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Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility

  • Teräsvirta, Timo


    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Zhao, Zhenfang


    (Dept. of Economic Statistics, Stockholm School of Economics)

Financial return series of sufficiently high frequency display stylized facts such as volatility clustering, high kurtosis, low starting and slow-decaying autocorrelation function of squared returns and the so-called Taylor effect. In order to evaluate the capacity of volatility models to reproduce these facts, we apply both standard and robust measures of kurtosis and autocorrelation of squares to first-order GARCH, EGARCH and ARSV models. Robust measures provide a fresh view of stylized facts which is useful because many financial time series can be viewed as being contaminated with outliers.

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Paper provided by Stockholm School of Economics in its series SSE/EFI Working Paper Series in Economics and Finance with number 662.

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Length: 51 pages
Date of creation: 01 Jun 2007
Date of revision: 05 Jun 2007
Publication status: Published as Teräsvirta, Timo and Zhenfang Zhao, 'Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility' in Applied Financial Economics, 2011, pages 67-94.
Handle: RePEc:hhs:hastef:0662
Contact details of provider: Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden
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  1. Jonathan H. Wright & Tim Bollerslev, 1999. "High frequency data, frequency domain inference and volatility forecasting," International Finance Discussion Papers 649, Board of Governors of the Federal Reserve System (U.S.).
  2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
  3. Liesenfeld, Roman & Jung, Robert C., 1997. "Stochastic volatility models: Conditional normality versus heavy tailed distributions," Tübinger Diskussionsbeiträge 103, University of Tübingen, School of Business and Economics.
  4. He, Changli & Teräsvirta, Timo & Malmsten, Hans, 1999. "Fourth Moment Structure of a Family of First-Order Exponential GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 345, Stockholm School of Economics.
  5. Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach," Working Papers 593, Queen Mary University of London, School of Economics and Finance.
  6. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 319-342.
  7. C. W. J. GRANGER & Zhuanxin DING, 1995. "Some Properties of Absolute Return: An Alternative Measure of Risk," Annales d'Economie et de Statistique, ENSAE, issue 40, pages 67-91.
  8. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing Unconditional Skewness in Models for Financial Time Series," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(2), pages 208-230, Spring.
  9. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
  10. Stefan Lundbergh & Timo Teräsvirta, 1999. "Evaluating GARCH Models," Tinbergen Institute Discussion Papers 99-008/4, Tinbergen Institute.
  11. He, Changli & Ter svirta, Timo & Malmsten, Hans, 2002. "Moment Structure Of A Family Of First-Order Exponential Garch Models," Econometric Theory, Cambridge University Press, vol. 18(04), pages 868-885, August.
  12. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155.
  13. Eklund, Bruno, 2003. "Estimating confidence regions over bounded domains," SSE/EFI Working Paper Series in Economics and Finance 548, Stockholm School of Economics.
  14. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
  15. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," CREATES Research Papers 2011-01, School of Economics and Management, University of Aarhus.
  16. He, Changli & Terasvirta, Timo, 1999. "Properties of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 92(1), pages 173-192, September.
  17. repec:cup:cbooks:9780521405737 is not listed on IDEAS
  18. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December.
  19. Van Bellegem, Sebastien & von Sachs, Rainer, 2004. "Forecasting economic time series with unconditional time-varying variance," International Journal of Forecasting, Elsevier, vol. 20(4), pages 611-627.
  20. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
  21. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
  22. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  23. Kim, Tae-Hwan & White, Halbert, 2004. "On more robust estimation of skewness and kurtosis," Finance Research Letters, Elsevier, vol. 1(1), pages 56-73, March.
  24. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models: Comments: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 413-17, October.
  25. repec:cup:cbooks:9780521321969 is not listed on IDEAS
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