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cff-version: 1.2.0
message: 'To cite package "REN" in publications use:'
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license: AGPL-3.0-or-later
title: 'REN: Regularization Ensemble for Robust Portfolio Optimization'
version: 0.1.0
doi: 10.32614/CRAN.package.REN
abstract: 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.
authors:
- family-names: Dixit
  given-names: Hardik
- family-names: Wang
  given-names: Shijia
- family-names: Koo
  given-names: Bonsoo
  email: bonsoo.koo@monash.edu
- family-names: Looi
  given-names: Cash
- family-names: Wang
  given-names: Hong
repository: https://CRAN.R-project.org/package=REN
date-released: '2024-10-10'
contact:
- family-names: Koo
  given-names: Bonsoo
  email: bonsoo.koo@monash.edu