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Book part
Publication date: 21 November 2014

Igor Vaynman and Brendan K. Beare

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and…

Abstract

The variance targeting estimator (VTE) for generalized autoregressive conditionally heteroskedastic (GARCH) processes has been proposed as a computationally simpler and misspecification-robust alternative to the quasi-maximum likelihood estimator (QMLE). In this paper we investigate the asymptotic behavior of the VTE when the stationary distribution of the GARCH process has infinite fourth moment. Existing studies of historical asset returns indicate that this may be a case of empirical relevance. Under suitable technical conditions, we establish a stable limit theory for the VTE, with the rate of convergence determined by the tails of the stationary distribution. This rate is slower than that achieved by the QMLE. The limit distribution of the VTE is nondegenerate but singular. We investigate the use of subsampling techniques for inference, but find that finite sample performance is poor in empirically relevant scenarios.

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Book part
Publication date: 21 November 2014

Abstract

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

Book part
Publication date: 21 November 2014

Abstract

Details

Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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