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(Martingale) Optimal Transport And Anomaly Detection With Neural Networks: A Primal-Dual Algorithm

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  • Pierre Henry-Labordère

    (Societe Generale - Société Générale)

Abstract

In this paper, we introduce a primal-dual algorithm for solving (martingale) optimal transportation problems, with cost functions satisfying the twist condition, close to the one that has been used recently for training generative adversarial networks. As some additional applications, we consider anomaly detection and automatic generation of financial data.

Suggested Citation

  • Pierre Henry-Labordère, 2019. "(Martingale) Optimal Transport And Anomaly Detection With Neural Networks: A Primal-Dual Algorithm," Working Papers hal-02095222, HAL.
    • Handle: RePEc:hal:wpaper:hal-02095222
    Note: View the original document on HAL open archive server: https://hal.science/hal-02095222
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    References listed on IDEAS

    as
    1. Pierre Henry-Labordère & Nizar Touzi, 2016. "An explicit martingale version of the one-dimensional Brenier theorem," Finance and Stochastics, Springer, vol. 20(3), pages 635-668, July.
    2. Alfred Galichon & Pierre Henri-Labordère & Nizar Touzi, 2013. "A stochastic control approach to No-Arbitrage bounds given marginals, with an application to Lookback options," Sciences Po publications info:hdl:2441/5rkqqmvrn4t, Sciences Po.
    3. Pierre Henry-Labordère, 2013. "Automated Option Pricing: Numerical Methods," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(08), pages 1-27.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Stéphane Crépey & Lehdili Noureddine & Nisrine Madhar & Maud Thomas, 2022. "Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural Networks," Working Papers hal-03777995, HAL.
    2. St'ephane Cr'epey & Lehdili Noureddine & Nisrine Madhar & Maud Thomas, 2022. "Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural Networks," Papers 2209.11686, arXiv.org, revised Oct 2022.
    3. Ariel Neufeld & Julian Sester & Daiying Yin, 2022. "Detecting data-driven robust statistical arbitrage strategies with deep neural networks," Papers 2203.03179, arXiv.org, revised Feb 2024.
    4. Joshua Zoen-Git Hiew & Tongseok Lim & Brendan Pass & Marcelo Cruz de Souza, 2023. "Geometry of vectorial martingale optimal transport and robust option pricing," Papers 2309.04947, arXiv.org, revised Sep 2023.
    5. Ariel Neufeld & Julian Sester, 2021. "Model-free price bounds under dynamic option trading," Papers 2101.01024, arXiv.org, revised Jul 2021.
    6. Hans Buhler & Blanka Horvath & Terry Lyons & Imanol Perez Arribas & Ben Wood, 2020. "A Data-driven Market Simulator for Small Data Environments," Papers 2006.14498, arXiv.org.

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