Forecasting chaotic systems: The role of local Lyapunov exponents

Dominique Guégan and Justin Leroux

No 07-12, Cahiers de recherche from HEC Montréal, Institut d'économie appliquée

Abstract: 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.

Pages: 12 pages
Date: 2007-12
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Citations: View citations in EconPapers (2)

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http://www.hec.ca/iea/cahiers/2007/iea0712_jleroux.pdf (application/pdf)

Related works:
Working Paper: Forecasting chaotic systems: The role of local Lyapunov exponents (2009)
Working Paper: Forecasting chaotic systems: the role of local Lyapunov exponents (2008)
Working Paper: Forecasting chaotic systems: the role of local Lyapunov exponents (2008)
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