Article ID: | iaor20165057 |
Volume: | 36 |
Issue: | 1 |
Start Page Number: | 43 |
End Page Number: | 55 |
Publication Date: | Jan 2017 |
Journal: | Journal of Forecasting |
Authors: | O'Shea Michael J |
Keywords: | stochastic processes, financial, investment |
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.