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The structural Theta method and its predictive performance in the M4-Competition

Author

Listed:
  • Giacomo Sbrana

    (NEOMA Business School)

  • Andrea Silvestrini

    (Bank of Italy)

Abstract

The Theta method is a well-established prediction benchmark widely used in forecast competitions. Introduced more than 20 years ago, this method has received significant attention, with several authors proposing different variants to improve its performance. This paper considers the multiple sources of error version of the Theta model, belonging to the family of structural time series models, and investigates its out-of-sample forecast performance using the extensive M4-Competition dataset, which includes 100,000 time series. We compare the proposed structural Theta model against several benchmarks, including all variants of the Theta method. The results clearly demonstrate its remarkable predictive abilities as it outperforms all its variants and competitors, emerging as a solid benchmark for use in forecast competitions.

Suggested Citation

  • Giacomo Sbrana & Andrea Silvestrini, 2024. "The structural Theta method and its predictive performance in the M4-Competition," Temi di discussione (Economic working papers) 1457, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:wptemi:td_1457_24
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    File URL: https://www.bancaditalia.it/pubblicazioni/temi-discussione/2024/2024-1457/en_tema_1457.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Theta method; state-space models; Kalman filter; M4-Competition; predictive accuracy;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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