Financial Markets and Portfolio Management

, Volume 28, Issue 3, pp 233–262 | Cite as

Reciprocal social influence on investment decisions: behavioral evidence from a group of mutual fund managers

  • Frederik KönigEmail author


In this paper, I analyze reciprocal social influence on investment decisions in an international group of roughly 2,000 mutual fund managers who invested in companies in the DAX30. Using a robust estimation procedure, I provide empirical evidence that the average fund manager puts 0.69 % more portfolio weight on a particular stock if his or her peers, on average, assign a weight to the corresponding position that is 1 % higher compared to other stocks in the portfolio. The dynamics of this influence on choice of portfolio weights suggest that fund managers adjust their behavior based on the prevailing market situation and are more strongly influenced by others in times of an economic downturn. Analyzing the working locations of the fund managers, I conclude that more than 90 % of the magnitude of influence stems from social learning. Although this form of influence varies a great deal over time, the magnitude of influence resulting from the exchange of opinions is more or less constant.


Mutual fund managers Social interaction Herding  Word-of-mouth 

JEL Classification

A14 D83 G11 G23 



I thank Horst Entorf, Uwe Walz, Jan Krahnen, Alfons Weichenrieder, Markus M. Schmid (the editor), and an anonymous referee for valuable comments and suggestions.


  1. Arnswald, T.: Investment behaviour of german equity fund managers: an exploratory analysis of survey data. Deutsche Bundesbank Discussion Paper 08/01 (2001)Google Scholar
  2. Avery, C., Zemsky, P.: Multidimensional uncertainty and herd behavior in financial markets. Am. Econ. Rev. 88(4), 724–748 (1998)Google Scholar
  3. Bala, V., Goyal, S.: Learning from neighbours. Rev. Econ. Stud. 65, 595–621 (1998)CrossRefGoogle Scholar
  4. Banerjee, A.V.: A simple model of herd behavior. Q. J. Econ. 107(3), 797–817 (1992)CrossRefGoogle Scholar
  5. Bikhchandani, S., Hirshleifer, D., Welch, I.: A theory of fads, fashion, custom, and cultural change as informational cascades. J. Polit. Econ. 100(5), 992–1026 (1992)CrossRefGoogle Scholar
  6. Bikhchandani, S., Hirshleifer, D., Welch, I.: Learning from the behavior of others: conformity, fads, and informational cascades. J. Econ. Perspect. 12(3), 151–170 (1998)CrossRefGoogle Scholar
  7. Bikhchandani, S., Sharma, S.: Herd behavior in financial markets: a review. IMF Staff Papers 47(3), 279–310 (2000)Google Scholar
  8. Blume, L.E., Brock, W.A., Durlauf, S.N., Ioannides, Y.M.: Identification of social interactions. In: Benhabib, J., Bisin, A., Jackson, M. (eds.) Handbook of Social Economics. Elsevier, San Diego (2010)Google Scholar
  9. Bramoullé, Y., Djebbari, H., Fortin, B.: Identification of peer effects through social networks. J. Econom. 150, 41–55 (2009)CrossRefGoogle Scholar
  10. Brock, W.A., Durlauf, S.N.: The econometrics of interactions-based models. In: Heckman, J., Leamer, E. (eds.) Handbook of Econometrics. North-Holland, Amsterdam (2001)Google Scholar
  11. Coval, J.D., Moskowitz, T.J.: Home bias at home: local equity preference in domestic portfolios. J. Fin. 54, 2045–2073 (1999)CrossRefGoogle Scholar
  12. Dasgupta, A., Prat, A.: Information aggregation in financial markets with career concerns. J. Econ. Theory 143, 83–113 (2008)CrossRefGoogle Scholar
  13. Ellison, G., Fudenberg, D.: Rules of thumb for social learning. J. Polit. Econ. 101(4), 612–643 (1993)CrossRefGoogle Scholar
  14. Ellison, G., Fudenberg, D.: Word-of-mouth communication and social learning. Q. J. Econ. 110(1), 93–125 (1995)CrossRefGoogle Scholar
  15. Elton, E.J., Gruber, M.J., Blake, C.R., Krasny, Y., Ozelge, S.: The effect of the frequency of holdings data on conclusions about mutual fund management behavior. J. Bank. Fin. 34(5), 912–922 (2010)CrossRefGoogle Scholar
  16. Eren, N., Ozsoylev, H.N.: Communication dilemma in speculative markets. Working Paper, University of Oxford (2006)Google Scholar
  17. Franck, A., Walter, A., Witt, J.F.: Momentum strategies of german mutual funds. Financ. Mark. Portf. Manag. 27(3), 307–332 (2013)CrossRefGoogle Scholar
  18. Frey, S., Herbst, P., Walter, A.: Measuring mutual fund herding—a structural approach. Working Paper, Goethe-University Frankfurt (2006)Google Scholar
  19. Gray, W.R.: Private information exchange in the asset management industry. Working Paper, University of Chicago (2010)Google Scholar
  20. Hirshleifer, D., Teoh, S.H.: Herd behaviour and cascading in capital markets: a review and synthesis. Eur. Financ. Manag. 9(1), 25–66 (2003)CrossRefGoogle Scholar
  21. Hirshleifer, D., Teoh, S.H.: Thought and behavior contagion in capital markets. In: Hens, T., Schenk-Hoppé, K.R. (eds.) Handbook of Financial Markets: Dynamics and Evolution. Elsevier, San Diego (2008)Google Scholar
  22. Hong, H., Kubik, J.D., Stein, J.C.: Thy neighbor’s portfolio: word-of-mouth effects in the holdings and trades of money managers. J. Fin. 60, 2801–2824 (2005)CrossRefGoogle Scholar
  23. Honoré, B.E., Leth-Petersen, S.: Estimation of panel data models with two-sided censoring. Working Paper, Princeton University and University of Copenhagen (2007)Google Scholar
  24. Kelejian, H.H., Prucha, I.R.: A generalized spatial two stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. J. Real Estate Fin. Econ. 17, 99–121 (1998)CrossRefGoogle Scholar
  25. Kraft, H., Korn, R.: Continuous-time delegated portfolio management with homogeneous expectations: can an agency conflict be avoided? Financ. Mark. Portf. Manag. 22(1), 67–90 (2008)CrossRefGoogle Scholar
  26. Lakonishok, J., Shleifer, A., Vishny, R.W.: The impact of institutional trading on stock prices. J. Financ. Econ. 31, 23–43 (1992)CrossRefGoogle Scholar
  27. Lee, L.-F.: Consistency and efficiency of least squares estimation for mixed regressive, spatial autoregressive models. Econom. Theory 18, 252–277 (2002)CrossRefGoogle Scholar
  28. Lee, L.-F.: Best spatial two-stage least squares estimators for a spatial autoregressive model with autoregressive disturbances. Econom. Rev. 22(4), 307–335 (2003)CrossRefGoogle Scholar
  29. Lee, L.-F., Liu, X., Lin, X.: Specification and estimation of social interaction models with network structures. Econom. J. 13(2), 145–176 (2010)CrossRefGoogle Scholar
  30. Manski, C.: Identification of endogenous social interactions: the reflection problem. Rev. Econ. Stud. 60(3), 531–542 (1993)CrossRefGoogle Scholar
  31. Maug, E., Naik, N.: Herding and delegated portfolio management: the impact of relative performance evaluation on asset allocation. Working Paper, London Business School (1996)Google Scholar
  32. Moffitt, R.A.: Policy interventions low-level equilibria and social interactions. In: Durlauf, S., Young, P. (eds.) Social Dynamics. MIT Press, Cambridge (2001)Google Scholar
  33. Oehler, A., Wendt, S.: Herding behaviour of mutual fund managers in germany. Working Paper, University of Bamberg (2009)Google Scholar
  34. Pareek, A.: Information networks: Implications for mutual fund trading behavior and stock returns. Working Paper, Rutgers University (2011)Google Scholar
  35. Pomorski, L.: Follow the leader: peer effects in mutual fund portfolio decisions. Working Paper, University of Toronto (2009)Google Scholar
  36. Scharfstein, D.S., Stein, J.C.: Herd behavior and investment. Am. Econ. Rev. 80(3), 465–479 (1990)Google Scholar
  37. Shiller, R.J.: Irrational Exuberance. Broadway Books, New York (2000)Google Scholar
  38. Shiller, R.J., Pound, J.: Survey evidence on diffusion of interest and information among investors. J. Econ. Behav. Org. 12, 47–66 (1989)CrossRefGoogle Scholar
  39. Stein, J.C.: Conversations among competitors. Am. Econ. Rev. 98(5), 2150–2162 (2008)CrossRefGoogle Scholar
  40. Walter, A., Weber, F.M.: Herding in the german mutual fund industry. Eur. Financ. Manag. 12(3), 375–406 (2006)CrossRefGoogle Scholar
  41. Welch, I.: Sequential sales, learning, and cascades. J. Fin. 47(2), 695–732 (1992)CrossRefGoogle Scholar
  42. Wermers, R.: Mutual fund herding and the impact on stock prices. J. Fin. 54(2), 581–622 (1999)CrossRefGoogle Scholar
  43. Zwiebel, J.: Corporate conservatism and relative compensation. J. Polit. Econ. 103(1), 1–25 (1995)CrossRefGoogle Scholar

Copyright information

© Swiss Society for Financial Market Research 2014

Authors and Affiliations

  1. 1.Faculty of Business Administration and EconomicsGoethe-UniversityFrankfurt/MainGermany

Personalised recommendations