Forecasting Ability of a Periodic Component Extracted from Large‐Cap Index Time Series |
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Authors: | Michael J O'Shea |
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Institution: | Department of Physics, Kansas State University, Manhattan, KS, USA |
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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. |
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Keywords: | hidden periodicity large‐cap index 1‐year periodicity forecast out‐of‐sample |
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