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

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  • Jiaqi Chen
  • Michael Tindall

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.

Suggested Citation

  • Jiaqi Chen & Michael Tindall, 2016. "Dynamic Methods for Analyzing Hedge-Fund Performance: A Note Using Texas Energy-Related Funds," Occasional Papers 16-2, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddop:2016_002
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    File URL: https://www.dallasfed.org/-/media/documents/banking/occasional/1602.pdf
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    1. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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    Keywords

    hidden Markov models; Kalman filter; Dynamic regression;

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