Chapter

Models of conditional heteroskedasticity

Timo Teräsvirta, Dag Tjøstheim and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print December 2010 | ISBN: 9780199587148
Published online May 2011 | e-ISBN: 9780191595387 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780199587148.003.0008

Series: Advanced Texts in Econometrics

Models of conditional heteroskedasticity

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This chapter considers modelling conditional heteroskedasticity and begins with the well known autoregressive conditional heteroskedasticity (ARCH) model. Its basic extension to the generalized autoregressive conditional heteroskedasticity (GARCH) model is described, and various extensions of the GARCH model are considered. They include the exponential GARCH model and the stochastic volatility model that is not a GARCH model but belongs to a separate family of models. Building GARCH models, including specification, estimation and evaluation, is discussed. The GARCH‐in‐mean model and the concept of realized volatility are briefly mentioned. There is also a section on multivariate GARCH models whose popularity has been increasing during the last few years.

Keywords: ARCH; exponential GARCH; GARCH; GARCH‐in‐mean model; GARCH model building; multivariate GARCH model; stochastic volatility

Chapter.  28663 words.  Illustrated.

Subjects: Econometrics and Mathematical Economics

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