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Adjust backtest so sell uses stop-loss or roi value as closerate

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This commit is contained in:
Matthias 2018-08-16 11:31:41 +02:00
parent a0e8bfbd77
commit 233c442af9
3 changed files with 39 additions and 24 deletions
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18
freqtrade/optimize/backtesting.py
View File

@ -206,12 +206,20 @@ class Backtesting(object):
buy_signal = sell_row.buy buy_signal = sell_row.buy
sell = self.strategy.should_sell(trade, sell_row.open, sell_row.date, buy_signal, sell = self.strategy.should_sell(trade, sell_row.open, sell_row.date, buy_signal,
sell_row.sell) sell_row.sell, low=sell_row.low, high=sell_row.high)
if sell.sell_flag: if sell.sell_flag:
if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
# Set close_rate to stoploss
closerate = trade.stop_loss
elif sell.sell_type == (SellType.ROI):
# set close-rate to min-roi
closerate = trade.open_rate + trade.open_rate * self.strategy.minimal_roi[0]
else:
closerate = sell_row.open
return BacktestResult(pair=pair, return BacktestResult(pair=pair,
profit_percent=trade.calc_profit_percent(rate=sell_row.open), profit_percent=trade.calc_profit_percent(rate=closerate),
profit_abs=trade.calc_profit(rate=sell_row.open), profit_abs=trade.calc_profit(rate=closerate),
open_time=buy_row.date, open_time=buy_row.date,
close_time=sell_row.date, close_time=sell_row.date,
trade_duration=int(( trade_duration=int((
@ -220,7 +228,7 @@ class Backtesting(object):
close_index=sell_row.Index, close_index=sell_row.Index,
open_at_end=False, open_at_end=False,
open_rate=buy_row.open, open_rate=buy_row.open,
close_rate=sell_row.open, close_rate=closerate,
sell_reason=sell.sell_type sell_reason=sell.sell_type
) )
if partial_ticker: if partial_ticker:
@ -260,7 +268,7 @@ class Backtesting(object):
position_stacking: do we allow position stacking? (default: False) position_stacking: do we allow position stacking? (default: False)
:return: DataFrame :return: DataFrame
""" """
headers = ['date', 'buy', 'open', 'close', 'sell'] headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
processed = args['processed'] processed = args['processed']
max_open_trades = args.get('max_open_trades', 0) max_open_trades = args.get('max_open_trades', 0)
position_stacking = args.get('position_stacking', False) position_stacking = args.get('position_stacking', False)

12
freqtrade/strategy/interface.py
View File

@ -203,18 +203,22 @@ class IStrategy(ABC):
return buy, sell return buy, sell
def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool, def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
sell: bool) -> SellCheckTuple: sell: bool, low: float=None, high: float=None) -> SellCheckTuple:
""" """
This function evaluate if on the condition required to trigger a sell has been reached This function evaluate if on the condition required to trigger a sell has been reached
if the threshold is reached and updates the trade record. if the threshold is reached and updates the trade record.
:return: True if trade should be sold, False otherwise :return: True if trade should be sold, False otherwise
""" """
current_profit = trade.calc_profit_percent(rate) # Set current rate to low for backtesting sell
stoplossflag = self.stop_loss_reached(current_rate=rate, trade=trade, current_time=date, current_rate = rate if not low else low
current_profit = trade.calc_profit_percent(current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade, current_time=date,
current_profit=current_profit) current_profit=current_profit)
if stoplossflag.sell_flag: if stoplossflag.sell_flag:
return stoplossflag return stoplossflag
# Set current rate to low for backtesting sell
current_rate = rate if not high else high
current_profit = trade.calc_profit_percent(current_rate)
experimental = self.config.get('experimental', {}) experimental = self.config.get('experimental', {})
if buy and experimental.get('ignore_roi_if_buy_signal', False): if buy and experimental.get('ignore_roi_if_buy_signal', False):

33
freqtrade/tests/optimize/test_backtest_detail.py
View File

@ -72,8 +72,8 @@ tc1 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9955, 9975, 9955, 9990, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9955, 9975, 9955, 9990, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9990, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9990, 9990, 9990, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS) # should be stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.01, sell_r=SellType.STOP_LOSS) # should be
stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.003, sell_r=SellType.FORCE_SELL) # # stop_loss=-0.01, roi=1, trades=1, profit_perc=-0.003, sell_r=SellType.FORCE_SELL) #
# Test 2 Minus 4% Low, minus 1% close # Test 2 Minus 4% Low, minus 1% close
@ -88,8 +88,8 @@ tc2 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sell_r=SellType.STOP_LOSS) #should be stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.03, sell_r=SellType.STOP_LOSS) #should be
stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # # stop_loss=-0.03, roi=1, trades=1, profit_perc=-0.007, sell_r=SellType.FORCE_SELL) #
# Test 3 Candle drops 4%, Recovers 1%. # Test 3 Candle drops 4%, Recovers 1%.
@ -108,8 +108,9 @@ tc3 = BTContainer(data=DataFrame([
[getdate('2018-06-10 12:00:00').datetime, 9925, 9975, 8000, 8000, 12345, 0, 0], [getdate('2018-06-10 12:00:00').datetime, 9925, 9975, 8000, 8000, 12345, 0, 0],
[getdate('2018-06-10 13:00:00').datetime, 9900, 9950, 9950, 9900, 12345, 0, 0] [getdate('2018-06-10 13:00:00').datetime, 9900, 9950, 9950, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.4, sell_r=SellType.STOP_LOSS) #should be stop_loss=-0.02, roi=1, trades=2, profit_perc=-0.04, sell_r=SellType.STOP_LOSS) #should be
stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # # stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
# stop_loss=-0.02, roi=1, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
# Test 4 Minus 3% / recovery +15% # Test 4 Minus 3% / recovery +15%
@ -124,8 +125,8 @@ tc4 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9875, 9900, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # stop_loss=-0.02, roi=0.06, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
# Test 5 / Drops 0.5% Closes +20% # Test 5 / Drops 0.5% Closes +20%
# Candle Data for test 5 # Candle Data for test 5
@ -139,8 +140,8 @@ tc5 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be stop_loss=-0.01, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be
stop_loss=-0.01, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # stop_loss=-0.01, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL)
# Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve # Test 6 / Drops 3% / Recovers 6% Positive / Closes 1% positve
# Candle Data for test 6 # Candle Data for test 6
@ -154,8 +155,8 @@ tc6 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.02, sell_r=SellType.STOP_LOSS) #should be
stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # # stop_loss=-0.02, roi=0.05, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
# Test 7 - 6% Positive / 1% Negative / Close 1% Positve # Test 7 - 6% Positive / 1% Negative / Close 1% Positve
# Candle Data for test 7 # Candle Data for test 7
@ -169,8 +170,8 @@ tc7 = BTContainer(data=DataFrame([
[getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0], [getdate('2018-06-10 11:00:00').datetime, 9925, 9975, 9945, 9900, 12345, 0, 0],
[getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0] [getdate('2018-06-10 12:00:00').datetime, 9900, 9950, 9850, 9900, 12345, 0, 0]
], columns=columns), ], columns=columns),
# stop_loss=-0.02, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be stop_loss=-0.02, roi=0.03, trades=1, profit_perc=0.03, sell_r=SellType.ROI) #should be
stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) # # stop_loss=-0.02, roi=0.03, trades=1, profit_perc=-0.012, sell_r=SellType.FORCE_SELL) #
TESTS = [ TESTS = [
# tc_profit1, # tc_profit1,
@ -193,7 +194,9 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
""" """
default_conf["stoploss"] = data.stop_loss default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi} default_conf["minimal_roi"] = {"0": data.roi}
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee) # mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
# TODO: don't Mock fee to for now
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.0))
patch_exchange(mocker) patch_exchange(mocker)
backtesting = Backtesting(default_conf) backtesting = Backtesting(default_conf)