TY - JOUR

T1 - Forecasting Multivariate Time Series with the Theta Method

AU - Thomakos, D.D.

AU - Nikolopoulos, K.

PY - 2015/2/26

Y1 - 2015/2/26

N2 - 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

AB - 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

U2 - 10.1002/for.2334

DO - 10.1002/for.2334

M3 - Article

VL - 34

SP - 220

EP - 229

JO - Journal of Forecasting

JF - Journal of Forecasting

SN - 0277-6693

IS - 3

ER -