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EGARCH models with fat tails, skewness and leverage

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Author Info

  • Harvey, A.
  • Sucarrat, G.

Abstract

An EGARCH model in which the conditional distribution is heavy-tailed and skewed is proposed. The properties of the model, including unconditional moments, autocorrelations and the asymptotic distribution of the maximum likelihood estimator, are obtained. Evidence for skewness in conditional t-distribution is found for a range of returns series and the model is shown to give a better .t than the corresponding skewed-t GARCH model.

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File URL: http://www.econ.cam.ac.uk/research/repec/cam/pdf/cwpe1236.pdf
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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 1236.

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Date of creation: 17 Aug 2012
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Handle: RePEc:cam:camdae:1236

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Web page: http://www.econ.cam.ac.uk/index.htm

Related research

Keywords: General error distribution; heteroskedasticity; leverage; score; Student?s t; two components.;

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References

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  1. Dongming Zhu & John Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
  2. ZHU, Dongming & ZINDE-WALSH, Victoria, 2007. "Properties and Estimation of Asymmetric Exponential Power Distribution," Cahiers de recherche 13-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  3. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range-Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, 06.
  4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, Elsevier.
  5. GIOT, Pierre & LAURENT, Sébastien, 2001. "Value-at-risk for long and short trading positions," CORE Discussion Papers 2001022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  6. Jensen, S ren Tolver & Rahbek, Anders, 2004. "Asymptotic Inference For Nonstationary Garch," Econometric Theory, Cambridge University Press, vol. 20(06), pages 1203-1226, December.
  7. Drew Creal & Siem Jan Koopman & Andre Lucas, 2009. "A General Framework for Observation Driven Time-Varying Parameter Models," Global COE Hi-Stat Discussion Paper Series gd08-038, Institute of Economic Research, Hitotsubashi University.
  8. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
  9. Pierre Giot & Sébastien Laurent, 2002. "Modelling Daily Value-at-Risk Using Realized Volatility and ARCH Type Models," Computing in Economics and Finance 2002 52, Society for Computational Economics.
  10. Xin Zhang & Drew Creal & Siem Jan Koopman & Andre Lucas, 2011. "Modeling Dynamic Volatilities and Correlations under Skewness and Fat Tails," Tinbergen Institute Discussion Papers 11-078/2/DSF22, Tinbergen Institute.
  11. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
  12. repec:dgr:uvatin:2011078 is not listed on IDEAS
  13. Wang, Kai-Li & Fawson, Christopher B. & Barrett, Christopher B. & McDonald, James B., 1998. "A Flexible Parametric Garch Model With An Application To Exchange Rates," Economics Research Institute, ERI Study Papers 28355, Utah State University, Economics Department.
  14. Escanciano, J. Carlos & Lobato, Ignacio N., 2009. "An automatic Portmanteau test for serial correlation," Journal of Econometrics, Elsevier, vol. 151(2), pages 140-149, August.
  15. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, 06.
  16. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, 08.
  17. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  18. Drew Creal & Siem Jan Koopman & Andr� Lucas, 2010. "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations," Tinbergen Institute Discussion Papers 10-032/2, Tinbergen Institute.
  19. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
  20. repec:dgr:uvatin:2008108 is not listed on IDEAS
  21. repec:dgr:uvatin:2010032 is not listed on IDEAS
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Citations

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Cited by:
  1. Krenar AVDULAJ & Jozef BARUNIK, 2013. "Can We Still Benefit from International Diversification? The Case of the Czech and German Stock Markets," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 63(5), pages 425-442, November.
  2. M. Caivano & A. Harvey, 2013. "Two EGARCH models and one fat tail," Cambridge Working Papers in Economics 1326, Faculty of Economics, University of Cambridge.
  3. M. Caivano & A. Harvey, 2013. "Time series models with an EGB2 conditional distribution," Cambridge Working Papers in Economics 1325, Faculty of Economics, University of Cambridge.
  4. Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? A new evidence from a dynamic copulas and high frequency data," Papers 1307.5981, arXiv.org.
  5. Harvey, A. & Luati, A., 2012. "Filtering with heavy tails," Cambridge Working Papers in Economics 1255, Faculty of Economics, University of Cambridge.

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