We evaluate the effects of data dimension on the asymptotic normality of the empirical likelihood ratio for high-dimensional data under a general multivariate model. Data dimension and dependence among components of the multivariate random vector affect the empirical likelihood directly through...

Hall & Yao (2003) showed that, for ARCH/GARCH, i.e. autoregressive conditional heteroscedastic/generalised autoregressive conditional heteroscedastic, models with heavy-tailed errors, the conventional maximum quasilikelihood estimator suffers from complex limit distributions and slow convergence...

The weighted least absolute deviations estimator is studied for an AR(1) process with ARCH(1) errors ϵ-sub-t. Unlike for the quasi maximum likelihood estimator, the estimator's, limiting distribution is shown to be normal even when E(ϵ-sub-t-super-4) = ∞. Furthermore, the estimator can be...