Optimal Dynamic Futures Portfolio in a Regime-Switching Market Framework

TL;DR

This paper develops a stochastic framework for optimizing futures trading strategies in markets with regime switches, using Markov-modulated models and solving associated HJB equations to maximize utility.

Contribution

It introduces a novel utility maximization approach for dynamic futures trading in regime-switching markets, reducing complex HJB equations to linear ODEs for practical solutions.

Findings

Optimal futures positions vary across market regimes.

The framework applies to RS-GBM and RS-XOU models.

Numerical examples demonstrate strategy effectiveness.

Abstract

We study the problem of dynamically trading futures in a regime-switching market. Modeling the underlying asset price as a Markov-modulated diffusion process, we present a utility maximization approach to determine the optimal futures trading strategy. This leads to the analysis of the associated system of Hamilton-Jacobi-Bellman (HJB) equations, which are reduced to a system of linear ODEs. We apply our stochastic framework to two models, namely, the Regime-Switching Geometric Brownian Motion (RS-GBM) model and Regime-Switching Exponential Ornstein-Uhlenbeck (RS-XOU) model. Numerical examples are provided to illustrate the investor's optimal futures positions and portfolio value across market regimes.