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Is There a Relation between Discrete-Time GARCH and Continuous-Time Diffusion Models?

In: Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models

Author

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  • Turan G. Bali

Abstract

Following the introduction of autoregressive conditional heteroscedasticity (ARCH) processes by Engle (1982) and their generalization by Bollerslev (1986), there have been numerous refinements of this approach to modeling conditional volatility. Most of these refinements have been driven by three empirical regularities of stock prices. First, equity returns are fat-tailed and this leptokurtosis cannot be eliminated by the time-varying variances of GARCH processes because even allowing for changing variances, there remain too many very large events.

Suggested Citation

  • Turan G. Bali, 2011. "Is There a Relation between Discrete-Time GARCH and Continuous-Time Diffusion Models?," Palgrave Macmillan Books, in: Greg N. Gregoriou & Razvan Pascalau (ed.), Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models, chapter 9, pages 160-175, Palgrave Macmillan.
    • Handle: RePEc:pal:palchp:978-0-230-29522-3_9
    DOI: 10.1057/9780230295223_9
    as

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