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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 gmail.com> |
BugReports: | http://github.com/yanyachen/FinCovRegularization/issues |
License: | GPL-2 |
URL: | http://github.com/yanyachen/FinCovRegularization |
NeedsCompilation: | no |
CRAN checks: | FinCovRegularization results |
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 |
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 imports: | bspcov |
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