FinCovRegularization: FinCovRegularization: Covariance Matrix Estimation and...
In yanyachen/FinCovRegularization: Covariance Matrix Estimation and Regularization for Finance
Description
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.
yanyachen/FinCovRegularization documentation built on May 4, 2019, 2:30 p.m.
R Package Documentation
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Description
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.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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