Trailing pct instead of ATR

[riodda]

Expected Behavior

Allow trailing with PRC instead of ATR

Actual Behavior

Currently the backtesting allow trailing sels only based on ATR, most of crypto bots works in pct trailing (pct for trailing activation and then pct trailing for position close).

[kernc]

This is the whole of TrailingStrategy:

backtesting.py/backtesting/lib.py

Lines 406 to 450 in 1ee5670

	class TrailingStrategy(Strategy):
	"""
	A strategy with automatic trailing stop-loss, trailing the current
	price at distance of some multiple of average true range (ATR). Call
	`TrailingStrategy.set_trailing_sl()` to set said multiple
	(`6` by default). See [tutorials] for usage examples.
	[tutorials]: index.html#tutorials
	Remember to call `super().init()` and `super().next()` in your
	overridden methods.
	"""
	__n_atr = 6.
	__atr = None
	def init(self):
	super().init()
	self.set_atr_periods()
	def set_atr_periods(self, periods: int = 100):
	"""
	Set the lookback period for computing ATR. The default value
	of 100 ensures a _stable_ ATR.
	"""
	h, l, c_prev = self.data.High, self.data.Low, pd.Series(self.data.Close).shift(1)
	tr = np.max([h - l, (c_prev - h).abs(), (c_prev - l).abs()], axis=0)
	atr = pd.Series(tr).rolling(periods).mean().bfill().values
	self.__atr = atr
	def set_trailing_sl(self, n_atr: float = 6):
	"""
	Sets the future trailing stop-loss as some multiple (`n_atr`)
	average true bar ranges away from the current price.
	"""
	self.__n_atr = n_atr
	def next(self):
	super().next()
	for trade in self.trades:
	if trade.is_long:
	trade.sl = max(trade.sl or -np.inf,
	self.data.Close[-1] - self.__atr[-1] * self.__n_atr)
	else:
	trade.sl = min(trade.sl or np.inf,
	self.data.Close[-1] + self.__atr[-1] * self.__n_atr)

It should be fairly simple to adapt/duplicate one for percent values.

[riodda]

Yup, the trailing strategy only supports ATR multiples, but most of the cyrpto bots trail in percentage would be nice to implement as option for trailing strategy so you can choose between ATR or pct for backtesting the best trailing.

[kernc]

As a quick workaround, something like this might work:

def pct_to_atr(pct: float, data: pd.DataFrame):
    """Express `pct` change in units of ATR."""
    assert 0 < pct < 1
    h, l, c_prev = data.High, data.Low, pd.Series(data.Close).shift(1) 
    tr = np.max([h - l, (c_prev - h).abs(), (c_prev - l).abs()], axis=0) 
    atr = np.nanmean(tr)
    return (pct * data.Close.iloc[-1]) / atr

[riodda]

Actually i would need the oppsite, as with backtesting i can find the optimal atr value for trailing the will have to calculate the equivalent pct for program the bot.
I'll find a solution, thanks anyway.

[kernc]

Should be rather easy to invert, something like:

def atr_to_pct(n_atr: float, data: pd.DataFrame):
    """Express `n_atr` in units of ATR as percentage of current price."""
    h, l, c_prev = data.High, data.Low, pd.Series(data.Close).shift(1) 
    tr = np.max([h - l, (c_prev - h).abs(), (c_prev - l).abs()], axis=0) 
    atr = np.nanmean(tr)
    return n_atr * atr / data.Close.iloc[-1]

[zlpatel]

I am working on this enhancement.