Show new metrics in backtesting
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@ -287,8 +287,8 @@ def calculate_sharpe(trades: pd.DataFrame,
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return sharp_ratio
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return sharp_ratio
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def calculate_calmar(trades: pd.DataFrame,
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def calculate_calmar(trades: pd.DataFrame, min_date: datetime, max_date: datetime,
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min_date: datetime, max_date: datetime) -> float:
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starting_balance: float) -> float:
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"""
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"""
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Calculate calmar
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Calculate calmar
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:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
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:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
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@ -297,17 +297,17 @@ def calculate_calmar(trades: pd.DataFrame,
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if (len(trades) == 0) or (min_date is None) or (max_date is None) or (min_date == max_date):
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if (len(trades) == 0) or (min_date is None) or (max_date is None) or (min_date == max_date):
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return 0
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return 0
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total_profit = trades["profit_ratio"]
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total_profit = trades['profit_abs'].sum() / starting_balance
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days_period = (max_date - min_date).days
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days_period = max(1, (max_date - min_date).days)
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# adding slippage of 0.1% per trade
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# adding slippage of 0.1% per trade
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# total_profit = total_profit - 0.0005
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# total_profit = total_profit - 0.0005
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expected_returns_mean = total_profit.sum() / days_period * 100
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expected_returns_mean = total_profit / days_period * 100
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# calculate max drawdown
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# calculate max drawdown
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try:
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try:
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_, _, _, _, _, max_drawdown = calculate_max_drawdown(
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_, _, _, _, _, max_drawdown = calculate_max_drawdown(
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trades, value_col="profit_abs"
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trades, value_col="profit_abs", starting_balance=starting_balance
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)
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)
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except ValueError:
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except ValueError:
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max_drawdown = 0
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max_drawdown = 0
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@ -9,8 +9,9 @@ from tabulate import tabulate
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from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT,
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from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT,
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Config)
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Config)
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from freqtrade.data.metrics import (calculate_cagr, calculate_csum, calculate_market_change,
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from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_csum,
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calculate_max_drawdown)
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calculate_expectancy, calculate_market_change,
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calculate_max_drawdown, calculate_sharpe, calculate_sortino)
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from freqtrade.misc import decimals_per_coin, file_dump_joblib, file_dump_json, round_coin_value
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from freqtrade.misc import decimals_per_coin, file_dump_joblib, file_dump_json, round_coin_value
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from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
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from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
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@ -448,6 +449,10 @@ def generate_strategy_stats(pairlist: List[str],
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'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
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'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
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'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
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'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
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'cagr': calculate_cagr(backtest_days, start_balance, content['final_balance']),
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'cagr': calculate_cagr(backtest_days, start_balance, content['final_balance']),
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'expectancy': calculate_expectancy(results),
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'sortino': calculate_sortino(results, min_date, max_date),
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'sharpe': calculate_sharpe(results, min_date, max_date),
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'calmar': calculate_calmar(results, min_date, max_date, start_balance),
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'profit_factor': profit_factor,
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'profit_factor': profit_factor,
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'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
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'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
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'backtest_start_ts': int(min_date.timestamp() * 1000),
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'backtest_start_ts': int(min_date.timestamp() * 1000),
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@ -785,6 +790,9 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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strat_results['stake_currency'])),
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strat_results['stake_currency'])),
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('Total profit %', f"{strat_results['profit_total']:.2%}"),
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('Total profit %', f"{strat_results['profit_total']:.2%}"),
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('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
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('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
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('Sortino', f"{strat_results['sortino']:.2f}" if 'sortino' in strat_results else 'N/A'),
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('Sharpe', f"{strat_results['sharpe']:.2f}" if 'sharpe' in strat_results else 'N/A'),
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('Calmar', f"{strat_results['calmar']:.2f}" if 'calmar' in strat_results else 'N/A'),
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('Profit factor', f'{strat_results["profit_factor"]:.2f}' if 'profit_factor'
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('Profit factor', f'{strat_results["profit_factor"]:.2f}' if 'profit_factor'
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in strat_results else 'N/A'),
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in strat_results else 'N/A'),
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('Trades per day', strat_results['trades_per_day']),
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('Trades per day', strat_results['trades_per_day']),
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