Concurrent neural network: a model of competition between times series

Rémy Garnier ()
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Rémy Garnier: Universite de Cergy-Pontoise

Annals of Operations Research, 2022, vol. 313, issue 2, No 16, 945-964

Abstract: Abstract Competition between times series often arises in sales prediction, when similar products are on sale on a marketplace. This article provides a model of the presence of cannibalization between times series. This model creates a "competitiveness" function that depends on external features such as price and margin. It also provides a theoretical guaranty on the error of the model under some reasonable conditions, and implement this model using a neural network to compute this competitiveness function. This implementation outperforms other traditional time series methods and classical neural networks for market share prediction on a real-world data set. Moreover, it allows controlling underprediction, which plagues traditional forecasts models.

Keywords: High dimensional times series; Multivariate count times series; Non-stationnary times series; Sales forecasting; Cannibalization; Competition modeling; E-commerce data (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-021-04253-3

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