Testing for GARCH effects: an exact procedure based on quasi-likelihood ratios
نویسنده
چکیده
A procedure is developed to test the null hypothesis of conditional homoskedasticity in the context of GARCH models. The approach is based on the quasi-likelihood function, leaving the true distribution of model disturbances completely unspecified. The presence of possible nuisance parameters in the testing problem is dealt with by using a pivotal bound and Monte Carlo resampling techniques to obtain a level-exact test procedure. The results of simulation experiments reveal that the permutation-based likelihood ratio test has very good power properties in comparison to omnibus Lagrange multiplier tests. An empirical application of the new procedure finds strong evidence of GARCH effects in Fama-French portfolio returns, even when conditioning on the market risk factor.
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