Correlation analysis of forecasting methods: The case of the M4 competition

Pantelis Agathangelou, Demetris Trihinas, Ioannis Katakis

    Research output: Contribution to journalComment/debatepeer-review

    1 Citation (Scopus)


    This commentary introduces a correlation analysis of the top-10 ranked forecasting methods that participated in the M4 forecasting competition. The “M” competitions attempt to promote and advance research in the field of forecasting by inviting both industry and academia to submit forecasting algorithms for evaluation over a large corpus of real-world datasets. After performing the initial analysis to derive the errors of each method, we proceed to investigate the pairwise correlations among them in order to understand the extent to which they produce errors in similar ways. Based on our results, we conclude that there is indeed a certain degree of correlation among the top-10 ranked methods, largely due to the fact that many of them consist of a combination of well-known, statistical and machine learning techniques. This fact has a strong impact on the results of the correlation analysis, and therefore leads to similar forecasting error patterns.

    Original languageEnglish
    JournalInternational Journal of Forecasting
    Publication statusPublished - 1 Jan 2019


    • Forecasting
    • M4
    • Machine learning
    • Makridakis
    • Statistics


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