Forecasting Multivariate Time Series with the Theta Method
Research output: Contribution to journal › Article › peer-review
Electronic versions
DOI
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
Original language | English |
---|---|
Pages (from-to) | 220-229 |
Journal | Journal of Forecasting |
Volume | 34 |
Issue number | 3 |
DOIs | |
Publication status | Published - 26 Feb 2015 |