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Add support for collating and analysing rejected trades in backtest

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This commit is contained in:
froggleston
2022-12-05 15:34:31 +00:00
parent f28b314266
commit 5a4e99b413
9 changed files with 254 additions and 57 deletions
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64
freqtrade/optimize/backtesting.py
View File

@@ -29,6 +29,7 @@ from freqtrade.mixins import LoggingMixin
from freqtrade.optimize.backtest_caching import get_strategy_run_id
from freqtrade.optimize.bt_progress import BTProgress
from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
store_backtest_rejected_trades,
store_backtest_signal_candles,
store_backtest_stats)
from freqtrade.persistence import LocalTrade, Order, PairLocks, Trade
@@ -83,6 +84,8 @@ class Backtesting:
self.strategylist: List[IStrategy] = []
self.all_results: Dict[str, Dict] = {}
self.processed_dfs: Dict[str, Dict] = {}
self.rejected_dict: Dict[str, List] = {}
self.rejected_df: Dict[str, Dict] = {}
self._exchange_name = self.config['exchange']['name']
self.exchange = ExchangeResolver.load_exchange(
@@ -1048,6 +1051,18 @@ class Backtesting:
return None
return row
def _collate_rejected(self, pair, row):
"""
Temporarily store rejected trade information for downstream use in backtesting_analysis
"""
# It could be fun to enable hyperopt mode to write
# a loss function to reduce rejected signals
if (self.config.get('export', 'none') == 'signals' and
self.dataprovider.runmode == RunMode.BACKTEST):
if pair not in self.rejected_dict:
self.rejected_dict[pair] = []
self.rejected_dict[pair].append([row[DATE_IDX], row[ENTER_TAG_IDX]])
def backtest_loop(
self, row: Tuple, pair: str, current_time: datetime, end_date: datetime,
max_open_trades: int, open_trade_count_start: int, is_first: bool = True) -> int:
@@ -1073,20 +1088,22 @@ class Backtesting:
if (
(self._position_stacking or len(LocalTrade.bt_trades_open_pp[pair]) == 0)
and is_first
and self.trade_slot_available(max_open_trades, open_trade_count_start)
and current_time != end_date
and trade_dir is not None
and not PairLocks.is_pair_locked(pair, row[DATE_IDX], trade_dir)
):
trade = self._enter_trade(pair, row, trade_dir)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behavior - not sure if this is correct
# Prevents entering if the trade-slot was freed in this candle
open_trade_count_start += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
LocalTrade.add_bt_trade(trade)
self.wallets.update()
if (self.trade_slot_available(max_open_trades, open_trade_count_start)):
trade = self._enter_trade(pair, row, trade_dir)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behavior - not sure if this is correct
# Prevents entering if the trade-slot was freed in this candle
open_trade_count_start += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
LocalTrade.add_bt_trade(trade)
self.wallets.update()
else:
self._collate_rejected(pair, row)
for trade in list(LocalTrade.bt_trades_open_pp[pair]):
# 3. Process entry orders.
@@ -1266,6 +1283,7 @@ class Backtesting:
if (self.config.get('export', 'none') == 'signals' and
self.dataprovider.runmode == RunMode.BACKTEST):
self._generate_trade_signal_candles(preprocessed_tmp, results)
self._generate_rejected_trades(preprocessed_tmp, self.rejected_dict)
return min_date, max_date
@@ -1282,12 +1300,33 @@ class Backtesting:
for t, v in pairresults.open_date.items():
allinds = pairdf.loc[(pairdf['date'] < v)]
signal_inds = allinds.iloc[[-1]]
signal_candles_only_df = pd.concat([signal_candles_only_df, signal_inds])
signal_candles_only_df = pd.concat([
signal_candles_only_df.infer_objects(),
signal_inds.infer_objects()])
signal_candles_only[pair] = signal_candles_only_df
self.processed_dfs[self.strategy.get_strategy_name()] = signal_candles_only
def _generate_rejected_trades(self, preprocessed_df, rejected_dict):
rejected_candles_only = {}
for pair, trades in rejected_dict.items():
rejected_trades_only_df = DataFrame()
pairdf = preprocessed_df[pair]
for t in trades:
data_df_row = pairdf.loc[(pairdf['date'] == t[0])].copy()
data_df_row['pair'] = pair
data_df_row['enter_tag'] = t[1]
rejected_trades_only_df = pd.concat([
rejected_trades_only_df.infer_objects(),
data_df_row.infer_objects()])
rejected_candles_only[pair] = rejected_trades_only_df
self.rejected_df[self.strategy.get_strategy_name()] = rejected_candles_only
def _get_min_cached_backtest_date(self):
min_backtest_date = None
backtest_cache_age = self.config.get('backtest_cache', constants.BACKTEST_CACHE_DEFAULT)
@@ -1353,6 +1392,9 @@ class Backtesting:
store_backtest_signal_candles(
self.config['exportfilename'], self.processed_dfs, dt_appendix)
store_backtest_rejected_trades(
self.config['exportfilename'], self.rejected_df, dt_appendix)
# Results may be mixed up now. Sort them so they follow --strategy-list order.
if 'strategy_list' in self.config and len(self.results) > 0:
self.results['strategy_comparison'] = sorted(

28
freqtrade/optimize/optimize_reports.py
View File

@@ -45,29 +45,41 @@ def store_backtest_stats(
file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
def store_backtest_signal_candles(
recordfilename: Path, candles: Dict[str, Dict], dtappendix: str) -> Path:
def _store_backtest_analysis_data(
recordfilename: Path, data: Dict[str, Dict],
dtappendix: str, name: str) -> Path:
"""
Stores backtest trade signal candles
Stores backtest trade candles for analysis
:param recordfilename: Path object, which can either be a filename or a directory.
Filenames will be appended with a timestamp right before the suffix
while for directories, <directory>/backtest-result-<datetime>_signals.pkl will be used
while for directories, <directory>/backtest-result-<datetime>_<name>.pkl will be used
as filename
:param stats: Dict containing the backtesting signal candles
:param candles: Dict containing the backtesting data for analysis
:param dtappendix: Datetime to use for the filename
:param name: Name to use for the file, e.g. signals, rejected
"""
if recordfilename.is_dir():
filename = (recordfilename / f'backtest-result-{dtappendix}_signals.pkl')
filename = (recordfilename / f'backtest-result-{dtappendix}_{name}.pkl')
else:
filename = Path.joinpath(
recordfilename.parent, f'{recordfilename.stem}-{dtappendix}_signals.pkl'
recordfilename.parent, f'{recordfilename.stem}-{dtappendix}_{name}.pkl'
)
file_dump_joblib(filename, candles)
file_dump_joblib(filename, data)
return filename
def store_backtest_signal_candles(
recordfilename: Path, candles: Dict[str, Dict], dtappendix: str) -> Path:
return _store_backtest_analysis_data(recordfilename, candles, dtappendix, "signals")
def store_backtest_rejected_trades(
recordfilename: Path, trades: Dict[str, Dict], dtappendix: str) -> Path:
return _store_backtest_analysis_data(recordfilename, trades, dtappendix, "rejected")
def _get_line_floatfmt(stake_currency: str) -> List[str]:
"""
Generate floatformat (goes in line with _generate_result_line())