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High Frequency Trading in the Korean Index Futures Market

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  • Eun Jung Lee

Abstract

We investigate the trading behavior of high frequency trading (HFT), the impact of HFT on market quality, its role in the price discovery process, and its profitability, using a very detailed data set of the KOSPI 200 index futures market. We find that high frequency traders (HFTs) do not provide liquidity in the futures market, nor does HFT have any role in enhancing market quality. Indeed, HFT is detrimental to the price discovery process. This finding is contrary to those in the existing literature on HFT in equity markets. We also find that profitable opportunities for HFTs are rare after transaction costs are considered, with the notable exception that foreign HFTs can earn a profit in the index futures market. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 35:31–51, 2015

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  • 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.
    • Handle: RePEc:wly:jfutmk:v:35:y:2015:i:1:p:31-51
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    1. Jian Yang & David A. Bessler & David J. Leatham, 2001. "Asset storability and price discovery in commodity futures markets: A new look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 279-300, March.
    2. Hyuk Choe & Bong-Chan Kho & René M. Stulz, 2005. "Do Domestic Investors Have an Edge? The Trading Experience of Foreign Investors in Korea," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 795-829.
    3. repec:bla:jfinan:v:43:y:1988:i:3:p:617-37 is not listed on IDEAS
    4. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.
    5. Krista Schwarz, 2012. "Are speculators informed?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 1-23, January.
    6. Grossman, S.J. & Miller, M.H., 1988. "Liquidity And Market Structure," Papers 88, Princeton, Department of Economics - Financial Research Center.
    7. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    8. Subrahmanyam, Avanidhar, 1991. "A Theory of Trading in Stock Index Futures," The Review of Financial Studies, Society for Financial Studies, vol. 4(1), pages 17-51.
    9. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    10. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    11. Grinblatt, Mark & Keloharju, Matti, 2000. "The investment behavior and performance of various investor types: a study of Finland's unique data set," Journal of Financial Economics, Elsevier, vol. 55(1), pages 43-67, January.
    12. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    13. Tomas Dvorak, 2001. "Do Domestic Investors Have an Information Advantage? Evidence from Indonesia," Center for Development Economics 168, Department of Economics, Williams College.
    14. Harald Hau, 2001. "Location Matters: An Examination of Trading Profits," Journal of Finance, American Finance Association, vol. 56(5), pages 1959-1983, October.
    15. 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.
    16. Chan, Kalok, 1992. "A Further Analysis of the Lead-Lag Relationship between the Cash Market and Stock Index Futures Market," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 123-152.
    17. Joon Chae & Jaeuk Khil & Eun Jung Lee, 2013. "Who Makes Markets? Liquidity Providers Versus Algorithmic Traders," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(5), pages 397-420, May.
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    Cited by:

    1. Yue Zhao & Difang Wan, 2018. "Institutional high frequency trading and price discovery: Evidence from an emerging commodity futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 243-270, February.
    2. Yang, Yurun & Göncü, Ahmet & Pantelous, Athanasios A., 2018. "Momentum and reversal strategies in Chinese commodity futures markets," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 177-196.
    3. Yang, Heejin & Kutan, Ali M. & Ryu, Doojin, 2019. "Volatility information trading in the index options market: An intraday analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 412-426.
    4. Nimalendran, Mahendrarajah & Rzayev, Khaladdin & Sagade, Satchit, 2024. "High-frequency trading in the stock market and the costs of options market making," LSE Research Online Documents on Economics 124228, London School of Economics and Political Science, LSE Library.
    5. 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).
    6. Carè, Rosella & Cumming, Douglas, 2024. "Technology and automation in financial trading: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 71(C).
    7. Nimalendran, Mahendrarajah & Rzayev, Khaladdin & Sagade, Satchit, 2022. "High-frequency trading in the stock market and the costs of option market making," LSE Research Online Documents on Economics 118885, London School of Economics and Political Science, LSE Library.
    8. Jeewon Jang & Jangkoo Kang & Jaeram Lee, 2023. "Who has an edge in trading index derivatives?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(3), pages 325-348, March.
    9. Zijian Shi & John Cartlidge, 2024. "Neural stochastic agent‐based limit order book simulation with neural point process and diffusion probabilistic model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
    10. Jongho Kang & Jangkoo Kang & Jaeram Lee, 2022. "Who and what drives informed options trading after the market opens?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 338-364, March.
    11. 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.
    12. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    13. Nimalendran, Mahendrarajah & Rzayev, Khaladdin & Sagade, Satchit, 2024. "High-frequency trading in the stock market and the costs of options market making," Journal of Financial Economics, Elsevier, vol. 159(C).
    14. Kim, Jun Sik & Ryu, Doojin, 2015. "Are the KOSPI 200 implied volatilities useful in value-at-risk models?," Emerging Markets Review, Elsevier, vol. 22(C), pages 43-64.
    15. Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2020. "Does Speed Matter? The Role Of High‐Frequency Trading For Order Book Resiliency," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 43(4), pages 933-964, December.
    16. Atilgan, Yigit & Demirtas, K. Ozgur & Simsek, Koray D., 2016. "Derivative markets in emerging economies: A survey," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 88-102.
    17. Phiri, Andrew, 2017. "Threshold convergence between the federal fund rate and South African equity returns around the colocation period," Business and Economic Horizons (BEH), Prague Development Center (PRADEC), vol. 13(1).
    18. Viktor Manahov, 2021. "High‐frequency trading order cancellations and market quality: Is stricter regulation the answer?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5385-5407, October.
    19. Olgun, Onur & Ekinci, Cumhur & Arıkan, Ramazan, 2024. "The performance of selected high-frequency trading proxies: An application on Turkish index futures market," Finance Research Letters, Elsevier, vol. 65(C).
    20. Zijian Shi & John Cartlidge, 2023. "Neural Stochastic Agent-Based Limit Order Book Simulation: A Hybrid Methodology," Papers 2303.00080, arXiv.org.
    21. Lee, Jaeram & Kang, Jangkoo & Ryu, Doojin, 2015. "Common deviation and regime-dependent dynamics in the index derivatives markets," Pacific-Basin Finance Journal, Elsevier, vol. 33(C), pages 1-22.
    22. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    23. Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2023. "The Impact of High-Frequency Trading on Modern Securities Markets," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 7-24, February.
    24. 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).
    25. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).

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