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add backtesting results abs profit min/abs profit max, to get a better view if a strategy has a enough money to succeed

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This commit is contained in:
Florian Reitmeir 2020-12-24 22:17:24 +01:00 committed by Matthias
parent 10a11bda34
commit 5c263c7ffd
2 changed files with 35 additions and 1 deletions
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18
freqtrade/data/btanalysis.py
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@ -383,3 +383,21 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
low_date = profit_results.loc[idxmin, date_col]
return abs(min(max_drawdown_df['drawdown'])), high_date, low_date
def calculate_csum(trades: pd.DataFrame) -> Tuple[float, float]:
"""
Calculate min/max cumsum of trades, to show if the wallet/stake amount ratio is sane
:param trades: DataFrame containing trades (requires columns close_date and profit_percent)
:return: Tuple (float, float) with cumsum of profit_abs
:raise: ValueError if trade-dataframe was found empty.
"""
if len(trades) == 0:
raise ValueError("Trade dataframe empty.")
csum_df = pd.DataFrame()
csum_df['sum'] = trades['profit_abs'].cumsum()
csum_min = csum_df['sum'].min()
csum_max = csum_df['sum'].max()
return csum_min, csum_max

18
freqtrade/optimize/optimize_reports.py
View File

@ -9,7 +9,8 @@ from pandas import DataFrame
from tabulate import tabulate
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.data.btanalysis import calculate_market_change, calculate_max_drawdown
from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change,
calculate_max_drawdown)
from freqtrade.misc import decimals_per_coin, file_dump_json, round_coin_value
@ -324,6 +325,13 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'drawdown_end': drawdown_end,
'drawdown_end_ts': drawdown_end.timestamp() * 1000,
})
csum_min, csum_max = calculate_csum(results)
strat_stats.update({
'csum_min': csum_min,
'csum_max': csum_max
})
except ValueError:
strat_stats.update({
'max_drawdown': 0.0,
@ -331,6 +339,8 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'drawdown_start_ts': 0,
'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
'drawdown_end_ts': 0,
'csum_min': 0,
'csum_max': 0
})
strategy_results = generate_strategy_metrics(all_results=all_results)
@ -439,6 +449,12 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('', ''), # Empty line to improve readability
('Abs Profit Min', round_coin_value(strat_results['csum_min'],
strat_results['stake_currency'])),
('Abs Profit Max', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])),
('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)),
('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)),