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REN  

Regularization Ensemble for Robust Portfolio Optimization
View on CRAN: Click here


Download and install REN package within the R console
Install from CRAN:
install.packages("REN")

Install from Github:
library("remotes")
install_github("cran/REN")

Install by package version:
library("remotes")
install_version("REN", "0.1.0")



Attach the package and use:
library("REN")
Maintained by
Bonsoo Koo
[Scholar Profile | Author Map]
First Published: 2024-10-10
Latest Update: 2024-10-10
Description:
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.
How to cite:
Bonsoo Koo (2024). REN: Regularization Ensemble for Robust Portfolio Optimization. R package version 0.1.0, https://cran.r-project.org/web/packages/REN. Accessed 01 May. 2025.
Previous versions and publish date:
No previous versions
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View REN citation profile
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Complete documentation for REN
Functions, R codes and Examples using the REN R package
Full REN package functions and examples
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