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Detection of non-constant long memory parameter

Abstract : This article deals with detection of non-constant long memory parameter in time series. The null hypothesis includes stationary or nonstationary time series with constant long memory parameter, in particular I(d) series, d > −.5. The alternative corresponds to a change in the long memory parameter and gathers in particular an abrupt or gradual change from I(d1) to I(d2), −.5 < d1 < d2. Various test statistics are considered. They are all based on the ratio of forward and backward sample variances of the partial sums. The consistency of the tests is proved under a very general setting. Moreover, the behavior of the test statistics is studied for some models with changing memory parameter. A simulation study shows that our testing procedures have good finite sample properties and turn out to be more powerful than the KPSS-based tests considered in some previous works.
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Preprints, Working Papers, ...
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Contributor : Anne Philippe <>
Submitted on : Sunday, October 23, 2011 - 1:57:23 PM
Last modification on : Wednesday, September 4, 2019 - 5:18:01 PM
Long-term archiving on: : Thursday, November 15, 2012 - 10:21:11 AM


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  • HAL Id : hal-00634777, version 1
  • ARXIV : 1110.5138


Frédéric Lavancier, Remigijus Leipus, Anne Philippe, Donatas Surgailis. Detection of non-constant long memory parameter. 2011. ⟨hal-00634777v1⟩



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