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Order Flow and Market State in Quasi-Centralized Limit Order Books

Article arXiv papers · Author: Martin D. Gould et al.
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Summary

This study examines quasi-centralized limit order books, where institutions can trade only with counterparties for whom they have sufficient bilateral credit. It analyzes high-quality data from a large electronic trading platform that uses this structure, focusing on how order flow and market state behave in this setting.

The reported results differ in many significant ways from findings commonly reported for other limit order books. The study also finds that distributions of order flow and market state vary across trading days, but can be aligned onto a common curve through simple linear rescaling. Based on that pattern, it proposes a semi-parametric model for a single trading day. The model performs similarly to parametric curve-fitting approaches while requiring less computation and being faster to implement. The evidence is specific to the platform and data studied, so the excerpt does not establish that the observed scaling or model performance generalizes to other venues or markets.

Key ideas

  • A quasi-centralized order book restricts trading to counterparties with adequate bilateral credit.
  • The empirical analysis reports meaningful differences from patterns described for other limit order books.
  • Linear rescaling brings daily order-flow and market-state distributions onto a common curve.
  • A semi-parametric single-day model offers performance similar to curve fitting with simpler, faster implementation.

Tags

Market microstructureStatisticsExecution
Full text
# Quasi-Centralized Limit Order Books


# Quasi-Centralized Limit Order Books









A quasi-centralized limit order book (QCLOB) is a limit order book (LOB) in which financial institutions can only access the trading opportunities offered by counterparties with whom they possess sufficient bilateral credit. We perform an empirical analysis of a recent, high-quality data set from a large electronic trading platform that utilizes QCLOBs to facilitate trade. We find many significant differences between our results and those widely reported for other LOBs. We also uncover a remarkable empirical universality: although the distributions describing order flow and market state vary considerably across days, a simple, linear rescaling causes them to collapse onto a single curve. Motivated by this finding, we propose a semi-parametric model of order flow and market state in a QCLOB on a single trading day. Our model provides similar performance to that of parametric curve-fitting techniques, while being simpler to compute and faster to implement.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.