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
Author: YaChen Yan [aut, cre], FangZhu Lin [aut]
Maintainer: YaChen Yan <yanyachen21 at gmail.com>
BugReports: http://github.com/yanyachen/FinCovRegularization/issues
License: GPL-2
URL: http://github.com/yanyachen/FinCovRegularization
NeedsCompilation: no
CRAN checks: FinCovRegularization results

Downloads:

Reference manual: FinCovRegularization.pdf
Package source: FinCovRegularization_1.1.0.tar.gz
Windows binaries: r-devel: FinCovRegularization_1.1.0.zip, r-release: FinCovRegularization_1.1.0.zip, r-oldrel: FinCovRegularization_1.1.0.zip
OS X binaries: r-release: FinCovRegularization_1.1.0.tgz, r-oldrel: FinCovRegularization_1.1.0.tgz
Old sources: FinCovRegularization archive

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