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
This package has been downloaded 131 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 891 times in the last 365 days. Not bad! The download count is somewhere between 'small-town buzz' and 'moderate academic conference'. The day with the most downloads was Oct 11, 2024 with 40 downloads.
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