Adaptive Test for Periodicity in Autoregressive Conditional Heteroskedastic Processes

作者：Bentarzi M; Merzougui M^*

来源：Communications in Statistics - Simulation and Computation, 2010, 39(9): 1735-1753.

DOI：10.1080/03610918.2010.512694

• Adaptive test
• Local asymptotic &quot
• most stringent&quot
• test
• Local asymptotic normality
• Periodic ARCH
• Swensen's conditions

This article is concerned with the periodicity testing problem in Autoregressive Conditional Heteroskedastic (ARCH) process. Adaptive locally asymptotically optimal test is derived, when the innovation density is unspecified but symmetric satisfying only some general technical assumptions, for the null hypothesis of classical ARCH process against an alternative of periodically correlated ARCH dependence. The main technical tool is LeCam's (1960) Local Asymptotic Normality (LAN) property. The LAN property of the central sequence is shown via the adapted sufficient Swensen's conditions (1985). The performance of the established test is shown via simulation studies.

• 出版日期2010