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