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Trading performance and market efficiency: Evidence from algorithmic trading

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  • Syamala, Sudhakara Reddy
  • Wadhwa, Kavita

Abstract

In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.

Suggested Citation

  • Syamala, Sudhakara Reddy & Wadhwa, Kavita, 2020. "Trading performance and market efficiency: Evidence from algorithmic trading," Research in International Business and Finance, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:riibaf:v:54:y:2020:i:c:s0275531920304050
    DOI: 10.1016/j.ribaf.2020.101283
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    References listed on IDEAS

    as
    1. Syamala, Sudhakara Reddy & Wadhwa, Kavita & Goyal, Abhinav, 2017. "Determinants of commonality in liquidity: Evidence from an order-driven emerging market," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 38-52.
    2. Roman Kozhan & Wing Wah Tham, 2012. "Execution Risk in High-Frequency Arbitrage," Management Science, INFORMS, vol. 58(11), pages 2131-2149, November.
    3. Kewei Hou & Tobias J. Moskowitz, 2005. "Market Frictions, Price Delay, and the Cross-Section of Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 981-1020.
    4. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    5. 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.
    6. Bruno Biais & Thierry Foucault, 2014. "HFT and Market Quality," Bankers, Markets & Investors, ESKA Publishing, issue 128, pages 5-19, January-F.
    7. Hasabrouck, Joel & Sofianos, George, 1993. "The Trades of Market Makers: An Empirical Analysis of NYSE Specialists," Journal of Finance, American Finance Association, vol. 48(5), pages 1565-1593, December.
    8. Kelejian, Harry H. & Mukerji, Purba, 2016. "Does high frequency algorithmic trading matter for non-AT investors?," Research in International Business and Finance, Elsevier, vol. 37(C), pages 78-92.
    9. Syamala, Sudhakar Reddy & Reddy, V. Nagi & Goyal, Abhinav, 2014. "Commonality in liquidity: An empirical examination of emerging order-driven equity and derivatives market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 317-334.
    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. Thierry Foucault & Albert J. Menkveld, 2008. "Competition for Order Flow and Smart Order Routing Systems," Journal of Finance, American Finance Association, vol. 63(1), pages 119-158, February.
    12. Mech, Timothy S., 1993. "Portfolio return autocorrelation," Journal of Financial Economics, Elsevier, vol. 34(3), pages 307-344, December.
    13. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    14. 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.
    15. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    16. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    17. Ben Ammar, Imen & Hellara, Slaheddine & Ghadhab, Imen, 2020. "High-frequency trading and stock liquidity: An intraday analysis," Research in International Business and Finance, Elsevier, vol. 53(C).
    18. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2005. "Evidence on the speed of convergence to market efficiency," Journal of Financial Economics, Elsevier, vol. 76(2), pages 271-292, May.
    19. 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.
    20. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    21. 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.
    22. Dubey, Ritesh Kumar & Chauhan, Yogesh & Syamala, Sudhakara Reddy, 2017. "Evidence of algorithmic trading from Indian equity market: Interpreting the transaction velocity element of financialization," Research in International Business and Finance, Elsevier, vol. 42(C), pages 31-38.
    23. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    24. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    25. Nidhi Aggarwal & Susan Thomas, 2014. "The causal impact of algorithmic trading on market quality," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-023, Indira Gandhi Institute of Development Research, Mumbai, India.
    26. 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.
    27. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    28. Wadhwa, Kavita & Nagi Reddy, V. & Goyal, Abhinav & Mohamed, Abdulkadir, 2016. "IPOs and SEOs, real investments, and market timing: Emerging market evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 21-41.
    29. repec:bla:jfinan:v:43:y:1988:i:1:p:97-112 is not listed on IDEAS
    30. Brennan, Michael J & Jegadeesh, Narasimhan & Swaminathan, Bhaskaran, 1993. "Investment Analysis and the Adjustment of Stock Prices to Common Information," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 799-824.
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    More about this item

    Keywords

    Algorithmic trading; VWAP; Trading performance; Intraday trading;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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