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Asymptotics of the QMLE for Non-Linear ARCH Models

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Author Info
Dennis Kristensen (Columbia University)
Anders Rahbek (University of Copenhagen)

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Abstract

Asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for non-linear ARCH(q) models -- including for example Asymmetric Power ARCH and log-ARCH -- are derived. Strong consistency is established under the assumptions that the ARCH process is geometrically ergodic, the conditional variance function has a finite log-moment, and finite second moment of the rescaled error. Asymptotic normality of the estimator is established under the additional assumption that certain ratios involving the conditional variance function are suitably bounded, and that the rescaled errors have little more than fourth moment. We verify our general conditions, including identification, for a wide range of leading specific ARCH models.

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File URL: http://www.bepress.com/cgi/viewcontent.cgi?article=1001&context=jtse
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Publisher Info
Article provided by Berkeley Electronic Press in its journal Journal of Time Series Econometrics.

Volume (Year): 1 (2009)
Issue (Month): 1 ()
Pages:
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Handle: RePEc:bpj:jtsmet:v:1:y:2009:i:1:n:2

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Web page: http://www.bepress.com/jtse

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Related research
Keywords: C13; C22; ARCH; non-linear; QMLE; asymptotic theory;

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This page was last updated on 2010-1-21.


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