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

Turan G. Bali

Chapter 9 in Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models, 2011, pp 160-175 from Palgrave Macmillan

Abstract: 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.

Keywords: Stock Return; Stochastic Volatility; Stochastic Volatility Model; Stock Market Volatility; Stock Return Volatility (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-0-230-29522-3_9

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DOI: 10.1057/9780230295223_9

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