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Hedge fund contagion and risk-adjusted returns: A Markov-switching dynamic factor approach

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  • Akay, Ozgur (Ozzy)
  • Senyuz, Zeynep
  • Yoldas, Emre

Abstract

We provide an empirical analysis of two important phenomena influencing the hedge fund industry—contagion and time variation in risk adjusted return (alpha)—in a flexible unified framework. After accounting for standard hedge fund pricing factors, we quantify the common latent factor in hedge fund style index returns and model its time-varying behavior using a dynamic factor framework featuring Markov regime-switching. We find that three regimes—crash, low mean and high mean—are necessary to provide a complete description of joint hedge fund return dynamics. We also document significant time variation in the alpha generating ability of all hedge fund investment styles. The period following the stock market crash of 2000 is dominated by the persistent low return state while the long bull market of 1990s is associated with the strongest performance of the industry generating high positive returns. We also investigate drivers of the regime shifts in the common latent pricing factor and find that both flight to safety and large funding liquidity shocks play an important role in explaining the abrupt shift of the common factor to the crash state.

Suggested Citation

  • Akay, Ozgur (Ozzy) & Senyuz, Zeynep & Yoldas, Emre, 2013. "Hedge fund contagion and risk-adjusted returns: A Markov-switching dynamic factor approach," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 16-29.
  • Handle: RePEc:eee:empfin:v:22:y:2013:i:c:p:16-29
    DOI: 10.1016/j.jempfin.2013.02.005
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    Cited by:

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    3. Mardi Dungey & Eric Renault, 2018. "Identifying contagion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 227-250, March.
    4. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    5. Doina PRODAN-PALADE, 2017. "Bankruptcy risk prediction models based on artificial neural networks," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 15(147), pages 418-418.
    6. Hamed Amini & Andreea Minca, 2014. "Inhomogeneous Financial Networks and Contagious Links," Working Papers hal-01081559, HAL.
    7. Bussière, Matthieu & Hoerova, Marie & Klaus, Benjamin, 2015. "Commonality in hedge fund returns: Driving factors and implications," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 266-280.
    8. Rama Cont & Andreea Minca, 2016. "Credit default swaps and systemic risk," Annals of Operations Research, Springer, vol. 247(2), pages 523-547, December.
    9. Tareq Saeed & Elie Bouri & Dang Khoa Tran, 2020. "Hedging Strategies of Green Assets against Dirty Energy Assets," Energies, MDPI, Open Access Journal, vol. 13(12), pages 1-17, June.
    10. Aristeidis, Samitas & Elias, Kampouris, 2018. "Empirical analysis of market reactions to the UK’s referendum results – How strong will Brexit be?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 53(C), pages 263-286.
    11. Stafylas, Dimitrios & Anderson, Keith & Uddin, Moshfique, 2017. "Recent advances in explaining hedge fund returns: Implicit factors and exposures," Global Finance Journal, Elsevier, vol. 33(C), pages 69-87.

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    More about this item

    Keywords

    Hedge fund; Contagion; Risk-adjusted return; Dynamic factor models; Funding liquidity; Flight to safety;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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