Portfolio Optimization for Hedge Funds Through Time-Varying Coefficients

Abstract

In this paper, we show the interest of the time-varying coefficient model in hedge fund performance assessment and selection. We argue that the alpha of hedge funds is dynamic and that the time-varying alpha captures this dynamic behavior. Therefore, forming portfolios based on their time-varying alpha should lead to outperforming portfolios. Using a persistence analysis, we check this conjecture and show that contrary to top performers in terms of OLS alpha, the top performers in terms of past time-varying alpha generate superior and significant ex-post performance. Additionally, this analysis shows that persistence exists in the hedge fund industry and can be as long as 3 years.Secondly, building on the conclusion that the time-varying analysis gives a better picture of the alpha of the manager at a certain point in time, we use the timevarying analysis to obtain estimates of the expected returns of hedge funds. Using those estimates to construct a mean-variance optimal portfolio enhances the performance of this portfolio, suggesting that in terms of hedge fund performance detection, the time-varying model is superior to the OLS analysis.