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The uncertainty track: Machine learning, statistical modeling, synthesis

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  • Ord, J. Keith

Abstract

This note provides an evaluation of the contributions of the M5 Competition to the construction of prediction intervals. We consider the choice of criteria used in the evaluations, the relative performance of designed and benchmark methods and the take-home lessons both for statistical forecasters and for those interested in forecasting retail sales.

Suggested Citation

  • Ord, J. Keith, 2022. "The uncertainty track: Machine learning, statistical modeling, synthesis," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1526-1530.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:4:p:1526-1530
    DOI: 10.1016/j.ijforecast.2021.09.007
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    References listed on IDEAS

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    1. Bradley Efron, 2020. "Prediction, Estimation, and Attribution," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 636-655, April.
    2. Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
    3. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
    4. Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
    5. Taylor, James W., 2020. "Forecast combinations for value at risk and expected shortfall," International Journal of Forecasting, Elsevier, vol. 36(2), pages 428-441.
    6. Athanasopoulos, George & Ahmed, Roman A. & Hyndman, Rob J., 2009. "Hierarchical forecasts for Australian domestic tourism," International Journal of Forecasting, Elsevier, vol. 25(1), pages 146-166.
    7. Du, Ning & Budescu, David V. & Shelly, Marjorie K. & Omer, Thomas C., 2011. "The appeal of vague financial forecasts," Organizational Behavior and Human Decision Processes, Elsevier, vol. 114(2), pages 179-189, March.
    8. Snyder, Ralph D. & Koehler, Anne B. & Hyndman, Rob J. & Ord, J. Keith, 2004. "Exponential smoothing models: Means and variances for lead-time demand," European Journal of Operational Research, Elsevier, vol. 158(2), pages 444-455, October.
    9. Bradley Efron, 2020. "Prediction, Estimation, and Attribution," International Statistical Review, International Statistical Institute, vol. 88(S1), pages 28-59, December.
    10. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios, 2020. "The M4 Competition: 100,000 time series and 61 forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(1), pages 54-74.
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    Cited by:

    1. Xu Gong & Mengjie Li & Keqin Guan & Chuanwang Sun, 2023. "Climate change attention and carbon futures return prediction," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(9), pages 1261-1288, September.

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    More about this item

    Keywords

    M5 Competition; Interval forecasts; Predictive distributions; Data analysis; Hierarchical data;
    All these keywords.

    JEL classification:

    • M5 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics

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