Deep Prediction of Investor Interest: a Supervised Clustering Approach

09/11/2019
by   Baptiste Barreau, et al.
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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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