Merge branch 'develop' into feature_keyval_storage
This commit is contained in:
@@ -1058,6 +1058,7 @@ class Backtesting:
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# Close trade
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open_trade_count -= 1
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open_trades[pair].remove(t)
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LocalTrade.trades_open.remove(t)
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self.wallets.update()
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# 2. Process entries.
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@@ -1081,6 +1082,8 @@ class Backtesting:
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open_trade_count += 1
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# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
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open_trades[pair].append(trade)
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LocalTrade.add_bt_trade(trade)
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self.wallets.update()
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for trade in list(open_trades[pair]):
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# 3. Process entry orders.
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@@ -1088,7 +1091,6 @@ class Backtesting:
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if order and self._get_order_filled(order.price, row):
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order.close_bt_order(current_time, trade)
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trade.open_order_id = None
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LocalTrade.add_bt_trade(trade)
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self.wallets.update()
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# 4. Create exit orders (if any)
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@@ -1267,13 +1269,14 @@ class Backtesting:
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self.results['strategy_comparison'].extend(results['strategy_comparison'])
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else:
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self.results = results
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dt_appendix = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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if self.config.get('export', 'none') in ('trades', 'signals'):
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store_backtest_stats(self.config['exportfilename'], self.results)
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store_backtest_stats(self.config['exportfilename'], self.results, dt_appendix)
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if (self.config.get('export', 'none') == 'signals' and
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self.dataprovider.runmode == RunMode.BACKTEST):
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store_backtest_signal_candles(self.config['exportfilename'], self.processed_dfs)
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store_backtest_signal_candles(
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self.config['exportfilename'], self.processed_dfs, dt_appendix)
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# Results may be mixed up now. Sort them so they follow --strategy-list order.
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if 'strategy_list' in self.config and len(self.results) > 0:
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@@ -17,21 +17,21 @@ from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
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logger = logging.getLogger(__name__)
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def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> None:
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def store_backtest_stats(
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recordfilename: Path, stats: Dict[str, DataFrame], dtappendix: str) -> None:
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"""
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Stores backtest results
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:param recordfilename: Path object, which can either be a filename or a directory.
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Filenames will be appended with a timestamp right before the suffix
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while for directories, <directory>/backtest-result-<datetime>.json will be used as filename
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:param stats: Dataframe containing the backtesting statistics
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:param dtappendix: Datetime to use for the filename
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"""
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if recordfilename.is_dir():
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filename = (recordfilename /
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f'backtest-result-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.json')
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filename = (recordfilename / f'backtest-result-{dtappendix}.json')
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else:
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filename = Path.joinpath(
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recordfilename.parent,
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f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}'
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recordfilename.parent, f'{recordfilename.stem}-{dtappendix}'
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).with_suffix(recordfilename.suffix)
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# Store metadata separately.
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@@ -44,7 +44,8 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
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file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
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def store_backtest_signal_candles(recordfilename: Path, candles: Dict[str, Dict]) -> Path:
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def store_backtest_signal_candles(
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recordfilename: Path, candles: Dict[str, Dict], dtappendix: str) -> Path:
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"""
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Stores backtest trade signal candles
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:param recordfilename: Path object, which can either be a filename or a directory.
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@@ -52,14 +53,13 @@ def store_backtest_signal_candles(recordfilename: Path, candles: Dict[str, Dict]
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while for directories, <directory>/backtest-result-<datetime>_signals.pkl will be used
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as filename
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:param stats: Dict containing the backtesting signal candles
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:param dtappendix: Datetime to use for the filename
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"""
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if recordfilename.is_dir():
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filename = (recordfilename /
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f'backtest-result-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}_signals.pkl')
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filename = (recordfilename / f'backtest-result-{dtappendix}_signals.pkl')
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else:
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filename = Path.joinpath(
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recordfilename.parent,
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f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}_signals.pkl'
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recordfilename.parent, f'{recordfilename.stem}-{dtappendix}_signals.pkl'
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)
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file_dump_joblib(filename, candles)
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@@ -416,6 +416,9 @@ def generate_strategy_stats(pairlist: List[str],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
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key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
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winning_profit = results.loc[results['profit_abs'] > 0, 'profit_abs'].sum()
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losing_profit = results.loc[results['profit_abs'] < 0, 'profit_abs'].sum()
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profit_factor = winning_profit / abs(losing_profit) if losing_profit else 0.0
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backtest_days = (max_date - min_date).days or 1
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strat_stats = {
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@@ -443,6 +446,7 @@ 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_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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'profit_factor': profit_factor,
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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_end': max_date.strftime(DATETIME_PRINT_FORMAT),
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@@ -497,8 +501,10 @@ def generate_strategy_stats(pairlist: List[str],
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(drawdown_abs, drawdown_start, drawdown_end, high_val, low_val,
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max_drawdown) = calculate_max_drawdown(
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results, value_col='profit_abs', starting_balance=start_balance)
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# max_relative_drawdown = Underwater
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(_, _, _, _, _, max_relative_drawdown) = calculate_max_drawdown(
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results, value_col='profit_abs', starting_balance=start_balance, relative=True)
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strat_stats.update({
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'max_drawdown': max_drawdown_legacy, # Deprecated - do not use
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'max_drawdown_account': max_drawdown,
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@@ -777,6 +783,8 @@ def text_table_add_metrics(strat_results: Dict) -> str:
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strat_results['stake_currency'])),
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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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('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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('Trades per day', strat_results['trades_per_day']),
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('Avg. daily profit %',
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f"{(strat_results['profit_total'] / strat_results['backtest_days']):.2%}"),
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