IDEAS home Printed from https://ideas.repec.org/a/eee/ememar/v65y2025ics1566014124001468.html
   My bibliography  Save this article

Message traffic and short-term illiquidity in high-speed markets

Author

Listed:
  • Abad, David
  • Massot, Magdalena
  • Nawn, Samarpan
  • Pascual, Roberto
  • Yagüe, José

Abstract

We examine which components of message traffic in a high-speed equity market, including orders from traders with varying technological capabilities, signal short-term illiquidity. Our findings show that only the unexpected component of high-frequency traders' (HFTs') net buying pressure — arising from both aggressive and non-aggressive orders — predicts increases in immediacy costs and price impacts. Updates to outstanding limit orders, driven by prior efficient pre returns, strengthen the signaling power of HFTs' order flow. Additionally, market-wide HFTs' net buying pressure improves the ability to forecast short-term illiquidity in individual stocks.

Suggested Citation

  • Abad, David & Massot, Magdalena & Nawn, Samarpan & Pascual, Roberto & Yagüe, José, 2025. "Message traffic and short-term illiquidity in high-speed markets," Emerging Markets Review, Elsevier, vol. 65(C).
  • Handle: RePEc:eee:ememar:v:65:y:2025:i:c:s1566014124001468
    DOI: 10.1016/j.ememar.2024.101251
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1566014124001468
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ememar.2024.101251?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. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    2. Ekkehart Boehmer & Dan Li & Gideon Saar, 2018. "The Competitive Landscape of High-Frequency Trading Firms," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2227-2276.
    3. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows," Review of Finance, European Finance Association, vol. 33(4), pages 1484-1533.
    4. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    5. Roberto Pascual & David Veredas, 2010. "Does the Open Limit Order Book Matter in Explaining Informational Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 57-87, Winter.
    6. Pierre Collin-Dufresne & Vyacheslav Fos, 2015. "Do Prices Reveal the Presence of Informed Trading?," Journal of Finance, American Finance Association, vol. 70(4), pages 1555-1582, August.
    7. Kim, Sukwon Thomas & Stoll, Hans R., 2014. "Are trading imbalances indicative of private information?," Journal of Financial Markets, Elsevier, vol. 20(C), pages 151-174.
    8. Stefan Nagel, 2012. "Evaporating Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 25(7), pages 2005-2039.
    9. Andriy Shkilko & Konstantin Sokolov, 2020. "Every Cloud Has a Silver Lining: Fast Trading, Microwave Connectivity, and Trading Costs," Journal of Finance, American Finance Association, vol. 75(6), pages 2899-2927, December.
    10. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    11. Rama Cont & Arseniy Kukanov & Sasha Stoikov, 2014. "The Price Impact of Order Book Events," Journal of Financial Econometrics, Oxford University Press, vol. 12(1), pages 47-88.
    12. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    13. Hasbrouck, Joel, 2018. "High-Frequency Quoting: Short-Term Volatility in Bids and Offers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 613-641, April.
    14. Benos, Evangelos & Brugler, James & Hjalmarsson, Erik & Zikes, Filip, 2017. "Interactions among High-Frequency Traders," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1375-1402, August.
    15. Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
    16. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    17. Thompson, Samuel B., 2011. "Simple formulas for standard errors that cluster by both firm and time," Journal of Financial Economics, Elsevier, vol. 99(1), pages 1-10, January.
    18. Charles Cao & Oliver Hansch & Xiaoxin Wang, 2009. "The information content of an open limit‐order book," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(1), pages 16-41, January.
    19. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    20. Jegadeesh N. & Titman S., 1995. "Short-Horizon Return Reversals and the Bid-Ask Spread," Journal of Financial Intermediation, Elsevier, vol. 4(2), pages 116-132, April.
    21. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2000. "Commonality in liquidity," Journal of Financial Economics, Elsevier, vol. 56(1), pages 3-28, April.
    22. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    23. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    24. Upson, James & Van Ness, Robert A., 2017. "Multiple markets, algorithmic trading, and market liquidity," Journal of Financial Markets, Elsevier, vol. 32(C), pages 49-68.
    25. Conrad, Jennifer & Wahal, Sunil & Xiang, Jin, 2015. "High-frequency quoting, trading, and the efficiency of prices," Journal of Financial Economics, Elsevier, vol. 116(2), pages 271-291.
    26. Albert J. Menkveld, 2016. "The Economics of High-Frequency Trading: Taking Stock," Annual Review of Financial Economics, Annual Reviews, vol. 8(1), pages 1-24, October.
    27. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2019. "Price Discovery without Trading: Evidence from Limit Orders," Journal of Finance, American Finance Association, vol. 74(4), pages 1621-1658, August.
    28. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "Liquidity and Autocorrelations in Individual Stock Returns," Journal of Finance, American Finance Association, vol. 61(5), pages 2365-2394, October.
    29. Bongaerts, Dion & Achter, Mark Van, 2021. "Competition among liquidity providers with access to high-frequency trading technology," Journal of Financial Economics, Elsevier, vol. 140(1), pages 220-249.
    30. Vincent Van Kervel & Albert J. Menkveld, 2019. "High‐Frequency Trading around Large Institutional Orders," Journal of Finance, American Finance Association, vol. 74(3), pages 1091-1137, June.
    31. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," The Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    32. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    33. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    34. Andersen, Torben G. & Bondarenko, Oleg, 2014. "VPIN and the flash crash," Journal of Financial Markets, Elsevier, vol. 17(C), pages 1-46.
    35. Easley, David & de Prado, Marcos Lopez & O'Hara, Maureen, 2016. "Discerning information from trade data," Journal of Financial Economics, Elsevier, vol. 120(2), pages 269-285.
    36. Andersen, Torben G. & Bondarenko, Oleg, 2014. "Reflecting on the VPIN dispute," Journal of Financial Markets, Elsevier, vol. 17(C), pages 53-64.
    37. Ho, Thomas & Stoll, Hans R., 1981. "Optimal dealer pricing under transactions and return uncertainty," Journal of Financial Economics, Elsevier, vol. 9(1), pages 47-73, March.
    38. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, Enero-Abr.
    39. Hasbrouck, Joel, 2007. "Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading," OUP Catalogue, Oxford University Press, number 9780195301649, Decembrie.
    40. Bae, Kee-Hong & Jang, Hasung & Park, Kyung Suh, 2003. "Traders' choice between limit and market orders: evidence from NYSE stocks," Journal of Financial Markets, Elsevier, vol. 6(4), pages 517-538, August.
    41. Mark S. Seasholes & Terrence Hendershott, 2007. "Market Maker Inventories and Stock Prices," American Economic Review, American Economic Association, vol. 97(2), pages 210-214, May.
    42. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    43. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1484-1533.
    44. Brogaard, Jonathan & Carrion, Allen & Moyaert, Thibaut & Riordan, Ryan & Shkilko, Andriy & Sokolov, Konstantin, 2018. "High frequency trading and extreme price movements," Journal of Financial Economics, Elsevier, vol. 128(2), pages 253-265.
    45. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    46. James J. Angel & Lawrence E. Harris & Chester S. Spatt, 2015. "Equity Trading in the 21st Century: An Update," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-39.
    47. Pierre Collin-Dufresne & Vyacheslav Fos, 2013. "Do Prices Reveal the Presence of Informed Trading?," Swiss Finance Institute Research Paper Series 13-69, Swiss Finance Institute, revised Sep 2015.
    48. Madhavan, Ananth & Sofianos, George, 1998. "An empirical analysis of NYSE specialist trading," Journal of Financial Economics, Elsevier, vol. 48(2), pages 189-210, May.
    49. Li, Sida & Wang, Xin & Ye, Mao, 2021. "Who provides liquidity, and when?," Journal of Financial Economics, Elsevier, vol. 141(3), pages 968-980.
    50. Brolley, Michael & Malinova, Katya, 2021. "Informed liquidity provision in a limit order market," Journal of Financial Markets, Elsevier, vol. 52(C).
    51. Anand, Amber & Venkataraman, Kumar, 2016. "Market conditions, fragility, and the economics of market making," Journal of Financial Economics, Elsevier, vol. 121(2), pages 327-349.
    52. Malceniece, Laura & Malcenieks, Kārlis & Putniņš, Tālis J., 2019. "High frequency trading and comovement in financial markets," Journal of Financial Economics, Elsevier, vol. 134(2), pages 381-399.
    53. Vincent van Kervel, 2015. "Competition for Order Flow with Fast and Slow Traders," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 2094-2127.
    54. Yashar H Barardehi & Dan Bernhardt & Ryan J Davies, 2019. "Trade-Time Measures of Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 32(1), pages 126-179.
    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. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    2. Cox, Justin & Woods, Donovan, 2023. "COVID-19 and market structure dynamics," Journal of Banking & Finance, Elsevier, vol. 147(C).
    3. Breckenfelder, Johannes, 2024. "Competition among high-frequency traders and market quality," Journal of Economic Dynamics and Control, Elsevier, vol. 166(C).
    4. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    5. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    6. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    7. Michael Goldstein & Amy Kwan & Richard Philip, 2023. "High-Frequency Trading Strategies," Management Science, INFORMS, vol. 69(8), pages 4413-4434, August.
    8. Aliyev, Nihad & Huseynov, Fariz & Rzayev, Khaladdin, 2022. "Algorithmic trading and investment-to-price sensitivity," LSE Research Online Documents on Economics 118844, London School of Economics and Political Science, LSE Library.
    9. Rzayev, Khaladdin & Ibikunle, Gbenga & Steffen, Tom, 2023. "The market quality implications of speed in cross-platform trading: Evidence from Frankfurt-London microwave," Journal of Financial Markets, Elsevier, vol. 66(C).
    10. Tripathi, Abhinava & Dixit, Alok & Vipul,, 2021. "Information content of order imbalance in an order-driven market: Indian Evidence," Finance Research Letters, Elsevier, vol. 41(C).
    11. Zheng, Jiayi & Zhu, Yushu, 2023. "Algorithmic trading and block ownership initiation: An information perspective," The British Accounting Review, Elsevier, vol. 55(4).
    12. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    13. Rzayev, Khaladdin & Ibikunle, Gbenga & Steffen, Tom, 2023. "The market quality implications of speed in cross-platform trading: evidence from Frankfurt-London microwave," LSE Research Online Documents on Economics 119989, London School of Economics and Political Science, LSE Library.
    14. Chakrabarty, Bidisha & Pascual, Roberto, 2023. "Stock liquidity and algorithmic market making during the COVID-19 crisis," Journal of Banking & Finance, Elsevier, vol. 147(C).
    15. Anagnostidis, Panagiotis & Fontaine, Patrice & Varsakelis, Christos, 2020. "Are high–frequency traders informed?," Economic Modelling, Elsevier, vol. 93(C), pages 365-383.
    16. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
    17. Xu, Ke, 2023. "High frequency market making during stressed periods," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 379-397.
    18. Anagnostidis, Panagiotis & Fontaine, Patrice, 2020. "Liquidity commonality and high frequency trading: Evidence from the French stock market," International Review of Financial Analysis, Elsevier, vol. 69(C).
    19. Bongaerts, Dion & Achter, Mark Van, 2021. "Competition among liquidity providers with access to high-frequency trading technology," Journal of Financial Economics, Elsevier, vol. 140(1), pages 220-249.
    20. Baldauf, Markus & Mollner, Joshua, 2022. "Fast traders make a quick buck: The role of speed in liquidity provision," Journal of Financial Markets, Elsevier, vol. 58(C).

    More about this item

    Keywords

    Order flow; HFT; Limit orders; Market orders; Cancellations; Toxicity;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:ememar:v:65:y:2025:i:c:s1566014124001468. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620356 .

    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.