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:
FinCovRegularization_1.1.0.tar.gz
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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')) |
Bug tracker:https://github.com/yanyachen/fincovregularization/issues
- m.excess.c10sp9003 - 10 stock and S&P 500 excess returns
Last updated 8 years agofrom:cd3ff5b5d0. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 29 2024 |
| R-4.5-win | NOTE | Oct 29 2024 |
| R-4.5-linux | NOTE | Oct 29 2024 |
| R-4.4-win | NOTE | Oct 29 2024 |
| R-4.4-mac | NOTE | Oct 29 2024 |
| R-4.3-win | NOTE | Oct 29 2024 |
| R-4.3-mac | NOTE | Oct 29 2024 |
Exports:bandingbanding.cvF.norm2FundamentalFactor.CovGMVPhard.thresholdingInd.CovMacroFactor.CovO.norm2RiskParitysoft.thresholdingStatFactor.Covtaperingtapering.cvthreshold.cvthreshold.min
Dependencies:quadprog
