Title

The Limiting Behavior of Kernel Estimates of the Lyapunov Exponent for Stochastic Time Series

Document Type

Discussion Paper

Publication Date

8-1-1996

CFDP Number

1130R

CFDP Revision Date

1997-10-01

CFDP Pages

47

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.

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