ENBIS-16 in Sheffield

11 – 15 September 2016; Sheffield Abstract submission: 20 March – 4 July 2016

A Locally Asymptotically Optimal Test for ARCH Models

13 September 2016, 12:10 – 12:40

Abstract

Submitted by
Joseph Ngatchou-Wandji
Authors
Joseph Ngatchou-Wandji (EHESP Rennes & Université de Lorraine), Tewfik Lounis (Université de Lorraine)
Abstract
We construct a locally asymptotically optimal test for discriminating between ARCH models within a large class. The test statistic is based on a new type of estimator. Its asymptotic properties are studied under the null hypothesis and under a sequence of local alternatives. The latter study is done by establishing a contiguity result and using the resulting LAN property. Our theoretical results extend existing ones, which are generally established under the assumption that the parameter vector is known. A simulation experiment shows that our test behaves well under the hypotheses considered. The results are also applied to a set of real data.
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