fynance.algorithms.allocation.IVP

fynance.algorithms.allocation.IVP(X, normalize=False, low_bound=0.0, up_bound=1.0)

Get weights of the Inverse Variance Portfolio allocation.

Parameters:

X : array_like

Each column is a price or return’s asset series.

normalize : bool, optional

If True normalize the weights such that \(\sum_{i=1}^{N} w_i = 1\) and \(0 \leq w_i \leq 1\). Default is False.

low_bound, up_bound : float, optional

Respectively minimum and maximum values of weights, such that low_bound \(\leq w_i \leq\) up_bound \(\forall i\). Default is 0 and 1.

Returns:

np.ndarray

Vector of weights computed by the IVP algorithm.

Notes

w are computed by the inverse of the asset’s variance [3] such that:

\[w_i = \frac{1}{\sigma_k^2} (\sum_{i} \frac{1}{\sigma_i^2})^{-1}\]

With \(\sigma_i^2\) is the variance of asset i.

References

[3]	https://en.wikipedia.org/wiki/Inverse-variance_weighting