Update backtest result data frame to conform to table schema
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@ -8,7 +8,6 @@ from dotenv import load_dotenv
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from dataclasses import dataclass
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from datetime import datetime, timedelta
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from enum import Enum
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from os import getenv
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load_dotenv()
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@ -40,6 +39,8 @@ class OptionStrat:
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@dataclass
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class BacktestResult:
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date: str
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entry_time: str
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exit_time: str
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trade_entered: bool
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trade_pnl: float
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profit: float
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@ -55,10 +56,13 @@ wins = []
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exit_times = []
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def plot(backtest_results: pd.DataFrame, title: str):
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backtest_results.rename(columns = {'date' : 'Date', 'profit' : 'Profit'}, inplace = True)
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backtest_results.drop('Profit', axis = 1, inplace = True)
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backtest_results.rename(columns = {'Cumulative Profit' : 'Profit'}, inplace = True)
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# Exclude dates on which the market was closed from being plotted in order to prevent gaps on chart.
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backtest_date_range = pd.date_range(start="2016-01-01", end="2023-12-31").to_list()
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start_date = backtest_results['Date'].min()
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end_date = backtest_results['Date'].max()
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backtest_date_range = pd.date_range(start = start_date, end = end_date).to_list()
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backtest_date_range = set([timestamp.strftime('%Y-%m-%d') for timestamp in backtest_date_range])
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backtested_dates = set(backtest_results['Date'].to_list())
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excluded_dates = backtest_date_range - backtested_dates
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@ -66,9 +70,6 @@ def plot(backtest_results: pd.DataFrame, title: str):
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backtest_results['Color'] = np.where(backtest_results['Profit'] >= 0, 'limegreen', 'red')
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color_sequence = ['limegreen', 'red'] if backtest_results.iloc[0]['Profit'] >= 0 else ['red', 'limegreen']
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print('Backtest Results:')
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print(backtest_results)
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chart = px.bar(backtest_results, x='Date', y='Profit', title=title, color='Color', color_discrete_sequence=color_sequence, hover_data={'Color': False})
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chart.update_layout({
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'font_color': '#7a7c7d',
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@ -170,10 +171,12 @@ def _backtest_iron_condor(
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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 + ' ' + call_spread_strat.trade_entry_time]
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entry_time = call_spread_strat.trade_entry_time
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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 + ' ' + put_spread_strat.trade_entry_time]
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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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@ -195,13 +198,13 @@ def _backtest_iron_condor(
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max_profit = 0.0
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max_drawdown = 0.0
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exit_time = 160000
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exit_time = '16:00:00'
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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(call_spread_strat.trade_entry_time):
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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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@ -226,7 +229,8 @@ def _backtest_iron_condor(
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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 = int(call_spread.name[-8:].replace(':', ''))
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# exit_time = int(call_spread.name[-8:].replace(':', ''))
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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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@ -234,7 +238,8 @@ def _backtest_iron_condor(
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premium_received -= original_put_spread_price * (put_spread_strat.stop_loss_multiple + 1)
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premium_received -= 0.10 # TODO: Make this configurable.
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put_spread_stopped_out = True
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exit_time = int(call_spread.name[-8:].replace(':', ''))
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# exit_time = int(call_spread.name[-8:].replace(':', ''))
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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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@ -291,19 +296,22 @@ def _backtest_iron_condor(
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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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trade_entered = True,
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trade_pnl = premium_received,
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profit = 0.0,
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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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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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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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strategy_name: str,
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call_spread_strat: OptionStrat,
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put_spread_strat: OptionStrat,
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start_date: datetime,
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@ -317,7 +325,7 @@ def backtest_iron_condor(
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result_dates = []
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result_pnl = []
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results = []
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backtest_results = []
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start_year = start_date.year
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end_year = end_date.year
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@ -343,7 +351,7 @@ def backtest_iron_condor(
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backtest_result = _backtest_iron_condor(historical_option_data, call_spread_strat, put_spread_strat)
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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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results.append(backtest_result)
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backtest_results.append(backtest_result)
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if backtest_result.trade_entered:
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total_trades += 1
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@ -358,7 +366,17 @@ def backtest_iron_condor(
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result_dates.append(current_date)
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result_pnl.append(total_premium_received)
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backtest_results = pd.DataFrame([result.__dict__ for result in results])
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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': strategy_name,
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'Entry Time': result.entry_time,
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'Exit Time': result.exit_time,
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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
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def create_strategies(entry_time, number_of_contracts=1):
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@ -389,8 +407,15 @@ def create_strategies(entry_time, number_of_contracts=1):
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return call_spread_strat, put_spread_strat
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if __name__ == '__main__':
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start_date = datetime(2023, 1, 1)
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start_date = datetime(2024, 1, 12)
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end_date = datetime.now()
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call_spread_strat, put_spread_strat = create_strategies(entry_time = '10:05:00')
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backtest_result = backtest_iron_condor(call_spread_strat, put_spread_strat, start_date, end_date)
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backtest_result = backtest_iron_condor(
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f'Iron Condor @ {call_spread_strat.trade_entry_time}',
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call_spread_strat,
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put_spread_strat,
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start_date,
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end_date
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)
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print(backtest_result)
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plot(backtest_result, title = 'Iron Condor Backtest Results')
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