Multi-period mean-variance portfolio selection with practical constraints using heuristic genetic algorithms

IF 0.4 Q4 ECONOMICS

International Journal of Computational Economics and Econometrics Pub Date : 2020-06-10 DOI:10.1504/ijcee.2020.10029943

Y. Chen, Hao Yang

引用次数: 2

Abstract

Since Markowitz proposed the mean-variance (MV) formulation in 1952, it has been used to configure various portfolio selection problems. However Markowitz's solution is only for a single period. Multi-period portfolio selection problems have been studied for a long time but most solutions depend on various forms of utility function, which are unfamiliar to general investors. Some works have formulated the problems as MV models and solved them analytically in closed form subject to certain assumptions. Unlike analytical solutions, genetic algorithms (GA) are more flexible because they can solve problems without restrictive assumptions. The purpose of this paper is to formulate multi-period portfolio selection problems as MV models and solve them by GA. To illustrate the generality of our algorithm, we implement a program by Microsoft Visual Studio to solve a multi-period portfolio selection problem for which there exists no general analytical solution.

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基于启发式遗传算法的具有实际约束的多期均值方差投资组合选择

自1952年Markowitz提出均值方差（MV）公式以来，它已被用于配置各种投资组合选择问题。然而，Markowitz的解决方案只针对一个时期。多期投资组合选择问题已经研究了很长时间，但大多数解决方案都依赖于各种形式的效用函数，这对普通投资者来说是陌生的。一些工作将这些问题公式化为MV模型，并在一定假设下以封闭形式解析求解。与分析解不同，遗传算法更灵活，因为它们可以在没有限制性假设的情况下解决问题。本文的目的是将多期投资组合选择问题公式化为MV模型，并用GA进行求解。为了说明我们算法的通用性，我们用Microsoft Visual Studio实现了一个程序来解决一个没有通用分析解的多期投资组选问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Computational Economics and Econometrics ECONOMICS-

CiteScore

0.60

自引率

0.00%

发文量

期刊介绍： IJCEE explores the intersection of economics, econometrics and computation. It investigates the application of recent computational techniques to all branches of economic modelling, both theoretical and empirical. IJCEE aims at an international and multidisciplinary standing, promoting rigorous quantitative examination of relevant economic issues and policy analyses. The journal''s research areas include computational economic modelling, computational econometrics and statistics and simulation methods. It is an internationally competitive, peer-reviewed journal dedicated to stimulating discussion at the forefront of economic and econometric research. Topics covered include: -Computational Economics: Computational techniques applied to economic problems and policies, Agent-based modelling, Control and game theory, General equilibrium models, Optimisation methods, Economic dynamics, Software development and implementation, -Econometrics: Applied micro and macro econometrics, Monte Carlo simulation, Robustness and sensitivity analysis, Bayesian econometrics, Time series analysis and forecasting techniques, Operational research methods with applications to economics, Software development and implementation.