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GMM Estimation for Long Memory Latent Variable Volatility and Duration Models

Willa Chen and Rohit Deo ()
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Willa Chen: Texas A&M University

Econometrics from University Library of Munich, Germany

Abstract: We study the rate of convergence of moment conditions that have been commonly used in the literature for Generalised Method of Moments (GMM) estimation of short memory latent variable volatility models. We show that when the latent variable possesses long memory, these moment conditions have an n^{1/2-d} rate of convergence where 0

Keywords: GMM; long memory; stochastic volatility and durations (search for similar items in EconPapers)
JEL-codes: C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fin
Date: 2005-01-14
Note: Type of Document - pdf; pages: 8
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0501006

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