FinCovRegularization: Covariance Matrix Estimation and Regularization for Finance

Estimation and regularization for covariance matrix of asset returns. For covariance matrix estimation, three major types of factor models are included: macroeconomic factor model, fundamental factor model and statistical factor model. For covariance matrix regularization, four regularized estimators are included: banding, tapering, hard-thresholding and soft- thresholding. The tuning parameters of these regularized estimators are selected via cross-validation.

Version: 1.1.0
Depends: R (≥ 2.10)
Imports: stats, graphics, quadprog
Published: 2016-04-25
DOI: 10.32614/CRAN.package.FinCovRegularization
Author: YaChen Yan [aut, cre], FangZhu Lin [aut]
Maintainer: YaChen Yan <yanyachen21 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: FinCovRegularization results


Reference manual: FinCovRegularization.pdf


Package source: FinCovRegularization_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): FinCovRegularization_1.1.0.tgz, r-oldrel (arm64): FinCovRegularization_1.1.0.tgz, r-release (x86_64): FinCovRegularization_1.1.0.tgz, r-oldrel (x86_64): FinCovRegularization_1.1.0.tgz
Old sources: FinCovRegularization archive

Reverse dependencies:

Reverse imports: bspcov


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