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Autoregressive Conditional Heteroskedasticy Under Error-Term Non-Normality

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  • Ramirez, Octavio A.

Abstract

This paper explores the impact of error-term non-normality on the performance of the normal-error Generalized Autoregressive Conditional Heteroskedastic (GARCH) model under small and moderate sample sizes. A non-normal-, asymmetric-error GARCH model is proposed, and its finite-sample performance is evaluated in comparison to the normal-error GARCH under various underlying error-term distributions. The results suggest that one must be skeptical of using the normal-error GARCH when there is evidence of conditional error-term non-normality. The conditional distribution of the error-term in a previous mainstream application of the normal GARCH is found to be non-normal and asymmetric. The same application is used to illustrate the advantages of the proposed non-normal-error GARCH model.

Suggested Citation

  • Ramirez, Octavio A., 2001. "Autoregressive Conditional Heteroskedasticy Under Error-Term Non-Normality," 2001 Annual meeting, August 5-8, Chicago, IL 20595, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea01:20595
    DOI: 10.22004/ag.econ.20595
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    References listed on IDEAS

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