A financial market is a market for creation and exchange of financial assets. If you buy or sell financial assets, you will participate in financial markets in some way or the other. Economists define a market as an institution or arrangement that facilitates the purchase and sale of goods, services and other things. A Financial Market is an institution or arrangement that facilitates the exchange of financial assets, including deposits and loans, corporate stocks and bonds, government bonds and more exotic instrument such as option and futures contracts. This market may or may not have a precise physical location. There several ways to classify financial markets. One obvious method is to classify markets by the type of asset traded, e.g. short-term assets. The broadest way to categorize markets is to distinguish between primary and secondary markets. We can classify financial markets according to the nature of the instruments traded. This classification consists of debt, equity and financial services markets.
Function of Financial Markets
Financial markets play a pivotal role in allocating resources in an economy by performing three important functions:
Ø Financial market facilitate price discovery. The continual interaction among numerous buyers and sellers who throng financial markets help in establishing the prices of financial assets. Well-organized financial markets seem to be remarkably efficient in price discovery.
Ø Financial markets provide liquidity to the financial assets. Investors can readily sell their financial assets through the mechanism of financial markets. In the absence of financial markets which provide such liquidity, the motivation of investors to hold financial assets will be considerably diminished. Thanks to negotiability and transferability of securities through the financial markets, it is possible for companies (and other entities) to raise long-term funds from investors with short-term and medium-term horizons.
Ø Financial markets considerably reduce the cost of transacting. The two major costs associated with transacting are search costs and information costs. Search costs comprise explicit costs such as the expenses incurred on advertising when one wants to buy or sell an asset and implicit costs such as the efforts and time one has to put in to locate a customer. Information costs refer to costs incurred in evaluating the investment merits of financial assets.
“Our capital markets have been on a roller coaster ride since the nineties, with no reason being troughs. The companies and intermediaries have been exploiting the weakness and loopholes of the system at the cost of the small investor. The investor for whom the primary market was once a happy hunting ground for speculation has moved away realizing that the primary market is no more risk-free investment. Does this mean that curtains are down on the primary market? No, we have to take lesson from other countries to plug the inadequacies in our market by making it more streamlined and transparent.” We can define financial market with the help of its financial institutions. These institutions are:
- Commercial Banks
- Mutual saving Banks
- Mutual Funds
- Credit Unions
- Depository Institutions
- Saving and Loan Association
- Non Depository Institutions
- Pension Funds
Commercial banks ordinarily are simple business concerns which provide various types of financial services to customers in return for payments in one form or another, such as interest, discounts, fees, commission, and so on. Their objective is to make profits.
Mutual Saving Banks
Mutual saving banks are much like saving and loans, but are owned cooperatively by members with a common interest, union members or congregation members. Originally they accepted deposits and made mortgage loans.
Investment companies or investment trusts obtain funds from large number of investors through sale of units. The funds collected from the investors are placed under professional management for the benefit of the investors. A mutual fund represents a vehicle for collective investment. When you participate in a scheme of mutual fund, you become a part-owner of the investment held under the scheme.
Credit unions are organized as cooperative depository institutions, much like mutual saving banks. Depositors are credited with purchasing shares in the cooperative, which they own and operate. Like saving and loans, credit unions were originally restricted by law to accepting saving deposits and making consumer loans.
Depository Institutions are those institutions which accept the funds from the individuals and firms and use these funds to participate in the debt market, making loans or purchase other debt instruments such as treasury bills.
Saving And Loan Associations
Saving and loan associations were originally designed as mutual associations, (i.e., owned by depositors) to convert funds from saving accounts into mortgage loans. The purpose was to ensure a market for financing housing loans.
Non Depository Institutions
In contrast to depository institutions, non-depository institutions do not accept check able deposits. With one exception that will be noted shortly, you cannot simply write a “check” to withdraw funds from a non-depository institution. Non depository institutions serve various functions in financial markets, ranging from financial intermediation to selling insurance against risk.
The setting up of the first investment-based pension fund proposed by the UTI was approved by the government in October 1994. This retirement benefit plan is meant to enable self-employed people to contribute to a pension fund so as to provide security in their old age.
Classification Of The Financial Market
The market for long term securities like bonds, equity stocks and preferred stocks and preferred stocks is divided into primary market and secondary market. The primary market deals with the new issues of securities. Outstanding securities are traded in the secondary market, which is commonly known as stock market or stock exchange. In the secondary market, the investors can sell and buy securities. Stock markets predominantly deal in the equity shares. Debt instruments like bonds and debentures are also traded in the stock market. Growth of primary market depends on the secondary market. The health of the economy is reflected by the growth of the stock market.
Stocks available for the first time are offered through new issue market. The issuer may be a new company or an existing company. These issues may be of new type or the security used in the past. In the new issue market the issuer can be considered as a manufacturer. The issuing houses, investment bankers and brokers act as the channel of distribution for the issues. They take the responsibility of selling the stocks to the public. The New Issue Market/Primary Market deals with the new securities, which were not previously trade able to the investing public. The market thus derives its name from the fact that it makes available new securities for public subscription. In other words, a New Issue Market deal with rising of fresh capital either for cash or for consideration other than cash by companies and encompasses all institutions dealing in the issue of fresh debt. The form in which this debt is incurred are equity shares, preference shares, debentures, time deposits, bonds, miscellaneous loan etc. of both public and private companies. All the financial institutions in the capital market that contribute, underwrite or directly subscribe are part of New Issue Market. When the new companies make new issues, they are known as “Initial Issues” where as issue made by existing companies are known as “Further Issues”. Initial capital can be received by issuing only ordinary preference shares while debentures can also be issued for raising further capital. The proportion in which funds are raised in various forms as equity capital and debt indicate the capital structure of the company.
Secondary market is mainly concerned with the buying and selling of existing industrial securities like equity shares, preference shares, debentures and bonds of listed public limited companies and government securities. A well- developed securities market is characterized by liquidity, price continuity, safeguard the interest of the investors, evaluation of securities etc. thus to meet the different characteristics of the companies and objectives of the investors, the multitier structure exists in secondary market which is as follows:
Trading in listed companies on the floor of stock exchange with the help of brokers and dealers.
Trading over the counter on the OTC issues.
Trading in listed companies, not on the floor of stock exchange with the help of brokers and dealers.
Trading in listed companies, not on the floor of stock exchange, without the help of brokers and dealers. It is a direct deal in buyers and sellers.
Stock exchanges play a very important role in secondary market. India has now the largest number of organized and recognized stock exchanges in the world. All of them are regulated by the SEBI. They are organized wither as voluntary, non-profit making associations, public limited companies or company limited by guarantee.
The origin of the stock market in India goes back to the end of the eighteenth century when long-term negotiable securities were first issued. However, for all practical purposes, the real beginning occurred in the middle of the nineteenth century after the enactment of the Companies Act in 1850, which introduced the feature of limited liability and generated investor interest in corporate securities. As of January 2002 there were 23 stock exchanges to seek governmental recognition.
Significance Of The Study
A capital market is a market for long term financial assets i.e. the share and the debentures. These securities are regularly transected i.e. sold and purchased at the prevailing price which is suppose to reflect all the information relating to the issuing company. The efficiency of a capital market is often defined in terms of its ability to reflect the impact of all relevant information in the prices of the securities quickly adjust to new information and reflect it in the market prices of the securities. To understand why good financial decisions are reflected in positive share price adjustments, as well as how securities are valued or priced in the market, it is necessary to have an understanding of the concept of efficient markets. Whatever decisions a financial manager takes will affect the market price of the shares. If the capital market is efficient, it will truly and immediately reflect the effect. Moreover, the financial manager then take decision to maximize the net present value of the decision or to wealth of the shareholders.
Focus Of The Study
The study is focused to test market efficiency specific investment strategies are examined to see whether they earn excess return. Since excess return represent the difference between the actual retrun and the expected return, implicit in a test of market efficiency is some model of the expected return. The expected may be based on the capital asset pricing model or the arbitrage pricing model or some other model. Hence, a test of market efficiency is really a joint test of market efficiency and the model used for expected returns. If threw is evidence of excess return, it may mean that the market is inefficient or that the model used to calculate the expected return is wrong or both. This seems to be an insoluble problem. However, if the results of a study do not vary with different models of expected return one can argue that the results can be attributed to market inefficiency and not model misspecification.
Objectives Of The Study
Every research work has its own objectives. Without objective there is no benefit of doing a research. So the main objective of this study is the empirical test of the semi-strong form of market efficiency. There are some other sub objectives of this study, which are helpful in achieving the main objective:
ü To check the semi-strong form of market efficiency according to the announcement made by the company.
ü To check the semi-strong form of market efficiency according to the size of the company.
ü To check the semi-strong form of market efficiency according to the share price fluctuation of the company when the announcement is made.
Review Of Exisiting Literature
Review Of Literature
Review of related literature is very important before doing any research because it gives the guidance to the researcher for that particular field. It also gives information about the work already done in this field. Three type of informational efficiency (weak, semi-strong and strong) have been well identified by researcher in the field of capital markets throughout the world.
Weak efficiency states that current prices fully reflect all the information contained in the history of past prices and denies the utility of charting and technical analysis. This issue has been researched in India over a long period and the overwhelming preponderance of evidence, for example, Barua (1980,1987); Sharma (1983); Ramachandran (1985); Sharma and Kennedy (1977); Gupta (1985) is in favour of weak form efficiency. There have been only a few studies (Kulkarni (1978) and Chaudhury (1991a,b,c)) which did not support the weak efficiency hypothesis.
In the light of the above evidence, the results of Bhat and Pandey (1987) appear paradoxical. On the basis of a questionnaire survey, they conclude that the users and preparers of accounting information in India do not believe that the market is efficient in any of its three forms.
Bhat (1988a) studies the relationship between the regional market indices in the Indian stock market over the period 1971-85 using monthly data. He finds that the regional price indicators respond immediately to the all India index, but cautions that his study is not adequate to conclude the existence of an integrated national market.
Semi-strong form of efficiency deals with the speed with which publicly available information is assimilated by the market and incorporated in market prices. The evidence on this issue is mixed.
Subramaniam (1989) found that in the case of political events, the market appeared to respond more efficiently to events whose impact on share values was characterized by low complexity and high clarity. The market seemed to have difficulty with ambiguous and complex events. Ramachandran (1985) and Srinivasan (1988) found that the market was by and large efficient in responding to the information content of bonus issues and rights issues respectively.
A closely related question is the extent to which share prices reflect (publicly known) fundamentals. Dixit (1986) shows that dividend is the most important determinant of share prices. This is consistent with standard theories of fundamental value. However, Barua and Raghunathan (1990a), Sundaram (1991) and Obaidullah (1991), Sinha (1992) cast doubts on whether the observed price earning ratios are consistent with fundamental factors like dividend growth and payout ratios.
Barua and Raghunathan (1986) provide evidence of the systematic mispricing of convertible securities in violation of the risk return parity and argue that this represents an arbitrage opportunity. Though this paper provoked a heated debate on whether the arbitrage opportunity was really risk free, the mispricing of convertible securities remains an unexplained anomaly.
Regarding the behaviour of interest rates and fixed income securities, there is hardly any research yet. Interest rates have been progressively freed since 1991 but the transition to a total free market regime is likely to be complete only by the mid 1990's. The study by Nachane (1988) of the few interest rates that have historically been subject to some extent to market forces assume significance in the context. Nachane found that the market for lend able funds as reflected in the call market rate, bazaar bill rate and the SBI Hundi rate is inefficient. The Fisherine hypothesis that interest rates reflect anticipated inflation is also rejected.
The third form of market efficiency (strong form) assert that even inside information which is not publicly available is reflected in market prices very rapidly. This hypothesis is usually tested by evaluating the performance of mutual funds whose managers can be expected to have some degree of inside information.
In the present study “Review of Literature” has been classified into three categories i.e. literature related to weak form of market-efficiency, semi-strong form of market-efficiency and strong form of market-efficiency.
1. O.P. Gupta (1985) worked on the Weak form of efficient market hypothesis. The author want to test the hypothesis that share price movement over the short periods, such as a day, or a week or month are independent of each other. He used weekend closing prices of 39 shares listed on the four principal stock exchanges viz., Bombay, Calcutta, Delhi and Ahemdabad for the period January1971 to March 1976. the data was adjusted for bonus and right issues. In the study, the random walk hypothesis has been tested by means of (1) parametric test for independence and (2) non-parametric test for randomness. The period of the study has been divided into two groups (a) “Pre-Dividend Restriction period” and (b) “Post-Dividend Restriction period”. In the study, the serial correlations tests indicate that the behaviour of individual share prices mostly confirm the applicability, of random walk model for both the periods. In some cases, the first order serial correlation coefficients were significantly different from zero. Square values are small, and one cannot reject the null hypothesis that the price changes are independent and the probability of rise or fall in prices is equal. In the study the spectral densities are estimated for two sets of series: (1) the raw series of the three stock indexes and (2) first different of log indexes of BSE, LSE and NYSE. In the study it was found the spectrum of the log first difference for all the three stock indexes also flat. The spectrum shows power both at low frequencies and at as relatively high frequencies, at periods 18 months, at 3.3 months, and 2.5 months. Otherwise, the spectrum as a whole is flat, confirming the random walk hypothesis. Based on two tests, author found that stocks on the Bombay Stock Exchange obey a random walk and are equivalent in this sense to the behaviour of stock prices in the markets of advanced industrialized countries.
2. N.S. Malik (2000) studied on weak form of market efficiency to test the validity of the random walk hypothesis or the weak form of the efficient market hypothesis in the Indian Capital Market over a very short period of time i.e. a day to explore the levels of the weak form of market efficiency in the specified (group A) and non-specified (cash) groups of shares separately. The study was based on the data of 133 companies consisting 48 companies from the specified group and 85 companies from the non-specified group. The period of the study was April 1996 to March 1997. In the study two kinds of tests have been used. These are parametric test ( by means of serial correlation analysis) for independence and non-parametric test 9by means of runs analysis) for randomness. Serial correlation coefficient have been computed for each of the price series for lags extending from 1 to 15, where as in the runs analysis test, sums of the consecutive price changes of the same sign have been analyzed. In the study, it has been found that the results of price changes don't display serial dependence in the majority of cases but some first order dependence has been reflected by the results of price changes. But the number of significant coefficient is not adequate to suggest the prediction of future price behaviour on the basis of past price data. On a comparative basis, it is observed that the tendency of dependence is more in the case of the non-specified (7.4 per cent) than in the specified (6 per cent) group of share. The results of ‘runs analysis test' reflects non-randomness in some cases on the basis of daily price changes, but these are not generally in agreement with the serial correlation results analyzed earlier. The results of the runs tests conducted on the daily price changes of companies from the specified group reveal some tendency for non-randomness in the behaviour of some of the daily price data which reflect some deviation from the random walk hypothesis but in case of non-specified groups the figure is quite large, yet the degree of non-randomness is too negligible to predict likely price changes on a day-to-day basis. In s nutshell it can be concluded that the runs test generally follows the random walk model or the successive price changes are random in the respect of most of the series. Taking an overall view on the basis of “Serial Correlation Test” and “Runs Analysis Test”. It can be concluded that share prices in general follow a random behaviour in Indian and are is a weak form of efficiency.
3. R.K. Mittal (1994) studied on the “Stock Market Anomalies: The Day-of-the Week Effect in Stock Returns” with the help of the daily closing prices if the BSE National Index for the period January, 1990 to February, 1993 are used to calculated daily returns to investigate the day of the week effect and for the period January 1991 to February, 1993 the examine the behaviour of trading and non-trading period returns. The data have been collected from Official Stock Exchange Directory, Bombay. Daily close-to close returns are computed as the natural logarithm of the ratio of successive closing index. In the study, non-parametric kruskal-wallis test have been use. In the study, it has been found that Tuesday not only had the most negative mean return but also has been found that standard deviation. Friday has the highest mean return and the lowest standard deviation. The computed value of H (8.164) is higher than its critical value (7.779) at 10% level of significance so it rejects the hypothesis of equal mean return across all weekdays. This asymmetry in the distribution of the daily stock returns in further confirmed by the degree of skew ness and kurtosis. In the study it has been found that Wednesday have the highest degree of skew ness and kurtosis while Friday reveals the lowest degree of kurtosis. The author concludes that the day of the week effects exist in Indian Market Tuesday has the most negative return. Tuesday effect is actually a non-trading period in characterized mostly by negative returns, close-to-open and open-to-close returns are also not normally distributed across all the weekdays. A trading strategy of postponing already planned purchases for Thursday or Friday to Tuesday non-trading period and sales panned for Tuesday to Friday afternoon may be of immense value to increased expected returns.
4. S Amanulla and B Kamiah (1998) studied on the weak form of market efficiency with the help of monthly data of 53 selected stocks. The random walk model, which forms a special case of ARIMA, has been used in the study. In the study it has been found that the null hypothesis of no autocorrelation is accepted in 40 out of 55 cases at 5% level of significance implying that corresponding price series follow random walk. A random walk in stock prices indices of BSE sensitive and national indices in also observed however, the presence of auto correlation is found in 15 individual securities with Q value ranging 40.2327 in Indian Hotels to 19.7457 in Bajaj Auto. On the basis of lagged prices it has been found that except 4 cases, the F-statistics proves that past prices are not helpful in predicting current price. But the results from Q-statistics provide evidence of autocorrelation in 23, 18, 18 and 17 cases at lags 3, 6, 9 and 12 respectively. It has also been found that the BSE national index is efficient at all lags. The author concludes that the results by and large reveal that the Indian stock market in informationally efficient in weak form.
5. Pardeep Gupta (2001) studied on the market efficiency to examine the semi-strong form at efficient market hypothesis with the help of selected accounting variables and selected macro-economic variables. In the study yearly time series data has been used. The period of the study was from 1986-95, on an yearly basis for accounting variables of the 41 companies listed in the forward list of Bombay Stock Exchange, the period for macro-economic variables was from 1991-95 and short term data has been collected of six months. In concerned with accounting variables it has been found that the dividend per share was positively and significantly related to the market share prices, return on equity did not show a significant influence, the growth in price-earning ratio showed little evidence and growth in earning per share and leverage had negligible influence in explaining the share prices. On the basis of macro-economic variables. It has been observed that consumer price Index is most significant in explaining the share prices followed by gross national product at market price, export-related nominal effective exchange rate showed a reasonable influence on the dependent variables, money supply and index of industrial production did not prove to be an important factor in explain the share prices and GNP at factor cost did not turn out to be a satisfactory explanation for share price movement.
6. Ball and Brown conducted another test in this area by analyzing the stock market's ability to absorb the information content of reported annual earnings per share information. In their study the authors examined stock price movements of companies that experienced “good” earning reports as opposed to the stock price movements of companies that experienced “bad” earning reports. A “good” earning report was a reported earning per share figure that was higher than the preciously forecast earnings per share, and conversely a “bad” earnings report was a reported earnings per share figure that was lower than had been forecast previously. They found that those companies with “good” earnings reports experienced price increases in their stock and those with “bad” earnings report experienced stock price declines. The interesting result was that about 85 percent of the informational content of the annual earnings announcement was reflected in stock price movements prior to the release of the actual annual earnings figure.
7. S.Basu (19977) tested for the informational content of the price-earning multiple. He tested to see whether low P/E stocks tended to outperform stocks with high P/E ratios. If historical P/E ratios provided useful information to investors in obtaining superior stock market returns, this would be a refutation of the semi strong form of the efficient market hypothesis. Because if historical publicly available P/E information led an investor to buy a particular type of stock and this in turn led to abnormal returns, this would be a direct contradiction of the semi strong form. His results indicated that the low P/E portfolios experienced superior returns relative to the market and high P/E portfolios performed in an inferior manner relative to the overall market.
An efficient market is one in which the market price of a security is an unbiased estimate of its intrinsic value. Note that market efficiency does not imply that the market price equals intrinsic value at every point in time. All that it says is that the errors in the market prices are unbiased. This means that the price can deviate from the intrinsic value but the deviations are random and uncorrelated with any observable variable. If the deviations of market from intrinsic value are random, it is not possible to consistently identify over or under-valued securities.
Market efficiency is defined in relation to information that is reflected in security prices. Richard Roll adds his own nuance. He says: “In an efficient financial market costless trading policies will not generate ‘excess returns'. This is often thought to imply something about the amount of ‘information' reflected in asset prices. However, it really doesn't mean that prices reflect all information nor even that they reflect publicly available information. Instead, it means that the connection between unreflected information and prices is too subtle and tenuous to be easily or costless detected.”
Rational investors seek to maximize returns at a given level of risk. If a security is under price, investors will quickly identify it and rush to pick it up. Competition for the under priced security drives the price up. Hence it would be difficult to consistently achieve superior performance.
Most securities are correctly priced and it should be possible to earn a normal return by randomly choosing securities of a given risk level. Nation of financial market efficiency is in fact akin to the concept of profit in a perfectly competitive market. Abnormal or excess profits, in such a market are competed away. In an efficient market new information is discounted as it arrives. Price instantaneously adjusts to a new and correct level.
An investor cannot consistently earn abnormal profits, by undertaking fundamental analysis or by studying the behaviour of share prices with a view to discerning patterns. Eugene Fama suggested that it is useful to distinguish three level of market efficiency:
Forms Of Market Efficiency
There are 3 type of market efficiency 1. Weak form of efficiency 2. Semi-strong form of efficiency 3. Strong form of efficiency
1) Weak Form Of Efficeincy:
The weak form says that the current prices of stocks already fully reflect all the information that is contained in the historical sequence of prices. Therefore, there is no benefit as far as forecasting the future is concerned in examining the historical sequence of prices. According to it, current price reflect all information found in the prices and traded volumes. Future prices can not be predicted by analyzing the prices from the past. Everyone has the access to the past prices, even though some people can get these more conveniently than others. Liquidity traders may sell their stocks with out considering the intrinsic value of the shares and cause price fluctuations. Buying and selling activities of the information traders lead the market price to align with the intrinsic value. In the weak efficient market short term traders may earn a positive return. On an average, short term traders will not out perform the blind folded investor picking the stock with dart. That is traders may earn by the naïve buy and hold strategy while some may incur loss, the average buy and hold strategy can not be beaten to the chartist. Many studies of the market analysts have proved the weak form of the EMH.
Empirical Evidence On Weak-Form Efficient Market Hypothesis
The weak-form efficient 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 the past and future price movements.
Three types of tests have been commonly employed to empirically verify the weak-form efficient market hypothesis: (a) Serial Correlation Tests; (b) Runs Tests; and (c) Filter Rules Tests.
Serial Correlation Tests
One way to test for randomness in stock price changes is to look at their serial correlations (also called auto-correlations). 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. Numerous serial correlation studies, employing different stocks, different time-lags, and different time-periods, have been conducted to detect serial correlations. In general, these studies have failed to discover any significant serial correlations. Remember that these studies were concerned only with short-term trends (daily, weekly, fortnightly, and monthly, etc.) and not long-term trends in stock prices; we know that in the long-term stock prices tend to move upwards.
Given a series of stock price changes, each price change is designated as a plus (+) if it represents an increase or a minus (-) if it represents a decrease. The resulting series, for example, may look follows:
+ + - + + - - +
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 begin. 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. Many studies have been carried out, employing the ‘runs test' of independence. By and large, the results of these studies seem to strongly support the random walk model.
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 price decreases by at least n percent from a subsequent high. When the price decreases by at least n percent or more sell it.” If the behaviour of stock price changes is random, filter rules should not outperform a simple buy-and-hold strategy. Many studies have been conducted employing different stocks and different filter rules. By and large, they suggest that filter rules do not outperform a simple buy-and hold strategy, particularly after considering the commissions on transactions.
2) Semi-Strong Form Of 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 publically availableknowledge about the corporations being studied. Furthermore, the semi strong form says that efforts by analysts and investors to acquire and analyze public information will not yield consistently superior returns to the analyst.
In effect, the semi strong form of the efficient market hypothesis maintains that as soon as information becomes publicly available, it is absorbed and reflected in stock prices. Even if this adjustment is not the correct on e immediately, it will in a very short time be properly analyzed by the market. Thus the analyst would have great difficulty trying to profit using fundamental analysis. Furthermore, even while the correct adjustment is taking place, the analyst cannot obtain consistent superior returns. Why? Because the incorrect adjustments will not take place consistently; that is, sometimes the adjustments will over adjustments and some-times they will be under adjustments. Therefore, an analyst will not be able to develop a trading strategy based on these quick adjustments to new publicly available information.
Empirical Evidence On Semi Strong Form Efficient Market Hypothesis:
To test market efficiency specific investment strategies are examined to see whether they earn excess return. Since excess return represents the difference between the actual return and expected return, implicit in a test of market efficiency is some model of the expected return. The expected return may be based on the capital asset pricing model or the arbitrage pricing model or some other model.
To test market efficiency, empirical studies have been conducted that have examined the following questions:
Ø Is it possible to earn superior risk-adjusted returns by trading on information events like earning announcements, stock splits, bonus issues, or acquisition usually tested with an “event study”.
Ø Is it possible to earn superior risk-adjusted returns by trading on an observable characteristic of a firm like price-earning ratio, price-book value ratio, or dividend yield? A scheme based upon trading on an observable characteristic is tested using a “portfolio study”.
An event study examines the market reaction to and the excess market returns around a specific information event like acquisition announcement or stock split. The key steps involved in an event study are as follows:
1. Identify the event to be studied and pinpoint the date on which the event was announced Event studies presume that the timing of the event can be specified with a fair degree of precision. Because financial markets react to the announcement of an event, rather than the event itself, event studies focus on the announcement date of the event.
2.Collect returns data around the announcement date In this context two issues have to be resolved: What should be the period for calculating returns---weekly, daily, or some other interval? For how many periods should returns be calculated before and after the announcement date?
3.Calculate the excess returns, by period, around the announcement date for each firm in the sample The excess return is calculated by making adjustment for market performance and risk.
4.Compute the average and the standard error of excess returns across all firms The standard error of the excess return is standard deviation of the sample average.
5. Assess whether the excess returns around the announcement date are different from zero To determine whether the excess returns around the announcement date are different from zero, estimate the T statistic for each day:
T statistic for excess return on day t = average excess return/standard error
Statistically significant T statistics imply that the event has a bearing on returns; the sign of the excess return indicates whether the effect is positive or negative.
In portfolio study, a portfolio of stocks having the observable characteristic (low price-earning ratio or whatever) is created and tracked over time see whether it earns superior risk-adjusted returns. The basic steps involved in a portfolio study are as follows:
1.Define the variable (characteristic) on which firms will be classified The proposed investment strategy spells out the relevant variable. Note that the variable must be observable, but not necessarily numerical. Example: price-earning ratio, company size, price-book value ratio, bond ratings, and so on.
2.Classify firms into portfolios based upon the magnitude of the variable Collect data on the variable for every firm in the defined universe at the beginning of the period and use that information for classifying firms into different portfolios. For example, if the price-earnings ratio is the screening variable, classify firms on the basis of the price-earnings ratio into portfolios from the lowest price-earnings class to the highest price-earnings class. The size of the universe will determine the number of classes.
3.Compute the returns for each portfolio Collect information on the returns for each firm in each portfolio for the testing period and calculate the return for each portfolio, assuming that the stocks included in the portfolio are equally weighted.
4.Calculate the excess returns for each portfolio The risk-return model commonly employed for calculating the excess returns is the capital asset pricing model. So the calculation of excess returns earned by a portfolio calls for estimating the portfolio beta and determining the excess returns:
E Rjt = Rjt - Beta j X RMt
Where E Rjt = excess returns earned by portfolio in period t
Rjt = returns earned by portfolio j in period t
Beta j = beta of portfolio j
RMt = returns earned by the market portfolio in period t
Note that the beta of a portfolio is estimated by taking the average of the betas of the individuals stocks in the portfolio or by regressing the returns on the portfolio against market returns over some prior time period (for example, the year before the testing period).
5.Assess whether the average excess returns are different across the portfolios Several statistical tests are available to test whether the average excess returns differ across these portfolios. Some of these tests are parametric and some nonparametric.
3. Strong Form Of Efficiency
To review briefly, we have seen that the weak form of the efficient-market hypothesis maintains that past prices and past price changes cannot be used to forecast future price changes and future prices. We will review many of the tests that have been conducted to test the weak form of the efficient market hypothesis. We have examined the semi strong form of the efficient market hypothesis, which says that publicly available information cannot be used to earn consistently superior investment returns. Several studies that tend to support the semi strong theory of the efficient-market hypothesis were cited. Finally, the strong form of the efficient market hypothesis maintains that not only is publicly available information useless to the investor or analyst but all information is useless. Specifically, no information that is available, be it public or an”inside,” can be used to earn consistently superior investment returns.
The semi strong form of the efficient market hypothesis could only be tested indirectly-namely, by testing what happened to prices on days surrounding announcements of various types, such as earnings announcements dividend announcements, and stock-split announcements. To test the strong form of efficient market hypothesis, even more indirect methods must be used. For the strong form, as has already been mentioned, says that no type of information is useful. This implies that not even security analysts and portfolio managers who have access to information more quickly than the general investing public are able to use this information to earn superior returns. Therefore, many of the tests of the strong form of the efficient market hypothesis deal with tests of mutual-fund performance.
Empirical Evidence On The Strong-Form Efficient Market Hypothesis:
The strong-form efficient market hypothesis holds that all available information, public or private, is reflected in the stock prices. Obviously, this represents an extreme hypothesis and we would be surprised if it were true.
To test the strong-form efficient market hypothesis, researchers analyzed the returns earned by certain groups who have access to information which is not publicly available and/or ostensibly possess greater resources and abilities to intensively analyze information which is in the public domain.
Ø 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 rates of return, after adjustment for risk.
Ø Mutual fund managers do not, on an average, earn a superior rate of return. As Malkiel put it: “No scientific evidence has yet been assembled to indicate that the investment performance of professionally managed portfolios as a group has been any better than that of randomly selected portfolios.”
This research is conducted on the basis of empirical research. And the empirical research relies on the observation alone often without due regard for system and theory. This is data based research in it we use different type of tools for analysis, coming up with conclusions, which are verified by the observation.
This study is based on the closing share prices data of 30 companies which are included in Bombay Stock Exchange as on January 2003. the name of these companies are as follows:
1 Reliance Industries 2 Infosys Technologies
3 HLL 4 ITC
5 ICICI 6 Ranbaxy Laborataries
7 HDFC 8 SBI
9 Tata Steel 10 L&T
11 Hindalco Industries 12 Satyam Computers
13 Tata Motors 14 HDFC Bank
15 DR Reddy Labs 16 wipro
17 Bajaj auto 18 Grasim Industries
19 HPCL 20 ONGC
21 Cipla 22 Tata Power
23 BHEL 24 Hero Honda Motors
25 ACC 26 MTNL
27 Bharti Tele Venture 28 Gujarat Ambuja Cement
29 Zee Telefilms 30 BSES (reliance energy)
Collection Of Data
There are two type of data which are used by the researcher in the research. These two types are as follows:
Ø Primary Data
Ø Secondary Data
Primary data is that raw data which is collected by the researcher for very first time for the research purpose. This data is first time collected from the different source of data. This data are in raw form and then it is tabulated according to the research requirement and after that it is used for the research purpose.
Secondary data is that data which is already collected for any other research and the objective of collecting the data is different for the purpose of our research that's why it is necessary to made required changes in that according to the requirement of our research work and then it is used for research work .
There are many ways of the collecting the data about the closing share prices. This study is based on the secondary data, which will be collected from the different Newspapers, websites and magazines.
Ø After collection, the raw data will be processed through editing, loading, classification and tabulation to make the data in analytical form.
Ø For the analysis of data we choose some selected announcements made by the company within the span of one year and the we choose the data of 10 days before and after of the date of announcement. Then we took the data of past 20 days from the bse sensex and the find the value of Beta by using the formula
Ø After finding the value of Beta we find the expected return and excess return and finding the standard deviation of that excess return and then find out the (exc ret/std) and then check the value of significance with the help of test of significance at the level of 95% and 99%.
Ø After this analysis the findings will be drawn from the study which is written in the next part of the study.