A Bayesian approach to developing a strategic early warning system for the French milk market

Christophe Bisson, Furkan Gurpinar

Abstract


A new approach is provided in our paper for creating a strategic early warning
system allowing the estimation of the future state of the milk market as scenarios. This is in
line with the recent call from the EU commission for tools that help to better address such a
highly volatile market. We applied different multivariate time series regression and Bayesian
networks on a pre-determined map of relations between macro-economic indicators. The
evaluation of our findings with root mean square error (RMSE) performance score enhances
the robustness of the prediction model constructed. Our model could be used by competitive
intelligence teams to obtain sharper scenarios, leading companies and public organisations to
better anticipate market changes and make more robust decisions.


Keywords


Bayesian networks, competitive intelligence, forecasting, milk market, strategic early warning system

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