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Forecasting Multivariate Time Series with the Theta Method

Research output: Contribution to journal › Article › peer-review

Standard Standard

Forecasting Multivariate Time Series with the Theta Method. / Thomakos, D.D.; Nikolopoulos, K.
In: Journal of Forecasting, Vol. 34, No. 3, 26.02.2015, p. 220-229.

Research output: Contribution to journal › Article › peer-review

HarvardHarvard

Thomakos, DD & Nikolopoulos, K 2015, 'Forecasting Multivariate Time Series with the Theta Method', Journal of Forecasting, vol. 34, no. 3, pp. 220-229. https://doi.org/10.1002/for.2334

APA

Thomakos, D. D., & Nikolopoulos, K. (2015). Forecasting Multivariate Time Series with the Theta Method. Journal of Forecasting, 34(3), 220-229. https://doi.org/10.1002/for.2334

CBE

Thomakos DD, Nikolopoulos K. 2015. Forecasting Multivariate Time Series with the Theta Method. Journal of Forecasting. 34(3):220-229. https://doi.org/10.1002/for.2334

MLA

Thomakos, D.D. and K. Nikolopoulos. "Forecasting Multivariate Time Series with the Theta Method". Journal of Forecasting. 2015, 34(3). 220-229. https://doi.org/10.1002/for.2334

VancouverVancouver

Thomakos DD, Nikolopoulos K. Forecasting Multivariate Time Series with the Theta Method. Journal of Forecasting. 2015 Feb 26;34(3):220-229. doi: 10.1002/for.2334

Author

Thomakos, D.D. ; Nikolopoulos, K. / Forecasting Multivariate Time Series with the Theta Method. In: Journal of Forecasting. 2015 ; Vol. 34, No. 3. pp. 220-229.

RIS

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 -