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

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

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

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