Testing a Class of Piece-Wise CHARN Models with Application to Change-Point Study

Youssef Salman, Joseph Ngatchou-Wandji () and Zaher Khraibani
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Youssef Salman: Mines Saint-Etienne, CNRS, UMR 6158 LIMOS, Institut Henri Fayol, University Clermont Auvergne, 42023 Saint-Etienne, France
Joseph Ngatchou-Wandji: EHESP Rennes and Institut Élie Cartan de Lorraine, CEDEX, 54506 Vandoeuvre-lès-Nancy, France
Zaher Khraibani: Department of Applied Mathematics, Faculty of Sciences, Lebanese University, Beirut 2038 1003, Lebanon

Mathematics, 2024, vol. 12, issue 13, 1-40

Abstract: We study a likelihood ratio test for testing the conditional mean of a class of piece-wise stationary CHARN models. We establish the locally asymptotically normal (LAN) structure of the family of likelihoods under study. We prove that the test is asymptotically optimal, and we give an explicit form of its asymptotic local power. We describe an algorithm for detecting change points and estimating their locations. The estimates are obtained as time indices, maximizing the estimate of the local power. The simulation study we conduct shows the good performance of our method on the examples considered. This method is also applied to a set of financial data.

Keywords: CHARN models; change points; LAN; likelihood ratio tests (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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