sigma_estim_evc_bp: Eigenvalue Clipping Covariance Estimation (Bouchaud-Potters)

In antshi/CovEstim: (High-dimensional) Covariance Estimation

Description

Computes the eigenvalue clipping estimator of the covariance matrix with the Bouchaud-Potters technique.

Usage

sigma_estim_evc_bp(data, cut_edge)

Arguments

data	an nxp data matrix
cut_edge	a double, indicating the proportion for the applied eigenvalue clipping.

Details

The eigenvalue clipping covariance matrix estimator is computed with the following formula:

\hat{Σ}=Δ\hat{Λ}Δ',

where Δ is the matrix with the sample eigenvectors of the data matrix and \hat{Λ} is a diagonal matrix with the clipped sample eigenvalues. The clipping procedure follows \insertCitebouchaudpotters2009;textualCovEstim. In particular, the user-defined cutting edge s gives the proportion for the applied eigenvalue clipping so that the (1-s)\times p largest eigenvalues are kept and the remaining s\times p eigenvalues are substituted by their average.

Value

a list with the following entries

• a pxp estimated covariance matrix.

• an estimation specific tuning parameter, here the user-supplied cut edge.

References

\insertAllCited

Examples

data(sp200)
sp_rets <- sp200[,-1]
sigma_evc_bp <- sigma_estim_evc_bp(sp_rets, cut_edge=0.3)[[1]]

antshi/CovEstim documentation built on Nov. 13, 2020, 2:25 p.m.