Limited memory predictors based on polynomial approximation of periodic exponentials

Nikolai Dokuchaev

Journal of Forecasting, 2022, vol. 41, issue 5, 1037-1045

Abstract: The paper presents transfer functions for limited memory time‐invariant linear integral predictors for continuous time processes such that the corresponding predicting kernels have bounded support. It is shown that processes with exponentially decaying Fourier transforms are predictable with these predictors in some weak sense, meaning that convolution integrals over the future times can be approximated by causal convolutions over past times. For a given predicting horizon, the predictors are based on polynomial approximation of a periodic exponentials (complex sinusoid) in a weighted L2‐space.

Date: 2022
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https://doi.org/10.1002/for.2843

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:41:y:2022:i:5:p:1037-1045

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