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Add leverage adjustment to "stoploss_from_absolute"

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Matthias
2023-09-02 11:01:59 +02:00
parent a87404b5a8
commit 6f86e30c7e
4 changed files with 17 additions and 7 deletions
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11
docs/strategy-customization.md
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@@ -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)
```

2
docs/strategy_migration.md
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@@ -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)
```

6
freqtrade/strategy/strategy_helper.py
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@@ -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

5
tests/strategy/test_strategy_helpers.py
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@@ -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'])