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Analysis of Financial Time Series, Third Edition by RUEY S. TSAY

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3.8 The Exponential GARCH Model

To overcome some weaknesses of the GARCH model in handling financial time series, Nelson (1991) proposes the exponential GARCH (EGARCH) model. In particular, to allow for asymmetric effects between positive and negative asset returns, he considered the weighted innovation

(3.24) 3.24

where θ and γ are real constants. Both ϵt and |ϵt| − E(|ϵt|) are zero-mean iid sequences with continuous distributions. Therefore, E[gt)] = 0. The asymmetry of gt) can easily be seen by rewriting it as

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Remark

For the standard Gaussian random variable ϵt, Inline. For the standardized Student-t distribution in Eq. (3.7), we have

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An EGARCH(m, s) model can be written as

(3.25) 3.25   

where α0 is a constant, B is the back-shift (or lag) operator such that Bgt) = gt−1), and 1 + β1B + ⋯ + βs−1Bs−1 and 1 − α1B − ⋯ − αmBm are polynomials with zeros outside the unit circle and have no common factors. By outside the unit circle we mean that absolute values of the zeros are greater than 1. ...

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