diff --git a/docs/strategy-callbacks.md b/docs/strategy-callbacks.md index 81366c66e..f1cdc9f3b 100644 --- a/docs/strategy-callbacks.md +++ b/docs/strategy-callbacks.md @@ -316,11 +316,11 @@ class AwesomeStrategy(IStrategy): # evaluate highest to lowest, so that highest possible stop is used if current_profit > 0.40: - return stoploss_from_open(0.25, current_profit, is_short=trade.is_short) + return stoploss_from_open(0.25, current_profit, is_short=trade.is_short, leverage=trade.leverage) elif current_profit > 0.25: - return stoploss_from_open(0.15, current_profit, is_short=trade.is_short) + return stoploss_from_open(0.15, current_profit, is_short=trade.is_short, leverage=trade.leverage) elif current_profit > 0.20: - return stoploss_from_open(0.07, current_profit, is_short=trade.is_short) + return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage) # return maximum stoploss value, keeping current stoploss price unchanged return 1 diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md index 3519a80cd..8ab0b1464 100644 --- a/docs/strategy-customization.md +++ b/docs/strategy-customization.md @@ -881,7 +881,7 @@ All columns of the informative dataframe will be available on the returning data ### *stoploss_from_open()* -Stoploss values returned from `custom_stoploss` must specify a percentage relative to `current_rate`, but sometimes you may want to specify a stoploss relative to the open price instead. `stoploss_from_open()` is a helper function to calculate a stoploss value that can be returned from `custom_stoploss` which will be equivalent to the desired percentage above the open price. +Stoploss values returned from `custom_stoploss` must specify a percentage relative to `current_rate`, but sometimes you may want to specify a stoploss relative to the entry point instead. `stoploss_from_open()` is a helper function to calculate a stoploss value that can be returned from `custom_stoploss` which will be equivalent to the desired trade profit above the entry point. ??? Example "Returning a stoploss relative to the open price from the custom stoploss function" @@ -889,6 +889,8 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati If we want a stop price at 7% above the open price we can call `stoploss_from_open(0.07, current_profit, False)` which will return `0.1157024793`. 11.57% below $121 is $107, which is the same as 7% above $100. + This function will consider leverage - so at 10x leverage, the actual stoploss would be 0.7% above $100 (0.7% * 10x = 7%). + ``` python @@ -907,7 +909,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati # once the profit has risen above 10%, keep the stoploss at 7% above the open price if current_profit > 0.10: - return stoploss_from_open(0.07, current_profit, is_short=trade.is_short) + return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage) return 1 diff --git a/freqtrade/strategy/strategy_helper.py b/freqtrade/strategy/strategy_helper.py index aa753a829..27ebe7e69 100644 --- a/freqtrade/strategy/strategy_helper.py +++ b/freqtrade/strategy/strategy_helper.py @@ -86,37 +86,41 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame, def stoploss_from_open( open_relative_stop: float, current_profit: float, - is_short: bool = False + is_short: bool = False, + leverage: float = 1.0 ) -> float: """ - - Given the current profit, and a desired stop loss value relative to the open price, + Given the current profit, and a desired stop loss value relative to the trade entry price, return a stop loss value that is relative to the current price, and which can be returned from `custom_stoploss`. The requested stop can be positive for a stop above the open price, or negative for a stop below the open price. The return value is always >= 0. + `open_relative_stop` will be considered as adjusted for leverage if leverage is provided.. Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price - :param open_relative_stop: Desired stop loss percentage relative to open price + :param open_relative_stop: Desired stop loss percentage, relative to the open price, + adjusted for leverage :param current_profit: The current profit percentage :param is_short: When true, perform the calculation for short instead of long + :param leverage: Leverage to use for the calculation :return: Stop loss value relative to current price """ # formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value - if (current_profit == -1 and not is_short) or (is_short and current_profit == 1): + _current_profit = current_profit / leverage + if (_current_profit == -1 and not is_short) or (is_short and _current_profit == 1): return 1 if is_short is True: - stoploss = -1 + ((1 - open_relative_stop) / (1 - current_profit)) + stoploss = -1 + ((1 - open_relative_stop / leverage) / (1 - _current_profit)) else: - stoploss = 1 - ((1 + open_relative_stop) / (1 + current_profit)) + stoploss = 1 - ((1 + open_relative_stop / leverage) / (1 + _current_profit)) # negative stoploss values indicate the requested stop price is higher/lower # (long/short) than the current price - return max(stoploss, 0.0) + return max(stoploss * leverage, 0.0) def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float: diff --git a/tests/strategy/test_strategy_helpers.py b/tests/strategy/test_strategy_helpers.py index cb79ac171..a55580780 100644 --- a/tests/strategy/test_strategy_helpers.py +++ b/tests/strategy/test_strategy_helpers.py @@ -177,26 +177,30 @@ def test_stoploss_from_open(side, profitrange): ("long", 0.1, 0.2, 1, 0.08333333), ("long", 0.1, 0.5, 1, 0.266666666), ("long", 0.1, 5, 1, 0.816666666), # 500% profit, set stoploss to 10% above open price + ("long", 0, 5, 10, 3.3333333), # 500% profit, set stoploss break even + ("long", 0.1, 5, 10, 3.26666666), # 500% profit, set stoploss to 10% above open price + ("long", -0.1, 5, 10, 3.3999999), # 500% profit, set stoploss to 10% belowopen price ("short", 0, 0.1, 1, 0.1111111), ("short", -0.1, 0.1, 1, 0.2222222), ("short", 0.1, 0.2, 1, 0.125), ("short", 0.1, 1, 1, 1), + ("short", -0.01, 5, 10, 10.01999999), # 500% profit at 10x ]) def test_stoploss_from_open_leverage(side, rel_stop, curr_profit, leverage, expected): - stoploss = stoploss_from_open(rel_stop, curr_profit, side == 'short') + stoploss = stoploss_from_open(rel_stop, curr_profit, side == 'short', leverage) assert pytest.approx(stoploss) == expected open_rate = 100 if stoploss != 1: if side == 'long': - current_rate = open_rate * (1 + curr_profit) - stop = current_rate * (1 - stoploss) - assert pytest.approx(stop) == open_rate * (1 + rel_stop) + current_rate = open_rate * (1 + curr_profit / leverage) + stop = current_rate * (1 - stoploss / leverage) + assert pytest.approx(stop) == open_rate * (1 + rel_stop / leverage) else: - current_rate = open_rate * (1 - curr_profit) - stop = current_rate * (1 + stoploss) - assert pytest.approx(stop) == open_rate * (1 - rel_stop) + current_rate = open_rate * (1 - curr_profit / leverage) + stop = current_rate * (1 + stoploss / leverage) + assert pytest.approx(stop) == open_rate * (1 - rel_stop / leverage) def test_stoploss_from_absolute():