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High-frequency traders and price informativeness during earnings announcements

Author

Listed:
  • Nilabhra Bhattacharya

    (Southern Methodist University)

  • Bidisha Chakrabarty

    (Saint Louis University)

  • Xu (Frank) Wang

    (Saint Louis University)

Abstract

High frequency traders (HFTs) account for a significant fraction of the total market volume. Prompted by concerns that HFTs reap unfair advantages over other traders by using super-fast trading technologies, some regulatory proposals aim to curb HFTs’ ultra-low-latency activities. However, research suggests that HFTs also play beneficial roles in financial markets, including liquidity provision as voluntary market makers. Currently, little is known about their role in incorporating firm-specific fundamental information into prices. Employing a novel dataset that identifies trades by HFTs and non-HFTs, we find that earnings response coefficients are larger and abnormal price impact of trades are lower when HFTs trade more following earnings announcements, suggesting that HFTs facilitate efficient assimilation of earnings news. HFTs also enhance the forecasting capabilities of financial analysts. Furthermore, HFT participation increases return synchronicity around earnings announcements when multiple firms in the same industry announce earnings on the same day. The evidence suggests that HFTs help incorporate relevant industry information, and this effect arises from HFTs’ liquidity supplying function. We address the endogenous preference of HFTs for large and liquid stocks by including multiple controls for firm size and liquidity, implementing abnormal or change specification for the price impact tests, and performing pre-treatment placebo tests for all of our analyses.

Suggested Citation

  • Nilabhra Bhattacharya & Bidisha Chakrabarty & Xu (Frank) Wang, 2020. "High-frequency traders and price informativeness during earnings announcements," Review of Accounting Studies, Springer, vol. 25(3), pages 1156-1199, September.
  • Handle: RePEc:spr:reaccs:v:25:y:2020:i:3:d:10.1007_s11142-020-09550-z
    DOI: 10.1007/s11142-020-09550-z
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    as
    1. Ekkehart Boehmer & Dan Li & Gideon Saar, 2018. "The Competitive Landscape of High-Frequency Trading Firms," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2227-2276.
    2. Bessembinder, Hendrik & Kaufman, Herbert M., 1997. "A Comparison of Trade Execution Costs for NYSE and NASDAQ-Listed Stocks," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(3), pages 287-310, September.
    3. Brown, Ld & Richardson, Gd & Schwager, Sj, 1987. "An Information Interpretation Of Financial Analyst Superiority In Forecasting Earnings," Journal of Accounting Research, Wiley Blackwell, vol. 25(1), pages 49-67.
    4. Henk Berkman & Cameron Truong, 2009. "Event Day 0? After‐Hours Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 47(1), pages 71-103, March.
    5. Verrecchia, Robert E, 1982. "Information Acquisition in a Noisy Rational Expectations Economy," Econometrica, Econometric Society, vol. 50(6), pages 1415-1430, November.
    6. Karl B. Diether & Christopher J. Malloy & Anna Scherbina, 2002. "Differences of Opinion and the Cross Section of Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2113-2141, October.
    7. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    8. Lee, Charles M C & Mucklow, Belinda & Ready, Mark J, 1993. "Spreads, Depths, and the Impact of Earnings Information: An Intraday Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 345-374.
    9. Daniel Bradley & Jonathan Clarke & Suzanne Lee & Chayawat Ornthanalai, 2014. "Are Analysts’ Recommendations Informative? Intraday Evidence on the Impact of Time Stamp Delays," Journal of Finance, American Finance Association, vol. 69(2), pages 645-673, April.
    10. repec:bla:jfinan:v:44:y:1989:i:3:p:633-46 is not listed on IDEAS
    11. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    12. Jin, Li & Myers, Stewart C., 2006. "R2 around the world: New theory and new tests," Journal of Financial Economics, Elsevier, vol. 79(2), pages 257-292, February.
    13. 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.
    14. Krinsky, Itzhak & Lee, Jason, 1996. "Earnings Announcements and the Components of the Bid-Ask Spread," Journal of Finance, American Finance Association, vol. 51(4), pages 1523-1535, September.
    15. 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.
    16. Conrad, Jennifer & Wahal, Sunil & Xiang, Jin, 2015. "High-frequency quoting, trading, and the efficiency of prices," Journal of Financial Economics, Elsevier, vol. 116(2), pages 271-291.
    17. Huang, Roger D. & Stoll, Hans R., 1996. "Dealer versus auction markets: A paired comparison of execution costs on NASDAQ and the NYSE," Journal of Financial Economics, Elsevier, vol. 41(3), pages 313-357, July.
    18. 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.
    19. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    20. Subramanyam, K. R., 1996. "The pricing of discretionary accruals," Journal of Accounting and Economics, Elsevier, vol. 22(1-3), pages 249-281, October.
    21. Frankel, Richard & Litov, Lubomir, 2009. "Earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 47(1-2), pages 182-190, March.
    22. Frankel, Richard & Kothari, S.P. & Weber, Joseph, 2006. "Determinants of the informativeness of analyst research," Journal of Accounting and Economics, Elsevier, vol. 41(1-2), pages 29-54, April.
    23. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1469-1497, August.
    24. Lawrence, Alastair, 2013. "Individual investors and financial disclosure," Journal of Accounting and Economics, Elsevier, vol. 56(1), pages 130-147.
    25. 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.
    26. Abarbanell, Jeffery S., 1991. "Do analysts' earnings forecasts incorporate information in prior stock price changes?," Journal of Accounting and Economics, Elsevier, vol. 14(2), pages 147-165, June.
    27. Dechow, Patricia & Ge, Weili & Schrand, Catherine, 2010. "Understanding earnings quality: A review of the proxies, their determinants and their consequences," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 344-401, December.
    28. Collins, Daniel W. & Kothari, S. P., 1989. "An analysis of intertemporal and cross-sectional determinants of earnings response coefficients," Journal of Accounting and Economics, Elsevier, vol. 11(2-3), pages 143-181, July.
    29. Stefano Dellavigna & Joshua M. Pollet, 2009. "Investor Inattention and Friday Earnings Announcements," Journal of Finance, American Finance Association, vol. 64(2), pages 709-749, April.
    30. Chakrabarty, Bidisha & Moulton, Pamela C., 2012. "Earnings announcements and attention constraints: The role of market design," Journal of Accounting and Economics, Elsevier, vol. 53(3), pages 612-634.
    31. Lev, B, 1989. "On The Usefulness Of Earnings And Earnings Research - Lessons And Directions From 2 Decades Of Empirical-Research," Journal of Accounting Research, Wiley Blackwell, vol. 27, pages 153-192.
    32. Jeremiah W. Bentley & Theodore E. Christensen & Kurt H. Gee & Benjamin C. Whipple, 2018. "Disentangling Managers’ and Analysts’ Non‐GAAP Reporting," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1039-1081, September.
    33. Dichev, Ilia D. & Tang, Vicki Wei, 2009. "Earnings volatility and earnings predictability," Journal of Accounting and Economics, Elsevier, vol. 47(1-2), pages 160-181, March.
    34. 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.
    35. Rosenbaum, Paul R., 2010. "Design Sensitivity and Efficiency in Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 692-702.
    36. Lys, Thomas & Sohn, Sungkyu, 1990. "The association between revisions of financial analysts' earnings forecasts and security-price changes," Journal of Accounting and Economics, Elsevier, vol. 13(4), pages 341-363, December.
    37. Jiang, Christine X. & Likitapiwat, Tanakorn & McInish, Thomas H., 2012. "Information Content of Earnings Announcements: Evidence from After-Hours Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1303-1330, December.
    38. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    39. Nilabhra Bhattacharya & Hemang Desai & Kumar Venkataraman, 2013. "Does Earnings Quality Affect Information Asymmetry? Evidence from Trading Costs," Contemporary Accounting Research, John Wiley & Sons, vol. 30(2), pages 482-516, June.
    40. Mozes, Haim A., 2003. "Accuracy, usefulness and the evaluation of analysts' forecasts," International Journal of Forecasting, Elsevier, vol. 19(3), pages 417-434.
    41. Michael J. Fishman & Kathleen M. Hagerty, 1989. "Disclosure Decisions by Firms and the Competition for Price Efficiency," Journal of Finance, American Finance Association, vol. 44(3), pages 633-646, July.
    42. Asquith, Paul & Mikhail, Michael B. & Au, Andrea S., 2005. "Information content of equity analyst reports," Journal of Financial Economics, Elsevier, vol. 75(2), pages 245-282, February.
    43. 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.
    44. Frino, Alex & Prodromou, Tina & Wang, George H.K. & Westerholm, P. Joakim & Zheng, Hui, 2017. "An empirical analysis of algorithmic trading around earnings announcements," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 34-51.
    45. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    46. Li, Feng, 2008. "Annual report readability, current earnings, and earnings persistence," Journal of Accounting and Economics, Elsevier, vol. 45(2-3), pages 221-247, August.
    47. David Hirshleifer & Sonya Seongyeon Lim & Siew Hong Teoh, 2009. "Driven to Distraction: Extraneous Events and Underreaction to Earnings News," Journal of Finance, American Finance Association, vol. 64(5), pages 2289-2325, October.
    48. 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.
    49. I. Krinsky & J. Lee, 1996. "Earning Announcements and the Components of the Bid-Ask Aspread," Quantitative Studies in Economics and Population Research Reports 313, McMaster University.
    50. Zhang, Yuan, 2008. "Analyst responsiveness and the post-earnings-announcement drift," Journal of Accounting and Economics, Elsevier, vol. 46(1), pages 201-215, September.
    51. deHaan, Ed & Shevlin, Terry & Thornock, Jacob, 2015. "Market (in)attention and the strategic scheduling and timing of earnings announcements," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 36-55.
    52. Hasbrouck, Joel & Seppi, Duane J., 2001. "Common factors in prices, order flows, and liquidity," Journal of Financial Economics, Elsevier, vol. 59(3), pages 383-411, March.
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    More about this item

    Keywords

    High frequency trading; Earnings announcements; Earnings response coefficient; Price impact of trades; Analyst forecast;
    All these keywords.

    JEL classification:

    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • 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
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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