Merge pull request #2624 from freqtrade/backtest_refactor
handle and document ROI=-1
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hroff-1902
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@ -194,7 +194,10 @@ Since backtesting lacks some detailed information about what happens within a ca
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- Buys happen at open-price
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- Sell signal sells happen at open-price of the following candle
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- Low happens before high for stoploss, protecting capital first.
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- ROI sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
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- ROI
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- sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
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- sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit
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- Forcesells caused by `<N>=-1` ROI entries use low as sell value, unless N falls on the candle open (e.g. `120: -1` for 1h candles)
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- Stoploss sells happen exactly at stoploss price, even if low was lower
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- Trailing stoploss
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- High happens first - adjusting stoploss
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@ -169,6 +169,9 @@ This parameter can be set in either Strategy or Configuration file. If you use i
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`minimal_roi` value from the strategy file.
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If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal roi is disabled unless your trade generates 1000% profit.
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!!! Note "Special case to forcesell after a specific time"
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A special case presents using `"<N>": -1` as ROI. This forces the bot to sell a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-sell.
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### Understand stoploss
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Go to the [stoploss documentation](stoploss.md) for more details.
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@ -261,6 +261,45 @@ class Backtesting:
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ticker[pair] = [x for x in ticker_data.itertuples()]
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return ticker
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def _get_close_rate(self, sell_row, trade: Trade, sell, trade_dur) -> float:
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"""
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Get close rate for backtesting result
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"""
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# Special handling if high or low hit STOP_LOSS or ROI
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if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
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# Set close_rate to stoploss
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return trade.stop_loss
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elif sell.sell_type == (SellType.ROI):
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roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
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if roi is not None:
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if roi == -1 and roi_entry % self.timeframe_mins == 0:
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# When forceselling with ROI=-1, the roi time will always be equal to trade_dur.
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# If that entry is a multiple of the timeframe (so on candle open)
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# - we'll use open instead of close
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return sell_row.open
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# - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
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close_rate = - (trade.open_rate * roi + trade.open_rate *
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(1 + trade.fee_open)) / (trade.fee_close - 1)
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if (trade_dur > 0 and trade_dur == roi_entry
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and roi_entry % self.timeframe_mins == 0
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and sell_row.open > close_rate):
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# new ROI entry came into effect.
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# use Open rate if open_rate > calculated sell rate
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return sell_row.open
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# Use the maximum between close_rate and low as we
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# cannot sell outside of a candle.
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# Applies when a new ROI setting comes in place and the whole candle is above that.
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return max(close_rate, sell_row.low)
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else:
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# This should not be reached...
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return sell_row.open
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else:
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return sell_row.open
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def _get_sell_trade_entry(
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self, pair: str, buy_row: DataFrame,
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partial_ticker: List, trade_count_lock: Dict,
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@ -287,26 +326,7 @@ class Backtesting:
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sell_row.sell, low=sell_row.low, high=sell_row.high)
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if sell.sell_flag:
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trade_dur = int((sell_row.date - buy_row.date).total_seconds() // 60)
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# Special handling if high or low hit STOP_LOSS or ROI
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if sell.sell_type in (SellType.STOP_LOSS, SellType.TRAILING_STOP_LOSS):
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# Set close_rate to stoploss
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closerate = trade.stop_loss
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elif sell.sell_type == (SellType.ROI):
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roi = self.strategy.min_roi_reached_entry(trade_dur)
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if roi is not None:
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# - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
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closerate = - (trade.open_rate * roi + trade.open_rate *
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(1 + trade.fee_open)) / (trade.fee_close - 1)
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# Use the maximum between closerate and low as we
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# cannot sell outside of a candle.
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# Applies when using {"xx": -1} as roi to force sells after xx minutes
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closerate = max(closerate, sell_row.low)
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else:
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# This should not be reached...
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closerate = sell_row.open
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else:
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closerate = sell_row.open
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closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
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return BacktestResult(pair=pair,
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profit_percent=trade.calc_profit_percent(rate=closerate),
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@ -394,7 +394,7 @@ class IStrategy(ABC):
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return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
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def min_roi_reached_entry(self, trade_dur: int) -> Optional[float]:
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def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
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"""
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Based on trade duration defines the ROI entry that may have been reached.
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:param trade_dur: trade duration in minutes
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@ -403,9 +403,9 @@ class IStrategy(ABC):
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# Get highest entry in ROI dict where key <= trade-duration
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roi_list = list(filter(lambda x: x <= trade_dur, self.minimal_roi.keys()))
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if not roi_list:
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return None
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return None, None
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roi_entry = max(roi_list)
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return self.minimal_roi[roi_entry]
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return roi_entry, self.minimal_roi[roi_entry]
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def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
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"""
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@ -415,7 +415,7 @@ class IStrategy(ABC):
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"""
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# Check if time matches and current rate is above threshold
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trade_dur = int((current_time.timestamp() - trade.open_date.timestamp()) // 60)
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roi = self.min_roi_reached_entry(trade_dur)
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_, roi = self.min_roi_reached_entry(trade_dur)
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if roi is None:
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return False
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else:
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@ -265,6 +265,69 @@ tc16 = BTContainer(data=[
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trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
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)
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# Test 17: Buy, hold for 120 mins, then forcesell using roi=-1
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# Causes negative profit even though sell-reason is ROI.
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# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
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# Uses open as sell-rate (special case) - since the roi-time is a multiple of the ticker interval.
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tc17 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
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[2, 4987, 5300, 4950, 5050, 6172, 0, 0],
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[3, 4980, 5000, 4940, 4962, 6172, 0, 0], # ForceSell on ROI (roi=-1)
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[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
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[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
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stop_loss=-0.10, roi={"0": 0.10, "120": -1}, profit_perc=-0.004,
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trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
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)
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# Test 18: Buy, hold for 120 mins, then drop ROI to 1%, causing a sell in candle 3.
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# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
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# uses open_rate as sell-price
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tc18 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
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[2, 4987, 5300, 4950, 5200, 6172, 0, 0],
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[3, 5200, 5220, 4940, 4962, 6172, 0, 0], # Sell on ROI (sells on open)
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[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
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[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
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stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.04,
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trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
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)
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# Test 19: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
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# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
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# uses calculated ROI (1%) as sell rate, otherwise identical to tc18
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tc19 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
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[2, 4987, 5300, 4950, 5200, 6172, 0, 0],
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[3, 5000, 5300, 4940, 4962, 6172, 0, 0], # Sell on ROI
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[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
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[5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
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stop_loss=-0.10, roi={"0": 0.10, "120": 0.01}, profit_perc=0.01,
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trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
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)
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# Test 20: Buy, hold for 119 mins, then drop ROI to 1%, causing a sell in candle 3.
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# stop-loss: 10%, ROI: 10% (should not apply), -100% after 100 minutes (limits trade duration)
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# uses calculated ROI (1%) as sell rate, otherwise identical to tc18
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tc20 = BTContainer(data=[
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# D O H L C V B S
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[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
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[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
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[2, 4987, 5300, 4950, 5200, 6172, 0, 0],
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[3, 5200, 5300, 4940, 4962, 6172, 0, 0], # Sell on ROI
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[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
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[5, 4550, 4975, 4925, 4950, 6172, 0, 0]],
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stop_loss=-0.10, roi={"0": 0.10, "119": 0.01}, profit_perc=0.01,
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trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
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)
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TESTS = [
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tc0,
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tc1,
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@ -283,6 +346,10 @@ TESTS = [
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tc14,
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tc15,
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tc16,
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tc17,
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tc18,
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tc19,
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tc20,
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]
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