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Local asymptotically optimal test in ARCH model

Authors: Tewfik Lounis
Journal: arXiv
mental health psychology open access

Abstract

This work is an extension in Arch models of the theorem of S.Y. Hwang and I.V. Basawa Hwang and Basawa (2001) which was used before in nonlinear time series contiguous to AR(1) processes. Our results are established under some general assumptions and stationarity and ergodicity conditions. Local asymptotic normality (LAN) for the log likelihood ratio was established.An optimal test was constructed when the parameter is assumed known. Also the optimality of our test was proved when the parameter is unspecified. The method is based on the introducing of a new estimator.