遗传算法

Burcu Adigüzel Mercangöz, Ergün Eroğlu
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引用次数: 2

摘要

投资组合优化是金融科学的一个重要研究领域。在投资组合优化问题中,其目的是从资产池中获得一定风险水平下的最佳收益,或者选择在一定收益水平下风险最低的资产来创建投资组合。投资组合的多样性提供了通过最小化风险来增加回报的机会。作为数学模型的有力替代,启发式方法被广泛应用于解决投资组合优化问题。遗传算法(GA)是一种受到生物进化启发的技术。虽然本书考虑了投资组合优化问题的启发式方法,但本章将给出遗传算法的实现步骤,并将该方法应用于一个基本示例中的投资组合优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Genetic Algorithm
The portfolio optimization is an important research field of the financial sciences. In portfolio optimization problems, it is aimed to create portfolios by giving the best return at a certain risk level from the asset pool or by selecting assets that give the lowest risk at a certain level of return. The diversity of the portfolio gives opportunity to increase the return by minimizing the risk. As a powerful alternative to the mathematical models, heuristics is used widely to solve the portfolio optimization problems. The genetic algorithm (GA) is a technique that is inspired by the biological evolution. While this book considers the heuristics methods for the portfolio optimization problems, this chapter will give the implementing steps of the GA clearly and apply this method to a portfolio optimization problem in a basic example.
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