efficient market hypothesis

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EFFICIENT MARKET HYPOTHESIS

In the mid-1960s Eugene Fama introduced the idea of an efficient capital market to the literature

of finance. He believed that intense competition in the capital market leads to fair pricing of debt and

equity securities. This is indeed a sweeping statement and continues to be controversial even today.

In the early 1950s, Maurice Kendall examined the behaviour of stock and commodity prices in

search of regular cycles. Instead of discovering any regular price cycle, he found that prices appeared to

follow a random walk, implying that successive price changes are independent of one another.

An efficient market is one in which the market price of a security is an unbiased estimate of its

intrinsic value. However it should be noted that market efficiency does not imply that the market price

equals intrinsic value every time. All that it says is that the errors in the market price are unbiased.

The statement that prices reflect all available information represents the highest order of market

efficiency. As Eugene Fama suggested it is useful to distinguish three levels of market efficiency:

i. Weak form efficient market hypothesis

ii. Semi-strong form efficient market hypothesis

iii. Strong-form efficient market hypothesis

Weak form of efficient market hypothesis

The weak form market hypothesis says that the current price of a stock reflects all information

found in the record of past prices and volumes. This means that there is no relationship between past and

future price movements. Three types of tests have been commonly employed to empirically verify the

weak-form efficiency market hypothesis:

i. Serial Correlation test

ii. Runs test

iii. Filter Rules test

Serial Correlation Test

One way to test for randomness in stock price changes is to look at their serial correlations (also

called as auto-correlations). Here we try to get answers to such questions as Is the price change in one

period correlated with the price change in some other period? If such auto-correlations are negligible, the

price changes are considered to be serially independent.

Runs Test

Given a series of stock price changes, each price change is designed as a plus (+) if it presents an

increase or a minus (-) if it represents a decrease. The resulting series for example may look as follows :

+++-++--+



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A run occurs when there is no difference between the sign of two changes. When the sign of

change differs, the run ends and a new run begins.

To test a series of price changes for independence, the number of runs in that series is compared to

see whether it is statistically different from the number of runs in a purely random series of the same size.

Filter Rules Test

An n percent filter rule may be defined as follows : If the price of a stock increases by at least n

percent, buy and hold it until its prices decreased by at least n percent from a subsequent high. When the

price of a stock decreases by at least n percent or more sell it.

By and large these tests have been overwhelming in favour of the weak-form of efficient market

hypothesis.

Semi-strong form of efficient market hypothesis

The Semi-strong form of efficient market hypothesis believes that the stock prices adjust rapidly to

all publicly available information. This implies that by using publicly available information, investors cannotearn superior risk-adjusted returns.

Two kinds of studies have been conducted to test the semi-strong form market hypothesis. They

are:

i. Event studies

ii. Portfolio studies

Event Studies

An event study examines the market reactions to and excess returns around a specific informationevent like an earnings announcement or a stock split.

The results of event studies are mixed. Most event studies support the semi-strong form efficient

market hypothesis. Several event studies, however, raised doubts about the validity of the semi-strong

form efficient market hypothesis.

Portfolio Studies

A portfolio study examines the returns earned by a portfolio of stocks having some observable

characteristics like low price-earnings ratio or small market captialisation.

The results of portfolio studies are also mixed. Some portfolio studies suggest that it is not possible

to earn superior risk-adjusted returns by trading on observable characteristics. However, other portfolio

studies have highlighted various inefficiencies and anomalies. The most important anomalies are :

i. Stocks of small capitalization companies seem outperform stocks of large capitalisation companies.

ii. Low PE ratio stocks tend to outperform higher PE ratio stocks.

Strong form efficient market hypothesis



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Strong form efficient market hypothesis says that all available information, public or private is

reflected in the stock price. This is an extreme hypothesis and is questionable. To test this hypothesis,

researchers have analyzed the return earned by certain groups who may specially be privileged in terms of

access to information. The groups are Corporate insiders, Stock exchange specialists and Mutual fund

managers

The results of the tests have proved that corporate insiders who may benefit from access to inside

information and stock exchange specialists who have monopolistic access to buy and sell order position

earn superior rate of return after adjustment for risk. However, mutual fund managers do not on an

average earn a superior rate of return.

Other evidences

Apart from the standard tests for various forms of market efficiency, many other studies have been

done to explore the behavior of security prices and interest rates. Further, economists have reflected on

certain financial episodes like the crash of 1987. These studies suggest the following:

Price Overreaction

It appears that prices of individual stocks overreact to information and then correct themselves.

Calendar Anomalies

Researchers have found some season patterns. One well documented anomaly is the week-end

effect. Stock returns tend to be negative over the period from Fridays close to Mondays opening.

Another calendar anomaly is the January effect. Stock prices seem to rise more in January than in

any other month of the year. Several explanations have been offered to explain the January effect. First,investors sell the stocks on which they have lost money in December to get the tax benefit from capital loss

and then buy them back in January. Second, in the first few weeks of January, which is the 4th

quarter of

the year, a lot of information is revealed about the firms. Third, there are substantial inflows to portfolios

around the end of the financial year. These are just partial explanations for the January effect.

Excess volatility

Robert Shiller and others have argued that investors pursue fads and behave like a herd. As a result

stock market overreacts to events. To prove this point he has provided evidence which proves that

volatility of sock prices is too large to be justified by the volatility of dividends.

efficient market hypothesis

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