fynance.features.metrics.roll_mdd

fynance.features.metrics.roll_mdd(X, w=None, raw=False, axis=0, dtype=None)

Compute the rolling maximum drawdown for each X’ series.

Where drawdown is the measure of the decline from a historical peak in some variable [5] (typically the cumulative profit or total open equity of a financial trading strategy).

Parameters:

X : np.ndarray[dtype, ndim=1 or 2]

Time series (price, performance or index).

w : int, optional

Size of the lagged window of the rolling function, must be positive. If w is None or w=0, then w=X.shape[axis]. Default is None.

raw : bool, optional

• If True then compute the raw drawdown.
• Else (default) compute the drawdown in percentage.

axis : {0, 1}, optional

Axis along wich the computation is done. Default is 0.

dtype : np.dtype, optional

The type of the output array. If dtype is not given, infer the data type from X input.

Returns:

np.ndrray[dtype, ndim=1 or 2]

Series of rolling maximum drawdown for each series.

See also

mdd, roll_calmar, roll_sharpe, drawdown

References

[5]	https://www.investopedia.com/terms/m/maximum-drawdown-mdd.asp

Examples

>>> X = np.array([70, 100, 80, 120, 160, 80])
>>> roll_mdd(X, dtype=np.float64)
array([0. , 0. , 0.2, 0.2, 0.2, 0.5])
>>> roll_mdd(X, w=3, dtype=np.float64)
array([0. , 0. , 0.2, 0.2, 0. , 0.5])
>>> X = np.array([100, 80, 70, 75, 110, 80]).astype(np.float64)
>>> roll_mdd(X, raw=True, w=3, dtype=np.float64)
array([ 0., 20., 30., 10.,  0., 30.])