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On single point forecasts for fat-tailed variables

Author

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  • Taleb, Nassim Nicholas
  • Bar-Yam, Yaneer
  • Cirillo, Pasquale

Abstract

We discuss common errors and fallacies when using naive “evidence based” empiricism and point forecasts for fat-tailed variables, as well as the insufficiency of using naive first-order scientific methods for tail risk management.

Suggested Citation

  • Taleb, Nassim Nicholas & Bar-Yam, Yaneer & Cirillo, Pasquale, 2022. "On single point forecasts for fat-tailed variables," International Journal of Forecasting, Elsevier, vol. 38(2), pages 413-422.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:2:p:413-422
    DOI: 10.1016/j.ijforecast.2020.08.008
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    References listed on IDEAS

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    1. Juan D. Borrero & Jesus Mariscal, 2022. "Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter," Mathematics, MDPI, vol. 10(16), pages 1-13, August.
    2. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).

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