REN
Regularization Ensemble for Robust Portfolio Optimization
Portfolio optimization is achieved through a combination of regularization techniques and ensemble methods that are designed to generate stable out-of-sample return predictions, particularly in the presence of strong correlations among assets. The package includes functions for data preparation, parallel processing, and portfolio analysis using methods such as Mean-Variance, James-Stein, LASSO, Ridge Regression, and Equal Weighting. It also provides visualization tools and performance metrics, such as the Sharpe ratio, volatility, and maximum drawdown, to assess the results.
- Version0.1.0
- R version≥ 2.10
- LicenseAGPL (≥ 3)
- Needs compilation?No
- Last release10/10/2024
Documentation
Team
Bonsoo Koo
Hong Wang
Show author detailsRolesAuthorHardik Dixit
Show author detailsRolesAuthorShijia Wang
Show author detailsRolesAuthorCash Looi
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports10 packages
- Suggests5 packages