Paper 2023/971
Defining and Controlling Information Leakage in US Equities Trading
, Proof Trading, City College CUNYAbstract
We present a new framework for defining information leakage in the setting of US equities trading, and construct methods for deriving trading schedules that stay within specified information leakage bounds. Our approach treats the stock market as an interactive protocol performed in the presence of an adversary, and draws inspiration from the related disciplines of differential privacy as well as quantitative information flow. We apply a linear programming solver using examples from historical trade and quote (TAQ) data for US equities and describe how this framework can inform actual algorithmic trading strategies.
Metadata
- Available format(s)
-
PDF
- Category
- Foundations
- Publication info
- Preprint.
- Keywords
- differential privacy
- Contact author(s)
-
arthuramerico @ gmail com
allison @ prooftrading com
pcesaretti @ gradcenter cuny edu
garrisonwgrogan @ gmail com
amckoy000 @ citymail cuny edu
robertnmoss @ icloud com
oakley l @ northeastern edu
marcel @ prooftrading com
mshokri @ gradcenter cuny edu - History
- 2023-06-21: approved
- 2023-06-21: received
- See all versions
- Short URL
- https://ia.cr/2023/971
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2023/971,
author = {Arthur Americo and Allison Bishop and Paul Cesaretti and Garrison Grogan and Adam McKoy and Robert Moss and Lisa Oakley and Marcel Ribeiro and Mohammad Shokri},
title = {Defining and Controlling Information Leakage in {US} Equities Trading},
howpublished = {Cryptology {ePrint} Archive, Paper 2023/971},
year = {2023},
url = {https://eprint.iacr.org/2023/971}
}
