文章基本信息

标题：Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends
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作者：Jana Doering ; Renatas Kizys ; Angel A. Juan 等
期刊名称：Operations Research Perspectives
印刷版ISSN：2214-7160
电子版ISSN：2214-7160
出版年度：2019
卷号：6
页码：1-19
DOI：10.1016/j.orp.2019.100121
语种：English
出版社：Elsevier
摘要：Highlights•Reviews financial applications of metaheuristic algorithms.•Provides an updated review of rich portfolio optimization problems.•Provides an updated review of risk management problems.•Outlines future trends in applications of metaheuristics to finance.AbstractComputational finance is an emerging application field of metaheuristic algorithms. In particular, these optimisation methods are becoming the solving approach alternative when dealing with realistic versions of several decision-making problems in finance, such asrichportfolio optimisation and risk management. This paper reviews the scientific literature on the use of metaheuristics for solving NP-hard versions of these optimisation problems and illustrates their capacity to provide high-quality solutions under scenarios considering realistic constraints. The paper contributes to the existing literature in three ways. Firstly, it reviews the literature on metaheuristic optimisation applications for portfolio and risk management in a systematic way. Secondly, it identifies the linkages between portfolio optimisation and risk management and presents a unified view and classification of both problems. Finally, it outlines the trends that have gradually become apparent in the literature and will dominate future research in order to further improve the state-of-the-art in this knowledge area.
关键词：KeywordsPortfolio optimisationRisk managementCombinatorial optimisationMetaheuristics