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Order aggressiveness and flash crashes

Author

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  • 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
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    References listed on IDEAS

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    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. 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.
    8. 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.
    9. 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.
    10. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    11. 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.
    12. 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.
    13. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    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.
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