A Maximum Entropy Method for a Robust Portfolio Problem

Abstract

We propose a continuous maximum entropy method to investigate the robust optimal portfolio selection problem for the market with transaction costs and dividends. This robust model aims to maximize the worst-case portfolio return in the case that all of asset returns lie within some prescribed intervals. A numerical optimal solution to the problem is obtained by using a continuous maximum entropy method. Furthermore, some numerical experiments indicate that the robust model in this paper can result in better portfolio performance than a classical mean-variance model.

An Entropy-Based Approach to Portfolio Optimization

“…These methods do not use the joint entropy, as they deal only with the one-dimensional entropy of the portfolio weights vector. A maximum entropy method was proposed by Xu (2014) [ 50 ] that aimed to maximize the worst-case portfolio returns. In recent years, entropy was used to evaluate tail risks by Geman (2015) [ 51 ].…”

Optimal portfolio of continuous‐time mean‐variance model with futures and options

“…(iii)û 2 (t) ≤ 0 From (34), it is obtained that γ 1 ≥ γ 2 . From (22), we find the minimum of f(u(t)) by comparing the minimum of f 2 (u(t)) or f 1 (u(t)) while u 2 (t) = 0 with the minimum of f 1 (u(t)) under no constraints. It is obtained that the minimum of f 2 (u(t)) or f 1 (u(t)) while u 2 (t) = 0 is greater than the minimum of f 2 (u(t)) under no constraints.…”

Predicting the Outcome of NBA Playoffs Based on Maximum Entropy Principle

“…Tseng and Tuszynski [19] gave several examples of applications of maximum entropy in different stages of drug discovery. Xu et al [20] proposed a continuous maximum entropy method to investigate the robust optimal portfolio selection problem for the market with transaction costs and dividends. Berger et al [21] described statistical modeling based on maximum entropy and used the model to solve natural language processing problems.…”