投资组合选择中的均值-方差和均值- etl优化：更新

IF 4.4 3区管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Annals of Operations Research Pub Date : 2024-10-21 DOI:10.1007/s10479-024-06337-2

Barret Pengyuan Shao, John B. Guerard Jr., Ganlin Xu

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引用次数: 0

摘要

在本研究更新中，我们将均值-方差（MV）和均值-期望尾部损失（ETL）投资组合优化技术应用于收益预测和基于稳健回归的复合模型。采用多变量正态回火稳定（MNTS）创新的时间序列模型生成样本外情景，用于投资组合优化。我们报告(1)分析师预测、修正和修正方向的复合变量在投资组合构建中继续产生价值；(2)稳健回归模型持续产生有意义的主动收益；(3) Mean-Variance和Mean-ETL组合优化通过Markowitz和Xu （Journal of portfolio Management, 1994, 21:1-60）数据挖掘修正检验，产生统计显著的主动收益。

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Mean-variance and mean-ETL optimizations in portfolio selection: an update

In this research update, we apply the Mean-Variance (MV) and Mean-Expected Tail Loss (ETL) portfolio optimization techniques on earnings forecasting and robust regression-based composite models. A time series model with multivariate normal tempered stable (MNTS) innovations is applied to generate the out-of-sample scenarios for the portfolio optimization. We report that (1) a composite variable of analysts’ forecasts, revisions, and direction of analysts’ revisions continues to produce value in portfolio construction; (2) robust regression-based models continue to produce meaningful active returns; and (3) the Mean-Variance and Mean-ETL portfolio optimizations produce statistically significant active returns, passing the Markowitz and Xu (Journal of Portfolio Management 21:1–60, 1994) data mining corrections test.

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来源期刊

Annals of Operations Research 管理科学-运筹学与管理科学

CiteScore

7.90

自引率

16.70%

发文量

596

审稿时长

8.4 months

期刊介绍： The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications. In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.