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Merge pull request #8273 from freqtrade/stop_from_open_lev
Stop from open lev
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5b2a291109
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@ -316,11 +316,11 @@ class AwesomeStrategy(IStrategy):
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# evaluate highest to lowest, so that highest possible stop is used
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if current_profit > 0.40:
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return stoploss_from_open(0.25, current_profit, is_short=trade.is_short)
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return stoploss_from_open(0.25, current_profit, is_short=trade.is_short, leverage=trade.leverage)
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elif current_profit > 0.25:
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return stoploss_from_open(0.15, current_profit, is_short=trade.is_short)
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return stoploss_from_open(0.15, current_profit, is_short=trade.is_short, leverage=trade.leverage)
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elif current_profit > 0.20:
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return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
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return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage)
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# return maximum stoploss value, keeping current stoploss price unchanged
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return 1
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@ -881,7 +881,7 @@ All columns of the informative dataframe will be available on the returning data
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### *stoploss_from_open()*
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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.
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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.
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??? Example "Returning a stoploss relative to the open price from the custom stoploss function"
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@ -889,6 +889,8 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
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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.
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This function will consider leverage - so at 10x leverage, the actual stoploss would be 0.7% above $100 (0.7% * 10x = 7%).
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``` python
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@ -907,7 +909,7 @@ Stoploss values returned from `custom_stoploss` must specify a percentage relati
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# once the profit has risen above 10%, keep the stoploss at 7% above the open price
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if current_profit > 0.10:
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return stoploss_from_open(0.07, current_profit, is_short=trade.is_short)
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return stoploss_from_open(0.07, current_profit, is_short=trade.is_short, leverage=trade.leverage)
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return 1
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@ -86,37 +86,41 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
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def stoploss_from_open(
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open_relative_stop: float,
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current_profit: float,
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is_short: bool = False
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is_short: bool = False,
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leverage: float = 1.0
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) -> float:
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"""
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Given the current profit, and a desired stop loss value relative to the open price,
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Given the current profit, and a desired stop loss value relative to the trade entry price,
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return a stop loss value that is relative to the current price, and which can be
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returned from `custom_stoploss`.
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The requested stop can be positive for a stop above the open price, or negative for
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a stop below the open price. The return value is always >= 0.
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`open_relative_stop` will be considered as adjusted for leverage if leverage is provided..
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Returns 0 if the resulting stop price would be above/below (longs/shorts) the current price
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:param open_relative_stop: Desired stop loss percentage relative to open price
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:param open_relative_stop: Desired stop loss percentage, relative to the open price,
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adjusted for leverage
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:param current_profit: The current profit percentage
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:param is_short: When true, perform the calculation for short instead of long
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:param leverage: Leverage to use for the calculation
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:return: Stop loss value relative to current price
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"""
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# formula is undefined for current_profit -1 (longs) or 1 (shorts), return maximum value
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if (current_profit == -1 and not is_short) or (is_short and current_profit == 1):
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_current_profit = current_profit / leverage
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if (_current_profit == -1 and not is_short) or (is_short and _current_profit == 1):
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return 1
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if is_short is True:
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stoploss = -1 + ((1 - open_relative_stop) / (1 - current_profit))
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stoploss = -1 + ((1 - open_relative_stop / leverage) / (1 - _current_profit))
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else:
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stoploss = 1 - ((1 + open_relative_stop) / (1 + current_profit))
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stoploss = 1 - ((1 + open_relative_stop / leverage) / (1 + _current_profit))
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# negative stoploss values indicate the requested stop price is higher/lower
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# (long/short) than the current price
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return max(stoploss, 0.0)
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return max(stoploss * leverage, 0.0)
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def stoploss_from_absolute(stop_rate: float, current_rate: float, is_short: bool = False) -> float:
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@ -177,26 +177,30 @@ def test_stoploss_from_open(side, profitrange):
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("long", 0.1, 0.2, 1, 0.08333333),
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("long", 0.1, 0.5, 1, 0.266666666),
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("long", 0.1, 5, 1, 0.816666666), # 500% profit, set stoploss to 10% above open price
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("long", 0, 5, 10, 3.3333333), # 500% profit, set stoploss break even
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("long", 0.1, 5, 10, 3.26666666), # 500% profit, set stoploss to 10% above open price
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("long", -0.1, 5, 10, 3.3999999), # 500% profit, set stoploss to 10% belowopen price
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("short", 0, 0.1, 1, 0.1111111),
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("short", -0.1, 0.1, 1, 0.2222222),
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("short", 0.1, 0.2, 1, 0.125),
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("short", 0.1, 1, 1, 1),
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("short", -0.01, 5, 10, 10.01999999), # 500% profit at 10x
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])
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def test_stoploss_from_open_leverage(side, rel_stop, curr_profit, leverage, expected):
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stoploss = stoploss_from_open(rel_stop, curr_profit, side == 'short')
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stoploss = stoploss_from_open(rel_stop, curr_profit, side == 'short', leverage)
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assert pytest.approx(stoploss) == expected
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open_rate = 100
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if stoploss != 1:
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if side == 'long':
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current_rate = open_rate * (1 + curr_profit)
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stop = current_rate * (1 - stoploss)
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assert pytest.approx(stop) == open_rate * (1 + rel_stop)
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current_rate = open_rate * (1 + curr_profit / leverage)
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stop = current_rate * (1 - stoploss / leverage)
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assert pytest.approx(stop) == open_rate * (1 + rel_stop / leverage)
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else:
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current_rate = open_rate * (1 - curr_profit)
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stop = current_rate * (1 + stoploss)
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assert pytest.approx(stop) == open_rate * (1 - rel_stop)
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current_rate = open_rate * (1 - curr_profit / leverage)
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stop = current_rate * (1 + stoploss / leverage)
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assert pytest.approx(stop) == open_rate * (1 - rel_stop / leverage)
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def test_stoploss_from_absolute():
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