Forecasting Multivariate Time Series with the Theta Method
In this study building on earlier work on the properties and performance of the univariate Theta method for a unit root data‐generating process we: (a) derive new theoretical formulations for the application of the method on multivariate time series; (b) investigate the conditions for which the multivariate Theta method is expected to forecast better than the univariate one; (c) evaluate through simulations the bivariate form of the method; and (d) evaluate this latter model in real macroeconomic and financial time series. The study provides sufficient empirical evidence to illustrate the suitability of the method for vector forecasting; furthermore it provides the motivation for further investigation of the multivariate Theta method for higher dimensions. Copyright © 2015 John Wiley & Sons, Ltd.
Year of publication: |
2015
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Authors: | Thomakos, Dimitrios D. ; Nikolopoulos, Konstantinos |
Published in: |
Journal of Forecasting. - John Wiley & Sons, Ltd.. - Vol. 34.2015, 3, p. 220-229
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Publisher: |
John Wiley & Sons, Ltd. |
Saved in:
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