Impact of Stock Split on Returns

8/7/2019 Impact of Stock Split on Returns

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Impact of Stock Splits on Stock Returns Volatility

M P Birla Institute of Management 1

A RESEARCH REPORT

ON

IMPACT OF STOCK SPLITS ON STOCKRETURNS VOLATILITY

(AN ANALYTICAL STUDY OF THE EFFECT OF STOCK SPLITS ON LIQUIDITY ANDRETURNS: EVIDENCE FROM INDIAN COMPANIES)

Submitted in partial fulfillment of requirement for the award

of the degree of

MASTER OF BUSINESS ADMINISTRATION

OF

BANGALORE UNIVERSITY

BY:

SANDEEP R. BHAT

REG. NO: 06XQCM6071

UNDER THE GUIDANCE AND SUPERVISION

OF

PROF. PRAVEEN BHAGAWAN

M.P.BIRLA INSTITUTE OF MANAGEMENTASSOCIATE BHARATIYA VIDYA BHAVAN

#43, RACE COURSE ROAD, BANGALORE-560 001

2008


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DECLARATION

I hereby, declare that this dissertation report:

Impact of stock splits on stock returns volatility - An analytical study

of the effect of stock splits on liquidity and returns: Evidence from

Indian Companies, submitted in partial fulfillment for the award ofMaster

of Business Administration of Bangalore University is a record of

independent work carried out by me under the guidance of Prof. Praveen

Bhagawan, faculty member, M P Birla Institute of Management (Associate

Bharatiya Vidya Bhavan), Bangalore.

I also declare that this report is a result of my own effort and has not

been submitted earlier for the award of any degree or diploma of Bangalore

University or any other University.

Place: Bangalore SANDEEP R. BHAT

Date: REG. NO: 06XQCM6071


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PRINCIPALS CERTIFICATE

This is to certify that the dissertation report entitled, Impact of

stock splits on stock returns volatility - An analytical study of the

effect of stock splits on liquidity and returns: Evidence from Indian

Companies, has been prepared by Mr. Sandeep R. Bhat bearing the

registration number06XQCM6071, under the guidance and supervision of

Prof. Praveen Bhagawan, faculty member, M P Birla Institute of

Management (Associate Bharatiya Vidya Bhavan), Bangalore.

To the best of my knowledge this report has not formed the basis for

the award of any other degree.

Place: Bangalore PrincipalDate: (Dr. N. S. Malavalli)


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GUIDES CERTIFICATE

This is to certify that the dissertation report entitled, Impact of

stock splits on stock returns volatility - An analytical study of the

effect of stock splits on liquidity and returns: Evidence from Indian

Companies, prepared by Mr. Sandeep R. Bhat bearing the registration

number06XQCM6071 is a bonafide work done under my guidance during

the academic year 2007-2008 in partial fulfillment 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.

Place: Bangalore

Date: Prof. Praveen Bhagawan


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ACKNOWLEDGEMENT

It is with great pleasure and gratitude that I acknowledge the

contribution of several individuals towards the successful

completion of the project.

I sincerely thank Dr. Nagesh Malavalli, Principal, M. P. Birla

Institute of Management, Bangalore for granting me permission to

take up the project.

I wish to express my heartfelt gratitude to my guide

Prof. Praveen Bhagawan, faculty member, M P Birla Institute of

Management, Bangalore, for his invaluable suggestions and

guidance throughout the project period which was a source of great

motivation for me.

Finally, I am indebted to all those persons who have spared

their precious time in guiding me in the preparation of my

dissertation report and have been a part of this project work.

Place:

Date: SANDEEP R. BHAT


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1. RESEARCH ABSTRACT

Stock splits are conceptually a very simple corporate event thatconsists in the division of each share into a higher number of shares of

smaller par value. These operations have long been a part of financial

markets. Non-stationarity in the distribution of security returns is a

theoretically acceptable phenomenon that is well confirmed empirically.

Less acceptable from a theoretical viewpoint is the possibility that the non-

stationarity should be associated with irrelevant events such as stock

splits.

Past research on stock splits stands evidence to the fact that stock

splits increases volatility of returns after the effective date of split. Empirical

evidences have been documented regarding the extreme behavior of stock

returns around the ex-days of stock split though going by the actual

definition of stock split there shouldnt be any change in the returns

volatility, post split.

This study investigates into the effects of stock splits on the stock

returns volatility and the liquidity of the stock. The study investigates in the

Indian context, if the simple corporate action of stock split results in

significant deviation in the stock returns and also if it leads to increase in

liquidity of stock as it is intended to be

The study presents empirical evidence on the effects of stock split

and concludes that stock splits results in significant change in returns

volatility post-split when compared to volatility before split in India. It also

concludes that liquidity after stock split increases in terms of average daily

trading volume, but decreases in terms of average daily turnover, thus not

providing enough evidence as to the increase in the liquidity of stock after

stock split.


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2. Introduction

Stock splits remain one of the most popular and least understoodphenomena in equity markets. Stock splits have confounded financial

economists for years because they merely increase the number of

outstanding shares without providing any new funds to the company and

without changing the shareholders claims on the firms assets.

Nevertheless, companies bear real costs to undertake these transactions.

Stock splits are corporate actions by which a company lowers the

face value of its stocks; thereby increasing the number of shares owned byeach shareholder. Such actions increase the number of outstanding shares

without providing any additional cash inflows to the company. Further, there

is no change in the shareholders' claims on the assets of the firm.

All the same, companies take the trouble and costs to carry out

these activities. Therefore, the question arises as to why companies resort

to stock splits? As such, stock splits world over have puzzled researchers

who tried to find out possible explanations for such actions, for years. Over

the years, enough evidence has been gathered to show that this so-called

`cosmetic change' appears to enhance the value of the firm, as positive

abnormal returns are witnessed at the announcement and execution of

stock splits. In recent years, several Indian companies, too, have resorted

to stock splits. As the subject has not received much attention amongst

researchers in India, there is very little understanding on the effects of

stock splits in the Indian context.

Before going deep into the study of effects of stock splits it is very

essential to understand the concept of stock split and other aspects related

to it.


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2.1 Meaning of Stock Split:

A stock split is a decision by the company's board of directors toincrease the number of shares that are outstanding by issuing more shares

to current shareholders. A stock split is a corporate action that increases

the number of the corporation's outstanding shares by dividing each share,

which in turn diminishes its price. The stock's market capitalization,

however, remains the same. For example, in a 2-for-1 stock split,

every shareholder with one stock is given an additional share. So, if a

company had 10 million shares outstanding before the split, it will have 20

million shares outstanding after a 2-for-1 split.

A stock's price is also affected by a stock split. After a split, the stock

price will be reduced since the number of shares outstanding has

increased. In the example of a 2-for-1 split, the share price will be halved.

Thus, although the number of outstanding shares and the stock price

change, the market capitalization remains constant.

A stock split is a procedure that increases or decreases a

corporation's total number of shares outstanding without altering the firm's

market value or the proportionate ownership interest of existing

shareholders. This action, which requires advance approval from the

company's board of directors, usually involves the issuance of additional

shares to existing stockholders.


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2.2 Different Types of Stock Splits

Different types of stock splits can have different effects based on thereasons they are implemented. Several of the concepts to understand

about this technique are literal stock splits, reverse stock splits and

dividend payouts.

2.2.1 Literal stock splits:

Because of the existence of reverse splits, it is necessary to

differentiate between the two. For example, a literal stock split occurs when

a company announces that it will do a 2-for-1 split of their common stock. If

ABC Industries has 1,000 shares of public stock at Rs.50 per share before

a 2:1 split, they will have 2,000 shares of public stock at Rs.25 per share

after.

2.2.2 Reverse splits:

Reverse stock splits are less common and have a somewhat

negative investment strategy attached to them. If the price of a stock dropstoo low, many mutual funds will not purchase them and they even run the

risk of being de-listed, or removed from the market indexes. In addition, the

low stock prices create a psychological stigma as people view them as

worthless. By doing a reverse stock split, companies can raise the stock

price by lowering the number of outstanding shares, eliminating the

problems caused by the low stock prices.

2.2.3 Dividends

Sometimes a company will choose to avoid a stock split and lower

the share prices by paying a stock dividend to shareholders. The effect of

this move is somewhat the same as a split in that it lowers the share price

since the company is worth less after the payout. This can be a good


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investment philosophy for companies that already have a large number of

available shares plus the move is usually well received by stockholders,

since this is basically investing a portion of the profits back into the people

that have already invested in the company

2.3 Reasons for Companies to Issue Stock Splits

A stock split is usually done by companies that have seen their

share price increase to levels that are either too high or are beyond the

price levels of similar companies in their sector. The primary motive is to

make shares seem more affordable to small investors even though the

underlying value of the company has not changed.

So, if the value of the stock doesn't change, what motivates a

company to split its stock? Good question. There are several reasons

companies consider carrying out this corporate action.

The first reason is psychology. As the price of a stock gets higher

and higher, some investors may feel the price is too high for them to buy, or

small investors may feel it is unaffordable. Splitting the stock brings the

share price down to a more "attractive" level. The effect here is purelypsychological. The actual value of the stock doesn't change one bit, but the

lower stock price may affect the way the stock is perceived and therefore

entice new investors. Splitting the stock also gives existing shareholders

the feeling that they suddenly have more shares than they did before, and

of course, if the prices rise, they have more stock to trade.

Another reason, and arguably a more logical one, for splitting a

stock, is to increase a stock's liquidity, which increases with the stock's

number of outstanding shares. You see, when stocks get into the

thousands of rupees per share, very large bid/ask spreads can result by

splitting shares a lower bid/ask spread is often achieved, thereby

increasing liquidity.


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Current literature has studied the reasons for splits, to a large extent,

from the perspectives of management teams (board of directors) and

market makers. This is understandably so as shareholder approval for

stock-split decisions is generally not needed because the split is affected

as a stock dividend and in most cases the number of shares outstanding

after the split is still below the maximum number of shares authorized by

the splitting companys shareholders. Almost always only board of

directors approval is necessary and enough.

Thus, most theories trying to explain the reasons-for-splits are

management centric and most of these theories also look for reasons to

explain how market-makers would benefit from split decisions. Yet, studies

documenting the changes in clientele structures following splits suggest

that one should consider existing (pre-split) and prospective (post-split)

shareholders as meaningful actors of any theory hoping to explain why

companies split their stocks.

2.4 Theories for Stock Splits

In the letter dated June 9, 2006, Terri L. Turner, Corporate Secretary

for Marriot International, Inc. tells the existing shareholders of her company

why the Board of Directors has decided to undertake a 2-for-1 stock split

with the following statement taken from the letter dated June 9, 2006 from

the Management of Marriot International, Inc. to shareholders of Marriot

International, Inc. informing them about the 2-for-1 stock split decision

undertaken by the Board of Directors on April 28, 2006, with an effective

split ex-date of June 12, 2006.

It is my pleasure to inform you that on April 28, 2006, the Board of

Directors of Marriott International, Inc. (Marriott) approved a two-for-one

split of the companys Class A common stock in the form of a stock

dividend. The stock split was declared in recognition of our strong

confidence in our companys strength, competitive position, and growth


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prospects. We also believe that the split will make a share of Marriott

common stock more affordable to a broader range of potential investors

and increase liquidityin the trading of Marriott shares.

Surveys show that managers justify splits on the basis that they

improve liquidity and marketability. Every year, on average there are one

several stock-split events taking place and most board of directors mention

similar reasons as to why they have decided to split their stock. Finance

literature has tested these and other possible explanations. The following

are the major theories that have been offered as possible reasons-for-

splits:

2.4.1 Signaling Theory:

According to the signaling hypothesis, managers declare stock splits

to convey favorable private information about the current value of the firm.

Managers obtain pertinent information about the future because of their

expertise in making operating and investment decisions. Splits credibly

signal such information if it is costly for firms without favorable information

to signal falsely.

Fama et al. (1969) theorize that management decides to undertake

a split if it believes that the future dividends of the company will be higher.

First formalization of the signaling theory, however, has been put forward

by Grinblatt, Masulis, and Titman (1984) (GMT) as a possible explanation

of the excess returns observed around split announcement and split-ex

dates. GMT (1984) hypothesize that a management team with preference

for a specific price range for its stock may choose the timing of a stock split

in order to reveal private managerial information regarding future stock-

returns.

It has been suggested that, given asymmetric information between

managers and investors, the former might use financial decisions, such as


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stock splits and stock dividend distributions, to convey favorable

information to the latter.

2.4.2 Optimal Price / Optimal Trading Range Theory:

It is a widely held belief, particularly among practitioners, that stock

splits are intended to keep the price of shares within some "optimal" range.

Specifically, investors of small means are presumably penalized by high

stock prices that deny them the economies of buying stocks in round lots.

On the other hand, wealthy investors and institutions will save brokerage

costs if securities are priced high because of the fixed per-share

transaction cost component. Therefore, the argument goes, there exists an

optimal price range that equilibrates the preferences of these classes of

investors. Managers interested in a broad and heterogeneous stockholder

base or in "wider marketability" may strive to adjust stock prices to such an

optimum by splitting their stock or distributing stock dividends. It is

interesting to note here that a survey of managers' motives for stock splits

revealed that 98.4 percent of the respondents indicated that splits make it

easier for small investors to purchase round lots, and 93.7 percent believed

that splits keep a firm's stock price in an optimal range and increase thenumber of stockholders.

2.4.3 Self Serving Management and Dispersion of Control Theory /

Enlarged Clientele:

A possible explanation for stock splits claims that a self-serving

management prefers a diffused ownership since small investors can not

exercise much control over the company and a stock split would likelyachieve this. However studies done by experts (Maloney-Mulherin (1992)

and Powell- Baker-1993-1994) show that management dispersion

hypothesis does not hold. On the contrary their results show that stock

splits accompany increases in institutional ownership for firms. It seems

that the shareholder base of a company subsequent to a split expands, yet


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the theory of a self-serving management that aims to reduce overall

institutional ownership does not hold as the empirical results disprove this

theory. Evidence against this theory is too strong. By stock splits

management reaches the goal of a more diversified Clientele, yet this

does not mean that the splitting firms end up with a more diffused

shareholder base.

2.4.4 Increased Liquidity Theory:

Researchers have also proposed the idea that companies split their

stock to achieve greater liquidity. The fundamental question in regards to

this theory is whether splits increase or decrease liquidity, and if so how

one should go about measuring liquidity around a stock split. There is also

a related question: if liquidity decreases subsequent to splits, is the

abnormal return achieved around the split event just a liquidity premium?

Past literature has attempted to measure changes in liquidity around stock

splits by analyzing the changes in three parameters: trading volume,

relative effective bid-ask spread, and number of limit orders.

After analyzing all the competing theories it can be concluded thatthe following hypothesis proposed by one expert best explains the causes

and results of stock splits in agreement with empirical measurements:

1.Signal:Management team of an exceptionally well performing company

with private information regarding the future performance of their firm

decides to split the companys shares.

This signal may be strengthened if it is accompanied with an

announcement that declares futures dividends will be larger, or that

the company, if it was not paying dividends up to that point, will

initiate giving dividends

This signal may also be strengthened if the company went through a

previous stock split event. The market would expect the companys

stock to split to the post-split price level of the previous split event.


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If the split factor is bigger than this expected level future expected

returns are even higher

The signal is costly to the firm. There are two cost components

o Relative bid-ask spread increases due to the split and this

results in higher order processing costs, which in turn reduces

liquidity

o Pre-split shareholders incur higher aggregate costs resulting

from per share based commission costs.

2. Promotion: As per-share based commissions and order processing

costs will increase following the split market-maker has a lot to gain from

increased trading. Market maker heavily promotes the stock to add new

clientele.

3. Enlarged Clientele Base: With more coverage prospective shareholder

buys the stock, based on the management teams signal and the market

makers information dissemination in order to reap the benefits of excess

returns surrounding split announcement and split-ex dates. Prospect

expects that these excess returns will not be negated in the year

subsequent to the split ex-date. Furthermore prospect further diversifies hisportfolio with non-negative long-run excess returns. Prospect can be a

small investor or an institutional investor, but in most likelihood he is a

small investor.

4. Increased Number of Trades: Companys shareholder base is

enlarged; management has a more diversified clientele making their jobs

more secure. Furthermore the management has solidified the gains of the

exceptional returns period with this new clientele base. Shareholders earnexcess returns around the announcement and ex-dates and keep their

gains in the long-run. Market makers increase their revenues. At the same

time as the number of small shareholders increases so does the number of

small trades and aggregate number of trades. Due to the increase in

number of trades stock return volatility also goes up around the stock split


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event. As the split is costly, this signal has value over the year following the

split thus the number of trades in the subsequent year doesnt decrease.

Market makers promotion efforts also help sustain the level of trading

activity. Hence the increase return volatility is not temporary and is

sustained for over a year.

2.5 Advantages of Stock Splits for Investors

There are plenty of arguments over whether a stock split is an

advantage or disadvantage to investors. One side says a stock split is a

good buying indicator, signaling that the company's share price is

increasing and therefore doing very well. This may be true, but on the otherhand, you can't get around the fact that a stock split has no affect on the

fundamental value of the stock and therefore poses no real advantage to

investors. Despite this fact many experts have taken note of the often

positive sentiment surrounding a stock split. Critics would say that this

strategy is by no means a time-tested one and questionably successful at

best.

2.6 Actors Affected by Stock Split Decisions

A stock-split decision concerns four major parties. These are the

following:

1. The Board of Directors (in some cases the management team) of

the splitting firm (Decision-maker, possible beneficiary)

2. Market makers (possible beneficiary and the intermediary between

the management and Prospective shareholders)

3. Existing shareholders of the splitting firm (pre-split)

4. Prospective shareholders of the splitting firm (post-split or post-

announcement)


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2.7 Background of the study:

In an efficient market, the market value of a firms equity should beindependent of the number of shares it has outstanding. Therefore one

should expect to see no change in the distribution of stock returns around

ex-dates of stock splits. The ex-date for a stock split should simply involve

a change in the number of shares outstanding along with a change in the

level of the stock price. There should be no change in the distribution of

stock returns around ex dates of stock splits.

Previous research has documented changes in stock return

distributions. Researches have proved abnormal returns around

announcement days and ex-dates of splits. Several researches have also

proved the occurrence of short-term excess returns following stock splits. In

addition to changes in the distribution of stock returns around ex-dates of

stock splits, some experts through their research have showed that stock

return volatilities jump significantly after stock splits as well and that these

volatility changes hold for more than a year subsequent to the split ex date.

While these facts stand, there is no convincing theory that

affirmatively explains why companies continue to split their stocks, and

furthermore the cause and effect of the increase in stock return volatility

following the split ex-date remains uncertain. In recent years, several Indian

companies, too, have resorted to stock splits. As the subject has not

received much attention amongst researchers in India, there is very little

understanding on the effects of stock splits in the Indian context.

Therefore, this research dissertation has been conducted to analyze

and interpret the effect of stock split on the stock returns volatility and the

liquidity in the Indian context.


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2.8 Problem Statement

In a perfect market, the market value of a firm's equity isindependent of the number of shares outstanding. Therefore the ex-date for

stock split should simply involve a change in the number of shares

outstanding along with a change in the level of the stock price. There

should be no change in the distribution of stock returns around ex-dates of

stock dividends and stock splits. Previous research has documented

changes in stock return distributions around these ex-dates, i.e. post split

dates. This suggests that there is an implied volatility in stock returns after

the stock splits.

2.9 Research Objectives

The present study has been undertaken with the following objectives.

To examine the effects of stock splits on equity prices and returns of

the companies.

To investigate the changes in volatility of returns around the ex-

dates.

To investigate the effect of stock splits on liquidity and trading

volumes post split.


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2.10 Hypothesis

H0: (Null hypothesis), there is no change in return volatility post-split,when compared with pre-split

H0: (Null hypothesis), there is no increase in liquidity post stock split,

when compared to pre stock split liquidity

H1: (Alternative Hypothesis), there is a change in return volatility

post-split compared with pre-split.

H1: (Alternative Hypothesis), there is an increase in liquidity post

stock split, when compared to pre stock split liquidity.

2.11 Scope of the Study

The scope of the research investigation is restricted only to the

following:

1. The study focuses on investigating the effect of stock split on the

returns volatility. It does not provide any evidence as to the

movement of returns upwards or downwards or positive returns or

negative returns earned due to stock split. Thus, it restricts itself to

the investigation of post split volatility of returns.

2. The study does not take into consideration the ratio of the split while

investigating the effects of stock split on distribution of returns

around ex-split date. Thus the effect of split ratio on returns volatility

cannot be judged from this study.

3. The study does not investigate the reasons or factors responsible for

the change in returns volatility if there exists any. It explains only the

existence or non-existence of returns volatility after stock split.


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2.12 Significance of the Study

This study is essential as there has been evidence in the foreign

market about the existence of volatility around the ex-dates. But

there has been no strong empirical evidence in the Indian context

concerning the Indian companies if stock splits really imply changes

in returns distribution around ex-dates.

The study is essential to analyze if there exists a change in volatility

post split, i.e. ex-dates for Indian companies that have resorted to

stock split and has it resulted in change in return distribution around

the ex-dates for the investors. The study is essential to understand the impact of stock split on the

returns volatility and liquidity in the Indian context and help

companies and investors in taking rational decisions pertaining to

stock splits.

2.13 Importance of the Study

The investigation can be used by the company to decide upon the

action to split to control the liquidity and returns volatility around

stock splits.

The investigation can also be used by the investors to decide upon

the timing of their investment while dealing with the stocks going for

the split.

The investigation can also be used by the investors to understand

the impact of stock splits on the returns volatility and liquidity and

plan the investment accordingly.


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2.14 Research Gap

In recent years, several Indian companies, too, have resorted tostock splits. There is no convincing evidence that affirmatively explains the

cause and effect of the increase in stock return volatility following the split

ex-date. As the subject has not received much attention amongst

researchers in India, there is very little understanding on the effects of

stock splits in the Indian context.

Therefore, this research dissertation has been conducted to

analyze and interpret the effect of stock split on the stock returns volatility

and the liquidity in the Indian context.

2.15 Limitations of the Study

The study confines itself to the data of companies which have gone

for stock splits between the years 2000 to 2007. The stock splits

before the period have not been taken into consideration.

Due to time constraint the study has been confined to only 28

companies from four different sectors, thus limiting the scope.


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2.16 Operational Definitions

1. 2-for-1 split: If the number of pre-split outstanding shares is N, aftera 2-for-1 split the number of outstanding shares rises to 2*N.

2. Split Ratio: If split ratio is x% and the number of total outstanding

shares before the split is N, then the number of total outstanding

shares post-split is (1+x%)*N.

3. Announcement date: The day on which the board of directors of

the company decides and announces to split the common stock ofthe company on a certain future date is called the announcement

day. The announcement of a split is an unanticipated event in which

the firm announces the size and date of the split.

4. Ex-date: It is the date on which the stock is split. In other words the

day on which the stock split is brought into effect and the price of the

stock is decreased by the ratio pre-determined is termed as Ex-

dates. On the split date (or split ex-date), the stock begins trading at

the new, split-adjusted price.

5. Reverse Split:A reverse split occurs when a company reduces the

number of its shares outstanding by a pre-determined value. For

example, if a firm has 100 shares outstanding pre-reverse split and

its reverse-split factor is 1-for-1 then the total number of shares

outstanding post-event is 50. (100 / (1+1) = 50)


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3. Review of Literature

This section of the report would deal with the literature available withrespect to stock splits proposed by experts in the field of finance and their

findings with respect to effects of stock splits on returns volatility post split

or split ex-dates.

3.1 Long Term Excess Returns Preceding Split Announcements:

The first empirical study on stock splits was done by Fama, Fisher,

Jensen and Roll in 1969. In this paper Fama et al. (1969) examine 940

stock splits over the period 19271959. Using a market model and monthlyreturns they find on average an abnormal excess return of 34.07% over the

29 months preceding the split date for splitting companies. Fama et al. find

no abnormal returns after the ex-split date.

Lakonishok and Lev (1987) expand on the Fama et al. (1969) paper

and define split events around announcement dates using a sample size of

1015 in the time frame from 1963 to 1982. They also find significant

abnormal returns for splitting firms preceding the splits (on average they

find 53% excess returns in aggregate during the 5 years preceding the split

announcement).

Further validating these studies Asquith et al. (1989) find statistically

significant market adjusted excess returns of 56.8% for splitting firms for

the 240 day time period preceding a split in the 1970-1980 time period.

McNichols and Dravid (1990), and Maloney and Mulherin (1992) also find

similar results and these numbers are also confirmed by later studies such

as Ikenberry, Rankine, and Stice (1996) and Desai and Jain (1997) for

different time-periods. These studies confirm without a doubt that split

events are preceded by very strong performances for the splitting

companies as they compare to non-splitting firms.


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Earlier papers by Ohlson and Penman (1985), Dravid (1987),

Dubofsky (1991), and Koski (1998) have documented a significant increase

in return volatility of US-based equities following stock splits with split

factors larger than 5-for-4. Furthermore Reboredo (2003) has documented

similar results for 2-for-1 and larger stock splits that take place in the

Spanish Stock Market, Bolsa de Madrid for the 1998-1999 time period.

Ohlson and Penman show that the increase in return volatility is

permanent as there is no fading in the volatility value one year following the

split. This increase also is quite large and Ohlson and Penman find a mean

increase of 30% in the standard deviation of returns. Some in the literature

have related this huge increase in return volatility to measurement error.

Blume and Stambaugh (1983), Gottlieb and Kalay (1985), and

Amihud and Mendelson (1987) show that bid-ask spreads and price

discreteness induce an upward bias in the estimated volatility of observed

stock returns. It has been suggested since such measurement biases

increase at lower price levels the increase in return volatility around splits

may be due to measurement error.

In response to this possibility Koski (1998) shows that almost none

of the observed increase in realized volatility is due to bid-ask spreads or

price discreteness. Furthermore, in their recent paper Julio and Deng

(2006) show a clear response to stock split announcements in the options

market and provide additional evidence that changes in volatility around the

split ex-date are real and not due to error in the measurement procedure. In

this section these empirical results will be explained and the measurement

techniques used carefully.


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3.2 Standard Method of Measuring Realized Volatility Increases

Around Split Ex-Dates:

In order to test for changes in volatility subsequent to a split Ohlsonand Penman (1985) used a non-parametric test. In order to test for

changes in volatility subsequent to a split most studies use a non

parametric test proposed by Ohlson and Penman (1985). Dravid (1987),

Dubofsky (1991), Koski (1998), Reboredo (2003) all use the same

methodology

The Methodology:

The binomial proportionality statistic, P, where P=Pr(x2 > x1) isapplied to test the hypothesis:

H0: P = 0.05 (H), no change in return volatility post-split, when

compared with pre-split

H1: P= 0.05 (A), there is change in return volatility post-split

compared with pre-split

Where x1 and x2 denote pre and post split values for the variable of

interest.

x1 and x2 in thiscase denote daily stock return volatility.

Since squared values of expected daily returns (E2[r]) are about

1/1000th of expected squared daily returns (E[r2]), Ohlson and

Penman approximate for daily return volatilities with expected

squared daily returns. Hence x1 and x2 simplify to pre and post-split

values of E[r2].

To control for day of the week effects on the variables of interest,

Ohlson and Penman (1985) compare pre- and post-split squared daily

returns by matching the squared return for the first trading day following the

split declaration date with the squared return for the first same day of the


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week following the split date (for example Monday to Monday). This

process is repeated for the second day, and so on until the day just prior to

the split date for the whole time period between split announcement and

split ex-date. The number of comparisons for each split is equivalent to the

number of trading days between the declaration and split dates.

The value of the binomial z-statistic is used for statistical

significance. With this result one can calculate the change in stock return

volatility subsequent to the split as:

Percent Change in Volatility = (post split-pre-split)

-Pre-split

Where = standard deviation

Conclusion:

The study conducted by Ohlson and Penman documents that, for

stock splits larger than two-for-one (one hundred percent), the volatility of

stock returns after the ex-split date is significantly higher than the pre-split

volatility. The increase in the standard deviation of daily returns is of theorder of twenty-eight to thirty-five percent and persists for as long as a full

year after the ex-date.'

Ohlson and Penman show that the increase in return volatility is

permanent as there is no fading in the volatility value one year following the

split. This increase also is quite large and Ohlson and Penman find a mean

increase of 30% in the standard deviation of returns.


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3.3 Stock Splits, Volatility Increases, and Implied Volatilities

A study on stock splits and its implied volatilities and increase in

volatility around stock split conducted by Mr. Aamir M. Sheikh, published

in the Journal of Finance, Vol. 44, No. 5. (Dec., 1989), presents a test of

the efficiency of the Chicago Board Options Exchange, relative to post-split

increases in the volatility of common stocks. The Black-Scholes and Roll

option pricing formulas are used to examine the behavior of implied

standard deviations (ISDs) around split announcement and ex-dates.

In this paper, he examines the announcement and ex-date behavior

of return volatilities implied by call prices, thereby controlling for stock price

and maturity changes. The Black-Scholes (1973) and Roll (1977) call

option pricing formulas are used to solve for implied standard deviations

(ISDs) of stock returns.

Methodology:

Data:

The study includes all CBOE option able stocks that split between

December 1, 1976 and December 31, 1983, had split factors larger than

0.25, and did not undergo major structural changes, such as mergers, in

the nine months following the split. This leads to a sample of 83 stock

splits, of which 30 had split factors smaller than one. The smallest length of

time between announcement and ex-dates was 34 days, the largest 165

days. The splits were identified from the CRSP Monthly Master file and

checked against a list of stocks with CBOE options.


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Tests:

Because the results may be sensitive to the way ISDs are

aggregated, three different measures are used to test the effect of the split

announcement and ex-dates on anticipated volatility. The first, anticipated

volatility, uses the sample mean of the ISDs of each stock to obtain a single

ISD for that stock both before and after the event; e.g., all the ISDs

obtained from IBM options in the two weeks before the split announcement

are averaged into a single pre-announcement ISD for IBM, and all the ISDs

for IBM in the two weeks after the announcement are averaged into a

single post-announcement ISD for IBM. Percent changes in anticipated

volatility are then obtained for each stock, and the paired-sample sign test

and the Wilcoxon signedrank test are applied to these percent changes

across the sample of stocks. The null hypothesis of no change in ISDs is

tested against the one-sided alternative of an increase in ISDs.

Results:

The post-split standard deviation estimated from daily returns was

found to be larger than the pre-split estimated standard deviation in 55 out

of 83 cases, with an associated z-statistic of 2.85, which is significantlypositive at the 1% level. The median change in estimated standard

deviations was 20.6%. Thus, consistent with the findings of Ohlson and

Penman, the split sample exhibits a significant ex-date increase in return

variances.

3.4 Firm and Split Characteristics and Realized Volatility Changes

around Stock Split Ex-Dates:

Julio and Deng (2006) incorporated firm characteristics into their

split dataset. They report that small splits (factors less than 50%)

experience no significant increase in realized volatility at the ex-date, while

volatility increases for medium-sized splits (with factors between 50% and

200%) are the largest and significant. For very large splits (split factor


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greater than 200%), the change in volatility is still significant but not as

large as for the medium-sized splits.

3.5 Risk Changes Induced by Stock Splits:

Dubofsky (1991) conducted a study that was basically an extension

of a previous study by Ohlson and Penman (1985). In contrast to these

authors, Dubofsky focused on both NYSE stocks and AMEX stocks and

used a large time period from July 2, 1962 to December 31, 1987. The

results obtained for the two exchanges lead the author to conclude there

was a more pronounced increase in variance connected to NYSE stocks.

Desai et al. (1998) conducted a more in-depth study of volatility

changes. These authors reported a significant increase in volatility following

the split. Their conclusions were stronger than those of Dubofski (1991)

since their calculations took into account the effects of price discreteness in

the bid-ask bounce. They reported an increase in the relative bid-ask

spread, which in turn lead to the need to estimate volatility with more

complex procedures.

3.6 Intra-Daily Estimation of Realized Volatility Increases around SplitEx-Dates:

Squared daily returns have quite often been used as a measure of

volatility. However, Anderson and Bollerslev (1998) demonstrate that the

incorporation of high-frequency data vastly improves ex-post volatility

measurements.

Poteshman, another expert shows that almost half of the forecastingbias in the S&P 500 index (SPX) options market is eliminated if one

estimates realized volatility using intraday observations on SPX futures that

are sampled every five minutes rather than using daily close values.

Julio and Deng (2006) use NYSE TAQ database and observe prices

for 16 splitting stocks every 5 minutes in the 1996-2003 time period.


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The Methodology:

They define ph,tbe the natural logarithm of the stock price at time h

on date t, where h=1, ,H and t =1, ,T.

H represents the number of intra-daily observations used per day

and

Tis the number of days in the sampling period.

They calculate a series of intra-day log returns

rh,t = ph,t ph- 1,t and

Then using the squared values of these intra-day log returns they

find an unbiased estimator of the population return variance SD t2 :

St2 , where S2t is as follows:

SD = Standard Deviation of daily returns

The Results:

With this methodology Julio and Deng (2006) calculate 2 average

intra-day return volatilities for each split event: One for the 20 days

preceding the split ex-date and the other for the 20 days subsequent to the

split ex-date. On average for all split events they find a statistically

meaningful 32.83% increase in realized volatility around the ex-date. This

value is similar in magnitude to the change reported by earlier studies.


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4. Research Design and Research Methodology

4.1 Type of Research

The research conducted in this case is of a quantitative type of

research wherein the data collected is basically of quantitative type in the

form of share prices of the stocks before and after the split. The share

prices thus collected have been used to calculate price relatives and daily

returns.

The results will be presented in terms of quantitative data and

interpretation of the data analysis will be done using the quantitative

parameters. Thus, this research is a quantitative research.

4.2 Sources of data

All the data concerning the stock split and share prices for the study

are collected through websites like capital online and NSE-India.

4.3 Sampling Technique

The sampling technique used in this research is random sampling

technique as each company had an equal opportunity of making it to the

final sample. The population size is finite as the companies qualifying for

the research are the companies that have resorted to stock splits during

2000 to 2007. Thus, the sampling technique used is the random samplingtechnique.


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4.4 Sample Size

The sample includes 28 companies from different sectors whichhave resorted to stock splits during the period 2000-2007. Thus, the

sample size has been restricted to 28 for this research.

4.5 Data Collection

Information about the companies that have resorted to stock split

during the period 2000-2007 has been gathered from Capital online plus

database. The dates of stock split could be gathered from the same

database.

The information regarding the share price before and after stock split

has been gathered from the NSE website. The closing price of the shares

of the respective companies has been taken into consideration for the

analysis.

For the purpose of this analysis and hypothesis testing, the share

prices of fifteen days duration before split and after split has been taken

into consideration, assuming that the fifteen days price fluctuations would

give a considerable idea about the returns volatility before and after split.


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4.6 Data processing and analysis plan

Methodology and tools used for testing of hypothesis: The price relative of stock based on daily closing price of the stock has

been calculated using the formula:

(Pt/Pt-1)

Where:

Pt =Price of the stock at the time t

Pt-1= Price of the stock at the time t-1

The daily returns have been calculated there from using the log

naturals, i.e.

Ln(Pt/Pt-1)

The mean and standard deviation and the volatility of the daily returns

have been determined using the Excel Application.

The percentage change in the volatility of daily returns has been

determined using the formula:

Post-split of returns Pre-split of returns

Pre-split of returns

Where = standard deviation

t Test:

t test is used to test for the significance of differences of means of

daily returns and to find out if there is any significant change in volatility of

returns after stock split.

To find whether there is significant difference in mean before and

after the event the t test is conducted at 5% level of significance.


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Formula Used:

The formula used for the calculation of t statistic is as under:

t = [(sample mean 1-sample mean 2)-(mean of population 1-

mean of population 2)]

Square Root [Pooled ^2(1/n1 + 1/n2)]

Pooled SD^2 = [(n1-1) 1^2 + (n2 1) 2^2] / [(n1 - 1) + (n2 1)]

Where:

Pooled SD^2 = Pooled variance of the means of daily returns before

split and after split

n1 = Number of sample before split

n2 = number of sample after split

SD = standard deviation

P-value approach:

The P-value approach has been followed to decide upon the

acceptance and rejection of the hypothesis.

The P-value has been determined using the Excel application.

If P-value < , we reject Ho at level of significance.

If P-value > , we fail to reject Ho at level of significance.

Post Split Liquidity Measurement:

In order to examine the effect of stock splits on liquidity, two

measures of trading activity were used:

(a) Trading volume which is the daily number of shares traded,

(b) Daily turnover

The percentage change in trading volume and turnover has been

determined using the excel application.


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Paired t test:

To test the significance of change in liquidity after stock split Paired

t-test has been used at 5 percent level of significance.

Formula Used:

The formula used for the calculation of t statistic is as under:

D 0t =

diffnWhere:

D = Mean of differences between observations

diff= Standard deviations of differences

n = Number of matched pairs

Rejection region method:

Rejection region method has been followed to decide upon the

acceptance or rejection of the hypothesis in paired t-test.

Regression analysis:

A regression analysis has been conducted to determine the co-efficient

of determination of the volatility in the returns, post split.

The regression analysis has been conducted using the Excel

application.


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Steps followed:

Price relatives were calculated using the fifteen day share prices,

both before and after split

Daily returns were determined using the log naturals

Means and standard deviations of the daily returns before and after

split were then calculated.

Using the means of daily returns before and after split

t-test has been applied to test the significance of difference between

the means before and after split.

t-cal was calculated using the excel application

Based on the P-value the acceptance and rejection of hypothesiswas decided upon.

Based on the regression analysis the cause for the volatility in the

post split returns was determined.

The effect of stock split on liquidity was measured by determining

the percentage change in average daily trading volume and average

daily turnover after split when compared to trading volume and

turnover before split.

The significance of increase in the liquidity was then tested using the

paired t-test and hypothesis was accepted or rejected based on the

tabulated value of students t-distribution.

Tools and software used for data analysis:

All the calculations pertaining to data analysis has been done using

the MS-Excel application software.


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4.7 Chapter Scheme

This report has been presented in seven chapters:

Chapter 1 presents the research extract

Chapter 2 deals with the conceptual framework of stock splits. It

throws some light on the theoretical aspects of stock split. It also

presents the statement of problem, research objectives, significance

of the study, scope of the study, importance, limitations of the study

and some operational definitions.

Chapter 3 deals with the review of literature and presents the

analysis of different researches conducted by different authors andtheir results.

Chapter 4 deals with the research design and the methodology

followed. It highlights the research design implemented in this study

and the tools and methods used for data analysis and interpretation.

Chapter 5 deals with theprofile of the sample industry. It presents in

brief, information about the industry from which the sample

companies have been selected.

Chapter 6 deals with data analysis and interpretation. It presents

the data analysis and interpretations made there from and testing of

significance of hypothesis.

Chapter 7 deals with the research findings, conclusions,

implications and suggestions for future research.


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5. Industry Profile

The sample of 28 companies includes companies that have resortedto stock splits during the period 2000-2007. The companies belong to

different sectors. The sectors that the companies belong to in this research

are:

Pharmaceuticals Industry - Indian - Bulk Drugs & Formulation

Large

Construction Industry Civil Turnkey large, small and medium

Petrochemicals Industry

Information Technology Industry - Hardware and Software.

5.1 Pharmaceutical Industry:

The Indian Pharmaceutical Industry today is in the front rank of

Indias science-based industries with wide ranging capabilities in the

complex field of drug manufacture and technology. A highly organized

sector, the Indian Pharma Industry is estimated to be worth $ 4.5 billion,

growing at about 8 to 9 percent annually. It ranks very high in the third

world, in terms of technology, quality and range of medicines

manufactured. From simple headache pills to sophisticated antibiotics and

complex cardiac compounds, almost every type of medicine is now made

indigenously.

The Indian Pharmaceutical sector is highly fragmented with more

than 20,000 registered units. It has expanded drastically in the last two

decades. The leading 250 pharmaceutical companies control 70% of the

market with market leader holding nearly 7% of the market share. It is an

extremely fragmented market with severe price competition and

government price control.


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The pharmaceutical industry in India meets around 70% of the

country's demand for bulk drugs, drug intermediates, pharmaceutical

formulations, chemicals, tablets, capsules, orals and injectibles. There are

about 250 large units and about 8000 Small Scale Units, which form the

core of the pharmaceutical industry in India (including 5 Central Public

Sector Units). These units produce the complete range of pharmaceutical

formulations, i.e., medicines ready for consumption by patients and about

350 bulk drugs, i.e., chemicals having therapeutic value and used for

production of pharmaceutical formulations.

5.1.1 ADVANTAGE INDIA:

Competent workforce: India has a pool of personnel with high managerial

and technical competence and also skilled workforce. It has an educated

work force and English is commonly used. Professional services are easily

available.

Cost-effective chemical synthesis: Its track record of development,

particularly in the area of improved cost-beneficial chemical synthesis for

various drug molecules is excellent. It provides a wide variety of bulk drugsand exports sophisticated bulk drugs.

Legal & Financial Framework: India has a 53 year old democracy and

hence has a solid legal framework and strong financial markets. There is

already an established international industry and business community.

Information & Technology: It has a good network of world-class

educational institutions and established strengths in InformationTechnology.


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Globalization: The country is committed to a free market economy

and globalization. Above all, it has a 70 million middle class market, which

is continuously growing.

Consolidation: For the first time in many years, the international

pharmaceutical industry is finding great opportunities in India. The process

of consolidation, which has become a generalized phenomenon in the

world pharmaceutical industry, has started taking place in India.

5.1.2 Growth Prospects:

The industry's exports were worth more than $3.75 billion in 2006-07

and they have been growing at a compound annual rate of 22.7 percent

over the last few years, according to the government's draft National

Pharmaceuticals Policy for 2006, published in January 2006. The Policy

estimates that, by the year 2010, the industry has the potential to achieve

$22.40 billion in formulations, with bulk drug production going up from

$1.79 billion to $5.60 billion: India's rich human capital is believed to be the

strongest asset for this knowledge-led industry. Various studies show that

the scientific talent pool of 4 million Indians is the second-largest English-speaking group worldwide, after the USA.

5.1.3 Top Ten Indian Pharmaceutical Companies: The top ten Indian

Pharmaceutical Companies are:

Aurobindo Pharma

Aventis Pharma

Cipla

Dr. Reddys Laboratories

Lupin

Nicholos Piramal

Ranbaxy Laboratoriess

Sun Pharma


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Wockhardt

Zydus Cadila

5.2 Construction Industry:

5.2.1 Industry Definition

The construction industry comprises establishments that are

primarily engaged in theconstruction of buildings or engineering projects

(e.g., highways and utility systems). This mayinclude new work, additions,

alterations, or maintenance and repairs. The construction industry is

divided into three major sectors. The first is the construction of buildings

(both residential andnonresidential). The second involves heavy and civil

engineering construction such as utility systems, land subdivision, and

highways, streets, and bridges. Firms in these first two sectors areprimarily

engaged in contracts that include responsibility for all aspects of individual

projects andare commonly know as general contractors. The third major

sector of the construction industry includes establishments in the specialty

trades, which are primarily engaged in activities to produce a specific

component (e.g. masonry, painting, and electrical work) of a project.

5.2.2 Industry Profile

The construction industry is the second largest industry in India after

agriculture. It accounts for about 11% of Indias GDP. It makes significant

contribution to the national economy and provides employment to large

number of people.

There are mainly three segments in the construction industry like

real estate construction which includes residential and commercial

construction; infrastructure building which includes roads, railways, power

etc; and industrial construction that consists of oil and gas refineries,

pipelines, textiles etc.


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According to a study by ASSOCHAM, the burgeoning Indian

construction industry, currently worth $70 billion, will rise to US$120 billion

by 2010.

5.2.3 Industry Trends

The Indian construction industry recorded a consistent double-digit

year-on-year growth of 12% during 2000-2005, and is expected to grow at

25-30% during 2005-2010. The key drivers of this growth are government

investment in infrastructure creation and real estate demand in the

residential and industrial sectors.

The industry is experiencing increasing polarization between large

and small players. The top 10 players, such as Gammon India, Patel

Engineering Limited (PEL), and Hindustan Construction Company (HCC),

contributed to 75% of the total revenue in 2005.

These players are increasing their market share through large-scale

contracts, joint ventures and foreign operations. Though an increasing

number of small players are also entering the market, most of them do not

have the resources to bid for big contracts.

The Indian construction industry is facing the challenges of outdated

land and property ownership regulations, infrastructural bottlenecks and a

shortage of civil engineers.

5.2.4 Top players

The few heavy weights in the Indian construction Industry are:

Larsen & Toubro Limited

Jaiprakash Associates

Hindustan Construction Company

Gammon India

Royal Indian Raj International Corporation (RIRIC) etc.


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5.3 Petrochemicals Industry

Petrochemicals are useful chemicals obtained from crackingpetroleum feedstock. The three main petrochemicals produced are

ethylene, propylene and benzene.

The Indian petrochemicals industry is small by international

standards, with ethylene capacity accounting for only 2.2% of global. The

Indian polymers industry is also small, accounting for only around 2.5% of

the global production. India was ranked 13th in the world as on January 1,

2005 in terms of ethylene capacity. The capacity had registered increasesduring early 2000 following the commissioning of crackers of Haldia

Petrochemicals Limited (HPL) and Indian Petrochemicals Corporation

Limited (IPCL).

The petrochemical industry is a capital-intensive and high-volumes

industry. The demand elasticity is high in petrochemicals. The raw material

cost is the major expense any petrochemical industry has to endure. The

raw material cost generally accounts for 50 per cent of the selling price.

There are only three major players: Reliance Industries, NOCIL and

IPCL. All the three companies have fully integrated plants. As the domestic

market is closely linked to global events and occurrences, some companies

will witness squeezing margins, owing to depressed global petrochemical

prices.

Polymers constitute over 70 per cent of petrochemicals produced.

The largest end-user of plastics includes packaging industry, PVC pipes

and fittings industry and molded luggage industry. In the last five years,

these industries have grown at the rate of 16-18 per cent per annum. The

domestic plastic processing industry is highly fragmented and scattered.

There are more than 15,000 manufacturing units. Most of them are small-


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scale industries. The medium scale operators produce almost 60 per cent

of the total production. The unorganized sector, with the 40 per cent of the

balance production, is an important player. The total capacity of the

industry to process polymers is estimated at 4.8 million tpa.

Although, by global standards, Indian polymers (the key

petrochemical product) demand is small, it is amongst the fastest growing

countries in the world. In the past, because of higher GDP growth than the

world GDP growth and higher presence of the traditional materials

(therefore, more potential for substitution by polymers), India has shown a

significantly higher growth rate in polymer consumption in the last five

years. The growth rate in Indian polymer consumption is even higher than

China and other key Asian Economies.

5.3.1 Players

The Indian basic petrochemicals manufacturers are integrated from

basic petrochemical to polymers, manmade fibers, fiber intermediates and

downstream petrochemical production. Non integrated players are present

in production of polyvinyl chloride, polystyrene, manmade fibers and

products such as phenol, linear alkyl benzene, phthalic anhydride etc.

The Indian polymers market is dominated by local players, with the

foreign stake holding in Indian polymer plants restricted to Haldia

Petrochemicals Limited (HPL), BASF Styrenics India Private Limited

(BSIL), and LG Polymers Limited. HPL is a joint sector company in which

Chatterjee Petrochem, Mauritius, has a 43% stake along with the West

Bengal Industrial Development Corporation. As for BSIL, it is a 100%

subsidiary of BASF AG, a multinational chemicals company and the worlds

second largest PS producer, while LG Polymers is a wholly-owned

subsidiary of the LG Group, South Korea. The production of polyethylene

and polypropylene in India is accounted for almost in their entirety by

companies with integrated petrochemical complexes. Such companies are

Reliance Industries Limited (RIL), Indian Petrochemicals Corporation


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Limited (IPCL), Haldia Petrochemicals Limited (HPL), and Gas Authority of

India Limited (GAIL).

5.4 Information Technology Industry:

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 the global markets. IT industry in India comprises of software

industry, hardware 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 favorite destination

for IT-enabled services.

The IT/ITES industrys contribution to the countrys GDP has been

steadily increasing from a share of 1.2% in FY98 to 5.2% in FY07; it has

contributed to foreign exchange reserves of the country by increasing

exports by almost 36%.

Software and IT enabled services have emerged as a niche sector

for India. This was one of the fastest growing sectors in the last decade

with a compounded annual growth rate exceeding 50 percent.

Software service exports increased from US$ 0.5 millions in 1990 to

$5.9 billion in 2000-01 to $23.6 billion in 2005-06 recording a 34% growth.

The major players in this sector currently are:

Infosys

TCS

Wipro

HCL

Satyam, etc.


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6. Data Analysis, Interpretation and Presentation

This section of the report deals with the data analysis, interpretationand presentation of results of the research. This part has been divided into

two main sections.

The first section presents:

The determination of daily stock returns of the sample companies.

The determination of percentage change in volatility after stock split

and the inferences drawn there upon.

Testing of significance of hypothesis concerning the effect of stock

split on returns volatility and the inferences drawn there upon.

The regression analysis and the inferences drawn there upon.

The second section presents:

The measurement of effect of stock split on liquidity and inferences

drawn there upon.


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6.1 Hypothesis

H0: (Null hypothesis), there is no change in return volatility post-split,

when compared with pre-split

H0: (Null hypothesis), there is no increase in liquidity post stock split,

when compared to pre stock split liquidity

H1: (Alternative Hypothesis), there is a change in return volatility

post-split compared with pre-split.

H1: (Alternative Hypothesis), there is an increase in liquidity post

stock split, when compared to pre stock split liquidity.


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6.2 Determination of daily returns of stock

Alembic Pharma

Table 1.0: Daily Returns before ex-dates of stock split

Dates

Closingstockprice

Pricerelative(Si / Si-1)

Daily returns(ln of Si / Si-1)

1-Sep-06 340.1

4-Sep-06 344.4 1.01264 0.01256

5-Sep-06 353.6 1.02671 0.02636

6-Sep-06 378.1 1.06929 0.06699

7-Sep-06 365.25 0.96601 -0.03458

8-Sep-06 356.95 0.97728 -0.02299

11-Sep-06 354.8 0.99398 -0.00604

12-Sep-06 354.45 0.99901 -0.0009913-Sep-06 354.8 1.00099 0.00099

14-Sep-06 365.65 1.03058 0.03012

15-Sep-06 368.4 1.00752 0.00749

18-Sep-06 372.25 1.01045 0.01040

19-Sep-06 375.15 1.00779 0.00776

20-Sep-06 377.75 1.00693 0.00691

21-Sep-06 380.5 1.00728 0.00725

Table 1.1: Daily Returns after ex-dates of stock split

Dates

Closingstockprice


Daily returns(ln of Si / Si-1)

26-Sep-06 72.9

27-Sep-06 69.65 0.95542 -0.04561

28-Sep-06 69.45 0.99713 -0.00288

29-Sep-06 69.65 1.00288 0.00288

3-Oct-06 69.65 1.00000 0.00000

4-Oct-06 67.15 0.96411 -0.03655

5-Oct-06 68.75 1.02383 0.02355

6-Oct-06 67.25 0.97818 -0.02206

9-Oct-06 66.65 0.99108 -0.00896

10-Oct-06 66.2 0.99325 -0.00677

11-Oct-06 64.65 0.97659 -0.02369

12-Oct-06 63.85 0.98763 -0.01245

13-Oct-06 64.6 1.01175 0.01168

16-Oct-06 65.95 1.02090 0.02068

17-Oct-06 68.05 1.03184 0.03135


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Aurobindo Pharma


Dates

Closingstockprice


Daily return(ln of Si / Si-1)

1-Oct-03 665.5

3-Oct-03 655 0.98422 -0.01590

6-Oct-03 654.5 0.99924 -0.00076

7-Oct-03 669.8 1.02338 0.02311

8-Oct-03 691.35 1.03217 0.03167

9-Oct-03 692.6 1.00181 0.00181

10-Oct-03 677 0.97748 -0.02278

13-Oct-03 690.85 1.02046 0.02025

14-Oct-03 660.95 0.95672 -0.04424

15-Oct-03 672.35 1.01725 0.01710

16-Oct-03 664.05 0.98766 -0.01242

17-Oct-03 663.75 0.99955 -0.00045

20-Oct-03 640.05 0.96429 -0.03636

21-Oct-03 596.25 0.93157 -0.07089

22-Oct-03 594.3 0.99673 -0.00328


Dates

Closing

stockprice

Price

relative(Si / Si-1)


25-Oct-03 309.2

27-Oct-03 299.1 0.96734 -0.03321

28-Oct-03 298.25 0.99716 -0.00285

29-Oct-03 297.6 0.99782 -0.00218

30-Oct-03 303.8 1.02083 0.02062

31-Oct-03 327.2 1.07702 0.07420

3-Nov-03 340.35 1.04019 0.03940

4-Nov-03 335.7 0.98634 -0.01376

5-Nov-03 325.1 0.96842 -0.03209

6-Nov-03 316 0.97201 -0.02839

7-Nov-03 311.9 0.98703 -0.01306

10-Nov-03 316.9 1.01603 0.01590

11-Nov-03 315.15 0.99448 -0.00554

12-Nov-03 312.05 0.99016 -0.00989

13-Nov-03 304.9 0.97709 -0.02318


50/92



Cipla Ltd.


Dates

Closingstockprice

Price relative(Si / Si-1)


17-Apr-04 1,240.85

19-Apr-04 1,249.75 1.00717 0.00715

20-Apr-04 1,250.00 1.00020 0.00020

21-Apr-04 1,311.25 1.04900 0.04784

22-Apr-04 1,335.45 1.01846 0.01829

23-Apr-04 1,301.60 0.97465 -0.02567

27-Apr-04 1,344.10 1.03265 0.03213

28-Apr-04 1,312.15 0.97623 -0.02406

29-Apr-04 1,344.15 1.02439 0.02409

30-Apr-04 1,369.80 1.01908 0.01890

3-May-04 1,398.65 1.02106 0.02084

4-May-04 1,372.95 0.98163 -0.01855

5-May-04 1,375.60 1.00193 0.00193

6-May-04 1,353.60 0.98401 -0.01612

7-May-04 1,329.90 0.98249 -0.01766


Dates

Closing

stockprice



12-May-04 260.95

13-May-04 262.15 1.00460 0.00459

14-May-04 246.85 0.94164 -0.06014

17-May-04 216.5 0.87705 -0.13119

18-May-04 236.85 1.09400 0.08984

19-May-04 244.15 1.03082 0.03036

20-May-04 246.9 1.01126 0.01120

21-May-04 245.25 0.99332 -0.00671

24-May-04 255.6 1.04220 0.04134

25-May-04 251.4 0.98357 -0.01657

26-May-04 255.05 1.01452 0.01441

27-May-04 246.9 0.96805 -0.03248

28-May-04 240.15 0.97266 -0.02772

31-May-04 234.15 0.97502 -0.02530

1-Jun-04 239.9 1.02456 0.02426


51/92



Dr. Reddys Labs



Dates

Closing

stockprice



15-Oct-01 927.1

16-Oct-01 933.6 1.00701 0.00699

17-Oct-01 969.95 1.03894 0.03820

18-Oct-01 963.95 0.99381 -0.00621

19-Oct-01 981.2 1.01790 0.01774

22-Oct-01 974.75 0.99343 -0.00660

23-Oct-01 999.5 1.02539 0.02507

24-Oct-01 1078.4 1.07894 0.07598

25-Oct-01 1101.2 1.02114 0.02092

29-Oct-01 1041.65 0.94592 -0.05559

30-Oct-01 1031.1 0.98987 -0.01018

31-Oct-01 1041.7 1.01028 0.01023

1-Nov-01 1,082.20 1.03888 0.03814

2-Nov-01 1,038.10 0.95925 -0.04160

5-Nov-01 993.75 0.95728 -0.04366

Dates

Closingstockprice



19-Sep-01 1846.55

20-Sep-01 1769.05 0.95803 -0.04288

21-Sep-01 1760 0.99488 -0.00513

24-Sep-01 1726.5 0.98097 -0.01922

25-Sep-01 1799.25 1.04214 0.04127

26-Sep-01 1771.75 0.98472 -0.01540

27-Sep-01 1767.15 0.99740 -0.00260

28-Sep-01 1789.75 1.01279 0.01271

1-Oct-01 1785.6 0.99768 -0.00232

3-Oct-01 1764.6 0.98824 -0.01183

4-Oct-01 1792.85 1.01601 0.01588

5-Oct-01 1796.2 1.00187 0.00187

8-Oct-01 1789.35 0.99619 -0.00382

9-Oct-01 1789.05 0.99983 -0.00017

10-Oct-01 1829.45 1.02258 0.02233


52/92



Glenmark Pharmaceuticals Ltd.


Dates

Closingstockprice



16-Aug-07 620.95

17-Aug-07 616 0.99203 -0.00800

20-Aug-07 619.95 1.00641 0.00639

21-Aug-07 600.45 0.96855 -0.03196

22-Aug-07 607.85 1.01232 0.01225

23-Aug-07 629.35 1.03537 0.03476

24-Aug-07 649.95 1.03273 0.03221

27-Aug-07 665.85 1.02446 0.02417

28-Aug-07 665.25 0.99910 -0.00090

29-Aug-07 660 0.99211 -0.00792

30-Aug-07 663.5 1.00530 0.00529

31-Aug-07 687.75 1.03655 0.03590

3-Sep-07 696.9 1.01330 0.01322

4-Sep-07 731.6 1.04979 0.04859

5-Sep-07 729.55 0.99720 -0.00281


Dates

Closing

stockprice



10-Sep-07 367.35

11-Sep-07 376.3 1.02436 0.02407

12-Sep-07 379.15 1.00757 0.00755

13-Sep-07 381.3 1.00567 0.00565

14-Sep-07 374.8 0.98295 -0.01719

17-Sep-07 379 1.01121 0.01114

18-Sep-07 380.55 1.00409 0.00408

19-Sep-07 391.25 1.02812 0.02773

20-Sep-07 388.2 0.99220 -0.00783

21-Sep-07 376.15 0.96896 -0.03153

24-Sep-07 388.95 1.03403 0.03346

25-Sep-07 400.9 1.03072 0.03026

26-Sep-07 395.6 0.98678 -0.01331

27-Sep-07 415 1.04904 0.04787

28-Sep-07 422.45 1.01795 0.01779


53/92



JB Chem Ltd.


Dates

Closingstockprice



10-Mar-05 433.25

11-Mar-05 434.4 1.00265 0.00265

14-Mar-05 430.65 0.99137 -0.00867

15-Mar-05 428.55 0.99512 -0.00489

16-Mar-05 427.7 0.99802 -0.00199

17-Mar-05 429.65 1.00456 0.00455

18-Mar-05 426.45 0.99255 -0.00748

21-Mar-05 421.1 0.98745 -0.01262

22-Mar-05 413.05 0.98088 -0.01930

23-Mar-05 398.35 0.96441 -0.03624

24-Mar-05 395.55 0.99297 -0.00705

28-Mar-05 413.3 1.04487 0.04390

29-Mar-05 401.2 0.97072 -0.02971

30-Mar-05 402.8 1.00399 0.00398

31-Mar-05 413.15 1.02570 0.02537


Dates

Closing

stockprice



5-Apr-05 86.5

6-Apr-05 85.85 0.99249 -0.00754

7-Apr-05 84.1 0.97962 -0.02060

8-Apr-05 83 0.98692 -0.01317

11-Apr-05 81.25 0.97892 -0.02131

12-Apr-05 79.5 0.97846 -0.02177

13-Apr-05 79.45 0.99937 -0.00063

15-Apr-05 77.05 0.96979 -0.03067

18-Apr-05 74.65 0.96885 -0.03164

19-Apr-05 75.3 1.00871 0.00867

20-Apr-05 74.8 0.99336 -0.00666

21-Apr-05 75.6 1.01070 0.01064

22-Apr-05 75.15 0.99405 -0.00597

25-Apr-05 76 1.01131 0.01125

26-Apr-05 77.75 1.02303 0.02277


54/92



Morepen Laboratories Ltd.


Dates

Closingstockprice



12-Oct-00 491.2

13-Oct-00 486.95 0.99135 -0.00869

16-Oct-00 531.55 1.09159 0.08764

17-Oct-00 512.1 0.96341 -0.03728

18-Oct-00 502.6 0.98145 -0.01873

19-Oct-00 516.7 1.02805 0.02767

20-Oct-00 538.15 1.04151 0.04067

23-Oct-00 535.35 0.99480 -0.00522

24-Oct-00 523.45 0.97777 -0.02248

25-Oct-00 564.8 1.07900 0.07603

26-Oct-00 616.65 1.09180 0.08783

27-Oct-00 601.35 0.97519 -0.02512

30-Oct-00 505.15 0.84003 -0.17432

31-Oct-00 512.55 1.01465 0.01454

1-Nov-00 507.8 0.99073 -0.00931


Dates

Closing

stockprice



6-Nov-00 120.25

7-Nov-00 124.5 1.03534 0.03473

8-Nov-00 123.3 0.99036 -0.00969

9-Nov-00 121.55 0.98581 -0.01429

10-Nov-00 117.8 0.96915 -0.03134

13-Nov-00 113.4 0.96265 -0.03807

14-Nov-00 117.45 1.03571 0.03509

15-Nov-00 119.3 1.01575 0.01563

16-Nov-00 118.85 0.99623 -0.00378

17-Nov-00 119 1.00126 0.00126

20-Nov-00 121 1.01681 0.01667

21-Nov-00 122.7 1.01405 0.01395

22-Nov-00 123.8 1.00896 0.00893

23-Nov-00 123.35 0.99637 -0.00364

24-Nov-00 122.35 0.99189 -0.00814


55/92



Nicholas Piramal Ltd.


Dates

Closingstockprice



2-De

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