IDEAS home Printed from https://ideas.repec.org/a/spr/envsyd/v36y2016i2d10.1007_s10669-016-9597-2.html
   My bibliography  Save this article

Visual analysis to support regulators in electronic order book markets

Author

Listed:
  • Mark E. Paddrik

    (U.S. Department of the Treasury)

  • Richard Haynes

    (Commodity Futures Trading Commission)

  • Andrew E. Todd

    (University of Virginia)

  • William T. Scherer

    (University of Virginia)

  • Peter A. Beling

    (University of Virginia)

Abstract

Electronic markets and automated trading have resulted in a drastic increase in the quantity and complexity of regulatory data. Reconstructing the limit order book and analyzing order flow is an emerging challenge for financial regulators. New order types, intra-market behavior, and other exchange functionality further complicate the task of understanding market behavior at multiple levels. Data visualizations have proven to be a fundamental tool for building intuition and enabling exploratory data analysis in many fields. In this paper, we propose the incorporation of visualizations in the workflow of multiple financial regulatory roles, including market surveillance, enforcement and supporting academic research.

Suggested Citation

  • Mark E. Paddrik & Richard Haynes & Andrew E. Todd & William T. Scherer & Peter A. Beling, 2016. "Visual analysis to support regulators in electronic order book markets," Environment Systems and Decisions, Springer, vol. 36(2), pages 167-182, June.
    • Handle: RePEc:spr:envsyd:v:36:y:2016:i:2:d:10.1007_s10669-016-9597-2
    DOI: 10.1007/s10669-016-9597-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10669-016-9597-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10669-016-9597-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Olivier Blanchard, 2009. "The Crisis: Basic Mechanisms and Appropriate Policies," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(01), pages 3-14, April.
    2. Harris, Larry, 2002. "Trading and Exchanges: Market Microstructure for Practitioners," OUP Catalogue, Oxford University Press, number 9780195144703.
    3. Sarlin, Peter, 2016. "Macroprudential oversight, risk communication and visualization," Journal of Financial Stability, Elsevier, vol. 27(C), pages 160-179.
    4. Flood, Mark D. & Lemieux, Victoria L. & Varga, Margaret & William Wong, B.L., 2016. "The application of visual analytics to financial stability monitoring," Journal of Financial Stability, Elsevier, vol. 27(C), pages 180-197.
    5. Andrew Todd & Peter Beling & William Scherer, 2016. "Crossed and Locked Quotes in a Multi-Market Simulation," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-19, March.
    6. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    7. Roy L. Hayes & Peter A. Beling & William T. Scherer, 2013. "Action-based feature representation for reverse engineering trading strategies," Environment Systems and Decisions, Springer, vol. 33(3), pages 413-426, September.
    8. Steve Y. Yang & Qifeng Qiao & Peter A. Beling & William T. Scherer & Andrei A. Kirilenko, 2015. "Gaussian process-based algorithmic trading strategy identification," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1683-1703, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marjolein E. Verhulst & Philippe Debie & Stephan Hageboeck & Joost M. E. Pennings & Cornelis Gardebroek & Axel Naumann & Paul van Leeuwen & Andres A. Trujillo‐Barrera & Lorenzo Moneta, 2021. "When two worlds collide: Using particle physics tools to visualize the limit order book," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1715-1734, November.
    2. Qifeng Qiao & Peter A. Beling, 2016. "Decision analytics and machine learning in economic and financial systems," Environment Systems and Decisions, Springer, vol. 36(2), pages 109-113, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marcello Rambaldi & Emmanuel Bacry & Jean-Franc{c}ois Muzy, 2018. "Disentangling and quantifying market participant volatility contributions," Papers 1807.07036, arXiv.org.
    2. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.
    3. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    4. Kinsella, Stephen, 2019. "Visualising economic crises using accounting models," Accounting, Organizations and Society, Elsevier, vol. 75(C), pages 1-16.
    5. Qifeng Qiao & Peter A. Beling, 2016. "Decision analytics and machine learning in economic and financial systems," Environment Systems and Decisions, Springer, vol. 36(2), pages 109-113, June.
    6. Mark Paddrik & Richard Haynes & Andrew E. Todd & Peter A. Beling & William T. Scherer, 2014. "The Role of Visual Analysis in the Regulation of Electronic Order Book Markets," Staff Discussion Papers 14-02, Office of Financial Research, US Department of the Treasury.
    7. Zhibin Niu & Runlin Li & Junqi Wu & Dawei Cheng & Jiawan Zhang, 2020. "iConViz: Interactive Visual Exploration of the Default Contagion Risk of Networked-Guarantee Loans," Papers 2006.09542, arXiv.org, revised Aug 2020.
    8. Paul Ormerod, 2010. "La crisis actual y la culpabilidad de la teoría macroeconómica," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 12(22), pages 111-128, January-J.
    9. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    10. Panayi, Efstathios & Peters, Gareth W. & Danielsson, Jon & Zigrand, Jean-Pierre, 2018. "Designating market maker behaviour in limit order book markets," Econometrics and Statistics, Elsevier, vol. 5(C), pages 20-44.
    11. Mahmoud Mahfouz & Angelos Filos & Cyrine Chtourou & Joshua Lockhart & Samuel Assefa & Manuela Veloso & Danilo Mandic & Tucker Balch, 2019. "On the Importance of Opponent Modeling in Auction Markets," Papers 1911.12816, arXiv.org.
    12. Marios Panayides & Barbara Rindi & Ingrid M.Werner, 2017. "Trading Fees and Intermarket Competition," BAFFI CAREFIN Working Papers 1751, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    13. Matthew Zook & Michael H Grote, 2017. "The microgeographies of global finance: High-frequency trading and the construction of information inequality," Environment and Planning A, , vol. 49(1), pages 121-140, January.
    14. Álvaro Cartea & José Penalva, 2012. "Where is the Value in High Frequency Trading?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-46.
    15. Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
    16. Robert J. Kauffman & Yuzhou Hu & Dan Ma, 2015. "Will high-frequency trading practices transform the financial markets in the Asia Pacific Region?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-27, December.
    17. Gagnon, Marie-Hélène & Gimet, Céline, 2013. "The impacts of standard monetary and budgetary policies on liquidity and financial markets: International evidence from the credit freeze crisis," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4599-4614.
    18. George Jiang & Ingrid Lo & Giorgio Valente, 2014. "High-Frequency Trading around Macroeconomic News Announcements: Evidence from the U.S. Treasury Market," Staff Working Papers 14-56, Bank of Canada.
    19. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    20. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:envsyd:v:36:y:2016:i:2:d:10.1007_s10669-016-9597-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.