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Forecasting chaotic systems: The role of local Lyapunov exponents

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  • Dominique Guegan

    ()
    (EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris, CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris 1 - Panthéon-Sorbonne)

  • Justin Leroux

    ()
    (HEC - Institute for Applied Economics - HEC MONTRÉAL)

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

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Keywords: chaotic systems;

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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.
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Cited by:
  1. 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.
  2. Dominique Guegan, 2009. "Chaos in Economics and Finance," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375713, HAL.
  3. 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.

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