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Merge branch 'develop' into feat/short

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This commit is contained in:
Matthias
2021-11-06 15:24:52 +01:00
parent c094ac5762 d99eaccb5a
commit ebc38159b8
57 changed files with 1202 additions and 197 deletions
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19
freqtrade/optimize/backtesting.py
View File

@@ -46,6 +46,7 @@ ELONG_IDX = 6 # Exit long
SHORT_IDX = 7
ESHORT_IDX = 8 # Exit short
ENTER_TAG_IDX = 9
EXIT_TAG_IDX = 10
class Backtesting:
@@ -257,7 +258,7 @@ class Backtesting:
# Every change to this headers list must evaluate further usages of the resulting tuple
# and eventually change the constants for indexes at the top
headers = ['date', 'open', 'high', 'low', 'close', 'enter_long', 'exit_long',
'enter_short', 'exit_short', 'enter_tag']
'enter_short', 'exit_short', 'enter_tag', 'exit_tag']
data: Dict = {}
self.progress.init_step(BacktestState.CONVERT, len(processed))
@@ -283,7 +284,7 @@ class Backtesting:
if col in df_analyzed.columns:
df_analyzed.loc[:, col] = df_analyzed.loc[:, col].shift(1)
else:
df_analyzed.loc[:, col] = 0 if col != 'enter_tag' else None
df_analyzed.loc[:, col] = 0 if col not in ('enter_tag', 'exit_tag') else None
# Update dataprovider cache
self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
@@ -326,7 +327,9 @@ class Backtesting:
# Worst case: price ticks tiny bit above open and dives down.
stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
assert stop_rate < sell_row[HIGH_IDX]
return stop_rate
# Limit lower-end to candle low to avoid sells below the low.
# This still remains "worst case" - but "worst realistic case".
return max(sell_row[LOW_IDX], stop_rate)
# Set close_rate to stoploss
return trade.stop_loss
@@ -375,6 +378,16 @@ class Backtesting:
if sell.sell_flag:
trade.close_date = sell_candle_time
trade.sell_reason = sell.sell_reason
# Checks and adds an exit tag, after checking that the length of the
# sell_row has the length for an exit tag column
if(
len(sell_row) > EXIT_TAG_IDX
and sell_row[EXIT_TAG_IDX] is not None
and len(sell_row[EXIT_TAG_IDX]) > 0
):
trade.sell_reason = sell_row[EXIT_TAG_IDX]
trade_dur = int((trade.close_date_utc - trade.open_date_utc).total_seconds() // 60)
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)

131
freqtrade/optimize/optimize_reports.py
View File

@@ -55,6 +55,15 @@ def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
'Win Draw Loss Win%']
def _get_line_header_sell(first_column: str, stake_currency: str) -> List[str]:
"""
Generate header lines (goes in line with _generate_result_line())
"""
return [first_column, 'Sells', 'Avg Profit %', 'Cum Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%']
def _generate_wins_draws_losses(wins, draws, losses):
if wins > 0 and losses == 0:
wl_ratio = '100'
@@ -127,6 +136,71 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, starting_b
return tabular_data
def generate_tag_metrics(tag_type: str,
starting_balance: int,
results: DataFrame,
skip_nan: bool = False) -> List[Dict]:
"""
Generates and returns a list of metrics for the given tag trades and the results dataframe
:param starting_balance: Starting balance
:param results: Dataframe containing the backtest results
:param skip_nan: Print "left open" open trades
:return: List of Dicts containing the metrics per pair
"""
tabular_data = []
if tag_type in results.columns:
for tag, count in results[tag_type].value_counts().iteritems():
result = results[results[tag_type] == tag]
if skip_nan and result['profit_abs'].isnull().all():
continue
tabular_data.append(_generate_tag_result_line(result, starting_balance, tag))
# Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True)
# Append Total
tabular_data.append(_generate_result_line(results, starting_balance, 'TOTAL'))
return tabular_data
else:
return []
def _generate_tag_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict:
"""
Generate one result dict, with "first_column" as key.
"""
profit_sum = result['profit_ratio'].sum()
# (end-capital - starting capital) / starting capital
profit_total = result['profit_abs'].sum() / starting_balance
return {
'key': first_column,
'trades': len(result),
'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_sum': profit_sum,
'profit_sum_pct': round(profit_sum * 100.0, 2),
'profit_total_abs': result['profit_abs'].sum(),
'profit_total': profit_total,
'profit_total_pct': round(profit_total * 100.0, 2),
'duration_avg': str(timedelta(
minutes=round(result['trade_duration'].mean()))
) if not result.empty else '0:00',
# 'duration_max': str(timedelta(
# minutes=round(result['trade_duration'].max()))
# ) if not result.empty else '0:00',
# 'duration_min': str(timedelta(
# minutes=round(result['trade_duration'].min()))
# ) if not result.empty else '0:00',
'wins': len(result[result['profit_abs'] > 0]),
'draws': len(result[result['profit_abs'] == 0]),
'losses': len(result[result['profit_abs'] < 0]),
}
def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
"""
Generate small table outlining Backtest results
@@ -347,6 +421,10 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
starting_balance=starting_balance,
results=results, skip_nan=False)
buy_tag_results = generate_tag_metrics("buy_tag", starting_balance=starting_balance,
results=results, skip_nan=False)
sell_reason_stats = generate_sell_reason_stats(max_open_trades=max_open_trades,
results=results)
left_open_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
@@ -370,6 +448,7 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
'best_pair': best_pair,
'worst_pair': worst_pair,
'results_per_pair': pair_results,
'results_per_buy_tag': buy_tag_results,
'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results,
# 'days_breakdown_stats': days_breakdown_stats,
@@ -542,6 +621,37 @@ def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_curren
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
if(tag_type == "buy_tag"):
headers = _get_line_header("TAG", stake_currency)
else:
headers = _get_line_header_sell("TAG", stake_currency)
floatfmt = _get_line_floatfmt(stake_currency)
output = [
[
t['key'] if t['key'] is not None and len(
t['key']) > 0 else "OTHER",
t['trades'],
t['profit_mean_pct'],
t['profit_sum_pct'],
t['profit_total_abs'],
t['profit_total_pct'],
t['duration_avg'],
_generate_wins_draws_losses(
t['wins'],
t['draws'],
t['losses'])] for t in tag_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_periodic_breakdown(days_breakdown_stats: List[Dict[str, Any]],
stake_currency: str, period: str) -> str:
"""
@@ -687,6 +797,16 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if results.get('results_per_buy_tag') is not None:
table = text_table_tags(
"buy_tag",
results['results_per_buy_tag'],
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
print(' BUY TAG STATS '.center(len(table.splitlines()[0]), '='))
print(table)
table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
stake_currency=stake_currency)
if isinstance(table, str) and len(table) > 0:
@@ -714,6 +834,7 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
if isinstance(table, str) and len(table) > 0:
print('=' * len(table.splitlines()[0]))
print()
@@ -735,3 +856,13 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
print(table)
print('=' * len(table.splitlines()[0]))
print('\nFor more details, please look at the detail tables above')
def show_sorted_pairlist(config: Dict, backtest_stats: Dict):
if config.get('backtest_show_pair_list', False):
for strategy, results in backtest_stats['strategy'].items():
print(f"Pairs for Strategy {strategy}: \n[")
for result in results['results_per_pair']:
if result["key"] != 'TOTAL':
print(f'"{result["key"]}", // {round(result["profit_mean_pct"], 2)}%')
print("]")