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Comment on the Three Conditions on Market Efficiency

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Comment on the Three Conditions on Market Efficiency
An efficient capital market is one in which stock prices fully reflect available information. Professor Andrei Shleifer has suggested three conditions lead to market efficiency. (1)rationality, (2)independent deviations from rationality, and (3)arbitrage. This essay will examine investors’ behavioral biases and then discuss the behavioral and empirical challenges to market efficiency.

In the attached article, James Montier suggested three behavioral biases that investors had. (1) illusion of control, (2)self-attribution, and (3)over-confident. Illusion of control means people fell they are in control of a situation far more than they are. Self-attribution means good outcomes are contributed to their skill while bad outcomes are contributed to external, such as back luck. These two biases lead people to be over-optimistic and exaggerate their own abilities. People are always over-confident as well. They always think they are smarter and have better information than they actually do. These three behavioral biases form a potential combination and lead investors to overestimate their ability and knowledge and understate the risks.

In reality, there are some other behavioral biases. Investors usually prefer to put their money into a company that they know or familiar with. This is known as familiarity bias. They will invest heavily in the company they work for. They will also allocate a larger fraction of their investments to domestic stock even though it is easier to diversify investments across geographies. In addition, people tend to perceive probabilities and resonate with their own pre-existing ideas even though the conclusions drawn are statistically invalid. And this is called representativeness. The next bias exists in reality is conservatism, it means that people are too slow in adjusting their beliefs to new information. They clings to prior views or forecasts at the expense of acknowledging new information. The last bias I want to mention is herd

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