Resource title

Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos

Resource image

image for OpenScout resource :: Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos

Resource description

This paper derives the asymptotic distribution of the nonparametric neural network estimator of the Lyapunov exponent in a noisy system. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for testing the chaotic hypothesis based on the estimated Lyapunov exponents and a consistent variance estimator. A simulation study to evaluate small sample performance is reported. We also apply our procedures to daily stock return data. In most cases, the hypothesis of chaos in the stock return series is rejected at the 1% level with an exception in some higher power transformed absolute returns.

Resource author

Resource publisher

Resource publish date

Resource language

en

Resource content type

application/pdf

Resource resource URL

http://eprints.lse.ac.uk/2097/1/Nonparametric_Neural_Network_Estimation_of_Lyapunov_Exponents_and_a_Direct_Test_for_Chaos.pdf

Resource license