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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:
feedback
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]