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

Mariana Botelho da Gama; John P Cartlidge; Antigoni Polychroniadou; Nigel P Smart; Younes Talibi Alaoui

doi:10.1007/978-3-031-18283-9_2

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

Mariana Botelho da Gama, John P Cartlidge, Antigoni Polychroniadou, Nigel P Smart, Younes Talibi Alaoui

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

4 Citations (Scopus)

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.

Original language	English
Title of host publication	Financial Cryptography and Data Security. FC 2022.
Subtitle of host publication	Lecture Notes in Computer Science
Editors	I Eyal, J Garay
Publisher	Springer, Cham
Pages	20-37
Number of pages	18
Volume	13411
ISBN (Electronic)	9783031182839
ISBN (Print)	9783031182822
DOIs	https://doi.org/10.1007/978-3-031-18283-9_2
Publication status	Published - 2 May 2022
Event	Financial Cryptography and Data Security - St. George's, Grenada Duration: 2 May 2022 → 6 May 2022 Conference number: 26 https://fc22.ifca.ai/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13411 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Financial Cryptography and Data Security
Abbreviated title	FC
Country/Territory	Grenada
City	St. George's
Period	2/05/22 → 6/05/22
Internet address	https://fc22.ifca.ai/

Bibliographical note

Funding Information:
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.

Publisher Copyright:
© 2022, International Financial Cryptography Association.

Keywords

dark pool
mechanism design
financial trading
financial technology
multi-party computation

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10.1007/978-3-031-18283-9_2Licence: Unspecified

https://eprint.iacr.org/2021/1549.pdfLicence: CC BY
https://fc22.ifca.ai/preproceedings/27.pdfLicence: Unspecified
https://eprint.iacr.org/2021/1549Licence: CC BY

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Botelho da Gama, M., Cartlidge, J. P., Polychroniadou, A., Smart, N. P., & Talibi Alaoui, Y. (2022). Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets. In I. Eyal, & J. Garay (Eds.), Financial Cryptography and Data Security. FC 2022.: Lecture Notes in Computer Science (Vol. 13411, pp. 20-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13411 LNCS). Springer, Cham. https://doi.org/10.1007/978-3-031-18283-9_2

Botelho da Gama, Mariana ; Cartlidge, John P ; Polychroniadou, Antigoni et al. / Kicking-the-Bucket : Fast Privacy-Preserving Trading Using Buckets. Financial Cryptography and Data Security. FC 2022.: Lecture Notes in Computer Science. editor / I Eyal ; J Garay. Vol. 13411 Springer, Cham, 2022. pp. 20-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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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author = "{Botelho da Gama}, Mariana and Cartlidge, {John P} and Antigoni Polychroniadou and Smart, {Nigel P} and {Talibi Alaoui}, Younes",

note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 2022, International Financial Cryptography Association.; Financial Cryptography and Data Security, FC ; Conference date: 02-05-2022 Through 06-05-2022",

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Botelho da Gama, M, Cartlidge, JP, Polychroniadou, A, Smart, NP & Talibi Alaoui, Y 2022, Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets. in I Eyal & J Garay (eds), Financial Cryptography and Data Security. FC 2022.: Lecture Notes in Computer Science. vol. 13411, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13411 LNCS, Springer, Cham, pp. 20-37, Financial Cryptography and Data Security, St. George's, Grenada, 2/05/22. https://doi.org/10.1007/978-3-031-18283-9_2

Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets. / Botelho da Gama, Mariana; Cartlidge, John P; Polychroniadou, Antigoni et al.
Financial Cryptography and Data Security. FC 2022.: Lecture Notes in Computer Science. ed. / I Eyal; J Garay. Vol. 13411 Springer, Cham, 2022. p. 20-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13411 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Kicking-the-Bucket

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AU - Botelho da Gama, Mariana

AU - Cartlidge, John P

AU - Polychroniadou, Antigoni

AU - Smart, Nigel P

AU - Talibi Alaoui, Younes

N1 - Conference code: 26

PY - 2022/5/2

Y1 - 2022/5/2

N2 - 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.

AB - 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.

KW - dark pool

KW - mechanism design

KW - financial trading

KW - financial technology

KW - multi-party computation

U2 - 10.1007/978-3-031-18283-9_2

DO - 10.1007/978-3-031-18283-9_2

M3 - Conference Contribution (Conference Proceeding)

SN - 9783031182822

VL - 13411

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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A2 - Garay, J

PB - Springer, Cham

Y2 - 2 May 2022 through 6 May 2022

ER -

Botelho da Gama M, Cartlidge JP, Polychroniadou A, Smart NP, Talibi Alaoui Y. Kicking-the-Bucket: Fast Privacy-Preserving Trading Using Buckets. In Eyal I, Garay J, editors, Financial Cryptography and Data Security. FC 2022.: Lecture Notes in Computer Science. Vol. 13411. Springer, Cham. 2022. p. 20-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-18283-9_2

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

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