Testing the Nullity of GARCH Coefficients: Correction of the Standard Tests and Relative Efficiency Comparisons
GARCH 系数为零的检验:标准检验修正与相对效率比较AI 解读 ↓
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GARCH 系数为零的检验:标准检验修正与相对效率比较AI 解读 ↓
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This article is concerned with testing the nullity of coefficients in generalized autoregressive conditionally heteroscedastic (GARCH) models. The problem is nonstandard because the quasi-maximum likelihood estimator is subject to positivity constraints. This article establishes the asymptotic null and local alternative distributions of Wald, score, and quasi-likelihood ratio tests. Efficiency comparisons under fixed alternatives are considered. Two cases of special interest are tests of the null hypothesis of one coefficient equal to zero and tests of the null hypothesis of no conditional heteroscedasticity. Finally, the proposed approach is used in the analysis of financial data and suggests reconsidering the preeminence of GARCH(1,1) among GARCH models.
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