Nonlinear models for autoregressive conditional heteroskedasticity

Timo Teräsvirta

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: This paper contains a brief survey of nonlinear models of autoregressive conditional heteroskedasticity. The models in question are parametric nonlinear extensions of the original model by Engle (1982). After presenting the individual models, linearity testing and parameter estimation are discussed. Forecasting volatility with nonlinear models is considered. Finally, parametric nonlinear models based on multiplicative decomposition of the variance receive attention.

Keywords: nonlinear ARCH; nonlinear GARCH; neural network; nonlinear volatility; smooth transition GARCH; threshold GARCH. (search for similar items in EconPapers)
JEL-codes: C22 C52 (search for similar items in EconPapers)
Pages: 29
Date: 2011-01-05
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Citations: View citations in EconPapers (1)

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