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Analysis and Generalisation of a Multivariate Exponential Smoothing Model

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Author Info

  • A. C. Harvey

    (London School of Economics, Houghton Street, London WC2A 2AE, United Kingdom)

Abstract

The multivariate exponential smoothing model of Enns, Machak, Spivey and Wrobleski is examined and it is found that its structure is such that it can be estimated by using techniques designed for a univariate exponential smoothing model. Similarly forecasts can be made using algorithms for the univariate model. The model can therefore be handled very easily. A more general univariate time series model, which can include polynomial trends and seasonal factors, is then set up and a multivariate generalisation, analogous to the multivariate exponential smoothing model, is introduced. It is shown that this model can also be handled using algorithms designed for the univariate case.

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File URL: http://dx.doi.org/10.1287/mnsc.32.3.374
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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 32 (1986)
Issue (Month): 3 (March)
Pages: 374-380

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Handle: RePEc:inm:ormnsc:v:32:y:1986:i:3:p:374-380

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Related research

Keywords: multiple time series; exponential smoothing;

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Cited by:
  1. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
  2. González, Fernando & Launonen, Simo, 2005. "Towards European monetary integration: the evolution of currency risk premium as a measure for monetary convergence prior to the implementation of currency unions," Working Paper Series 0569, European Central Bank.
  3. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
  4. Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2013. "Forecasting multivariate time series with the Theta Method," Working Papers 13004, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
  5. Croux, Christophe & Gelper, Sarah & Mahieu, Koen, 2010. "Robust exponential smoothing of multivariate time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2999-3006, December.
  6. Bermúdez, José D. & Corberán-Vallet, Ana & Vercher, Enriqueta, 2009. "Multivariate exponential smoothing: A Bayesian forecast approach based on simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1761-1769.
  7. Bekiros, Stelios, 2014. "Forecasting with a state space time-varying parameter VAR model: Evidence from the Euro area," Economic Modelling, Elsevier, vol. 38(C), pages 619-626.
  8. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
  9. Triantafyllopoulos, Kostas, 2006. "Multivariate discount weighted regression and local level models," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3702-3720, August.

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