cov_estim_efm: Exact Factor Model Covariance Estimation

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

Exact Factor Model Covariance Estimation

Description

Computes the Exact Factor Model (EFM) estimator of the covariance matrix.

Usage

cov_estim_efm(data, factors = NULL, zeromean_log = FALSE)

Arguments

data	an nxp data matrix.
factors	a nxf matrix with factors. Default value is NULL and the factor is equal to the cross-sectional average of all the variables in the data.
zeromean_log	a logical, indicating whether the data matrix has zero means (TRUE) or not (FALSE). Default value is FALSE.

Details

The EFM covariance estimator is calculated with the following formula:

\hat{\Sigma} = B\hat{\Sigma}_F B' + \hat{\Sigma_u},

where \hat{\Sigma}_F is the sample covariance matrix of the common factors and \hat{\Sigma}_u is the covariaance matrix of residuals, assumed to have zero correlation.

Value

a list with the following entries

• a pxp estimated covariance matrix.

• an estimation specific tuning parameter, here NA.

Examples

data(rets_m)
sigma_efm <- cov_estim_efm(rets_m)[[1]]

antshi/CovEstim documentation built on June 10, 2025, 3:11 a.m.