Heuristic portfolio optimisation for a hedge fund strategy using the Geometric Nelder-Mead Algorithm

A. Alentorn, A. Moraglio, Colin Johnson
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引用次数: 2

Abstract

This paper presents a framework for heuristic portfolio optimisation applied to a hedge fund investment strategy. The first contribution of the paper is to present a framework for implementing portfolio optimisation of a market neutral hedge fund strategy. The paper also illustrates the application of the recently developed Geometric Nelder-Mead Algorithm (GNMA) in solving this real world optimization problem, compared with a Genetic Algorithm (GA) approach.
基于几何Nelder-Mead算法的对冲基金启发式投资组合优化
本文提出了一个应用于对冲基金投资策略的启发式投资组合优化框架。本文的第一个贡献是提出了实施市场中性对冲基金策略的投资组合优化的框架。本文还举例说明了最近发展的几何Nelder-Mead算法(GNMA)在解决实际优化问题中的应用,并与遗传算法(GA)方法进行了比较。
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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