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ABSTRACT
We study reputational herding in financial markets in a laboratory experiment. In the spirit of Dasgupta and Prat [2008], career concerns are introduced in a sequential asset market where wages for investors are set by subjects in the role of employers. Employers can observe investment behavior, but not investors' ability types. Thereby, reputational incentives may arise endogenously. We find that a sizable fraction of investors follows an established trend even in a setting where there are no reputational incentives. In a setting where there are reputational concerns, they do not seem to create substantial herd behavior.
Acknowledgments
We would like to thank seminar participants at the University of Heidelberg and at the 2012 World Congress of the Game Theory Society in Istanbul. We are also grateful to a referee for helpful comments. This paper was part of Andrea Voskort's PhD thesis at the University of Heidelberg. It represents the analysis and views of the authors and should not be thought to represent those of the German Federal Financial Supervisory Authority (BaFin), Bonn.
Notes
1. In Avery and Zemsky [Citation1998], this is the case in a setup with two dimensions of uncertainty and two states of the world. Traders have private information not only about the assets' values, but also about whether some event occurs that changes the value of the asset substantially (“event uncertainty”). While in Avery and Zemsky [Citation1998] herding does not emerge if there is one-dimensional uncertainty with respect to the assets' values only, Park and Sabourian [Citation2011] show that, even in this case, there may be herding if there are more than two states of the world.
2. For other theoretical work on reputational incentives in a financial markets context, see, for example, Villatoro [Citation2009], Dasgupta and Prat [Citation2006], and Huddart [Citation1999].
3. Investors might, for example, have an intrinsic preference for conformity.
4. Herd behavior, in our setup, refers to the case in which investors follow the investment decisions of predecessors regardless of their own signal. In this case, investors' behavior thus does not carry informational value and asset prices do not converge to the true liquidation values.
5. While an experimental approach has its own issues, it has the advantage of being able to control for decision makers' private information and monetary incentives (which is, in general, difficult when working with real financial market data).
6. Of course, as mentioned above, experimental studies might have their own issues such as the external validity of the findings. Hence, both approaches complement each other.
7. Beginning with Anderson and Holt [Citation1997], there is a vast experimental literature on such “information cascades” in settings with fixed prices. These studies, however, do not directly apply to financial markets where prices are flexible. For an overview, see, for example, Weizsacker [Citation2010] or Drehmann, Oechssler and Roider [2007].
8. Note that sufficient complexity of the environment seems to be necessary for information-based herding to emerge: Drehmann, Oechssler and Roider [2005] and Cipriani and Guarino [Citation2005] confirm Avery and Zemsky's [Citation1998] prediction of no herding in a simple financial market with one-dimensional uncertainty over two potential states of the world.
9. See also the experiment by Irlenbusch and Sliwka [Citation2006] where, however, not only career concerns, but also gift-exchange considerations might have affected subjects' behavior.
10. The reasons for considering sequences of three investors are discussed in detail in the section Experimental Design.
11. Dasgupta and Prat [Citation2008] consider the choice between buying or (short) selling a single asset. In line with other experiments on herding in financial markets (see, e.g., Drehmann, Oechssler and Roider [2005], Cipriani and Guarino [Citation2005]) we consider the strategically equivalent choice between buying either A or B, which seems to be easier to explain to experimental subjects.
12. In their model, Dasgupta and Prat [Citation2008] assume that a certain fraction of the investors are noise traders whose trading is purely random. For two reasons, we do not include such noise traders. First, this simplification does not affect the theoretical predictions; and, second, it makes it easier to explain the experimental setting to subjects. Note that despite of this simplification, market breakdown is not an issue as, in the experiment, subjects have to buy one of the two assets. The issue of uninformed traders is discussed in more detail in the Conclusion.
13. Note that, in the experiment, investors learn the state and their payoffs only at the very end of the experiment after all decisions have been made.
14. In the presence of reputational concerns (see the section Investors with Reputational Concerns) this will be a useful feature because, from a theoretical perspective, “extreme” prices facilitate reputational herding.
15. In case of a tie, each of the highest bidding principals wins with equal probability.
16. To see this, note that in any equilibrium the following has to hold: (a) all bids must be weakly below 20 · γ (because otherwise the winning bid would lead to a loss), (b) the maximum bid must be equal to 20 · γ (because otherwise a losing bidder would have an incentive to overbid), and (c) at least two bids must be equal to 20 · γ (because otherwise the winning bidder would have an incentive to lower his or her bid). Hence, in any equilibrium of the first-price auction at least two principals bid 20 · γ while the remaining principals bid weakly less than that.
17. Note that in Dasgupta and Prat [Citation2008], the weight of reputational concerns in an investor's payoff function is determined by the parameter (1 - β), where β constitutes the payoff fraction from investing in the asset. By fixing the value of the good investor to 20 and the successful asset's payoff to 10, (1 - β) equals 2/3 in our setup.
18. For a more detailed sketch of Dasgupta and Prat's [Citation2008] argument, see Appendix A.
19. Recall that the role of market maker is played by the experimenter, and hence potential losses are not an issue.
20. As argued above, for a given investor, principals' equilibrium wage bids only depend on (i) investors' equilibrium strategies and (ii) the realized true state of the world. In Appendix A, we show that, given equilibrium wage bidding strategies of principals, equilibrium investment strategies of investors are the same independent of whether one sets market prices according to or whether market prices take potential herd behavior by Investor 3 into account.
21. That is, in this equilibrium information is revealed in the fastest possible way in the sense that there is no other (reasonable) equilibrium where, at any date t, more information is revealed.
22. Subjects were allowed to keep a copy of their first-round decision sheet as a reference for the second round. Importantly, we made it clear to subjects that second-round decision making did not require recalling first-round decisions.
23. Drehmann, Oechssler and Roider [2005] conduct an experiment on information-based herding in financial markets and document behavior that is quite robust across pricing rules that make different assumptions on the behavior of investors (e.g., pricing rules that allow for different forms of “mistakes”).
24. The maximum possible bid for an investor was limited to 20 points.
25. That is, in all of the sessions there were six investor groups in treatment investment and four investor groups in treatment reputation.
26. In both rounds, by experimental design, investors can never lose more money than the initial endowment of 20 points. If, in treatment reputation, a principal wins many auctions and happens to hire a number of investors of bad type, he or she may, in principle, accumulate losses that exceed the initial endowment of 20 points. We excluded this possibility by informing principals that the minimum they could earn were zero points (including the initial endowment). While, in principle, this constraint might have given principals an incentive to overbid relative to what is predicted by Proposition 2, we do not find evidence for this. In fact, looking at all principals, there is even evidence for some underbidding as the average actual wage bid is equal to 6.28 while Proposition 2 would predict an average wage bid of 8.25.
27. For each pair of such symmetric information sets (and for both treatments separately), we conduct McNemar change tests, which all indicate insignificant differences.
28. According to a Wilcoxon signed ranks test (where for each subject, we compare the number of decisions that are in line with theory in treatment investment respectively in treatment reputation), this difference is (marginally) significant with a p-value of 0.056. This might be indicative of some learning effects across rounds.
29. In particular, for both treatments separately, we run pair-wise McNemar change tests comparing behavior at information set AAb (BBa) to behavior at each of the other information sets except BBa (AAb), which all indicate statistical significance at the 1% level.
30. This remains true if McNemar change tests are separately applied to behavior at information sets AAb respectively BBa.
31. The model (on which the theoretical predictions in Propositions 1 and 2 are based) assumes risk-neutrality of investors and principals. In Question 1 of the (nonincentivized) postexperimental questionnaire, we elicited subjects' degree of risk-aversion. The question that we use has been widely employed in survey studies, and it has been validated in laboratory experiments with substantial stakes (see, e.g., Dohmen et al. [Citation2011]). In unreported regressions, we find no significant effect of an investor's degree of risk-aversion on his tendency to follow his signal. This holds both in treatment investment and in treatment reputation. It also holds when we only consider decisions at information sets XXx or XXy.
32. In the postexperimental questionnaire, we asked subjects whether they believe that investors always decide as suggested by their signals. While 77.77% of subjects thought that Investor 1 behaves this way, 45.55% thought that Investor 2 behaves this way and only 11.11% thought that Investor 3 always follows his signal.
33. For a similar approach to capture the influence of predecessors' behavior, see, for example, Drehmann, Oechssler and Roider [2005].
34. On the one hand, this finding is intuitive because the behavior of Investor 2 itself is influenced by the behavior of Investor 1 (see and the discussion above). On the other hand, it might be a special feature of the experimental design that there is a well-defined Investor 1 who has access to objective information only (i.e., his or her signal), but who is not affected by decisions of earlier investors (as there are none). Nevertheless, the above finding seems to indicate that early investors (who had less chance to be affected by other investors' behavior) might exert an especially large influence on financial market trends.
35. From a behavioral perspective, it might be possible to explain the behavior of Investor 3 in treatment investment. There is ample evidence that decision makers display asymmetric reactions to good news and bad news in the sense that bad news tends to be ignored (for a recent contribution, see, e.g., Eil and Rao [Citation2011]). It might be that Investor 3 interprets XXx (XXy) as good news (bad news) because his own signal confirms (goes against) the preexisting trend. If this is the case, this might help to explain Investor 3′s tendency to disregard his signal at information set XXy. At information sets XYy and XYx, it is less obvious whether Investor 3′s signal is good news or bad news, and indeed the tendency to follow one's own signal does not differ much. Alternatively, it might be that some investors simply have a preference for conformity, which leads them to imitate earlier investors.
36. In case of rall (rmax), we compare average wage offers for successful respectively unsuccessful investors at the principal level (at the session level).
37. Only in case of an unsuccessful investment, the difference between wage bids rall given a history XXX and wage bids rall given any other history is marginally statistically significant with p = 0.069 (Wilcoxon signed ranks test that compares average wage bids at the principal level).
38. Note that the history of trades XXY is off the equilibrium path. In order to calculate the respective payoff difference, we assume that in this case principals hold the off-equilibrium belief that Investor 3 has traded sincerely (which is in line with the assumption made in Dasgupta and Prat [Citation2008]).
39. In particular, this also holds for bad types because investors were assumed to be unaware of their type.