Apply special case for negative ROI

freqtrade/optimize/backtesting.py

@@ -267,7 +267,7 @@ class Backtesting:
             # Set close_rate to stoploss
             closerate = trade.stop_loss
         elif sell.sell_type == (SellType.ROI):
-            roi = self.strategy.min_roi_reached_entry(trade_dur)
+            roi_entry, roi = self.strategy.min_roi_reached_entry(trade_dur)
             if roi is not None:
                 # - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
                 closerate = - (trade.open_rate * roi + trade.open_rate *
@@ -275,8 +275,14 @@ class Backtesting:
 
                 # Use the maximum between closerate and low as we
                 # cannot sell outside of a candle.
-                # Applies when using {"xx": -1} as roi to force sells after xx minutes
+                # Applies when a new ROI setting comes in place and the whole candle is above that.
                 closerate = max(closerate, sell_row.low)
+                if roi == -1 and roi_entry % self.timeframe_mins == 0:
+                    # When forceselling with ROI=-1, the roi-entry will always be "on the entry".
+                    # If that entry is a multiple of the timeframe (so on open)
+                    # - we'll use open instead of close
+                    closerate = max(closerate, sell_row.open)
+
             else:
                 # This should not be reached...
                 closerate = sell_row.open

freqtrade/strategy/interface.py

@@ -394,7 +394,7 @@ class IStrategy(ABC):
 
         return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
 
-    def min_roi_reached_entry(self, trade_dur: int) -> Optional[float]:
+    def min_roi_reached_entry(self, trade_dur: int) -> Tuple[Optional[int], Optional[float]]:
         """
         Based on trade duration defines the ROI entry that may have been reached.
         :param trade_dur: trade duration in minutes
@@ -403,9 +403,9 @@ class IStrategy(ABC):
         # Get highest entry in ROI dict where key <= trade-duration
         roi_list = list(filter(lambda x: x <= trade_dur, self.minimal_roi.keys()))
         if not roi_list:
-            return None
+            return None, None
         roi_entry = max(roi_list)
-        return self.minimal_roi[roi_entry]
+        return roi_entry, self.minimal_roi[roi_entry]
 
     def min_roi_reached(self, trade: Trade, current_profit: float, current_time: datetime) -> bool:
         """
@@ -415,7 +415,7 @@ class IStrategy(ABC):
         """
         # Check if time matches and current rate is above threshold
         trade_dur = int((current_time.timestamp() - trade.open_date.timestamp()) // 60)
-        roi = self.min_roi_reached_entry(trade_dur)
+        _, roi = self.min_roi_reached_entry(trade_dur)
         if roi is None:
             return False
         else: