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Simple Bayesian Forecast Combination

Author

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  • PHILIP HANS FRANSES

    (Econometric Institute, Erasmus School of Economics, POB 1738, NL-3000 DR Rotterdam, The Netherlands)

Abstract

In this paper, it is proposed to combine the forecasts using a simple Bayesian forecast combination algorithm. The algorithm is applied to forecasts from three non-nested diffusion models for S shaped processes like virus diffusion. An illustration to daily data on first-wave cumulative Covid-19 cases in the Netherlands shows the ease of use of the algorithm and the accuracy of the newly combined forecasts.

Suggested Citation

  • Philip Hans Franses, 2020. "Simple Bayesian Forecast Combination," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-7, December.
    • Handle: RePEc:wsi:afexxx:v:15:y:2020:i:04:n:s2010495220500165
    DOI: 10.1142/S2010495220500165
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    Cited by:

    1. Juntao Li & Tianxu Cui & Kaiwen Yang & Ruiping Yuan & Liyan He & Mengtao Li, 2021. "Demand Forecasting of E-Commerce Enterprises Based on Horizontal Federated Learning from the Perspective of Sustainable Development," Sustainability, MDPI, vol. 13(23), pages 1-29, November.

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