Herding: An Introduction
While psychologist call it as Herd behavior, the financial pundits go with the word ‘’ Herding’’. Herding is a behavior trait found in an individual where his investment decisions are decided by the majority. In other words, it refers to instances when the individuals gravitate towards same or similar investment based solely on the fact that the majority of the investors are doing so. Important to note, since decades, financial pundits has claimed that such action of investors where they enter into herding environment, leads to inefficiency of the financial markets by causing large or unsubstantiated sell-offs which have no fundamental or rational base whatsoever.
Although there is a common consent over the symptoms of herding behavior, however, different academic papers classify it under different categories as Informational Cascade Herding, Reputational Herding and Investigating Herding. While we have briefly introduced the herding behavior, in the preceding sections of this paper, we will unearth ‘Herding’’ using the academic research conducted while unfolding each aspect in a hierarchal manner.
Causes of herding behavior:
Most of the academic research has attributed the concerns of the analysts to thei reputation and career, that prevents them from including any private or exclusive information in the leading analysts forecasted reports. For Instance, Graham in his research paper has concluded that the primary initiator of the herding behavior is the analyst themselves. He propose the theoretical fact that there it is the incentives that force the analyst (second-mover) to disregard his private information and mimic the action taken by the first-mover such as Increase in his/her reputation, decrease with his/her abilities, increase in the strength of prior public information that is consistent with the leader’s action and increases with the level of correlation across informative signal
In addition, Clement and Tse propose that the causes of such behavior of the analysts are that they extract relevant information about stock forecasts from other leader analyst. Hence, when they do not see their private information, they simply do not use this information to alter the leader’s report, simply to remain closer to the mean forecasts and thus, with similar forecasts posted by the analyst, the foundation of herding is laid.
The second cause of herding in the financial markets is the ambiguity that arises from lack of confidence over informational quality. As proposed by Ford and Pang, it is the ambiguity that causes herding as it directly influences investor behavior. Ambiguity arises from the situation of low confidence and informational cascade that forces the individual to follow the herd behavior ignoring his personal view. In other words, because of the presence of informational cascade, the existing information of the stock becomes so strong enough that an individual’s own personal view(even though is rational) comes with no meaning and even that individual chooses to mimic the action of the crowd as he assumes that the group might have some information which he don’t have. If this scenario holds for one individual, then it likely also holds for anyone acting after this person.
Third cause of herding is the psychological behavior of individual itself. This is different from what we discussed under the information cascade. Researchers claim that under information cascade herding, investors let their private information go undermine to follow the herd. However, under the psychological approach, it is just the emotions that force the individual to join the herd and do what other investors are doing. For Instance, at the time of housing bubble in the United States when real estate prices were consistently reaching peaks, rarely an American family had not participated in this bubble without thinking fundamentally as it was just their emotions and expectation to gain as everyone was doing so.
Consequences of herding behavior:
As we have already discussed in the previous section that informational cascade is one of the primary reasons for herding behavior in the financial markets, all such factors are detrimental to the market efficiency. Following informational cascade under which the individual or analyst do not introduce their private information into the market, such blockage of information leads to price inefficiency and stock prices move away from their intrinsic value. Thus, herding behavior can cause long lasting misalignments between the price and the intrinsic value of an asset.
A good number of research work has been conducted to test if herding indeed leads to stock price volatility. For Instance, Blasco in his research work over the impact of herding behavior on the Spanish Stock Market, found that higher the intensity of herding behavior in the financial market, greater the volatility was found in the stock prices. Similar results were also found by Prosad who conducted the research work on Indian Equity Market.
In addition, since the base foundation of herding behavior is trading with asymmetric information, the choice of individual to join the herd and mimic other’s behavior can also increase the level of systemic risk in the market, thus further retarding the production of information. Thus, herding not only causes the stock price to be away from their intrinsic value but also induce negative externalities in the form of increased market risk.
Why policymakers should be concerned and what should they do?
As we had already discussed as how the herding behavior of the investors can be detrimental to the stock market efficiency by promoting stock price volatility and creation of systemic risk in the financial market, the policymakers and the regulator should be concerned as these two ill- effects of herding can lead to financial disasters. The very first threat of herding activities was noticed by Henri Poncare in 1914, as he stated that ‘’herding sets-off volatility bubble build-ups that sometimes extend, if not stopped, to the so called Critical Point, that is, a Market Crash.’’ Hence, the authorities should use their intervention powers to intervene and try to control the herding process.
However, since the global financial market is so huge, intervening to stop the herding process is possible only if all the regulators become so coordinated that they behave as one global regulator as by doing this, they will be able to place the required and forcible amount of intervention. For Instance, the maximum threat of market crash is posed by the financial institutions because if the financial institutions collectively practice herding, this will correlate the risk exposure more highly and a simultaneous failure of these institutions becomes more likely. Hence, if the regulators come to know that herding is being prevailed in the market, they should ask the financial institutions to create an additional cushion of capital for strategic risk. However, they should not disclose to them as which market is at risk as if in that case tighter risk management techniques are employed for those markets where evidence of herding activity has been found, it will only prove detrimental as the ill-effects of herding becomes more vicious when such negative news is spread in the market.
In an another step to suppress herding, it has been found that in the environment of herding investors, government or policymakers should avoid release of information with high frequency such as on daily basis.
Benefits of anti-herding regulations
Important to note, implementation of anti-herding regulations will reap following benefits:
1)Reduction in systemic risk: At times when there is lack of behavioral diversification, anti-herding regulation will reduce the systemic risk in the financial market.
2)Low information asymmetry: Anti-herding information can produce socially-beneficial information. For Instance, by promoting separating equilibria, the anti-herding regulations can reduce the information asymmetry and can induce the financial market participants to take actions according to evidence-based outcomes.
Works Cited
Bhattacharya, S. G. The Madness of Crowds and Risk Management of Banks. In S. G. Bhattacharya, Developing Countries and the Global Financial System (pp. 65-66).
Blasco, N. (1998-99). T he Implications of Herding on Volatility: The case of the Spanish Stock Market.
Graham, J. (1999). Herding among Investment Newsletters: Theory and Evidence. Journal of Finance , 237-268.
Gundstrom, E. H. Governance and Control of Financial System. In E. H. Gundstrom, Governance and Control of Financial Systems: A Resilience Engineering (p. 134).
Hachicha, D. N. New sight of herding behavioural through trading volume. France.
Herd Instinct. (n.d.). Retrieved November 11, 2014, from Investopedia: http://www.investopedia.com/terms/h/herdinstinct.asp
JL Ford, D. K. (2008). Information and Ambiguity: Herd and Contrarian Behavior in Financial Market. 1-34.
Mitts, I. A. Anti-Herding Regulation. Yale Law School.
Prasod, J. (2012). An Examination of Herding: An Emperical Study on Indian Equity Market. Delhi.
Tse, M. C. (2005). Financial Analyst Characteristics and Herding behavior in Forecasting . Journal of Finance , 301-342.
