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Market versus limit orders of speculative high-frequency traders and price discovery

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  • Kang, Jongho
  • Kang, Jangkoo
  • Kwon, Kyung Yoon

Abstract

The Korea Composite Stock Price Index (KOSPI) 200 futures market is one of the largest and most liquid index derivatives markets globally. We utilize high-quality intraday data on KOSPI 200 futures and find that high-frequency traders’ (HFTs’) market orders contribute much more to price discovery than their limit orders, as opposed to the findings of Brogaard, Hendershott, and Riordan (2019) in the Canadian equity market. To explain this phenomenon, we suggest that HFTs in the KOSPI 200 futures market are more speculative traders rather than market makers, which makes market orders more informative.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:riibaf:v:63:y:2022:i:c:s0275531922001805
    DOI: 10.1016/j.ribaf.2022.101794
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    References listed on IDEAS

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    1. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    2. 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.
    3. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    4. Benos, Evangelos & Sagade, Satchit, 2016. "Price discovery and the cross-section of high-frequency trading," Journal of Financial Markets, Elsevier, vol. 30(C), pages 54-77.
    5. Avanidhar Subrahmanyam & Hui Zheng, 2016. "Limit order placement by high-frequency traders," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(4), pages 185-209, December.
    6. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    7. Chen Yao & Mao Ye, 2018. "Why Trading Speed Matters: A Tale of Queue Rationing under Price Controls," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2157-2183.
    8. Hasbrouck, Joel, 1991. "The Summary Informativeness of Stock Trades: An Econometric Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 571-595.
    9. 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.
    10. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    11. Park, Seongkyu Gilbert & Ryu, Doojin, 2019. "Speed and trading behavior in an order-driven market," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 145-164.
    12. 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.
    13. Baron, Matthew & Brogaard, Jonathan & Hagströmer, Björn & Kirilenko, Andrei, 2019. "Risk and Return in High-Frequency Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 993-1024, June.
    14. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    15. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    16. Brogaard, Jonathan & Hendershott, Terrence & Riordan, Ryan, 2017. "High frequency trading and the 2008 short-sale ban," Journal of Financial Economics, Elsevier, vol. 124(1), pages 22-42.
    17. Webb, Robert I. & Ryu, Doojin & Ryu, Doowon & Han, Joongho, 2016. "The price impact of futures trades and their intraday seasonality," Emerging Markets Review, Elsevier, vol. 26(C), pages 80-98.
    18. Li, Sida & Wang, Xin & Ye, Mao, 2021. "Who provides liquidity, and when?," Journal of Financial Economics, Elsevier, vol. 141(3), pages 968-980.
    19. Eun Jung Lee, 2015. "High Frequency Trading in the Korean Index Futures Market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 35(1), pages 31-51, January.
    20. Tarun Chordia & T Clifton Green & Badrinath Kottimukkalur, 2018. "Rent Seeking by Low-Latency Traders: Evidence from Trading on Macroeconomic Announcements," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4650-4687.
    21. Jangkoo Kang & Kyung Yoon Kwon & Wooyeon Kim, 2020. "Flow toxicity of high‐frequency trading and its impact on price volatility: Evidence from the KOSPI 200 futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(2), pages 164-191, February.
    22. 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.
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    More about this item

    Keywords

    High-frequency trading; Price discovery; Limit order; Market order; KOSPI 200 futures;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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