Strategies for sequential prediction of stationary time series

László Györfi and Gabor Lugosi

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: We present simple procedures for the prediction of a real valued sequence. The algorithms are based on a combination of several simple predictors. We show that if the sequence is a realization of a bounded stationary and ergodic random process then the average of squared errors converges, almost surely, to that of the optimum, given by the Bayes predictor. We offer an analog result for the prediction of stationary gaussian processes.

Keywords: Sequential prediction; ergodic process; individual sequence; gaussian process (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Date: 2000-09
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:507

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