skfolio.distribution.empirical_tail_concentration#

skfolio.distribution.empirical_tail_concentration(X, quantiles)[source]#

Compute empirical tail concentration for the two variables in X. This function computes the concentration at each quantile provided.

The tail concentration are estimated as:
  • Lower tail: λ_L(q) = P(U₂ ≤ q | U₁ ≤ q)

  • Upper tail: λ_U(q) = P(U₂ ≥ q | U₁ ≥ q)

where U₁ and U₂ are the pseudo-observations.

Parameters:
Xarray-like of shape (n_observations, 2)

A 2D array with exactly 2 columns representing the pseudo-observations.

quantilesarray-like of shape (n_quantiles,)

A 1D array of quantile levels (values between 0 and 1) at which to compute the concentration.

Returns:
concentrationndarray of shape (n_quantiles,)

An array of empirical tail concentration values for the given quantiles.

Raises:
ValueError

If X is not a 2D array with exactly 2 columns or if quantiles are not in [0, 1].

References

[1]

“Quantitative Risk Management: Concepts, Techniques, and Tools”, McNeil, Frey, Embrechts (2005)