Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series

Michael J. O'Shea

Journal of Forecasting, 2017, vol. 36, issue 1, 43-55

Abstract: We develop a method to extract periodic variations in a time series that are hidden in large non‐periodic and stochastic variations. This method relies on folding the time series many times and allows direct visualization of a hidden periodic component without resorting to any fitting procedure. Applying this method to several large‐cap stock time series in Europe, Japan and the USA yields a component with periodicity of 1 year. Out‐of‐sample tests on these large‐cap time series indicate that this periodic component is able to forecast long‐term (decade) behavior for large‐cap time series. Copyright © 2016 John Wiley & Sons, Ltd.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:wly:jforec:v:36:y:2017:i:1:p:43-55

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