Add leverage adjustment to "stoploss_from_absolute"

docs/strategy-customization.md

@@ -927,13 +927,14 @@ In some situations it may be confusing to deal with stops relative to current ra
 
 ??? Example "Returning a stoploss using absolute price from the custom stoploss function"
 
-    If we want to trail a stop price at 2xATR below current price we can call `stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)`.
+    If we want to trail a stop price at 2xATR below current price we can call `stoploss_from_absolute(current_rate + (side * candle['atr'] * 2), current_rate, is_short=trade.is_short, leverage=trade.leverage)`.
+    For futures, we need to adjust the direction (up or down), as well as adjust for leverage, since the [`custom_stoploss`](strategy-callbacks.md#custom-stoploss) callback  returns the ["risk for this trade"](stoploss.md#stoploss-and-leverage) - not the relative price movement.
 
     ``` python
 
     from datetime import datetime
     from freqtrade.persistence import Trade
-    from freqtrade.strategy import IStrategy, stoploss_from_absolute
+    from freqtrade.strategy import IStrategy, stoploss_from_absolute, timeframe_to_prev_date
 
     class AwesomeStrategy(IStrategy):
 
@@ -947,8 +948,12 @@ In some situations it may be confusing to deal with stops relative to current ra
                             current_rate: float, current_profit: float, after_fill: bool,
                             **kwargs) -> Optional[float]:
             dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
+            trade_date = timeframe_to_prev_date(self.timeframe, trade.open_date_utc)
             candle = dataframe.iloc[-1].squeeze()
-            return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)
+            sign = 1 if trade.is_short else -1
+            return stoploss_from_absolute(current_rate + (side * candle['atr'] * 2), 
+                                          current_rate, is_short=trade.is_short,
+                                          leverage=trade.leverage)
 
     ```
 

docs/strategy_migration.md

@@ -317,7 +317,7 @@ After:
         if current_profit > 0.10:
             return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
 
-        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short)
+        return stoploss_from_absolute(current_rate - (candle['atr'] * 2), current_rate, is_short=trade.is_short, leverage=trade.leverage)
 
 
 ```

freqtrade/strategy/strategy_helper.py

@@ -123,7 +123,8 @@ def stoploss_from_open(
     return max(stoploss * leverage, 0.0)
 
 
-def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float:
+def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False,
+                           leverage: float = 1.0) -> float:
     """
     Given current price and desired stop price, return a stop loss value that is relative to current
     price.
@@ -136,6 +137,7 @@ def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool
     :param stop_rate: Stop loss price.
     :param current_rate: Current asset price.
     :param is_short: When true, perform the calculation for short instead of long
+    :param leverage: Leverage to use for the calculation
     :return: Positive stop loss value relative to current price
     """
 
@@ -150,4 +152,4 @@ def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool
     # negative stoploss values indicate the requested stop price is higher/lower
     # (long/short) than the current price
     # shorts can yield stoploss values higher than 1, so limit that as well
-    return max(min(stoploss, 1.0), 0.0)
+    return max(min(stoploss, 1.0), 0.0) * leverage

tests/strategy/test_strategy_helpers.py

@@ -211,15 +211,18 @@ def test_stoploss_from_absolute():
     assert pytest.approx(stoploss_from_absolute(110, 100)) == 0
     assert pytest.approx(stoploss_from_absolute(100, 0)) == 1
     assert pytest.approx(stoploss_from_absolute(0, 100)) == 1
+    assert pytest.approx(stoploss_from_absolute(0, 100, False, leverage=5)) == 5
 
     assert pytest.approx(stoploss_from_absolute(90, 100, True)) == 0
     assert pytest.approx(stoploss_from_absolute(100, 100, True)) == 0
     assert pytest.approx(stoploss_from_absolute(110, 100, True)) == -(1 - (110 / 100))
     assert pytest.approx(stoploss_from_absolute(110, 100, True)) == 0.1
     assert pytest.approx(stoploss_from_absolute(105, 100, True)) == 0.05
+    assert pytest.approx(stoploss_from_absolute(105, 100, True, 5)) == 0.05 * 5
     assert pytest.approx(stoploss_from_absolute(100, 0, True)) == 1
     assert pytest.approx(stoploss_from_absolute(0, 100, True)) == 0
-    assert pytest.approx(stoploss_from_absolute(100, 1, True)) == 1
+    assert pytest.approx(stoploss_from_absolute(100, 1, is_short=True)) == 1
+    assert pytest.approx(stoploss_from_absolute(100, 1, is_short=True, leverage=5)) == 5
 
 
 @pytest.mark.parametrize('trading_mode', ['futures', 'spot'])