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Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets

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Financial Cryptography and Data Security (FC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13411))

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Abstract

We examine bucket-based and volume-based algorithms for privacy-preserving asset trading in a financial dark pool. Our bucket-based algorithm places orders in quantised buckets, whereas the volume-based algorithm allows any volume size but requires more complex validation mechanisms. In all cases, we conclude that these algorithms are highly efficient and offer a practical solution to the commercial problem of preserving privacy of order information in a dark pool trading venue.

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Notes

  1. 1.

    Plus one engine that serves as an entry gateway for orders; therefore a total of 282 engines required.

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Acknowledgments

This work has been supported in part by ERC Advanced Grant ERC-2015-AdG-IMPaCT, by the FWO under an Odysseus project GOH9718N, and by CyberSecurity Research Flanders with reference number VR20192203. Additionally, the first author is supported by the Flemish Government through FWO SBO project SNIPPET S007619N. The second author is sponsored by Refinitiv.

This paper was prepared in part for information purposes by the Artificial Intelligence Research group of JPMorgan Chase & Co and its affiliates (“JPMorgan”), and is not a product of the Research Department of JPMorgan. JPMorgan makes no representation and warranty whatsoever and disclaims all liability, for the completeness, accuracy or reliability of the information contained herein. This document is not intended as investment research or investment advice, or a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, financial product or service, or to be used in any way for evaluating the merits of participating in any transaction, and shall not constitute a solicitation under any jurisdiction or to any person, if such solicitation under such jurisdiction or to such person would be unlawful.

Author information

Authors and Affiliations

  1. imec-COSIC, KU Leuven, Leuven, Belgium

    Mariana Botelho da Gama, Nigel P. Smart & Younes Talibi Alaoui

  2. University of Bristol, Bristol, UK

    John Cartlidge

  3. J. P. Morgan AI Research, New York, USA

    Antigoni Polychroniadou

Authors
  1. Mariana Botelho da Gama
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  2. John Cartlidge
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  3. Antigoni Polychroniadou
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  4. Nigel P. Smart
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  5. Younes Talibi Alaoui
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Corresponding author

Correspondence to Nigel P. Smart .

Editor information

Editors and Affiliations

  1. Technion - Israel Institute of Technology, Haifa, Israel

    Ittay Eyal

  2. Texas A&M University, College Station, TX, USA

    Juan Garay

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© 2022 International Financial Cryptography Association

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da Gama, M.B., Cartlidge, J., Polychroniadou, A., Smart, N.P., Alaoui, Y.T. (2022). Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets. In: Eyal, I., Garay, J. (eds) Financial Cryptography and Data Security. FC 2022. Lecture Notes in Computer Science, vol 13411. Springer, Cham. https://doi.org/10.1007/978-3-031-18283-9_2

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  • DOI: https://doi.org/10.1007/978-3-031-18283-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18282-2

  • Online ISBN: 978-3-031-18283-9

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