Abstract

This paper examines how the Investors Exchange (IEX) integrates socio -technical mechanisms to promote fairness in high -frequency trading environments. Our study focuses on the IEX’s Crumbling Quote Indicator (CQI), a predictive algorithm designed to mitiga te latency arbitrage and protect long -term investors. We analyze the algorithmic incorporation of financial market fairness principles into market design and examine how the resulting protective mechanisms enhance investor confidence and participation. Usi ng reverse -engineered training data reconstruction, we analyze the evolution of CQI versions 5.1 and 5.2. The ongoing refinement of the CQI by the market operator demonstrates how this innovation is adapted to evolving market contexts and conditions. Thus, the IEX case shows that fairness, ensured algorithmically, is a moving target, continuously redefined by the co -evolution of technical subsystems (algorithms) and social subsystems (trading strategies)

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