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Few changes to backtesting reports

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* Added more stats for SUMMARY METRICS
* Removed Cum Profit % column, as it is very confusing
* Fixed Total % column calculation
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citizen3942 2021-03-02 16:25:50 +02:00 committed by GitHub
parent 18f61141c2
commit c60274ec95
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1 changed files with 80 additions and 36 deletions
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116
freqtrade/optimize/optimize_reports.py
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@ -9,9 +9,8 @@ from pandas import DataFrame
from tabulate import tabulate from tabulate import tabulate
from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
from freqtrade.data.btanalysis import (calculate_csum, calculate_market_change, from freqtrade.data.btanalysis import calculate_market_change, calculate_max_drawdown, calculate_csum
calculate_max_drawdown) from freqtrade.misc import file_dump_json, round_coin_value, decimals_per_coin
from freqtrade.misc import decimals_per_coin, file_dump_json, round_coin_value
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -39,38 +38,37 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
file_dump_json(latest_filename, {'latest_backtest': str(filename.name)}) file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
def _get_line_floatfmt(stake_currency: str) -> List[str]: def _get_line_floatfmt() -> List[str]:
""" """
Generate floatformat (goes in line with _generate_result_line()) Generate floatformat (goes in line with _generate_result_line())
""" """
return ['s', 'd', '.2f', '.2f', f'.{decimals_per_coin(stake_currency)}f', return ['s', 'd', '.2f', '.2f', '.8f', '.2f', 'd', 'd', 'd', 'd']
'.2f', 'd', 'd', 'd', 'd']
def _get_line_header(first_column: str, stake_currency: str) -> List[str]: def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
""" """
Generate header lines (goes in line with _generate_result_line()) Generate header lines (goes in line with _generate_result_line())
""" """
return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %', return [first_column, 'Buys', 'Avg Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration', f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Wins', 'Draws', 'Losses'] 'Wins', 'Draws', 'Losses']
def _generate_result_line(result: DataFrame, max_open_trades: int, first_column: str) -> Dict: def _generate_result_line(result: DataFrame, starting_balance: float, first_column: str) -> Dict:
""" """
Generate one result dict, with "first_column" as key. Generate one result dict, with "first_column" as key.
""" """
profit_sum = result['profit_ratio'].sum() profit_sum = result['profit_ratio'].sum()
profit_total = profit_sum / max_open_trades profit_total = result['profit_abs'].sum() / starting_balance
return { return {
'key': first_column, 'key': first_column,
'trades': len(result), 'trades': len(result),
'profit_mean': result['profit_ratio'].mean() if len(result) > 0 else 0.0, 'profit_mean': result['profit_ratio'].mean() if len(result) > 0 else 0.0,
'profit_mean_pct': result['profit_ratio'].mean() * 100.0 if len(result) > 0 else 0.0, 'profit_mean_pct': result['profit_ratio'].mean() * 100.0 if len(result) > 0 else 0.0, # Average Profit %
'profit_sum': profit_sum, 'profit_sum': profit_sum,
'profit_sum_pct': round(profit_sum * 100.0, 2), 'profit_sum_pct': round(profit_sum * 100.0, 2), # Cum Profit % -> Profit % Per Stake
'profit_total_abs': result['profit_abs'].sum(), 'profit_total_abs': result['profit_abs'].sum(), # Total Profit [stake_currency]
'profit_total': profit_total, 'profit_total': profit_total,
'profit_total_pct': round(profit_total * 100.0, 2), 'profit_total_pct': round(profit_total * 100.0, 2),
'duration_avg': str(timedelta( 'duration_avg': str(timedelta(
@ -88,13 +86,13 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column:
} }
def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_trades: int, def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_balance: int,
results: DataFrame, skip_nan: bool = False) -> List[Dict]: results: DataFrame, skip_nan: bool = False) -> List[Dict]:
""" """
Generates and returns a list for the given backtest data and the results dataframe Generates and returns a list for the given backtest data and the results dataframe
:param data: Dict of <pair: dataframe> containing data that was used during backtesting. :param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param stake_currency: stake-currency - used to correctly name headers :param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades :param starting_balance: Starting balance
:param results: Dataframe containing the backtest results :param results: Dataframe containing the backtest results
:param skip_nan: Print "left open" open trades :param skip_nan: Print "left open" open trades
:return: List of Dicts containing the metrics per pair :return: List of Dicts containing the metrics per pair
@ -107,10 +105,10 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_t
if skip_nan and result['profit_abs'].isnull().all(): if skip_nan and result['profit_abs'].isnull().all():
continue continue
tabular_data.append(_generate_result_line(result, max_open_trades, pair)) tabular_data.append(_generate_result_line(result, starting_balance, pair))
# Append Total # Append Total
tabular_data.append(_generate_result_line(results, max_open_trades, 'TOTAL')) tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL'))
return tabular_data return tabular_data
@ -246,15 +244,16 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
continue continue
config = content['config'] config = content['config']
max_open_trades = min(config['max_open_trades'], len(btdata.keys())) max_open_trades = min(config['max_open_trades'], len(btdata.keys()))
starting_balance = config['dry_run_wallet']
stake_currency = config['stake_currency'] stake_currency = config['stake_currency']
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency, pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
max_open_trades=max_open_trades, starting_balance=starting_balance,
results=results, skip_nan=False) results=results, skip_nan=False)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades, sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results) results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency, left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
max_open_trades=max_open_trades, starting_balance=starting_balance,
results=results.loc[results['is_open']], results=results.loc[results['is_open']],
skip_nan=True) skip_nan=True)
daily_stats = generate_daily_stats(results) daily_stats = generate_daily_stats(results)
@ -265,6 +264,13 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
results['open_timestamp'] = results['open_date'].astype(int64) // 1e6 results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
results['close_timestamp'] = results['close_date'].astype(int64) // 1e6 results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
max_date_real = Arrow.fromtimestamp(max(results['close_timestamp']))
ended_early = False #
if (max_date_real < max_date):
max_date = max_date_real
ended_early = True
backtest_days = (max_date - min_date).days backtest_days = (max_date - min_date).days
strat_stats = { strat_stats = {
'trades': results.to_dict(orient='records'), 'trades': results.to_dict(orient='records'),
@ -275,13 +281,16 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'sell_reason_summary': sell_reason_stats, 'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results, 'left_open_trades': left_open_results,
'total_trades': len(results), 'total_trades': len(results),
'total_volume': float(results['stake_amount'].sum()),
'avg_stake_amount': results['stake_amount'].mean(),
'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0, 'profit_mean': results['profit_ratio'].mean() if len(results) > 0 else 0,
'profit_total': results['profit_ratio'].sum() / max_open_trades, 'profit_total': results['profit_abs'].sum() / starting_balance,
'profit_total_abs': results['profit_abs'].sum(), 'profit_total_abs': results['profit_abs'].sum(),
'backtest_start': min_date.datetime, 'backtest_start': min_date.datetime,
'backtest_start_ts': min_date.int_timestamp * 1000, 'backtest_start_ts': min_date.int_timestamp * 1000,
'backtest_end': max_date.datetime, 'backtest_end': max_date.datetime,
'backtest_end_ts': max_date.int_timestamp * 1000, 'backtest_end_ts': max_date.int_timestamp * 1000,
'early_end': '* ' if ended_early else '',
'backtest_days': backtest_days, 'backtest_days': backtest_days,
'backtest_run_start_ts': content['backtest_start_time'], 'backtest_run_start_ts': content['backtest_start_time'],
@ -292,6 +301,10 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'pairlist': list(btdata.keys()), 'pairlist': list(btdata.keys()),
'stake_amount': config['stake_amount'], 'stake_amount': config['stake_amount'],
'stake_currency': config['stake_currency'], 'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'starting_balance': starting_balance,
'dry_run_wallet': starting_balance,
'final_balance': starting_balance + results['profit_abs'].sum(),
'max_open_trades': max_open_trades, 'max_open_trades': max_open_trades,
'max_open_trades_setting': (config['max_open_trades'] 'max_open_trades_setting': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1), if config['max_open_trades'] != float('inf') else -1),
@ -316,17 +329,23 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
result['strategy'][strategy] = strat_stats result['strategy'][strategy] = strat_stats
try: try:
max_drawdown, drawdown_start, drawdown_end = calculate_max_drawdown( max_drawdown, _, _, _, _ = calculate_max_drawdown(
results, value_col='profit_ratio') results, value_col='profit_ratio')
drawdown_abs, drawdown_start, drawdown_end, high_val, low_val = calculate_max_drawdown(
results, value_col='profit_abs')
strat_stats.update({ strat_stats.update({
'max_drawdown': max_drawdown, 'max_drawdown': max_drawdown,
'max_drawdown_abs': drawdown_abs,
'drawdown_start': drawdown_start, 'drawdown_start': drawdown_start,
'drawdown_start_ts': drawdown_start.timestamp() * 1000, 'drawdown_start_ts': drawdown_start.timestamp() * 1000,
'drawdown_end': drawdown_end, 'drawdown_end': drawdown_end,
'drawdown_end_ts': drawdown_end.timestamp() * 1000, 'drawdown_end_ts': drawdown_end.timestamp() * 1000,
'max_drawdown_low': low_val,
'max_drawdown_high': high_val,
}) })
csum_min, csum_max = calculate_csum(results) csum_min, csum_max = calculate_csum(results, starting_balance)
strat_stats.update({ strat_stats.update({
'csum_min': csum_min, 'csum_min': csum_min,
'csum_max': csum_max 'csum_max': csum_max
@ -335,6 +354,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
except ValueError: except ValueError:
strat_stats.update({ strat_stats.update({
'max_drawdown': 0.0, 'max_drawdown': 0.0,
'max_drawdown_abs': 0.0,
'max_drawdown_low': 0.0,
'max_drawdown_high': 0.0,
'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc), 'drawdown_start': datetime(1970, 1, 1, tzinfo=timezone.utc),
'drawdown_start_ts': 0, 'drawdown_start_ts': 0,
'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc), 'drawdown_end': datetime(1970, 1, 1, tzinfo=timezone.utc),
@ -363,9 +385,9 @@ def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: st
""" """
headers = _get_line_header('Pair', stake_currency) headers = _get_line_header('Pair', stake_currency)
floatfmt = _get_line_floatfmt(stake_currency) floatfmt = _get_line_floatfmt()
output = [[ output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['key'], t['trades'], t['profit_mean_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in pair_results] ] for t in pair_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that # Ignore type as floatfmt does allow tuples but mypy does not know that
@ -387,16 +409,13 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren
'Draws', 'Draws',
'Losses', 'Losses',
'Avg Profit %', 'Avg Profit %',
'Cum Profit %',
f'Tot Profit {stake_currency}', f'Tot Profit {stake_currency}',
'Tot Profit %', 'Tot Profit %',
] ]
output = [[ output = [[
t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'], t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'],
t['profit_mean_pct'], t['profit_sum_pct'], t['profit_mean_pct'], t['profit_total_abs'], t['profit_total_pct'],
round_coin_value(t['profit_total_abs'], stake_currency, False),
t['profit_total_pct'],
] for t in sell_reason_stats] ] for t in sell_reason_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right") return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
@ -409,11 +428,11 @@ def text_table_strategy(strategy_results, stake_currency: str) -> str:
:param all_results: Dict of <Strategyname: DataFrame> containing results for all strategies :param all_results: Dict of <Strategyname: DataFrame> containing results for all strategies
:return: pretty printed table with tabulate as string :return: pretty printed table with tabulate as string
""" """
floatfmt = _get_line_floatfmt(stake_currency) floatfmt = _get_line_floatfmt()
headers = _get_line_header('Strategy', stake_currency) headers = _get_line_header('Strategy', stake_currency)
output = [[ output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['key'], t['trades'], t['profit_mean_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses'] t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in strategy_results] ] for t in strategy_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that # Ignore type as floatfmt does allow tuples but mypy does not know that
@ -426,13 +445,26 @@ def text_table_add_metrics(strat_results: Dict) -> str:
best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio']) best_trade = max(strat_results['trades'], key=lambda x: x['profit_ratio'])
worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio']) worst_trade = min(strat_results['trades'], key=lambda x: x['profit_ratio'])
metrics = [ metrics = [
('Strategy', strat_results['strategy_name']),
('', ''), # Empty line to improve readability
('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)), ('Backtesting from', strat_results['backtest_start'].strftime(DATETIME_PRINT_FORMAT)),
('Backtesting to', strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)), (f"{strat_results['early_end']}Backtesting to", strat_results['backtest_end'].strftime(DATETIME_PRINT_FORMAT)),
('Max open trades', strat_results['max_open_trades']), ('Max open trades', strat_results['max_open_trades']),
('', ''), # Empty line to improve readability ('', ''), # Empty line to improve readability
('Total trades', strat_results['total_trades']), ('Total trades', strat_results['total_trades']),
('Total Profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"), ('Starting balance', round_coin_value(strat_results['starting_balance'],
strat_results['stake_currency'])),
('Final balance', round_coin_value(strat_results['final_balance'],
strat_results['stake_currency'])),
('Absolute profit ', round_coin_value(strat_results['profit_total_abs'],
strat_results['stake_currency'])),
('Total profit %', f"{round(strat_results['profit_total'] * 100, 2)}%"),
('Trades per day', strat_results['trades_per_day']), ('Trades per day', strat_results['trades_per_day']),
('Avg. stake amount', round_coin_value(strat_results['avg_stake_amount'],
strat_results['stake_currency'])),
('Total trade volume', round_coin_value(strat_results['total_volume'],
strat_results['stake_currency'])),
('', ''), # Empty line to improve readability ('', ''), # Empty line to improve readability
('Best Pair', f"{strat_results['best_pair']['key']} " ('Best Pair', f"{strat_results['best_pair']['key']} "
f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"), f"{round(strat_results['best_pair']['profit_sum_pct'], 2)}%"),
@ -450,12 +482,18 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"), ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('', ''), # Empty line to improve readability ('', ''), # Empty line to improve readability
('Abs Profit Min', round_coin_value(strat_results['csum_min'], ('Min balance', round_coin_value(strat_results['csum_min'],
strat_results['stake_currency'])), strat_results['stake_currency'])),
('Abs Profit Max', round_coin_value(strat_results['csum_max'], ('Max balance', round_coin_value(strat_results['csum_max'],
strat_results['stake_currency'])), strat_results['stake_currency'])),
('Max Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"), ('Drawdown', f"{round(strat_results['max_drawdown'] * 100, 2)}%"),
('Drawdown', round_coin_value(strat_results['max_drawdown_abs'],
strat_results['stake_currency'])),
('Drawdown high', round_coin_value(strat_results['max_drawdown_high'],
strat_results['stake_currency'])),
('Drawdown low', round_coin_value(strat_results['max_drawdown_low'],
strat_results['stake_currency'])),
('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)), ('Drawdown Start', strat_results['drawdown_start'].strftime(DATETIME_PRINT_FORMAT)),
('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)), ('Drawdown End', strat_results['drawdown_end'].strftime(DATETIME_PRINT_FORMAT)),
('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"), ('Market change', f"{round(strat_results['market_change'] * 100, 2)}%"),
@ -481,21 +519,27 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'], table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
stake_currency=stake_currency) stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0: if isinstance(table, str) and len(table) > 0:
print('')
print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '=')) print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table) print(table)
table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency) table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0: if isinstance(table, str) and len(table) > 0:
print('')
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '=')) print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table) print(table)
table = text_table_add_metrics(results) table = text_table_add_metrics(results)
if isinstance(table, str) and len(table) > 0: if isinstance(table, str) and len(table) > 0:
print('')
print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '=')) print(' SUMMARY METRICS '.center(len(table.splitlines()[0]), '='))
print(table) print(table)
if isinstance(table, str) and len(table) > 0: if isinstance(table, str) and len(table) > 0:
print('=' * len(table.splitlines()[0])) print('=' * len(table.splitlines()[0]))
if(results['early_end']=='* '):
print('* - Backtest ended at an earlier time.')
print() print()
if len(backtest_stats['strategy']) > 1: if len(backtest_stats['strategy']) > 1: