IDEAS home Printed from https://ideas.repec.org/p/zbw/cfrwps/1007.html
   My bibliography  Save this paper

Do higher-moment equity risks explain hedge fund returns?

Author

Listed:
  • Agarwal, Vikas
  • Bakshi, Gurdip
  • Huij, Joop

Abstract

Hedge funds are fundamentally exposed to equity volatility, skewness, and kurtosis risks based on the systematic pattern and significant spread in alphas from the existing models that do not control for the higher-moment risks. The spread and pattern in alphas do not disappear with bootstrap simulation, Bayesian analysis to account for potential estimation error, adjustment for backfilling bias, and the inclusion of additional systematic factors. Significant cross-sectional variation in higher-moment exposures is observed across fund styles with equity-oriented styles displaying more extreme exposures. Investable higher-moment factors explain the time series behavior of returns of a large number of Managed Futures, Event Driven, and Long/Short Equity hedge funds. Average exposure sensitivities for higher-moment factors are statistically significant in an estimation that accounts for style fixed effects and fund random effects.

Suggested Citation

  • Agarwal, Vikas & Bakshi, Gurdip & Huij, Joop, 2009. "Do higher-moment equity risks explain hedge fund returns?," CFR Working Papers 10-07, University of Cologne, Centre for Financial Research (CFR).
  • Handle: RePEc:zbw:cfrwps:1007
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/41366/1/637040821.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark Britten‐Jones & Anthony Neuberger, 2000. "Option Prices, Implied Price Processes, and Stochastic Volatility," Journal of Finance, American Finance Association, vol. 55(2), pages 839-866, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Karagiorgis, Ariston & Drakos, Konstantinos, 2022. "The Skewness-Kurtosis plane for non-Gaussian systems: The case of hedge fund returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    2. Vikas Agarwal & Stefan Ruenzi & Florian Weigert, 2018. "Unobserved Performance of Hedge Funds," Working Papers on Finance 1825, University of St. Gallen, School of Finance.
    3. Elyasiani, Elyas & Gambarelli, Luca & Muzzioli, Silvia, 2020. "Moment risk premia and the cross-section of stock returns in the European stock market," Journal of Banking & Finance, Elsevier, vol. 111(C).
    4. Jozef Barunik & Josef Kurka, 2021. "Risks of heterogeneously persistent higher moments," Papers 2104.04264, arXiv.org, revised Mar 2024.
    5. Charles Chevalier & Serge Darolles, 2019. "Trends everywhere? The case of hedge fund styles," Journal of Asset Management, Palgrave Macmillan, vol. 20(6), pages 442-468, October.
    6. Subbiah, Mohan & Fabozzi, Frank J., 2016. "Hedge fund allocation: Evaluating parametric and nonparametric forecasts using alternative portfolio construction techniques," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 189-201.
    7. Andrea J. Heuson & Mark C. Hutchinson & Alok Kumar, 2020. "Predicting hedge fund performance when fund returns are skewed," Financial Management, Financial Management Association International, vol. 49(4), pages 877-896, December.
    8. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    9. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    10. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2016. "Moment Risk Premia and the Cross-Section of Stock Returns," Department of Economics 0103, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    11. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2012. "Systematic risk and the cross section of hedge fund returns," Journal of Financial Economics, Elsevier, vol. 106(1), pages 114-131.
    12. Agarwal, Vikas & Green, Tracy Clifton & Ren, Honglin, 2017. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," CFR Working Papers 15-08, University of Cologne, Centre for Financial Research (CFR), revised 2017.
    13. Agarwal, Vikas & Ruenzi, Stefan & Weigert, Florian, 2017. "Tail risk in hedge funds: A unique view from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 125(3), pages 610-636.
    14. Agarwal, Vikas & Green, T. Clifton & Ren, Honglin, 2018. "Alpha or beta in the eye of the beholder: What drives hedge fund flows?," Journal of Financial Economics, Elsevier, vol. 127(3), pages 417-434.
    15. Bali, Turan G. & Brown, Stephen J. & Caglayan, Mustafa Onur, 2011. "Do hedge funds' exposures to risk factors predict their future returns?," Journal of Financial Economics, Elsevier, vol. 101(1), pages 36-68, July.
    16. Paul Karehnke & Frans de Roon, 2020. "Spanning Tests for Assets with Option-Like Payoffs: The Case of Hedge Funds," Management Science, INFORMS, vol. 66(12), pages 5969-5989, December.
    17. Lambert, Marie & Fays, Boris & Hübner, Georges, 2020. "Factoring characteristics into returns: A clinical study on the SMB and HML portfolio construction methods," Journal of Banking & Finance, Elsevier, vol. 114(C).
    18. Yang, Huan & Cai, Jun & Huang, Lin & Marcus, Alan J., 2021. "Bank stocks, risk factors, and tail behavior," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 203-229.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bruno Feunou & Jean-Sébastien Fontaine & Abderrahim Taamouti & Roméo Tédongap, 2014. "Risk Premium, Variance Premium, and the Maturity Structure of Uncertainty," Review of Finance, European Finance Association, vol. 18(1), pages 219-269.
    2. Peter Carr & Liuren Wu, 2014. "Static Hedging of Standard Options," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 3-46.
    3. Toshiaki Ogawa & Masato Ubukata & Toshiaki Watanabe, 2020. "Stock Return Predictability and Variance Risk Premia around the ZLB," IMES Discussion Paper Series 20-E-09, Institute for Monetary and Economic Studies, Bank of Japan.
    4. Marins, Jaqueline Terra Moura & Vicente, José Valentim Machado, 2017. "Do the central bank actions reduce interest rate volatility?," Economic Modelling, Elsevier, vol. 65(C), pages 129-137.
    5. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    6. Geert Bekaert & Eric Engstrom, 2017. "Asset Return Dynamics under Habits and Bad Environment-Good Environment Fundamentals," Journal of Political Economy, University of Chicago Press, vol. 125(3), pages 713-760.
    7. Damiano Brigo, 2008. "The general mixture-diffusion SDE and its relationship with an uncertain-volatility option model with volatility-asset decorrelation," Papers 0812.4052, arXiv.org.
    8. Maneesoonthorn, Worapree & Martin, Gael M. & Forbes, Catherine S. & Grose, Simone D., 2012. "Probabilistic forecasts of volatility and its risk premia," Journal of Econometrics, Elsevier, vol. 171(2), pages 217-236.
    9. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    10. Fong, Wai Mun, 2013. "Footprints in the market: Hedge funds and the carry trade," Journal of International Money and Finance, Elsevier, vol. 33(C), pages 41-59.
    11. Turan G. Bali & Hao Zhou, 2011. "Risk, uncertainty, and expected returns," Finance and Economics Discussion Series 2011-45, Board of Governors of the Federal Reserve System (U.S.).
    12. Yang-Ho Park, 2013. "Volatility of volatility and tail risk premiums," Finance and Economics Discussion Series 2013-54, Board of Governors of the Federal Reserve System (U.S.).
    13. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    14. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    15. Ammann, Manuel & Buesser, Ralf, 2013. "Variance risk premiums in foreign exchange markets," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 16-32.
    16. Jin-Chuan Duan & Weiqi Zhang, 2014. "Forward-Looking Market Risk Premium," Management Science, INFORMS, vol. 60(2), pages 521-538, February.
    17. Peter Van Tassel, 2020. "The Law of One Price in Equity Volatility Markets," Staff Reports 953, Federal Reserve Bank of New York.
    18. Masato Ubukata & Toshiaki Watanabe, 2011. "Market Variance Risk Premiums in Japan as Predictor Variables and Indicators of Risk Aversion," Global COE Hi-Stat Discussion Paper Series gd11-214, Institute of Economic Research, Hitotsubashi University.
    19. Wang, Hao & Zhou, Hao & Zhou, Yi, 2013. "Credit default swap spreads and variance risk premia," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3733-3746.
    20. Wael Bahsoun & Pawel Góra & Silvia Mayoral & Manuel Morales, 2006. "Random Dynamics and Finance: Constructing Implied Binomial Trees from a Predetermined Stationary Den," Faculty Working Papers 13/06, School of Economics and Business Administration, University of Navarra.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:cfrwps:1007. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/cfkoede.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.