Options backtesting-verts-Pure Pandas Final-Github.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3b82e6df",
   "metadata": {},
   "source": [
    "## Cong's Backtesting Python Script Mar 2022 - Verticals - Pandas rewrite - Working"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63d161a1",
   "metadata": {},
   "source": [
    "This code backtests the performance of an at-the-money SPY put (sold) and a SPY put (bought) 25 points below, opened every Wednesday from Jan 2022 to May 2022. \n",
    "\n",
    "- This file reads from various data sources, TDA Ameritrade (in_tda), CBOE (in_cboe), Yahoo Finance (in_yahoo), combines them into a new df (in_all) and outputs a df called out.\n",
    "- The backtesting involves running the same trade through many different combinations of variables (DTE, days_to_close, take_prof, take_loss) to find out what was the ideal parameter set, using grid search.\n",
    "- A total of 7,200 possible combinations were evaluated.\n",
    "- Once this ideal set of parameters are determined, trades can be placed while monitoring and comparing the performance of future trades to past trades.\n",
    "- Please contact chuayaocong@gmail.com if you require assistance. Do note that the source files will not be provided due to the large data size (> 3GB)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f61b68fd",
   "metadata": {},
   "source": [
    "### Metadata:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b766b4dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n- DTE            - days to expiry (counting from open_date, will offset slightly (a few days) depending on when is expiry Friday)\\n- days_to_close  - no. of days before closing trade, assuming no early exit\\n- take_prof      - a ratio of credit received. once this ratio is exceeded, to take profit   \\n- take_loss      - a ratio of max loss. once this ratio is exceeded, to take profit  \\n- spy_upper      - upper leg of vertical (assume bullish vertical)\\n- spy_lower      - lower leg of vertical (assume bullish vertical)\\n- spy_upp+0      - the price of upper leg on Day 0\\n- spy_lower+0    - the price of lower leg on Day 0\\n- credit_0       - the credit received on Day 0 for opening the trade\\n- norm_pl+7      - the P/L if the trade is closed normally, i.e. no early exit\\n- norm_pl        - the consolidated PL\\n- takeprof_day+5 - boolean. if True, this means take profit is triggered on Day 5\\n- takeloss_day+5 - boolean. if True, this means take loss is triggered on Day 5\\n- credit_day     - an intermediate value computed for credit value of options on a particular day (not impt)\\n- early_prof+7   - P/L if early profit is taken on Day 7\\n- early_loss+7   - P/L if early loss is taken on Day 7 (+ve value means gain, -ve value means loss)\\n- final_pl       - final P/L of a particular trade taking into account normal exit and early exit\\n- max_loss       - theoretical max loss\\n- final_pl%      - final P/L% of a particular trade\\n- combi_no       - serial no each denoting a set of trades with same params (DTE, days to close, take prof, take loss)\\n- mean_pl%       - computes the mean P/L of each set of params\\n'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "- DTE            - days to expiry (counting from open_date, will offset slightly (a few days) depending on when is expiry Friday)\n",
    "- days_to_close  - no. of days before closing trade, assuming no early exit\n",
    "- take_prof      - a ratio of credit received. once this ratio is exceeded, to take profit   \n",
    "- take_loss      - a ratio of max loss. once this ratio is exceeded, to take profit  \n",
    "- spy_upper      - upper leg of vertical (assume bullish vertical)\n",
    "- spy_lower      - lower leg of vertical (assume bullish vertical)\n",
    "- spy_upp+0      - the price of upper leg on Day 0\n",
    "- spy_lower+0    - the price of lower leg on Day 0\n",
    "- credit_0       - the credit received on Day 0 for opening the trade\n",
    "- norm_pl+7      - the P/L if the trade is closed normally, i.e. no early exit\n",
    "- norm_pl        - the consolidated PL\n",
    "- takeprof_day+5 - boolean. if True, this means take profit is triggered on Day 5\n",
    "- takeloss_day+5 - boolean. if True, this means take loss is triggered on Day 5\n",
    "- credit_day     - an intermediate value computed for credit value of options on a particular day (not impt)\n",
    "- early_prof+7   - P/L if early profit is taken on Day 7\n",
    "- early_loss+7   - P/L if early loss is taken on Day 7 (+ve value means gain, -ve value means loss)\n",
    "- final_pl       - final P/L of a particular trade taking into account normal exit and early exit\n",
    "- max_loss       - theoretical max loss\n",
    "- final_pl%      - final P/L% of a particular trade\n",
    "- combi_no       - serial no each denoting a set of trades with same params (DTE, days to close, take prof, take loss)\n",
    "- mean_pl%       - computes the mean P/L of each set of params\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "383c5d2f",
   "metadata": {},
   "source": [
    "## 1a. Import from TDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fbdc2eb7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd            #opens all CSV files and adds them to dataframe\n",
    "import glob\n",
    "import os\n",
    "from pprint import pprint\n",
    "import pandas_datareader.data as web\n",
    "import numpy as np\n",
    "import datetime\n",
    "from time import time\n",
    "import math\n",
    "\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ba3e72b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading csv ...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\cai_t\\anaconda3\\lib\\site-packages\\numpy\\lib\\arraysetops.py:583: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  mask |= (ar1 == a)\n"
     ]
    },
    {
     "data": {
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       "        vertical-align: middle;\n",
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       "    .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>putCall</th>\n",
       "      <th>symbol</th>\n",
       "      <th>description</th>\n",
       "      <th>mark</th>\n",
       "      <th>inTheMoney</th>\n",
       "      <th>quoteTimeInLong</th>\n",
       "      <th>volatility</th>\n",
       "      <th>delta</th>\n",
       "      <th>gamma</th>\n",
       "      <th>theta</th>\n",
       "      <th>vega</th>\n",
       "      <th>rho</th>\n",
       "      <th>strikePrice</th>\n",
       "      <th>expirationDate</th>\n",
       "      <th>daysToExpiration</th>\n",
       "      <th>quoteTimeInLong_ts</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CALL</td>\n",
       "      <td>SPY_021622C285</td>\n",
       "      <td>SPY Feb 16 2022 285 Call (Weekly)</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-02-16 21:14:22</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.638</td>\n",
       "      <td>0.0</td>\n",
       "      <td>188.996</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005</td>\n",
       "      <td>285.0</td>\n",
       "      <td>2022-02-16 21:00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2022-02-16 21:14:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CALL</td>\n",
       "      <td>SPY_021622C290</td>\n",
       "      <td>SPY Feb 16 2022 290 Call (Weekly)</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-02-16 21:14:22</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>290.0</td>\n",
       "      <td>2022-02-16 21:00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2022-02-16 21:14:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CALL</td>\n",
       "      <td>SPY_021622C295</td>\n",
       "      <td>SPY Feb 16 2022 295 Call (Weekly)</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-02-16 21:14:44</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>295.0</td>\n",
       "      <td>2022-02-16 21:00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2022-02-16 21:14:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CALL</td>\n",
       "      <td>SPY_021622C300</td>\n",
       "      <td>SPY Feb 16 2022 300 Call (Weekly)</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-02-16 21:14:44</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>300.0</td>\n",
       "      <td>2022-02-16 21:00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2022-02-16 21:14:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CALL</td>\n",
       "      <td>SPY_021622C305</td>\n",
       "      <td>SPY Feb 16 2022 305 Call (Weekly)</td>\n",
       "      <td>0.00</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-02-16 21:14:44</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>305.0</td>\n",
       "      <td>2022-02-16 21:00:00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2022-02-16 21:14:44</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",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9520</th>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY_122024P700</td>\n",
       "      <td>SPY Dec 20 2024 700 Put</td>\n",
       "      <td>285.44</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.349</td>\n",
       "      <td>-1.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>700.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9521</th>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY_122024P705</td>\n",
       "      <td>SPY Dec 20 2024 705 Put</td>\n",
       "      <td>290.44</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.355</td>\n",
       "      <td>-1.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>705.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9522</th>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY_122024P710</td>\n",
       "      <td>SPY Dec 20 2024 710 Put</td>\n",
       "      <td>295.43</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.350</td>\n",
       "      <td>-1.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>710.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9523</th>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY_122024P715</td>\n",
       "      <td>SPY Dec 20 2024 715 Put</td>\n",
       "      <td>300.43</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.333</td>\n",
       "      <td>-1.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>715.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9524</th>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY_122024P720</td>\n",
       "      <td>SPY Dec 20 2024 720 Put</td>\n",
       "      <td>305.43</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.302</td>\n",
       "      <td>-1.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>720.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10131206 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           putCall          symbol                        description    mark  \\\n",
       "Unnamed: 0                                                                      \n",
       "1             CALL  SPY_021622C285  SPY Feb 16 2022 285 Call (Weekly)    0.00   \n",
       "2             CALL  SPY_021622C290  SPY Feb 16 2022 290 Call (Weekly)    0.00   \n",
       "3             CALL  SPY_021622C295  SPY Feb 16 2022 295 Call (Weekly)    0.00   \n",
       "4             CALL  SPY_021622C300  SPY Feb 16 2022 300 Call (Weekly)    0.00   \n",
       "5             CALL  SPY_021622C305  SPY Feb 16 2022 305 Call (Weekly)    0.00   \n",
       "...            ...             ...                                ...     ...   \n",
       "9520           PUT  SPY_122024P700            SPY Dec 20 2024 700 Put  285.44   \n",
       "9521           PUT  SPY_122024P705            SPY Dec 20 2024 705 Put  290.44   \n",
       "9522           PUT  SPY_122024P710            SPY Dec 20 2024 710 Put  295.43   \n",
       "9523           PUT  SPY_122024P715            SPY Dec 20 2024 715 Put  300.43   \n",
       "9524           PUT  SPY_122024P720            SPY Dec 20 2024 720 Put  305.43   \n",
       "\n",
       "            inTheMoney      quoteTimeInLong  volatility  delta  gamma  \\\n",
       "Unnamed: 0                                                              \n",
       "1                 True  2022-02-16 21:14:22       0.000  0.638    0.0   \n",
       "2                 True  2022-02-16 21:14:22       0.000  0.000    0.0   \n",
       "3                 True  2022-02-16 21:14:44       0.000  0.000    0.0   \n",
       "4                 True  2022-02-16 21:14:44       0.000  0.000    0.0   \n",
       "5                 True  2022-02-16 21:14:44       0.000  0.000    0.0   \n",
       "...                ...                  ...         ...    ...    ...   \n",
       "9520              True  2022-05-27 20:14:40      17.349 -1.000    0.0   \n",
       "9521              True  2022-05-27 20:14:40      17.355 -1.000    0.0   \n",
       "9522              True  2022-05-27 20:14:40      17.350 -1.000    0.0   \n",
       "9523              True  2022-05-27 20:14:40      17.333 -1.000    0.0   \n",
       "9524              True  2022-05-27 20:14:40      17.302 -1.000    0.0   \n",
       "\n",
       "              theta  vega    rho  strikePrice       expirationDate  \\\n",
       "Unnamed: 0                                                           \n",
       "1           188.996   0.0  0.005        285.0  2022-02-16 21:00:00   \n",
       "2             0.000   0.0  0.000        290.0  2022-02-16 21:00:00   \n",
       "3             0.000   0.0  0.000        295.0  2022-02-16 21:00:00   \n",
       "4             0.000   0.0  0.000        300.0  2022-02-16 21:00:00   \n",
       "5             0.000   0.0  0.000        305.0  2022-02-16 21:00:00   \n",
       "...             ...   ...    ...          ...                  ...   \n",
       "9520          0.000   0.0  0.000        700.0  2024-12-20 21:00:00   \n",
       "9521          0.000   0.0  0.000        705.0  2024-12-20 21:00:00   \n",
       "9522          0.000   0.0  0.000        710.0  2024-12-20 21:00:00   \n",
       "9523          0.000   0.0  0.000        715.0  2024-12-20 21:00:00   \n",
       "9524          0.000   0.0  0.000        720.0  2024-12-20 21:00:00   \n",
       "\n",
       "            daysToExpiration  quoteTimeInLong_ts  \n",
       "Unnamed: 0                                        \n",
       "1                        0.0 2022-02-16 21:14:22  \n",
       "2                        0.0 2022-02-16 21:14:22  \n",
       "3                        0.0 2022-02-16 21:14:44  \n",
       "4                        0.0 2022-02-16 21:14:44  \n",
       "5                        0.0 2022-02-16 21:14:44  \n",
       "...                      ...                 ...  \n",
       "9520                   936.0 2022-05-27 20:14:40  \n",
       "9521                   936.0 2022-05-27 20:14:40  \n",
       "9522                   936.0 2022-05-27 20:14:40  \n",
       "9523                   936.0 2022-05-27 20:14:40  \n",
       "9524                   936.0 2022-05-27 20:14:40  \n",
       "\n",
       "[10131206 rows x 16 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time taken to read csv:  85.31009697914124\n"
     ]
    }
   ],
   "source": [
    "print(\"Reading csv ...\")\n",
    "beforetime = time()\n",
    "\n",
    "in_tda = pd.read_csv(\"C:\\\\Users\\\\cai_t\\\\Desktop\\\\2022 files\\\\_BACKTEST\\\\rstudio-export\\\\combined.csv\", index_col=0)\n",
    "\n",
    "in_tda = in_tda[[\"putCall\",\"symbol\",\"description\",\"mark\",\"inTheMoney\",\n",
    "               \"quoteTimeInLong\",\"volatility\",\"delta\",\"gamma\",\n",
    "               \"theta\",\"vega\",\"rho\",\"strikePrice\",\"expirationDate\",\n",
    "               \"daysToExpiration\"]]\n",
    "\n",
    "quoteTimeInLong_series = (pd.to_datetime(in_tda[\"quoteTimeInLong\"])).copy() #creates new column quotetimeinlong in timestamp format\n",
    "quoteTimeInLong_series = quoteTimeInLong_series.rename(\"quoteTimeInLong_ts\")    #renames column to _ts\n",
    "in_tda = pd.concat([in_tda,quoteTimeInLong_series], sort=False, axis=1)\n",
    "display(in_tda)\n",
    "print(\"time taken to read csv: \",time()-beforetime)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "960010d9",
   "metadata": {},
   "source": [
    "## 1b. Import CSVs from CBOE datashop (local drive)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "48b93a9e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Joining files ... \n"
     ]
    },
    {
     "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>option_type</th>\n",
       "      <th>underlying_symbol</th>\n",
       "      <th>quote_date</th>\n",
       "      <th>expiration</th>\n",
       "      <th>strike</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>underlying_bid_eod</th>\n",
       "      <th>quoteTimeInLong_ts</th>\n",
       "      <th>symbol</th>\n",
       "      <th>mark</th>\n",
       "      <th>putCall</th>\n",
       "      <th>description</th>\n",
       "      <th>inTheMoney</th>\n",
       "      <th>quoteTimeInLong</th>\n",
       "      <th>volatility</th>\n",
       "      <th>delta</th>\n",
       "      <th>gamma</th>\n",
       "      <th>theta</th>\n",
       "      <th>vega</th>\n",
       "      <th>rho</th>\n",
       "      <th>strikePrice</th>\n",
       "      <th>expirationDate</th>\n",
       "      <th>daysToExpiration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C</td>\n",
       "      <td>SPY</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.59</td>\n",
       "      <td>2022-01-03 00:00:00</td>\n",
       "      <td>SPY_091622C140</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>P</td>\n",
       "      <td>SPY</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>140.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.59</td>\n",
       "      <td>2022-01-03 00:00:00</td>\n",
       "      <td>SPY_091622P140</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "      <td>SPY</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.59</td>\n",
       "      <td>2022-01-03 00:00:00</td>\n",
       "      <td>SPY_091622C145</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>P</td>\n",
       "      <td>SPY</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.59</td>\n",
       "      <td>2022-01-03 00:00:00</td>\n",
       "      <td>SPY_091622P145</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>C</td>\n",
       "      <td>SPY</td>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>2022-09-16</td>\n",
       "      <td>150.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>477.59</td>\n",
       "      <td>2022-01-03 00:00:00</td>\n",
       "      <td>SPY_091622C150</td>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9520</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>SPY_122024P700</td>\n",
       "      <td>285.44</td>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY Dec 20 2024 700 Put</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.349</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9521</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>SPY_122024P705</td>\n",
       "      <td>290.44</td>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY Dec 20 2024 705 Put</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.355</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>705.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9522</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>SPY_122024P710</td>\n",
       "      <td>295.43</td>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY Dec 20 2024 710 Put</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.350</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>710.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9523</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>SPY_122024P715</td>\n",
       "      <td>300.43</td>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY Dec 20 2024 715 Put</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.333</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>715.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9524</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>SPY_122024P720</td>\n",
       "      <td>305.43</td>\n",
       "      <td>PUT</td>\n",
       "      <td>SPY Dec 20 2024 720 Put</td>\n",
       "      <td>True</td>\n",
       "      <td>2022-05-27 20:14:40</td>\n",
       "      <td>17.302</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>720.0</td>\n",
       "      <td>2024-12-20 21:00:00</td>\n",
       "      <td>936.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10427624 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     option_type underlying_symbol  quote_date  expiration  strike  open  \\\n",
       "0              C               SPY  2022-01-03  2022-09-16   140.0   0.0   \n",
       "1              P               SPY  2022-01-03  2022-09-16   140.0   0.0   \n",
       "2              C               SPY  2022-01-03  2022-09-16   145.0   0.0   \n",
       "3              P               SPY  2022-01-03  2022-09-16   145.0   0.0   \n",
       "4              C               SPY  2022-01-03  2022-09-16   150.0   0.0   \n",
       "...          ...               ...         ...         ...     ...   ...   \n",
       "9520         NaN               NaN         NaN         NaN     NaN   NaN   \n",
       "9521         NaN               NaN         NaN         NaN     NaN   NaN   \n",
       "9522         NaN               NaN         NaN         NaN     NaN   NaN   \n",
       "9523         NaN               NaN         NaN         NaN     NaN   NaN   \n",
       "9524         NaN               NaN         NaN         NaN     NaN   NaN   \n",
       "\n",
       "      high  low  close  underlying_bid_eod  quoteTimeInLong_ts  \\\n",
       "0      0.0  0.0    0.0              477.59 2022-01-03 00:00:00   \n",
       "1      0.0  0.0    0.0              477.59 2022-01-03 00:00:00   \n",
       "2      0.0  0.0    0.0              477.59 2022-01-03 00:00:00   \n",
       "3      0.0  0.0    0.0              477.59 2022-01-03 00:00:00   \n",
       "4      0.0  0.0    0.0              477.59 2022-01-03 00:00:00   \n",
       "...    ...  ...    ...                 ...                 ...   \n",
       "9520   NaN  NaN    NaN                 NaN 2022-05-27 20:14:40   \n",
       "9521   NaN  NaN    NaN                 NaN 2022-05-27 20:14:40   \n",
       "9522   NaN  NaN    NaN                 NaN 2022-05-27 20:14:40   \n",
       "9523   NaN  NaN    NaN                 NaN 2022-05-27 20:14:40   \n",
       "9524   NaN  NaN    NaN                 NaN 2022-05-27 20:14:40   \n",
       "\n",
       "              symbol    mark putCall              description inTheMoney  \\\n",
       "0     SPY_091622C140    0.00     NaN                      NaN        NaN   \n",
       "1     SPY_091622P140    0.00     NaN                      NaN        NaN   \n",
       "2     SPY_091622C145    0.00     NaN                      NaN        NaN   \n",
       "3     SPY_091622P145    0.00     NaN                      NaN        NaN   \n",
       "4     SPY_091622C150    0.00     NaN                      NaN        NaN   \n",
       "...              ...     ...     ...                      ...        ...   \n",
       "9520  SPY_122024P700  285.44     PUT  SPY Dec 20 2024 700 Put       True   \n",
       "9521  SPY_122024P705  290.44     PUT  SPY Dec 20 2024 705 Put       True   \n",
       "9522  SPY_122024P710  295.43     PUT  SPY Dec 20 2024 710 Put       True   \n",
       "9523  SPY_122024P715  300.43     PUT  SPY Dec 20 2024 715 Put       True   \n",
       "9524  SPY_122024P720  305.43     PUT  SPY Dec 20 2024 720 Put       True   \n",
       "\n",
       "          quoteTimeInLong  volatility  delta  gamma  theta  vega  rho  \\\n",
       "0                     NaN         NaN    NaN    NaN    NaN   NaN  NaN   \n",
       "1                     NaN         NaN    NaN    NaN    NaN   NaN  NaN   \n",
       "2                     NaN         NaN    NaN    NaN    NaN   NaN  NaN   \n",
       "3                     NaN         NaN    NaN    NaN    NaN   NaN  NaN   \n",
       "4                     NaN         NaN    NaN    NaN    NaN   NaN  NaN   \n",
       "...                   ...         ...    ...    ...    ...   ...  ...   \n",
       "9520  2022-05-27 20:14:40      17.349   -1.0    0.0    0.0   0.0  0.0   \n",
       "9521  2022-05-27 20:14:40      17.355   -1.0    0.0    0.0   0.0  0.0   \n",
       "9522  2022-05-27 20:14:40      17.350   -1.0    0.0    0.0   0.0  0.0   \n",
       "9523  2022-05-27 20:14:40      17.333   -1.0    0.0    0.0   0.0  0.0   \n",
       "9524  2022-05-27 20:14:40      17.302   -1.0    0.0    0.0   0.0  0.0   \n",
       "\n",
       "      strikePrice       expirationDate  daysToExpiration  \n",
       "0             NaN                  NaN               NaN  \n",
       "1             NaN                  NaN               NaN  \n",
       "2             NaN                  NaN               NaN  \n",
       "3             NaN                  NaN               NaN  \n",
       "4             NaN                  NaN               NaN  \n",
       "...           ...                  ...               ...  \n",
       "9520        700.0  2024-12-20 21:00:00             936.0  \n",
       "9521        705.0  2024-12-20 21:00:00             936.0  \n",
       "9522        710.0  2024-12-20 21:00:00             936.0  \n",
       "9523        715.0  2024-12-20 21:00:00             936.0  \n",
       "9524        720.0  2024-12-20 21:00:00             936.0  \n",
       "\n",
       "[10427624 rows x 26 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "files = os.path.join(\"C:\\\\Users\\\\cai_t\\\\Desktop\\\\2022 files\\\\_BACKTEST\\\\rstudio-export\\\\CBOE purchase\", \"UnderlyingOptionsEOD*.csv\")\n",
    "files = glob.glob(files)\n",
    "print(\"Joining files ... \");\n",
    "in_cboe = pd.concat(map(pd.read_csv, files), ignore_index=True)\n",
    "# pprint(df)\n",
    "\n",
    "in_cboe = in_cboe[[\"option_type\",\"underlying_symbol\",\"quote_date\",\"expiration\",\"strike\",\"open\",\n",
    "                  \"high\",\"low\",\"close\",\"underlying_bid_eod\"]]\n",
    "\n",
    "quote_date = (pd.to_datetime(in_cboe[\"quote_date\"])).copy() #creates new column quotetimeinlong in timestamp format\n",
    "quote_date = quote_date.rename(\"quoteTimeInLong_ts\")    #renames column to _ts\n",
    "in_cboe = pd.concat([in_cboe,quote_date], sort=False, axis=1)\n",
    "\n",
    "lista=[]\n",
    "\n",
    "for i in range(len(in_cboe['expiration'])):               #process text string to format SPY_021622C285 for e.g.\n",
    "    lista.append(in_cboe['underlying_symbol'][i] + \"_\" +\n",
    "                 in_cboe['expiration'][i][5:7] + \n",
    "                 in_cboe['expiration'][i][8:10] +\n",
    "                 in_cboe['expiration'][i][2:4] +\n",
    "                 in_cboe['option_type'][i] +\n",
    "                 str(int(in_cboe['strike'][i])))\n",
    "\n",
    "in_cboe['symbol'] = lista                                   #creates and stores in new column 'symbol' in df\n",
    "in_cboe['mark'] = in_cboe['close']\n",
    "in_all0 = pd.concat([in_cboe, in_tda])                  #combine 2 datasets into 1\n",
    "\n",
    "display(in_all0)\n",
    "# print(in_all['symbol'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12ef2608",
   "metadata": {},
   "source": [
    "## 1c. Import data from Yahoo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "84c413ad",
   "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>^VIX</th>\n",
       "      <th>SPY</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-05-30</th>\n",
       "      <td>10.380000</td>\n",
       "      <td>221.303299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-31</th>\n",
       "      <td>10.410000</td>\n",
       "      <td>221.248352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>9.890000</td>\n",
       "      <td>223.007782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-02</th>\n",
       "      <td>9.750000</td>\n",
       "      <td>223.750061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-05</th>\n",
       "      <td>10.070000</td>\n",
       "      <td>223.585098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-24</th>\n",
       "      <td>29.450001</td>\n",
       "      <td>393.890015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-25</th>\n",
       "      <td>28.370001</td>\n",
       "      <td>397.369995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-26</th>\n",
       "      <td>27.500000</td>\n",
       "      <td>405.309998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-27</th>\n",
       "      <td>25.719999</td>\n",
       "      <td>415.260010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-30</th>\n",
       "      <td>26.180000</td>\n",
       "      <td>415.260010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1261 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ^VIX         SPY\n",
       "Date                             \n",
       "2017-05-30  10.380000  221.303299\n",
       "2017-05-31  10.410000  221.248352\n",
       "2017-06-01   9.890000  223.007782\n",
       "2017-06-02   9.750000  223.750061\n",
       "2017-06-05  10.070000  223.585098\n",
       "...               ...         ...\n",
       "2022-05-24  29.450001  393.890015\n",
       "2022-05-25  28.370001  397.369995\n",
       "2022-05-26  27.500000  405.309998\n",
       "2022-05-27  25.719999  415.260010\n",
       "2022-05-30  26.180000  415.260010\n",
       "\n",
       "[1261 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas_datareader.data as web\n",
    "\n",
    "all_data = {ticker: web.get_data_yahoo(ticker)       #dictionary comprehension\n",
    "           for ticker in [\"^VIX\",\"SPY\"]}\n",
    "\n",
    "\n",
    "try:\n",
    "    in_yahoo = pd.DataFrame({ticker: data ['Adj Close']\n",
    "               for ticker, data in all_data.items()})\n",
    "except:\n",
    "    print(\"Error encountered during copy from Yahoo Finance, should self resolve during market hours. putting [^VIX,SPY] results in error during 315am to 915am ET due to uneven length of columns\")\n",
    "\n",
    "# Calculate EMAs\n",
    "data = []\n",
    "in_yahoo0 = in_yahoo.fillna(method=\"ffill\")                 \n",
    "display(in_yahoo0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15514be8",
   "metadata": {},
   "source": [
    "## 2. Main backtesting code for Verticals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "1f138763",
   "metadata": {},
   "outputs": [],
   "source": [
    "# holding lot for dataframes, run code from here on instead to avoid having to compile code above\n",
    "in_all = in_all0.copy()\n",
    "in_yahoo = in_yahoo0.copy()\n",
    "out = pd.DataFrame([])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9d95d8f",
   "metadata": {},
   "source": [
    "### 2b. Normalise 30 min data into daily data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "a9cf2f48",
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize(in_all):            # normalise 30min data into daily data from SPY files\n",
    "\n",
    "    in_all.set_index('quoteTimeInLong_ts', inplace=True)     #NEW\n",
    "    in_all.index = in_all.index.normalize()      #normalise the datetime to dates only\n",
    "    in_all = in_all[['symbol','mark']]\n",
    "    in_all = in_all.groupby(['quoteTimeInLong_ts','symbol'])['mark'].mean()      #this dataframe df shows the average mark price of each option for each day\n",
    "    return in_all\n",
    "\n",
    "in_all = normalize(in_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dee04c60",
   "metadata": {},
   "source": [
    "### 2c. Initialise Parameters for options "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "8d617707",
   "metadata": {},
   "outputs": [],
   "source": [
    "def init_param():\n",
    "       \n",
    "    master_list = []\n",
    "\n",
    "# #     mini test list\n",
    "#     dte = [18, 21]\n",
    "#     days_to_close = [7, 9]\n",
    "#     take_prof = [0.9]\n",
    "#     take_loss = [1]\n",
    "\n",
    "#     #medium test list\n",
    "#     dte = [18,21,24,27,32]\n",
    "#     days_to_close = [7,9,12,16]\n",
    "#     take_prof = [0.2,0.4,0.6,0.8,1.0]\n",
    "#     take_loss = [0.2,0.4,0.6,0.8,1.0]\n",
    "#     #5*4*3*6 = 360 loops -> 4 hrs\n",
    "    #5*4*5*9 = 900 loops -> 10 hrs\n",
    "        \n",
    "    dte = [18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]\n",
    "    days_to_close = [7, 8, 9, 12, 13, 14, 15, 16]                      # skipping days which will result in weekends\n",
    "    take_prof = [0.5, 0.6, 0.7, 0.8, 0.9, 1]\n",
    "    take_loss = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]\n",
    "   # 15*8*6*10 = 7200\n",
    "    master_list.clear()\n",
    "\n",
    "    for i in range(len(dte)):\n",
    "        for j in range(len(days_to_close)):\n",
    "            for k in range(len(take_prof)):\n",
    "                for l in range(len(take_loss)):\n",
    "                    master_list.append([dte[i], days_to_close[j], take_prof[k], take_loss[l]])\n",
    "\n",
    "    master_list = np.array(master_list)        #convert to numpy array\n",
    "    no_of_iter = len(dte) * len(days_to_close) * len(take_prof) * len(take_loss)    # returns no of iterations for later use\n",
    "    \n",
    "    return master_list, no_of_iter, days_to_close\n",
    "\n",
    "mast_list, no_of_iter, days_to_close = init_param()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "5350df5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def false_func():\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ccc3828",
   "metadata": {},
   "source": [
    "### 2d. Create open date column in out df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "cd7baaf7",
   "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>index</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2022-05-18</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151195</th>\n",
       "      <td>16</td>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151196</th>\n",
       "      <td>17</td>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151197</th>\n",
       "      <td>18</td>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151198</th>\n",
       "      <td>19</td>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151199</th>\n",
       "      <td>20</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151200 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        index          0     0     1    2    3\n",
       "0           0 2022-05-25  18.0   7.0  0.5  0.1\n",
       "1           1 2022-05-18  18.0   7.0  0.5  0.1\n",
       "2           2 2022-05-11  18.0   7.0  0.5  0.1\n",
       "3           3 2022-05-04  18.0   7.0  0.5  0.1\n",
       "4           4 2022-04-27  18.0   7.0  0.5  0.1\n",
       "...       ...        ...   ...   ...  ...  ...\n",
       "151195     16 2022-02-02  32.0  16.0  1.0  1.0\n",
       "151196     17 2022-01-26  32.0  16.0  1.0  1.0\n",
       "151197     18 2022-01-19  32.0  16.0  1.0  1.0\n",
       "151198     19 2022-01-12  32.0  16.0  1.0  1.0\n",
       "151199     20 2022-01-05  32.0  16.0  1.0  1.0\n",
       "\n",
       "[151200 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def open_date():      # create open_date column\n",
    "    date = pd.Timestamp(datetime.date.today()).round(freq = 'D')- pd.offsets.Week(weekday=2)\n",
    "    \n",
    "    try:\n",
    "        in_yahoo.loc[date][1]\n",
    "    \n",
    "    except:\n",
    "        print(\"Key error because you are probably searching for today's SPY price which doesnt exist (yet)!\",\"\\nDate you searched for:\",date)\n",
    "        date = date - pd.Timedelta(\"7 day\")\n",
    "        print(\"Decreasing days by 7 to try..\")\n",
    "    \n",
    "    finally:\n",
    "        list_dates = []\n",
    "        \n",
    "        while pd.Timestamp(2022,1,1,0) < date < pd.Timestamp(datetime.date.today()):       # initialising trades every 7 days\n",
    "                     \n",
    "            list_dates.append(date)\n",
    "            date -= pd.Timedelta(\"7 day\")\n",
    "\n",
    "    # create columns of params\n",
    " \n",
    "    out_param = np.repeat(mast_list, len(list_dates), axis=0)                                    # repeat params over length of list dates\n",
    "    out_param = pd.DataFrame(out_param)\n",
    "    out_dates = pd.DataFrame(list_dates)\n",
    "    out_dates = pd.concat([out_dates] * no_of_iter, axis=0)                            # repeat the open_dates n times, based on the no. of iterations  \n",
    "    out_dates.reset_index(inplace=True)\n",
    "    \n",
    "    out = pd.concat([out_dates, out_param], axis=1) \n",
    "    out.columns = ['trade_no','open_date', 'DTE', 'days_to_close', 'take_prof','take_loss']   #rename columns\n",
    "    out = pd.merge(out, in_yahoo, left_on = ['open_date'], right_on = ['Date'], how='left')        #merge out and in_yahoo together \n",
    "\n",
    "    return out\n",
    "\n",
    "out = open_date()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51b52602",
   "metadata": {},
   "source": [
    "### 2e. Determining options to buy/sell based on params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "ab59f0fd",
   "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>trade_no</th>\n",
       "      <th>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>^VIX</th>\n",
       "      <th>SPY</th>\n",
       "      <th>spy_upper</th>\n",
       "      <th>spy_lower</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2022-05-25</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>28.370001</td>\n",
       "      <td>397.369995</td>\n",
       "      <td>SPY_061722P395</td>\n",
       "      <td>SPY_061722P370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2022-05-18</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>30.959999</td>\n",
       "      <td>391.859985</td>\n",
       "      <td>SPY_061022P390</td>\n",
       "      <td>SPY_061022P365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>32.560001</td>\n",
       "      <td>392.750000</td>\n",
       "      <td>SPY_060322P390</td>\n",
       "      <td>SPY_060322P365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>25.420000</td>\n",
       "      <td>429.059998</td>\n",
       "      <td>SPY_052722P425</td>\n",
       "      <td>SPY_052722P400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>417.269989</td>\n",
       "      <td>SPY_052022P415</td>\n",
       "      <td>SPY_052022P390</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151195</th>\n",
       "      <td>16</td>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.090000</td>\n",
       "      <td>455.933594</td>\n",
       "      <td>SPY_031122P455</td>\n",
       "      <td>SPY_031122P430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151196</th>\n",
       "      <td>17</td>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.959999</td>\n",
       "      <td>432.037842</td>\n",
       "      <td>SPY_030422P430</td>\n",
       "      <td>SPY_030422P405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151197</th>\n",
       "      <td>18</td>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.850000</td>\n",
       "      <td>450.350922</td>\n",
       "      <td>SPY_022522P450</td>\n",
       "      <td>SPY_022522P425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151198</th>\n",
       "      <td>19</td>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.620001</td>\n",
       "      <td>469.561249</td>\n",
       "      <td>SPY_021822P465</td>\n",
       "      <td>SPY_021822P440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151199</th>\n",
       "      <td>20</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.730000</td>\n",
       "      <td>466.929443</td>\n",
       "      <td>SPY_021122P465</td>\n",
       "      <td>SPY_021122P440</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>151200 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        trade_no  open_date   DTE  days_to_close  take_prof  take_loss  \\\n",
       "0              0 2022-05-25  18.0            7.0        0.5        0.1   \n",
       "1              1 2022-05-18  18.0            7.0        0.5        0.1   \n",
       "2              2 2022-05-11  18.0            7.0        0.5        0.1   \n",
       "3              3 2022-05-04  18.0            7.0        0.5        0.1   \n",
       "4              4 2022-04-27  18.0            7.0        0.5        0.1   \n",
       "...          ...        ...   ...            ...        ...        ...   \n",
       "151195        16 2022-02-02  32.0           16.0        1.0        1.0   \n",
       "151196        17 2022-01-26  32.0           16.0        1.0        1.0   \n",
       "151197        18 2022-01-19  32.0           16.0        1.0        1.0   \n",
       "151198        19 2022-01-12  32.0           16.0        1.0        1.0   \n",
       "151199        20 2022-01-05  32.0           16.0        1.0        1.0   \n",
       "\n",
       "             ^VIX         SPY       spy_upper       spy_lower  \n",
       "0       28.370001  397.369995  SPY_061722P395  SPY_061722P370  \n",
       "1       30.959999  391.859985  SPY_061022P390  SPY_061022P365  \n",
       "2       32.560001  392.750000  SPY_060322P390  SPY_060322P365  \n",
       "3       25.420000  429.059998  SPY_052722P425  SPY_052722P400  \n",
       "4       31.600000  417.269989  SPY_052022P415  SPY_052022P390  \n",
       "...           ...         ...             ...             ...  \n",
       "151195  22.090000  455.933594  SPY_031122P455  SPY_031122P430  \n",
       "151196  31.959999  432.037842  SPY_030422P430  SPY_030422P405  \n",
       "151197  23.850000  450.350922  SPY_022522P450  SPY_022522P425  \n",
       "151198  17.620001  469.561249  SPY_021822P465  SPY_021822P440  \n",
       "151199  19.730000  466.929443  SPY_021122P465  SPY_021122P440  \n",
       "\n",
       "[151200 rows x 10 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def open_trade(df):\n",
    "    df['opex_date'] = df.open_date + pd.to_timedelta(df.DTE, unit='d') + pd.offsets.Week(weekday=4)        #changed pd.DateOffset(days = 25) to pd.to_timedelta(df.DTE, unit='d')\n",
    "    df['opex_date'] = df['opex_date'].astype(str)\n",
    "    df['opex_date'] = df.opex_date.str[5:7] + df.opex_date.str[8:10] + df.opex_date.str[2:4]\n",
    "    \n",
    "    df['spy_upper'] = df['SPY']    \n",
    "    df['spy_upper'] = df['spy_upper'] - (df['spy_upper'] % 5)                  # round to nearest 5\n",
    "    df['spy_lower'] = df['spy_upper'] - 25\n",
    "    \n",
    "    df['spy_upper'] = df['spy_upper'].astype(int).astype(str)\n",
    "    df['spy_lower'] = df['spy_lower'].astype(int).astype(str)\n",
    "    \n",
    "    df['spy_upper'] = \"SPY_\" + df['opex_date'] + \"P\" + df['spy_upper']\n",
    "    df['spy_lower'] = \"SPY_\" + df['opex_date'] + \"P\" + df['spy_lower']\n",
    "    \n",
    "    df.drop(['opex_date'], axis=1, inplace=True)\n",
    "    \n",
    "    return df\n",
    "\n",
    "open_trade(out)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ca6d1a6",
   "metadata": {},
   "source": [
    "### 2f. Updating options interim prices via columns spy_upp+ and spy_lower+"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "871ba8bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def interim_price(out, in_all):    # this function merges the out and in_all dfs together (using merge as a sort of vlookup) and returns the 0 to 16 day SPY option prices as columns.\n",
    "    \n",
    "    merged = out.copy()\n",
    "    \n",
    "    for days in range(0, 17):\n",
    "        merged = pd.merge(merged, in_all, \n",
    "                          left_on = ['spy_upper', out['open_date'] + datetime.timedelta(days)], \n",
    "                          right_on = ['symbol','quoteTimeInLong_ts'], \n",
    "                          how ='left')\n",
    "        merged.rename(columns = {'mark':\"spy_upp+\" + str(days)}, inplace=True)\n",
    "    \n",
    "    for days in range(0, 17):        \n",
    "        merged = pd.merge(merged, in_all, \n",
    "                          left_on = ['spy_lower', out['open_date'] + datetime.timedelta(days)], \n",
    "                          right_on = ['symbol','quoteTimeInLong_ts'], \n",
    "                          how = 'left')\n",
    "        merged.rename(columns = {'mark':\"spy_lower+\" + str(days)}, inplace=True)\n",
    "\n",
    "    return merged\n",
    "\n",
    "out = interim_price(out, in_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "00d1f083",
   "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>quoteTimeInLong_ts</th>\n",
       "      <th>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>^VIX</th>\n",
       "      <th>SPY</th>\n",
       "      <th>spy_upper</th>\n",
       "      <th>spy_lower</th>\n",
       "      <th>spy_upp+0</th>\n",
       "      <th>spy_upp+1</th>\n",
       "      <th>spy_upp+2</th>\n",
       "      <th>spy_upp+3</th>\n",
       "      <th>spy_upp+4</th>\n",
       "      <th>spy_upp+5</th>\n",
       "      <th>spy_upp+6</th>\n",
       "      <th>spy_upp+7</th>\n",
       "      <th>spy_upp+8</th>\n",
       "      <th>spy_upp+9</th>\n",
       "      <th>spy_upp+10</th>\n",
       "      <th>spy_upp+11</th>\n",
       "      <th>spy_upp+12</th>\n",
       "      <th>spy_upp+13</th>\n",
       "      <th>spy_upp+14</th>\n",
       "      <th>spy_upp+15</th>\n",
       "      <th>spy_upp+16</th>\n",
       "      <th>spy_lower+0</th>\n",
       "      <th>spy_lower+1</th>\n",
       "      <th>spy_lower+2</th>\n",
       "      <th>spy_lower+3</th>\n",
       "      <th>spy_lower+4</th>\n",
       "      <th>spy_lower+5</th>\n",
       "      <th>spy_lower+6</th>\n",
       "      <th>spy_lower+7</th>\n",
       "      <th>spy_lower+8</th>\n",
       "      <th>spy_lower+9</th>\n",
       "      <th>spy_lower+10</th>\n",
       "      <th>spy_lower+11</th>\n",
       "      <th>spy_lower+12</th>\n",
       "      <th>spy_lower+13</th>\n",
       "      <th>spy_lower+14</th>\n",
       "      <th>spy_lower+15</th>\n",
       "      <th>spy_lower+16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_no</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",
       "      <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",
       "      <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",
       "      <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",
       "      <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>2</th>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>32.560001</td>\n",
       "      <td>392.750000</td>\n",
       "      <td>SPY_060322P390</td>\n",
       "      <td>SPY_060322P365</td>\n",
       "      <td>8.787143</td>\n",
       "      <td>11.882143</td>\n",
       "      <td>6.408293</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>3.523571</td>\n",
       "      <td>7.051429</td>\n",
       "      <td>8.888571</td>\n",
       "      <td>9.086190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>7.227857</td>\n",
       "      <td>4.637857</td>\n",
       "      <td>1.684286</td>\n",
       "      <td>0.341707</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>4.145714</td>\n",
       "      <td>1.800244</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>0.756429</td>\n",
       "      <td>1.737857</td>\n",
       "      <td>2.275714</td>\n",
       "      <td>2.027381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.630714</td>\n",
       "      <td>0.229286</td>\n",
       "      <td>0.090244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>25.420000</td>\n",
       "      <td>429.059998</td>\n",
       "      <td>SPY_052722P425</td>\n",
       "      <td>SPY_052722P400</td>\n",
       "      <td>13.824286</td>\n",
       "      <td>16.206429</td>\n",
       "      <td>18.944524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>27.169286</td>\n",
       "      <td>28.667857</td>\n",
       "      <td>35.492857</td>\n",
       "      <td>25.042439</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>19.578571</td>\n",
       "      <td>29.685714</td>\n",
       "      <td>34.800000</td>\n",
       "      <td>36.642381</td>\n",
       "      <td>5.157143</td>\n",
       "      <td>6.400714</td>\n",
       "      <td>7.304048</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>11.200714</td>\n",
       "      <td>11.573571</td>\n",
       "      <td>15.675714</td>\n",
       "      <td>8.495122</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>4.689286</td>\n",
       "      <td>9.822143</td>\n",
       "      <td>12.705000</td>\n",
       "      <td>13.509524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>417.269989</td>\n",
       "      <td>SPY_052022P415</td>\n",
       "      <td>SPY_052022P390</td>\n",
       "      <td>9.671429</td>\n",
       "      <td>7.765000</td>\n",
       "      <td>11.266905</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>9.415000</td>\n",
       "      <td>8.088571</td>\n",
       "      <td>9.904286</td>\n",
       "      <td>11.644762</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>18.274286</td>\n",
       "      <td>19.430714</td>\n",
       "      <td>25.720714</td>\n",
       "      <td>15.472439</td>\n",
       "      <td>3.747857</td>\n",
       "      <td>2.972857</td>\n",
       "      <td>4.401190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>3.102143</td>\n",
       "      <td>2.367143</td>\n",
       "      <td>3.053571</td>\n",
       "      <td>3.204524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.412143</td>\n",
       "      <td>5.354286</td>\n",
       "      <td>8.162143</td>\n",
       "      <td>2.845854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>20.320000</td>\n",
       "      <td>444.709991</td>\n",
       "      <td>SPY_051322P440</td>\n",
       "      <td>SPY_051322P415</td>\n",
       "      <td>5.892857</td>\n",
       "      <td>7.034286</td>\n",
       "      <td>16.913333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>21.599286</td>\n",
       "      <td>22.029286</td>\n",
       "      <td>18.343571</td>\n",
       "      <td>25.666429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>23.948571</td>\n",
       "      <td>22.081429</td>\n",
       "      <td>25.399286</td>\n",
       "      <td>29.867619</td>\n",
       "      <td>1.596429</td>\n",
       "      <td>2.013571</td>\n",
       "      <td>6.326429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>8.405000</td>\n",
       "      <td>8.255714</td>\n",
       "      <td>6.379286</td>\n",
       "      <td>9.604524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>7.676429</td>\n",
       "      <td>6.375714</td>\n",
       "      <td>7.965714</td>\n",
       "      <td>9.495952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>21.820000</td>\n",
       "      <td>443.309998</td>\n",
       "      <td>SPY_050622P440</td>\n",
       "      <td>SPY_050622P415</td>\n",
       "      <td>7.939286</td>\n",
       "      <td>7.896429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>6.210714</td>\n",
       "      <td>4.767143</td>\n",
       "      <td>5.832857</td>\n",
       "      <td>15.903095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>20.779286</td>\n",
       "      <td>21.305000</td>\n",
       "      <td>17.327857</td>\n",
       "      <td>25.090476</td>\n",
       "      <td>2.457143</td>\n",
       "      <td>2.212143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>1.385000</td>\n",
       "      <td>0.975000</td>\n",
       "      <td>1.263571</td>\n",
       "      <td>4.863571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>6.530000</td>\n",
       "      <td>6.329286</td>\n",
       "      <td>4.466429</td>\n",
       "      <td>7.291190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-04-06</td>\n",
       "      <td>2022-04-06</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>22.100000</td>\n",
       "      <td>446.519989</td>\n",
       "      <td>SPY_042922P445</td>\n",
       "      <td>SPY_042922P420</td>\n",
       "      <td>8.194167</td>\n",
       "      <td>7.410000</td>\n",
       "      <td>5.994286</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.038571</td>\n",
       "      <td>8.976154</td>\n",
       "      <td>8.387143</td>\n",
       "      <td>8.468571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.785714</td>\n",
       "      <td>6.425000</td>\n",
       "      <td>4.653571</td>\n",
       "      <td>5.903571</td>\n",
       "      <td>18.676905</td>\n",
       "      <td>2.684167</td>\n",
       "      <td>2.268571</td>\n",
       "      <td>1.625714</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.532143</td>\n",
       "      <td>2.388462</td>\n",
       "      <td>1.948571</td>\n",
       "      <td>1.650000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.641429</td>\n",
       "      <td>0.830000</td>\n",
       "      <td>0.511429</td>\n",
       "      <td>0.657143</td>\n",
       "      <td>3.762143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-03-30</td>\n",
       "      <td>2022-03-30</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>19.330000</td>\n",
       "      <td>458.700012</td>\n",
       "      <td>SPY_042222P455</td>\n",
       "      <td>SPY_042222P430</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.390000</td>\n",
       "      <td>8.388750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.950000</td>\n",
       "      <td>6.820833</td>\n",
       "      <td>11.641667</td>\n",
       "      <td>10.811429</td>\n",
       "      <td>8.887143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.824286</td>\n",
       "      <td>14.074615</td>\n",
       "      <td>13.795000</td>\n",
       "      <td>14.714286</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.760000</td>\n",
       "      <td>1.932500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.890000</td>\n",
       "      <td>1.363333</td>\n",
       "      <td>2.824167</td>\n",
       "      <td>2.355714</td>\n",
       "      <td>1.557857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.637857</td>\n",
       "      <td>2.400769</td>\n",
       "      <td>1.895000</td>\n",
       "      <td>1.502857</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2022-03-23</td>\n",
       "      <td>2022-03-23</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>23.570000</td>\n",
       "      <td>443.799988</td>\n",
       "      <td>SPY_041522P440</td>\n",
       "      <td>SPY_041522P415</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2022-03-16</td>\n",
       "      <td>2022-03-16</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>26.670000</td>\n",
       "      <td>434.270874</td>\n",
       "      <td>SPY_040822P430</td>\n",
       "      <td>SPY_040822P405</td>\n",
       "      <td>10.351429</td>\n",
       "      <td>7.409286</td>\n",
       "      <td>5.317143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.280714</td>\n",
       "      <td>2.815000</td>\n",
       "      <td>3.137143</td>\n",
       "      <td>2.504286</td>\n",
       "      <td>1.412381</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.112500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>0.242500</td>\n",
       "      <td>3.911429</td>\n",
       "      <td>2.615714</td>\n",
       "      <td>1.847143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.341429</td>\n",
       "      <td>0.878571</td>\n",
       "      <td>0.905714</td>\n",
       "      <td>0.695714</td>\n",
       "      <td>0.393810</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.281667</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0.078750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2022-03-09</td>\n",
       "      <td>2022-03-09</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>32.450001</td>\n",
       "      <td>426.086304</td>\n",
       "      <td>SPY_040122P425</td>\n",
       "      <td>SPY_040122P400</td>\n",
       "      <td>11.710714</td>\n",
       "      <td>13.120714</td>\n",
       "      <td>11.812143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.224286</td>\n",
       "      <td>11.829286</td>\n",
       "      <td>7.107143</td>\n",
       "      <td>4.610000</td>\n",
       "      <td>2.966429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.080714</td>\n",
       "      <td>1.180714</td>\n",
       "      <td>1.235714</td>\n",
       "      <td>0.848571</td>\n",
       "      <td>0.273333</td>\n",
       "      <td>4.767143</td>\n",
       "      <td>5.179286</td>\n",
       "      <td>4.252143</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.225000</td>\n",
       "      <td>4.042857</td>\n",
       "      <td>2.078571</td>\n",
       "      <td>1.257143</td>\n",
       "      <td>0.793571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.461429</td>\n",
       "      <td>0.310000</td>\n",
       "      <td>0.280714</td>\n",
       "      <td>0.211429</td>\n",
       "      <td>0.090000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         quoteTimeInLong_ts  open_date   DTE  days_to_close  take_prof  \\\n",
       "trade_no                                                                 \n",
       "2                2022-05-11 2022-05-11  18.0            7.0        0.5   \n",
       "3                2022-05-04 2022-05-04  18.0            7.0        0.5   \n",
       "4                2022-04-27 2022-04-27  18.0            7.0        0.5   \n",
       "5                2022-04-20 2022-04-20  18.0            7.0        0.5   \n",
       "6                2022-04-13 2022-04-13  18.0            7.0        0.5   \n",
       "7                2022-04-06 2022-04-06  18.0            7.0        0.5   \n",
       "8                2022-03-30 2022-03-30  18.0            7.0        0.5   \n",
       "9                2022-03-23 2022-03-23  18.0            7.0        0.5   \n",
       "10               2022-03-16 2022-03-16  18.0            7.0        0.5   \n",
       "11               2022-03-09 2022-03-09  18.0            7.0        0.5   \n",
       "\n",
       "          take_loss       ^VIX         SPY       spy_upper       spy_lower  \\\n",
       "trade_no                                                                     \n",
       "2               0.1  32.560001  392.750000  SPY_060322P390  SPY_060322P365   \n",
       "3               0.1  25.420000  429.059998  SPY_052722P425  SPY_052722P400   \n",
       "4               0.1  31.600000  417.269989  SPY_052022P415  SPY_052022P390   \n",
       "5               0.1  20.320000  444.709991  SPY_051322P440  SPY_051322P415   \n",
       "6               0.1  21.820000  443.309998  SPY_050622P440  SPY_050622P415   \n",
       "7               0.1  22.100000  446.519989  SPY_042922P445  SPY_042922P420   \n",
       "8               0.1  19.330000  458.700012  SPY_042222P455  SPY_042222P430   \n",
       "9               0.1  23.570000  443.799988  SPY_041522P440  SPY_041522P415   \n",
       "10              0.1  26.670000  434.270874  SPY_040822P430  SPY_040822P405   \n",
       "11              0.1  32.450001  426.086304  SPY_040122P425  SPY_040122P400   \n",
       "\n",
       "          spy_upp+0  spy_upp+1  spy_upp+2  spy_upp+3  spy_upp+4  spy_upp+5  \\\n",
       "trade_no                                                                     \n",
       "2          8.787143  11.882143   6.408293        NaN        NaN   5.657857   \n",
       "3         13.824286  16.206429  18.944524        NaN        NaN  25.995385   \n",
       "4          9.671429   7.765000  11.266905        NaN        NaN  13.258571   \n",
       "5          5.892857   7.034286  16.913333        NaN        NaN  19.348571   \n",
       "6          7.939286   7.896429        NaN        NaN        NaN   8.862143   \n",
       "7          8.194167   7.410000   5.994286        NaN        NaN   9.038571   \n",
       "8               NaN   6.390000   8.388750        NaN        NaN   4.950000   \n",
       "9               NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "10        10.351429   7.409286   5.317143        NaN        NaN   4.280714   \n",
       "11        11.710714  13.120714  11.812143        NaN        NaN  14.224286   \n",
       "\n",
       "          spy_upp+6  spy_upp+7  spy_upp+8  spy_upp+9  spy_upp+10  spy_upp+11  \\\n",
       "trade_no                                                                       \n",
       "2          3.523571   7.051429   8.888571   9.086190         NaN         NaN   \n",
       "3         27.169286  28.667857  35.492857  25.042439         NaN         NaN   \n",
       "4          9.415000   8.088571   9.904286  11.644762         NaN         NaN   \n",
       "5         21.599286  22.029286  18.343571  25.666429         NaN         NaN   \n",
       "6          6.210714   4.767143   5.832857  15.903095         NaN         NaN   \n",
       "7          8.976154   8.387143   8.468571        NaN         NaN         NaN   \n",
       "8          6.820833  11.641667  10.811429   8.887143         NaN         NaN   \n",
       "9               NaN        NaN        NaN        NaN         NaN         NaN   \n",
       "10         2.815000   3.137143   2.504286   1.412381         NaN         NaN   \n",
       "11        11.829286   7.107143   4.610000   2.966429         NaN         NaN   \n",
       "\n",
       "          spy_upp+12  spy_upp+13  spy_upp+14  spy_upp+15  spy_upp+16  \\\n",
       "trade_no                                                               \n",
       "2           5.404286    7.227857    4.637857    1.684286    0.341707   \n",
       "3          24.811429   19.578571   29.685714   34.800000   36.642381   \n",
       "4          17.395385   18.274286   19.430714   25.720714   15.472439   \n",
       "5          29.715714   23.948571   22.081429   25.399286   29.867619   \n",
       "6          18.450000   20.779286   21.305000   17.327857   25.090476   \n",
       "7           9.785714    6.425000    4.653571    5.903571   18.676905   \n",
       "8          13.824286   14.074615   13.795000   14.714286         NaN   \n",
       "9                NaN         NaN         NaN         NaN         NaN   \n",
       "10          1.112500         NaN         NaN    0.340000    0.242500   \n",
       "11          2.080714    1.180714    1.235714    0.848571    0.273333   \n",
       "\n",
       "          spy_lower+0  spy_lower+1  spy_lower+2  spy_lower+3  spy_lower+4  \\\n",
       "trade_no                                                                    \n",
       "2            2.900000     4.145714     1.800244          NaN          NaN   \n",
       "3            5.157143     6.400714     7.304048          NaN          NaN   \n",
       "4            3.747857     2.972857     4.401190          NaN          NaN   \n",
       "5            1.596429     2.013571     6.326429          NaN          NaN   \n",
       "6            2.457143     2.212143          NaN          NaN          NaN   \n",
       "7            2.684167     2.268571     1.625714          NaN          NaN   \n",
       "8                 NaN     1.760000     1.932500          NaN          NaN   \n",
       "9                 NaN          NaN          NaN          NaN          NaN   \n",
       "10           3.911429     2.615714     1.847143          NaN          NaN   \n",
       "11           4.767143     5.179286     4.252143          NaN          NaN   \n",
       "\n",
       "          spy_lower+5  spy_lower+6  spy_lower+7  spy_lower+8  spy_lower+9  \\\n",
       "trade_no                                                                    \n",
       "2            1.363571     0.756429     1.737857     2.275714     2.027381   \n",
       "3           10.873846    11.200714    11.573571    15.675714     8.495122   \n",
       "4            5.160000     3.102143     2.367143     3.053571     3.204524   \n",
       "5            7.385000     8.405000     8.255714     6.379286     9.604524   \n",
       "6            2.303571     1.385000     0.975000     1.263571     4.863571   \n",
       "7            2.532143     2.388462     1.948571     1.650000          NaN   \n",
       "8            0.890000     1.363333     2.824167     2.355714     1.557857   \n",
       "9                 NaN          NaN          NaN          NaN          NaN   \n",
       "10           1.341429     0.878571     0.905714     0.695714     0.393810   \n",
       "11           5.225000     4.042857     2.078571     1.257143     0.793571   \n",
       "\n",
       "          spy_lower+10  spy_lower+11  spy_lower+12  spy_lower+13  \\\n",
       "trade_no                                                           \n",
       "2                  NaN           NaN      0.940000      1.250000   \n",
       "3                  NaN           NaN      7.717857      4.689286   \n",
       "4                  NaN           NaN      5.391538      5.412143   \n",
       "5                  NaN           NaN     11.557857      7.676429   \n",
       "6                  NaN           NaN      5.750714      6.530000   \n",
       "7                  NaN           NaN      1.641429      0.830000   \n",
       "8                  NaN           NaN      2.637857      2.400769   \n",
       "9                  NaN           NaN           NaN           NaN   \n",
       "10                 NaN           NaN      0.281667           NaN   \n",
       "11                 NaN           NaN      0.461429      0.310000   \n",
       "\n",
       "          spy_lower+14  spy_lower+15  spy_lower+16  \n",
       "trade_no                                            \n",
       "2             0.630714      0.229286      0.090244  \n",
       "3             9.822143     12.705000     13.509524  \n",
       "4             5.354286      8.162143      2.845854  \n",
       "5             6.375714      7.965714      9.495952  \n",
       "6             6.329286      4.466429      7.291190  \n",
       "7             0.511429      0.657143      3.762143  \n",
       "8             1.895000      1.502857           NaN  \n",
       "9                  NaN           NaN           NaN  \n",
       "10                 NaN      0.125000      0.078750  \n",
       "11            0.280714      0.211429      0.090000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#drop out 1st 2 rows due to incomplete data\n",
    "out.set_index('trade_no', inplace=True)\n",
    "out.drop([0, 1], inplace=True)\n",
    "\n",
    "display(out.head(10))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "7d6c77ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>quoteTimeInLong_ts</th>\n",
       "      <th>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>^VIX</th>\n",
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       "      <th>spy_upper</th>\n",
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       "      <th>spy_upp+4</th>\n",
       "      <th>spy_upp+5</th>\n",
       "      <th>spy_upp+6</th>\n",
       "      <th>spy_upp+7</th>\n",
       "      <th>spy_upp+8</th>\n",
       "      <th>spy_upp+9</th>\n",
       "      <th>spy_upp+10</th>\n",
       "      <th>spy_upp+11</th>\n",
       "      <th>spy_upp+12</th>\n",
       "      <th>spy_upp+13</th>\n",
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       "      <th>spy_upp+15</th>\n",
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       "      <th>spy_lower+2</th>\n",
       "      <th>spy_lower+3</th>\n",
       "      <th>spy_lower+4</th>\n",
       "      <th>spy_lower+5</th>\n",
       "      <th>spy_lower+6</th>\n",
       "      <th>spy_lower+7</th>\n",
       "      <th>spy_lower+8</th>\n",
       "      <th>spy_lower+9</th>\n",
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       "      <th>spy_lower+13</th>\n",
       "      <th>spy_lower+14</th>\n",
       "      <th>spy_lower+15</th>\n",
       "      <th>spy_lower+16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_no</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",
       "      <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",
       "      <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",
       "      <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",
       "      <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>2</th>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>32.560001</td>\n",
       "      <td>392.750000</td>\n",
       "      <td>SPY_060322P390</td>\n",
       "      <td>SPY_060322P365</td>\n",
       "      <td>8.787143</td>\n",
       "      <td>11.882143</td>\n",
       "      <td>6.408293</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>3.523571</td>\n",
       "      <td>7.051429</td>\n",
       "      <td>8.888571</td>\n",
       "      <td>9.086190</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>7.227857</td>\n",
       "      <td>4.637857</td>\n",
       "      <td>1.684286</td>\n",
       "      <td>0.341707</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>4.145714</td>\n",
       "      <td>1.800244</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>0.756429</td>\n",
       "      <td>1.737857</td>\n",
       "      <td>2.275714</td>\n",
       "      <td>2.027381</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.630714</td>\n",
       "      <td>0.229286</td>\n",
       "      <td>0.090244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>25.420000</td>\n",
       "      <td>429.059998</td>\n",
       "      <td>SPY_052722P425</td>\n",
       "      <td>SPY_052722P400</td>\n",
       "      <td>13.824286</td>\n",
       "      <td>16.206429</td>\n",
       "      <td>18.944524</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>27.169286</td>\n",
       "      <td>28.667857</td>\n",
       "      <td>35.492857</td>\n",
       "      <td>25.042439</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>19.578571</td>\n",
       "      <td>29.685714</td>\n",
       "      <td>34.800000</td>\n",
       "      <td>36.642381</td>\n",
       "      <td>5.157143</td>\n",
       "      <td>6.400714</td>\n",
       "      <td>7.304048</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>11.200714</td>\n",
       "      <td>11.573571</td>\n",
       "      <td>15.675714</td>\n",
       "      <td>8.495122</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>4.689286</td>\n",
       "      <td>9.822143</td>\n",
       "      <td>12.705000</td>\n",
       "      <td>13.509524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>417.269989</td>\n",
       "      <td>SPY_052022P415</td>\n",
       "      <td>SPY_052022P390</td>\n",
       "      <td>9.671429</td>\n",
       "      <td>7.765000</td>\n",
       "      <td>11.266905</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>9.415000</td>\n",
       "      <td>8.088571</td>\n",
       "      <td>9.904286</td>\n",
       "      <td>11.644762</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>18.274286</td>\n",
       "      <td>19.430714</td>\n",
       "      <td>25.720714</td>\n",
       "      <td>15.472439</td>\n",
       "      <td>3.747857</td>\n",
       "      <td>2.972857</td>\n",
       "      <td>4.401190</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>3.102143</td>\n",
       "      <td>2.367143</td>\n",
       "      <td>3.053571</td>\n",
       "      <td>3.204524</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.412143</td>\n",
       "      <td>5.354286</td>\n",
       "      <td>8.162143</td>\n",
       "      <td>2.845854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>20.320000</td>\n",
       "      <td>444.709991</td>\n",
       "      <td>SPY_051322P440</td>\n",
       "      <td>SPY_051322P415</td>\n",
       "      <td>5.892857</td>\n",
       "      <td>7.034286</td>\n",
       "      <td>16.913333</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>21.599286</td>\n",
       "      <td>22.029286</td>\n",
       "      <td>18.343571</td>\n",
       "      <td>25.666429</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>23.948571</td>\n",
       "      <td>22.081429</td>\n",
       "      <td>25.399286</td>\n",
       "      <td>29.867619</td>\n",
       "      <td>1.596429</td>\n",
       "      <td>2.013571</td>\n",
       "      <td>6.326429</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>8.405000</td>\n",
       "      <td>8.255714</td>\n",
       "      <td>6.379286</td>\n",
       "      <td>9.604524</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>7.676429</td>\n",
       "      <td>6.375714</td>\n",
       "      <td>7.965714</td>\n",
       "      <td>9.495952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>21.820000</td>\n",
       "      <td>443.309998</td>\n",
       "      <td>SPY_050622P440</td>\n",
       "      <td>SPY_050622P415</td>\n",
       "      <td>7.939286</td>\n",
       "      <td>7.896429</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>6.210714</td>\n",
       "      <td>4.767143</td>\n",
       "      <td>5.832857</td>\n",
       "      <td>15.903095</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>20.779286</td>\n",
       "      <td>21.305000</td>\n",
       "      <td>17.327857</td>\n",
       "      <td>25.090476</td>\n",
       "      <td>2.457143</td>\n",
       "      <td>2.212143</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>1.385000</td>\n",
       "      <td>0.975000</td>\n",
       "      <td>1.263571</td>\n",
       "      <td>4.863571</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>6.530000</td>\n",
       "      <td>6.329286</td>\n",
       "      <td>4.466429</td>\n",
       "      <td>7.291190</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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.090000</td>\n",
       "      <td>455.933594</td>\n",
       "      <td>SPY_031122P455</td>\n",
       "      <td>SPY_031122P430</td>\n",
       "      <td>9.790000</td>\n",
       "      <td>15.820000</td>\n",
       "      <td>16.580000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>10.750000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>12.420000</td>\n",
       "      <td>18.720000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>13.258000</td>\n",
       "      <td>17.053750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.790000</td>\n",
       "      <td>6.080000</td>\n",
       "      <td>5.050000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>4.110000</td>\n",
       "      <td>2.850000</td>\n",
       "      <td>5.090000</td>\n",
       "      <td>8.070000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>5.190000</td>\n",
       "      <td>4.667000</td>\n",
       "      <td>6.407500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.959999</td>\n",
       "      <td>432.037842</td>\n",
       "      <td>SPY_030422P430</td>\n",
       "      <td>SPY_030422P405</td>\n",
       "      <td>12.560000</td>\n",
       "      <td>13.650000</td>\n",
       "      <td>8.540000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>3.880000</td>\n",
       "      <td>2.880000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.800000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>3.150000</td>\n",
       "      <td>1.940000</td>\n",
       "      <td>3.960000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>6.450000</td>\n",
       "      <td>6.280000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>1.620000</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>2.580000</td>\n",
       "      <td>1.760000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.040000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>1.340000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.850000</td>\n",
       "      <td>450.350922</td>\n",
       "      <td>SPY_022522P450</td>\n",
       "      <td>SPY_022522P425</td>\n",
       "      <td>10.980000</td>\n",
       "      <td>13.420000</td>\n",
       "      <td>17.830000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>19.950000</td>\n",
       "      <td>22.300000</td>\n",
       "      <td>23.510000</td>\n",
       "      <td>16.300000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>6.940000</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>9.110000</td>\n",
       "      <td>8.840000</td>\n",
       "      <td>4.610000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.410000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>10.550000</td>\n",
       "      <td>10.270000</td>\n",
       "      <td>10.520000</td>\n",
       "      <td>6.650000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>2.340000</td>\n",
       "      <td>1.860000</td>\n",
       "      <td>3.780000</td>\n",
       "      <td>2.910000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.620001</td>\n",
       "      <td>469.561249</td>\n",
       "      <td>SPY_021822P465</td>\n",
       "      <td>SPY_021822P440</td>\n",
       "      <td>6.650000</td>\n",
       "      <td>10.160000</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>17.140000</td>\n",
       "      <td>20.510000</td>\n",
       "      <td>28.340000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>32.070000</td>\n",
       "      <td>32.420000</td>\n",
       "      <td>32.520000</td>\n",
       "      <td>24.410000</td>\n",
       "      <td>2.580000</td>\n",
       "      <td>4.150000</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>6.710000</td>\n",
       "      <td>8.950000</td>\n",
       "      <td>12.850000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>15.290000</td>\n",
       "      <td>14.980000</td>\n",
       "      <td>15.090000</td>\n",
       "      <td>9.930000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.730000</td>\n",
       "      <td>466.929443</td>\n",
       "      <td>SPY_021122P465</td>\n",
       "      <td>SPY_021122P440</td>\n",
       "      <td>8.240000</td>\n",
       "      <td>7.650000</td>\n",
       "      <td>8.560000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>6.580000</td>\n",
       "      <td>5.680000</td>\n",
       "      <td>9.160000</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>16.250000</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>25.340000</td>\n",
       "      <td>3.240000</td>\n",
       "      <td>3.450000</td>\n",
       "      <td>3.130000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>2.380000</td>\n",
       "      <td>2.280000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>2.730000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>5.740000</td>\n",
       "      <td>7.690000</td>\n",
       "      <td>11.830000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136800 rows × 44 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         quoteTimeInLong_ts  open_date   DTE  days_to_close  take_prof  \\\n",
       "trade_no                                                                 \n",
       "2                2022-05-11 2022-05-11  18.0            7.0        0.5   \n",
       "3                2022-05-04 2022-05-04  18.0            7.0        0.5   \n",
       "4                2022-04-27 2022-04-27  18.0            7.0        0.5   \n",
       "5                2022-04-20 2022-04-20  18.0            7.0        0.5   \n",
       "6                2022-04-13 2022-04-13  18.0            7.0        0.5   \n",
       "...                     ...        ...   ...            ...        ...   \n",
       "16               2022-02-02 2022-02-02  32.0           16.0        1.0   \n",
       "17               2022-01-26 2022-01-26  32.0           16.0        1.0   \n",
       "18               2022-01-19 2022-01-19  32.0           16.0        1.0   \n",
       "19               2022-01-12 2022-01-12  32.0           16.0        1.0   \n",
       "20               2022-01-05 2022-01-05  32.0           16.0        1.0   \n",
       "\n",
       "          take_loss       ^VIX         SPY       spy_upper       spy_lower  \\\n",
       "trade_no                                                                     \n",
       "2               0.1  32.560001  392.750000  SPY_060322P390  SPY_060322P365   \n",
       "3               0.1  25.420000  429.059998  SPY_052722P425  SPY_052722P400   \n",
       "4               0.1  31.600000  417.269989  SPY_052022P415  SPY_052022P390   \n",
       "5               0.1  20.320000  444.709991  SPY_051322P440  SPY_051322P415   \n",
       "6               0.1  21.820000  443.309998  SPY_050622P440  SPY_050622P415   \n",
       "...             ...        ...         ...             ...             ...   \n",
       "16              1.0  22.090000  455.933594  SPY_031122P455  SPY_031122P430   \n",
       "17              1.0  31.959999  432.037842  SPY_030422P430  SPY_030422P405   \n",
       "18              1.0  23.850000  450.350922  SPY_022522P450  SPY_022522P425   \n",
       "19              1.0  17.620001  469.561249  SPY_021822P465  SPY_021822P440   \n",
       "20              1.0  19.730000  466.929443  SPY_021122P465  SPY_021122P440   \n",
       "\n",
       "          spy_upp+0  spy_upp+1  spy_upp+2  spy_upp+3  spy_upp+4  spy_upp+5  \\\n",
       "trade_no                                                                     \n",
       "2          8.787143  11.882143   6.408293   5.657857   5.657857   5.657857   \n",
       "3         13.824286  16.206429  18.944524  25.995385  25.995385  25.995385   \n",
       "4          9.671429   7.765000  11.266905  13.258571  13.258571  13.258571   \n",
       "5          5.892857   7.034286  16.913333  19.348571  19.348571  19.348571   \n",
       "6          7.939286   7.896429   8.862143   8.862143   8.862143   8.862143   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "16         9.790000  15.820000  16.580000  13.180000  13.180000  13.180000   \n",
       "17        12.560000  13.650000   8.540000   5.420000   5.420000   5.420000   \n",
       "18        10.980000  13.420000  17.830000  17.440000  17.440000  17.440000   \n",
       "19         6.650000  10.160000   9.200000  14.360000  14.360000  14.360000   \n",
       "20         8.240000   7.650000   8.560000   8.390000   8.390000   8.390000   \n",
       "\n",
       "          spy_upp+6  spy_upp+7  spy_upp+8  spy_upp+9  spy_upp+10  spy_upp+11  \\\n",
       "trade_no                                                                       \n",
       "2          3.523571   7.051429   8.888571   9.086190    5.404286    5.404286   \n",
       "3         27.169286  28.667857  35.492857  25.042439   24.811429   24.811429   \n",
       "4          9.415000   8.088571   9.904286  11.644762   17.395385   17.395385   \n",
       "5         21.599286  22.029286  18.343571  25.666429   29.715714   29.715714   \n",
       "6          6.210714   4.767143   5.832857  15.903095   18.450000   18.450000   \n",
       "...             ...        ...        ...        ...         ...         ...   \n",
       "16        10.750000   7.750000  12.420000  18.720000   19.560000   19.560000   \n",
       "17         3.880000   2.880000   5.000000   4.800000    4.340000    4.340000   \n",
       "18        19.950000  22.300000  23.510000  16.300000    9.990000    9.990000   \n",
       "19        14.360000  17.140000  20.510000  28.340000   26.960000   26.960000   \n",
       "20         6.580000   5.680000   9.160000   8.200000   13.690000   13.690000   \n",
       "\n",
       "          spy_upp+12  spy_upp+13  spy_upp+14  spy_upp+15  spy_upp+16  \\\n",
       "trade_no                                                               \n",
       "2           5.404286    7.227857    4.637857    1.684286    0.341707   \n",
       "3          24.811429   19.578571   29.685714   34.800000   36.642381   \n",
       "4          17.395385   18.274286   19.430714   25.720714   15.472439   \n",
       "5          29.715714   23.948571   22.081429   25.399286   29.867619   \n",
       "6          18.450000   20.779286   21.305000   17.327857   25.090476   \n",
       "...              ...         ...         ...         ...         ...   \n",
       "16         19.560000   14.360000   13.258000   17.053750         NaN   \n",
       "17          4.340000    3.150000    1.940000    3.960000    6.500000   \n",
       "18          9.990000    6.940000    6.880000    9.110000    8.840000   \n",
       "19         26.960000   32.070000   32.420000   32.520000   24.410000   \n",
       "20         13.690000   13.690000   16.250000   20.500000   25.340000   \n",
       "\n",
       "          spy_lower+0  spy_lower+1  spy_lower+2  spy_lower+3  spy_lower+4  \\\n",
       "trade_no                                                                    \n",
       "2            2.900000     4.145714     1.800244     1.363571     1.363571   \n",
       "3            5.157143     6.400714     7.304048    10.873846    10.873846   \n",
       "4            3.747857     2.972857     4.401190     5.160000     5.160000   \n",
       "5            1.596429     2.013571     6.326429     7.385000     7.385000   \n",
       "6            2.457143     2.212143     2.303571     2.303571     2.303571   \n",
       "...               ...          ...          ...          ...          ...   \n",
       "16           3.790000     6.080000     5.050000     5.890000     5.890000   \n",
       "17           6.450000     6.280000     4.250000     2.520000     2.520000   \n",
       "18           4.610000     6.000000     8.410000     8.180000     8.180000   \n",
       "19           2.580000     4.150000     3.500000     5.660000     5.660000   \n",
       "20           3.240000     3.450000     3.130000     3.060000     3.060000   \n",
       "\n",
       "          spy_lower+5  spy_lower+6  spy_lower+7  spy_lower+8  spy_lower+9  \\\n",
       "trade_no                                                                    \n",
       "2            1.363571     0.756429     1.737857     2.275714     2.027381   \n",
       "3           10.873846    11.200714    11.573571    15.675714     8.495122   \n",
       "4            5.160000     3.102143     2.367143     3.053571     3.204524   \n",
       "5            7.385000     8.405000     8.255714     6.379286     9.604524   \n",
       "6            2.303571     1.385000     0.975000     1.263571     4.863571   \n",
       "...               ...          ...          ...          ...          ...   \n",
       "16           5.890000     4.110000     2.850000     5.090000     8.070000   \n",
       "17           2.520000     1.620000     1.300000     2.580000     1.760000   \n",
       "18           8.180000    10.550000    10.270000    10.520000     6.650000   \n",
       "19           5.660000     5.660000     6.710000     8.950000    12.850000   \n",
       "20           3.060000     2.380000     2.280000     3.300000     2.730000   \n",
       "\n",
       "          spy_lower+10  spy_lower+11  spy_lower+12  spy_lower+13  \\\n",
       "trade_no                                                           \n",
       "2             0.940000      0.940000      0.940000      1.250000   \n",
       "3             7.717857      7.717857      7.717857      4.689286   \n",
       "4             5.391538      5.391538      5.391538      5.412143   \n",
       "5            11.557857     11.557857     11.557857      7.676429   \n",
       "6             5.750714      5.750714      5.750714      6.530000   \n",
       "...                ...           ...           ...           ...   \n",
       "16            8.140000      8.140000      8.140000      5.190000   \n",
       "17            1.610000      1.610000      1.610000      1.040000   \n",
       "18            3.620000      3.620000      3.620000      2.340000   \n",
       "19           12.030000     12.030000     12.030000     15.290000   \n",
       "20            4.920000      4.920000      4.920000      4.920000   \n",
       "\n",
       "          spy_lower+14  spy_lower+15  spy_lower+16  \n",
       "trade_no                                            \n",
       "2             0.630714      0.229286      0.090244  \n",
       "3             9.822143     12.705000     13.509524  \n",
       "4             5.354286      8.162143      2.845854  \n",
       "5             6.375714      7.965714      9.495952  \n",
       "6             6.329286      4.466429      7.291190  \n",
       "...                ...           ...           ...  \n",
       "16            4.667000      6.407500           NaN  \n",
       "17            0.660000      1.340000      2.500000  \n",
       "18            1.860000      3.780000      2.910000  \n",
       "19           14.980000     15.090000      9.930000  \n",
       "20            5.740000      7.690000     11.830000  \n",
       "\n",
       "[136800 rows x 44 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# fill missing values with interpolate()\n",
    "\n",
    "out_low = out.filter(like= 'spy_lower+', axis=1).copy()            #filter out spy_lower columns and fill na\n",
    "out_low.interpolate(method='bfill', inplace=True, axis=1)\n",
    "\n",
    "out_upp = out.filter(like= 'spy_upp+', axis=1).copy()             #filter out spy_upp columns and fill na\n",
    "out_upp.interpolate(method='bfill', inplace=True, axis=1)\n",
    "\n",
    "for days in range(0,17):                                                 #copy back the columns into main out df\n",
    "    out['spy_upp+' + str(days)] = out_upp['spy_upp+' + str(days)]\n",
    "    out['spy_lower+' + str(days)] = out_low['spy_lower+' + str(days)]\n",
    "display(out)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0dd3cd7",
   "metadata": {},
   "source": [
    "### 2g. Calculating P/L for trades with normal expiry (i.e. expire by days_to_close)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "fdd759cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate p/l for the rest of the trades which are not triggered by take_prof or take_loss\n",
    "out['credit_0'] = out['spy_upp+0'] - out['spy_lower+0'] \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "4478049b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for days in days_to_close:\n",
    "#     print(days)\n",
    "    out['norm_pl+'+str(days)] = np.where(out['days_to_close']==days, \n",
    "                         out['credit_0'] - (out['spy_upp+'+str(days)] - out['spy_lower+'+str(days)]),                    \n",
    "                         false_func())\n",
    "\n",
    "for i in range(len(days_to_close)-1):                                               # merging the data from different days into a single column, at last element of days_to_close\n",
    "      out['norm_pl+'+str(days_to_close[i+1])] = out['norm_pl+'+str(days_to_close[i])].combine_first(out['norm_pl+'+str(days_to_close[i+1])])\n",
    "      \n",
    "out['norm_pl'] = out['norm_pl+'+str(days_to_close[-1])]\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "194b159b",
   "metadata": {},
   "source": [
    "### 2h. Determining trades which need early exit (i.e. create takeprof_day and takeloss_day)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "aad0bc74",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>quoteTimeInLong_ts</th>\n",
       "      <th>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>^VIX</th>\n",
       "      <th>SPY</th>\n",
       "      <th>spy_upper</th>\n",
       "      <th>spy_lower</th>\n",
       "      <th>spy_upp+0</th>\n",
       "      <th>spy_upp+1</th>\n",
       "      <th>spy_upp+2</th>\n",
       "      <th>spy_upp+3</th>\n",
       "      <th>spy_upp+4</th>\n",
       "      <th>spy_upp+5</th>\n",
       "      <th>spy_upp+6</th>\n",
       "      <th>spy_upp+7</th>\n",
       "      <th>spy_upp+8</th>\n",
       "      <th>spy_upp+9</th>\n",
       "      <th>spy_upp+10</th>\n",
       "      <th>spy_upp+11</th>\n",
       "      <th>spy_upp+12</th>\n",
       "      <th>spy_upp+13</th>\n",
       "      <th>spy_upp+14</th>\n",
       "      <th>spy_upp+15</th>\n",
       "      <th>spy_upp+16</th>\n",
       "      <th>spy_lower+0</th>\n",
       "      <th>spy_lower+1</th>\n",
       "      <th>spy_lower+2</th>\n",
       "      <th>spy_lower+3</th>\n",
       "      <th>spy_lower+4</th>\n",
       "      <th>spy_lower+5</th>\n",
       "      <th>spy_lower+6</th>\n",
       "      <th>spy_lower+7</th>\n",
       "      <th>spy_lower+8</th>\n",
       "      <th>spy_lower+9</th>\n",
       "      <th>spy_lower+10</th>\n",
       "      <th>spy_lower+11</th>\n",
       "      <th>spy_lower+12</th>\n",
       "      <th>spy_lower+13</th>\n",
       "      <th>spy_lower+14</th>\n",
       "      <th>spy_lower+15</th>\n",
       "      <th>spy_lower+16</th>\n",
       "      <th>credit_0</th>\n",
       "      <th>norm_pl+7</th>\n",
       "      <th>norm_pl+8</th>\n",
       "      <th>norm_pl+9</th>\n",
       "      <th>norm_pl+12</th>\n",
       "      <th>norm_pl+13</th>\n",
       "      <th>norm_pl+14</th>\n",
       "      <th>norm_pl+15</th>\n",
       "      <th>norm_pl+16</th>\n",
       "      <th>norm_pl</th>\n",
       "      <th>takeprof_day+0</th>\n",
       "      <th>takeloss_day+0</th>\n",
       "      <th>takeprof_day+1</th>\n",
       "      <th>takeloss_day+1</th>\n",
       "      <th>takeprof_day+2</th>\n",
       "      <th>takeloss_day+2</th>\n",
       "      <th>takeprof_day+3</th>\n",
       "      <th>takeloss_day+3</th>\n",
       "      <th>takeprof_day+4</th>\n",
       "      <th>takeloss_day+4</th>\n",
       "      <th>takeprof_day+5</th>\n",
       "      <th>takeloss_day+5</th>\n",
       "      <th>takeprof_day+6</th>\n",
       "      <th>takeloss_day+6</th>\n",
       "      <th>takeprof_day+7</th>\n",
       "      <th>takeloss_day+7</th>\n",
       "      <th>takeprof_day+8</th>\n",
       "      <th>takeloss_day+8</th>\n",
       "      <th>takeprof_day+9</th>\n",
       "      <th>takeloss_day+9</th>\n",
       "      <th>takeprof_day+10</th>\n",
       "      <th>takeloss_day+10</th>\n",
       "      <th>takeprof_day+11</th>\n",
       "      <th>takeloss_day+11</th>\n",
       "      <th>takeprof_day+12</th>\n",
       "      <th>takeloss_day+12</th>\n",
       "      <th>takeprof_day+13</th>\n",
       "      <th>takeloss_day+13</th>\n",
       "      <th>takeprof_day+14</th>\n",
       "      <th>takeloss_day+14</th>\n",
       "      <th>takeprof_day+15</th>\n",
       "      <th>takeloss_day+15</th>\n",
       "      <th>takeprof_day+16</th>\n",
       "      <th>takeloss_day+16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_no</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",
       "      <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",
       "      <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",
       "      <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",
       "      <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",
       "      <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",
       "      <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",
       "      <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",
       "      <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",
       "      <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>2</th>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>2022-05-11</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>32.560001</td>\n",
       "      <td>392.750000</td>\n",
       "      <td>SPY_060322P390</td>\n",
       "      <td>SPY_060322P365</td>\n",
       "      <td>8.787143</td>\n",
       "      <td>11.882143</td>\n",
       "      <td>6.408293</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>5.657857</td>\n",
       "      <td>3.523571</td>\n",
       "      <td>7.051429</td>\n",
       "      <td>8.888571</td>\n",
       "      <td>9.086190</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>5.404286</td>\n",
       "      <td>7.227857</td>\n",
       "      <td>4.637857</td>\n",
       "      <td>1.684286</td>\n",
       "      <td>0.341707</td>\n",
       "      <td>2.900000</td>\n",
       "      <td>4.145714</td>\n",
       "      <td>1.800244</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>1.363571</td>\n",
       "      <td>0.756429</td>\n",
       "      <td>1.737857</td>\n",
       "      <td>2.275714</td>\n",
       "      <td>2.027381</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>0.940000</td>\n",
       "      <td>1.250000</td>\n",
       "      <td>0.630714</td>\n",
       "      <td>0.229286</td>\n",
       "      <td>0.090244</td>\n",
       "      <td>5.887143</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>0.573571</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>2022-05-04</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>25.420000</td>\n",
       "      <td>429.059998</td>\n",
       "      <td>SPY_052722P425</td>\n",
       "      <td>SPY_052722P400</td>\n",
       "      <td>13.824286</td>\n",
       "      <td>16.206429</td>\n",
       "      <td>18.944524</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>25.995385</td>\n",
       "      <td>27.169286</td>\n",
       "      <td>28.667857</td>\n",
       "      <td>35.492857</td>\n",
       "      <td>25.042439</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>24.811429</td>\n",
       "      <td>19.578571</td>\n",
       "      <td>29.685714</td>\n",
       "      <td>34.800000</td>\n",
       "      <td>36.642381</td>\n",
       "      <td>5.157143</td>\n",
       "      <td>6.400714</td>\n",
       "      <td>7.304048</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>10.873846</td>\n",
       "      <td>11.200714</td>\n",
       "      <td>11.573571</td>\n",
       "      <td>15.675714</td>\n",
       "      <td>8.495122</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>7.717857</td>\n",
       "      <td>4.689286</td>\n",
       "      <td>9.822143</td>\n",
       "      <td>12.705000</td>\n",
       "      <td>13.509524</td>\n",
       "      <td>8.667143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>-8.427143</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>2022-04-27</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>31.600000</td>\n",
       "      <td>417.269989</td>\n",
       "      <td>SPY_052022P415</td>\n",
       "      <td>SPY_052022P390</td>\n",
       "      <td>9.671429</td>\n",
       "      <td>7.765000</td>\n",
       "      <td>11.266905</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>13.258571</td>\n",
       "      <td>9.415000</td>\n",
       "      <td>8.088571</td>\n",
       "      <td>9.904286</td>\n",
       "      <td>11.644762</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>17.395385</td>\n",
       "      <td>18.274286</td>\n",
       "      <td>19.430714</td>\n",
       "      <td>25.720714</td>\n",
       "      <td>15.472439</td>\n",
       "      <td>3.747857</td>\n",
       "      <td>2.972857</td>\n",
       "      <td>4.401190</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>5.160000</td>\n",
       "      <td>3.102143</td>\n",
       "      <td>2.367143</td>\n",
       "      <td>3.053571</td>\n",
       "      <td>3.204524</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.391538</td>\n",
       "      <td>5.412143</td>\n",
       "      <td>5.354286</td>\n",
       "      <td>8.162143</td>\n",
       "      <td>2.845854</td>\n",
       "      <td>5.923571</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>0.202143</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>2022-04-20</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>20.320000</td>\n",
       "      <td>444.709991</td>\n",
       "      <td>SPY_051322P440</td>\n",
       "      <td>SPY_051322P415</td>\n",
       "      <td>5.892857</td>\n",
       "      <td>7.034286</td>\n",
       "      <td>16.913333</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>19.348571</td>\n",
       "      <td>21.599286</td>\n",
       "      <td>22.029286</td>\n",
       "      <td>18.343571</td>\n",
       "      <td>25.666429</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>29.715714</td>\n",
       "      <td>23.948571</td>\n",
       "      <td>22.081429</td>\n",
       "      <td>25.399286</td>\n",
       "      <td>29.867619</td>\n",
       "      <td>1.596429</td>\n",
       "      <td>2.013571</td>\n",
       "      <td>6.326429</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>7.385000</td>\n",
       "      <td>8.405000</td>\n",
       "      <td>8.255714</td>\n",
       "      <td>6.379286</td>\n",
       "      <td>9.604524</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>11.557857</td>\n",
       "      <td>7.676429</td>\n",
       "      <td>6.375714</td>\n",
       "      <td>7.965714</td>\n",
       "      <td>9.495952</td>\n",
       "      <td>4.296429</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>-9.477143</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>21.820000</td>\n",
       "      <td>443.309998</td>\n",
       "      <td>SPY_050622P440</td>\n",
       "      <td>SPY_050622P415</td>\n",
       "      <td>7.939286</td>\n",
       "      <td>7.896429</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>8.862143</td>\n",
       "      <td>6.210714</td>\n",
       "      <td>4.767143</td>\n",
       "      <td>5.832857</td>\n",
       "      <td>15.903095</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>18.450000</td>\n",
       "      <td>20.779286</td>\n",
       "      <td>21.305000</td>\n",
       "      <td>17.327857</td>\n",
       "      <td>25.090476</td>\n",
       "      <td>2.457143</td>\n",
       "      <td>2.212143</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>2.303571</td>\n",
       "      <td>1.385000</td>\n",
       "      <td>0.975000</td>\n",
       "      <td>1.263571</td>\n",
       "      <td>4.863571</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>5.750714</td>\n",
       "      <td>6.530000</td>\n",
       "      <td>6.329286</td>\n",
       "      <td>4.466429</td>\n",
       "      <td>7.291190</td>\n",
       "      <td>5.482143</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>1.69</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</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",
       "      <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",
       "      <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",
       "      <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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>2022-02-02</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.090000</td>\n",
       "      <td>455.933594</td>\n",
       "      <td>SPY_031122P455</td>\n",
       "      <td>SPY_031122P430</td>\n",
       "      <td>9.790000</td>\n",
       "      <td>15.820000</td>\n",
       "      <td>16.580000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>13.180000</td>\n",
       "      <td>10.750000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>12.420000</td>\n",
       "      <td>18.720000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>19.560000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>13.258000</td>\n",
       "      <td>17.053750</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.790000</td>\n",
       "      <td>6.080000</td>\n",
       "      <td>5.050000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>5.890000</td>\n",
       "      <td>4.110000</td>\n",
       "      <td>2.850000</td>\n",
       "      <td>5.090000</td>\n",
       "      <td>8.070000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>5.190000</td>\n",
       "      <td>4.667000</td>\n",
       "      <td>6.407500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>2022-01-26</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.959999</td>\n",
       "      <td>432.037842</td>\n",
       "      <td>SPY_030422P430</td>\n",
       "      <td>SPY_030422P405</td>\n",
       "      <td>12.560000</td>\n",
       "      <td>13.650000</td>\n",
       "      <td>8.540000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>5.420000</td>\n",
       "      <td>3.880000</td>\n",
       "      <td>2.880000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>4.800000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>3.150000</td>\n",
       "      <td>1.940000</td>\n",
       "      <td>3.960000</td>\n",
       "      <td>6.500000</td>\n",
       "      <td>6.450000</td>\n",
       "      <td>6.280000</td>\n",
       "      <td>4.250000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>2.520000</td>\n",
       "      <td>1.620000</td>\n",
       "      <td>1.300000</td>\n",
       "      <td>2.580000</td>\n",
       "      <td>1.760000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.610000</td>\n",
       "      <td>1.040000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>1.340000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>6.110000</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>2.11</td>\n",
       "      <td>2.11</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>2022-01-19</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23.850000</td>\n",
       "      <td>450.350922</td>\n",
       "      <td>SPY_022522P450</td>\n",
       "      <td>SPY_022522P425</td>\n",
       "      <td>10.980000</td>\n",
       "      <td>13.420000</td>\n",
       "      <td>17.830000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>17.440000</td>\n",
       "      <td>19.950000</td>\n",
       "      <td>22.300000</td>\n",
       "      <td>23.510000</td>\n",
       "      <td>16.300000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>9.990000</td>\n",
       "      <td>6.940000</td>\n",
       "      <td>6.880000</td>\n",
       "      <td>9.110000</td>\n",
       "      <td>8.840000</td>\n",
       "      <td>4.610000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>8.410000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>8.180000</td>\n",
       "      <td>10.550000</td>\n",
       "      <td>10.270000</td>\n",
       "      <td>10.520000</td>\n",
       "      <td>6.650000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>3.620000</td>\n",
       "      <td>2.340000</td>\n",
       "      <td>1.860000</td>\n",
       "      <td>3.780000</td>\n",
       "      <td>2.910000</td>\n",
       "      <td>6.370000</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.44</td>\n",
       "      <td>0.44</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>2022-01-12</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.620001</td>\n",
       "      <td>469.561249</td>\n",
       "      <td>SPY_021822P465</td>\n",
       "      <td>SPY_021822P440</td>\n",
       "      <td>6.650000</td>\n",
       "      <td>10.160000</td>\n",
       "      <td>9.200000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>14.360000</td>\n",
       "      <td>17.140000</td>\n",
       "      <td>20.510000</td>\n",
       "      <td>28.340000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>26.960000</td>\n",
       "      <td>32.070000</td>\n",
       "      <td>32.420000</td>\n",
       "      <td>32.520000</td>\n",
       "      <td>24.410000</td>\n",
       "      <td>2.580000</td>\n",
       "      <td>4.150000</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>5.660000</td>\n",
       "      <td>6.710000</td>\n",
       "      <td>8.950000</td>\n",
       "      <td>12.850000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>12.030000</td>\n",
       "      <td>15.290000</td>\n",
       "      <td>14.980000</td>\n",
       "      <td>15.090000</td>\n",
       "      <td>9.930000</td>\n",
       "      <td>4.070000</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-10.41</td>\n",
       "      <td>-10.41</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>32.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.730000</td>\n",
       "      <td>466.929443</td>\n",
       "      <td>SPY_021122P465</td>\n",
       "      <td>SPY_021122P440</td>\n",
       "      <td>8.240000</td>\n",
       "      <td>7.650000</td>\n",
       "      <td>8.560000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>8.390000</td>\n",
       "      <td>6.580000</td>\n",
       "      <td>5.680000</td>\n",
       "      <td>9.160000</td>\n",
       "      <td>8.200000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>13.690000</td>\n",
       "      <td>16.250000</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>25.340000</td>\n",
       "      <td>3.240000</td>\n",
       "      <td>3.450000</td>\n",
       "      <td>3.130000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>3.060000</td>\n",
       "      <td>2.380000</td>\n",
       "      <td>2.280000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>2.730000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>4.920000</td>\n",
       "      <td>5.740000</td>\n",
       "      <td>7.690000</td>\n",
       "      <td>11.830000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-8.51</td>\n",
       "      <td>-8.51</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>136800 rows × 88 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         quoteTimeInLong_ts  open_date   DTE  days_to_close  take_prof  \\\n",
       "trade_no                                                                 \n",
       "2                2022-05-11 2022-05-11  18.0            7.0        0.5   \n",
       "3                2022-05-04 2022-05-04  18.0            7.0        0.5   \n",
       "4                2022-04-27 2022-04-27  18.0            7.0        0.5   \n",
       "5                2022-04-20 2022-04-20  18.0            7.0        0.5   \n",
       "6                2022-04-13 2022-04-13  18.0            7.0        0.5   \n",
       "...                     ...        ...   ...            ...        ...   \n",
       "16               2022-02-02 2022-02-02  32.0           16.0        1.0   \n",
       "17               2022-01-26 2022-01-26  32.0           16.0        1.0   \n",
       "18               2022-01-19 2022-01-19  32.0           16.0        1.0   \n",
       "19               2022-01-12 2022-01-12  32.0           16.0        1.0   \n",
       "20               2022-01-05 2022-01-05  32.0           16.0        1.0   \n",
       "\n",
       "          take_loss       ^VIX         SPY       spy_upper       spy_lower  \\\n",
       "trade_no                                                                     \n",
       "2               0.1  32.560001  392.750000  SPY_060322P390  SPY_060322P365   \n",
       "3               0.1  25.420000  429.059998  SPY_052722P425  SPY_052722P400   \n",
       "4               0.1  31.600000  417.269989  SPY_052022P415  SPY_052022P390   \n",
       "5               0.1  20.320000  444.709991  SPY_051322P440  SPY_051322P415   \n",
       "6               0.1  21.820000  443.309998  SPY_050622P440  SPY_050622P415   \n",
       "...             ...        ...         ...             ...             ...   \n",
       "16              1.0  22.090000  455.933594  SPY_031122P455  SPY_031122P430   \n",
       "17              1.0  31.959999  432.037842  SPY_030422P430  SPY_030422P405   \n",
       "18              1.0  23.850000  450.350922  SPY_022522P450  SPY_022522P425   \n",
       "19              1.0  17.620001  469.561249  SPY_021822P465  SPY_021822P440   \n",
       "20              1.0  19.730000  466.929443  SPY_021122P465  SPY_021122P440   \n",
       "\n",
       "          spy_upp+0  spy_upp+1  spy_upp+2  spy_upp+3  spy_upp+4  spy_upp+5  \\\n",
       "trade_no                                                                     \n",
       "2          8.787143  11.882143   6.408293   5.657857   5.657857   5.657857   \n",
       "3         13.824286  16.206429  18.944524  25.995385  25.995385  25.995385   \n",
       "4          9.671429   7.765000  11.266905  13.258571  13.258571  13.258571   \n",
       "5          5.892857   7.034286  16.913333  19.348571  19.348571  19.348571   \n",
       "6          7.939286   7.896429   8.862143   8.862143   8.862143   8.862143   \n",
       "...             ...        ...        ...        ...        ...        ...   \n",
       "16         9.790000  15.820000  16.580000  13.180000  13.180000  13.180000   \n",
       "17        12.560000  13.650000   8.540000   5.420000   5.420000   5.420000   \n",
       "18        10.980000  13.420000  17.830000  17.440000  17.440000  17.440000   \n",
       "19         6.650000  10.160000   9.200000  14.360000  14.360000  14.360000   \n",
       "20         8.240000   7.650000   8.560000   8.390000   8.390000   8.390000   \n",
       "\n",
       "          spy_upp+6  spy_upp+7  spy_upp+8  spy_upp+9  spy_upp+10  spy_upp+11  \\\n",
       "trade_no                                                                       \n",
       "2          3.523571   7.051429   8.888571   9.086190    5.404286    5.404286   \n",
       "3         27.169286  28.667857  35.492857  25.042439   24.811429   24.811429   \n",
       "4          9.415000   8.088571   9.904286  11.644762   17.395385   17.395385   \n",
       "5         21.599286  22.029286  18.343571  25.666429   29.715714   29.715714   \n",
       "6          6.210714   4.767143   5.832857  15.903095   18.450000   18.450000   \n",
       "...             ...        ...        ...        ...         ...         ...   \n",
       "16        10.750000   7.750000  12.420000  18.720000   19.560000   19.560000   \n",
       "17         3.880000   2.880000   5.000000   4.800000    4.340000    4.340000   \n",
       "18        19.950000  22.300000  23.510000  16.300000    9.990000    9.990000   \n",
       "19        14.360000  17.140000  20.510000  28.340000   26.960000   26.960000   \n",
       "20         6.580000   5.680000   9.160000   8.200000   13.690000   13.690000   \n",
       "\n",
       "          spy_upp+12  spy_upp+13  spy_upp+14  spy_upp+15  spy_upp+16  \\\n",
       "trade_no                                                               \n",
       "2           5.404286    7.227857    4.637857    1.684286    0.341707   \n",
       "3          24.811429   19.578571   29.685714   34.800000   36.642381   \n",
       "4          17.395385   18.274286   19.430714   25.720714   15.472439   \n",
       "5          29.715714   23.948571   22.081429   25.399286   29.867619   \n",
       "6          18.450000   20.779286   21.305000   17.327857   25.090476   \n",
       "...              ...         ...         ...         ...         ...   \n",
       "16         19.560000   14.360000   13.258000   17.053750         NaN   \n",
       "17          4.340000    3.150000    1.940000    3.960000    6.500000   \n",
       "18          9.990000    6.940000    6.880000    9.110000    8.840000   \n",
       "19         26.960000   32.070000   32.420000   32.520000   24.410000   \n",
       "20         13.690000   13.690000   16.250000   20.500000   25.340000   \n",
       "\n",
       "          spy_lower+0  spy_lower+1  spy_lower+2  spy_lower+3  spy_lower+4  \\\n",
       "trade_no                                                                    \n",
       "2            2.900000     4.145714     1.800244     1.363571     1.363571   \n",
       "3            5.157143     6.400714     7.304048    10.873846    10.873846   \n",
       "4            3.747857     2.972857     4.401190     5.160000     5.160000   \n",
       "5            1.596429     2.013571     6.326429     7.385000     7.385000   \n",
       "6            2.457143     2.212143     2.303571     2.303571     2.303571   \n",
       "...               ...          ...          ...          ...          ...   \n",
       "16           3.790000     6.080000     5.050000     5.890000     5.890000   \n",
       "17           6.450000     6.280000     4.250000     2.520000     2.520000   \n",
       "18           4.610000     6.000000     8.410000     8.180000     8.180000   \n",
       "19           2.580000     4.150000     3.500000     5.660000     5.660000   \n",
       "20           3.240000     3.450000     3.130000     3.060000     3.060000   \n",
       "\n",
       "          spy_lower+5  spy_lower+6  spy_lower+7  spy_lower+8  spy_lower+9  \\\n",
       "trade_no                                                                    \n",
       "2            1.363571     0.756429     1.737857     2.275714     2.027381   \n",
       "3           10.873846    11.200714    11.573571    15.675714     8.495122   \n",
       "4            5.160000     3.102143     2.367143     3.053571     3.204524   \n",
       "5            7.385000     8.405000     8.255714     6.379286     9.604524   \n",
       "6            2.303571     1.385000     0.975000     1.263571     4.863571   \n",
       "...               ...          ...          ...          ...          ...   \n",
       "16           5.890000     4.110000     2.850000     5.090000     8.070000   \n",
       "17           2.520000     1.620000     1.300000     2.580000     1.760000   \n",
       "18           8.180000    10.550000    10.270000    10.520000     6.650000   \n",
       "19           5.660000     5.660000     6.710000     8.950000    12.850000   \n",
       "20           3.060000     2.380000     2.280000     3.300000     2.730000   \n",
       "\n",
       "          spy_lower+10  spy_lower+11  spy_lower+12  spy_lower+13  \\\n",
       "trade_no                                                           \n",
       "2             0.940000      0.940000      0.940000      1.250000   \n",
       "3             7.717857      7.717857      7.717857      4.689286   \n",
       "4             5.391538      5.391538      5.391538      5.412143   \n",
       "5            11.557857     11.557857     11.557857      7.676429   \n",
       "6             5.750714      5.750714      5.750714      6.530000   \n",
       "...                ...           ...           ...           ...   \n",
       "16            8.140000      8.140000      8.140000      5.190000   \n",
       "17            1.610000      1.610000      1.610000      1.040000   \n",
       "18            3.620000      3.620000      3.620000      2.340000   \n",
       "19           12.030000     12.030000     12.030000     15.290000   \n",
       "20            4.920000      4.920000      4.920000      4.920000   \n",
       "\n",
       "          spy_lower+14  spy_lower+15  spy_lower+16  credit_0 norm_pl+7  \\\n",
       "trade_no                                                                 \n",
       "2             0.630714      0.229286      0.090244  5.887143  0.573571   \n",
       "3             9.822143     12.705000     13.509524  8.667143 -8.427143   \n",
       "4             5.354286      8.162143      2.845854  5.923571  0.202143   \n",
       "5             6.375714      7.965714      9.495952  4.296429 -9.477143   \n",
       "6             6.329286      4.466429      7.291190  5.482143      1.69   \n",
       "...                ...           ...           ...       ...       ...   \n",
       "16            4.667000      6.407500           NaN  6.000000      None   \n",
       "17            0.660000      1.340000      2.500000  6.110000      None   \n",
       "18            1.860000      3.780000      2.910000  6.370000      None   \n",
       "19           14.980000     15.090000      9.930000  4.070000      None   \n",
       "20            5.740000      7.690000     11.830000  5.000000      None   \n",
       "\n",
       "         norm_pl+8 norm_pl+9 norm_pl+12 norm_pl+13 norm_pl+14 norm_pl+15  \\\n",
       "trade_no                                                                   \n",
       "2         0.573571  0.573571   0.573571   0.573571   0.573571   0.573571   \n",
       "3        -8.427143 -8.427143  -8.427143  -8.427143  -8.427143  -8.427143   \n",
       "4         0.202143  0.202143   0.202143   0.202143   0.202143   0.202143   \n",
       "5        -9.477143 -9.477143  -9.477143  -9.477143  -9.477143  -9.477143   \n",
       "6             1.69      1.69       1.69       1.69       1.69       1.69   \n",
       "...            ...       ...        ...        ...        ...        ...   \n",
       "16            None      None       None       None       None       None   \n",
       "17            None      None       None       None       None       None   \n",
       "18            None      None       None       None       None       None   \n",
       "19            None      None       None       None       None       None   \n",
       "20            None      None       None       None       None       None   \n",
       "\n",
       "         norm_pl+16   norm_pl  takeprof_day+0  takeloss_day+0  takeprof_day+1  \\\n",
       "trade_no                                                                        \n",
       "2          0.573571  0.573571           False           False           False   \n",
       "3         -8.427143 -8.427143           False           False           False   \n",
       "4          0.202143  0.202143           False           False           False   \n",
       "5         -9.477143 -9.477143           False           False           False   \n",
       "6              1.69      1.69           False           False           False   \n",
       "...             ...       ...             ...             ...             ...   \n",
       "16              NaN       NaN           False           False           False   \n",
       "17             2.11      2.11           False           False           False   \n",
       "18             0.44      0.44           False           False           False   \n",
       "19           -10.41    -10.41           False           False           False   \n",
       "20            -8.51     -8.51           False           False           False   \n",
       "\n",
       "          takeloss_day+1  takeprof_day+2  takeloss_day+2  takeprof_day+3  \\\n",
       "trade_no                                                                   \n",
       "2                  False           False           False           False   \n",
       "3                  False           False            True           False   \n",
       "4                  False           False           False           False   \n",
       "5                  False           False            True           False   \n",
       "6                  False           False           False           False   \n",
       "...                  ...             ...             ...             ...   \n",
       "16                 False           False           False           False   \n",
       "17                 False           False           False           False   \n",
       "18                 False           False           False           False   \n",
       "19                 False           False           False           False   \n",
       "20                 False           False           False           False   \n",
       "\n",
       "          takeloss_day+3  takeprof_day+4  takeloss_day+4  takeprof_day+5  \\\n",
       "trade_no                                                                   \n",
       "2                  False           False           False           False   \n",
       "3                   True           False            True           False   \n",
       "4                   True           False            True           False   \n",
       "5                   True           False            True           False   \n",
       "6                  False           False           False           False   \n",
       "...                  ...             ...             ...             ...   \n",
       "16                 False           False           False           False   \n",
       "17                 False           False           False           False   \n",
       "18                 False           False           False           False   \n",
       "19                 False           False           False           False   \n",
       "20                 False           False           False           False   \n",
       "\n",
       "          takeloss_day+5  takeprof_day+6  takeloss_day+6  takeprof_day+7  \\\n",
       "trade_no                                                                   \n",
       "2                  False            True           False           False   \n",
       "3                   True           False            True           False   \n",
       "4                   True           False           False           False   \n",
       "5                   True           False            True           False   \n",
       "6                  False           False           False           False   \n",
       "...                  ...             ...             ...             ...   \n",
       "16                 False           False           False           False   \n",
       "17                 False           False           False           False   \n",
       "18                 False           False           False           False   \n",
       "19                 False           False           False           False   \n",
       "20                 False           False           False           False   \n",
       "\n",
       "          takeloss_day+7  takeprof_day+8  takeloss_day+8  takeprof_day+9  \\\n",
       "trade_no                                                                   \n",
       "2                  False           False           False           False   \n",
       "3                   True           False            True           False   \n",
       "4                  False           False           False           False   \n",
       "5                   True           False            True           False   \n",
       "6                  False           False           False           False   \n",
       "...                  ...             ...             ...             ...   \n",
       "16                 False           False           False           False   \n",
       "17                 False           False           False           False   \n",
       "18                 False           False           False           False   \n",
       "19                 False           False           False           False   \n",
       "20                 False           False           False           False   \n",
       "\n",
       "          takeloss_day+9  takeprof_day+10  takeloss_day+10  takeprof_day+11  \\\n",
       "trade_no                                                                      \n",
       "2                  False            False            False            False   \n",
       "3                   True            False             True            False   \n",
       "4                   True            False             True            False   \n",
       "5                   True            False             True            False   \n",
       "6                   True            False             True            False   \n",
       "...                  ...              ...              ...              ...   \n",
       "16                 False            False            False            False   \n",
       "17                 False            False            False            False   \n",
       "18                 False            False            False            False   \n",
       "19                 False            False            False            False   \n",
       "20                 False            False            False            False   \n",
       "\n",
       "          takeloss_day+11  takeprof_day+12  takeloss_day+12  takeprof_day+13  \\\n",
       "trade_no                                                                       \n",
       "2                   False            False            False            False   \n",
       "3                    True            False             True            False   \n",
       "4                    True            False             True            False   \n",
       "5                    True            False             True            False   \n",
       "6                    True            False             True            False   \n",
       "...                   ...              ...              ...              ...   \n",
       "16                  False            False            False            False   \n",
       "17                  False            False            False            False   \n",
       "18                  False            False            False            False   \n",
       "19                  False            False            False            False   \n",
       "20                  False            False            False            False   \n",
       "\n",
       "          takeloss_day+13  takeprof_day+14  takeloss_day+14  takeprof_day+15  \\\n",
       "trade_no                                                                       \n",
       "2                   False            False            False             True   \n",
       "3                    True            False             True            False   \n",
       "4                    True            False             True            False   \n",
       "5                    True            False             True            False   \n",
       "6                    True            False             True            False   \n",
       "...                   ...              ...              ...              ...   \n",
       "16                  False            False            False            False   \n",
       "17                  False            False            False            False   \n",
       "18                  False            False            False            False   \n",
       "19                  False            False            False            False   \n",
       "20                  False            False            False            False   \n",
       "\n",
       "          takeloss_day+15  takeprof_day+16  takeloss_day+16  \n",
       "trade_no                                                     \n",
       "2                   False             True            False  \n",
       "3                    True            False             True  \n",
       "4                    True            False             True  \n",
       "5                    True            False             True  \n",
       "6                    True            False             True  \n",
       "...                   ...              ...              ...  \n",
       "16                  False            False            False  \n",
       "17                  False            False            False  \n",
       "18                  False            False            False  \n",
       "19                  False            False            False  \n",
       "20                  False            False            False  \n",
       "\n",
       "[136800 rows x 88 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#creating takeprof_day+X and takeprof_day+Y to compute the percentages\n",
    "for days in range(0,17):\n",
    "    credit_0 = out['spy_upp+0'] - out['spy_lower+0']         # credit on day 0\n",
    "    credit_day = out['spy_upp+' + str(days)] - out['spy_lower+'+ str(days)]       # credit of that day\n",
    "    out['takeprof_day+' + str(days)] = ((credit_0 - credit_day) / credit_0 > out['take_prof'])           # if the take prof ratio that day is larger than 'take prof' column, return True\n",
    "        \n",
    "    max_loss = 25 - credit_0\n",
    "    out['takeloss_day+' + str(days)] = ((credit_0 - credit_day) / max_loss) < (out['take_loss'] * -1)       # if the take loss ratio that day is larger than 'take loss' column, return True\n",
    "    \n",
    "display(out)    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4152aa96",
   "metadata": {},
   "source": [
    "### 2i. Create actual profit columns (actual_prof) which computes actual profit when taken early"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "4e56551c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# creates actual profit columns (by days) which computes actual profit when profit is taken early\n",
    "\n",
    "out['credit_0'] = out['spy_upp+0'] - out['spy_lower+0']\n",
    "\n",
    "for days in range(16,-1,-1):\n",
    "\n",
    "    out['credit_day'] = out['spy_upp+' + str(days)] - out['spy_lower+'+ str(days)] \n",
    "    out['early_prof+'+ str(days)] = np.where(out['takeprof_day+'+str(days)]==True, \n",
    "                         out['credit_0'] - out['credit_day'], \n",
    "                         false_func())\n",
    "out = out.copy()                                                 #to remove fragmented df warning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2e386c6",
   "metadata": {},
   "source": [
    "### 2j. Create actual loss columns (actual_loss) which computes actual profit when taken early"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "c98ee18e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# creates actual loss columns (by days) which computes actual loss when loss is taken early\n",
    "# working well\n",
    "\n",
    "for days in range(16,-1,-1):\n",
    "\n",
    "    out['credit_day_l'] = out['spy_upp+' + str(days)] - out['spy_lower+'+ str(days)] \n",
    "    out['early_loss+'+ str(days)] = np.where(out['takeloss_day+'+str(days)]==True, \n",
    "                                              out['credit_0'] - out['credit_day_l'] , \n",
    "                                              false_func())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27b26827",
   "metadata": {},
   "source": [
    "### 2k. Combine actual prof/loss into actual_pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "1a41969b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#combine actual_prof and actual_loss by day\n",
    "for days in range(0,17):\n",
    "    out['early_pl+'+ str(days)] = out['early_loss+'+ str(days)].combine_first(out['early_prof+'+ str(days)])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ea3c14b",
   "metadata": {},
   "source": [
    "### 2l. Combine all p/l into final_pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "4295da08",
   "metadata": {},
   "outputs": [],
   "source": [
    "#combine actual_pl into 1 column only\n",
    "\n",
    "for days in range(0,16):\n",
    "    \n",
    "    days_plus_1 = days + 1\n",
    "    out['early_pl+'+ str(days_plus_1)] = out['early_pl+'+ str(days)].combine_first(out['early_pl+'+ str(days_plus_1)])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "b5584514",
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_early_exit(df):\n",
    "    \n",
    "    early_exit = False\n",
    "    \n",
    "    for days in range(0, int(df['days_to_close'])+1):\n",
    "        if (df['takeprof_day+'+str(days)] == True) or (df['takeloss_day+'+str(days)] == True):\n",
    "            early_exit = True\n",
    "                               \n",
    "    if early_exit == True:\n",
    "        return df['early_pl+'+str(days)]    #, df['remarks']   # update remarks - early exit on day X\n",
    "    else:\n",
    "        return df['norm_pl']                #, df['remarks']               # update remarks - normal exit \n",
    "        \n",
    "out['final_pl'] = out.apply(check_early_exit, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "3d4b879b",
   "metadata": {},
   "outputs": [],
   "source": [
    "out['max_loss'] = 25 - (out['spy_upp+0'] - out['spy_lower+0'])\n",
    "out['final_pl%'] = out['final_pl'] / out['max_loss'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "8dbe0258",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create new column combi_no to groupby later\n",
    "\n",
    "reps = out.index.nunique()\n",
    "count = range(len(out.index) // int(reps))\n",
    "combi_no = np.repeat(count, reps)\n",
    "out['combi_no'] = combi_no\n",
    "\n",
    "# calculate mean for each combi and manipulate to correct format\n",
    "combi = out.groupby('combi_no')['final_pl%'].mean()\n",
    "series = pd.Series(np.repeat(combi, reps))\n",
    "series = series.rename('mean_pl%')\n",
    "series = series.reset_index()\n",
    "series = series['mean_pl%']\n",
    "series = series.copy()\n",
    "\n",
    "out = out.reset_index()\n",
    "out = pd.concat([out,series], axis=1)             # copy to out df.\n",
    "\n",
    "out['last5MA'] = out['final_pl%'].rolling(window=5).mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "293dc666",
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_8924/3710255576.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'last5MA'\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mout\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'mean_pl%'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrolling\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwindow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_csv\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'out116.csv'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\generic.py\u001b[0m in \u001b[0;36mto_csv\u001b[1;34m(self, path_or_buf, sep, na_rep, float_format, columns, header, index, index_label, mode, encoding, compression, quoting, quotechar, line_terminator, chunksize, date_format, doublequote, escapechar, decimal, errors, storage_options)\u001b[0m\n\u001b[0;32m   3464\u001b[0m         )\n\u001b[0;32m   3465\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3466\u001b[1;33m         return DataFrameRenderer(formatter).to_csv(\n\u001b[0m\u001b[0;32m   3467\u001b[0m             \u001b[0mpath_or_buf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3468\u001b[0m             \u001b[0mline_terminator\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mline_terminator\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\formats\\format.py\u001b[0m in \u001b[0;36mto_csv\u001b[1;34m(self, path_or_buf, encoding, sep, columns, index_label, mode, compression, quoting, quotechar, line_terminator, chunksize, date_format, doublequote, escapechar, errors, storage_options)\u001b[0m\n\u001b[0;32m   1103\u001b[0m             \u001b[0mformatter\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfmt\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1104\u001b[0m         )\n\u001b[1;32m-> 1105\u001b[1;33m         \u001b[0mcsv_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msave\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1106\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1107\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcreated_buffer\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\formats\\csvs.py\u001b[0m in \u001b[0;36msave\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    255\u001b[0m             )\n\u001b[0;32m    256\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 257\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_save\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    258\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    259\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_save\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\formats\\csvs.py\u001b[0m in \u001b[0;36m_save\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    260\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_need_to_save_header\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    261\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_save_header\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 262\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_save_body\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    263\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    264\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_save_header\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\formats\\csvs.py\u001b[0m in \u001b[0;36m_save_body\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    298\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mstart_i\u001b[0m \u001b[1;33m>=\u001b[0m \u001b[0mend_i\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    299\u001b[0m                 \u001b[1;32mbreak\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 300\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_save_chunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstart_i\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend_i\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    301\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    302\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_save_chunk\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstart_i\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend_i\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\io\\formats\\csvs.py\u001b[0m in \u001b[0;36m_save_chunk\u001b[1;34m(self, start_i, end_i)\u001b[0m\n\u001b[0;32m    305\u001b[0m         \u001b[0mdf\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mslicer\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    306\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 307\u001b[1;33m         \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_mgr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mto_native_types\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_number_format\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    308\u001b[0m         \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miget_values\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    309\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\internals\\managers.py\u001b[0m in \u001b[0;36mto_native_types\u001b[1;34m(self, **kwargs)\u001b[0m\n\u001b[0;32m    464\u001b[0m         \u001b[1;32min\u001b[0m \u001b[0mformatting\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mrepr\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mcsv\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    465\u001b[0m         \"\"\"\n\u001b[1;32m--> 466\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"to_native_types\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    467\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    468\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mis_consolidated\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mbool\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\internals\\managers.py\u001b[0m in \u001b[0;36mapply\u001b[1;34m(self, f, align_keys, ignore_failures, **kwargs)\u001b[0m\n\u001b[0;32m    325\u001b[0m                     \u001b[0mapplied\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    326\u001b[0m                 \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 327\u001b[1;33m                     \u001b[0mapplied\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mb\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    328\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mTypeError\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    329\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mignore_failures\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\internals\\blocks.py\u001b[0m in \u001b[0;36mto_native_types\u001b[1;34m(self, na_rep, quoting, **kwargs)\u001b[0m\n\u001b[0;32m    639\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mto_native_types\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mna_rep\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"nan\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mquoting\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    640\u001b[0m         \u001b[1;34m\"\"\"convert to our native types format\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 641\u001b[1;33m         \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mto_native_types\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mna_rep\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mna_rep\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mquoting\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mquoting\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    642\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake_block\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    643\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\lib\\site-packages\\pandas\\core\\internals\\blocks.py\u001b[0m in \u001b[0;36mto_native_types\u001b[1;34m(values, na_rep, quoting, float_format, decimal, **kwargs)\u001b[0m\n\u001b[0;32m   2076\u001b[0m                 \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"object\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2077\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2078\u001b[1;33m             \u001b[0mvalues\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmask\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mna_rep\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2079\u001b[0m             \u001b[0mvalues\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mvalues\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobject\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2080\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mvalues\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "out.to_csv('out116.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "ef7b4282",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lowest mean_pl%\n",
    "out2 = out[['trade_no','open_date','DTE','days_to_close','take_prof','take_loss','mean_pl%','combi_no','last5MA','final_pl%']]\n",
    "out2.set_index('trade_no', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e373c3a4",
   "metadata": {},
   "source": [
    "# Some performance tracking"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8c157e0",
   "metadata": {},
   "source": [
    "## Check last 5 MA with best performance "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "53fafee8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>6</th>\n",
       "      <td>2022-04-13</td>\n",
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       "      <td>16.0</td>\n",
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       "      <td>-0.496267</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022-04-13</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.5</td>\n",
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       "    <tr>\n",
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       "      <td>2022-04-13</td>\n",
       "      <td>21.0</td>\n",
       "      <td>16.0</td>\n",
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       "      <td>1869</td>\n",
       "      <td>-0.496267</td>\n",
       "      <td>-0.63107</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "          open_date   DTE  days_to_close  take_prof  take_loss  mean_pl%  \\\n",
       "trade_no                                                                   \n",
       "6        2022-04-13  22.0           16.0        0.5        0.9 -0.275335   \n",
       "6        2022-04-13  22.0           16.0        0.5        1.0 -0.275335   \n",
       "6        2022-04-13  21.0           16.0        0.5        1.0 -0.275335   \n",
       "\n",
       "          combi_no   last5MA  final_pl%  \n",
       "trade_no                                 \n",
       "6             2348 -0.496267   -0.63107  \n",
       "6             2349 -0.496267   -0.63107  \n",
       "6             1869 -0.496267   -0.63107  "
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>mean_pl%</th>\n",
       "      <th>combi_no</th>\n",
       "      <th>last5MA</th>\n",
       "      <th>final_pl%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_no</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",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-04-06</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.8</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-04-06</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.262283</td>\n",
       "      <td>2369</td>\n",
       "      <td>-0.625424</td>\n",
       "      <td>-0.482543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022-04-06</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.0</td>\n",
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       "</div>"
      ],
      "text/plain": [
       "          open_date   DTE  days_to_close  take_prof  take_loss  mean_pl%  \\\n",
       "trade_no                                                                   \n",
       "7        2022-04-06  22.0           16.0        0.8        0.9 -0.252790   \n",
       "7        2022-04-06  22.0           16.0        0.7        1.0 -0.262283   \n",
       "7        2022-04-06  22.0           16.0        0.5        1.0 -0.275335   \n",
       "\n",
       "          combi_no   last5MA  final_pl%  \n",
       "trade_no                                 \n",
       "7             2378 -0.625424  -0.482543  \n",
       "7             2369 -0.625424  -0.482543  \n",
       "7             2349 -0.625424  -0.482543  "
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       "        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>open_date</th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>mean_pl%</th>\n",
       "      <th>combi_no</th>\n",
       "      <th>last5MA</th>\n",
       "      <th>final_pl%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_no</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>8</th>\n",
       "      <td>2022-03-30</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-0.218335</td>\n",
       "      <td>2353</td>\n",
       "      <td>-0.442032</td>\n",
       "      <td>-0.421278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-03-30</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-0.212796</td>\n",
       "      <td>2363</td>\n",
       "      <td>-0.442032</td>\n",
       "      <td>-0.421278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022-03-30</td>\n",
       "      <td>22.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-0.197448</td>\n",
       "      <td>2383</td>\n",
       "      <td>-0.442032</td>\n",
       "      <td>-0.421278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          open_date   DTE  days_to_close  take_prof  take_loss  mean_pl%  \\\n",
       "trade_no                                                                   \n",
       "8        2022-03-30  22.0           16.0        0.6        0.4 -0.218335   \n",
       "8        2022-03-30  22.0           16.0        0.7        0.4 -0.212796   \n",
       "8        2022-03-30  22.0           16.0        0.9        0.4 -0.197448   \n",
       "\n",
       "          combi_no   last5MA  final_pl%  \n",
       "trade_no                                 \n",
       "8             2353 -0.442032  -0.421278  \n",
       "8             2363 -0.442032  -0.421278  \n",
       "8             2383 -0.442032  -0.421278  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(out2.loc[6].sort_values(by='last5MA').head(3))\n",
    "display(out2.loc[7].sort_values(by='last5MA').head(3))\n",
    "display(out2.loc[8].sort_values(by='last5MA').head(3))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01a2a303",
   "metadata": {},
   "source": [
    "## Checks the top mean_pl for all trades from Jan 2022"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "34bf826a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DTE</th>\n",
       "      <th>days_to_close</th>\n",
       "      <th>take_prof</th>\n",
       "      <th>take_loss</th>\n",
       "      <th>combi_no</th>\n",
       "      <th>last5MA</th>\n",
       "      <th>final_pl%</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean_pl%</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-0.283029</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1387.0</td>\n",
       "      <td>-0.342018</td>\n",
       "      <td>-0.283029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.276476</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.70</td>\n",
       "      <td>1386.0</td>\n",
       "      <td>-0.332623</td>\n",
       "      <td>-0.276476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.275863</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1397.0</td>\n",
       "      <td>-0.332486</td>\n",
       "      <td>-0.275863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.275335</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1388.5</td>\n",
       "      <td>-0.349943</td>\n",
       "      <td>-0.275335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.269978</th>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.80</td>\n",
       "      <td>1407.0</td>\n",
       "      <td>-0.329366</td>\n",
       "      <td>-0.269978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>-0.051981</th>\n",
       "      <td>31.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.85</td>\n",
       "      <td>0.10</td>\n",
       "      <td>6275.0</td>\n",
       "      <td>-0.074948</td>\n",
       "      <td>-0.051981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.049646</th>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.10</td>\n",
       "      <td>970.0</td>\n",
       "      <td>-0.066441</td>\n",
       "      <td>-0.049646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.047384</th>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.10</td>\n",
       "      <td>980.0</td>\n",
       "      <td>-0.063433</td>\n",
       "      <td>-0.047384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-0.047112</th>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.10</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>-0.062297</td>\n",
       "      <td>-0.047112</td>\n",
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       "    <tr>\n",
       "      <th>-0.045246</th>\n",
       "      <td>20.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.10</td>\n",
       "      <td>960.0</td>\n",
       "      <td>-0.099010</td>\n",
       "      <td>-0.045246</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>719 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            DTE  days_to_close  take_prof  take_loss  combi_no   last5MA  \\\n",
       "mean_pl%                                                                   \n",
       "-0.283029  20.0           16.0       0.50       0.80    1387.0 -0.342018   \n",
       "-0.276476  20.0           16.0       0.50       0.70    1386.0 -0.332623   \n",
       "-0.275863  20.0           16.0       0.60       0.80    1397.0 -0.332486   \n",
       "-0.275335  20.0           16.0       0.50       0.95    1388.5 -0.349943   \n",
       "-0.269978  20.0           16.0       0.70       0.80    1407.0 -0.329366   \n",
       "...         ...            ...        ...        ...       ...       ...   \n",
       "-0.051981  31.0            7.0       0.85       0.10    6275.0 -0.074948   \n",
       "-0.049646  20.0            7.0       0.60       0.10     970.0 -0.066441   \n",
       "-0.047384  20.0            7.0       0.70       0.10     980.0 -0.063433   \n",
       "-0.047112  20.0            7.0       0.90       0.10    1000.0 -0.062297   \n",
       "-0.045246  20.0            7.0       0.50       0.10     960.0 -0.099010   \n",
       "\n",
       "           final_pl%  \n",
       "mean_pl%              \n",
       "-0.283029  -0.283029  \n",
       "-0.276476  -0.276476  \n",
       "-0.275863  -0.275863  \n",
       "-0.275335  -0.275335  \n",
       "-0.269978  -0.269978  \n",
       "...              ...  \n",
       "-0.051981  -0.051981  \n",
       "-0.049646  -0.049646  \n",
       "-0.047384  -0.047384  \n",
       "-0.047112  -0.047112  \n",
       "-0.045246  -0.045246  \n",
       "\n",
       "[719 rows x 7 columns]"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out2.groupby(by='mean_pl%',sort='True').mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee6d6cbf",
   "metadata": {},
   "source": [
    "From above, we can tell that the worst strategy is using DTE=20, days_to_close=16, take_prof=0.5, and take_loss=0.8. The YTD loss is 28.3%.\n",
    "On the flipside, we would have generated the best profit if the reverse strategy was traded - i.e. buy a put ATM, sell a put 25 points below.\n",
    "This is so far a viable strategy, however, close monitoring is required to see if the strategy continues to perform well in the future due to fast changing market conditions."
   ]
  }
 ],
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