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Modelling Nonlinear Economic Time Series$
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Timo Teräsvirta, Dag Tjøstheim, and Clive W. J. Granger

Print publication date: 2010

Print ISBN-13: 9780199587148

Published to Oxford Scholarship Online: May 2011

DOI: 10.1093/acprof:oso/9780199587148.001.0001

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Models of conditional heteroskedasticity

Models of conditional heteroskedasticity

Chapter:
(p.162) 8 Models of conditional heteroskedasticity
Source:
Modelling Nonlinear Economic Time Series
Author(s):

Timo Teräsvirta

Dag Tjøstheim (Contributor Webpage)

W. J. Granger

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199587148.003.0008

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

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