options-backtesting/backtesting/backtest_iron_condor.py

import logging
import os
import pandas as pd

from concurrent.futures import ProcessPoolExecutor
from dataclasses import dataclass
from datetime import datetime
from dotenv import load_dotenv

from .credit_target_strategy import CreditTargetStrategy
from .delta_target_strategy import DeltaTargetStrategy
from .option_spread_strategy import OptionSpreadStrategy
from .option_type import OptionType

load_dotenv()

logging.basicConfig(level=logging.WARN)

FEES_PER_CONTRACT = 0.80
MARKET_CLOSE = '16:00:00'
MARKET_OPEN = '09:35:00'
OPTION_DATA_DIRECTORY = os.getenv('OPTION_DATA_DIRECTORY')
STRIKE_MULTIPLE = 5.0

@dataclass
class BacktestResult:
    date: str
    entry_time: str
    exit_time: str
    spreads: list
    trade_entered: bool
    trade_pnl: float
    profit: float
    credit: float
    mfe: float
    mae: float

# Metrics
dates = []
max_drawdowns = []
max_profits = []
wins = []
exit_times = []

def get_spread_history_credit(historical_option_data: pd.DataFrame, option_strat: CreditTargetStrategy) -> pd.DataFrame:
    current_date = historical_option_data.iloc[0]['quote_datetime'][:10]
    opening_quotes = historical_option_data[(historical_option_data['quote_datetime'] == (current_date + ' ' + option_strat.trade_entry_time))]
    if opening_quotes.empty:
        return None
    else:
        opening_quotes_by_contract_type = opening_quotes[opening_quotes['option_type'] == option_strat.option_type.value]
        short_contract_candidates = opening_quotes_by_contract_type[(opening_quotes_by_contract_type['bid'] >= (option_strat.credit_target - 1.0)) & (opening_quotes_by_contract_type['bid'] < (option_strat.credit_target + 1.0))]
        credit_increment = 2.00
        while short_contract_candidates.empty:
            short_contract_candidates = opening_quotes_by_contract_type[(opening_quotes_by_contract_type['bid'] >= (option_strat.credit_target - credit_increment)) & (opening_quotes_by_contract_type['bid'] < (option_strat.credit_target + credit_increment))]
            credit_increment += 1.00

        strike_candidates = {}
        for i in range(len(short_contract_candidates)):
            candidate = short_contract_candidates.iloc[i]
            strike_candidates[candidate['bid']] = candidate['strike']

        closest_bid = min(strike_candidates, key=lambda candidate_bid: abs(option_strat.credit_target - candidate_bid))
        short_strike = strike_candidates[closest_bid]
        logging.info('Short Strike: %s', short_strike)

        long_strike = short_strike + (option_strat.spread_width if option_strat.option_type == OptionType.CALL else -option_strat.spread_width)
        # Sometimes the strike we're interested in doesn't exist. Find the nearest one that does.
        increment = 5.0 if option_strat.option_type == OptionType.CALL else -5.0
        while opening_quotes_by_contract_type[(opening_quotes_by_contract_type['strike'] == long_strike)].empty: # TODO: Doesn't work for one day in 2018.
            long_strike = long_strike + increment
        logging.info('Long Strike: %s', long_strike)

        short_strike_history = historical_option_data[(historical_option_data['strike'] == short_strike) & (historical_option_data['option_type'] == option_strat.option_type.value)].set_index('quote_datetime')
        long_strike_history = historical_option_data[(historical_option_data['strike'] == long_strike) & (historical_option_data['option_type'] == option_strat.option_type.value)].set_index('quote_datetime')
        spread_history = short_strike_history.join(long_strike_history, lsuffix='_short_strike', rsuffix='_long_strike', on='quote_datetime')
        return spread_history

def get_spread_history(historical_option_data: pd.DataFrame, option_strat: DeltaTargetStrategy) -> pd.DataFrame:
    current_date = historical_option_data.iloc[0]['quote_datetime'][:10]
    opening_quotes = historical_option_data[(historical_option_data['quote_datetime'] == (current_date + ' ' + option_strat.trade_entry_time))]
    if opening_quotes.empty:
        return None
    else:
        if option_strat.option_type == OptionType.PUT:
            short_contract_candidates = opening_quotes[(opening_quotes['delta'] > -option_strat.delta_upper_bound) & (opening_quotes['delta'] <= -option_strat.delta_lower_bound)]
        else:
            short_contract_candidates = opening_quotes[(opening_quotes['delta'] < option_strat.delta_upper_bound) & (opening_quotes['delta'] >= option_strat.delta_lower_bound)]
        delta_increment = 0.01
        while short_contract_candidates.empty:
            if option_strat.option_type == OptionType.PUT:
                short_contract_candidates = opening_quotes[(opening_quotes['delta'] > (-option_strat.delta_upper_bound - delta_increment)) & (opening_quotes['delta'] <= -option_strat.delta_lower_bound)]
            else:
                short_contract_candidates = opening_quotes[(opening_quotes['delta'] < (option_strat.delta_upper_bound + delta_increment)) & (opening_quotes['delta'] >= option_strat.delta_lower_bound)]
            delta_increment = delta_increment + 0.01
        # Might return more than one, take greatest strike
        short_contract = short_contract_candidates.iloc[-1]

        short_strike = short_contract['strike']
        logging.info('Short Strike: %s', short_strike)

        long_strike = short_strike + (option_strat.spread_width if option_strat.option_type == OptionType.CALL else -option_strat.spread_width)
        # Sometimes the strike we're interested in doesn't exist. Find the nearest one that does.
        increment = 5.0 if option_strat.option_type == OptionType.CALL else -5.0
        while opening_quotes[(opening_quotes['strike'] == long_strike)].empty: # TODO: Doesn't work for one day in 2018.
            long_strike = long_strike + increment
        logging.info('Long Strike: %s', long_strike)

        short_strike_history = historical_option_data[(historical_option_data['strike'] == short_strike) & (historical_option_data['option_type'] == option_strat.option_type.value)].set_index('quote_datetime')
        long_strike_history = historical_option_data[(historical_option_data['strike'] == long_strike) & (historical_option_data['option_type'] == option_strat.option_type.value)].set_index('quote_datetime')
        spread_history = short_strike_history.join(long_strike_history, lsuffix='_short_strike', rsuffix='_long_strike', on='quote_datetime')
        return spread_history

def _backtest_iron_condor(
        historical_data_file: str, 
        call_spread_strategy: OptionSpreadStrategy, 
        put_spread_strategy: OptionSpreadStrategy
    ) -> BacktestResult:

    print('Processing File:', historical_data_file)
    historical_option_data = pd.read_csv(historical_data_file)

    if isinstance(call_spread_strategy, CreditTargetStrategy):
        call_spread_history = get_spread_history_credit(historical_option_data, call_spread_strategy)
        put_spread_history = get_spread_history_credit(historical_option_data, put_spread_strategy)
    else:
        call_spread_history = get_spread_history(historical_option_data, call_spread_strategy)
        put_spread_history = get_spread_history(historical_option_data, put_spread_strategy)
    
    entry_time = call_spread_strategy.trade_entry_time

    if call_spread_history is None or put_spread_history is None:
        # This can happen when the market closes early for the day.
        logging.warn('No spread history found in %s for %s', historical_data_file, entry_time)
        return None

    current_date = call_spread_history.iloc[0].name[:10]

    call_spread_entry = call_spread_history.loc[current_date + ' ' + entry_time]
    original_call_spread_price = ((call_spread_entry['ask_short_strike'] + call_spread_entry['bid_short_strike']) / 2.0) - ((call_spread_entry['ask_long_strike'] + call_spread_entry['bid_long_strike']) / 2.0)

    put_spread_entry = put_spread_history.loc[current_date + ' ' + entry_time]
    original_put_spread_price = ((put_spread_entry['ask_short_strike'] + put_spread_entry['bid_short_strike']) / 2.0) - ((put_spread_entry['ask_long_strike'] + put_spread_entry['bid_long_strike']) / 2.0)

    # Calculate entry slippage.
    if original_call_spread_price > 0.05:
        original_call_spread_price = original_call_spread_price - (original_call_spread_price % 0.05)
    logging.info('Original Call Spread Price: %s', original_call_spread_price)

    if original_put_spread_price > 0.05:
        original_put_spread_price = original_put_spread_price - (original_put_spread_price % 0.05)
    logging.info('Original Put Spread Price: %s', original_put_spread_price)
    
    premium_received = original_call_spread_price + original_put_spread_price

    call_spread_details = {
        "legs": [{"action": "SELL", "strike": call_spread_entry['strike_short_strike'], "type": "CALL"}, 
                 {"action": "BUY", "strike": call_spread_entry['strike_long_strike'], "type": "CALL"}],
        "open": original_call_spread_price,
        "high": None,
        "low": None,
        "close": None
    }

    put_spread_details = {
        "legs": [{"action": "SELL", "strike": put_spread_entry['strike_short_strike'], "type": "PUT"}, 
                 {"action": "BUY", "strike": put_spread_entry['strike_long_strike'], "type": "PUT"}],
        "open": original_put_spread_price,
        "high": None,
        "low": None,
        "close": None
    }

    trades_entered = False
    call_spread_stopped_out = False
    put_spread_stopped_out = False

    max_profit = 0.0
    max_drawdown = 0.0
    exit_time = '16:00:00'

    for i in range(len(call_spread_history)):
        call_spread = call_spread_history.iloc[i]
        put_spread = put_spread_history.iloc[i]

        if call_spread.name.endswith(entry_time):
            trades_entered = True
            continue

        if not trades_entered:
            continue
        
        if call_spread.name.endswith('16:05:00') or call_spread.name.endswith('16:10:00') or call_spread.name.endswith('16:15:00'):
            continue

        if call_spread['high_short_strike'] > call_spread['high_long_strike']:
            current_call_spread_price = call_spread['high_short_strike'] - call_spread['high_long_strike']
        else:
            current_call_spread_price = ((call_spread['ask_short_strike'] + call_spread['bid_short_strike']) / 2.0) - ((call_spread['ask_long_strike'] + call_spread['bid_long_strike']) / 2.0)
        if put_spread['high_short_strike'] > put_spread['high_long_strike']:
            current_put_spread_price = put_spread['high_short_strike'] - put_spread['high_long_strike']
        else:
            current_put_spread_price = ((put_spread['ask_short_strike'] + put_spread['bid_short_strike']) / 2.0) - ((put_spread['ask_long_strike'] + put_spread['bid_long_strike']) / 2.0)
        
        call_spread_details['high'] = max(call_spread_details['high'] or float('-inf'), current_call_spread_price)
        call_spread_details['low'] = min(call_spread_details['low'] or float('inf'), current_call_spread_price)
        call_spread_details['close'] = current_call_spread_price

        put_spread_details['high'] = max(put_spread_details['high'] or float('-inf'), current_put_spread_price)
        put_spread_details['low'] = min(put_spread_details['low'] or float('inf'), current_put_spread_price)
        put_spread_details['close'] = current_put_spread_price

        if not call_spread_stopped_out:
            if current_call_spread_price >= ((call_spread_strategy.stop_loss_multiple + 1) * original_call_spread_price):
                premium_received -= original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1)
                call_spread_details['close'] = original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1) + 0.10
                # Calculate exit slippage.
                premium_received -= 0.10 # TODO: Make this configurable.
                call_spread_stopped_out = True
                exit_time = call_spread.name[-8:]
                logging.info('Call Spread Stopped Out')
        
        if not put_spread_stopped_out:
            if current_put_spread_price >= ((put_spread_strategy.stop_loss_multiple + 1) * original_put_spread_price):
                premium_received -= original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1)
                premium_received -= 0.10 # TODO: Make this configurable.
                put_spread_details['close'] = original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1) + 0.10
                put_spread_stopped_out = True
                exit_time = call_spread.name[-8:]
                logging.info('Put Spread Stopped Out')

        if not (call_spread_stopped_out and put_spread_stopped_out):
            if current_call_spread_price > current_put_spread_price:
                if put_spread['low_short_strike'] > put_spread['low_long_strike']:
                    current_put_spread_price = put_spread['low_short_strike'] - put_spread['low_long_strike']
                else:
                    current_put_spread_price = ((put_spread['ask_short_strike'] + put_spread['bid_short_strike']) / 2.0) - ((put_spread['ask_long_strike'] + put_spread['bid_long_strike']) / 2.0)  
            else:
                if call_spread['low_short_strike'] > call_spread['low_long_strike']:
                    current_call_spread_price = call_spread['low_short_strike'] - call_spread['low_long_strike']
                else:
                    current_call_spread_price = ((call_spread['ask_short_strike'] + call_spread['bid_short_strike']) / 2.0) - ((call_spread['ask_long_strike'] + call_spread['bid_long_strike']) / 2.0)
            if call_spread_stopped_out:
                current_call_spread_price = original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1)
                if put_spread['high_short_strike'] > put_spread['high_long_strike']:
                    current_put_spread_price = put_spread['high_short_strike'] - put_spread['high_long_strike']
                else:
                    current_put_spread_price = ((put_spread['ask_short_strike'] + put_spread['bid_short_strike']) / 2.0) - ((put_spread['ask_long_strike'] + put_spread['bid_long_strike']) / 2.0)
            if put_spread_stopped_out:
                current_put_spread_price = original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1)
                if call_spread['high_short_strike'] > call_spread['high_long_strike']:
                    current_call_spread_price = call_spread['high_short_strike'] - call_spread['high_long_strike']
                else:
                    current_call_spread_price = ((call_spread['ask_short_strike'] + call_spread['bid_short_strike']) / 2.0) - ((call_spread['ask_long_strike'] + call_spread['bid_long_strike']) / 2.0)
            current_profit = (original_call_spread_price - current_call_spread_price) + (original_put_spread_price - current_put_spread_price)
            current_profit_dollars = current_profit * call_spread_strategy.number_of_contracts * 100
            if current_profit_dollars > max_profit:
                max_profit = current_profit_dollars
            if current_profit_dollars < max_drawdown:
                max_drawdown = current_profit_dollars
    
    if not call_spread_stopped_out and current_call_spread_price > 0.05:
            premium_received -= current_call_spread_price
    
    if not put_spread_stopped_out and current_put_spread_price > 0.05:
        premium_received -= current_put_spread_price
    
    number_of_contracts = call_spread_strategy.number_of_contracts
    stop_out_fees = 0.0 # It costs money to get stopped out.
    if call_spread_stopped_out:
        stop_out_fees += (2 * FEES_PER_CONTRACT * number_of_contracts)
    if put_spread_stopped_out:
        stop_out_fees += (2 * FEES_PER_CONTRACT * number_of_contracts)
    fees = 4 * FEES_PER_CONTRACT * number_of_contracts
    commissions = 4 * number_of_contracts
    premium_received = (premium_received * number_of_contracts * 100) - (fees + commissions) - stop_out_fees

    dates.append(current_date)
    max_drawdowns.append(max_drawdown)
    max_profits.append(max_profit)
    wins.append(True if premium_received > 0 else False)
    exit_times.append(exit_time)

    result = BacktestResult(
        date=current_date,
        entry_time=f'{current_date} {entry_time}',
        exit_time=f'{current_date} {exit_time}',
        spreads=[call_spread_details, put_spread_details],
        trade_entered=True,
        trade_pnl=premium_received,
        profit=0.0, # TODO: Calculated elsewhere. Clean this up.
        credit=original_call_spread_price + original_put_spread_price,
        mfe=max_profit,
        mae=max_drawdown
    )

    logging.info('Premium Received: %f', premium_received)
    return result

def backtest_iron_condor(
        backtest_name: str,
        call_spread_strategy: OptionSpreadStrategy, 
        put_spread_strategy: OptionSpreadStrategy, 
        start_date: datetime, 
        end_date: datetime
    ) -> pd.DataFrame:

    total_premium_received = 0.0
    total_trades = 0.0
    total_wins = 0.0

    start_year = start_date.year
    end_year = end_date.year

    futures = []
    with ProcessPoolExecutor(max_workers = 10) as executor:
        for year in range(start_year, end_year + 1):
            year_directory = os.path.join(OPTION_DATA_DIRECTORY, str(year))
            for file in os.listdir(year_directory):
                historical_data_file = os.path.join(year_directory, file)
                if os.path.isdir(historical_data_file) or not file.endswith('.csv'):
                    continue

                # Assuming file format 'YYYY-MM-DD.csv'.
                file_date_str = os.path.splitext(file)[0]
                file_date = datetime.strptime(file_date_str, '%Y-%m-%d')

                # TODO: This doesn't work as expected when the start date is not set to midnight.
                if file_date < start_date or file_date > end_date:
                    continue

                logging.info('Processing File: %s', historical_data_file)

                future = executor.submit(_backtest_iron_condor, 
                    historical_data_file, call_spread_strategy, put_spread_strategy)
                futures.append(future)

    backtest_results = []
    for future in futures:
        backtest_result = future.result()
        if backtest_result:
            total_premium_received += backtest_result.trade_pnl
            backtest_result.profit = total_premium_received
            backtest_results.append(backtest_result)

            if backtest_result.trade_entered:
                total_trades += 1
                if backtest_result.trade_pnl > 0.0:
                    total_wins += 1

            logging.info('Overall PnL: %f', total_premium_received)
            logging.info('Win Rate: %f', (total_wins / total_trades) if total_trades > 0 else 0.0)
            logging.info('Average Premium Received: %f', (total_premium_received / total_trades) if total_trades > 0 else 0.0)

    # TODO: Either look up the symbol in the historical option data or have the client provide it.
    backtest_results = pd.DataFrame([{
        'Date': result.date,
        'Symbol': 'SPX',
        'Strategy': backtest_name,
        'Entry Time': result.entry_time,
        'Exit Time': result.exit_time,
        'Spreads': result.spreads,
        'Profit': result.trade_pnl,
        'Cumulative Profit': result.profit
    } for result in backtest_results])

    return backtest_results