NDLI: Estimation and strict stationarity testing of ARCH processes based on weighted least squares

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Estimation and strict stationarity testing of ARCH processes based on weighted least squares

Content Provider	Springer Nature Link
Author	Akuche, A.
Copyright Year	2014
Abstract	This paper proposes a unified unconstrained two-stage weighted least squares estimate (2S-WLSE) theory for both stationary and nonstationary ARCH(1) processes. Without assuming strict stationarity, we show that the unconstrained 2S-WLSE of the conditional variance slope ARCH(1) parameter is consistent and asymptotically Gaussian and has the same asymptotic variance as its unconstrained quasi-maximum likelihood counterpart. Moreover, a consistent estimate of the asymptotic variance of the 2S-WLSE is provided irrespective of the stationarity requirement. As a result, strict stationarity testing of the ARCH process is considered. A numerical illustration on simulated and real data assesses the theory in finite samples.
Starting Page	81
Ending Page	102
Page Count	22
File Format	PDF
ISSN	10665307
Journal	Mathematical Methods of Statistics
Volume Number	23
Issue Number	2
e-ISSN	19348045
Language	English
Publisher	Allerton Press
Publisher Date	2014-06-25
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	ARCH process strict stationarity instability two-stage weighted least squares strict stationarity testing Time series, auto-correlation, regression, etc. Asymptotic properties of estimators Asymptotic properties of tests Statistical Theory and Methods
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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