Package: FinCovRegularization 1.1.0

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.

Authors:YaChen Yan [aut, cre], FangZhu Lin [aut]

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FinCovRegularization.pdf |FinCovRegularization.html
FinCovRegularization/json (API)

# Install 'FinCovRegularization' in R:
install.packages('FinCovRegularization', repos = c('https://yanyachen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/yanyachen/fincovregularization/issues

Datasets:

On CRAN:

4.30 score 7 stars 1 packages 19 scripts 209 downloads 16 exports 1 dependencies

Last updated 8 years agofrom:cd3ff5b5d0. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 27 2025
R-4.5-winNOTEJan 27 2025
R-4.5-macNOTEJan 27 2025
R-4.5-linuxNOTEJan 27 2025
R-4.4-winNOTEJan 27 2025
R-4.4-macNOTEJan 27 2025
R-4.3-winNOTEJan 27 2025
R-4.3-macNOTEJan 27 2025

Exports:bandingbanding.cvF.norm2FundamentalFactor.CovGMVPhard.thresholdingInd.CovMacroFactor.CovO.norm2RiskParitysoft.thresholdingStatFactor.Covtaperingtapering.cvthreshold.cvthreshold.min

Dependencies:quadprog