The Correct Regularity Condition and Interpretation of Asymmetry in EGARCH

Chia-Lin Chang () and Michael McAleer

No 2017-17, Documentos de Trabajo del ICAE from Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico

Abstract: In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive conditional heteroskedasticity (GARCH) model of Engle (1982) and Bollerslev (1986), the GJR (or threshold GARCH) model of Glosten, Jagannathan and Runkle (1992), and the exponential GARCH (or EGARCH) model of Nelson (1990, 1991). For purposes of deriving the mathematical regularity properties, including invertibility, to determine the likelihood function for estimation, and the statistical conditions to establish asymptotic properties, it is convenient to understand the stochastic properties underlying the three univariate models. The random coefficient autoregressive process was used to obtain GARCH by Tsay (1987), an extension of which was used by McAleer (2004) to obtain GJR. A random coefficient complex nonlinear moving average process was used by McAleer and Hafner (2014) to obtain EGARCH. These models can be used to capture asymmetry, which denotes the different effects on conditional volatility of positive and negative effects of equal magnitude, and possibly also leverage, which is the negative correlation between returns shocks and subsequent shocks to volatility (see Black 1979). McAleer (2014) showed that asymmetry was possible for GJR, but not leverage. McAleer and Hafner showed that leverage was not possible for EGARCH. Surprisingly, the conditions for asymmetry in EGARCH seem to have been ignored in the literature, or have concentrated on the incorrect conditions, with no clear explanation, and hence with associated misleading interpretations. The purpose of the paper is to derive the regularity condition for asymmetry in EGARCH to provide the correct interpretation. It is shown that, in practice, EGARCH always displays asymmetry, though not leverage.

Keywords: Conditional volatility models; Random coefficient complex nonlinear moving average process; EGARCH; Asymmetry; Leverage; Regularity condition. (search for similar items in EconPapers)
JEL-codes: C22 C52 C58 G32 (search for similar items in EconPapers)
Pages: 10 pages
Date: 2017-06
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Journal Article: The correct regularity condition and interpretation of asymmetry in EGARCH (2017)
Working Paper: The Correct Regularity Condition and Interpretation of Asymmetry in EGARCH (2017)
Working Paper: The Correct Regularity Condition and Interpretation of Asymmetry in EGARCH (2017)
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