Herd Behavior in Financial Market Essay

Custom Student Mr. Teacher ENG 1001-04 11 July 2017

Herd Behavior in Financial Market

Definition of herding

On Friday 14 September 2007, when Northern Rock in the UK opened it branches, many customers wanted to withdraw their savings and �1 billion, about 5% of the total bank deposits were withdrawn that day. And on Monday 17 September, a similar situation happened in front of Northern Rock branches in the UK. Even though every customer does not have the same amount of information, they all decided to behave in the same way and some were following the others on the following days without any clear plan. People thought that they were going to lose their bank deposits and that type of bank customers’ behavior caused liquidity problem and made the situation even worse.

However, none of the clients who kept their deposits lost due to the fact the British Government and the Bank of England would guarantee the safety of the deposits. How can we explain that kind of behavior? Originally Herding is a term meaning animal flocking behavior. And according to the definition of Wikipedia Herding is the act of bringing individual animals together into a group (herd), maintaining the group and moving the group from place to place-or any combination of those. Apart from this bank run case, Herd behavior describes how individuals in a group can act together without planned direction.

POSSIBLE EXPLICATION AND MECHANISM OF HERD BEHAVIOR

Animals’ Herd Behavior

According to evolutionary biologist W. D. Hamilton’s theory animals are forming a group to reduce the danger of being hunted by predictors. As a unit, they are moving together to the same direction. Animals are behaving in the same way to minimize the risk on the behalf of self-protection. Maybe this kind of behavior sounds rational if the result is always optimistic but copying your neighbor can be the worst decision sometimes. When something goes wrong and someone leads the group to the wrong direction, the whole group is going to be in danger.

Human Herd Behavior

However, human herd behavior is much more complicated than animals’ one and several scholars tried to explain it. Friedrich Nietzsche referred it as “herd morality” and the “herd instinct” which explain the phenomena when a lot of people are behaving in the same way at the same time. And according to Thorstein Veblen’s theory, some people imitate the other people with higher status. Human beings are continuously competing with others in order to survive or surpass others, and they try to move faster in order to take advantage of the others. As the proverbs says the early bird catches the worm, they think the faster they make the decision or do whatever they can, the better it is. However, this does not always lead to success.

Those decisions are based on the sources they have and the sources are

Sanctions upon deviants – dictators put their rivals in the prison (opposition is not allowed)

Preference interactions – some people are wearing Burberry coats just because the majority is wearing it while others prefer to wear coats with the colors they like

Direct communication – someone from your reference group or someone with credibility says that s/he likes certain products

Observational influence – you observe the consequences of others’ actions

Based on such sources, people make decision whether to herd or disperse, but people are herding for different reasons and their behavior is classified into several models.

Herding Models

Payoff Externalities Models (also called Network Externalities) – If more people are using facebook, it will attract more people to use facebook. In this case, people feel like they have to participate in the same situation so that they can have the same benefits.

Information Cascade Models – When you have a flood of information coming in, it is much more difficult to make a rational decision. Nowadays there are too many sources to consider and you can barely judge if information is true or false. In this kind of situation, people are getting irrational and they tend to make decision based on the decision of the majorities, and this situation is called information cascade which occurs when people observe the actions of others and then make the same choice that the others have made, independently of their own private information signals.

They are seen in groups under immediate stress from external forces, such as herd behaviour. A cascade arises naturally when people usually see what others do but not what they know. Because it is usually sensible to do what other people are doing, even this can be against what the individual believes to be true. This behavior is independent from their own private information or opinion.

Concept of information cascade is based on observational and social learning. People learn from their environment. Generally, people are oriented to avoid negative consequences of their decisions or behaviors. They wish to have positive results or effects. That’s why their behavior is related to social and observational learning. People subconsciously have the idea of ‘It is more likely that I am wrong than that all those other people are wrong. Therefore, I will do as they do’.

Examples of Herding Behavior

Bank runs: depositors running on banks when they observe other depositors doing so. More specifically, First; investors can observe in long run when others are running on banks. Second, forcing long-term projects to liquidate early possibly leads to shortfall of funds.

From the payoff externalities model’s view, people are withdrawing their deposits because they feel like they are losing their money if they keep their money on the bank account. And from informational cascade model’s view, some people may think they are not going to lose their money on their bank account but they are following the others because they think they are not wise enough and others are withdrawing their money.

In real case, Argentina experienced such a run in the last two days of November 2001, with total deposits in the banking system falling by more than 2 billion (US) dollars, or nearly 3 percent, on the second day of the run alone.1 Such runs were a common occurrence in the United States in the late nineteenth and early twentieth centuries and have also occurred in recent times in several developing countries, including Brazil in 1990 and Ecuador in 1999.

Asian crisis of 97-98, herding and speculation infection

The Asian crisis of 1997-98 that led to a regional economic fall in East Asia can be traced to overexpansion and under-regulation. The center of the Asian crisis was Thailand’s careless macroeconomic management that featured a fraudulent financial sector. The Asian expansion of the crisis was a due to the existing global financial integration (and similar export dependencies), current account inequities and attached exchange rates all mixed with the damaging effect of speculation and herding spreading all over the region. Resulting structural reforms and adjustments in Thailand and other damaged Asian nations came from the International Monetary Fund. A major result was a balanced exchange rate regime now prevalent in much of East Asia.

Facts:

During 1995 a number of experts started to wonder if the countries of Southeast Asia might be vulnerable to a macroeconomic crisis do to the poor administration of its financial procedures and to the volatility of their related economies. The main indicator was the rise of very large current account deficits among several Asian countries. Closer examination also revealed that several of the countries had developed some financial weaknesses: heavy investment in highly speculative real estate ventures, financed by borrowing from badly informed foreign sources or by credit from non regulated domestic financial institutions. It’s now known that during 1996 officials from the IMF and World Bank actually began warning the governments of Thailand, Malaysia, and other countries of the existing risks by their financial situation, and asked them to apply corrective policies. However, those governments rejected the warnings.

On July 2 1997, after months of declaring that it would not happen, the government of Thailand abandoned its efforts to maintain a fixed exchange rate for its currency, the baht. The currency was quickly depreciated by more than 20 percent so within a few days most neighboring countries fell like Thailand. What forced Thailand to devalue its currency was the massive speculation against the baht, assumptions that over a few months had consumed most of what initially seemed as a large war of foreign exchange. And why were speculators betting against Thailand? Because they expected the baht to be devalued, of course.

This kind of circular logic – in which investors escape a currency because they expect it to be devalued, and much of the pressure on the currency comes precisely because of this investor shortage of confidence – is the defining actor of a currency crisis and is known as Bank Run theory. In the context of a currency crisis, such behavior could mean that a wave of selling, whatever its initial cause, could be magnified through complete imitation and turn, into a rush out of the currency.

Bank run in Thai currency devaluation can be viewed in two main behaviors. First; investors run when other investors are running the bank; a magnified opinion of a certain group starts to be spread in some others by just herding or imitation. Second, when banks that were investing in long-term projects were forced to liquidate early (because of the invertors running away), there was a potential lost of funds. Consequently, the last depositors to withdraw were left empty-handed (first-come, first-served limitation).

BUBBLES

Bubbles are sort of mass errors caused by the nature of herd. Even though there is a convincing evidence of bubbles, people are still overly convinced by their belief that market is efficient and rational. Therefore people are optimistic of their investment and they take part in the bubble. Some people may doubt the situation and find some evidence of bubbles but they still invest their capital in the market because others are doing it which is a sort of informational cascade. However, the bubble collapses and that sort of herding behavior makes the impact of the collapse much significant.

The Dot-com Bubble

The dot-com bubble (also referred to as the Internet bubble) was a speculative which had its climax on March 10, 2000, with the NASDAQ hitting up to 5132.52 but closing at 5048.62 in the same day. During the dot-com bubble period mostly the developed countries experienced the growth in the Internet sector and related fields.

Companies such as Cisco Systems, Dell, Intel, and Microsoft were the dominant player of NASDAQ. And related to the Internet business a group of new Internet-based companies commonly referred to as dot-coms were founded. Just because of the fact that Companies had a name with an “e-” prefix to their name and a “.com” the stock price was going up. Investors were overly confident of their future profits due to the advancement of technology and individual speculation while they overlooked traditional stock market value until the bubble was collapsed.

Conclusion

As we can see massive herding behavior turned out to be a cause of crisis at the end, and herd behavior is seen as something very negative to the market. As we have seen bank runs, bubbles, and several forms of crises. However, we cannot prevent from herding because it is a sort of instinct and it is closely related to psychological factors. Partially, individuals can make profit of their herding behavior as they are following famous investors such as Warren Buffet but the fact is that no investor can really avoid bubbles and forecast the coming crises. What we have to remember is the financial market is a complex of rational and irrational behavior and we can barely categorize them before the disaster happens. We have to be prepared of the consequence the herd behavior and be rational when the irrationality happens.

Works Cited

BIKHCHANDANI, S., 1998, Learning from the behavior of others: conformity, fads, and informational cascades

BIKHCHANDANI, S., D. HIRSHLEIFER and I. WELCH, 2001. Informational Cascades and Rational Herding: An Annotated

Devenow, Andrea and Ivo Welch, 1996, Rational Herding in Financial Economics, European Economic Review 40, 603-615

Ennis, Huberto M. and Todd Keister, 2009, Bank Runs and Institutions: The Perils of Intervention.

Hirshleifer, David and Teoh, Siew Hong, 2011, Herd Behavior and Cascading in Capital Markets: A Review and Synthesis, MPRA Paper No. 5186

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