fynance.algorithms.allocation.HRP¶

fynance.algorithms.allocation.HRP(X, method='single', metric='euclidean', low_bound=0.0, up_bound=1.0)¶

Get weights of the Hierarchical Risk Parity allocation.

Parameters:

Parameters:	X : array_like Each column is a price or return’s asset series. Some errors will happen if one or more series are constant. method, metric: str Parameters for linkage algorithm, default `method='single'` and `metric='euclidean'`. low_bound, up_bound : float Respectively minimum and maximum value of weights, such that low_bound \(\leq w_i \leq\) up_bound \(\forall i\). Default is 0 and 1.
Returns:	np.ndarray Vecotr of weights computed by HRP algorithm.

X : array_like: Each column is a price or return’s asset series. Some errors will happen if one or more series are constant.
method, metric: str: Parameters for linkage algorithm, default method='single' and metric='euclidean'.
low_bound, up_bound : float: Respectively minimum and maximum value of weights, such that low_bound \(\leq w_i \leq\) up_bound \(\forall i\). Default is 0 and 1.

Returns:

Notes

Hierarchical Risk Parity algorithm is developed by Marco Lopez de Prado [2]. First step is clustering and second step is allocating weights.

References

[2]	https://ssrn.com/abstract=2708678