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基于广义熵投资组合优化的期权投资组合选择

Option Portfolio Selection with Generalized Entropic Portfolio Optimization.

作者信息

Mercurio Peter Joseph, Wu Yuehua, Xie Hong

机构信息

Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada.

Manulife Financial Corp, Toronto, ON M4W 1E5, Canada.

出版信息

Entropy (Basel). 2020 Jul 22;22(8):805. doi: 10.3390/e22080805.

Abstract

In this third and final paper of our series on the topic of portfolio optimization, we introduce a further generalized portfolio selection method called generalized entropic portfolio optimization (GEPO). GEPO extends discrete entropic portfolio optimization (DEPO) to include intervals of continuous returns, with direct application to a wide range of option strategies. This lays the groundwork for an adaptable optimization framework that can accommodate a wealth of option portfolios, including popular strategies such as covered calls, married puts, credit spreads, straddles, strangles, butterfly spreads, and even iron condors. These option strategies exhibit mixed returns: a combination of discrete and continuous returns with performance best measured by portfolio growth rate, making entropic portfolio optimization an ideal method for option portfolio selection. GEPO provides the mathematical tools to select efficient option portfolios based on their growth rate and relative entropy. We provide an example of GEPO applied to real market option portfolio selection and demonstrate how GEPO outperforms traditional Kelly criterion strategies.

摘要

在我们关于投资组合优化主题的系列论文的第三篇也是最后一篇中,我们介绍了一种进一步广义化的投资组合选择方法,称为广义熵投资组合优化(GEPO)。GEPO将离散熵投资组合优化(DEPO)扩展到包括连续收益区间,可直接应用于广泛的期权策略。这为一个适应性强的优化框架奠定了基础,该框架能够容纳大量的期权投资组合,包括诸如备兑认购期权、保护性看跌期权、信用价差、跨式期权、勒式期权、蝶式价差,甚至铁鹰式期权等流行策略。这些期权策略呈现出混合收益:离散收益和连续收益的组合,其表现最好用投资组合增长率来衡量,这使得熵投资组合优化成为期权投资组合选择的理想方法。GEPO提供了基于增长率和相对熵来选择有效期权投资组合的数学工具。我们给出了一个GEPO应用于实际市场期权投资组合选择的例子,并展示了GEPO如何优于传统的凯利准则策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b46/7517377/e115741e1273/entropy-22-00805-g001.jpg

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