329 lines
17 KiB
Python
329 lines
17 KiB
Python
import logging
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import os
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import pandas as pd
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from concurrent.futures import ProcessPoolExecutor
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from datetime import datetime, time
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from dotenv import load_dotenv
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from typing import List
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from .backtest_result import BacktestResult
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from .credit_targeting import CreditTargetStrategy
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from .delta_targeting import DeltaTargetStrategy
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from .filter import BacktestFilter
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from .option_spread_strategy import OptionSpreadStrategy
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from .option_type import OptionType
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load_dotenv()
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FEES_PER_CONTRACT = 0.80
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MARKET_CLOSE = '16:00:00'
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MARKET_OPEN = '09:35:00'
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OPTION_DATA_DIRECTORY = os.getenv('OPTION_DATA_DIRECTORY')
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STRIKE_MULTIPLE = 5.0
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# Metrics
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dates = []
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max_drawdowns = []
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max_profits = []
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wins = []
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exit_times = []
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def get_spread_history_credit(historical_option_data: pd.DataFrame, option_strat: CreditTargetStrategy) -> pd.DataFrame:
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current_date = historical_option_data.iloc[0]['quote_datetime'][:10]
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opening_quotes = historical_option_data[(historical_option_data['quote_datetime'] == (current_date + ' ' + option_strat.trade_entry_time))].copy()
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if opening_quotes.empty:
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return None
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else:
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opening_quotes_by_contract_type = opening_quotes[opening_quotes['option_type'] == option_strat.option_type.value].copy()
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opening_quotes_by_contract_type['credit_diff'] = (opening_quotes_by_contract_type['bid'] - option_strat.credit_target).abs()
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short_contract = opening_quotes_by_contract_type.loc[opening_quotes_by_contract_type['credit_diff'].idxmin()]
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short_strike = short_contract['strike']
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logging.info('Short Strike: %s', short_strike)
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long_strike = short_strike + (option_strat.spread_width if option_strat.option_type == OptionType.CALL else -option_strat.spread_width)
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# Sometimes the strike we're interested in doesn't exist. Find the nearest one that does.
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increment = 5.0 if option_strat.option_type == OptionType.CALL else -5.0
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while opening_quotes_by_contract_type[(opening_quotes_by_contract_type['strike'] == long_strike)].empty:
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long_strike = long_strike + increment
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logging.info('Long Strike: %s', long_strike)
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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')
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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')
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spread_history = short_strike_history.join(long_strike_history, lsuffix='_short_strike', rsuffix='_long_strike', on='quote_datetime')
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return spread_history
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def get_spread_history(historical_option_data: pd.DataFrame, option_strat: DeltaTargetStrategy) -> pd.DataFrame:
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current_date = historical_option_data.iloc[0]['quote_datetime'][:10]
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opening_quotes = historical_option_data[(historical_option_data['quote_datetime'] == (current_date + ' ' + option_strat.trade_entry_time))].copy()
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if opening_quotes.empty:
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return None
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else:
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opening_quotes['delta_diff'] = (opening_quotes['delta'] - option_strat.delta_target).abs()
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short_contract = opening_quotes.loc[opening_quotes['delta_diff'].idxmin()]
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short_strike = short_contract['strike']
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logging.info('Short Strike: %s', short_strike)
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long_strike = short_strike + (option_strat.spread_width if option_strat.option_type == OptionType.CALL else -option_strat.spread_width)
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# Sometimes the strike we're interested in doesn't exist. Find the nearest one that does.
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increment = 5.0 if option_strat.option_type == OptionType.CALL else -5.0
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while opening_quotes[(opening_quotes['strike'] == long_strike)].empty:
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long_strike = long_strike + increment
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logging.info('Long Strike: %s', long_strike)
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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')
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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')
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spread_history = short_strike_history.join(long_strike_history, lsuffix='_short_strike', rsuffix='_long_strike', on='quote_datetime')
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return spread_history
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def _backtest_iron_condor(
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historical_data_file: str,
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call_spread_strategy: OptionSpreadStrategy,
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put_spread_strategy: OptionSpreadStrategy
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) -> BacktestResult:
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print('Processing File:', historical_data_file)
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historical_option_data = pd.read_csv(historical_data_file)
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if isinstance(call_spread_strategy, CreditTargetStrategy):
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call_spread_history = get_spread_history_credit(historical_option_data, call_spread_strategy)
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put_spread_history = get_spread_history_credit(historical_option_data, put_spread_strategy)
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else:
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call_spread_history = get_spread_history(historical_option_data, call_spread_strategy)
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put_spread_history = get_spread_history(historical_option_data, put_spread_strategy)
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entry_time = call_spread_strategy.trade_entry_time
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if call_spread_history is None or put_spread_history is None:
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# This can happen when the market closes early for the day.
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logging.warn('No spread history found in %s for %s', historical_data_file, entry_time)
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return None
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current_date = call_spread_history.iloc[0].name[:10]
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call_spread_entry = call_spread_history.loc[current_date + ' ' + entry_time]
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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)
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put_spread_entry = put_spread_history.loc[current_date + ' ' + entry_time]
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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)
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# Calculate entry slippage.
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if original_call_spread_price > 0.05:
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original_call_spread_price = original_call_spread_price - (original_call_spread_price % 0.05)
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logging.info('Original Call Spread Price: %s', original_call_spread_price)
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if original_put_spread_price > 0.05:
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original_put_spread_price = original_put_spread_price - (original_put_spread_price % 0.05)
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logging.info('Original Put Spread Price: %s', original_put_spread_price)
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premium_received = original_call_spread_price + original_put_spread_price
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call_spread_details = {
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"Legs": [{"Action": "SELL", "Strike": call_spread_entry['strike_short_strike'], "Type": "CALL"},
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{"Action": "BUY", "Strike": call_spread_entry['strike_long_strike'], "Type": "CALL"}],
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"Open": original_call_spread_price,
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"High": float('-inf'),
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"Low": float('inf'),
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"Close": 0.0
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}
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put_spread_details = {
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"Legs": [{"Action": "SELL", "Strike": put_spread_entry['strike_short_strike'], "Type": "PUT"},
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{"Action": "BUY", "Strike": put_spread_entry['strike_long_strike'], "Type": "PUT"}],
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"Open": original_put_spread_price,
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"High": float('-inf'),
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"Low": float('inf'),
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"Close": 0.0
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}
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trades_entered = False
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call_spread_stopped_out = False
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put_spread_stopped_out = False
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max_profit = 0.0
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max_drawdown = 0.0
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exit_time = '16:00:00'
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current_call_spread_price = original_call_spread_price
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current_put_spread_price = original_put_spread_price
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for i in range(len(call_spread_history)):
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call_spread = call_spread_history.iloc[i]
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put_spread = put_spread_history.iloc[i]
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if call_spread.name.endswith(entry_time):
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trades_entered = True
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continue
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if not trades_entered:
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continue
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if call_spread.name.endswith('16:05:00') or call_spread.name.endswith('16:10:00') or call_spread.name.endswith('16:15:00'):
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continue
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if call_spread['high_short_strike'] > call_spread['high_long_strike']:
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current_call_spread_price = call_spread['high_short_strike'] - call_spread['high_long_strike']
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else:
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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)
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if put_spread['high_short_strike'] > put_spread['high_long_strike']:
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current_put_spread_price = put_spread['high_short_strike'] - put_spread['high_long_strike']
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else:
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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)
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call_spread_details['High'] = max(call_spread_details['High'], current_call_spread_price)
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call_spread_details['Low'] = min(call_spread_details['Low'], current_call_spread_price)
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put_spread_details['High'] = max(put_spread_details['High'], current_put_spread_price)
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put_spread_details['Low'] = min(put_spread_details['Low'], current_put_spread_price)
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if not call_spread_stopped_out:
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if current_call_spread_price >= ((call_spread_strategy.stop_loss_multiple + 1) * original_call_spread_price):
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premium_received -= original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1)
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call_spread_details['Close'] = original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1) + 0.10
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# Calculate exit slippage.
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premium_received -= 0.10 # TODO: Make this configurable.
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call_spread_stopped_out = True
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exit_time = call_spread.name[-8:]
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logging.info('Call Spread Stopped Out')
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if not put_spread_stopped_out:
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if current_put_spread_price >= ((put_spread_strategy.stop_loss_multiple + 1) * original_put_spread_price):
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premium_received -= original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1)
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premium_received -= 0.10 # TODO: Make this configurable.
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put_spread_details['Close'] = original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1) + 0.10
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put_spread_stopped_out = True
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exit_time = call_spread.name[-8:]
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logging.info('Put Spread Stopped Out')
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if not (call_spread_stopped_out and put_spread_stopped_out):
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if current_call_spread_price > current_put_spread_price:
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if put_spread['low_short_strike'] > put_spread['low_long_strike']:
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current_put_spread_price = put_spread['low_short_strike'] - put_spread['low_long_strike']
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else:
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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)
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else:
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if call_spread['low_short_strike'] > call_spread['low_long_strike']:
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current_call_spread_price = call_spread['low_short_strike'] - call_spread['low_long_strike']
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else:
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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)
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if call_spread_stopped_out:
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current_call_spread_price = original_call_spread_price * (call_spread_strategy.stop_loss_multiple + 1)
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if put_spread['high_short_strike'] > put_spread['high_long_strike']:
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current_put_spread_price = put_spread['high_short_strike'] - put_spread['high_long_strike']
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else:
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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)
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if put_spread_stopped_out:
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current_put_spread_price = original_put_spread_price * (put_spread_strategy.stop_loss_multiple + 1)
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if call_spread['high_short_strike'] > call_spread['high_long_strike']:
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current_call_spread_price = call_spread['high_short_strike'] - call_spread['high_long_strike']
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else:
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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)
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current_profit = (original_call_spread_price - current_call_spread_price) + (original_put_spread_price - current_put_spread_price)
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current_profit_dollars = current_profit * call_spread_strategy.number_of_contracts * 100
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if current_profit_dollars > max_profit:
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max_profit = current_profit_dollars
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if current_profit_dollars < max_drawdown:
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max_drawdown = current_profit_dollars
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if not call_spread_stopped_out and current_call_spread_price > 0.05:
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premium_received -= current_call_spread_price
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call_spread_details['Close'] = current_call_spread_price
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if not put_spread_stopped_out and current_put_spread_price > 0.05:
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premium_received -= current_put_spread_price
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put_spread_details['Close'] = current_put_spread_price
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number_of_contracts = call_spread_strategy.number_of_contracts
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stop_out_fees = 0.0 # It costs money to get stopped out.
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if call_spread_stopped_out:
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stop_out_fees += (2 * FEES_PER_CONTRACT * number_of_contracts)
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if put_spread_stopped_out:
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stop_out_fees += (2 * FEES_PER_CONTRACT * number_of_contracts)
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fees = 4 * FEES_PER_CONTRACT * number_of_contracts
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commissions = 4 * number_of_contracts
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premium_received = (premium_received * number_of_contracts * 100) - (fees + commissions) - stop_out_fees
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dates.append(current_date)
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max_drawdowns.append(max_drawdown)
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max_profits.append(max_profit)
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wins.append(True if premium_received > 0 else False)
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exit_times.append(exit_time)
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result = BacktestResult(
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date=current_date,
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entry_time=f'{current_date} {entry_time}',
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exit_time=f'{current_date} {exit_time}',
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spreads=[call_spread_details, put_spread_details],
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trade_entered=True,
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trade_pnl=premium_received,
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profit=0.0, # TODO: Calculated elsewhere. Clean this up.
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credit=original_call_spread_price + original_put_spread_price,
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mfe=max_profit,
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mae=max_drawdown
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)
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logging.info('Premium Received: %f', premium_received)
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return result
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def backtest_iron_condor(
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backtest_name: str,
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call_spread_strategy: OptionSpreadStrategy,
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put_spread_strategy: OptionSpreadStrategy,
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start_date: datetime,
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end_date: datetime,
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filters: List[BacktestFilter] = []
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) -> pd.DataFrame:
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# Setting dates to midnight to ensure all the data between them is included.
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start_date = datetime.combine(start_date, time())
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end_date = datetime.combine(end_date, time())
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futures = []
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with ProcessPoolExecutor(max_workers = 10) as executor:
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for year in range(start_date.year, end_date.year + 1):
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year_directory = os.path.join(OPTION_DATA_DIRECTORY, str(year))
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for file in os.listdir(year_directory):
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historical_data_file = os.path.join(year_directory, file)
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if os.path.isdir(historical_data_file) or not file.endswith('.csv'):
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continue
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# Assuming file format 'YYYY-MM-DD.csv'.
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current_date = datetime.strptime(os.path.splitext(file)[0], '%Y-%m-%d')
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if current_date < start_date or current_date > end_date:
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continue
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logging.info('Processing File: %s', historical_data_file)
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if (not filters) or all(filter.trade_allowed(current_date) for filter in filters):
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future = executor.submit(
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_backtest_iron_condor,
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historical_data_file,
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call_spread_strategy,
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put_spread_strategy
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)
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futures.append(future)
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backtest_results = []
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total_premium_received = 0.0
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for future in futures:
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backtest_result = future.result()
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if backtest_result:
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total_premium_received += backtest_result.trade_pnl
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backtest_result.profit = total_premium_received
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backtest_results.append(backtest_result)
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# TODO: Either look up the symbol in the historical option data or have the client provide it.
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backtest_results = pd.DataFrame([{
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'Date': result.date,
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'Symbol': 'SPX',
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'Strategy': backtest_name,
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'Entry Time': result.entry_time,
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'Exit Time': result.exit_time,
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'Spreads': result.spreads,
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'Profit': result.trade_pnl,
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'Cumulative Profit': result.profit
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} for result in backtest_results])
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return backtest_results |