Option Portfolio Selection with Generalized Entropic Portfolio Optimization.

Peter Joseph Mercurio, Yuehua Wu, Hong Xie
Author Information
  1. Peter Joseph Mercurio: Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada. ORCID
  2. Yuehua Wu: Department of Mathematics and Statistics, York University, Toronto, ON M3J 1P3, Canada. ORCID
  3. Hong Xie: Manulife Financial Corp, Toronto, ON M4W 1E5, Canada.

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.

Keywords

References

  1. Entropy (Basel). 2020 Mar 14;22(3): [PMID: 33286106]
  2. Entropy (Basel). 2020 Jul 09;22(7): [PMID: 33286524]

Grants

  1. 0000000000/Natural Sciences and Engineering Research Council of Canada

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