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Show new metrics in backtesting

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This commit is contained in:
Matthias 2022-12-25 21:29:37 +01:00
parent 89c7c2fec6
commit 7a5439321c
2 changed files with 16 additions and 8 deletions
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12
freqtrade/data/metrics.py
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@ -287,8 +287,8 @@ def calculate_sharpe(trades: pd.DataFrame,
return sharp_ratio
def calculate_calmar(trades: pd.DataFrame,
min_date: datetime, max_date: datetime) -> float:
def calculate_calmar(trades: pd.DataFrame, min_date: datetime, max_date: datetime,
starting_balance: float) -> float:
"""
Calculate calmar
:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
@ -297,17 +297,17 @@ def calculate_calmar(trades: pd.DataFrame,
if (len(trades) == 0) or (min_date is None) or (max_date is None) or (min_date == max_date):
return 0
total_profit = trades["profit_ratio"]
days_period = (max_date - min_date).days
total_profit = trades['profit_abs'].sum() / starting_balance
days_period = max(1, (max_date - min_date).days)
# adding slippage of 0.1% per trade
# total_profit = total_profit - 0.0005
expected_returns_mean = total_profit.sum() / days_period * 100
expected_returns_mean = total_profit / days_period * 100
# calculate max drawdown
try:
_, _, _, _, _, max_drawdown = calculate_max_drawdown(
trades, value_col="profit_abs"
trades, value_col="profit_abs", starting_balance=starting_balance
)
except ValueError:
max_drawdown = 0

12
freqtrade/optimize/optimize_reports.py
View File

@ -9,8 +9,9 @@ from tabulate import tabulate
from freqtrade.constants import (DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN, UNLIMITED_STAKE_AMOUNT,
Config)
from freqtrade.data.metrics import (calculate_cagr, calculate_csum, calculate_market_change,
calculate_max_drawdown)
from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_csum,
calculate_expectancy, calculate_market_change,
calculate_max_drawdown, calculate_sharpe, calculate_sortino)
from freqtrade.misc import decimals_per_coin, file_dump_joblib, file_dump_json, round_coin_value
from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
@ -448,6 +449,10 @@ def generate_strategy_stats(pairlist: List[str],
'profit_total_long_abs': results.loc[~results['is_short'], 'profit_abs'].sum(),
'profit_total_short_abs': results.loc[results['is_short'], 'profit_abs'].sum(),
'cagr': calculate_cagr(backtest_days, start_balance, content['final_balance']),
'expectancy': calculate_expectancy(results),
'sortino': calculate_sortino(results, min_date, max_date),
'sharpe': calculate_sharpe(results, min_date, max_date),
'calmar': calculate_calmar(results, min_date, max_date, start_balance),
'profit_factor': profit_factor,
'backtest_start': min_date.strftime(DATETIME_PRINT_FORMAT),
'backtest_start_ts': int(min_date.timestamp() * 1000),
@ -785,6 +790,9 @@ def text_table_add_metrics(strat_results: Dict) -> str:
strat_results['stake_currency'])),
('Total profit %', f"{strat_results['profit_total']:.2%}"),
('CAGR %', f"{strat_results['cagr']:.2%}" if 'cagr' in strat_results else 'N/A'),
('Sortino', f"{strat_results['sortino']:.2f}" if 'sortino' in strat_results else 'N/A'),
('Sharpe', f"{strat_results['sharpe']:.2f}" if 'sharpe' in strat_results else 'N/A'),
('Calmar', f"{strat_results['calmar']:.2f}" if 'calmar' in strat_results else 'N/A'),
('Profit factor', f'{strat_results["profit_factor"]:.2f}' if 'profit_factor'
in strat_results else 'N/A'),
('Trades per day', strat_results['trades_per_day']),