n",
      "Contribution to sigma_squared at K=140.0: 0.07666471058227359\n",
      "F: 129.88431062662593, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=145.0: 7000\n",
      "Contribution to sigma_squared at K=145.0: 0.3369438286436838\n",
      "Date 2024-03-07: The calculated VIX-equivalent index is 1501.53\n",
      "F: 127.25630939233668, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 500\n",
      "Contribution to sigma_squared at K=137.0: 0.05335712977931165\n",
      "F: 128.56255119441747, K0: 128.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=151.0: 1500\n",
      "Contribution to sigma_squared at K=151.0: 0.33279448515244686\n",
      "Date 2024-03-08: The calculated VIX-equivalent index is 3036.68\n",
      "F: 126.19718235150094, K0: 126.0\n",
      "deltaK: 2.5\n",
      "Q_K at K=160.0: 1000\n",
      "Contribution to sigma_squared at K=160.0: 0.0977132550731502\n",
      "F: 127.4925525824898, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=143.0: 4000\n",
      "Contribution to sigma_squared at K=143.0: 0.3954635928663481\n",
      "Date 2024-03-11: The calculated VIX-equivalent index is 1546.98\n",
      "F: 127.70509646238395, K0: 127.0\n",
      "deltaK: 13.0\n",
      "Q_K at K=160.0: 500\n",
      "Contribution to sigma_squared at K=160.0: 0.2539803457836537\n",
      "F: 129.01594490781255, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 7000\n",
      "Contribution to sigma_squared at K=141.0: 0.3558129017627058\n",
      "Date 2024-03-12: The calculated VIX-equivalent index is 1519.76\n",
      "F: 129.31998762892917, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 6500\n",
      "Contribution to sigma_squared at K=141.0: 0.3303013048460911\n",
      "F: 130.3808418288363, K0: 130.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=130.0: 308000.0\n",
      "Contribution to sigma_squared at K=130.0: 37.125925770286045\n",
      "Date 2024-03-13: The calculated VIX-equivalent index is 1567.41\n",
      "F: 128.96302874878714, K0: 128.0\n",
      "deltaK: 158.0\n",
      "Q_K at K=300.0: 1000\n",
      "Contribution to sigma_squared at K=300.0: 1.7730583034924676\n",
      "F: 130.02095469812653, K0: 130.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=141.0: 27500\n",
      "Contribution to sigma_squared at K=141.0: 4.225443402016234\n",
      "Date 2024-03-14: The calculated VIX-equivalent index is 1572.95\n",
      "F: 127.9680715927277, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 6000\n",
      "Contribution to sigma_squared at K=140.0: 0.30908426719771115\n",
      "F: 129.0178355827514, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 57000\n",
      "Contribution to sigma_squared at K=137.0: 3.091459548855664\n",
      "Date 2024-03-15: The calculated VIX-equivalent index is 1470.95\n",
      "F: 128.07034184197218, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=143.0: 4000\n",
      "Contribution to sigma_squared at K=143.0: 0.5919850444964564\n",
      "F: 129.12094478833532, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 22500\n",
      "Contribution to sigma_squared at K=140.0: 1.167551744844987\n",
      "Date 2024-03-18: The calculated VIX-equivalent index is 1613.15\n",
      "F: 128.6125321075689, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=142.0: 8000\n",
      "Contribution to sigma_squared at K=142.0: 0.4001180498839816\n",
      "F: 129.66758281820233, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 22000\n",
      "Contribution to sigma_squared at K=141.0: 1.1251422346148372\n",
      "Date 2024-03-19: The calculated VIX-equivalent index is 1464.04\n",
      "F: 130.18408325797935, K0: 130.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=141.0: 9500\n",
      "Contribution to sigma_squared at K=141.0: 0.9635261415873062\n",
      "F: 131.25202591725002, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 20500\n",
      "Contribution to sigma_squared at K=143.0: 1.0190090450851148\n",
      "Date 2024-03-20: The calculated VIX-equivalent index is 1426.04\n",
      "F: 129.17220124064357, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 7500\n",
      "Contribution to sigma_squared at K=140.0: 0.7713590785202755\n",
      "F: 130.23184310042004, K0: 130.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=142.0: 21000\n",
      "Contribution to sigma_squared at K=142.0: 4.233232594034001\n",
      "Date 2024-03-21: The calculated VIX-equivalent index is 1454.11\n",
      "F: 127.9944304536025, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=142.0: 2500\n",
      "Contribution to sigma_squared at K=142.0: 0.12492748837781223\n",
      "F: 129.04441067399227, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=142.0: 15500\n",
      "Contribution to sigma_squared at K=142.0: 0.7809043187027748\n",
      "Date 2024-03-22: The calculated VIX-equivalent index is 1424.04\n",
      "F: 127.78616658790374, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=142.0: 2500\n",
      "Contribution to sigma_squared at K=142.0: 0.37445454566814057\n",
      "F: 128.83443835161435, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 20000\n",
      "Contribution to sigma_squared at K=140.0: 3.1071186508047552\n",
      "Date 2024-03-25: The calculated VIX-equivalent index is 1448.27\n",
      "F: 127.67999566823029, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=139.0: 4500\n",
      "Contribution to sigma_squared at K=139.0: 0.46881416212677396\n",
      "F: 128.72739647712478, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 16000\n",
      "Contribution to sigma_squared at K=140.0: 0.8283232494458842\n",
      "Date 2024-03-26: The calculated VIX-equivalent index is 1365.97\n",
      "F: 128.47543313058142, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=140.0: 1000\n",
      "Contribution to sigma_squared at K=140.0: 0.20533596084895075\n",
      "F: 129.52935917341821, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 17000\n",
      "Contribution to sigma_squared at K=139.0: 0.8925417542501858\n",
      "Date 2024-03-27: The calculated VIX-equivalent index is 1235.52\n",
      "F: 128.855863601684, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 5500\n",
      "Contribution to sigma_squared at K=137.0: 0.29475143707697243\n",
      "F: 129.91291044023419, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 23000\n",
      "Contribution to sigma_squared at K=139.0: 1.2072042006171948\n",
      "Date 2024-03-28: The calculated VIX-equivalent index is 1286.43\n",
      "F: 127.58469006959514, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 14000\n",
      "Contribution to sigma_squared at K=134.0: 0.7833321288482611\n",
      "F: 128.6313090554595, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 13000\n",
      "Contribution to sigma_squared at K=140.0: 1.3436708756855447\n",
      "Date 2024-04-01: The calculated VIX-equivalent index is 1416.43\n",
      "F: 128.10798659910418, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=138.0: 3000\n",
      "Contribution to sigma_squared at K=138.0: 0.6328836194849234\n",
      "F: 129.15889835773555, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 17500\n",
      "Contribution to sigma_squared at K=138.0: 1.8610531655087055\n",
      "Date 2024-04-02: The calculated VIX-equivalent index is 1280.50\n",
      "F: 127.83954061029762, K0: 127.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=140.0: 500\n",
      "Contribution to sigma_squared at K=140.0: 0.10245849859304247\n",
      "F: 128.88825021858938, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 17500\n",
      "Contribution to sigma_squared at K=138.0: 1.8605102251000918\n",
      "Date 2024-04-03: The calculated VIX-equivalent index is 1268.74\n",
      "F: 127.9117996960243, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 8000\n",
      "Contribution to sigma_squared at K=135.0: 0.44062566970012323\n",
      "F: 128.96110206925508, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 18500\n",
      "Contribution to sigma_squared at K=140.0: 0.9552369821342481\n",
      "Date 2024-04-04: The calculated VIX-equivalent index is 1482.75\n",
      "F: 129.19598712243317, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=137.0: 5000\n",
      "Contribution to sigma_squared at K=137.0: 0.2670972024155197\n",
      "F: 130.25582410558582, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=142.0: 12500\n",
      "Contribution to sigma_squared at K=142.0: 0.6266454921614598\n",
      "Date 2024-04-08: The calculated VIX-equivalent index is 1531.28\n",
      "F: 130.19392029413, K0: 130.0\n",
      "deltaK: 6.0\n",
      "Q_K at K=144.0: 1000\n",
      "Contribution to sigma_squared at K=144.0: 0.29002805933156495\n",
      "F: 131.26194364982902, K0: 131.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=145.0: 5000\n",
      "Contribution to sigma_squared at K=145.0: 1.2016164939603116\n",
      "Date 2024-04-09: The calculated VIX-equivalent index is 1500.38\n",
      "F: 128.31555265922685, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 500\n",
      "Contribution to sigma_squared at K=138.0: 0.052617336326791005\n",
      "F: 129.36816715020979, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 3500\n",
      "Contribution to sigma_squared at K=144.0: 0.17052113637937721\n",
      "Date 2024-04-10: The calculated VIX-equivalent index is 1524.94\n",
      "F: 127.61957621264361, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 2000\n",
      "Contribution to sigma_squared at K=134.0: 0.11157854959623988\n",
      "F: 128.66648138096164, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 4500\n",
      "Contribution to sigma_squared at K=143.0: 0.22225363776708137\n",
      "Date 2024-04-11: The calculated VIX-equivalent index is 1388.54\n",
      "F: 126.12996736539594, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 3500\n",
      "Contribution to sigma_squared at K=132.0: 0.20116562734720222\n",
      "F: 127.1646527846188, K0: 127.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=148.0: 1500\n",
      "Contribution to sigma_squared at K=148.0: 0.5531456936701186\n",
      "Date 2024-04-12: The calculated VIX-equivalent index is 1630.18\n",
      "F: 125.40705139589272, K0: 125.0\n",
      "deltaK: 164.0\n",
      "Q_K at K=300.0: 500\n",
      "Contribution to sigma_squared at K=300.0: 0.9116429557758085\n",
      "F: 126.43580649872371, K0: 126.0\n",
      "deltaK: 8.0\n",
      "Q_K at K=146.0: 500\n",
      "Contribution to sigma_squared at K=146.0: 0.18930227958510096\n",
      "Date 2024-04-15: The calculated VIX-equivalent index is 1594.69\n",
      "F: 125.44561786267332, K0: 125.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=139.0: 2500\n",
      "Contribution to sigma_squared at K=139.0: 0.2609848208510365\n",
      "F: 126.4746893388586, K0: 126.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=154.0: 3500\n",
      "Contribution to sigma_squared at K=154.0: 1.8006562815051177\n",
      "Date 2024-04-16: The calculated VIX-equivalent index is 1652.21\n",
      "F: 125.18976659902702, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 6500\n",
      "Contribution to sigma_squared at K=135.0: 0.35957869016195804\n",
      "F: 126.21673924352689, K0: 126.0\n",
      "deltaK: 145.0\n",
      "Q_K at K=300.0: 500\n",
      "Contribution to sigma_squared at K=300.0: 0.8188262370263141\n",
      "Date 2024-04-17: The calculated VIX-equivalent index is 1704.92\n",
      "F: 125.17847192176998, K0: 125.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 2000\n",
      "Contribution to sigma_squared at K=137.0: 0.21480296146478978\n",
      "F: 126.20535191233427, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 16000\n",
      "Contribution to sigma_squared at K=138.0: 0.853751232995285\n",
      "Date 2024-04-18: The calculated VIX-equivalent index is 1666.37\n",
      "F: 126.07714034568762, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 12000\n",
      "Contribution to sigma_squared at K=134.0: 0.6733894967209283\n",
      "F: 127.11139240757139, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=141.0: 7500\n",
      "Contribution to sigma_squared at K=141.0: 0.7664712141592191\n",
      "Date 2024-04-19: The calculated VIX-equivalent index is 1686.58\n",
      "F: 126.41871036969388, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 6000\n",
      "Contribution to sigma_squared at K=135.0: 0.3314349062870732\n",
      "F: 127.45576444231997, K0: 127.0\n",
      "deltaK: 159.0\n",
      "Q_K at K=300.0: 500\n",
      "Contribution to sigma_squared at K=300.0: 0.8965763484599945\n",
      "Date 2024-04-22: The calculated VIX-equivalent index is 1645.26\n",
      "F: 125.95400169006997, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 2000\n",
      "Contribution to sigma_squared at K=138.0: 0.10569626393208009\n",
      "F: 126.9872436052442, K0: 126.0\n",
      "deltaK: 158.0\n",
      "Q_K at K=300.0: 500\n",
      "Contribution to sigma_squared at K=300.0: 0.8906775829458382\n",
      "Date 2024-04-23: The calculated VIX-equivalent index is 1696.31\n",
      "F: 125.5073722467444, K0: 125.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=139.0: 500\n",
      "Contribution to sigma_squared at K=139.0: 0.10415053135550525\n",
      "F: 126.53695031436152, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=138.0: 13500\n",
      "Contribution to sigma_squared at K=138.0: 0.7190925956522228\n",
      "Date 2024-04-24: The calculated VIX-equivalent index is 1479.07\n",
      "F: 125.3750902965026, K0: 125.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=134.0: 4000\n",
      "Contribution to sigma_squared at K=134.0: 0.4481410901393464\n",
      "F: 126.40358321197074, K0: 126.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=142.0: 4000\n",
      "Contribution to sigma_squared at K=142.0: 0.40234239859456494\n",
      "Date 2024-04-25: The calculated VIX-equivalent index is 1547.71\n",
      "F: 127.22965877641494, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=135.0: 4000\n",
      "Contribution to sigma_squared at K=135.0: 0.44139774205102417\n",
      "F: 128.27336532433853, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 7500\n",
      "Contribution to sigma_squared at K=141.0: 0.3824536602982526\n",
      "Date 2024-04-26: The calculated VIX-equivalent index is 1435.10\n",
      "F: 127.94772092671667, K0: 127.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=136.0: 3000\n",
      "Contribution to sigma_squared at K=136.0: 0.3259124375679539\n",
      "F: 128.99731797356395, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=139.0: 16000\n",
      "Contribution to sigma_squared at K=139.0: 0.8388146548693266\n",
      "Date 2024-04-29: The calculated VIX-equivalent index is 1446.32\n",
      "F: 126.47653179372874, K0: 126.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=132.0: 15000\n",
      "Contribution to sigma_squared at K=132.0: 0.8646576309595158\n",
      "F: 127.51406019442781, K0: 127.0\n",
      "deltaK: 5.0\n",
      "Q_K at K=140.0: 9000\n",
      "Contribution to sigma_squared at K=140.0: 2.3249057460315607\n",
      "Date 2024-04-30: The calculated VIX-equivalent index is 1473.57\n",
      "F: 127.60535952402063, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=138.0: 3000\n",
      "Contribution to sigma_squared at K=138.0: 0.4743858004657813\n",
      "F: 128.65214806818713, K0: 127.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=138.0: 19000\n",
      "Contribution to sigma_squared at K=138.0: 3.0290898358861185\n",
      "Date 2024-05-02: The calculated VIX-equivalent index is 1514.85\n",
      "F: 128.95941503632127, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=138.0: 3000\n",
      "Contribution to sigma_squared at K=138.0: 0.3161649359858117\n",
      "F: 130.01731134119416, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 17000\n",
      "Contribution to sigma_squared at K=140.0: 0.8775292513696328\n",
      "Date 2024-05-03: The calculated VIX-equivalent index is 1437.60\n",
      "F: 128.8034877605132, K0: 128.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=137.0: 3500\n",
      "Contribution to sigma_squared at K=137.0: 0.2804520625362957\n",
      "F: 129.8601049428896, K0: 129.0\n",
      "deltaK: 12.0\n",
      "Q_K at K=154.0: 500\n",
      "Contribution to sigma_squared at K=154.0: 0.2557398489582123\n",
      "Date 2024-05-06: The calculated VIX-equivalent index is 1518.87\n",
      "F: 129.51244140952312, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=137.0: 2500\n",
      "Contribution to sigma_squared at K=137.0: 0.2670192799429613\n",
      "F: 130.57487437080485, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 14000\n",
      "Contribution to sigma_squared at K=141.0: 0.7116258035254116\n",
      "Date 2024-05-07: The calculated VIX-equivalent index is 1451.56\n",
      "F: 129.74562054305136, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=134.0: 5000\n",
      "Contribution to sigma_squared at K=134.0: 0.27902777706822457\n",
      "F: 130.8099663491119, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 6000\n",
      "Contribution to sigma_squared at K=143.0: 0.29642466210400226\n",
      "Date 2024-05-08: The calculated VIX-equivalent index is 1445.97\n",
      "F: 128.41295395199523, K0: 128.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=137.0: 1500\n",
      "Contribution to sigma_squared at K=137.0: 0.24017715287110059\n",
      "F: 129.46636745767344, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=141.0: 4500\n",
      "Contribution to sigma_squared at K=141.0: 0.22860342229762323\n",
      "Date 2024-05-09: The calculated VIX-equivalent index is 1400.18\n",
      "F: 127.7858613946535, K0: 127.0\n",
      "deltaK: 1.5\n",
      "Q_K at K=136.0: 500\n",
      "Contribution to sigma_squared at K=136.0: 0.04060850868408982\n",
      "F: 128.83413065476395, K0: 128.0\n",
      "deltaK: 7.0\n",
      "Q_K at K=147.0: 1500\n",
      "Contribution to sigma_squared at K=147.0: 0.4906099479328749\n",
      "Date 2024-05-10: The calculated VIX-equivalent index is 1405.93\n",
      "F: 128.55299382648394, K0: 128.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=136.0: 500\n",
      "Contribution to sigma_squared at K=136.0: 0.05408152159353819\n",
      "F: 129.60755612510386, K0: 129.0\n",
      "deltaK: 160.0\n",
      "Q_K at K=300.0: 500\n",
      "Contribution to sigma_squared at K=300.0: 0.8964422619845116\n",
      "Date 2024-05-14: The calculated VIX-equivalent index is 1598.91\n",
      "F: 129.07784223900583, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 4500\n",
      "Contribution to sigma_squared at K=140.0: 0.46295050748677524\n",
      "F: 130.40278144288573, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 28000\n",
      "Contribution to sigma_squared at K=140.0: 1.4550745489745691\n",
      "Date 2024-05-15: The calculated VIX-equivalent index is 1376.04\n",
      "F: 129.298240285595, K0: 129.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 4000\n",
      "Contribution to sigma_squared at K=140.0: 0.4113915085441469\n",
      "F: 130.62544179884824, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=144.0: 12500\n",
      "Contribution to sigma_squared at K=144.0: 0.6138207909205243\n",
      "Date 2024-05-16: The calculated VIX-equivalent index is 1317.18\n",
      "F: 129.12659691258622, K0: 129.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=140.0: 2500\n",
      "Contribution to sigma_squared at K=140.0: 0.38556702178319474\n",
      "F: 130.45203656625114, K0: 130.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=143.0: 12000\n",
      "Contribution to sigma_squared at K=143.0: 0.5973639608934367\n",
      "Date 2024-05-17: The calculated VIX-equivalent index is 1198.13\n",
      "F: 128.61113437729793, K0: 128.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=140.0: 2000\n",
      "Contribution to sigma_squared at K=140.0: 0.4109116440191775\n",
      "F: 129.93128298713003, K0: 129.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=145.0: 7500\n",
      "Contribution to sigma_squared at K=145.0: 1.0884192246830793\n",
      "Date 2024-05-20: The calculated VIX-equivalent index is 1279.34\n",
      "F: 128.232058105526, K0: 128.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 7500\n",
      "Contribution to sigma_squared at K=136.0: 0.40810438412140465\n",
      "F: 129.54831562913432, K0: 129.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 24000\n",
      "Contribution to sigma_squared at K=140.0: 1.245025200354967\n",
      "Date 2024-05-21: The calculated VIX-equivalent index is 1222.73\n",
      "F: 126.42230123967249, K0: 126.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=140.0: 1000\n",
      "Contribution to sigma_squared at K=140.0: 0.10266798042447538\n",
      "F: 127.71998223783328, K0: 127.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 12500\n",
      "Contribution to sigma_squared at K=140.0: 0.6482614473290664\n",
      "Date 2024-05-22: The calculated VIX-equivalent index is 1404.21\n",
      "F: 125.45940086787347, K0: 125.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=141.0: 500\n",
      "Contribution to sigma_squared at K=141.0: 0.07589049923176121\n",
      "F: 126.74719802826709, K0: 126.0\n",
      "deltaK: 4.0\n",
      "Q_K at K=141.0: 6500\n",
      "Contribution to sigma_squared at K=141.0: 1.3289378065433624\n",
      "Date 2024-05-23: The calculated VIX-equivalent index is 1515.09\n",
      "F: 124.99661339188897, K0: 124.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=137.0: 1500\n",
      "Contribution to sigma_squared at K=137.0: 0.24108991102322724\n",
      "F: 126.27966019963216, K0: 126.0\n",
      "deltaK: 3.0\n",
      "Q_K at K=141.0: 6500\n",
      "Contribution to sigma_squared at K=141.0: 0.9964125784069848\n",
      "Date 2024-05-24: The calculated VIX-equivalent index is 1361.85\n",
      "F: 125.07824602403956, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 1500\n",
      "Contribution to sigma_squared at K=135.0: 0.08268966317224793\n",
      "F: 126.36213076238938, K0: 126.0\n",
      "deltaK: 2.0\n",
      "Q_K at K=136.0: 19000\n",
      "Contribution to sigma_squared at K=136.0: 2.085299498197252\n",
      "Date 2024-05-27: The calculated VIX-equivalent index is 1229.37\n",
      "F: 124.32247470659226, K0: 124.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=136.0: 2500\n",
      "Contribution to sigma_squared at K=136.0: 0.1357572318504776\n",
      "F: 125.59860171495308, K0: 125.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 9000\n",
      "Contribution to sigma_squared at K=140.0: 0.4659318278133099\n",
      "Date 2024-05-28: The calculated VIX-equivalent index is 1556.35\n",
      "F: 123.20955601731346, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 2000\n",
      "Contribution to sigma_squared at K=135.0: 0.11018856364464374\n",
      "F: 124.47425930200039, K0: 124.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 22500\n",
      "Contribution to sigma_squared at K=135.0: 1.252345623374571\n",
      "Date 2024-05-29: The calculated VIX-equivalent index is 1472.53\n",
      "F: 122.52634988325775, K0: 122.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=135.0: 1000\n",
      "Contribution to sigma_squared at K=135.0: 0.05506214029185\n",
      "F: 123.78404029435124, K0: 123.0\n",
      "deltaK: 1.0\n",
      "Q_K at K=140.0: 5500\n",
      "Contribution to sigma_squared at K=140.0: 0.2844869844363441\n",
      "Date 2024-05-31: The calculated VIX-equivalent index is 1475.59\n"
     ]
    }
   ],
   "source": [
    "# Calculate daily VIX values\n",
    "vix_df = calculate_vix_df(spot='ibov', start='2022-01-01', end='2024-06-01')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(vix_df['Date'], vix_df['VIX'], label='VIX')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('VIX')\n",
    "plt.title('Daily VIX Values')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download IBOV Data for comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "# Define the ticker symbol for the IBOV index\n",
    "ibov_ticker = '^BVSP'  # '^BVSP' is the ticker symbol for the Bovespa Index on Yahoo Finance\n",
    "\n",
    "# Define the date range for the data\n",
    "start_date = '2022-01-01'\n",
    "end_date = '2024-09-01'\n",
    "\n",
    "# Download historical data\n",
    "ibov_data = yf.download(ibov_ticker, start=start_date, end=end_date)\n",
    "\n",
    "# Display the first few rows\n",
    "# Simplify the column structure\n",
    "ibov_data.columns = [col[0] for col in ibov_data.columns]  # Take just the first part of each tuple\n",
    "\n",
    "# Now calculate returns using the simplified column names\n",
    "adj_close_values = ibov_data['Adj Close']\n",
    "ibov_data['Log_Returns'] = np.log(adj_close_values / adj_close_values.shift(1))\n",
    "\n",
    "# Drop the first row with NaN returns\n",
    "ibov_data = ibov_data.dropna(subset=['Log_Returns'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Adj Close</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Log_Returns</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-04 00:00:00+00:00</th>\n",
       "      <td>103514.0</td>\n",
       "      <td>103514.0</td>\n",
       "      <td>104276.0</td>\n",
       "      <td>103096.0</td>\n",
       "      <td>103922.0</td>\n",
       "      <td>11491600</td>\n",
       "      <td>-0.003934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-05 00:00:00+00:00</th>\n",
       "      <td>101006.0</td>\n",
       "      <td>101006.0</td>\n",
       "      <td>103514.0</td>\n",
       "      <td>100850.0</td>\n",
       "      <td>103514.0</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.024527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-06 00:00:00+00:00</th>\n",
       "      <td>101561.0</td>\n",
       "      <td>101561.0</td>\n",
       "      <td>102235.0</td>\n",
       "      <td>101000.0</td>\n",
       "      <td>101006.0</td>\n",
       "      <td>11749200</td>\n",
       "      <td>0.005480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07 00:00:00+00:00</th>\n",
       "      <td>102719.0</td>\n",
       "      <td>102719.0</td>\n",
       "      <td>102719.0</td>\n",
       "      <td>101104.0</td>\n",
       "      <td>101561.0</td>\n",
       "      <td>11733200</td>\n",
       "      <td>0.011338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10 00:00:00+00:00</th>\n",
       "      <td>101945.0</td>\n",
       "      <td>101945.0</td>\n",
       "      <td>102719.0</td>\n",
       "      <td>101038.0</td>\n",
       "      <td>102719.0</td>\n",
       "      <td>10264700</td>\n",
       "      <td>-0.007564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-26 00:00:00+00:00</th>\n",
       "      <td>136889.0</td>\n",
       "      <td>136889.0</td>\n",
       "      <td>137013.0</td>\n",
       "      <td>135596.0</td>\n",
       "      <td>135608.0</td>\n",
       "      <td>7560000</td>\n",
       "      <td>0.009402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-27 00:00:00+00:00</th>\n",
       "      <td>136776.0</td>\n",
       "      <td>136776.0</td>\n",
       "      <td>137213.0</td>\n",
       "      <td>136664.0</td>\n",
       "      <td>136888.0</td>\n",
       "      <td>6745900</td>\n",
       "      <td>-0.000826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-28 00:00:00+00:00</th>\n",
       "      <td>137344.0</td>\n",
       "      <td>137344.0</td>\n",
       "      <td>137469.0</td>\n",
       "      <td>135746.0</td>\n",
       "      <td>136776.0</td>\n",
       "      <td>7457100</td>\n",
       "      <td>0.004144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-29 00:00:00+00:00</th>\n",
       "      <td>136041.0</td>\n",
       "      <td>136041.0</td>\n",
       "      <td>137370.0</td>\n",
       "      <td>135858.0</td>\n",
       "      <td>137349.0</td>\n",
       "      <td>8385100</td>\n",
       "      <td>-0.009532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-30 00:00:00+00:00</th>\n",
       "      <td>136004.0</td>\n",
       "      <td>136004.0</td>\n",
       "      <td>136139.0</td>\n",
       "      <td>134910.0</td>\n",
       "      <td>136041.0</td>\n",
       "      <td>18397900</td>\n",
       "      <td>-0.000272</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>666 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Adj Close     Close      High       Low      Open  \\\n",
       "Date                                                                           \n",
       "2022-01-04 00:00:00+00:00   103514.0  103514.0  104276.0  103096.0  103922.0   \n",
       "2022-01-05 00:00:00+00:00   101006.0  101006.0  103514.0  100850.0  103514.0   \n",
       "2022-01-06 00:00:00+00:00   101561.0  101561.0  102235.0  101000.0  101006.0   \n",
       "2022-01-07 00:00:00+00:00   102719.0  102719.0  102719.0  101104.0  101561.0   \n",
       "2022-01-10 00:00:00+00:00   101945.0  101945.0  102719.0  101038.0  102719.0   \n",
       "...                              ...       ...       ...       ...       ...   \n",
       "2024-08-26 00:00:00+00:00   136889.0  136889.0  137013.0  135596.0  135608.0   \n",
       "2024-08-27 00:00:00+00:00   136776.0  136776.0  137213.0  136664.0  136888.0   \n",
       "2024-08-28 00:00:00+00:00   137344.0  137344.0  137469.0  135746.0  136776.0   \n",
       "2024-08-29 00:00:00+00:00   136041.0  136041.0  137370.0  135858.0  137349.0   \n",
       "2024-08-30 00:00:00+00:00   136004.0  136004.0  136139.0  134910.0  136041.0   \n",
       "\n",
       "                             Volume  Log_Returns  \n",
       "Date                                              \n",
       "2022-01-04 00:00:00+00:00  11491600    -0.003934  \n",
       "2022-01-05 00:00:00+00:00         0    -0.024527  \n",
       "2022-01-06 00:00:00+00:00  11749200     0.005480  \n",
       "2022-01-07 00:00:00+00:00  11733200     0.011338  \n",
       "2022-01-10 00:00:00+00:00  10264700    -0.007564  \n",
       "...                             ...          ...  \n",
       "2024-08-26 00:00:00+00:00   7560000     0.009402  \n",
       "2024-08-27 00:00:00+00:00   6745900    -0.000826  \n",
       "2024-08-28 00:00:00+00:00   7457100     0.004144  \n",
       "2024-08-29 00:00:00+00:00   8385100    -0.009532  \n",
       "2024-08-30 00:00:00+00:00  18397900    -0.000272  \n",
       "\n",
       "[666 rows x 7 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ibov_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Calculate daily logarithmic returns\n",
    "adj_close_values = ibov_data['Adj Close']  # No need to index with ^BVSP since data is already filtered\n",
    "ibov_data['Log_Returns'] = np.log(adj_close_values / adj_close_values.shift(1))\n",
    "\n",
    "# Drop the first row with NaN returns\n",
    "ibov_data = ibov_data.dropna(subset=['Log_Returns'], inplace=False)  # Explicitly set inplace=False\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate daily logarithmic returns\n",
    "adj_close_values = ibov_data['Adj Close']  # No need to index with ^BVSP since data is already filtered\n",
    "ibov_data.loc[:, 'Log_Returns'] = np.log(adj_close_values / adj_close_values.shift(1))\n",
    "\n",
    "# Drop the first row with NaN returns\n",
    "ibov_data = ibov_data.dropna(subset=['Log_Returns'], inplace=False)  # Explicitly set inplace=False\n",
    "\n",
    "# Shift returns to align future returns with the current date\n",
    "ibov_data.loc[:, 'Future_Log_Returns'] = ibov_data['Log_Returns'].shift(-1)\n",
    "\n",
    "# Calculate realized volatility over the next 14 days (based on optimal window analysis)\n",
    "ibov_data.loc[:, 'Realized_Volatility'] = ibov_data['Future_Log_Returns'].rolling(window=30).std() * np.sqrt(252)\n",
    "\n",
    "# Drop rows with NaN values (these occur at the end due to shifting)\n",
    "ibov_data = ibov_data.dropna(subset=['Realized_Volatility'])  # Explicitly set inplace=False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "\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>Adj Close</th>\n",
       "      <th>Close</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Open</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Log_Returns</th>\n",
       "      <th>Future_Log_Returns</th>\n",
       "      <th>Realized_Volatility</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-02-16 00:00:00+00:00</th>\n",
       "      <td>115181.0</td>\n",
       "      <td>115181.0</td>\n",
       "      <td>115734.0</td>\n",
       "      <td>114816.0</td>\n",
       "      <td>114830.0</td>\n",
       "      <td>12052100</td>\n",
       "      <td>0.004534</td>\n",
       "      <td>-0.014455</td>\n",
       "      <td>0.142409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-17 00:00:00+00:00</th>\n",
       "      <td>113528.0</td>\n",
       "      <td>113528.0</td>\n",
       "      <td>115214.0</td>\n",
       "      <td>113389.0</td>\n",
       "      <td>115181.0</td>\n",
       "      <td>10807500</td>\n",
       "      <td>-0.014455</td>\n",
       "      <td>-0.006717</td>\n",
       "      <td>0.143617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-18 00:00:00+00:00</th>\n",
       "      <td>112768.0</td>\n",
       "      <td>112768.0</td>\n",
       "      <td>114213.0</td>\n",
       "      <td>112701.0</td>\n",
       "      <td>113534.0</td>\n",
       "      <td>11300700</td>\n",
       "      <td>-0.006717</td>\n",
       "      <td>-0.009292</td>\n",
       "      <td>0.144816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-21 00:00:00+00:00</th>\n",
       "      <td>111725.0</td>\n",
       "      <td>111725.0</td>\n",
       "      <td>113405.0</td>\n",
       "      <td>111608.0</td>\n",
       "      <td>112880.0</td>\n",
       "      <td>7864900</td>\n",
       "      <td>-0.009292</td>\n",
       "      <td>0.010391</td>\n",
       "      <td>0.139736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-22 00:00:00+00:00</th>\n",
       "      <td>112892.0</td>\n",
       "      <td>112892.0</td>\n",
       "      <td>113315.0</td>\n",
       "      <td>111727.0</td>\n",
       "      <td>111727.0</td>\n",
       "      <td>12707000</td>\n",
       "      <td>0.010391</td>\n",
       "      <td>-0.007861</td>\n",
       "      <td>0.135116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-23 00:00:00+00:00</th>\n",
       "      <td>135608.0</td>\n",
       "      <td>135608.0</td>\n",
       "      <td>136478.0</td>\n",
       "      <td>135174.0</td>\n",
       "      <td>135174.0</td>\n",
       "      <td>8649400</td>\n",
       "      <td>0.003213</td>\n",
       "      <td>0.009402</td>\n",
       "      <td>0.124693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-26 00:00:00+00:00</th>\n",
       "      <td>136889.0</td>\n",
       "      <td>136889.0</td>\n",
       "      <td>137013.0</td>\n",
       "      <td>135596.0</td>\n",
       "      <td>135608.0</td>\n",
       "      <td>7560000</td>\n",
       "      <td>0.009402</td>\n",
       "      <td>-0.000826</td>\n",
       "      <td>0.124516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-27 00:00:00+00:00</th>\n",
       "      <td>136776.0</td>\n",
       "      <td>136776.0</td>\n",
       "      <td>137213.0</td>\n",
       "      <td>136664.0</td>\n",
       "      <td>136888.0</td>\n",
       "      <td>6745900</td>\n",
       "      <td>-0.000826</td>\n",
       "      <td>0.004144</td>\n",
       "      <td>0.124668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-28 00:00:00+00:00</th>\n",
       "      <td>137344.0</td>\n",
       "      <td>137344.0</td>\n",
       "      <td>137469.0</td>\n",
       "      <td>135746.0</td>\n",
       "      <td>136776.0</td>\n",
       "      <td>7457100</td>\n",
       "      <td>0.004144</td>\n",
       "      <td>-0.009532</td>\n",
       "      <td>0.120305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-29 00:00:00+00:00</th>\n",
       "      <td>136041.0</td>\n",
       "      <td>136041.0</td>\n",
       "      <td>137370.0</td>\n",
       "      <td>135858.0</td>\n",
       "      <td>137349.0</td>\n",
       "      <td>8385100</td>\n",
       "      <td>-0.009532</td>\n",
       "      <td>-0.000272</td>\n",
       "      <td>0.120303</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>634 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Adj Close     Close      High       Low      Open  \\\n",
       "Date                                                                           \n",
       "2022-02-16 00:00:00+00:00   115181.0  115181.0  115734.0  114816.0  114830.0   \n",
       "2022-02-17 00:00:00+00:00   113528.0  113528.0  115214.0  113389.0  115181.0   \n",
       "2022-02-18 00:00:00+00:00   112768.0  112768.0  114213.0  112701.0  113534.0   \n",
       "2022-02-21 00:00:00+00:00   111725.0  111725.0  113405.0  111608.0  112880.0   \n",
       "2022-02-22 00:00:00+00:00   112892.0  112892.0  113315.0  111727.0  111727.0   \n",
       "...                              ...       ...       ...       ...       ...   \n",
       "2024-08-23 00:00:00+00:00   135608.0  135608.0  136478.0  135174.0  135174.0   \n",
       "2024-08-26 00:00:00+00:00   136889.0  136889.0  137013.0  135596.0  135608.0   \n",
       "2024-08-27 00:00:00+00:00   136776.0  136776.0  137213.0  136664.0  136888.0   \n",
       "2024-08-28 00:00:00+00:00   137344.0  137344.0  137469.0  135746.0  136776.0   \n",
       "2024-08-29 00:00:00+00:00   136041.0  136041.0  137370.0  135858.0  137349.0   \n",
       "\n",
       "                             Volume  Log_Returns  Future_Log_Returns  \\\n",
       "Date                                                                   \n",
       "2022-02-16 00:00:00+00:00  12052100     0.004534           -0.014455   \n",
       "2022-02-17 00:00:00+00:00  10807500    -0.014455           -0.006717   \n",
       "2022-02-18 00:00:00+00:00  11300700    -0.006717           -0.009292   \n",
       "2022-02-21 00:00:00+00:00   7864900    -0.009292            0.010391   \n",
       "2022-02-22 00:00:00+00:00  12707000     0.010391           -0.007861   \n",
       "...                             ...          ...                 ...   \n",
       "2024-08-23 00:00:00+00:00   8649400     0.003213            0.009402   \n",
       "2024-08-26 00:00:00+00:00   7560000     0.009402           -0.000826   \n",
       "2024-08-27 00:00:00+00:00   6745900    -0.000826            0.004144   \n",
       "2024-08-28 00:00:00+00:00   7457100     0.004144           -0.009532   \n",
       "2024-08-29 00:00:00+00:00   8385100    -0.009532           -0.000272   \n",
       "\n",
       "                           Realized_Volatility  \n",
       "Date                                            \n",
       "2022-02-16 00:00:00+00:00             0.142409  \n",
       "2022-02-17 00:00:00+00:00             0.143617  \n",
       "2022-02-18 00:00:00+00:00             0.144816  \n",
       "2022-02-21 00:00:00+00:00             0.139736  \n",
       "2022-02-22 00:00:00+00:00             0.135116  \n",
       "...                                        ...  \n",
       "2024-08-23 00:00:00+00:00             0.124693  \n",
       "2024-08-26 00:00:00+00:00             0.124516  \n",
       "2024-08-27 00:00:00+00:00             0.124668  \n",
       "2024-08-28 00:00:00+00:00             0.120305  \n",
       "2024-08-29 00:00:00+00:00             0.120303  \n",
       "\n",
       "[634 rows x 9 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ibov_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test Correlation and Plot  the accuracy of the model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between VIX and realized volatility: 0.7531\n"
     ]
    }
   ],
   "source": [
    "# Convert 'Date' column in vix_df to datetime if it exists\n",
    "if 'Date' in vix_df.columns:\n",
    "    vix_df['Date'] = pd.to_datetime(vix_df['Date'])\n",
    "\n",
    "# Reset the index of ibov_data to convert the Date index to a column\n",
    "ibov_data.reset_index(inplace=True)\n",
    "\n",
    "# Convert 'Date' column in ibov_data to datetime if it exists\n",
    "if 'Date' in ibov_data.columns:\n",
    "    ibov_data['Date'] = pd.to_datetime(ibov_data['Date'])\n",
    "\n",
    "# Remove timezone information from both Date columns\n",
    "vix_df['Date'] = vix_df['Date'].dt.tz_localize(None)  # Remove timezone from vix_df\n",
    "ibov_data['Date'] = ibov_data['Date'].dt.tz_localize(None)  # Remove timezone from ibov_data\n",
    "\n",
    "# Check if 'Date' column exists in ibov_data before merging\n",
    "if 'Date' in ibov_data.columns:\n",
    "    # Merge the VIX DataFrame with the realized volatility DataFrame\n",
    "    merged_df = pd.merge(vix_df, ibov_data[['Date', 'Realized_Volatility']], left_on='Date', right_on='Date', how='left')\n",
    "\n",
    "    # Drop redundant 'Date' column\n",
    "    merged_df.drop(columns=['Date'], inplace=True)\n",
    "\n",
    "    # Drop rows with NaN values in 'VIX' or 'Realized_Volatility'\n",
    "    merged_df.dropna(subset=['VIX', 'Realized_Volatility'], inplace=True)\n",
    "\n",
    "    # Multiply realized volatility by 100 to match VIX scale\n",
    "    merged_df['Realized_Volatility'] *= 50\n",
    "\n",
    "    # Calculate the correlation\n",
    "    correlation = merged_df['VIX'].corr(merged_df['Realized_Volatility'])\n",
    "    print(f\"Correlation between VIX and realized volatility: {correlation:.4f}\")\n",
    "else:\n",
    "    print(\"Warning: 'Date' column not found in ibov_data. Merge operation skipped.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VIX range: 1193.75 to 3189.06\n",
      "Realized Vol range: 5.22 to 15.05\n"
     ]
    }
   ],
   "source": [
    "# Plot the VIX and realized volatility over time\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Use index if Date is the index, or merged_df['date'] if that's the column name\n",
    "x_values = merged_df.index if 'Date' not in merged_df.columns else merged_df['date']\n",
    "\n",
    "# Normalize the VIX and Realized Volatility to the same scale\n",
    "vix_scaled = (merged_df['VIX'] - merged_df['VIX'].min()) / (merged_df['VIX'].max() - merged_df['VIX'].min())\n",
    "realized_vol_scaled = (merged_df['Realized_Volatility'] - merged_df['Realized_Volatility'].min()) / (merged_df['Realized_Volatility'].max() - merged_df['Realized_Volatility'].min())\n",
    "\n",
    "# Create plot with same y-axis scale\n",
    "plt.plot(x_values, vix_scaled, label='VIX (Scaled)')\n",
    "plt.plot(x_values, realized_vol_scaled, label='Realized Volatility (Next 30 Days, Scaled)')\n",
    "\n",
    "# Set the same scale for both lines\n",
    "plt.ylim(0, 1)  # Set y-axis limits to [0, 1] for normalized values\n",
    "\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Normalized Volatility')\n",
    "plt.title('VIX vs. Realized Volatility for IBOV Index (Scaled)')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "# Print the range of values for verification\n",
    "print(f\"VIX range: {merged_df['VIX'].min():.2f} to {merged_df['VIX'].max():.2f}\")\n",
    "print(f\"Realized Vol range: {merged_df['Realized_Volatility'].min():.2f} to {merged_df['Realized_Volatility'].max():.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  # Changed from 'import matplotlib as plt'\n",
    "\n",
    "# Scatter plot of VIX vs. Realized Volatility with linear regression line\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.scatter(merged_df['VIX'], merged_df['Realized_Volatility'], alpha=0.6, label='Data Points')\n",
    "\n",
    "# Calculate linear regression line\n",
    "m, b = np.polyfit(merged_df['VIX'], merged_df['Realized_Volatility'], 1)\n",
    "plt.plot(merged_df['VIX'], m*merged_df['VIX'] + b, color='red', label='Linear Regression Line')\n",
    "plt.xlabel('VIX')\n",
    "plt.ylabel('Realized Volatility (Next 30 Days)')\n",
    "plt.title('Scatter Plot of VIX vs. Realized Volatility with Linear Regression Line')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/pb/m5zk890j6b7g6pz541ycs93h0000gn/T/ipykernel_19024/154747639.py:5: FutureWarning: \n",
      "\n",
      "`shade` is now deprecated in favor of `fill`; setting `fill=True`.\n",
      "This will become an error in seaborn v0.14.0; please update your code.\n",
      "\n",
      "  sns.kdeplot(x=merged_df['VIX'], y=merged_df['Realized_Volatility'], cmap=\"Reds\", shade=True, thresh=0)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "# Create a heatmap\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.kdeplot(x=merged_df['VIX'], y=merged_df['Realized_Volatility'], cmap=\"Reds\", shade=True, thresh=0)\n",
    "plt.xlabel('VIX')\n",
    "plt.ylabel('Realized Volatility (Next 30 Days)')\n",
    "plt.title('Density Heatmap of VIX vs. Realized Volatility')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram of errors\n",
    "plt.figure(figsize=(8, 6))\n",
    "plt.hist(merged_df['VIX'] - merged_df['Realized_Volatility'], bins=30, edgecolor='black')\n",
    "plt.xlabel('Prediction Error (%)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.title('Histogram of VIX Prediction Errors')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}