投资组合优化
稳健性(进化)
文件夹
稳健优化
计算机科学
估计员
数学优化
现代投资组合理论
后现代投资组合理论
复制投资组合
经济
数学
金融经济学
生物化学
化学
统计
基因
作者
Jang Ho Kim,Woo Chang Kim,Yong Jae Lee,Byung-Uk Choi,Frank J. Fabozzi
标识
DOI:10.3905/jpm.2023.1.522
摘要
Portfolio optimization is the basic quantitative approach for finding optimal portfolio weights. It has become increasingly important as portfolio construction involves more and more data and automated approaches. The inherent uncertainty in financial markets has led to consistent demand for improved robustness of portfolio models. In this article, the authors discuss the importance of robustness in portfolio optimization and present powerful methods that include robust estimators, robust portfolio optimization, distributionally robust optimization, and scenario-based optimization. They also review data-driven methods, machine learning–based models, and practical approaches for improving portfolio robustness.
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