A Portfolio Optimization Model with Regime-Switching Risk Factors for Sector Exchange Traded Funds

This paper develops a portfolio optimization model with a market neutral strategy under a Markov regime-switching framework. The selected investment instruments consist of the nine sector exchange traded funds (ETFs) that represent the U.S. stock market. The Bayesian information criterion is used to determine the optimal number of regimes. The investment objective is to dynamically maximize the portfolio alpha (excess return over the T-Bill) subject to neutralization of the portfolio sensitivities to the selected risk factors. The portfolio risk exposures are shown to change with various style and macro factors over time. The maximization problem in this context can be established as a regime-dependent linear programming problem. The optimal portfolio constructed as such is expected to outperform a naive benchmark strategy, which equally weights the ETFs. We evaluate the in-sample and out-of-sample performance of the regime-dependent market neutral strategy against the equally weighted strategy. We find that the former generally outperforms the latter.

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