ANJALI-07XQCM6007

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A DISSERTATION REPORT ON

“EFFICIENT MARKET HYPOTHESIS IN THE

INDIAN SCENARIO”

Submitted in partial fulfilment of requirement for the award of the degree of

Master of Business Administration of Bangalore University

BY

Ms. ANJALI. S

(Reg no. 07XQCM6007)

Under the guidance and supervision of

Prof. M. Praveen Bhagawan

M.P.BIRLA INSTITUTE OF MANAGEMENT

(Associate Bharatiya Vidya Bhavan)

#43.RACE COURSE ROAD, BANGALORE 560001

2007 09

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DECLARATION

I hereby declare that this report titled “Efficient Market Hypothesis In The IndianScenario” is a record of independent work carried out by me under the guidance and

supervision of Mr. Praveen Bhagwan, Project Guide, MPBIM-BVB towards the

partial fulfilment of requirements for the M.B.A. degree course of Bangalore

University at M.P. Birla Institute of Management.

I further declare that this Project is the result of my own efforts and that it has not

been submitted to any other university or institute for the award of a degree or

diploma or any other similar title of recognition.

PLACE: Bangalore ANJALI S

DATE:

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PRINCIPAL’S CERTIFICATE

This is to certify that this report titled “Efficient Market Hypothesis In The Indian

Scenario” has been prepared by Ms. Anjali.S, bearing the registration No.07XQCM6007, under the guidance and supervision of Mr. M. Praveen Bhagwan,

Professor, M P Birla Institute of Management.

Place : Bangalore Dr. N. S. Malavalli

Date : (Principal)

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GUIDE’S CERTIFICATE

This is to certify that the Dissertation Project Report entitled “Efficient

Market Hypothesis In The Indian Scenario”, done by Anjali. S (Reg No.07XQCM6007) is a bona fide work done carried under my guidance during the

academic year 2007-09 in a partial fulfilment of the requirement for the award of

MBA degree by Bangalore University. To the best of my knowledge this report has

not formed the basis for the award of any other degree.

Signature Signature

Anjali S Prof. M. Praveen Bhagwan

(MBA STUDENT) (GUIDE)

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ACKNOWLEDGEMENTS

Any successful work is always a product of many hands coming together in co-

operation and assistance. This work is no different. A number of people are

responsible for accomplishment of this work. Their guidance and suggestions were

highly helpful during the course.

I express my deep sense of gratitude to Prof. M. Praveen Bhagwan, my project

guide, M. P. Birla Institute of Management (MPBIM), Associate Bharatiya Vidya

Bhavan, Bangalore, for his most valuable guidance, inspiring supervision, periodical

monitoring and sparing his precious time in my dissertation project.

I also express my sincere gratitude to my friends for all the inspirations and giving

me an opportunity to carry out the project report. Without their help, the project

report would not have been possible.

ANJALI. S

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Table of Contents

i. Declaration

ii. Principal’s Certificate

iii. Guide’s Certificate

iv. Acknowledgement

No. Chapter Page No.

Executive Summary 1

1) Background of the study 2

1. Introduction 3

2. Forms of hypothesis 4

3. Assumptions of EMH concept 5

4. Criticisms of EMH concept 6

5. Evidence against EMH 9

Review of Literature 11

6. For weak form hypothesis 12

7. For semi-strong form hypothesis 13

8. For strong form hypothesis 14

2) Research Design 16

1. Statement of problem 17

2. Objectives of the study 173. Hypothesis 17

4. Sampling technique 18

5. Data collection technique 18

6. Scope of the study 18

7. Statistical tests 19

8. Limitations of the study 19

9. Chapter Scheme 20

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3) Industry Profile 22

1. Banking and finance sector 24

2. Computer and IT sector 25

3. Engineering sector 264) Analysis and interpretation 27

1. Weak form hypothesis 28

1. Auto correlation 29

2. Run test 32

2. Semi-strong form hypothesis 36

1. Dividend declaration 38

2. Stock split 44

3. Strong form hypothesis 50

5) Findings, conclusion and recommendations 65

1. Findings 66

2. Conclusion 68

3. Recommendations 69

Bibliography 70

Annexure 71

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List of Tables

Sl No. Table name Page No.

1 Sample of Auto correlation 30

2 Compiled Auto correlation 31

3 Calculation of runs 33

4 Calculation of mean & standard deviation 34

5 Run-test values 356 Dividend declaration dates 39

7 T-test values for dividend declaration 43

8 Stock split announcement dates 45

9 T-test values for stock split 49

10 Annual returns of 35 mutual fund schemes 53

11 Sample of random portfolios 55

12 Average annual returns of random portfolios 56

13Comparative analysis of top 5 mutual fundschemes and top 5 random portfolios

58

14Comparative analysis of bottom 5 mutual fundschemes and bottom 5 random portfolios

58

15Comparison of mean returns, standarddeviation and co-efficient of variation

59

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List of Charts

Sl No. Chart name Page No.

1Share price movement 15 before and afterdeclaration of dividend

39-42

2Share price movement 15 before and afterannouncement of stock split

45-48

3 Annual returns of 35 mutual fund schemes 54

4Average annual returns of 30 random

portfolios57

5 Closing Market prices of ten companies 61-64

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EFFICIENT MARKET HYPOTHESIS IN INDIAN SCENARIO

1 M. P. BIRLA INSTITUTE OF MANAGEMENT

EXECUTIVE SUMMARY

The concept of EMH states that security prices reflect all information freely

available. This information can be either the historical stock prices or publicly availableinformation or even inside information related to the company. A very strong support for

the efficient market hypothesis comes from many finance experts. However, studies also

exist which question the EMH concept. This report aims at analysing whether the EMH

concept holds good in the Indian scenario. There are three forms of hypothesis, namely,

Weak form (wherein current prices of stocks are said to reflect all the information that is

contained in the historical sequence of prices), Semi strong form (wherein the current

market prices reflect all publicly available information about the corporations being studied)

and Strong form (wherein all information is discounted in the current stock prices).

There exists conflicting views with regard to the impact of all the information

available on the stock prices. Some are of the opinion that abnormal returns can be obtained

in the long run by analysing all kinds of information available while others argue it is not

possible. So this research article is being conducted “To check whether historical share

prices, publicly available information and inside information have an impact on the current

and future market prices of securities. In short, to check the validity of Efficient MarketHypothesis in the present Indian scenario”

The scope of this research is limited to companies listed on National Stock

Exchange. Ten companies have been selected as a sample on a convenience sampling

technique to test the weak and semi-strong form of hypothesis, whereas 215 companies and

35 mutual fund schemes have been taken as a sample for the purpose of testing strong form

of hypothesis. Data has been collected mainly from secondary sources such as websites and

journals for this purpose. The tests that have been conducted for the purpose of testing the

hypothesis are run test and Auto correlation test (in case of weak form hypothesis), T-test

(in case of semi-strong form hypothesis) and ANOVA(in case of strong form hypothesis).

After conducting all the tests, the results obtained revealed that markets in India are efficient

in the weak and semi-strong form but inefficient in the strong form. This concludes that

investors can earn superior returns in the long run only when they have access to insider

information. Abnormal returns cannot be earned by just having historical stock prices and

publicly available information (i.e. details regarding company fundamentals) as the market

discounts all such information as and when it occurs.

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Chapter 1

Theoretical

Background of thestudy

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1.1) Introduction

The EMH was developed by Professor Eugene Fama at the University Of

Chicago Booth School Of Business as an academic concept of study through hispublished Ph.D. thesis in the early 1960s at the same school. It was widely accepted

up until the 1990s, when behavioural finance economists became mainstream.

Empirical analysis have consistently found problems with the efficient markets

hypothesis, the most consistent being that stocks with low price to earnings (and

similarly, low price to cash-flow or book value) outperform other stocks. Alternative

theories have proposed that cognitive biases cause these inefficiencies, leading

investors to purchase overpriced growth stocks rather than value stocks. Although

the efficient markets hypothesis has become controversial because substantial and

lasting inefficiencies are observed, it remains a worthwhile starting point

In a market that is essentially characterized by a large number of rational and

profit seeking investors who compete with one another freely, the prices should

reflect all the available and expected information. An efficient market is one that

rapidly absorbs new information and adjusts the prices swiftly. Researchers and

analysts who have worked on the efficiency of stock market have realized that no

stock market is absolutely efficient.

This report deals with testing the validity of the Efficient Market Hypothesis

(EMH) in the present Indian market. The concept of EMH states that security prices

reflect all information freely available. This information can be either the historical

stock prices or publicly available information or even inside information related tothe company.

Markets are said to be efficient if the market value of shares are an unbiased

representation of their intrinsic values. Any deviation from the intrinsic value is said

to be purely random. So, according to the concept of EMH, it is not possible to earn

supernormal profits in the long-run as we cannot identify stocks which are

consistently over-valued or under-valued.

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To test for this, consistent upward or downward adjustments after the initial

change must be looked for. If there are any such adjustments it would suggest

that investors had interpreted the information in a biased fashion and hence in

an inefficient manner.

3. Strong form: In this type of market, all information is discounted in the

current stock prices. Thus, not only is any kind of analysis useless, even

insider information is useless for predicting future stock prices. Specifically,

no information that is available, be it public or inside, can be used to earn

consistently superior investment returns. To test for strong-form efficiency, a

market needs to exist where investors cannot consistently earn excess returns

over a long period of time. Even if some money managers are consistently

observed to beat the market, no refutation even of strong-form efficiency

follows: with hundreds of thousands of fund managers worldwide, even a

normal distribution of returns (as efficiency predicts) should be expected to

produce a few dozen "star" performers.

1.3) Assumptions of Efficient Market Hypothesis:

• Investors are rational.

• Markets are rational.

• There are no taxes – or, more specifically, taxes play no part in financial

decision-making.

• There are no transaction costs.

• An investor is indifferent between a dollar in dividends and a dollar in capital

gains.

• A company (and its investors) are indifferent between a dollar of additional

debt and a dollar of additional equity

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1.4) Criticisms of Efficient Market Hypothesis:

Critics of EMH have produced a wide range of arguments, of which the

following is a summary:

The assumption that investors are rational and therefore value investments

rationally – that is, by calculating the net present values of future cash flows,

appropriately discounted for risk – is not supported by the evidence, which shows

rather that investors are affected by:

• Herd instinct

• A tendency to ‘churn’ their portfolios

• A tendency to under-react or over-react to news

• Asymmetrical judgements about the causes of previous profits and losses.

Furthermore, many alleged anomalies have been detected in patterns of

historical share prices. The best known of these are the ‘small firm’ effect, the

January effect and the mean reversion.

Now let us see what are the criticisms put across by various financial

experts throughout the globe with respect to each form of market:

Weak-form EMH

In its weak form the EMH confines itself to just one subset of public

information, namely historical information about the share price itself. The argument

runs as follows. ‘New’ information must by definition be unrelated to previous

information; otherwise it would not be new. It follows from this that every

movement in the share price in response to new information cannot be predicted

from the last movement or price, and the development of the price assumes the

characteristics of the random walk. In other words, the future price cannot be

predicted from a study of historic prices.

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Semi-strong-form EMH

In a slightly less rigorous form, the EMH says a market is efficient if all

relevant publicly available information is quickly reflected in the market price. This

is called the semi-strong form of the EMH. If the strong form is theoretically the

most compelling, then the semi-strong form perhaps appeals most to our common

sense. It says that the market will quickly digest the publication of relevant new

information by moving the price to a new equilibrium level that reflects the change

in supply and demand caused by the emergence of that information. What it maylack in intellectual rigour, the semi-strong form of EMH certainly gains in empirical

strength, as it is less difficult to test than the strong form.

One problem with the semi-strong form lies with the identification of

‘relevant publicly available information’. Neat as the phrase might sound, the reality

is less clear-cut, because information does not arrive with a convenient label saying

which shares it does and does not affect. Does the definition of ‘new information’

include ‘making a connection for the first time’ between two pieces of already

available public information?

Strong-form EMH

In its strongest form, the EMH says a market is efficient if all information

relevant to the value of a share, whether or not generally available to existing or

potential investors, is quickly and accurately reflected in the market price.

For example, if the current market price is lower than the value justified by

some piece of privately held information, the holders of that information will exploit

the pricing anomaly by buying the shares. They will continue doing so until this

excess demand for the shares has driven the price up to the level supported by their

private information. At this point they will have no incentive to continue buying, so

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they will withdraw from the market and the price will stabilise at this new

equilibrium level. This is called the strong form of the EMH.

It is the most satisfying and compelling form of EMH in a theoretical sense,but it suffers from one big drawback in practice. It is difficult to confirm empirically,

as the necessary research would be unlikely to win the cooperation of the relevant

section of the financial community – insider dealers.

Warren Buffett, one of the world's most successful investors, has made the

following comment regarding the EMH concept:

"I'd be a bum in the street with a tin cup if the markets were efficient."

This statement makes us think twice about the validity of Efficient Market

Hypothesis concept.

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1.5) Evidence Against EMH and Alternate Theories of Market

Behaviour:

The EMH became controversial especially after the detection of certain

anomalies in the capital markets. Some of the main anomalies that have been

identified are as follows:

A. The January Effect: Rozeff and Kinney (1976) were the first to document

evidence of higher mean returns in January as compared to other months. Using

NYSE stocks for the period 1904-1974, they find that the average return for the

month of January was 3.48 percent as compared to only 0.42 percent for the other

months

B. The Weekend Effect (or Monday Effect): French (1980) analyzes daily returns

of stocks for the period 1953-1977 and finds that there is a tendency for returns to be

negative on Mondays whereas they are positive on the other days of the week. He

notes that these negative returns are "caused only by the weekend effect and not by a

general closed-market effect". However, Steeley (2001) finds that the weekend effect

in the UK has disappeared in the 1990s.

C. Other Seasonal Effects: Lakonishok and Smidt (1988) show that US stock

returns are significantly higher at the turn of the month, defined as the last and first

three trading days of the month. Ariel (1987) shows that returns tend to be higher on

the last day of the month. They also provide evidence to show that returns are, on

average, higher the day before a holiday, than on other trading days. The latter paper

describes the pre-holiday effect as one of the oldest and most consistent of all

seasonal regularities.

D. Small Firm Effect: Banz (1981) published one of the earliest articles on the

'small-firm effect' which is also known as the 'size-effect'. His analysis of the 1936-

1975 period reveals that excess returns would have been earned by holding stocks of

low capitalization companies. Supporting evidence is provided by Reinganum (1981)

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who a report that the risk adjusted annual return of small firms was greater than 20

percent. If the market were efficient, one would expect the prices of stocks of these

companies to go up to a level where the risk adjusted returns to future investors

would be normal. But this did not happen.

E. P/E Ratio Effect: Sanjoy Basu (1977) shows that stocks of companies with low

P/E ratios earned a premium for investors during the period 1957-1971. An investor

who held the low P/E ratio portfolio earned higher returns than an investor who held

the entire sample of stocks. These results also contradict the EMH.

F. Value-Line Enigma: The Value-Line organization divides the firm into five

groups and ranks them according to their estimated performance based on publicly

available information. Over a five year period starting from 1965, returns to investors

correspond to the rankings given to firms. That is, higher ranking firms earned higher

returns. Several researchers (e.g. Stickel, 1985) find positive risk-adjusted abnormal

(above average) returns using value line rankings to form trading strategies, thus

challenging the EMH.

G. Over/Under Reaction of Stock Prices to Earnings Announcements: DeBondt

and Thaler (1985, 1987) present evidence that is consistent with stock prices

overreacting to current changes in earnings. They report positive (negative)

estimated abnormal stock returns for portfolios that previously generated inferior

(superior) stock price and earning performance. This could be construed as the prior

period stock price behaviour overreacting to earnings developments (Bernard, 1993).

Bernard provides evidence that is consistent with the initial reaction being too small,and being completed over a period of at least six months. Thus, the evidence

suggests that information is not impounded in prices instantaneously as the EMH

would predict.

H. Standard & Poor’s (S&P) Index effect: Harris and Gurel (1986) and Shleifer

(1986) find a surprising increase in share prices (up to 3 percent) on the

announcement of a stock's inclusion into the S&P 500 index. Since in an efficient

market only information should change prices, the positive stock price reaction

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appears to be contrary to the EMH because there is no new information about the

firm other than its inclusion in the index.

Review of Literature

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Review of Literature

“EMH is one of the most controversial and well-studied propositions in all the

social sciences. Even after three decades of research and literally thousands of

journal articles, economists have not yet reached a consensus about whether markets,

particularly financial markets, are efficient or not.” – Roll

A very strong support for the Efficient Market Hypothesis comes in a rather

dramatic summarization which states that any portfolio selected by a blindfolded

chimpanzee by throwing darts at the stock pages would do as well as the one chosen

by the experts (G.Malkiel, 1973).

Research articles

1.6) . Research on testing of Weak form efficiency:

Over the years an impressive literature has been developed describing

empirical tests on weak form hypothesis (random walk theory). This research has

been aimed at testing whether successive price changes are independent. Simulation

tests, Auto correlation test, run test and filter tests have been conducted for this

purpose. The result obtained from all the tests proved that the share prices

moved in a random fashion and there is no definite pattern that can be established.

Burton G. Malkiel, an economist professor at Princeton University and writer

of “ A Random Walk Down Wall Street”, performed a test where his students were

given a hypothetical stock that was initially worth fifty dollars. The closing stock

price for each day was determined by a coin flip. If the result was heads, the price

would close a half point higher, but if the result was tails, it would close a half point

lower. Thus, each time, the price had a fifty-fifty chance of closing higher or lowerthan the previous day. Cycles or trends were determined from the tests. Malkiel then

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took the results in a chart and graph form to a chartist, a person who “seeks to predict

future movements by seeking to interpret past patterns on the assumption that

‘history tends to repeat itself’”.

The chartist told Malkiel that they needed to immediately buy the stock.

When Malkiel told him it was based purely on flipping a coin, the chartist was very

unhappy. Malkiel argued that this indicates that the market and stocks could be just

as random as flipping a coin.

1.7) Research on testing of Semi strong form efficiency:

While there have been an overwhelming number of studies to test the weak

form of EMH, studies to test the strong form are not many. Because of problems in

getting the relevant data to test the strong form of EMH, studies in this area are

limited. Semi-strong form has also been tested but not as extensively as the weak

form. The semi strong form of EMH has been extensively researched in the US, the

UK, other European countries, and Australia. However, there are limited studies in

India. A number of studies have confirmed that markets are efficient in the

semi strong form. However, a large number of studies have also concluded that

markets are not efficient in the semi strong form.

A research was conducted with the objective of finding out whether

announcement of dividend by company has any considerable impact on the

movement of share price before, during and after the occurrence of the event.

A hypothesis was formulated to examine whether the dividends’

announcements has any impact on the stock market reaction.

Sources of data:

The Dividends announcements made by companies included in CNX NIFTY

during the year 2006 07 are considered. Daily adjusted market price data for the

sample stocks for 30 days before and 30 days after the board meeting date are taken.

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beginning and end of the financial year were collected for the specified period of

2003-04, 2004-05 and 2005-06.

After this random portfolios were conducted. The theory behind randomportfolios is that the prices of securities reflect all the available information;

whatever the price they are quoted at reflects their intrinsic worth. Hence, any share

is a “good” share. Thus 30 random portfolios, with 30 stocks in each portfolio, were

constructed using random function of Microsoft Excel application.

A hypothesis was for formulated for this purpose to check whether there is

any significant difference between the returns offered by mutual fund schemes

(managed by professionals and experts who have an access to inside information

about the companies) and an average passive investor (who does not have access to

inside information).

Findings of the study:

Based on the test conducted it was found that only 2 schemes out of 70 had a

rate of return that was higher than the lowest average rate of return of the randomportfolios. The lowest return offered by random portfolio was 71.1% while the best

performing mutual fund scheme, Magnum Global, generated a three year annualized

return of 75.66%. The second best scheme, Magnum Contra had a return of 73.19%.

However no fund exceeded the rate of return offered by the top random portfolio of

146%.

A conclusion was drawn that it is not possible to earn excess returns byconducting technical and fundamental analysis as the current market price discounts

all the information. The study thus concludes that passive investing in index based

stocks would yield a return comparable, if not higher, to the returns provided by

mutual funds.

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Chapter 2

Research Design

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Research Design

2.1) Statement of the problem

There exists conflicting views with regard to the impact of all the information

available on the stock prices. Some are of the opinion that abnormal returns can be

obtained in the long run by analysing all kinds of information available while others

argue it is not possible. Thus there exists a research gap. The research problem under

consideration is as follows:

“To check whether historical share prices, publicly available information and

inside information have an impact on the current and future market prices of

securities. In short, to check the validity of Efficient Market Hypothesis in the

present Indian scenario”

2.2) Research Objectives

• To determine whether historical share prices have an impact on current and

future market prices

• To determine the impact of publicly available information on share prices

• To analyse whether the availability of inside information helps in earning

higher return in the long run

• To check the validity of Random-walk theory in the Indian market

2.3) Hypothesis

• For Weak form:

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Ho- Historical and future share prices are independent

HA- Historical and future share prices are dependent

• For Semi strong form:

Ho - There is no significant difference between share prices before and after

announcement of information

HA - There is a significant difference between share prices before and after

announcement of information

•

For Strong form:Ho - Inside information has no impact on share prices

HA - Inside information has an impact on share prices

2.4) Sampling Design

• Sampling unit - Companies listed on National Stock exchange (NSE)

• Sampling size - 10 companies for weak and semi-strong form hypothesis,

215 companies and 35 mutual fund schemes for strong form hypothesis

• Sampling technique - Convenience technique

2.5) Data Collection

• Textbooks and journals

• Websites

2.6) Scope of the study

• This study is restricted to only those stocks which are listed in NSE.

• Time frame of the study is 2008-09

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• Sample size of 10 is considered for testing Weak form and Semi-strong form

of hypothesis and Sample size of 215 stock returns and 35 mutual funds are

considered for testing Strong form of hypothesis

2.7) Statistical tools

• Auto correlation test: These tests are run to find correlation between present

price changes and the price changes in past period, with a lag of one day to a

few days. This test is used to test whether markets are efficient or not in the

Weak form. This is also known as Auto Correlation.

• Run tests: These tests are conducted by replacing absolute numbers by signs.

These merely count the number of runs, namely consecutive price changes or

signs in the same direction and their repetition at a later date. This is also a

form of test used to test the Weak form hypothesis.

• T – Test: T-tests are used when we have to check whether there is significant

difference in the mean values of two series of data. This test can be conducted

only when sample size is less than 30. In this report, T-test has been

conducted to see if there is any difference in the mean values of stock returnsbefore and after declaration of dividend and announcement of stock split.

• ANOVA: Analysis of variance has been used to test whether there is any

significant in the returns of mutual funds and random portfolios. In case there

is a significant difference, it means that mutual funds earn a superior return

which contradicts the EMH concept which says that excess returns cannot be

earned by mutual funds even though they have an access to insider

information.

2.8) Limitations of the study

• The data which have been collected for the purpose of analysis may be faulty

• One more limitation is time constraint

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2.9) Chapter scheme

The chapter scheme followed in this report is in the following manner:

1) Background of the study:

This chapter includes the following:

1. Introduction:

2.

Forms of hypothesis3. Assumptions of EMH concept

4. Criticisms of EMH concept

5. Evidence against EMH

6. Literature survey for weak form hypothesis

7. Literature survey for semi-strong form hypothesis

8. Literature survey for strong form hypothesis

2) Research design

1. Statement of problem

2. Objectives of the study

3. Hypothesis

4. Sampling technique

5. Data collection technique

6. Scope of the study

7. Statistical tests

8. Limitations of the study

9. Chapter Scheme

3) Industry Profile

Following are the three industries from which samples have been picked up:1. Banking and finance sector

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2. Computer and IT sector

3. Engineering sector

4) Analysis and interpretation

Analysis and interpretation of data contains the following:

1. Weak form hypothesis:

1. Auto correlation

2. Run test

2. Semi-strong form hypothesis:

1.

Dividend declaration2. Stock split

3. Strong form hypothesis:

5) Findings, conclusion and recommendation

This chapter includes the following in detail:

1. Findings

1. For weak form

2. For semi-strong form

3. For strong form

2. Recommendations

3. Conclusion

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Chapter 3

Industry Profile

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Industry Profile

Following are the ten companies which have been considered for analysis

purpose:

• State bank of Bikaner

• Apollo Sindhoori

• Hercules Hoist

• J M Financial

• Motilal Oswal Financial

• State bank of Travancore

• Take Solutions

• Tanla Solutions

• Texmaco Engineering

• Tricom India

The above mentioned ten companies have been selected at random from three

main sectors, which play a very dominating role in the Indian economy. These three

sectors are:

• Banking and Finance

• Computers and IT

• Engineering

The companies that have been chosen under the Banking and finance sector

are J.M.Financial, Motilal Oswal Financial, Apollo Sindhoori, State Bank of

Travancore and State Bank of Bikaner.

The companies chosen under the computer sector are Take Solutions, Tanla

Solutions and Tricom India.

The companies which come under the Engineering sector are Texmaco

Engineering Ltd and Hercules Hoist.

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3.1) Banking and Finance:

The Indian banking sector is growing at a fast pace along with the Indian

economy. In this age of globalization, foreigners are also making investments in

India and so Indian banks are planning global strategies. Thanks to liberalization,

that the Indian banks have been able to make a mark for themselves in the world

map. The commercial banks have made tremendous progress with respect to its

profitability, capital adequacy, risk management etc. The private banks too are

playing an important role in the Indian banking industry. The private banks are

growing at a rate of 35% per annum. As a result the share of the private banks has

increased to nearly 16%.

But still there is huge potential in the Indian banking sector. India has the

second largest financially excluded households (about 135 million) and it is expected

that nearly 60 million house hold will be added in India's bankable pool by end of

2009. So it is quite clear that the banking industry is going to grow very rapidly.

Indian banks are also very advanced in terms of technology and have vast

network of branches. Nine Indian banks have made their mark in the list of top 50

Asian Banks.

The Indian finance sector is on a roller coaster ride. This was because of the fact that

the investors are interested in the Indian stock market and they are interested in

investing.

This sector is also growing because new products and services are being

offered to the people. India is also attracting people to invest in mutual funds. The

Indian mutual funds industry is expected to grow at a rate of 30% in the next three

years. India's financial sector is generally sound, resilient and fairly liquid. But there

are some concerns that include corporate governance in the co-operative sector,

funding constraints of non-banking finance companies and the lack of up-to-date

data.

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3.2) Computer and IT sector:

Information Technology (IT) industry in India is one of the fastest growing

industries. Indian IT industry has built up valuable brand equity for itself in theglobal markets. IT industry in India comprises of software industry and information

technology enabled services (ITES), which also includes business process

outsourcing (BPO) industry. India is considered as a pioneer in software

development and a favourite destination for IT-enabled services.

The origin of IT industry in India can be traced to 1974, when the mainframe

manufacturer, Burroughs, asked its India sales agent, Tata Consultancy Services

(TCS), to export programmers for installing system software for a U.S. client.

The IT industry originated under unfavourable conditions. Local markets were

absent and government policy toward private enterprise was hostile. The industry

was begun by Bombay-based conglomerates which entered the business by

supplying programmers to global IT firms located overseas. Today, Indian IT

companies such as Tata Consultancy Services (TCS), Wipro, Infosys, HCL et al are

renowned in the global market for their IT prowess. Some of the factors which

played a key role in India's emergence as global IT player are:

• Indian Education System

• High quality human resource

• Competitive costs

• Infrastructure Scenario

In the last few years Indian IT industry has seen tremendous growth.

Destinations such as Bangalore, Hyderabad and Gurgaon have evolved into global IT

hubs. Several IT parks have come up at Bangalore, Hyderabad, Chennai, Pune,

Gurgaon etc. These parks offer Silicon Valley type infrastructure. In the light of all

the factors that have added to the strength of Indian IT industry, it seems that Indian

success story is all set to continue.

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3.3Engineering Sector:

The Indian engineering industry forms the crucial backbone of the economy

and is intricately linked with umpteen other core sectors for its demand. The

engineering industry derives its demand from capacity creations in core sectors viz.,

power, infrastructure, mining, oil and other several other sectors including general

manufacturing sector, consumer goods industry, automotive and process industries.

The intricacies of the demand base make demand forecasts a very complex issue, and

quite often players find their strategies fail due to erratic response from the market.

This report covers the industry.

The engineering sector is the largest segment of the overall Indian industrial

sector. India has a strong engineering and capital goods base. The important groups

within the engineering industry include machinery & instruments, primary and semi

finished iron & steel, steel bars & rods, non-ferrous metals, electronic goods and

project exports. The engineering sector employs over 4 million skilled and semi-

skilled workers (direct and indirect). The sector can be categorised into heavy

engineering and light engineering segments. Heavy engineering segment forms the

majority of the engineering sector in India. In the year 2003-04, out of the total

engineering production of US$ 22 billion, the heavy engineering market contributed

over 80 per cent with the light engineering segment accounting for the remaining.

India has a well-developed and diversified industrial machinery/ capital base

capable of manufacturing the entire range of industrial machinery. The industry has

also managed to successfully develop advanced manufacturing technology over the

years. Among the developing countries, India is a major exporter of heavy and light

engineering goods, producing a wide range of items. The bulk of capital goods

required for power projects, fertiliser, cement, steel and petrochemical plants and

mining equipment are made in India. The country also makes construction

machinery, equipment for irrigation projects, diesel engines, tractors, transport

vehicles, cotton textile and sugar mill machinery.

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Chapter 4

Analysis &

Interpretation of data

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4.1) Weak form Hypothesis

Random walk hypothesis

The random walk hypothesis is a financial theory stating that stock market

prices evolve according to a random walk and thus the prices of the stock market

cannot be predicted. It has been described as 'jibing' with the efficient market

hypothesis. Economists have historically accepted the random walk hypothesis. They

have run several tests and continue to believe that stock prices are completely

random because of the efficiency of the market.

The term was popularized by the 1973 book, “A Random Walk Down Wall

Street”, by Burton Malkiel, currently a Professor of Economics and Finance at

Princeton University, and was used earlier in Eugene Fama's 1965 article “Random

Walks In Stock Market Prices”, which was a less technical version of his Ph.D.

thesis. The theory that stock prices move randomly was earlier proposed by Maurice

Kendall in his 1953 paper, “The Analytics of Economic Time Series”.

The first part of this research aims at finding out whether there is any

relationship between historical share prices and future share prices. If there is no

relationship, then technical analysis, which is a technique of ascertaining future share

prices from past and present share prices using charts and graphs. For this purpose

run test and Auto correlation tests have been used. If the null hypothesis gets

accepted, then it means that past and future share prices are independent of eachother.

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4.1.1) Auto Correlation test:

A number of researchers like Fama, Fischer, Jensen etc in the USA and many

experts in India have conducted tests for auto correlation of the price changes. These

tests are run to find correlation between present price changes and the price changes

in past period, with a lag of one day to a few days. This test is used to test whether

markets are efficient or not in the Weak form. This is also known as Auto

Correlation.

This test is conducted by correlating the stock returns from the first day to nth

day and from second day to n+1th day. If the correlation is very high, then it means

that the stock returns for the coming period is predictable.

For this purpose, returns are calculated as follows:

After returns are calculated for all 365 days, returns from 1 to 364th day are

correlated with returns from 2nd to 365th day.

If historical and future share prices are correlated, then the values will form

almost a straight line, when plotted on a graph indicating that they move in the same

direction. If there is no correlation or a very low correlation, then the values will be

plotted on a random basis without having any significant pattern.

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A sample of auto correlation is shown for one of the under the study

companies, for just 25 days, with a lag of one day along with the final results

for all the ten companies under consideration in the coming pages.

RETURNS (%) RETURNS (%)

2.261948 -0.24973

-0.24973 -0.03577

-0.03577 1.610018

1.610018 1.93662

1.93662 4.145078

4.145078 4.3117744.311774 4.419564

4.419564 2.56772

2.56772 5.006878

5.006878 3.563008

3.563008 -5.31242

-5.31242 -4.83569

-4.83569 2.3020772.302077 0.274424

0.274424 5.145047

5.145047 4.997397

4.997397 5.007437

5.007437 -0.30689

-0.30689 -2.29695

-2.29695 -3.22346

-3.22346 -4.0571

-4.0571 3.315061

3.315061 5.760485

5.760485 -3.89393

-3.89393 -4.20085

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These are the final results obtained after computing Auto correlation:

COMPANY AUTO CORRELATION

STATE BANK OF BIKANER 0.047471127

APOLLO SINDHOORI 0.44047357

HERCULES HOIST 0.027838344

J M FINANCIAL 0.076896517

MOTILAL OSWAL 0.049817691

STATE BANK OF TRAVANCORE 0.162503346

TAKE 0.108387325

TANLA 0.095603805

TEXMACO -0.034868999

TRICOM -0.029500477

It has been observed that the stock movement predictability is very low for all

the companies except for Apollo Sindhoori, which has a correlation value of 0.44. In

fact, for two companies, negative auto correlation values which imply that future

stock return changes move in the opposite direction of current stock return changes.

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4.1.2) Run tests: These tests are conducted by replacing absolute numbers by signs.

These merely count the number of runs, namely consecutive price changes or signs

in the same direction and their repetition at a later date.

Following are the results obtained when Run test was conducted using the daily

closing adjusted market price of the ten companies under consideration:

Where n1 represents number of positive price changes

n2

represents number of negative price changes

ur represents mean of the sample

u represents number of runs

represents standard deviation of the sample

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Following is a sample to show how the number of runs is calculated. An

extract from one of the companies under consideration has been taken for one

month. In a similar manner, number of runs has been calculated for ten

companies for one year.

DATE ADJCLOSE

INCREASE/DECREASE PLUS/MINUS NO. OFRUNS

01-04-2008 28.16

02-04-2008 26.84 0.953125 MINUS 1

03-04-2008 26.84 1 PLUS 2

04-04-2008 27.67 1.030923994 PLUS

07-04-2008 26 0.939645826 MINUS 3

08-04-2008 26.5 1.019230769 PLUS 4

09-04-2008 26.52 1.000754717 PLUS

10-04-2008 28.65 1.080316742 PLUS

11-04-2008 28.24 0.985689354 MINUS 5

14-04-2008 28.24 1 PLUS 6

15-04-2008 26.99 0.955736544 MINUS 7

16-04-2008 27.06 1.002593553 PLUS 8

17-04-2008 27.48 1.015521064 PLUS

18-04-2008 27.48 1 PLUS

21-04-2008 27.97 1.01783115 PLUS

22-04-2008 29.44 1.05255631 PLUS

23-04-2008 30.67 1.041779891 PLUS

24-04-2008 34.39 1.121291164 PLUS

25-04-2008 33.22 0.965978482 MINUS 9

28-04-2008 33.12 0.996989765 MINUS

29-04-2008 33.12 1 PLUS 10

30-04-2008 32.38 0.977657005 MINUS 11

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Following is the summary of the results obtained after conducting run test for

the ten companies under consideration for the financial year 2008-09:

SL NO. COMPANY RUNS PLUS MINUS MEANSTANDARDDEVIATION

1STATE BANK OFBIKANER

104 122 96 108.4495 7.260128593

2 APOLLO SINDHOORI 114 109 125 117.453 7.596262416

3 HERCULES HOIST 116 102 135 117.2025 7.531522971

4 J M FINANCIAL 118 92 143 112.966 7.286684282

5MOTILAL OSWALFINANCIALS

119 113 126 120.1464 7.690638355

6STATE BANK OFTRAVANCORE

112 105 128 116.3648 7.541172579

7 TAKE SOLUTIONS 124 106 132 118.3276 7.605082979

8 TANLA SOLUTION 105 104 133 117.7257 7.565581146

9 TEXMACOENGINEERING LTD

114 104 135 118.4895 7.583236269

10 TRICOM INDIA 127 103 130 115.9356 7.512994965

Using the above mean, standard deviation and number of runs values, run test

is conducted to see if there is any relationship between historical and future

share prices.

If the calculated value is lesser than tabulated value, then the null hypothesis is

accepted and it is concluded that historical and future share prices are

independent. If not, they are considered to be dependent.

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Testing of Hypothesis:

Ho- Historical and future share prices are independent

HA- Historical and future share prices are dependent

SL NO. COMPANY Z-CAL VALUES

1 STATE BANK OF BIKANER 0.612873621

2 APOLLO SINDHOORI 0.45456453

3 HERCULES HOIST 0.159666465

4 J M FINANCIAL 0.690855039

5 MOTILAL OSWAL FINANCIAL 0.149070007

6 STATE BANK OF TRAVANCORE 0.578796841

7 TAKE SOLUTIONS 0.877356912

8 TANLA SOLUTIONS 1.632056957

9 TEXMACO ENGINEERING 0.592034798

10 TRICOM INDIA 1.472698669

Z tabulated value is 1.645 which is higher than Z calculated value in all the

cases. So, the null hypothesis is accepted.

Hence, it can be concluded that historical share prices are not related to futureshare prices.

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4.2) Semi-strong form Hypothesis

The semi strong form of efficient market hypothesis says that the current

market prices will reflect instantaneously all publicly available information 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. Examples of the type of public

information are corporate reports, corporate announcements and information relating

to corporate dividend policy, forthcoming stock splits, annual earnings per share,

initial public offering, bonus issue of shares etc. Hence, according to the semi-strong

form of hypothesis, analysts would have great difficulty trying to profit using

fundamental analysis.

The tests that will be conducted in this section test whether in fact all the

publicly available information and news announcements such as dividend declaration

and information about stock splits. Furthermore, these tests attempt to analyze if an

analyst using such data when they become available to him can successfully use thisinformation to obtain superior investment returns.

Fama, Fisher, Jensen and Roll made a major contribution with their study of

the Semi-strong form hypothesis in “The Adjustment of Stock Prices to New

Information”. They tested the speed of market’s reaction to a firm’s announcement

of a stock split and the accompanying information with respect to a change in

dividend policy. The authors concluded that the market was efficient with respect to

its reaction to information and stock split and also changes in dividend policy.

A great majority of the semi-strong efficient tests conducted provide strong empirical

support for the hypothesis. However, there have been some notable exceptions to this

support. Most of the reported results show that stock prices do adjust rapidly to

announcement of new information. Further, some studies indicate that investors are

unable to utilize this information to earn consistently above average returns.

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1. Event study: A scheme based upon trading on an information event is usually

tested with an event study. Event studies are conducted to test whether it is

possible to earn risk-adjusted returns by trading on information like earnings

announcements, stock splits, bonus issues and acquisition announcements.

2. Portfolio study: A scheme based upon trading on an observable characteristic

is usually tested with a portfolio study. Portfolio studies are conducted to test

whether it is possible to earn risk-adjusted returns by trading on an observable

characteristic of a firm like Price-earnings ratio, price-book value ratio and

dividend yield.

Tests conducted to test the validity of Semi-strong form Hypothesis:

• T – Test: T-tests are used when we have to check whether there is significant

difference in the mean values of two series of data. This test can be conducted

only when sample size is less than 30. In this report, T-test has been

conducted to see if there is any difference in the mean values of stock returns

before and after declaration of dividend and announcement of stock split.

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4.2.1) Dividend Declaration

Quarterly earnings reports are sometimes followed by announcements of

dividend changes which also affect the stock price. To examine this problem,

Aharony and Swary (1980) observe all dividend and earnings announcements within

the same quarter that are at least 11 trading days apart.

They conclude that both quarterly earnings announcements and dividend

change announcements have statistically significant effects on the stock price. But

more important, they find no evidence of market inefficiency when the two types of

announcement effects are separated.

Two studies, one by Pettit(1972) and one by Watts(1973), measured themarket’s reaction to dividend announcements. Although, the authors arrived at

different conclusions concerning the importance of dividend changes to market

participants, the results of both studies are consistent with the behaviour implied by

the EMH: there was no evidence that a firm’s dividend announcement affected the

firm’s security price in the periods following the announcement.

Handjinicolaou and Kalay (1984) and Woolridge (1983) have argued that one

cannot infer that dividend increases convey positive information about the firm by

examing share prices alone, since unexpected dividend increases could cause wealth

transfers from bondholders to shareholders by reducing the asset base of the firm.

Therefore, the observed increase in share price is consistent with both wealth

redistribution and positive information. To differentiate between the relative

importance of these two effects, Handjinicolaou and Kalay and Woolridge analyze

the changes in bond prices around dividend announcements since the two hypotheses

(information and wealth transfer) have different predictions for bond price

behaviour. In particular, the wealth transfer hypothesis predicts a negative bond price

reaction while the information content hypothesis predicts a positive reaction. The

findings of these studies provide strong support for the hypothesis that informational

effects dominate wealth redistribution effects wherever there are unexpected

dividend increases.

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Table showing details regarding the dividend declared by the ten companies

under consideration during the financial year 2008-09

SL NO. COMPANYDATE OF DIVIDEND

DECLAREDAMOUNT(IN $)

1 STATE BANK OF BIKANER 14-07-2008 0.5

2 APOLLO SINDHOORI 05-09-2008 0.1

3 HERCULES HOIST 16-07-2008 20

4 J M FINANCIAL 16-07-2008 25

5 MOTILAL OSWALFINANCIAL

14-05-2008 4

6STATE BANK OFTRAVANCORE

20-06-2008 2.5

7 TAKE SOLUTIONS 30-07-2008 2

8 TANLA SOLUTIONS 18-09-2008 1.2

9 TEXMACO ENGINEERING 31-07-2008 7.5

10 TRICOM INDIA 19-09-2008 0.46

The following charts show the movement of stock prices 15 days before and

15 days after the declaration of dividend:

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Ho - There is a no significant difference between share prices before and after

declaration of dividend


declaration of dividend

COMPANY T-TEST CALCULATED

VALUESSTATE BANK OF BIKANER 0.515653492






TAKE 0.017799133

TANLA 0.000169669

TEXMACO 0.000225386

TRICOM 0.015735399

T tabulated value is 1.833 at 5% level of significance. It is found that

calculated value of T to be lesser than 1.833 in all the above cases. So, Null

Hypothesis is accepted

Hence it can be concluded that there is no significant difference between

share prices before and after declaration of dividend.

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Table showing details regarding the stock splits by the ten companies under

consideration during the financial year 2008-09

SL NO. COMPANYDATE OF STOCKSPLIT

RATIO OFSPLIT

1 STATE BANK OF BIKANER 11-09-2008 2 : 1

2 APOLLO SINDHOORI 11-07-2008 10 : 1

3 HERCULES HOIST 17-09-2008 10 : 1

4 J M FINANCIAL 08-09-2008 10 : 1

5 MOTILAL OSWAL FINANCIAL 25-07-2008 5 : 1

6 STATE BANK OF TRAVANCORE 02-04-2008 1 : 10

7 TAKE SOLUTIONS 18-09-2008 10 : 1

8 TANLA SOLUTIONS 02-05-2008 2 : 1

9 TEXMACO ENGINEERING 01-01-2009 10 : 1

10 TRICOM INDIA 15-07-2008 5 : 1

The following charts show the movement of stock prices 15 days before and

15 days after the announcement of stock split:

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Ho - There is a no significant difference between share prices before and after

announcement of stock split



COMPANY T-TEST CALCULATEDVALUES

STATE BANK OF BIKANER 0.000590691






TAKE 0.000147123

TANLA 0.008521675

TEXMACO 0.563818195

TRICOM 0.000938619

T tabulated value is 1.833 at 5% level of significance. It has been found thatcalculated value of T to be lesser than 1.833 in all the above cases. So Null

Hypothesis is accepted.

Hence it can be concluded that there is no significant difference between share

prices before and after announcement of stock split.

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4.3) Strong Form Hypothesis

The Strong form efficient market hypothesis holds that all available

information, whether public or private, is reflected in the stock prices. Obviously,

this represents an extreme hypothesis and it would be surprising if it were true.

To test the strong form efficient market hypothesis, many researchers analysed

the returns earned by certain groups (like corporate insiders, specialists on stock exchanges and mutual fund managers) who have access to information which is not

publicly available and/or ostensibly possess greater resources and abilities to

intensively analyse information which is in the public domain. Empirical evidence

broadly suggests the following:

• 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.

• Mutual fund managers do not, on an average, earn 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”.

To test for strong-form efficiency, a market needs to exist where investors

cannot consistently earn excess returns over a long period of time. Even if some

money managers are consistently observed to beat the market, no refutation even of

strong-form efficiency follows: with hundreds of thousands of fund managers

worldwide, even a normal distribution of returns (as efficiency predicts) should be

expected to produce a few dozen "star" performers

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Insider Information

Insider trading is the trading of a corporation's stock or other securities (e.g.

bonds or stock options) by individuals with potential access to non-public

information about the company. In most countries, trading by corporate insiders such

as officers, key employees, directors, and large shareholders may be legal, if this

trading is done in a way that does not take advantage of non-public information.

However, the term is frequently used to refer to a practice in which an insider or a

related party trades based on material non-public information obtained during the

performance of the insider's duties at the corporation, or otherwise in breach of a

fiduciary duty or other relationship of trust and confidence or where the non-public

information was misappropriated from the company.

While "legal" insider trading cannot be based on material non-public

information, some investors believe corporate insiders nonetheless may have better

insights into the health of a corporation (broadly speaking) and that their trades

otherwise convey important information (e.g., about the pending retirement of an

important officer selling shares, greater commitment to the corporation by officers

purchasing shares, etc.)

It is believed that people and institutions which have access to insider

information earn superior returns as compared to those who do not have access. Thisbelief contradicts the efficient market hypothesis theory which propounds that it is

impossible to earn excess returns even with the availability of insider information.

The third part of this research aims to find out whether it is possible or not to earn

abnormal returns using insider information.

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Mutual Fund

A mutual fund is a professionally managed type of collective investment

scheme that pools money from many investors and invests it in stocks, bonds, short-

term money market instruments, and/or other securities. The mutual fund will have a

fund manager that trades the pooled money on a regular basis. As of early 2008, the

worldwide value of all mutual funds totals more than $26 trillion.

Mutual funds offer several advantages over investing in individual stocks. For

example, the transaction costs are divided among all the mutual fund shareholders,

which allows for cost-effective diversification. Investors may also benefit by having

a third party (professional fund managers) apply expertise and dedicate time to

manage and research investment options, although there is dispute over whether

professional fund managers can, on average, outperform simple index funds that

mimic public indexes. Yet, the Wall Street Journal reported that separately managed

accounts (SMA or SMAs) performed better than mutual funds in 22 of 25 categories

from 2006 to 2008.

The EMH theory propagates that the current market prices reflect the past

market prices, freely available information and also insider information. Hence

according to EMH it is not possible to earn excess returns even by carefully

analysing the historical prices and other information. So, this research is being

conducted with the objective to test whether the returns provided by diversified

equity funds of various mutual funds (which consider technical analysis,

fundamental analysis and also insider information) exceed the returns offered by

randomly constructed portfolios. For this purpose 35 mutual fund schemes have

been randomly selected and their performance over the past financial year will be

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compared to that of randomly selected portfolios which consists of stocks of NSE

listed companies.

The following table gives an extract of Annualized returns of 35 Mutual Fund

Schemes for the financial year 2008-09

SLNO.

MUTUAL FUND SCHEME ANNUALIZEDRETURN

1 UTI SPREAD FUND - GROWTH 9.6892

2 UTI SPREAD FUND - DIVIDEND 8.764

3 HDFC ARBITRAGE FUND - IP - GROWTH 7.8141

4 HDFC ARBITRAGE FUND - RETAIL - GROWTH 7.5555

5 ICICI PRUDENTIAL BLENDED PLAN - OPTION A - GROWTH 7.3368

6 KOTAK EQUITY ARBITRAGE FUND - GROWTH 7.2606

7 ICICI PRUDENTIAL EQUITY & DERIVATIVES FUND - I O - IP -GROWTH

6.8361

8 SBI ARBITRAGE OPPORTUNITIES FUND - GROWTH 6.817

9 ICICI PRUDENTIAL EQUITY & DERIVATIVES FUND - I O - RETAIL -GROWTH

6.5963

10 BENCHMARK EQUITY AND DERIVATIVE OPPORTUNITIES FUND -GROWTH

6.5718

11IDFC ARBITRAGE FUND - PLAN A (REGULAR) - GROWTH

5.896112 FRANKLIN PHARMA FUND - DIVIDEND -14.1809

13 RELIANCE PHARMA FUND - GROWTH -15.8025

14 UTI MNC FUND - DIVIDEND -18.0929

15 BIRLA SUN LIFE DIVIDEND YIELD PLUS - DIVIDEND -19.5495

16 UTI THEMATIC TRANSPORTATION AND LOGISTICS FUND - GROWTH -21.8329

17 DSP BLACKROCK TOP 100 EQUITY FUND - IP - GROWTH -24.0713

18 RELIANCE BANKING FUND - GROWTH -24.8347

19 BIRLA SUN LIFE INTERNATIONAL EQUITY FUND - PLAN A -DIVIDEND

-26.4816

20 ICICI PRUDENTIAL GROWTH PLAN - CUMULATIVE -26.9644

21 TATA LIFE SCIENCES AND TECHNOLOGY FUND - APPR -28.8876

22 FIDELITY INDIA GROWTH FUND - GROWTH -29.3155

23 ESCORTS HIGH YIELD EQUITY PLAN - BONUS -35.3593

24 DSP BLACKROCK SMALL AND MIDCAP FUND - DIVIDEND -38.7315

25 SAHARA MIDCAP FUND - GROWTH -41.2283

26 ESCORTS HIGH YIELD EQUITY PLAN - BONUS -35.3593

27 DSP BLACKROCK SMALL AND MIDCAP FUND - DIVIDEND -38.7315

28 SUNDARAM BNP PARIBAS INDIA LEADERSHIP FUND - GROWTH -38.6972

29 SAHARA MIDCAP FUND - GROWTH -41.2283

30 ING MIDCAP FUND - GROWTH -46.2083

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31 JM EQUITY - DIVIDEND -46.799

32 SBI MAGNUM MIDCAP FUND - GROWTH -51.6332

33 JPMORGAN INDIA SMALLER COMPANIES FUND - GROWTH -53.6974

34 JM BASIC FUND - GROWTH -63.0312

35 JM SMALL & MID-CAP FUND - REGULAR - DIVIDEND -72.9206

ANNUALISED RETURNS OF 35 MUTUAL FUND SCHEMES:

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Following is one of the samples out of the 30 random portfolios that werecreated containing 30 stocks each:

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PORTFOLIO 1

STOCK NAME

RETURN

GARDEN SILK MILLS LTD. -44.1628

CIPLA LTD. -6.91871

EIH LTD. -44.1192

GEOJIT FINANCIAL SERVICES LTD. -67.1125

GODREJ CONSUMER PRODUCTS LTD. 7.021277

B L KASHYAP & SONS LTD. -91.7194

ADLABS FILMS LTD. -81.8849

CONSOLIDATED FINVEST & HOLDINGS LTD. -57.3684

CRISIL LTD. -29.4813

BIOCON LTD. -76.0699

AXIS BANK LTD. -61.0472

CHENNAI PETROLEUM CORPORATION LTD. -66.1161

GUJARAT MINERAL DEVELOPMENT CORPORATION LTD. -90.8184

GUJARAT STATE FERTILIZERS & CHEMICALS LTD. -70.3396

DWARIKESH SUGAR INDUSTRIAL LTD. -49.2355

DEEPAK FERTILISERS & PETROCHEMICALS CORP. LTD. -59.7723

DR. REDDY'S LABORATORIES LTD. 64.25603

EVEREST INDUSTRIES LTD. -47.9857

BOC INDIA LTD. -20.6776

BHARTI AIRTEL LTD. -24.406

FEDERAL-MOGUL GOETZE (INDIA) LTD. -65.0485

GUJARAT STATE FERTILIZERS & CHEMICALS LTD. -70.3396

HERO HONDA MOTORS LTD. 23.71864

BIRLA CORPORATION LTD. -13.3132

BALRAMPUR CHINI MILLS LTD. -42.8803

FIRSTSOURCE SOLUTIONS LTD. -73.9662

CENTURY TEXTILE & INDUSTRIES LTD. -82.1111

AXIS BANK LTD. -61.0472

COSMO FILMS LTD. -38.9381

GREAT EASTERN SHIPPING CO. LTD. -60.6473

Following is the average annualized returns that were obtained from the 30random portfolios created:

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PORTFOLIOS AVERAGE ANNUAL RETURNS

1 -46.75103705

2 -57.427223993 -53.16213088

4 -54.42699664

5 -53.00701909

6 -54.23952623

7 -51.73613116

8 -47.75023317

9 -49.37823317

10 -43.1062368911 -50.30219268

12 -48.92842302

13 -60.42135384

14 -48.59567412

15 -47.01089813

16 -47.42894509

17 -55.44935929

18 -53.98680165

19 -49.39506616

20 -56.92411846

21 -58.84296786

22 -52.56991815

23 -56.70011363

24 -54.46381886

25 -56.34389218

26 -45.54630942

27 -59.0091152128 -56.23026256

29 -49.20870247

30 -54.14266802

AVERAGE ANNUALISED RETURNS OF 30 RANDOM PORTFOLIOS:

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Comparative Presentation of Top 5 Mutual Fund Schemes and Top 5 Random

Portfolios:

Name of Scheme % ReturnRandom Portfolio

Code%

Return

UTI Spread Fund – Growth 9.6892 10 -43.1062

UTI Spread Fund – Dividend 8.764 26 -45.5463

HDFC Arbitrage Fund - IP - Growth 7.8141 1 -46.751

HDFC Arbitrage Fund - Retail -

Growth

7.5555 15 -47.0109

ICICI Prudential Blended Plan -Growth

7.3368 16 -47.4289

Comparative Presentation of Bottom 5 Mutual Fund Schemes and Bottom 5

Random Portfolios:

Name of Scheme % ReturnRandom Portfolio

Code

%

ReturnJM Equity – Dividend -46.799 20 -56.9241

SBI Magnum Midcap Fund - Growth -51.6332 2 -57.4272

JPMorgan India Smaller CompaniesFund

-53.6974 21 -58.843

JM Basic Fund – Growth -63.0312 27 -59.0091

JM Small & Mid-Cap Fund - Dividend -72.9206 13 -60.4214

From the above, it has been observed that mutual funds earn comparatively higher

returns as compared to random portfolios. The highest return in mutual fund is

observed to be 9.6892% while in random portfolios the highest return is

-43.1062%. But it is also noticed that while the least returns in random portfolio is -

60.4214%, in case of mutual fund it is -72.9206%.

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Following table shows the mean returns, standard deviation and coefficient of

variation of the 35 mutual fund returns and the 215 NSE listed companies

under consideration:

PARTICULARS MUTUAL FUNDRANDOM

PORTFOLIO

MEAN -22.0714686 -52.41617897

STANDARD DEVIATION 23.68804923 4.44083794

CO-EFFICIENT OFVARIATION

-107.3243 -8.472265676

From the above table, it can be concluded that mutual funds on an average

have higher returns as compared to that of random portfolios. It has also been

observed that the mean returns of mutual funds, -22.07%, even though negative is

higher than that of random portfolios, which has an average annual return of -

52.42%.But it is also observed that the standard deviation and coefficient of variation

of mutual funds is substantially higher as compared to that of random portfolios. This

implies that the returns of mutual funds are very volatile and unstable. So the risk

involved in investing in mutual funds is higher.

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ANOVA:

Analysis of Variance has been used to test whether there is any significant in

the returns of mutual funds and random portfolios. In case there is a significant

difference, it means that mutual funds earn a superior return which contradicts the

EMH concept which says that excess returns cannot be earned by mutual funds even

though they have an access to insider information.

For this purpose, single factor ANOVA is calculated using inbuilt function of

Microsoft Excel. Level of Significance is taken at 5%.

H0: There is no significant difference in returns earned by mutual funds and randomportfolios.

HA: There is a significant difference in returns earned by mutual funds and random

portfolios.

SUMMARY

Groups Count Sum Average Variance

Column 1 35 -772.501 -22.0715 561.1237

Column 2 30 -1572.49 -52.4162 19.72104

ANOVA

Source of Variation SS df MS F P-value F crit

Between Groups 14874.48 1 14874.48 47.68891 2.92E-09 3.993365

Within Groups 19650.12 63 311.9066

Total 34524.6 64

Since Fcal value is greater than Ftab value i.e. 47.68>3.99, we reject the

null hypothesis. Therefore we can conclude that there is a significant

difference in returns earned by mutual funds and random portfolios

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The following charts represent the adjusted closing market prices of the

ten companies considered in this research for financial year 2008-09

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5.1) Findings

5.1.1) For weak form hypothesis:

The stock movement predictability is very low for all the companies exceptfor Apollo Sindhoori, which has a correlation value of 0.44. In fact, for two

companies we find negative auto correlation values which imply that future

stock return changes move in the opposite direction of current stock return

changes.

As stock predictability is low, there is a lot of risk and deviation involved if

we try to predict future share prices using past data. Hence, it is not possible

to earn abnormal returns consistently in the long run.

From conducting Run test, it has been found that historical share prices are

not related to future share prices.

As past and current stock prices are not related to future stock prices, it can be

concluded that the market discounts all past prices of shares.

It can be conclude that Indian stock market is efficient in its weak form as we

cannot earn superior returns using historical information of shares

Technical analysis is not a very effective tool in the Indian market in the

current scenario as markets are efficient in its weak form

5.1.2) For semi-strong form hypothesis:

There is no significant difference between share prices before and after

declaration of dividend.

Hence, market readily discounts information regarding dividend

announcement and these changes are reflected in the new market prices

There is no significant difference between share prices before and after


Hence, it is not possible to take advantage of availability of information

regarding stock split

Therefore it can be said that markets are efficient in the semi-strong form and

hence it is not possible to earn abnormal returns in the long run using publiclyavailable information, such as, company fundamentals etc.

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Bibliography BOOKS:

• Securities analysis portfolio management, Fischer, et.al, PHI publications, 2000

edition

• Securities analysis portfolio management, Adhvani, Himalaya Publication, 1999

edition

• C. R.Kothari, Research methodology, VishwaPradashan Publishing House,

Bangalore

JOURNALS:

• Obaidullah, M (1990), “Stock Price Adjustment to Half Yearly Earnings

Announcements—A Test of Market Efficiency”, Chartered Accountant,

Volume-38, Page 922 924.

• Indian Journal of Finance, “Efficient market hypothesis: A case study on Bombay

Stock Exchange”, Silky Vigg, et.al, Volume-2, No.6, October 2008

• Amitabh Gupta, (2006), “Impact of Earnings Announcements on Stock Prices:

Some Empirical Evidences from India”, The ICFAI Journal of Applied Finance.

WEBSITES:

1) www.investopedia.com

2)

www.blonnet.com3) www.nse-india .com

4) www.indiainfoline.com

5) www.equitymasters.com

6) www.capitaline.com

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Annexure

t-test calculations for dividend declaration

DAYS

STATE BANK OFBIKANER

APOLLOSINDHOORI

HERCULESHOIST

J M FINANCIAL MOTILALOSWAL

BEFORE AFTER BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

1 30.15 26.75 49.11 57.6 192.26 207.3 123.75 131 144.14 156.9

7

2 30.15 25.58 49.71 57.5 194.67 212.5 122.53 130.6 144.96 164.3

4

3 28.65 25.58 49.01 57.5 188.65 213.5 118.44 130.6

1

147.13 164.2

8

4 27.26 25.58 48.66 57.75 183.49 215 118.44 128 158.64 164.2

8

5 26.62 25.73 49.61 57.5 185.48 225 112.23 127.9 153.3 169.6

6 26.74 25.5 47.92 56.95 190 240 114.77 135 157.49 165.2

7 25.42 25.5 48.91 57 180.95 242.5 114.36 131.7

5

157.49 163

8 26.32 25.5 51.71 56.9 178.96 235.0

1

113.38 131.8

9

162.75 162

9 26.32 26.77 51.36 56.65 184.57 239.8 118.03 130.12

169.54 155.2

10 24.51 26.9 53.11 56.7 181.4 238 117.22 127 163.02 151.2

11 23.55 26.9 57.65 56.35 193 237 117.46 129.9 168.76 158.4

3

12 24.68 26.9 55.25 56.5 197.24 234.9

9

116.32 127.3 165.28 149.9

3

13 25.49 26.25 55.75 55.85 193.43 230.6

2

110.68 126.5 156.68 148.2

3

14 26.25 26.25 56.15 56.15 188.73 238.99

113.13 127 148.1 142.6

15 26.25 26.95 57.2 56.15 190 239.2 111.49 126.5 152 143

T-CAL

0.515653492 0.000378564 2.23862E-08 2.29678E-09 0.852115311

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DAYS

STATE BANKOFTRAVANCORE

TAKE TANLA TEXMACO TRICOM

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

1 395.24 359 56.32 53.7 214.48 186.0

5

109.03 124 21.98 21.6

2 392.06 365 53.48 53 208.42 170.0

5

104.01 127.0

3

22.72 22.15

3 383.32 383.5 51.99 51.81 213.48 183.1 103.02 133 21.98 23

4 361.47 388.85

51.04 53 212.49 183 102.88 135.8 22.33 22.5

5 341.61 395 52.09 53.29 213.98 189.2

5

104.34 132 22.03 22.8

6 335.65 397 50.25 52.5 213.48 174.9 105.84 130.0

1

22.86 22

7 338.63 381.5 48.62 50.33 213.98 171.0

5

106.13 130.7

9

22.67 20.5

8 317.78 385.1 51.41 55.2 209.96 165 105.75 129.6

8

22.57 21.3

9 324.73 380 50.54 57.15 207.28 162.7

5

108.95 129.5 22.42 23

10 352.53 400 50.64 53.31 196.45 160 115.43 130 21.89 21.05

11 352.53 379.9 51.51 53 187.62 159.0

5

119.29 127.0

2

21.4 19

12 372.4 386 49.2 52.8 187.67 144.0

5

116.79 127.0

2

20.18 18.1

13 374.38 388.5 54.88 52.8 175.3 145 117.5 127.1

5

19.25 17.35

14 379.35 420 51.12 53 186.57 140 115.43 128.0

1

19.4 13.9

15357.5 420 51.7 53.99 168.8 112 117.5 130 17.89 15.75

T-CAL

0.002673453 0.017799133 1.69669E-10 2.25386E-07 0.015735399

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t-test calculations for stock split

DAYS

STATE BANKOF BIKANER

APOLLOSINDHOORI

HERCULESHOIST

J M FINANCIAL MOTILALOSWAL

BEFORE

AFTER

BEFORE

AFTER

BEFORE

AFTER

BEFORE

AFTER

BEFORE

AFTER

1 34.15 37 52.91 51.56 222.1 268.8 126.5 67.35 108.99 105.3

5

2 35.88 36.15 54.21 50.91 214.1 261.5 126.7 71.45 109.8 101.7

3 35.75 33.6 51.92 50.81 218 258 126.01 71.25 112 99.35

4 35.33 32 49.33 50.61 220 234.2 123.3 68.7 113.24 99.45

5 34.75 32.95 51.74 52.16 220.71 231.5 125.3 63.55 108.74 99

6 34.75 32 49.91 49.66 220.71 226 125.4 57.45 106.02 98.35

7 33.5 30.4 47.37 47.92 217.54 218.3 126.9 54.5 99.4 101.5

8 33.25 28.9 47.12 47.22 218.04 198 124.5 53.1 97.22 102.2

5

9 33.35 27.5 49.13 48.17 237.15 183.4 123.6 53.85 93.2 104

10 33.35 27.5 51.59 47.17 285.43 166 134.4 52.5 91.6 105

11 35.2 26.5 51.11 50.51 292 183.1 142 49.4 89.82 106.5

12 35 25.25 50.41 50.06 288.8 169.3 137 46.6 95.6 114.3

5

13 35.15 24.5 50.31 48.91 273 156 137 46 96.4 114.3

14 35.5 25.1 50.41 50.91 250.5 152 145.25 43.9 101.6 112.5

15 36.88 22.35 52.4 49.41 303.08 145.5 139.7 43.85 105 107

T-CAL

0.000590691 0.040718788 0.039625376 5.39537E-11 0.363604292

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DAYS

SBT TAKE TANLA TEXMACO TRICOM

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

BEFOR

E

AFTE

R

1 373.39 405.1

7

62.2 51.1 227.38 295.5 60.93 76.5 22.42 26.3

2

2 372.45 399.1

1

62.5 57 227.38 286.8

6

61.5 76.3 24.29 29.1

3 387.29 412.1

2

61.55 53.5 235.82 278.0

2

62.5 74.8 24.38 28.2

7

4 385.26 408.8

9

63.39 54 247.74 280.9 64.6 73.9

5

24.8 27.1

5 381.83 407.1

5

63.39 55.6 268.09 275.0

4

62.5 73 24.18 29.0

5

6 401.29 399.21

61.47 53.5 268.09 269.09

63.8 71 21.56 27.3

7 382.33 402.1

9

60.21 47.5 272.09 267.1 67.2 64 21.59 27.7

9

8 382.33 394.2

4

61 47.5 261.64 265.6

1

70.3 60.5 20.08 26.3

2

9 382.33 391.1

6

61.21 48 262.63 265.6

1

70 63.7

5

20.13 26.3

2

10 394.74 375.4

7

62.12 48.1 258.16 285.9

7

69.7 61 22.23 27.2

5

11 405.17 368.5

2

59 43.1 256.68 284.4

8

69.7 59 20.86 25.8

4

12 417.08 387.3

4

59 40 258.16 283.9

8

68.39 57.4 23.38 24.8

6

13 413.21 388.2

8

53.5 38.4 269.09 279.1

2

68 56.9 25.04 24.5

7

14 417.08 394.2

4

53.4 37.9 280.01 275.0

4

72.2 55.4 24.18 23.4

15 417.08 389.6

8

53.7 34 280.01 267.1 74 53.9

5

25.04 24.3

7

T-

CAL

0.919432109 1.47123E-08 0.008521675 0.563818195 9.38619E-05

ANJALI-07XQCM6007

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