README.md

In yanyachen/FinCovRegularization: Covariance Matrix Estimation and Regularization for Finance

FinCovRegularization

Linux/Mac: Windows:

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")

yanyachen/FinCovRegularization documentation built on May 4, 2019, 2:30 p.m.