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From Wikipedia, the free encyclopedia
Herd behaviour describes how individuals in a group can act together without planned direction. The term pertains to the behaviour of animals in herds, flocks, and schools, and to human conduct during activities such as stock market bubbles and crashes, street demonstrations, sporting events, episodes of mob violence and even everyday decision making, judgment and opinion forming.
Herd behaviour in animals
A group of animals fleeing a predator shows the nature of herd behavior. In 1971, in the often cited article "Geometry For The Selfish Herd," evolutionary biologist W. D. Hamilton asserted that each individual group member reduces the danger to itself by moving as close as possible to the center of the fleeing group. Thus the herd appears to act as a unit in moving together, but its function emerges from the uncoordinated behavior of self-seeking individuals.[1]
Symmetry breaking in herding behavior
Asymmetric aggregation of animals under panic conditions has been observed in many species, including humans, mice, and ants. Theoretical models have demonstrated symmetry breaking similar to observations in empirical studies. For example when panicked individuals confined to a room with two equal and equidistant exits, a majority will favor one exit while the minority will favor the other.
Possible mechanisms:
Escape Panic Characteristics
Herd behaviour in human societies
Psychological and economic research has identified herd behavior in humans to explain the phenomena of large numbers of people acting in the same way at the same time. The British surgeon Wilfred Trotter popularized the "herd behavior" phrase in his book, Instincts of the Herd in Peace and War (1914). In The Theory of the Leisure Class, Thorstein Veblen explained economic behavior in terms of social influences such as "emulation," where some members of a group mimic other members of higher status. In "The Metropolis and Mental Life" (1903), early sociologist George Simmel referred to the "impulse to sociability in man", and sought to describe "the forms of association by which a mere sum of separate individuals are made into a 'society' ". Other social scientists explored behaviors related to herding, such as Freud (crowd psychology), Carl Jung (collective unconscious), and Gustave Le Bon (the popular mind). Swarm theory observed in non-human societies is a related concept and is being explored as it occurs
in human society.
[edit] Stock market bubbles
Large stock market trends often begin and end with periods of frenzied buying (bubbles) or selling (crashes). Many observers cite these episodes as clear examples of herding behavior that is irrational and driven by emotion -- greed in the bubbles, fear in the crashes. Individual investors join the crowd of others in a rush to get in or out of the market. [2]
Some followers of the technical analysis school of investing see the herding behaviour of investors as an example of extreme market sentiment.[3] The academic study of behavioral finance has identified herding in the collective irrationality of investors, particularly the work of Robert Shiller,[4] and Nobel laureates Vernon Smith, Amos Tversky, and Daniel Kahneman.
Hey and Morone (2004) analysed a model of herd behaviour in a market context. Their work is related to at least two important strands of literature. The first of these strands is that on herd behaviour in a non-market context. The seminal references are Banerjee (1992) and Bikhchandani, Hirshleifer and Welch (1992), both of which showed that herd behaviour may result from private information not publicly shared. More specifically, both of these papers showed that individuals, acting sequentially on the basis of private information and public knowledge about the behaviour of others, may end up choosing the socially undesirable option. The second of the strands of literature motivating this paper is that of information aggregation in market contexts. A very early reference is the classic paper by Grossman and Stiglitz (1976) that showed that uninformed traders in a market context can become informed through the price in such a way that private information is aggregated correctly and efficiently. A summary of
the progress of this strand of literature can be found in the paper by Plott (2000). Hey and Morone (2004) showed that it is possible to observe herd-type behaviour in a market context. Their result is even more interesting since it refers to a market with a well-defined fundamental value. Even if herd behaviour might only be observed rarely, this has important consequences for a whole range of real markets most particularly foreign exchange markets.
[edit] Behavior in crowds
Crowds that gather on behalf of a grievance can involve herding behavior that turns violent, particularly when confronted by an opposing ethnic or racial group. The Los Angeles riots of 1992, New York Draft Riots and Tulsa Race Riot are notorious in U.S. history, but those episodes are dwarfed by the scale of violence and death during the Partition of India. Population exchanges between India and Pakistan brought millions of migrating Hindus and Muslims into proximity; the ensuing violence produced an estimated death toll of between 200,000 and one million. The idea of a "group mind" or "mob behavior" was put forward by the French social psychologists Gabriel Tarde and Gustave Le Bon.
Sporting events can also produce violent episodes of herd behaviour. The most violent single riot in history may be the sixth-century Nika riots in Constantinople, precipitated by partisan factions attending the chariot races. The football hooliganism of the 1980s was a well-publicized, latter-day example of sports violence.
[edit] Everyday decision-making
Benign herding behaviors may be frequent in everyday decisions based on learning from the information of others, as when a person on the street decides which of two restaurants to dine in. Suppose that both look appealing, but both are empty because it is early evening; so at random, this person chooses restaurant A. Soon a couple walks down the same street in search of a place to eat. They see that restaurant A has customers while B is empty, and choose A on the assumption that having customers makes it the better choice. And so on with other passersby into the evening, with restaurant A doing more business that night than B. This phenomenon is also referred as an information cascade. [5] [6]