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Pré-Publication, Document De Travail Année : 2019

Deep Prediction Of Investor Interest: a Supervised Clustering Approach

Résumé

We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given timeframe. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a simulated scenario inspired by real data and then apply it to a large proprietary database from BNP Paribas Corporate and Institutional Banking.
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Dates et versions

hal-02276055 , version 1 (02-09-2019)
hal-02276055 , version 2 (12-11-2019)
hal-02276055 , version 3 (26-02-2021)

Identifiants

  • HAL Id : hal-02276055 , version 2

Citer

Baptiste Barreau, Laurent Carlier, Damien Challet. Deep Prediction Of Investor Interest: a Supervised Clustering Approach. 2019. ⟨hal-02276055v2⟩

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