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Retail trading and analyst coverage

Author

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  • Martineau, Charles
  • Zoican, Marius

Abstract

How does retail trading impact information supply in financial markets? We build a trading model with endogenous information supply where analysts maximize trading volume by institutional investors. In equilibrium, sell-side analysts provide higher quality signals in stocks with large retail interest, as institutional investors can trade more aggressively without revealing information. We provide empirical evidence supporting the main prediction of the model: A one standard deviation increase in retail trading leads to an additional 0.6 analysts covering the stock. To establish causality, we confirm our results using stock splits as a plausibly exogenous shock to retail trading.

Suggested Citation

  • Martineau, Charles & Zoican, Marius, 2023. "Retail trading and analyst coverage," Journal of Financial Markets, Elsevier, vol. 66(C).
  • Handle: RePEc:eee:finmar:v:66:y:2023:i:c:s1386418123000472
    DOI: 10.1016/j.finmar.2023.100849
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    References listed on IDEAS

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    1. Grossman, Sanford J, 1976. "On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information," Journal of Finance, American Finance Association, vol. 31(2), pages 573-585, May.
    2. Barrot, Jean-Noel & Kaniel, Ron & Sraer, David, 2016. "Are retail traders compensated for providing liquidity?," Journal of Financial Economics, Elsevier, vol. 120(1), pages 146-168.
    3. Verrecchia, Robert E, 1982. "Information Acquisition in a Noisy Rational Expectations Economy," Econometrica, Econometric Society, vol. 50(6), pages 1415-1430, November.
    4. Allaudeen Hameed & Randall Morck & Jianfeng Shen & Bernard Yeung, 2015. "Information, Analysts, and Stock Return Comovement," The Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3153-3187.
    5. Wei Jiang, 2017. "Have Instrumental Variables Brought Us Closer to the Truth," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 6(2), pages 127-140.
    6. Boris Groysberg & Paul M. Healy & David A. Maber, 2011. "What Drives Sell‐Side Analyst Compensation at High‐Status Investment Banks?," Journal of Accounting Research, Wiley Blackwell, vol. 49(4), pages 969-1000, September.
    7. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    8. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," Working Papers 18-08, New York University, Leonard N. Stern School of Business, Department of Economics.
    9. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    10. Juliane Begenau & Maryam Farboodi & Laura Veldkamp, 2018. "Big Data in Finance and the Growth of Large Firms," NBER Working Papers 24550, National Bureau of Economic Research, Inc.
    11. Ron Kaniel & Gideon Saar & Sheridan Titman, 2008. "Individual Investor Trading and Stock Returns," Journal of Finance, American Finance Association, vol. 63(1), pages 273-310, February.
    12. Michael W. Brandt & Alon Brav & John R. Graham & Alok Kumar, 2010. "The Idiosyncratic Volatility Puzzle: Time Trend or Speculative Episodes?," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 863-899, February.
    13. Alex Chinco & Vyacheslav Fos, 2021. "The Sound of Many Funds Rebalancing," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 11(3), pages 502-551.
    14. Brad M. Barber & Xing Huang & Terrance Odean & Christopher Schwarz, 2022. "Attention‐Induced Trading and Returns: Evidence from Robinhood Users," Journal of Finance, American Finance Association, vol. 77(6), pages 3141-3190, December.
    15. Ekkehart Boehmer & Charles M. Jones & Xiaoyan Zhang & Xinran Zhang, 2021. "Tracking Retail Investor Activity," Journal of Finance, American Finance Association, vol. 76(5), pages 2249-2305, October.
    16. 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.
    17. Eaton, Gregory W. & Green, T. Clifton & Roseman, Brian S. & Wu, Yanbin, 2022. "Retail trader sophistication and stock market quality: Evidence from brokerage outages," Journal of Financial Economics, Elsevier, vol. 146(2), pages 502-528.
    18. Ozik, Gideon & Sadka, Ronnie & Shen, Siyi, 2021. "Flattening the Illiquidity Curve: Retail Trading During the COVID-19 Lockdown," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(7), pages 2356-2388, November.
    19. Jordi Mondria & Xavier Vives & Liyan Yang, 2022. "Costly Interpretation of Asset Prices," Management Science, INFORMS, vol. 68(1), pages 52-74, January.
    20. Juliane Begenau & Laura Veldkamp & Maryam Farboodi, 2018. "Big Data in Finance and the Growth of Large Firms," 2018 Meeting Papers 155, Society for Economic Dynamics.
    21. Wang, Jiang, 1994. "A Model of Competitive Stock Trading Volume," Journal of Political Economy, University of Chicago Press, vol. 102(1), pages 127-168, February.
    22. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    23. Joshua Livnat & Richard R. Mendenhall, 2006. "Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 44(1), pages 177-205, March.
    24. Bhushan, Ravi, 1989. "Firm characteristics and analyst following," Journal of Accounting and Economics, Elsevier, vol. 11(2-3), pages 255-274, July.
    25. Justin Cox & Bonnie Van Ness & Robert Van Ness, 2022. "Stock splits and retail trading," The Financial Review, Eastern Finance Association, vol. 57(4), pages 731-750, November.
    26. Harrison Hong & Jeffrey D. Kubik, 2003. "Analyzing the Analysts: Career Concerns and Biased Earnings Forecasts," Journal of Finance, American Finance Association, vol. 58(1), pages 313-351, February.
    27. 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.
    28. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    29. Mary E. Barth & Ron Kasznik & Maureen F. McNichols, 2001. "Analyst Coverage and Intangible Assets," Journal of Accounting Research, Wiley Blackwell, vol. 39(1), pages 1-34, June.
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    More about this item

    Keywords

    Retail trading; Analyst coverage; Liquidity; Price efficiency;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G40 - Financial Economics - - Behavioral Finance - - - General
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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