IVP

Defined in fynance.portfolio.allocation

IVP(X, normalize=False, low_bound=0., up_bound=1.0)

Get weights of the Inverse Variance Portfolio allocation.

Parameters:

Xarray_like

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

normalizebool, optional

If True clip the weights to the [low_bound, up_bound] box and renormalize them to sum to one (via _normalize), preserving the inverse-variance ordering. If False (default) return the raw inverse-variance weights \(w_i \propto 1 / \sigma_i^2\), which already sum to one and lie in \([0, 1]\).

low_bound, up_boundfloat, 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