Bounded Temporal Fairness for FIFO Financial Markets

TL;DR

This paper examines the challenges of achieving fair treatment in FIFO financial markets, highlighting the impracticality of unbounded fairness and proposing a bounded fairness approach called epsilon-fairness.

Contribution

It introduces epsilon-fairness as a practical bounded fairness model and analyzes its implementation in real-world market scenarios.

Findings

Unbounded fairness is unrealistic in FIFO markets.

Implementation inefficiencies can lead to unfair advantages.

Epsilon-fairness offers a bounded, practical fairness solution.

Abstract

Financial exchange operators cater to the needs of their users while simultaneously ensuring compliance with the financial regulations. In this work, we focus on the operators' commitment for fair treatment of all competing participants. We first discuss unbounded temporal fairness and then investigate its implementation and infrastructure requirements for exchanges. We find that these requirements can be fully met only under ideal conditions and argue that unbounded fairness in FIFO markets is unrealistic. To further support this claim, we analyse several real-world incidents and show that subtle implementation inefficiencies and technical optimizations suffice to give unfair advantages to a minority of the participants. We finally introduce, {\epsilon}-fairness, a bounded definition of temporal fairness and discuss how it can be combined with non-continuous market designs to provide equal participant treatment with minimum divergence from the existing market operation.