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Volatility Feedback and Risk Premium in GARCH Models with Generalized Hyperbolic Distributions

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  • Yang Minxian

    (The University of New South Wales)

Abstract

The mixture structure of the generalized hyperbolic distribution of Barndorff-Nielsen (1997) is explored to quantify the contemporaneous correlation between return and volatility and to identify the effects of volatility feedback and risk premium within GARCH models. The statistical analysis of the excess returns based on the CRSP value-weighted portfolio index supports both volatility feedback and risk premium theories.

Suggested Citation

  • Yang Minxian, 2011. "Volatility Feedback and Risk Premium in GARCH Models with Generalized Hyperbolic Distributions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-21, May.
    • Handle: RePEc:bpj:sndecm:v:15:y:2011:i:3:n:6
    DOI: 10.2202/1558-3708.1820
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    Cited by:

    1. Wang, Jianxin & Yang, Minxian, 2013. "On the risk return relationship," Journal of Empirical Finance, Elsevier, vol. 21(C), pages 132-141.
    2. Suzanne G. M. Fifield & David G. McMillan & Fiona J. McMillan, 2020. "Is there a risk and return relation?," The European Journal of Finance, Taylor & Francis Journals, vol. 26(11), pages 1075-1101, July.
    3. Hao Liu & Shihan Shen & Tianyi Wang & Zhuo Huang, 2016. "Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect," China Economic Journal, Taylor & Francis Journals, vol. 9(2), pages 140-153, May.
    4. Dorofeenko Victor & Lee Gabriel & Salyer Kevin & Strobel Johannes, 2020. "Risk shocks with time-varying higher moments," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(2), pages 1-20, April.
    5. Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar & Alagidede, Imhotep Paul & Gil-Alana, Luis Alberiko, 2022. "Re-examination of risk-return dynamics in international equity markets and the role of policy uncertainty, geopolitical risk and VIX: Evidence using Markov-switching copulas," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Minxian Yang, 2014. "The Risk Return Relationship: Evidence from Index Return and Realised Variance Series," Discussion Papers 2014-16, School of Economics, The University of New South Wales.
    7. Bretó, Carles & Veiga, Helena, 2011. "Forecasting volatility: does continuous time do better than discrete time?," DES - Working Papers. Statistics and Econometrics. WS ws112518, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Yang, Minxian, 2019. "The risk return relationship: Evidence from index returns and realised variances," Journal of Economic Dynamics and Control, Elsevier, vol. 107(C), pages 1-1.

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