Sieve bootstrap monitoring for change from short to long memory

Zhanshou Chen, Yuhong Xing and Fuxiao Li

Economics Letters, 2016, vol. 140, issue C, 53-56

Abstract: This paper proposes a variance ratio statistic to monitor changes from short to long memory processes. The asymptotic distribution is derived under the null hypothesis and the consistency of the monitoring procedure is proven under the alternative hypothesis. A sieve bootstrap approximation method is introduced to determine the critical values. Simulations indicate that the new procedure is quite robust for many types of innovation processes and performs better than the existing retrospective test.

Keywords: Short memory process; Long memory process; Change point monitoring; Sieve bootstrap (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:140:y:2016:i:c:p:53-56

DOI: 10.1016/j.econlet.2015.12.023

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