Do individual investors’ stock recommendations in online communities contain investment value?


This paper investigates the investment value of individual investors’ stock recommendations within online communities. We find that aggregated recommendations contain no explicit investment value and that following these recommendations may have a negative impact on investment performance. Our results suggest that recommendations are mostly based on simple heuristics and concentrate on a small number of stocks. When restricting the set of recommendations to those made by the most experienced or successful recommenders, results marginally improve but still preclude profitable investment strategies. Experienced and successful recommenders seem more likely to avoid the most expensive pitfalls rather than actually exhibit superior investment performance.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11


  1. 1.

    Genetic algorithms find an optimized set of parameters for a particular problem by mimicking evolutionary processes. Preliminary solutions are combined and mutated in order to find superior solutions.

  2. 2.

    Recent studies have had to classify data into buy, hold, and sell recommendations.

  3. 3.

    For example, buying and selling stocks with recent outperformance (see also, Barber et al. 2009); concentrating on very few stocks, particularly those that are currently receiving much attention (see also, Barber and Odean 2008).

  4. 4.

  5. 5.

    That is, from the closing price of the day before to the closing price of the recommendation date.

  6. 6.

    Approximated with the JP Morgan US Cash 3M or JP Morgan EURO Cash 3M index with respect to the major currency of the relevant market.

  7. 7.

    Market capitalization, common equity, and deferred taxes data for the years 2005 to 2010 are taken from Datastream.

  8. 8.

    Not tabularized.

  9. 9.

    Referred to estimated round-trip transaction costs of \(1.3~\%\) for institutions (Barber et al. 2001) and commissions per trade of around \(1.5~\%\) for individual investors (Barber and Odean 2000). Other approaches considering flat fees and applicable duties (Siganos 2009) result in similar ranges for reasonable trades of individual investors.

  10. 10.

    Abnormal returns are significant after the recommendation date for all days in FF3M and C4M and also in CAPM with exception of the first 2 days.

  11. 11.

    Results for CAPM and FF3M are consistent.

  12. 12.

    We exclude the first recommendation, as we suppose it to be a technical trial for a number of users.

  13. 13.

    Reducing the timespan after the recommendation date to 10 days and analyzing the performance of buy and sell recommendations separately yielded very similar abnormal returns.

  14. 14.

    Less than 150 related recommendations.


  1. Altinkilic, O., Hansen, R.S.: On the information role of stock recommendation revisions. J. Account. Econ. 48(1), 17–36 (2009). doi:10.1016/j.jacceco.2009.04.005

    Google Scholar 

  2. Antweiler, W., Frank, M.Z.: Is all that talk just noise? The information content of internet stock message boards. J. Finance 59(3), 1259–1294 (2004). doi:10.1111/j.1540-6261.2004.00662.x

  3. Bailey, W., Kumar, A., Ng, D.: Behavioral biases of mutual fund investors. J. Financ. Econ. 102(1), 1–27 (2010)

    Article  Google Scholar 

  4. Bank, M., Larch, M., Peter, G.: Google search volume and its influence on liquidity and returns of german stocks. Financ. Mark. Portf. Manag. 25(3), 239–264 (2011). doi:10.1007/s11408-011-0165-y

  5. Barber, B.M., Odean, T.: Trading is hazardous to your wealth: The common stock investment performance of individual investors. J. Finance 55(2), 773–806 (2000). doi:10.1111/0022-1082.00226

    Google Scholar 

  6. Barber, B.M., Odean, T.: All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors. Rev. Financ. Stud. 21(2), 785–818 (2008). doi:10.1093/rfs/hhm079

  7. Barber, B.M., Odean, T.: The behavior of individual investors (2011).

  8. Barber, B.M., Lehavy, R., McNichols, M., Trueman, B.: Can investors profit from the prophets? Security analyst recommendations and stock returns. J. Finance 56(2), 531–563 (2001). doi:10.1111/0022-1082.00336

    Google Scholar 

  9. Barber, B.M., Odean, T., Zhu, N.: Systematic noise. J. Financ. Mark. 12(4), 547–569 (2009)

  10. Bjerring, J.H., Lakonishok, J., Vermaelen, T.: Stock prices and financial analysts’ recommendations. J. Finance 38(1), 187 (1983). doi:10.2307/2327646

    Google Scholar 

  11. Bollen, J., Mao, H., Zeng, X.: Twitter mood predicts the stock market. J. Comput. Sci. 2(1), 1–8 (2011). doi:10.1016/j.jocs.2010.12.007

    Google Scholar 

  12. Brennan, M.J., Jegadeesh. N., Swaminathan, B.: Investment analysis and the adjustment of stock prices to common information. Rev. Financ. Stud. 6(4), 799–824 (1993).

  13. Carhart, M.M.: On persistence in mutual fund performance. J Finance 52(1):57–82 (1997). doi:10.2307/2329556.

    Google Scholar 

  14. Chan, W.S.: Stock price reaction to news and no-news: drift and reversal after headlines. J. Financ. Econ. 70(2), 223–260 (2003). doi:10.1016/S0304-405X(03)00146-6

  15. Chevalier, J., Ellison, G.: Are some mutual fund managers better than others? Cross-sectional patterns in behavior and performance. J. Finance 54(3), 875–899 (1999). doi:10.1111/0022-1082.00130/ab

    Google Scholar 

  16. Chuang, W., Lee, B.: The informational role of institutional investors and financial analysts in the market. J. Financ. Mark. 14(3), 465–493 (2011).

  17. Cowles, A.: Can stock market forecasters forecast? Econometrica 1(3), 309–324 (1933).

  18. Dewally, M.: Internet investment advice: investing with a rock of salt. Financ. Anal. J. 59(4), 65–77 (2003).

  19. Dhar, R., Zhu, N.: Up close and personal: Investor sophistication and the disposition effect. Manag. Sci. 52(5), 726–740 (2006). doi:10.1287/mnsc.1040.0473

  20. Diefenbach, R.: How good is institutional brokerage research? Financ. Anal. J. 28(1), 54–60 (1972).

  21. Engelberg, J., Parsons, C.: The causal impact of media in financial markets. J. Finance 66(1), 67–97 (2011). doi:10.1111/j.1540-6261.2010.01626.x

    Google Scholar 

  22. Fama, E.F.: Efficient capital markets: a review of theory and empirical work. J. Finance 25(2), 383–417 (1970).

    Google Scholar 

  23. Fama, E.F., French, K.R.: The cross-section of expected stock returns. J. Finance 47(2), 427–465 (1992), doi:10.2307/2329112.

    Google Scholar 

  24. Fama, E.F., French, K.R.: Common risk factors in the returns on stocks and bonds. J. Financ. Econ. 33(1), 3–56 (1993). doi:10.1016/0304-405X(93)90023-5

    Google Scholar 

  25. Feng, L., Seasholes, M.S.: Do investor sophistication and trading experience eliminate behavioral biases in financial markets? Rev. Finance 9(3), 305–351 (2005). doi:10.1007/s10679-005-2262-0

    Google Scholar 

  26. Griffin, J.M.: Are the fama and french factors global or country specific? Rev. Financ. Stud. 15(3), 783–803 (2002). doi:10.1093/rfs/15.3.783

  27. Griffin, J.M., Hirschey, N.H., Kelly, P.J.: How important is the financial media in global markets? Rev. Financ. Stud. 24(12), 3941–3992 (2011). doi:10.1093/rfs/hhr099

    Google Scholar 

  28. Grinblatt, M., Keloharju, M.: The investment behavior and performance of various investor types: a study of Finland’s unique data set. J. Financ. Econ. 55, 43–67 (2000).

  29. Grinblatt, M., Keloharju, M.: What makes investors trade? J. Finance 56(2), 589–616 (2001),

    Google Scholar 

  30. Hill, S., Ready-Campbell, N.: Expert stock picker: The wisdom of (experts in) crowds. Int. J. Electron. Commer. 15(3), 73–102 (2011).

    Google Scholar 

  31. Hirshleifer, D.A., Myers, J.N., Myers, L.A.: Do individual investors cause post-earnings announcement drift? Direct evidence from personal trades. Account Rev. 83(6), 1521–1550 (2008). doi:10.2308/accr.2008.83.6.152I

    Article  Google Scholar 

  32. Hobbs, J., Kovacs, T., Sharma, V.: The investment value of the frequency of analyst recommendation changes for the ordinary investor. J Empir Finance 19(1):94–108 (2012). doi:10.1016/j.jempfin.2011.09.006

  33. Jegadeesh, N., Kim, J., Krische, S.D., Lee, C.M.C.: Analyzing the analysts: When do recommendations add value? J. Finance 59(3), 1083–1124 (2004). doi:10.1111/j.1540-6261.2004.00657.x.

    Google Scholar 

  34. Kahneman, D., Tversky, A.: Subjective probability: a judgment of representativeness. Cogn. Psychol. 3(3), 430–454 (1972). doi:10.1016/0010-0285(72)90016-3

  35. Kaniel, R., Saar, G., Titman, S.: Individual investor trading and stock returns. J. Finance 63(1), 273–310 (2008)

    Article  Google Scholar 

  36. Lampel, J., Bhalla, A.: The role of status seeking in online communities: Giving the gift of experience. J. Comput. Mediat. Commun. 12(2), 434–455 (2007). doi:10.1111/j.1083-6101.2007.00332.x

    Google Scholar 

  37. Lintner, J.: The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Rev. Econ. Stat. 47(1), 13 (1965). doi:10.2307/1924119.

    Google Scholar 

  38. List, J.: Does market experience eliminate market anomalies? Q. J. Econ. 118(1), 41–71 (2003).

    Google Scholar 

  39. Nicolosi, G., Peng, L., Zhu, N.: Do individual investors learn from their trading experience? J. Financ. Mark. 12(2), 317–336 (2009).

    Google Scholar 

  40. Odean, T.: Are investors reluctant to realize their losses? J. Finance 53(5), 1775–1798 (1998).

    Google Scholar 

  41. Seasholes, M.S., Wu, G.: Predictable behavior, profits, and attention. J. Empir Finance 14(5), 590–610 (2007). doi:10.1016/j.jempfin.2007.03.002

    Google Scholar 

  42. Sharpe, W.F.: Capital asset prices: a theory of market equilibrium under conditions of risk. J. Finance 19(3), 425–442 (1964). doi:10.2307/2329297.

  43. Shefrin, H., Statman, M.: The disposition to sell winners too early and ride losers too long: theory and evidence. J. Finance 40(3), 777 (1985). doi:10.2307/2327802.

  44. Siganos, A.: Can small investors exploit the momentum effect? Financ. Mark. Portf. Manag. 24(2), 171–192 (2009). doi:10.1007/s11408-009-0120-3.

  45. Stickel, S.E.: The anatomy of the performance of buy and sell recommendations. Financ. Anal. J. 51(5), 25–39 (1995). doi:10.2469/faj.v51.n5.1933.

  46. Strahilevitz, M., Odean, T., Barber, B.M.: Once burned, twice shy: How naïve learning, counterfactuals, and regret affect the repurchase of stocks previously sold. J. Mark. Res. 48(Special Issue),102–120 (2011)

    Google Scholar 

  47. Tumarkin, R., Whitelaw, R.F.: News or noise? Internet postings and stock prices. Financ. Anal. J. 57(3), 41–51 (2001)

    Article  Google Scholar 

  48. Womack, K.L.: Do brokerage analysts’ recommendations have investment value? J Finance 51(1), 137–167 (1996). doi:10.2307/2329305.

    Google Scholar 

Download references


We are grateful to an anonymous referee for valuable comments on our drafts and to Markus Schmid, the editor. We thank Cetin-Behzet Cengiz, Christian Wegener, Sarah Schiffer, and Philipp von Thunen for their comments on earlier versions of this manuscript.

Author information



Corresponding author

Correspondence to Philipp Stephan.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Stephan, P., von Nitzsch, R. Do individual investors’ stock recommendations in online communities contain investment value?. Financ Mark Portf Manag 27, 149–186 (2013).

Download citation


  • Individual investors
  • Online communities
  • Stock recommendations
  • Investment value
  • Event study
  • Abnormal returns

JEL Classification

  • D12
  • G11
  • G14