Forecasting chaotic systems : the role of local Lyapunov exponents

We propose a novel methodology for forecasting chaotic systems which is based on the nearest-neighbor predictor and improves upon it by incorporating local Lyapunov exponents to correct for its inevitable bias. Using simulated data, we show that gains in prediction accuracy can be substantial. The general intuition behind the proposed method can readily be applied to other non-parametric predictors.

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Year of publication:	2008-02
Authors:	Guegan, Dominique ; Leroux, Justin
Institutions:	HAL
Subject:	Chaos theory \| Lyapunov exponent \| logistic map \| Monte Carlo simulations

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Extent:	application/pdf
Series:	Post-Print.
Type of publication:	Book / Working Paper
Notes:	View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00259238
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010738670