Regularization of Portfolio Allocation

Benjamin Bruder, Nicolas Gaussel, J. Richard, T. Roncalli
{"title":"Regularization of Portfolio Allocation","authors":"Benjamin Bruder, Nicolas Gaussel, J. Richard, T. Roncalli","doi":"10.2139/ssrn.2767358","DOIUrl":null,"url":null,"abstract":"The mean-variance optimization (MVO) theory of Markowitz (1952) for portfolio selection is one of the most important methods used in quantitative finance. This portfolio allocation needs two input parameters, the vector of expected returns and the covariance matrix of asset returns. This process leads to estimation errors, which may have a large impact on portfolio weights. In this paper we review different methods which aim to stabilize the mean-variance allocation. In particular, we consider recent results from machine learning theory to obtain more robust allocation.","PeriodicalId":106740,"journal":{"name":"ERN: Other Econometrics: Econometric Model Construction","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Econometric Model Construction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2767358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

Abstract

The mean-variance optimization (MVO) theory of Markowitz (1952) for portfolio selection is one of the most important methods used in quantitative finance. This portfolio allocation needs two input parameters, the vector of expected returns and the covariance matrix of asset returns. This process leads to estimation errors, which may have a large impact on portfolio weights. In this paper we review different methods which aim to stabilize the mean-variance allocation. In particular, we consider recent results from machine learning theory to obtain more robust allocation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
投资组合配置的正则化
马科维茨(1952)的投资组合均值方差优化(MVO)理论是定量金融中最重要的方法之一。这种投资组合配置需要两个输入参数,即预期收益向量和资产收益协方差矩阵。这个过程会导致估计错误,这可能会对投资组合的权重产生很大的影响。本文综述了旨在稳定均值-方差分配的各种方法。特别是,我们考虑了机器学习理论的最新结果,以获得更稳健的分配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Rank Determination in Tensor Factor Model A Toolkit for Robust Risk Assessment Using F-Divergences One-factor Hull-White Model Calibration for CVA - Part I: Instrument Selection With a Kink High-Dimensional Granger Causality Tests with an Application to VIX and News Selective Linear Segmentation For Detecting Relevant Parameter Changes
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1