Is Herd Behavior Rational or Irrational?

Introduction

There is evidence in both zoology and psychology that in many species of animals, (man among them) exhibit tendencies of imitating the actions of fellow animals (Gibson and Hoglund, 1992). It has been observed by psychologists that people show a predisposition to get influenced by others, in almost all respects which of course is inclusive of investment activities. This idea of people copying the actions of others whether rationally or irrationally is exhibited in the field of finance where such a behavior is referred to as herding. In the wake of the global financial crises, the term herding has become a derogatory field of study.

For instance, when a great business personality purchases stocks in a given company, many investors are seen to echo this action by subsequently purchasing the same stocks not having analyzed such securities but really as a result of the influence of such a personality.

The concept of herding

In the context of financial markets, herds’ behavior can be defined as a mutual limitation leading to a convergence of action (Hirshleifer and Teoh, 2003). Herd behavior is the tendency exhibited by people when they try to copy the actions of a larger group irrespective of whether the actions are rational or irrational. The terms, herding and dispersing are in some contexts used interchangeably where they are taken to include any behavior similarity or otherwise that results from individuals interacting.

The herd phenomenon may happen due to the social pressure of compliance. Naturally, people are seen to have a desire to be aligned or associated with a given group that these people may tend to achieve this by mimicking the actions of others. People in this type of behavior are seen to obey the adage that says when you go to Rome, do as Romans do.

According to Hirshleifer, and Teoh (2003), the reasons why individuals get involved in the process of herding are as follows:

One reason concerns pay off externalities- These are market complementarities where for instance it is more efficient to use e-mail to communicate when everybody else does so. Herding may also result from preference interactions; where one may feel obliged to indulge in some activities just because everybody else is doing so. Another reason is that of observational influence. This is where one observes the actions of the others and their consequences and acts accordingly.

Sushill and Sunil (2001) suggest that, another reason to indulge in herding by investors is that the investors whose actions are copied may know a thing about the return on the investment and consequently, their actions may reveal such information. They further say that, when it comes to managers who invest on behalf of other stakeholders, the compensation system may be such that it encourages or rewards imitation. And lastly they talk of, imitation resulting from the individual’s need for conformity.

Herding-Rationality and Irrationality

Devenow and Welch (1996) suggest that irrational form of herding takes place when the investors tend to ignore some of their beliefs and blindly imitate the actions of others. Conversely, rational herding is the phenomenon of investors imitating one another while they take advantage of each other, as they believe other investors could be better informed than themselves or rather because there is a level of uncertainty at the information accessible to them.

It is therefore not usually irrational for investors to “herd”. Managers for instance are people whose effectiveness is established through their firm’s general performance over time. Incase there are huge variations in the general performance of these firms, keeping other factors constant, the poor performing managers could lose their jobs. Therefore, to mitigate the chances of such variations in their general performance, they tend to adopt similar investment criteria.

This is because, of the fact that, if they herd together despite the fact that the outcome may be unfavorable, they will be able to make a case for themselves that they were generally unfortunate. Besides, looking at the pressure to maximize the profits and to preserve the reputation, it can be seen that it would just be appropriate for these managers to wait for the leader(s) to make investment decisions rather than make their own decisions given the consequences of a bad decision.

Herding models

Some models tend to explain herding in the financial markets. These are as follows:

Information based herding and cascades. This model is based on the premise that agents obtain useful information by the virtue of observance of the actions of the previous agents. In such situations or circumstances, the agents are said to be in an informational cascade. A person is said to be in an information cascade on the condition that, based upon his examination of others, his chosen course of action does not depend on their private information signal (Banerjee, 1992). In a situation as such, the choice of action is uninformative. It can thus be said that, cascades are linked to the informational blockages in that; a person may do an action to his benefit, only for other different individuals’ to benefit from it as well.

When the agents realize that they are in a cascade, they also realize that the cascade is based on little or presumably no information. Thus, any new influx of new information or rather, better informed agents, results in the dismantlement of the cascade. In an information cascade, every person may be deemed to be acting rationally. Yet, even if all the involved parties may be having a lot of information collectively, they may be inclined to take the wrong courses individually.

Some little bit of information availed to the public can have the effect of demolishing a cascade. Fragility is therefore an important aspect of the cascade.

Information acquisition herding is another model that was proposed by, Froot, Scharfstein and Stein (1992). The theme of this model is that, investors decide to follow similar sources of information. In this model, the focus is set on the short term prospect of the investors which results to informational spillovers. According to this model, a well-versed investor who wishes to liquidate his shareholdings stands to gain if other investors acting on the same information trade on the same asset. This therefore leads to investors following the information sources that are likely to be followed by other investors. In such a case, rationality accompanies the decision.

A similar model was derived by Hirshleifer, Subrahmanyam and Titman (1994) which considers early as well as late informed investors. It postulates that the early informed investors trade aggressively in the beginning and later reverse their position in the next period to reduce the long-term risk whilst the late informed investors make the price to show the information from the early informed investors. The greater the profits made by the early informed investors, the greater will be the numbers of the late informed investors are likely to trade. Therefore, in the instances where the investors are not aware of whether which category they fall (early or late) informed, their ex ante utility rises in the sum of the investors taking or collecting information.

Principal-agent model of herding is third. This approach was formulated by Scharfstein and Steve (1990). These set of models lie on a platform that when the principals are not certain of their agents’ capability as regards picking of the right stocks, it can be deemed rationale for these agents to copy the decisions of other agents to preserve the principal’s uncertainty about the agent’s capability.

The fourth perspective focuses on the institutional investors. Here, institutional investors may share a preference towards stocks with some specific features such as liquidity or riskiness (Falkenstein, 1996). The result of this convergence in preference towards securities with a given feature, they may seem to follow each other from and out of a given set of stocks.

Lastly, a given set of investors may exhibit herding as a result of fads (Friedman, 1984) or where optimistic feedback traders invest at a style level and thus seek relative style returns. Such a practice aims high relative return stocks and shifts the prices further from the basics (Barberis and Shleifer 2003).

Conclusion

It is usually difficult to ascertain a firm’s herding tendencies. The fact that a group of individual or corporate investors make the same decisions for example, is not sufficient prove of herding because they could be adjusting their asset portfolios to respond to the same price movement. Herding can however be established by looking at the overall behavior of investors.

It cannot possibly be established with certainty that herding is either purely rational or irrational. However, herding may take both positions depending on the manner of approach adopted by the investor. In most cases though, herding is associated with rationality based on the argument that the other investors may have carried out analysis that revealed the superior benefits of such a move

References

Banerjee, A 1992, ‘A Simple Model of Herd Behavior’, Quarterly Journal of Economics 107:3, 797-818.

Barberis, N. & Shleifer, A 2003, ‘Style Investing’, Forthcoming Journal of Financial Economics.

Devenow, A. and Welch, I 1996, ‘Rational herding in financial economics’, European Economic Review, 40, 603-615.

Falkenstein, E.G., 1996, ‘Preferences for Stock Characteristics as Revealed by Mutual Fund Portfolio Holdings’, Journal of Finance, 51, 111-135.

Froot, K., Scharfstein, D and Stein, J, 1992, ‘Herd on the street: Informational inefficiencies in a market with short term speculation’, Journal of Finance, Vol. 47, pp1461-1486.

Gibson, R and Hoglund, J., 1992, ‘Copying and sexual selection’, Trends in Research in evolution and ecology, Vol.7, pp.229-232.

Hirshleifer S & Teoh, H 2003, ‘Herd behavior and cascading in capital markets’, European Financial Management, pp. 25 – 66.

Hirshleifer, D., Subrahmanyam, A and Titman, S 1994, ‘Security analysis and trading patterns when some investors receive information before others’, Journal of Finance, Vol.49, pp. 1665-1698.

Scharfstein, David and Jeremy Stein, 1990, “Herd Behavior and Investment,” American Economic Review, 80, 465-479.

Sushil, B & Sunil, S 2001, ‘Herd Behavior in Financial Markets’, IMF Staff Papers, Palgrave Macmillan Journals, vol. 47(3), pp 17-35.