IDEAS home Printed from https://ideas.repec.org/p/frd/wpaper/dp2012_04.html

Regime Identification in Limit Order Books

Author

Listed:
  • Rossen Trendafilov

    (Fordham University)

  • Erick W Rengifo

    (Fordham University)

Abstract

This article develops and implements a new methodology for identifying intraday information regimes in limit order books. Based on Lehmann (2008), in an information regime all the information is trade related and arrives via order ?ow and, the fundamental value that underlines the prices does not change, it is simply translated by the size of the executed market order and the back?lling adjustment. During an information regime the best quotes and the underlying values follow a path de?ned by the limit order book. A change of information regime within a given day is shown to alter the provision of liquidity to the market with consequences for asset prices, trading behavior, and optimal trading strategies. By applying wavelet theory we have developed a methodology that allowed us to clearly identify information regimes. Our results show that information regimes have an impact on price formation and price discovery, including dynamic issues such as the process by which prices come to capture information over time. The discovery and ideate?cation of information regimes essentially uncovers the mechanism by which latent demands are translated into realized prices and volumes. These results empirically support Lehmann�s theoretical model.

Suggested Citation

  • Rossen Trendafilov & Erick W Rengifo, 2012. "Regime Identification in Limit Order Books," Fordham Economics Discussion Paper Series dp2012_04, Fordham University, Department of Economics.
  • Handle: RePEc:frd:wpaper:dp2012_04
    as

    Download full text from publisher

    File URL: https://archive.fordham.edu/ECONOMICS_RESEARCH/PAPERS/dp2012_04_rengifo.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    2. Bruce Lehmann, 2008. "Arbitrage-free Limit Order Books and the Pricing of Order Flow Risk," NBER Working Papers 13848, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    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. Andrea Attar & Thomas Mariotti & François Salanié, 2020. "The Social Costs of Side Trading," The Economic Journal, Royal Economic Society, vol. 130(630), pages 1608-1622.
    2. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    3. Portniaguina, Evgenia & Bernhardt, Dan & Hughson, Eric, 2006. "Hybrid markets, tick size and investor trading costs," Journal of Financial Markets, Elsevier, vol. 9(4), pages 433-447, November.
    4. Baruch, Shmuel & Panayides, Marios & Venkataraman, Kumar, 2017. "Informed trading and price discovery before corporate events," Journal of Financial Economics, Elsevier, vol. 125(3), pages 561-588.
    5. Craig Pirrong, 1996. "Market liquidity and depth on computerized and open outcry trading systems: A comparison of DTB and LIFFE bund contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(5), pages 519-543, August.
    6. Hwang, Hae-shin & Jindapon, Paan, 2020. "Market making with convex quotes," Finance Research Letters, Elsevier, vol. 37(C).
    7. Bondarenko, Oleg, 2001. "Competing market makers, liquidity provision, and bid-ask spreads," Journal of Financial Markets, Elsevier, vol. 4(3), pages 269-308, June.
    8. Babus, Ana & Parlatore, Cecilia, 2022. "Strategic fragmented markets," Journal of Financial Economics, Elsevier, vol. 145(3), pages 876-908.
    9. Menkhoff, Lukas & Osler, Carol L. & Schmeling, Maik, 2010. "Limit-order submission strategies under asymmetric information," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2665-2677, November.
    10. Bodnar, Taras & Hautsch, Nikolaus, 2012. "Copula-based dynamic conditional correlation multiplicative error processes," SFB 649 Discussion Papers 2012-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Bayona, Anna & Dumitrescu, Ariadna & Manzano, Carolina, 2023. "Information and optimal trading strategies with dark pools," Economic Modelling, Elsevier, vol. 126(C).
    12. Hong Guo & Jianwu Lin & Fanlin Huang, 2023. "Market Making with Deep Reinforcement Learning from Limit Order Books," Papers 2305.15821, arXiv.org.
    13. J. Doyne Farmer & Austin Gerig & Fabrizio Lillo & Henri Waelbroeck, 2013. "How efficiency shapes market impact," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1743-1758, November.
    14. Thierry Foucault & Sophie Moinas & Erik Theissen, 2007. "Does Anonymity Matter in Electronic Limit Order Markets?," The Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1707-1747, 2007 28.
    15. Hagströmer, Björn, 2021. "Bias in the effective bid-ask spread," Journal of Financial Economics, Elsevier, vol. 142(1), pages 314-337.
    16. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    17. Wong, Woon K. & Liu, Bo & Zeng, Yong, 2009. "Can price limits help when the price is falling? Evidence from transactions data on the Shanghai Stock Exchange," China Economic Review, Elsevier, vol. 20(1), pages 91-102, March.
    18. Frey, Stefan & Sandås, Patrik, 2009. "The impact of iceberg orders in limit order books," CFR Working Papers 09-06, University of Cologne, Centre for Financial Research (CFR).
    19. Alan G. Isaac & Vasudeva Ramaswamy, 2023. "Rule-based trading on an order-driven exchange: a reassessment," Quantitative Finance, Taylor & Francis Journals, vol. 23(12), pages 1871-1886, November.
    20. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

    Statistics

    Access and download statistics

    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:frd:wpaper:dp2012_04. 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: Fordham Economics (email available below). General contact details of provider: https://edirc.repec.org/data/edforus.html .

    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.