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Abstract

We propose a novel methodology for forecasting chaotic systems which is based on exploiting the information conveyed by the local Lyapunov exponents of a system. This information is used to correct for the inevitable bias of most non-parametric predictors. Using simulated data, we show that gains in prediction accuracy can be substantial.

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Bibliographic Info

Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00431726.

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Date of creation: Sep 2009
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Publication status: Published, Chaos, Solitons & Fractals, 2009, 41, 5, 2401-2404
Handle: RePEc:hal:cesptp:halshs-00431726

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00431726
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Web page: http://hal.archives-ouvertes.fr/

Related research

Keywords: chaotic systems;

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Find related papers by JEL classification:

• C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
• C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
• C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
• C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

This paper has been announced in the following NEP Reports:

• NEP-ALL-2009-12-11 (All new papers)
• NEP-ECM-2009-12-11 (Econometrics)
• NEP-FOR-2009-12-11 (Forecasting)

References

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1. Oliver Linton & Mototsugu Shintani, 2002. "Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," STICERD - Econometrics Paper Series /2002/434, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
   
   • Shintani, Mototsugu & Linton, Oliver, 2004. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," Journal of Econometrics, Elsevier, vol. 120(1), pages 1-33, May.
   • Mototsugu Shintani & Oliver Linton, 2003. "Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," Vanderbilt University Department of Economics Working Papers 0309, Vanderbilt University Department of Economics.
   • Oliver Linton & Mototsugu Shintani, 2003. "Nonparametric Neural Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," STICERD - Econometrics Paper Series /2003/455, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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Cited by:

1. Dominique Guegan & Justin Leroux, 2009. "Local Lyapunov Exponents: A new way to predict chaotic systems," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00511996, HAL.
2. Dominique Guégan & Justin Leroux, 2008. "Local Lyapunov exponents: Zero plays no role in Forecasting chaotic systems," Cahiers de recherche 08-10, HEC Montréal, Institut d'économie appliquée.
3. Dominique Guegan, 2009. "Chaos in Economics and Finance," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375713, HAL.

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