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Deep Prediction Of Investor Interest: a Supervised Clustering Approach

Author

Listed:
  • Baptiste Barreau

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec, BNPP CIB GM Lab - BNP Paribas CIB Global Markets Data & AI Lab)

  • Laurent Carlier

    (BNPP CIB GM Lab - BNP Paribas CIB Global Markets Data & AI Lab)

  • Damien Challet

    (MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec)

Abstract

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.

Suggested Citation

  • Baptiste Barreau & Laurent Carlier & Damien Challet, 2021. "Deep Prediction Of Investor Interest: a Supervised Clustering Approach," Post-Print hal-02276055, HAL.
    • Handle: RePEc:hal:journl:hal-02276055
    DOI: 10.3233/AF-200296
    Note: View the original document on HAL open archive server: https://hal.science/hal-02276055v3
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    References listed on IDEAS

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    1. Federico Musciotto & Luca Marotta & Jyrki Piilo & Rosario N. Mantegna, 2018. "Long-term ecology of investors in a financial market," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-12, December.
    2. Justin Sirignano & Rama Cont, 2018. "Universal features of price formation in financial markets: perspectives from Deep Learning," Papers 1803.06917, arXiv.org.
    3. Damien Challet & R'emy Chicheportiche & Mehdi Lallouache & Serge Kassibrakis, 2016. "Statistically validated lead-lag networks and inventory prediction in the foreign exchange market," Papers 1609.04640, arXiv.org, revised Jul 2018.
    4. Justin Sirignano & Rama Cont, 2018. "Universal features of price formation in financial markets: perspectives from Deep Learning," Working Papers hal-01754054, HAL.
    5. Kk{e}stutis Baltakys & Juho Kanniainen & Frank Emmert-Streib, 2017. "Multilayer Aggregation with Statistical Validation: Application to Investor Networks," Papers 1708.09850, arXiv.org, revised May 2018.
    6. repec:wsi:acsxxx:v:21:y:2018:i:08:n:s0219525918500194 is not listed on IDEAS
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    More about this item

    Keywords

    investor activity prediction; deep learning; neural networks; mixture of experts; clustering;
    All these keywords.

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