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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Paper provided by HEC Montréal, Institut d'économie appliquée in its series Cahiers de recherche with number
07-12.
Length: 12 pages Date of creation: Dec 2007 Date of revision: Handle: RePEc:iea:carech:0712
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