Effects of Limit Order Book Information Level on Market Stability Metrics

Journal of Economic Interaction and Coordination, Forthcoming

Office of Financial Research Working Paper No. 14-09

27 Pages Posted: 22 Aug 2015 Last revised: 12 Nov 2015

See all articles by Mark E. Paddrik

Mark E. Paddrik

Government of the United States of America - Office of Financial Research

Roy Hayes

University of Virginia

William Scherer

University of Virginia

Peter Beling

University of Virginia, Dept. of System & Information Engineering

Date Written: November 25, 2014

Abstract

Using an agent-based model of the limit order book, we explore how the levels of information available to participants, exchanges, and regulators can be used to improve our understanding of the stability and resiliency of a market. Ultimately, we want to know if electronic market data contains previously undetected information that could allow us to better assess market stability. Using data produced in the controlled environment of an agent-based model’s limit order book, we examine various resiliency indicators to determine their predictive capabilities. Most of the types of data created have traditionally been available either publicly or on a restricted basis to regulators and exchanges, but other types have never been collected. We confirmed our findings using actual order flow data with user identifications included from the CME (Chicago Mercantile Exchange) and New York Mercantile Exchange (NYMEX). Our findings strongly suggest that high-fidelity microstructure data in combination with price data can be used to define stability indicators capable of reliably signaling a high likelihood for an imminent flash crash event about one minute before it occurs.

Suggested Citation

Paddrik, Mark Endel and Hayes, Roy Lee and Scherer, William and Beling, Peter, Effects of Limit Order Book Information Level on Market Stability Metrics (November 25, 2014). Journal of Economic Interaction and Coordination, Forthcoming, Office of Financial Research Working Paper No. 14-09, Available at SSRN: https://ssrn.com/abstract=2648457 or http://dx.doi.org/10.2139/ssrn.2648457

Mark Endel Paddrik (Contact Author)

Government of the United States of America - Office of Financial Research ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

Roy Lee Hayes

University of Virginia ( email )

United States

William Scherer

University of Virginia ( email )

United States

Peter Beling

University of Virginia, Dept. of System & Information Engineering ( email )

1400 University Ave
Charlottesville, VA 22903
United States

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