Optimizing Theta model for monthly data

Fotios Petropoulos, Konstantinos Nikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Forecasting accuracy and performance of extrapolation techniques has always been of major importance for both researchers and practitioners. Towards this direction, many forecasting competitions have conducted over the years, in order to provide solid performance measurement frameworks for new methods. The Theta model outperformed all other participants during the largest up-to-date competition (M3-competition). The model's performance is based to the a-priori decomposition of the original series into two separate lines, which contain specific amount of information regarding the short-term and long-term behavior of the data. The current research investigates possible modifications on the original Theta model, aiming to the development of an optimized version of the model specifically for the monthly data. The proposed adjustments refer to better estimation of the seasonal component, extension of the decomposition feature of the original model and better optimization procedures for the smoothing parameter. The optimized model was tested for its efficiency in a large data set containing more than 20,000 empirical series, displaying improved performance ability when monthly data are considered.

Original languageEnglish
Title of host publicationICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence
Pages190-195
Number of pages6
Publication statusPublished - 27 May 2013
Event5th International Conference on Agents and Artificial Intelligence, ICAART 2013 - Barcelona, Spain
Duration: 15 Feb 201318 Feb 2013

Publication series

NameICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence
Volume1

Conference

Conference5th International Conference on Agents and Artificial Intelligence, ICAART 2013
CountrySpain
CityBarcelona
Period15/02/1318/02/13

Keywords

  • Competitions
  • Forecasting accuracy
  • Seasonality
  • Theta model
  • Time series

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Petropoulos, F., & Nikolopoulos, K. (2013). Optimizing Theta model for monthly data. In ICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence (pp. 190-195). (ICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence; Vol. 1).