Forecasting Multivariate Time Series with the Theta Method
Copyright policy )Forecasting Multivariate Time Series with the Theta Method
AbstractIn 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.
- University of Peloponnese Greece
- ΠΑΝΕΠΙΣΤΗΜΙΟ ΠΕΛΟΠΟΝΝΗΣΟΥ
- Bangor University United Kingdom
Time series, auto-correlation, regression, etc. in statistics (GARCH), multivariate time series, univariate, Theta method; univariate; multivariate time series; unit roots; vector forecasting, vector forecasting, unit roots, Inference from stochastic processes and prediction
Time series, auto-correlation, regression, etc. in statistics (GARCH), multivariate time series, univariate, Theta method; univariate; multivariate time series; unit roots; vector forecasting, vector forecasting, unit roots, Inference from stochastic processes and prediction
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