IDEAS home Printed from https://ideas.repec.org/p/cvh/coecwp/2018-03.html
   My bibliography  Save this paper

Could crowdsourced financial analysis replace the equity research by investment banks?

Author

Listed:
  • Kommel, Karl Arnold
  • Sillasoo, Martin
  • Lublóy, Ágnes

Abstract

Equity research is gaining popularity in crowd-sourced information sharing platforms. This study analyses S&P 100 companies stock recommendations and user-contributed articles published on Seeking Alpha platform over a three-year period; and investigates whether investment banks’ rating consensus or the sentiment of single-ticker articles published by Seeking Alpha contributors can predict future abnormal returns more accurately. We find that both analyst groups underperform the market. Trading strategies based on the sentiment of the opinion articles perform worse than trading strategies designed around the recommendations of security analysts. Analyst recommendations are expected to remain relevant, there is no immediate pressure from crowd-sourced equity research for changing the business model.

Suggested Citation

  • Kommel, Karl Arnold & Sillasoo, Martin & Lublóy, Ágnes, 2018. "Could crowdsourced financial analysis replace the equity research by investment banks?," Corvinus Economics Working Papers (CEWP) 2018/03, Corvinus University of Budapest.
  • Handle: RePEc:cvh:coecwp:2018/03
    as

    Download full text from publisher

    File URL: https://unipub.lib.uni-corvinus.hu/3733/
    File Function: original version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Womack, Kent L, 1996. "Do Brokerage Analysts' Recommendations Have Investment Value?," Journal of Finance, American Finance Association, vol. 51(1), pages 137-167, March.
    2. Barber, Brad M. & Loeffler, Douglas, 1993. "The “Dartboard†Column: Second-Hand Information and Price Pressure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(2), pages 273-284, June.
    3. Christopher N. Avery & Judith A. Chevalier & Richard J. Zeckhauser, 2016. "The "CAPS" Prediction System and Stock Market Returns," Review of Finance, European Finance Association, vol. 20(4), pages 1363-1381.
    4. Tim Loughran & Bill Mcdonald, 2014. "Measuring Readability in Financial Disclosures," Journal of Finance, American Finance Association, vol. 69(4), pages 1643-1671, August.
    5. Anup Agrawal & Mark A. Chen, 2008. "Do Analyst Conflicts Matter? Evidence from Stock Recommendations," Journal of Law and Economics, University of Chicago Press, vol. 51(3), pages 503-537, August.
    6. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    7. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
    8. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    9. John S. Howe & Emre Unlu & Xuemin (Sterling) Yan, 2009. "The Predictive Content of Aggregate Analyst Recommendations," Journal of Accounting Research, Wiley Blackwell, vol. 47(3), pages 799-821, June.
    10. Michela Nardo & Marco Petracco-Giudici & Minás Naltsidis, 2016. "Walking Down Wall Street With A Tablet: A Survey Of Stock Market Predictions Using The Web," Journal of Economic Surveys, Wiley Blackwell, vol. 30(2), pages 356-369, April.
    11. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    12. Barber, Brad M. & Lehavy, Reuven & Trueman, Brett, 2007. "Comparing the stock recommendation performance of investment banks and independent research firms," Journal of Financial Economics, Elsevier, vol. 85(2), pages 490-517, August.
    13. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    14. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    15. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    16. R. David Mclean & Jeffrey Pontiff, 2016. "Does Academic Research Destroy Stock Return Predictability?," Journal of Finance, American Finance Association, vol. 71(1), pages 5-32, February.
    17. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    18. Moshirian, Fariborz & Ng, David & Wu, Eliza, 2009. "The value of stock analysts' recommendations: Evidence from emerging markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 74-83, March.
    19. Boni, Leslie & Womack, Kent L., 2006. "Analysts, Industries, and Price Momentum," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(1), pages 85-109, March.
    20. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    21. Ohad Kadan & Leonardo Madureira & Rong Wang & Tzachi Zach, 2009. "Conflicts of Interest and Stock Recommendations: The Effects of the Global Settlement and Related Regulations," Review of Financial Studies, Society for Financial Studies, vol. 22(10), pages 4189-4217, October.
    22. Sanjiv Sabherwal & Salil K. Sarkar & Ying Zhang, 2011. "Do Internet Stock Message Boards Influence Trading? Evidence from Heavily Discussed Stocks with No Fundamental News," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1209-1237, November.
    23. 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.
    24. Werner Antweiler & Murray Z. Frank, 2004. "Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards," Journal of Finance, American Finance Association, vol. 59(3), pages 1259-1294, June.
    25. Michaely, Roni & Womack, Kent L, 1999. "Conflict of Interest and the Credibility of Underwriter Analyst Recommendations," Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 653-686.
    26. Brad Barber & Reuven Lehavy & Maureen McNichols & Brett Trueman, 2001. "Can Investors Profit from the Prophets? Security Analyst Recommendations and Stock Returns," Journal of Finance, American Finance Association, vol. 56(2), pages 531-563, April.
    27. Michael Lachanski & Steven Pav, 2017. "Shy of the Character Limit: "Twitter Mood Predicts the Stock Market" Revisited," Econ Journal Watch, Econ Journal Watch, vol. 14(3), pages 302–345-3, September.
    28. Casey Dougal & Joseph Engelberg & Diego García & Christopher A. Parsons, 2012. "Journalists and the Stock Market," Review of Financial Studies, Society for Financial Studies, vol. 25(3), pages 639-679.
    29. Hailiang Chen & Prabuddha De & Yu (Jeffrey) Hu & Byoung-Hyoun Hwang, 2014. "Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media," Review of Financial Studies, Society for Financial Studies, vol. 27(5), pages 1367-1403.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Yang & Goodell, John W. & Wang, Yong & Abedin, Mohammad Zoynul, 2023. "Fintech, macroprudential policies and bank risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 87(C).
    2. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Shao, Xuefeng & Le, TN-Lan & Gyamfi, Matthew Ntow, 2023. "Financial technology stocks, green financial assets, and energy markets: A quantile causality and dependence analysis," Energy Economics, Elsevier, vol. 118(C).
    3. Le, Lan-TN & Yarovaya, Larisa & Nasir, Muhammad Ali, 2021. "Did COVID-19 change spillover patterns between Fintech and other asset classes?," Research in International Business and Finance, Elsevier, vol. 58(C).
    4. Le, TN-Lan & Abakah, Emmanuel Joel Aikins & Tiwari, Aviral Kumar, 2021. "Time and frequency domain connectedness and spill-over among fintech, green bonds and cryptocurrencies in the age of the fourth industrial revolution," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    5. Li, Jianping & Li, Jingyu & Zhu, Xiaoqian & Yao, Yinhong & Casu, Barbara, 2020. "Risk spillovers between FinTech and traditional financial institutions: Evidence from the U.S," International Review of Financial Analysis, Elsevier, vol. 71(C).
    6. Pacelli, Vincenzo & Miglietta, Federica & Foglia, Matteo, 2022. "The extreme risk connectedness of the new financial system: European evidence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    7. Christian Haddad & Lars Hornuf, 2021. "The Impact of Fintech Startups on Financial Institutions' Performance and Default Risk," CESifo Working Paper Series 9050, CESifo.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John S. Howe & Emre Unlu & Xuemin (Sterling) Yan, 2009. "The Predictive Content of Aggregate Analyst Recommendations," Journal of Accounting Research, Wiley Blackwell, vol. 47(3), pages 799-821, June.
    2. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    4. Thabang Mokoaleli-Mokoteli & Richard J. Taffler & Vineet Agarwal, 2009. "Behavioural Bias and Conflicts of Interest in Analyst Stock Recommendations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(3-4), pages 384-418.
    5. Cheolwoo Lee, 2013. "Analyst firm parent–subsidiary relationship and conflict of interest: evidence from IPO recommendations," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(3), pages 763-789, September.
    6. Thabang Mokoaleli‐Mokoteli & Richard J. Taffler & Vineet Agarwal, 2009. "Behavioural Bias and Conflicts of Interest in Analyst Stock Recommendations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 36(3‐4), pages 384-418, April.
    7. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
    8. Alan Crane & Kevin Crotty, 2020. "How Skilled Are Security Analysts?," Journal of Finance, American Finance Association, vol. 75(3), pages 1629-1675, June.
    9. Sy, Oumar & Zaman, Ashraf Al, 2020. "Is the presidential premium spurious?," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 94-104.
    10. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
    11. Aretz, Kevin & Bartram, Söhnke M. & Pope, Peter F., 2011. "Asymmetric loss functions and the rationality of expected stock returns," International Journal of Forecasting, Elsevier, vol. 27(2), pages 413-437.
    12. Hanousek, Jan & Kopřiva, František, 2013. "Do broker/analyst conflicts matter? Detecting evidence from internet trading platforms," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 86-92.
    13. Zhang, Yuzhao, 2014. "Contrarian flows, consumption and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 101-111.
    14. Maio, Paulo & Santa-Clara, Pedro, 2012. "Multifactor models and their consistency with the ICAPM," Journal of Financial Economics, Elsevier, vol. 106(3), pages 586-613.
    15. Qiang Kang & Qiao Liu & Rong Qi, 2010. "Predicting Stock Market Returns with Aggregate Discretionary Accruals," Journal of Accounting Research, Wiley Blackwell, vol. 48(4), pages 815-858, September.
    16. Ekaterini Panopoulou & Sotiria Plastira, 2014. "Fama French factors and US stock return predictability," Journal of Asset Management, Palgrave Macmillan, vol. 15(2), pages 110-128, April.
    17. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    18. Yu, Jialin, 2011. "Disagreement and return predictability of stock portfolios," Journal of Financial Economics, Elsevier, vol. 99(1), pages 162-183, January.
    19. Jiang, George J. & Yao, Tong & Yu, Tong, 2007. "Do mutual funds time the market? Evidence from portfolio holdings," Journal of Financial Economics, Elsevier, vol. 86(3), pages 724-758, December.
    20. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.

    More about this item

    Keywords

    stock recommendation; investment bank; crowdsourced financial analysis; sentiment; stock returns;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cvh:coecwp:2018/03. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adam Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/bkeeehu.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.