Definition of Efficient Market Theory

Stock prices are determined by a number of factors such as fundamental factors, technical factors and psychological factors. The behavior of stock prices is studied with the help of different methods such as fundamental analysis and technical analysis. Fundamental analysis seeks to evaluate the intrinsic value of securities by studying the fundamental factors affecting the performance of the economy, industry and companies. Technical analysis believes that the past behavior of stock prices gives an indication of the future behavior. It tries to study the patterns in stock price behavior through charts and predict the future movement in prices. There is a third theory on stock price behavior which questions the assumptions of technical analysis.

The basic assumption in technical analysis is that stock pie movement is quite orderly and not random. The new theory questions this assumption. From the results of several empirical studies on stock price movements, the advocates of the new theory assert that share price movements are random. The new theory came to be known as Random Walk Theory because of its principal contention that share price movements represent a random walk rather than an orderly movement.

Random Walk Theory

Stock price behavior is explained by the theory in the following manner. A change occurs in the price of a stock only because of certain changes in the economy, industry or company. Information about these changes alters the stock prices immediately and the stock moves to a new level, either upwards or downwards, depending on the type of information. This rapid shift to a new equilibrium level whenever new information is received is recognition of the fact that all information which is known is fully reflected in the price of the stock. Further change in the price of the stock will occur only as a result of some other new piece of information which was not available earlier. Thus, according to this theory, changes in stock prices show independent behavior and are dependent on the new pieces of information that are received but within themselves are independent of each other. Each price change is independent of other price changes because each change is caused by a new piece of information.

The basic premise in random walk theory is that the information on changes in the economy, industry and company performance is immediately and fully spread so that all investors have full knowledge of the information. There is an instant adjustment in stock prices either upwards or downwards. Thus, the current stock price fully reflects all available information on the stock. Therefore, the price of a security two days ago can in no way help in speculating the price two days later. The price of each day is independent. It may be unchanged, higher or lower from the previous price, but that depends on new pieces of information being received each day.

The random walk theory presupposes that the stock markets are so efficient and competitive that there is immediate price adjustment. This is the result of good communication system through which information can be spread almost anywhere in the country instantaneously. Thus, the random walk theory is based on the hypothesis that the stock markets are efficient. Hence, this theory later came to be known as the efficient market hypothesis (EMH) or the efficient market model.

The Efficient Market Hypothesis

This hypothesis states that the capital market is efficient in processing information. An efficient capital market is one in which security prices equal their intrinsic values at all times, and where most securities are correctly priced. The concept of an efficient capital market has been one of the dominant themes in academic literature since the 1960s. According to Elton and Gruber, “when someone refers to efficient capital markets, they mean that security prices fully reflect all available information”.’ According to Eugene Fama,2 in an efficient market, prices fully reflect all available information. The prices of securities observed at any time are based on correct evaluation of all information available at that time.

The efficient market model is actually concerned with the speed with which information is incorporated into security prices. The technicians believe that past price sequence contains information about the future price movements because they believe that information is slowly incorporated in security prices. This gives technicians an opportunity to earn excess returns by studying the patterns in price movements and trading accordingly.

Fundamentalists believe that it may take several days or weeks before investors can fully assess the impact of new information. As a consequence, the price may be volatile for a number of days before it adjusts to a new level. This provides an opportunity to the analyst who has superior analytical skills to earn excess returns.

The efficient market theory holds the view that in an efficient market, new information is processed and evaluated as it arrives and prices instantaneously adjust to new and correct levels. Consequently, an investor cannot consistently earn excess returns by undertaking fundamental analysis or technical analysis.

Forms of Market Efficiency

The capital market is considered to be efficient in three different forms: the weak form, semi-strong form and the strong form. Thus, the efficient market hypothesis has been subdivided into three forms, each dealing with a different type of information. The weak form deals with the information regarding the past sequence of security price movements, the semi-strong form deals with the publicly available information, while the strong form deals with all information, both public and private (or inside).

The different forms of efficient market hypothesis have been tested through several empirical studies. The tests of the weak form hypothesis are essentially tests of whether all information contained in historical prices of securities is fully reflected in current prices. Semi-strong form tests of the efficient market hypothesis are tests of whether publicly available information is fully reflected in current stock prices. Finally, strong form tests of the efficient market hypothesis are tests of whether all information, both public and private (or inside), is fully reflected in security prices and whether any type of investor is able to earn excess returns.

Empirical Tests of Weak Form Efficiency

The weak form of the efficient market hypothesis (EMH) says that the current prices of stocks already fully reflect all the information that is contained in the historical sequence of prices. The new price movements are completely random. They are produced by new pieces of information and are not related or dependent on past price movements. Therefore, there is no benefit in studying the historical sequence of prices to gain abnormal returns from trading in securities. This implies that technical analysis, which relies on charts of price movements in the past, is not a meaningful analysis for making abnormal trading profits.

The weak form of the efficient market hypothesis is thus a direct repudiation of technical analysis.

Two approaches have been used to test the weak form of the efficient market hy-pothesis. One approach looks for statistically significant patterns in security price changes. The alternative approach searches for profitable short-term trading rules.

Serial Correlation Test

Since the weak form EMH postulates independence between successive price changes, such independence or randomness in stock price movements can be tested by calculating the correlation between price changes in one period and changes for the same stock in another period. The correlation coefficient can take on a value ranging from —1 to 1; a positive number indicates a direct relation, a negative value implies an inverse relationship and a value close to zero implies no relationship. Thus, if correlation coefficient is close to zero, the price changes can be considered to be serially independent.

Run Test

The run test is another test used to test the randomness in stock price movements. In this test, the absolute values of price changes are ignored; oly the direction of change is considered. An increase in price is represented by + signs. The decrease is represented by – sign. When there is no change in prices, it is represented by ‘O’. A consecutive sequence.of the same sign is considered as a run.

For example, the sequence + + + — — — has two runs. In other words, a change of sign indicates a new run. The sequence — — — + + 0 — — — + + + + has five runs; a run of three — ‘s, followed by a run of two + ‘s, another run of one 0, a fourth run of three — ‘s and a fifth run of four + ‘s. In a run test, the actual number of runs observed in a series of stock price movements is compared with the number of runs in a randomly generated number series. If no significant differences are found, then the security price changes are considered to be random in nature.

Filter Tests

If stock price changes are random in nature, it would be extremely difficult to develop successful mechanical trading systems. Filter tests have been developed as direct tests of specific mechanical trading strategies to examine their validity and usefulness.

It is often believed that, as long as no new information enters the market, the price fluctuates randomly within two barriers—one lower, and the other higher—around the fair price. When new information comes into the market, a new equilibrium price will be determined. If the news is favorable, then the price should move up to a new equilibrium above the old price. Investors will know that this is occurring when the price breaks through the old barrier. If investors purchase at this point, they will benefit from the price increase to the new equilibrium level.

Likewise, if the news received is unfavorable, the price of the stock will decline to a lower equilibrium level. If investors sell the stock as it breaks the lower barrier, they will avoid much of the decline. Technicians set up trading strategies based on such patterns to earn excess returns.

The strategy is called a filter rule. The filter rule is usually stated in the following way: Purchase the stock when it rises by x per cent from the previous low and sell it when it declines by x per cent from the subsequent high. The filters may range from 1 per cent to 50 per cent or more. The alternative to this active trading strategy is the passive buy and hold strategy.

The returns generated by trading according to the filter rule are compared with the returns earned by an investor following the buy and hold strategy. If trading with filters results in superior returns that would suggest the existence of patterns in price movements and negate the weak form EMH.

Distribution Pattern

It is a rule of statistics that the distribution of random occurrences will conform to a normal distribution. Then, if price changes are random, their distribution should also be approximately normal. Therefore, the distribution of price changes can be studied to test the randomness or otherwise of stock price movements.

In the 1960s the efficient market theory was known as the random walk theory. The empirical studies regarding share price movements were testing whether prices followed a random walk.

Two articles by Roberts and Osborne, both published in 1959, stimulated a great deal of discussion of the new theory then called random walk theory.

Roberts’ study compared the movements in the Dow Jones Industrial Average (an American stock market index) with the movement of a variable generated from a random walk process. He found that the random walk process produced patterns which were very similar to those of the Dow Jones index.

Osborne’s study found a close resemblance between share price changes and the random movement of small particles suspended in a solution, which is known in Physics as the Brownian motion. Both the studies suggested that share price changes are random in nature and that past prices had no predictive value.

During the 1960s there was an enormous growth in serial correlation testing. None of these found any substantial linear dependence in price changes. Studies by Moore, Fama and Hagerman and Richmond are some of the early studies in this area. Moore found an average serial correlation coefficient of — 0.06 for price changes measured over weekly intervals. Fama’s study tested the serial correlation for the thirty stocks comprising the Dow Jones industrial average for the five years prior to 1962. The average serial correlation coefficient was found to be 0.03. Both the coefficients were not statistically different from zero; thus both the studies supported the random walk theory.

Fama also used run tests to measure dependency. The results again supported the random walk theory. Many studies followed Moore’s and Fama’s work each of which used different databases. The results of these studies were much the same as those of Moore and Fama.

Hagerman and Richmond conducted similar studies on securities traded in the ‘over- the-counter’ market and found little serial correlation. Serial correlation tests of dependence have also been carried out in various other stock markets around the world. These have similarly revealed little or no serial correlation.

Much research has also been directed towards testing whether mechanical trading strategies are able to earn above average returns. Many studies have tested the filter rules for its ability to earn superior returns. Early American studies were those by Alexander, who originally advocated the filter strategy, and by Fama and Blume. There were similar studies in the United Kingdom by Dryden and in Australia by Praetz. All these studies have found that filter strategies did not achieve above average returns. Thus, the results of empirical studies have been virtually unanimous in finding little or no statistical dependence and price patterns and this has corroborated the weak form efficient market hypothesis

Empirical Tests of Semi-Strong Form Efficiency

The semi-strong form of the efficient market hypothesis says that current prices of stocks not only reflect all informational content of historical prices, but also reflect all publicly available information about the company being studied. Examples of publicly available information are—corporate annual reports, company announcements, press releases, announcements of forthcoming dividends, stock splits, etc. The semi-strong hypothesis maintains that as soon as the information becomes public the stock prices change and absorb the full information. In other words, stock prices instantaneously adjust to the information that is received.

The implication of semi-strong hypothesis is that fundamental analysts cannot make superior gains by undertaking fundamental analysis because stock prices adjust to new pieces of information as soon as they are received. There is no time gap in which a fundamental analyst can trade for superior gains. Thus, the semi-strong hypothesis repudiates fundamental analysis.

Semi-strong form tests deal with whether or not security prices fully reflect all publicly available information. These tests attempt to establish whether share prices react precisely and quickly to new items of information. If prices do not react quickly and adequately, then an opportunity exists for investors or analysts to earn excess returns by using this information. Therefore, these tests also attempt to find if analysts are able to earn superior returns by using publicly available information.

There is an enormous amount and variety of public information. Semi-strong form tests have been performed with respect to many different types of information. Much of the methodology used in semi-strong form tests has been introduced by Fama, Fisher, Jensen and Roll. Theirs was the first of the studies that were directly concerned with the testing of the semi-strong form of EMH. Subsequent to their study, a number of refinements have been developed in the test procedure.

The general methodology followed in these studies has been to take an economic event and measure its impact on the share price. The impact is measured by taking the difference between the actual return and expected return on a security. The expected return on a security is generally estimated by using the market model (or single index model) suggested by William Sharpe. The model used for estimating expected returns is the following:

R_i=  a_i + b_iR_m + e_i

Where

This analysis is known as Residual analysis. The positive difference between the actual return and the expected return represents the excess return earned on a security. If the excess return is close to zero, it implies that the price reaction following the public announcement of information is immediate and the price adjusts to a new level almost immediately. Thus, the lack of excess returns would validate the semi-strong form EMH.

Major studies on the impact of capitalization issues such as stock splits and stock dividends have been conducted in the United States by Fama, Fisher, Jensen and Roll and Johnson, in Canada by Finn, and in the United Kingdom by Firth. All these studies found that the market adjusted share prices instantaneously and accurately for the new information. Both Pettit and Watts have investigated the market’s reaction to dividend announcements. They both found that all the price adjustment was over immediately after the announcement and thus, the market had acted quickly in evaluating the information.

Other items of information whose impact on share prices have been tested include announcements of purchase and sale of large blocks of shares of a company, takeovers, annual earnings of companies, quarterly earnings, accounting procedure changes, and earnings estimates made by company officials. All these studies which made use of the Residual analysis approach, showed the market to be relatively efficient.

Ball and Brown tested the stock market’s ability to absorb the informational content of reported annual earnings per share information. They found that companies with good earnings report experienced price increase in stock, while companies with bad earnings report experienced decline in stock prices. But surprisingly, about 85 per cent of the informational content of the earnings announcements was reflected in stock price movements prior to the release of the actual earnings figure. The market seems to adjust to new information rapidly with much of the impact taking place in anticipation of the announcement.

Joy, Litzenberger and McEnally tested the impact of quarterly earnings announcements on the stock price adjustment mechanism. Some of their results, however, contradicted the semi-strong form of the efficient market hypothesis. They found that the favorable information contained in published quarterly earnings reports was not always instantaneously adjusted in stock prices. This may suggest that the market does not adjust share prices equally well for all types of information.

By way of summary it may be stated that a great majority of the semi- strong efficiency tests provide strong empirical support for the hypothesis; however, there have been some contradictory results too. Most of the reported results show that stock prices do adjust rapidly to announcements of new information and that investors are typically unable to utilize this information to earn consistently above average returns.

Tests of Strong Form Efficiency

The strong form hypothesis represents the extreme case of market efficiency. The strong form of the efficient market hypothesis maintains that the current security prices reflect all information both publicly available information as well as private or inside information. This implies that no information, whether public or inside, can be used to earn superior returns consistently.

The directors of companies and other persons occupying senior management positions within companies have access to much information that is not available to the general public. This is known as inside information. Mutual funds and other professional analysts who have large research facilities may gather much private information regarding different stocks on their own. These are private information not available to the investing public at large.

The strong form efficiency tests involve two types of tests. The first type of tests attempt to find whether those who have access to inside information have been able to utilize profitably such inside information to earn excess returns. The second type of tests examine the performance of mutual funds and the recommendations of investment analysts to see if these have succeeded in achieving superior returns with the use of private information generated by them.

Jaffe, Lorie and Niederhoffer studied the profitability of insider trading (i.e. the investment activities of people who had inside information on companies). They found that insiders earned returns in excess of expected returns. Although there have been only a few empirical studies on the profitability of using inside information, the results show, as expected, that excess returns can be made. These results indicate that markets are probably not efficient in the strong form.

Many studies have been carried out regarding the performance of American mutual funds using fairly sophisticated evaluation models. All the major studies have found that mutual funds did no better than randomly constructed portfolios of similar risk. Firth studied the performance of Unit Trusts in the United Kingdom during the period 1965—75. He also found that unit trusts did not outperform the market index for their given levels of risk. A small research has been conducted into the profitability of investment recommendations by investment analysts. Such studies suggest that few analysts or firms of advisers can claim above average success with their forecasts.

The results of research on strong form EMH may be summarized as follows:

Inside information can be used to earn above average returns.

Mutual funds and investment analysts have not been able to earn superior returns by using their private information.

In conclusion, it may be stated that the strong form hypothesis is invalid as regards inside information, but valid as regards private information other than inside information.

EMH Vs. Fundamental and Technical Analyses

There are three broad theories concerning stock price movements. These are the fundamental analysis, technical analysis and efficient market hypothesis. Fundamental analysts believe that by analyzing key economic and financial variables they can estimate the intrinsic worth of a security and then determine what investment action to take. Fundamental analysis seeks to identify under priced securities and overpriced securities. Their investment strategy consists in buying under priced securities and selling overpriced securities, thereby earning superior returns.

A technical analyst maintains that fundamental analysis is unnecessary. He believes that history repeats itself. Hence, he tries to predict future movements in share prices by studying the historical patterns in share price movements.

The efficient market hypothesis is expressed in three forms. The weak form of the EMH directly contradicts technical analysis by maintaining that past prices and past price changes cannot be used to forecast future price changes because successive price changes are independent of each other. The semi-strong form of the EMH contradicts fundamental analysis to some extent by claiming that the market is efficient in the dissemination and processing of information and hence, publicly available information cannot be used consistently to earn superior investment returns.

The strong form of the EMH maintains that not only is publicly available information useless to the investor or analyst but all information is useless.

Even though the EMH repudiates both fundamental analysis and technical analysis, the market is efficient precisely because of the organized and systematic efforts of thousands of analysts undertaking fundamental and technical analysis. Thus, the paradox of efficient market hypothesis is that both fundamental and technical analyses are required to make the market efficient and thereby validate the hypothesis.

Competitive Market Hypothesis

An efficient market has been defined as one where share prices always fully reflect available information on companies. In practice, no existing stock market is perfectly efficient. There are evident shortcomings in the pricing mechanism. Often, the complete body of knowledge about a company’s prospects is not publicly available to market participants. Further, the available information would not be always interpreted in a completely accurate fashion. The research studies on EMH have shown that price changes are random or independent and hence unpredictable. The prices are also seen to adjust quickly to new information. Whether the price adjustments are correct and accurate, reflecting correctly and accurately the meaning of publicly available information is difficult to determine.

All that can be validly concluded is that prices are set in a very competitive market, but not necessarily in an efficient market. This competitive market hypothesis provides scope for earning superior returns by undertaking security analysis and following portfolio management strategies.

Market Inefficiencies

Many studies have proved the prevalence of the market efficiency. At the same time, several studies contradict the concept of market efficiency. For example, the studies conducted Joy, Lichtenberger and Mc. Enally over the period of 1963-1968 gave different results. The authors have examined the quarterly earnings of the stock prices. The earning of one quarter was compared with the same quarter of the previous year. If the current year’s earnings were 40% or more than the earnings for the same quarter in the previous year, the earnings were classified as good earnings than anticipated. If the current quarter’s earnings were below 40% of the previous year’s earnings, they are classified as bad than expected.

Then the abnormal returns were calculated from 13 weeks prior to the announcement of the earnings to 26 weeks after the announcement of the earnings. The stocks whose earn-ings are substantially greater than anticipated gave positive abnormal returns. The stocks whose earnings are below the anticipated earnings generated negative abnormal returns.

The author’s main claim is that after the announcement of the earnings, stocks that reported earnings substantially above those of the previous year continued to earn positive abnormal returns. According to the study, the investors could have earned positive abnormal returns of around 6.5 per cent over the next 26 weeks simply by buying stocks that have reported earnings 40% above the previous quarterly earnings. Meanwhile for those stocks with earnings substantially below the previous year, the cumulative average abnormal return remained relatively stable. This shows evidence against the semi-strong market hypothesis because it states that when the information is made public the analyst could not earn abnormal profits. A study made by C.P. Jones, R. S. Randleman for the period 1971-1980 had also given similar results to those of JLM.

Low PE effect many studies have provided evidences that stocks with low price earnings ratios yield higher returns than stocks with higher PEs. This is known as low PE effect. A study made by Basu in 1977 was risk adjusted return and even after the adjustment there was excess return in the low price-earnings stocks. If historical information of P/E ratios is useful to the investor in obtaining superior stock returns, the validity of the semi-strong form of market hypothesis is questioned. His results stated that low P/E portfolio experienced superior returns relative to the market and high P/E portfolio performed in an inferior manner relative to the overall market. Since his result directly contradicts semi-strong form of efficient market hypothesis, it is considered to be important.

Small firm effect the theory of the small firm effect maintains that investing in small firms (those with low capitalization) provides superior risk adjusted returns. Bans found that the size of the firm has been highly correlated with returns. Bans examined historical monthly returns of NYSE common stocks for the period 1931-1975. He formed portfolios consisting of 10 smallest firms and the 10 largest firms and computed the average return for these portfolios. The small firm portfolio has outperformed the large firm portfolio.

Several other studies have confirmed the existence of a small firm effect. The size effect has given rise to the doubts regarding the risk associated with small firms. The risk associated with them is underestimated and they do not trade as frequently as the those of the large firms. Correct measurement of risk and return of small portfolios tends to eliminate at least 50% of the small firm effect.

The weekend effect French in his study had examined the returns generated by the Standard and poor Index for each day of the week. Stock prices tend to rise all week long to a peak on Fridays. The stocks are traded on Monday at reduced prices, before they begin the next week’s price rise. Buying on Monday and selling on Friday from 1953 to 1977 would have generated average annual return 3.4% while simple buy and hold would have yielded 5.5% annual return. If the transaction costs are taken into account, the naive buy and hold strategy would have provided higher return. Yet the knowledge of the weekend effect is still of v Purchases planned on Thursday or Friday can be delayed until Monday, while sale planned for Monday can b delayed until the end of the week. The weekend effect is a small but significant deviation from perfectly random price movements and violates the weekly efficient market hypothesis.

Similar to this Venkatesh B. of the BL Research Bureau has stated that the Bombay Stock Exchange reveal a discernible pattern. Usually, Monday, is characterized by trading blues, and Friday by frenzied activity The Friday rush is more to do with speculators covering their open position. If the short sellers to cover their position within this period, their open positions are called to auction where prices are dear.

Summary

The technical analysts studies the behaviour of the price of the stock to determine the future price of the –stock

According to Charles H. Dow, stock price movements are divided into three: the primary movement, the secondary movement and the daily fluctuations.

A primary trend may be a bull market moving in a steady upward direction, or a bear market steadily dropping.

A secondary trend or secondary reaction is the movement of the market contrary to the primary trend.

Support level is the barrier for further decline. It provides a base for an up move. The resistance level is the level in which advances are temporarily stopped and the sellers overcome the demand.

Volume of the trade confirms the trend. Fall of volume with the rise in price indicates trend reversal and vice-versa.

Breadth of the market is the net number of stocks advancing versus, those declining in the market. If the Al D line slopes downward while the Sensex is rising, it gives a bearish signal and vice-versa.

Moving averages are used as a technical indicator. It smoothens out the short term fluctuations, helpful in comparing the stock price movement with the index movement and discovering the trend.