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The Impact of Shocks on Higher Moments

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  • Eric Jondeau
  • Michael Rockinger

Abstract

In this paper, we extend the concept of the news impact curve of volatility developed by Engle and Ng (1993) to the higher moments and co-moments of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model with non-normal innovations. For this purpose, we present a new methodology to describe the joint distribution of GARCH processes in a non-normal setting. Then, we provide expressions for the response of the moments of the subsequent distribution to a shock. This tool enhances the understanding of the temporal evolution of the joint distribution. We use our methodology to provide stylized facts for the four largest international stock markets. In particular, we document the persistence of large (positive or negative) daily returns. In a multivariate setting , we find that foreign holdings provide a good hedge against changes in domestic volatility after good shocks but a bad hedge after crashes. Finally, using generalized impulse responses, we show that the effect of shocks on the higher moments of the distribution is short-lasting. Copyright The Author 2008. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Suggested Citation

  • Eric Jondeau & Michael Rockinger, 2009. "The Impact of Shocks on Higher Moments," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 77-105, Spring.
    • Handle: RePEc:oup:jfinec:v:7:y:2009:i:2:p:77-105
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbn017
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    Cited by:

    1. Pauwels, Laurent & Radchenko, Peter & Vasnev, Andrey, 2019. "Higher Moment Constraints for Predictive Density Combinations," Working Papers BAWP-2019-01, University of Sydney Business School, Discipline of Business Analytics.
    2. Ruan, Qingsong & Huang, Ying & Jiang, Wei, 2016. "The exceedance and cross-correlations between the gold spot and futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 139-151.
    3. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    4. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    5. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    6. repec:dau:papers:123456789/6804 is not listed on IDEAS
    7. Markwat, T.D. & Kole, H.J.W.G. & van Dijk, D.J.C., 2009. "Time Variation in Asset Return Dependence: Strength or Structure?," ERIM Report Series Research in Management ERS-2009-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Jondeau, Eric, 2016. "Asymmetry in tail dependence in equity portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 351-368.
    9. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    10. Mehmet Balcilar & Rangan Gupta & Duc Khuong Nguyen & Mark E. Wohar, 2018. "Causal effects of the United States and Japan on Pacific-Rim stock markets: nonparametric quantile causality approach," Applied Economics, Taylor & Francis Journals, vol. 50(53), pages 5712-5727, November.
    11. Oscar Espinosa & Fabio Nieto, 2020. "A study on the leverage effect on financial series using a TAR model: a Bayesian approach," Papers 2002.05319, arXiv.org, revised Feb 2020.
    12. Linjie Wang & Jean‐Paul Chavas & Jian Li, 2024. "Dynamic linkages in agricultural and energy markets: A quantile impulse response approach," Agricultural Economics, International Association of Agricultural Economists, vol. 55(4), pages 639-676, July.
    13. Renée Fry-McKibbin & Cody Yu-Ling Hsiao, 2014. "Extremal Dependence and Contagion," CAMA Working Papers 2014-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
    15. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2018. "The sparse method of simulated quantiles: An application to portfolio optimization," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 375-398, August.
    16. Lai, Jing-yi, 2012. "Shock-dependent conditional skewness in international aggregate stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 72-83.

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