Journal Article

Dynamic Methods for Analyzing Hedge-Fund Performance: A Note Using Texas Energy-Related Funds


Abstract: We apply dynamic regression to Texas energy-related hedge funds to track changes in portfolio structure and manager performance in response to changing oil prices. We apply hidden Markov models to compute shifts in portfolio performance from boom to bust states. Using these dynamic methods, we find that, in the recent oil-price decline, these funds raised their exposure to high-grade energy-related bonds in a bet that the spread to low-grade energy bonds would widen. When the high-grade bonds eventually fell, the hedge funds entered into a bust state.

Keywords: hidden Markov models; Kalman filter; Dynamic regression;

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Authors

    Chen, Jiaqi

    Tindall, Michael

Bibliographic Information

Provider: Federal Reserve Bank of Dallas

Part of Series: Occasional Papers

Publication Date: 2016-07-01

Pages: 13 pages

Order Number: 16-2