def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
data, timerange = self.load_bt_data()
min_date = None
max_date = None
for strat in self.strategylist:
min_date, max_date = self.backtest_one_strategy(
strat, data, timerange)
stats = generate_backtest_stats(data,
self.all_results,
min_date=min_date,
max_date=max_date)
if self.config.get('export', False):
store_backtest_stats(self.config['exportfilename'], stats)
# Show backtest results
show_backtest_results(self.config, stats)
def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
data, timerange = self.load_bt_data()
self.load_bt_data_detail()
logger.info("Dataload complete. Calculating indicators")
for strat in self.strategylist:
min_date, max_date = self.backtest_one_strategy(
strat, data, timerange)
if len(self.strategylist) > 0:
self.results = generate_backtest_stats(data,
self.all_results,
min_date=min_date,
max_date=max_date)
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'],
self.results)
# Show backtest results
show_backtest_results(self.config, self.results)
def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
data, timerange = self.load_bt_data()
self.load_bt_data_detail()
logger.info("Dataload complete. Calculating indicators")
self.load_prior_backtest()
for strat in self.strategylist:
if self.results and strat.get_strategy_name(
) in self.results['strategy']:
# When previous result hash matches - reuse that result and skip backtesting.
logger.info(
f'Reusing result of previous backtest for {strat.get_strategy_name()}'
)
continue
min_date, max_date = self.backtest_one_strategy(
strat, data, timerange)
# Update old results with new ones.
if len(self.all_results) > 0:
results = generate_backtest_stats(data,
self.all_results,
min_date=min_date,
max_date=max_date)
if self.results:
self.results['metadata'].update(results['metadata'])
self.results['strategy'].update(results['strategy'])
self.results['strategy_comparison'].extend(
results['strategy_comparison'])
else:
self.results = results
if self.config.get('export', 'none') == 'trades':
store_backtest_stats(self.config['exportfilename'],
self.results)
# 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(
self.results['strategy_comparison'],
key=lambda c: self.config['strategy_list'].index(c['key']))
self.results['strategy'] = dict(
sorted(
self.results['strategy'].items(),
key=lambda kv: self.config['strategy_list'].index(kv[0])))
if len(self.strategylist) > 0:
# Show backtest results
show_backtest_results(self.config, self.results)
def test_store_backtest_stats(testdatadir, mocker):
dump_mock = mocker.patch('freqtrade.optimize.optimize_reports.file_dump_json')
store_backtest_stats(testdatadir, {})
assert dump_mock.call_count == 2
assert isinstance(dump_mock.call_args_list[0][0][0], Path)
assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir/'backtest-result'))
dump_mock.reset_mock()
filename = testdatadir / 'testresult.json'
store_backtest_stats(filename, {})
assert dump_mock.call_count == 2
assert isinstance(dump_mock.call_args_list[0][0][0], Path)
# result will be testdatadir / testresult-<timestamp>.json
assert str(dump_mock.call_args_list[0][0][0]).startswith(str(testdatadir / 'testresult'))
def test_generate_backtest_stats(default_conf, testdatadir):
default_conf.update({'strategy': 'DefaultStrategy'})
StrategyResolver.load_strategy(default_conf)
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"sell_reason": [
SellType.ROI, SellType.STOP_LOSS, SellType.ROI,
SellType.FORCE_SELL
]
}),
'config':
default_conf,
'locks': [],
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
}
}
timerange = TimeRange.parse_timerange('1510688220-1510700340')
min_date = Arrow.fromtimestamp(1510688220)
max_date = Arrow.fromtimestamp(1510700340)
btdata = history.load_data(testdatadir,
'1m', ['UNITTEST/BTC'],
timerange=timerange,
fill_up_missing=True)
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.datetime
assert strat_stats['backtest_end'] == max_date.datetime
assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown'] == 0.0
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [
SellType.ROI, SellType.STOP_LOSS, SellType.ROI,
SellType.FORCE_SELL
]
}),
'config':
default_conf
}
}
assert strat_stats['max_drawdown'] == 0.0
assert strat_stats['drawdown_start'] == datetime(1970,
1,
1,
tzinfo=timezone.utc)
assert strat_stats['drawdown_end'] == datetime(1970,
1,
1,
tzinfo=timezone.utc)
assert strat_stats['drawdown_end_ts'] == 0
assert strat_stats['drawdown_start_ts'] == 0
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
# Test storing stats
filename = Path(testdatadir / 'btresult.json')
filename_last = Path(testdatadir / LAST_BT_RESULT_FN)
_backup_file(filename_last, copy_file=True)
assert not filename.is_file()
store_backtest_stats(filename, stats)
# get real Filename (it's btresult-<date>.json)
last_fn = get_latest_backtest_filename(filename_last.parent)
assert re.match(r"btresult-.*\.json", last_fn)
filename1 = (testdatadir / last_fn)
assert filename1.is_file()
content = filename1.read_text()
assert 'max_drawdown' in content
assert 'strategy' in content
assert 'pairlist' in content
assert filename_last.is_file()
_clean_test_file(filename_last)
filename1.unlink()
def run_backtest():
from freqtrade.optimize.optimize_reports import (
generate_backtest_stats, store_backtest_stats)
from freqtrade.resolvers import StrategyResolver
asyncio.set_event_loop(asyncio.new_event_loop())
try:
# Reload strategy
lastconfig = ApiServer._bt_last_config
strat = StrategyResolver.load_strategy(btconfig)
validate_config_consistency(btconfig)
if (not ApiServer._bt
or lastconfig.get('timeframe') != strat.timeframe
or lastconfig.get('timeframe_detail') !=
btconfig.get('timeframe_detail')
or lastconfig.get('timerange') != btconfig['timerange']):
from freqtrade.optimize.backtesting import Backtesting
ApiServer._bt = Backtesting(btconfig)
if ApiServer._bt.timeframe_detail:
ApiServer._bt.load_bt_data_detail()
else:
ApiServer._bt.config = btconfig
ApiServer._bt.init_backtest()
# Only reload data if timeframe changed.
if (not ApiServer._bt_data or not ApiServer._bt_timerange
or lastconfig.get('timeframe') != strat.timeframe
or lastconfig.get('timerange') != btconfig['timerange']):
ApiServer._bt_data, ApiServer._bt_timerange = ApiServer._bt.load_bt_data(
)
lastconfig['timerange'] = btconfig['timerange']
lastconfig['timeframe'] = strat.timeframe
lastconfig['protections'] = btconfig.get('protections', [])
lastconfig['enable_protections'] = btconfig.get(
'enable_protections')
lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
ApiServer._bt.results = {}
ApiServer._bt.load_prior_backtest()
ApiServer._bt.abort = False
if (ApiServer._bt.results and strat.get_strategy_name()
in ApiServer._bt.results['strategy']):
# When previous result hash matches - reuse that result and skip backtesting.
logger.info(
f'Reusing result of previous backtest for {strat.get_strategy_name()}'
)
else:
min_date, max_date = ApiServer._bt.backtest_one_strategy(
strat, ApiServer._bt_data, ApiServer._bt_timerange)
ApiServer._bt.results = generate_backtest_stats(
ApiServer._bt_data,
ApiServer._bt.all_results,
min_date=min_date,
max_date=max_date)
if btconfig.get('export', 'none') == 'trades':
store_backtest_stats(btconfig['exportfilename'],
ApiServer._bt.results)
logger.info("Backtest finished.")
except DependencyException as e:
logger.info(f"Backtesting caused an error: {e}")
pass
finally:
ApiServer._bgtask_running = False
def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
StrategyResolver.load_strategy(default_conf)
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"exit_reason": [
ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI,
ExitType.FORCE_EXIT
]
}),
'config':
default_conf,
'locks': [],
'final_balance':
1000.02,
'rejected_signals':
20,
'timedout_entry_orders':
0,
'timedout_exit_orders':
0,
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
'run_id':
'123',
}
}
timerange = TimeRange.parse_timerange('1510688220-1510700340')
min_date = Arrow.fromtimestamp(1510688220)
max_date = Arrow.fromtimestamp(1510700340)
btdata = history.load_data(testdatadir,
'1m', ['UNITTEST/BTC'],
timerange=timerange,
fill_up_missing=True)
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.strftime(
DATETIME_PRINT_FORMAT)
assert strat_stats['backtest_end'] == max_date.strftime(
DATETIME_PRINT_FORMAT)
assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown_account'] == 0.0
# Retry with losing trade
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"exit_reason": [
ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS,
ExitType.FORCE_EXIT
]
}),
'config':
default_conf,
'locks': [],
'final_balance':
1000.02,
'rejected_signals':
20,
'timedout_entry_orders':
0,
'timedout_exit_orders':
0,
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
'run_id':
'124',
}
}
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert pytest.approx(strat_stats['max_drawdown_account']) == 1.399999e-08
assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00'
assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00'
assert strat_stats['drawdown_end_ts'] == 1510699380000
assert strat_stats['drawdown_start_ts'] == 1510697400000
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
# Test storing stats
filename = Path(tmpdir / 'btresult.json')
filename_last = Path(tmpdir / LAST_BT_RESULT_FN)
_backup_file(filename_last, copy_file=True)
assert not filename.is_file()
store_backtest_stats(filename, stats)
# get real Filename (it's btresult-<date>.json)
last_fn = get_latest_backtest_filename(filename_last.parent)
assert re.match(r"btresult-.*\.json", last_fn)
filename1 = Path(tmpdir / last_fn)
assert filename1.is_file()
content = filename1.read_text()
assert 'max_drawdown_account' in content
assert 'strategy' in content
assert 'pairlist' in content
assert filename_last.is_file()
_clean_test_file(filename_last)
filename1.unlink()
def start(self) -> None:
"""
Run backtesting end-to-end
:return: None
"""
data: Dict[str, Any] = {}
logger.info('Using stake_currency: %s ...',
self.config['stake_currency'])
logger.info('Using stake_amount: %s ...', self.config['stake_amount'])
# Use max_open_trades in backtesting, except --disable-max-market-positions is set
if self.config.get('use_max_market_positions', True):
max_open_trades = self.config['max_open_trades']
else:
logger.info(
'Ignoring max_open_trades (--disable-max-market-positions was used) ...'
)
max_open_trades = 0
position_stacking = self.config.get('position_stacking', False)
data, timerange = self.load_bt_data()
all_results = {}
for strat in self.strategylist:
logger.info("Running backtesting for Strategy %s",
strat.get_strategy_name())
self._set_strategy(strat)
# need to reprocess data every time to populate signals
preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
# Trim startup period from analyzed dataframe
for pair, df in preprocessed.items():
preprocessed[pair] = trim_dataframe(df, timerange)
min_date, max_date = history.get_timerange(preprocessed)
logger.info(
f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
f'({(max_date - min_date).days} days)..')
# Execute backtest and print results
all_results[self.strategy.get_strategy_name()] = self.backtest(
processed=preprocessed,
stake_amount=self.config['stake_amount'],
start_date=min_date,
end_date=max_date,
max_open_trades=max_open_trades,
position_stacking=position_stacking,
)
stats = generate_backtest_stats(self.config,
data,
all_results,
min_date=min_date,
max_date=max_date)
if self.config.get('export', False):
store_backtest_stats(self.config['exportfilename'], stats)
# Show backtest results
show_backtest_results(self.config, stats)
