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Algorithmic trading: Intraday profitability and trading behavior

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  • Arumugam, Devika

Abstract

This study examines the intraday profitability and interactions among Buy-side Algorithmic Traders (BATs), High-Frequency Traders (HFTs) and Non-Algorithmic Traders (NATs). When all trades are considered, ATs gain, and NATs lose. Demanding liquidity benefits all traders, with BATs outperforming HFTs. HFTs and NATs lose while providing liquidity, but BATs gain. Intraday timing efficiency increases NATs' trading but not ATs'. Market volatility triggers opposing trading behaviors; As volatility increases, BATs retreat while HFTs intensify trading, possibly driven by opposing hedging and speculative motives, respectively. BATs and HFTs exhibit within-group positive probabilities with their order imbalances. An increase in BATs' order imbalance decreases the likelihood of HFTs’ trading.

Suggested Citation

  • Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
    • Handle: RePEc:eee:ecmode:v:128:y:2023:i:c:s0264999323003334
    DOI: 10.1016/j.econmod.2023.106521
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    References listed on IDEAS

    as
    1. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2015. "Do High‐Frequency Data Improve High‐Dimensional Portfolio Allocations?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(2), pages 263-290, March.
    2. 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.
    3. Chakravarty, Sugato, 2001. "Stealth-trading: Which traders' trades move stock prices?," Journal of Financial Economics, Elsevier, vol. 61(2), pages 289-307, August.
    4. Aaron Tornell & Chunming Yuan, 2012. "Speculation and hedging in the currency futures markets: Are they informative to the spot exchange rates," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(2), pages 122-151, February.
    5. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    6. Arumugam, Devika & Prasanna, P. Krishna & Marathe, Rahul R., 2023. "Do algorithmic traders exploit volatility?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    7. 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.
    8. Hu, Yingyi & Prigent, Jean-Luc, 2019. "Information asymmetry, cluster trading, and market efficiency: Evidence from the Chinese stock market," Economic Modelling, Elsevier, vol. 80(C), pages 11-22.
    9. Arumugam, Devika & Krishna Prasanna, P., 2021. "Commonality and contrarian trading among algorithmic traders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    10. 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.
    11. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2012. "Multivariate high‐frequency‐based volatility (HEAVY) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 907-933, September.
    12. Joanne Hill & Thomas Schneeweis, 1982. "The Hedging Effectiveness Of Foreign Currency Futures," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 5(1), pages 95-104, March.
    13. Zi Ning & Yiuman Tse, 2009. "Order Imbalance in the FTSE Index Futures Market: Electronic versus Open Outcry Trading," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(1‐2), pages 230-252, January.
    14. Andrei A. Kirilenko & Andrew W. Lo, 2013. "Moore's Law versus Murphy's Law: Algorithmic Trading and Its Discontents," Journal of Economic Perspectives, American Economic Association, vol. 27(2), pages 51-72, Spring.
    15. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    16. Attila Ceffer & Norbert Fogarasi & Janos Levendovszky, 2018. "Trading by estimating the quantized forward distribution," Applied Economics, Taylor & Francis Journals, vol. 50(59), pages 6397-6405, December.
    17. Xiangkang Yin & Jing Zhao, 2015. "A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1210-1234, November.
    18. Yacine Aït-Sahalia & Mehmet Saglam, 2013. "High Frequency Traders: Taking Advantage of Speed," NBER Working Papers 19531, National Bureau of Economic Research, Inc.
    19. Devika Arumugam & P Krishna Prasanna, 2021. "A Game of Hide-and-Seek between Proprietary and Buy-Side Algorithmic Traders: Causal links with Market Quality," Applied Economics, Taylor & Francis Journals, vol. 53(41), pages 4788-4798, September.
    20. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    21. Chin‐Wen Hsln & Jerry Kuo & Cheng‐Few Lee, 1994. "A new measure to compare the hedging effectiveness of foreign currency futures versus options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 14(6), pages 685-707, September.
    22. Zi Ning & Yiuman Tse, 2009. "Order Imbalance in the FTSE Index Futures Market: Electronic versus Open Outcry Trading," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(1-2), pages 230-252.
    23. 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.
    24. Gagnon, Louis & Lypny, Gregory J. & McCurdy, Thomas H., 1998. "Hedging foreign currency portfolios," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 197-220, September.
    25. Locke, P R & Sayers, C L, 1993. "Intra-day Futures Price Volatility: Information Effects and Variance Persistence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 15-30, Jan.-Marc.
    26. Andreas Röthig, 2011. "On speculators and hedgers in currency futures markets: who leads whom?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 16(1), pages 63-69, January.
    27. Itay Goldstein & Yan Li & Liyan Yang, 2014. "Speculation and Hedging in Segmented Markets," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 881-922.
    28. 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.
    29. Manaster, Steven & Mann, Steven C, 1996. "Life in the Pits: Competitive Market Making and Inventory Control," The Review of Financial Studies, Society for Financial Studies, vol. 9(3), pages 953-975.
    30. repec:bla:jfinan:v:43:y:1988:i:1:p:97-112 is not listed on IDEAS
    31. Lai, Hung-Cheng & Wang, Kuan-Min, 2014. "Relationship between the trading behavior of three institutional investors and Taiwan Stock Index futures returns," Economic Modelling, Elsevier, vol. 41(C), pages 156-165.
    32. Kissell, Robert, 2013. "The Science of Algorithmic Trading and Portfolio Management," Elsevier Monographs, Elsevier, edition 1, number 9780124016897.
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    More about this item

    Keywords

    Algorithmic trading; High-frequency trading; Profitability; Intraday trading; High-frequency finance;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G40 - Financial Economics - - Behavioral Finance - - - General

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