IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i2p2647-2673.html
   My bibliography  Save this article

Order aggressiveness and flash crashes

Author

Listed:
  • Khaladdin Rzayev
  • Gbenga Ibikunle

Abstract

We present a novel framework illustrating the links between order aggressiveness and flash crashes. Our framework involves a trading sequence beginning with significant increases in aggressive sell orders relative to aggressive buy orders until instruments' prices fall to their lowest levels. Thereafter, a rise in aggressive buy orders propels prices back to their pre‐crash levels. Using a sample of S&P 500 stocks trading during the May 6, 2010, flash crash, we show that our framework is correctly specified and provide a basis for linking flash crashes to aggressive strategies, which are found to be more profitable during flash crashes.

Suggested Citation

  • Khaladdin Rzayev & Gbenga Ibikunle, 2021. "Order aggressiveness and flash crashes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2647-2673, April.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:2:p:2647-2673
    DOI: 10.1002/ijfe.1926
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.1926
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.1926?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
    ---><---

    References listed on IDEAS

    as
    1. Griffiths, Mark D. & Smith, Brian F. & Turnbull, D. Alasdair S. & White, Robert W., 2000. "The costs and determinants of order aggressiveness," Journal of Financial Economics, Elsevier, vol. 56(1), pages 65-88, April.
    2. Foucault, Thierry, 1998. "Order Flow Composition and Trading Costs in Dynamic Limit Order Markets," CEPR Discussion Papers 1817, C.E.P.R. Discussion Papers.
    3. Ibikunle, Gbenga, 2015. "Opening and closing price efficiency: Do financial markets need the call auction?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 208-227.
    4. Tarun Chordia & Richard Roll & Avanidhar Subrahmanyam, 2001. "Market Liquidity and Trading Activity," Journal of Finance, American Finance Association, vol. 56(2), pages 501-530, April.
    5. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. "An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    6. Andersen, Torben G. & Bondarenko, Oleg, 2014. "VPIN and the flash crash," Journal of Financial Markets, Elsevier, vol. 17(C), pages 1-46.
    7. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    8. Hans Degryse & Frank de Jong & Vincent van Kervel, 2015. "The Impact of Dark Trading and Visible Fragmentation on Market Quality," Review of Finance, European Finance Association, vol. 19(4), pages 1587-1622.
    9. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    10. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    11. 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.
    12. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    13. Hans Degryse & Frank De Jong & Maarten Van Ravenswaaij & Gunther Wuyts, 2005. "Aggressive Orders and the Resiliency of a Limit Order Market," Review of Finance, European Finance Association, vol. 9(2), pages 201-242.
    14. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "The Impact of Trades on Daily Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1241-1277.
    15. Ederington, Louis H. & Lee, Jae Ha, 1995. "The Short-Run Dynamics of the Price Adjustment to New Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(1), pages 117-134, March.
    16. Wu, Kesheng & Bethel, E. Wes & Gu, Ming & Leinweber, David & Rübe, Oliver, 2013. "A big data approach to analyzing market volatility," Algorithmic Finance, IOS Press, vol. 2(3-4), pages 241-267.
    17. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
    18. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, vol. 2(2), pages 99-134, May.
    19. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    20. 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.
    21. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    22. Frino, Alex & Ibikunle, Gbenga & Mollica, Vito & Steffen, Tom, 2018. "The impact of commodity benchmarks on derivatives markets: The case of the dated Brent assessment and Brent futures," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 27-43.
    23. Tom McInish & James Upson & Robert A. Wood, 2014. "The Flash Crash: Trading Aggressiveness, Liquidity Supply, and the Impact of Intermarket Sweep Orders," The Financial Review, Eastern Finance Association, vol. 49(3), pages 481-509, August.
    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. Rzayev, Khaladdin & Ibikunle, Gbenga, 2019. "A state-space modeling of the information content of trading volume," Journal of Financial Markets, Elsevier, vol. 46(C).
    2. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    3. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    4. Gbenga Ibikunle & Davide Mare & Yuxin Sun, 2020. "The paradoxical effects of market fragmentation on adverse selection risk and market efficiency," The European Journal of Finance, Taylor & Francis Journals, vol. 26(14), pages 1439-1461, September.
    5. Dimitri Vayanos & Jiang Wang, 2012. "Market Liquidity -- Theory and Empirical Evidence," NBER Working Papers 18251, National Bureau of Economic Research, Inc.
    6. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, January-A.
    7. Marvin Wee & Joey W. Yang, 2016. "The Evolution of Informed Liquidity Provision: Evidence from an Order†driven Market," European Financial Management, European Financial Management Association, vol. 22(5), pages 882-915, November.
    8. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 22, July-Dece.
    9. Ibikunle, Gbenga, 2018. "Trading places: Price leadership and the competition for order flow," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 178-200.
    10. Daniel Havran & Kata Varadi, 2015. "Price Impact and the Recovery of the Limit Order Book: Why Should We Care About Informed Liquidity Providers?," CERS-IE WORKING PAPERS 1540, Institute of Economics, Centre for Economic and Regional Studies.
    11. Ibikunle, Gbenga & Li, Youwei & Mare, Davide & Sun, Yuxin, 2021. "Dark matters: The effects of dark trading restrictions on liquidity and informational efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    12. 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).
    13. Hans Degryse & Frank Jong & Maarten Ravenswaaij & Gunther Wuyts, 2005. "Aggressive Orders and the Resiliency of a Limit Order Market," Review of Finance, Springer, vol. 9(2), pages 201-242, June.
    14. PASCUAL, Roberto & VEREDAS, David, 2006. "Does the open limit order book matter in explaining long run volatility ?," LIDAM Discussion Papers CORE 2006110, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. G. Wuyts, 2007. "Stock Market Liquidity.Determinants and Implications," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(2), pages 279-316.
    16. Lorne N. Switzer & Haibo Fan, 2010. "Limit Orders, Trading Activity, and Transactions Costs in Equity Futures in an Electronic Trading Environment," International Econometric Review (IER), Econometric Research Association, vol. 2(1), pages 11-35, April.
    17. Yildiz, Serhat & Van Ness, Bonnie & Van Ness, Robert, 2020. "VPIN, liquidity, and return volatility in the U.S. equity markets," Global Finance Journal, Elsevier, vol. 45(C).
    18. Ibikunle, Gbenga & Aquilina, Matteo & Diaz-Rainey, Ivan & Sun, Yuxin, 2021. "City goes dark: Dark trading and adverse selection in aggregate markets," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 1-22.
    19. Zhang, Zeyu & Ibikunle, Gbenga, 2023. "The market quality effects of sub-second frequent batch auctions: Evidence from dark trading restrictions," International Review of Financial Analysis, Elsevier, vol. 89(C).
    20. Helena Beltran & Alain Durré & Pierre Giot, 2004. "How does liquidity react to stress periods in a limit order market?," Working Paper Research 49, National Bank of Belgium.

    More about this item

    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:wly:ijfiec:v:26:y:2021:i:2:p:2647-2673. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.