Defining and Controlling Information Leakage in US Equities Trading

Authors: Arthur Américo (Proof Trading), Allison Bishop (Proof Trading and City College, CUNY), Paul Cesaretti (Graduate Center, CUNY and Proof Trading), Garrison Grogan, Adam McKoy (Proof Trading), Robert Nicholas Moss (Proof Trading), Lisa Oakley (Notheastern University and Proof Trading), Marcel Ribeiro (Proof Trading), Mohammad Shokri (Graduate Center, CUNY and Proof Trading)

Volume: 2024
Issue: 2
Pages: 351–371
DOI: https://doi.org/10.56553/popets-2024-0054

Artifact: Reproduced

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Abstract: 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.

Keywords: Differential Privacy, Equities Trading, Quantitative Information Flow, Optimization, Information Leakage

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