The Asymptotic Distribution of Nonparametric Estimates of the Lyapunov Exponent for Stochastic Time Series

Yoon-Jae Whang and Oliver Linton

No 1130R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This paper derives the asymptotic distribution of a smoothing-based estimator of the Lyapunov exponent for a stochastic time series under two general scenarios. In the first case, we are able to establish root-T consistency and asymptotic normality, while in the second case, which is more relevant for chaotic processes, we are only able to establish asymptotic normality at a slower rate of convergence. We provide consistent confidence intervals for both cases. We apply our procedures to simulated data.

Keywords: Chaos; kernel; nonlinear dynamics; nonparametric regression; semiparametric (search for similar items in EconPapers)
JEL-codes: C13 C14 C22 (search for similar items in EconPapers)
Pages: 47 pages
Date: 1997-10
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (1)

Published in Journal of Econometrics (1996), 91: 1-42

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Journal Article: The asymptotic distribution of nonparametric estimates of the Lyapunov exponent for stochastic time series (1999)
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Persistent link: https://EconPapers.repec.org/RePEc:cwl:cwldpp:1130r

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