Linux/Mac:
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.
- Covariance Estimation:
macroeconomic factor model, fundamental factor model and statistical factor model - Covariance Regularization:
banding, tapering, hard-thresholding, soft-thresholding - Portfolio Optimization:
global mimnum variance portfolio, risk parity portfolio
To install:
- the stable version from CRAN:
install.packages("FinCovRegularization")- the latest development version:
devtools::install_github("yanyachen/FinCovRegularization")