Determinants of Equityshare Prices-BandiPrasad Sangappa-0467

DETERMINANTS OF EQUITY SHARE PRICES

M P BIRLA INSTITUTE OF MANAGEMENT - 1 -

A RESEARCH REPORT ON

DETERMINANTS OF EQUITY SHARE PRICES IN

THE INDIAN CORPORATE SECTOR

Dissertation Submitted in partial fulfillment for the award

of

For Bangalore University

SUBMITTED BY

BANDI PRASAD SANGAPPA

REG NO: 04XQCM6013

UNDER THE GUIDANCE OF

Dr: T.V. N. RAO (FINANCE PROFESSOR)

M.P.BIRLA INSTITUTE OF MANAGEMENT ASSOCIATES WITH BHARATIYA VIDYA BHAVAN

#43.RACE COURSE ROAD,

BANGALORE-560001

2004-2006

MASTER IN BUSINESS ADMINISTRATION

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DECLARATION

I hereby declare that this dissertation work entitled

�DETERMINANTS OF EQUITY SHARE PRICES IN INDIAN

CORPORATE SECTOR� is a bonafide study, completed under the

guidance and supervision of Dr. T. V. N. Rao and submitted in partial

fulfillment for the award of MASTERS OF BUSINESS

ADMINISTRATION degree at Bangalore University.

I further declare that this project is the result of my own effort and

that it has not been submitted to any other university/institution for the

award of any degree or diploma or any other similar title of recognition.

BANGALORE BANDI PRASAD SANGAPPA

DATE: Reg No: 04XQCM6013



PRINCIPAL�S CERTIFICATE

I here by certify that this project dissertation report is undertaken

and completed by Mr. Bandi Prasad Sangappa bearing Reg. No.

04XQCM6013 on �DETERMINANTS OF EQUITY SHARE

PRICES IN THE INDIAN CORPORATE SECTOR� under the

guidance of Dr: T. V. N RAO Adjunct Professor, M P Birla Institute

of Management, Bangalore

Place: Bangalore

Date: Dr Nagesh S Malavalli



CERTIFICATE

I here by certify that project work embodied in the dissertation

entitled is the result of an study undertaken and completed by Mr.

Bandi Prasad Sangappa bearing Reg No: 04XQCM6013 on

DETERMINANTS OF EQUITY SHARE PRICES IN THE INDIAN

CORPORATE SECTOR under my guidance and supervision.

Place: Bangalore

DATE: Dr: T. V. N RAO



ACKNOWLEDGEMENT

As students collect accolades in the form of grades for the success in

his/her endeavors and his/her success depends on adequate

preparation and in domination and most important of all the support

received from his/her guide. So the accolades I earn of this project, I

would like to share with all those who have played a notable part in

its making

In these two months I have worked on it, I feel indebted to many and

extend my heartful gratitude and profusely thank those people who not

only gave assistance to me but also participated in the making of this

project.

I sincerely thank to Dr .T.V.N Rao my esteemed project guide for his

valuable advice, assistance and guidance provided.

I also remain grateful to all my friends for their assistance to prepare

this project successfully.

Bandi Prasad



INDEX CONTENT PAGE NO

EXECUTIVE SUMMARY i

CHAPTER 1

INTRODUCTION & THEORETICAL BACKGROUND

1.1 Evolution 01 1.2 Leading cities in Stock Market Operation 02 1.3 Growth of Indian Stock Exchange 03 1.4 Financial Analysis 09

CHAPTER 2

LITERATURE SURVEY & PROBLEM IDENTIFICATION 2.1 LITERATURE SURVEY 14

PAPER 1-Determinants of Stock Price in India 14 PAPER 2-Determinants of Price Earning Ratio 18 PAPER 3-Determinants of Share Price 23

2.2 PROBLEM IDENTIFICATION

CHAPTER 3

RESEARCH METHODOLOGY 3.1 Objectives And Scope Of Study 26 3.2 Sample and Period of Study 26 3.3 Sources Of Data 27 3.4 Period Of Data 27 3.5 Statistical Procedure 28 3.6 Variables Used In Determining The Equity Share Price 28

3.7 Limitations of the study 31

CHAPTER 4 ANALYSIS OF DATA & DESCRIPTIVE OF RESULTS

4.1 Descriptive analysis 32 4.2 Tables 32

CHAPTER 5 5.1 Conclusion 51

CHAPTER 6

BIBILOGRAPHY & ANNEXURES 52



TABLE

NO TABLE NAME PAGE NO 1 Growth pattern of Indian Stock Market 05 2 Corporate Financial Performance 07

3 Sample size 26 4 Aggregate Regression Results year 2000 33 5 Aggregate Regression Results year 2001 35 6 Aggregate Regression Results year 2002 37 7 Aggregate Regression Results year 2003 39 8 Aggregate Regression Results year 2004 41 9 Aggregate Regression Results year 2005 43 10 Summary of aggregate company result 45 11 Summary of all sector results 49 12 F-Values and Adj R2 50 13 List of the companies under the study 53 DIAGRAMS

1 Financial Performance And Its Components 08 2 Characteristics Relation With Performance 08



EXECUTIVE SUMMARY

This study examines the empirical relationship of explanatory variables namely,

dividend per share, earning per share, price earning ratio, book value per share, size.

Cover return on capital employed and payout ratio on the market price of the shares in the

past-reform era.

Share price is the most important indicator readily available to the investors for

their decision to invest or not in a particular share. Theories suggest that share price

changes are associated with changes in fundamental variables which are relevant for

share valuation like payout ratio, dividend yield, capital structure, earnings, size of the

firm and its growth.

Investigation of share price changes appear to yield evidence that changes in

fundamental variable should jointly bring about changes in share price both in developed

and emerging market. However, the actual fundamental factors found to be relevant may

vary from market to market.

Knowledge of relative influence of fundamental factors on equity share prices is

helpful to corporate, management, government and investors. To the corporate

management an understanding of the valuation mechanism in stock market is essential for

the sound financial management of the company



CCHHAAPPTTEERR II

IINNTTRROODDUUCCTTIIOONN



EVOLUTION

Indian Stock Markets are one of the oldest in Asia. Its history dates back to nearly 200

years ago. The earliest records of security dealings in India are meager and obscure. The

East India Company was the dominant institution in those days and business in its loan

securities used to be transacted towards the close of the eighteenth century.

By 1830, business on corporate stocks and shares in Bank and Cotton presses took place

in Bombay. Though the trading list was broader in 1839, there were only half a dozen

brokers recognized by banks and merchants during 1840 and 1850.

The 1850 witnessed a rapid development of commercial enterprise, brokerage business

attracted many men into the field, and by 1860, the number of brokers increased into 60.

In 1860-61 the American Civil War broke out and cotton supply from United States of

Europe was stopped; thus, the 'Share Mania' in India begun. The number of brokers

increased to about 200 to 250. However, at the end of the American Civil War, in 1865, a

disastrous slump began (for example, Bank of Bombay Share, which had touched Rs

2850, could only be sold at Rs. 87).

At the end of the American Civil War, the brokers who thrived out of Civil War in 1874,

found a place in a street (now appropriately called as Dalal Street) where they would

conveniently assemble and transact business. In 1887, they formally established in

Bombay, the "Native Share and Stock Brokers' Association" (which is alternatively

known as �The Stock Exchange "). In 1895, the Stock Exchange acquired a premise in

the same street and it was inaugurated in 1899. Thus, the Stock Exchange at Bombay was

consolidated.



OTHER LEADING CITIES IN STOCK MARKET OPERATIONS

Ahmedabad gained importance next to Bombay with respect to cotton textile industry.

After 1880, many mills originated from Ahmedabad and rapidly forged ahead. As new

mills were floated, the need for a Stock Exchange at Ahmedabad was realised and in

1894, the brokers formed "The Ahmedabad Share and Stock Brokers' Association".

The cotton textile industry was to Bombay and Ahmedabad, the jute industry was to

Calcutta. In addition, tea and coal industries were the other major industrial groups in

Calcutta. After the Share Mania in 1861-65, in the 1870's there was a sharp boom in jute

shares, which was followed by a boom in tea shares in the 1880's and 1890's; and a coal

boom between 1904 and 1908. On June 1908, some leading brokers formed "The

Calcutta Stock Exchange Association".

In the beginning of the twentieth century, the industrial revolution was on the way in

India with the Swadeshi Movement; and with the inauguration of the Tata Iron and Steel

Company Limited in 1907, an important stage in industrial advancement under Indian

enterprise was reached.

In 1920, the then demure city of Madras had the maiden thrill of a stock exchange

functioning in its midst, under the name and style of "The Madras Stock Exchange" with

100 members. However, when boom faded, the number of members stood reduced from

100 to three, by 1923, and so it went out of existence.

In 1935, the stock market activity improved, especially in South India where there was a

rapid increase in the number of textile mills and many plantation companies were floated.

In 1937, a stock exchange was once again organized in Madras - Madras Stock Exchange

Association (Pvt) Limited. Lahore Stock Exchange was formed in 1934 and it had a brief

life. It was merged with the Punjab Stock Exchange Limited, which was incorporated in

1936.



INDIAN STOCK EXCHANGES - AN UMBRELLA GROWTH

The Second World War broke out in 1939. It gave a sharp boom that was followed by a

slump. But, in 1943, the situation changed radically, when India was fully mobilized as a

supply base. Because of the restrictive controls on cotton, bullion, seeds and other

commodities, those dealing in them found in the stock market as the only outlet for their

activities. They were anxious to join the trade and numerous others swelled their number.

Many new associations were constituted for the purpose and Stock Exchanges in all parts

of the country were floated.

The Uttar Pradesh Stock Exchange Limited (1940), Nagpur Stock Exchange Limited

(1940) and Hyderabad Stock Exchange Limited (1944) were incorporated. In Delhi, two

stock exchanges - Delhi Stock and Share Brokers' Association Limited and the Delhi

Stocks and Shares Exchange Limited - were floated and later in June 1947, amalgamated

into the Delhi Stock Exchange Association Limited.

Post-independence Scenario

Most of the exchanges suffered almost a total eclipse during depression. Lahore

Exchange was closed during partition of the country and later migrated to Delhi and

merged with Delhi Stock Exchange. Bangalore Stock Exchange Limited was registered in

1957 and recognized in 1963.

Most of the other exchanges languished until 1957 when they applied to the Central

Government for recognition under the Securities Contracts (Regulation) Act, 1956. Only

Bombay, Calcutta, Madras, Ahmedabad, Delhi, Hyderabad and Indore, the well-

established exchanges, were recognized under the Act. Some of the members of the other

Associations were required to be admitted by the recognized stock exchanges on a

concessional basis, but acting on the principle of unitary control, all these pseudo stock

exchanges were refused recognition by the Government of India and they thereupon

ceased to function.



Thus, during early sixties there were eight recognized stock exchanges in India

(mentioned above). The number virtually remained unchanged, for nearly two decades.

During eighties, however, many stock exchanges were established: Cochin Stock

Exchange (1980), Uttar Pradesh Stock Exchange Association Limited (at Kanpur, 1982),

and Pune Stock Exchange Limited (1982), Ludhiana Stock Exchange Association

Limited (1983), Gauhati Stock Exchange Limited (1984), Kanara Stock Exchange

Limited (at Mangalore, 1985), Magadh Stock Exchange Association (at Patna, 1986),

Jaipur Stock Exchange Limited (1989), Bhubaneswar Stock Exchange Association

Limited (1989), Saurashtra Kutch Stock Exchange Limited (at Rajkot, 1989), Vadodara

Stock Exchange Limited (at Baroda, 1990) and recently established exchanges -

Coimbatore and Meerut. Thus, at present, there are totally twenty one recognized stock

exchanges in India excluding the Over the Counter Exchange of India Limited (OTCEI)

and the National Stock Exchange of India Limited (NSEIL).

The Table given below portrays the overall growth pattern of Indian stock markets since

independence. It is quite evident from the Table that Indian stock markets have not only

grown just in number of exchanges, but also in number of listed companies and in capital

of listed companies. The remarkable growth after 1985 can be clearly seen from the

Table, and this was due to the favoring government policies towards security market

industry.



Growth Pattern of the Indian Stock Market

TABLE 1

Sl. As on 31stDecember 1946 1961 1971 1975 1980 1985 1991 1995

1 No. of Stock

Exchanges

7 7 8 8 9 14 20 22

2 No. of Listed Cos. 1125 1203 1599 1552 2265 4344 6229 8593

3 No. of Stock Issues of

Listed Cos.

1506 2111 2838 3230 3697 6174 8967 11784

4 Capital of Listed Cos.

(Cr. Rs.)

270 753 1812 2614 3973 9723 32041 59583

5 Market value of

Capital of Listed Cos.

(Cr. Rs.)

971 1292 2675 3273 6750 25302 110279 478121

6 Capital per Listed Cos.

(4/2) (Lakh Rs.)

24 63 113 168 175 224 514 693

7 Market Value of

Capital per Listed Cos

(Lakh Rs.)

(5/2)

86 107 167 211 298 582 1770 5564

8 Appreciated valueof

Capital per Listed Cos.

(Lak Rs.)

358 170 148 126 170 260 344 803

Source: Various issues of the Stock Exchange Official Directory, Vol.2 (9) (iii), Bombay Stock Exchange,

Bombay.



Trading Pattern of the Indian Stock Market

Trading in Indian stock exchanges is limited to listed securities of public limited

companies. They are broadly divided into two categories, namely, specified securities

(forward list) and non-specified securities (cash list). Equity shares of dividend paying,

growth-oriented companies with a paid-up capital of at least Rs.50 million and a market

capitalization of at least Rs.100 million and having more than 20,000 shareholders are,

normally, put in the specified group and the balance in non-specified group.

Two types of transactions can be carried out on the Indian stock exchanges: (a) spot

delivery transactions "for delivery and payment within the time or on the date stipulated

when entering into the contract which shall not be more than 14 days following the date

of the contract�: and (b) forward transactions "delivery and payment can be extended by

further period of 14 days each so that the overall period does not exceed 90 days from the

date of the contract". The latter is permitted only in the case of specified shares. The

brokers who carry over the outstanding pay carry over charges which are usually

determined by the rates of interest prevailing.

A member broker in an Indian stock exchange can act as an agent, buy and sell securities

for his clients on a commission basis and also can act as a trader or dealer as a principal,

buy and sell securities on his own account and risk, in contrast with the practice

prevailing on New York and London Stock Exchanges, where a member can act as a

jobber or a broker only.

The nature of trading on Indian Stock Exchanges are that of age old conventional style of

face-to-face trading with bids and offers being made by open outcry. However, there is a

great amount of effort to modernize the Indian stock exchanges in the very recent times.



Corporate Financial Performance

TABLE 2

(Growth rates in per cent)

2003-04 2004-05 2004-05 2005-06 2004-05 2005-06

(April- (April-

Q1 Q2 Q3 Q4 Q1 Q2 Q3

December) December)

1 2 3 4 5 6 7 8 9 10 11 12

Sales 15.4 25.2 25.9 15.7 24.8 23.7 24.1 21.0 18.5 16.4 13.2

Expenditure 12.5 24.0 24.9 15.3 23.4 22.4 24.3 19.8 18.0 16.3 12.7

Gross Profit 26.6 38.9 37.8 24.1 36.0 35.8 30.5 35.3 32.0 19.1 21.2

Interest Cost -11.5 -2.0 -2.1 -6.4 -3.2 2.1 -13.0 -5.4 -13.5 -8.0 4.6

Profits After

Tax

57.9 53.8 48.0 35.0 51.2 45.3 45.5 51.4 54.2 27.5 27.0

Memo:

(Amount in Rupees crore)

No. of

Companies

2,201 1,273 895 2,010 1,255 1,353 1,464 1,301 2,355 2,361 2,366

Sales 4,28,072 5,68,476 3,63,140 5,77,271 1,35,156 1,53,040 1,62,193 1,79,632 1,94,608 2,12,693 2,19,098

Expenditure 4,06,838 4,90,204 3,11,105 4,95,121 1,15,656 1,31,227 1,40,574 1,56,647 1,66,972 1,83,717 1,88,934

Gross Profit 48,852 72,406 47,591 77,286 17,234 20,448 20,017 23,736 25,577 27,620 28,135

Interest Cost 14,724 12,528 7,831 12,140 3,597 3,584 3,273 3,177 4,241 4,467 4,555

Profits After

Tax

26,281 47,333 31,066 51,364 10,396 13,004 13,196 16,798 16,726 18,169 18,790

Note: 1.Growth rates are percentage change in the level for the period under

reference over the corresponding period of the previous year.

2. Data are based on the audited / unsuited abridged results of the

non-financial non-Government companies except column (2)

which are based on audited balance- sheets for 2003-04.



DIAGRAM 1

DIAGRAM 2



FINANCIAL ANALYSIS

The most important quality for financial analysis is the passion to go for, go into and go

beyond numbers. Let us begin by unlearning some common misconceptions. Many

people relate financial analysis to number crunching. There are some others who have set

benchmarks for financial ratios and numbers, like a current ratio of 2 or debt to equity

ratio of 1, etc. Many have a tendency to calculate expected share price by multiplying

EPS with a normative P/E. Were financial analysis such simple arithmetic, we would

have given you a spreadsheet with pre-written formulae rather than this verbose piece.

You have some acquired knowledge and techniques and then it is all upto your judgement

and experience. Yes, numbers are important. Financial analysis starts with numbers. But

it does not end there.

About Ratio: A ratio is nothing more than a simple division of two numbers. Often

numbers by themselves do not convey anything until they are related. In financial

analysis, we need qualitative information and try to read between the numbers. We have

to ask all the right questions. Over the years, there are some ratios, which have become

more popular and handy for rule of thumb analysis of financial statements. Our purpose

in this note is not deride them but to advice the reader to use them properly to derive the

correct results.

Key Objectives of a Business

Before you look at different ratios, let us look at a firm's objectives in a capitalist market.

The one and only intention of any firm is to maximize shareholders value, which is

effectively done by getting a bigger bang out of the capital employed. Exceptional cases

like charity, passion, hobbies, etc also try to maximize return on capital employed, but

there the definition of capital is different. For the time being, let us stick to financial

capital.



While businesses claim to have multiple objectives such as market share, brand building

and even social objectives, at the end of the day, what really matters is how much money

one makes. All are strategies to maximize return on capital employed, which is the one

and only long term goal of all management. Obviously one will look at money made in

relation to one's investment. If you use 10 times as much capital and make 5 times more

money, it is of no good. If business A earns Rs10 on Rs 100 investment (10%), it is better

than another business B that earns Rs50 on Rs1000 (5%).

To analyze the performance of any business, the key ratio is therefore Return on Capital

Employed (ROCE). We can further analyze this ratio using models popularly know as

The Du Pont model.

The model starts with analysis of ROCE in its two constituents

Profit margin on sales

Sales per unit of capital invested

To give an example, say business A is one in which Rs100 capital invested in a year

generates sales of Rs100 with net profit margin of 10%. Whereas, in business B Rs100

investment generates a turnover of Rs500 but with a net profit margin of only 4%.

As you can see, in business B, net profit margin can be lower but is more than

compensated by the fact that turnover generated per unit of capital invested is

significance higher or capital turnover ratio is higher. Return on capital invested is the

product of sales margin and capital turnover ratio.

The same can be presented in the formula as follows.

(Net profit/ sales) * (sales/ capital employed) = Return on capital employed

The above two are the mother of all ratios. Let us look at their children.



Profit Margin.

We all know that profit is revenue minus cost. Each element of cost can be presented as a

% of revenue and at different levels of costs; we have different versions of profit, i.e.

EBIDTA, EBIT, EBT, etc. EBITDA margin is a good indicator of operational efficiency

of any company.

Even revenue can be broken up for the purpose of analysis, which is of use in a multi

product, multi division entity. Typically, analysts look at the relative share of other

income, because this item is where most Indian companies show extra ordinary profits to

boost their bottom line.

Return Ratios

There are two types of providers of capital, owners and lenders. As returns to lenders are

fixed, we don't have to calculate any return ratio on debt, as the same is predetermined.

From owners' perspective, the key ratio is return on net worth. Net worth represents

owners' funds, paid up capital and retained profits called as reserves. As an owner, you

would also be interested in knowing how much return is being generated by the total

capital employed. Capital employed consists of net worth plus debt, i.e. owned and owed

money. So when we calculate this ratio we have to add back the cost of debt, i.e. adjust

for interest expenses. This ratio is calculated primarily on pre-tax basis and it is

equivalent to EBIT (Earnings before Interest and Tax) divided by total capital employed.

If we want to calculate it on post-tax basis, we will have to add interest adjusted for tax

i.e.

EBT + interest*(1-T)/ capital employed, where T is the tax rate.



Add Back Interest for ROCE

Because, while calculating ROCE, we have to add back interest. This ratio calculates the

returns to all the providers of capital. As mentioned earlier, capital can be debt or equity.

On debt, we pay interest while entire PAT belongs to equity holders. Therefore, when we

calculate return on capital employed, we have to do so before any payment is made to the

providers of capital. So if we do not add back interest we will be taking profits after

making some payment to the provider of capital thereby distorting the real picture.

Per Share Ratios

An equity share is a legal document representing ownership of any entity. Shares of listed

companies trade in stock markets. It therefore makes sense to look at most profitability

indicators on a per share basis. The key ratio is earnings per share which is net profit (if

the company has issued preference capital, then one must remove preference dividend to

reflect what belongs to the common equity holders only) divided by number of

outstanding shares

One variant of this ratio of cash earnings per share, which is cash, profited divided by

number of outstanding shares. Cash profit is equivalent to profit after tax plus

depreciation and other non-cash charges.

In stock market, a fraction of ownership known as shares is traded. Therefore in order to

arrive or get a proper picture of the worth of a share (one unit of the company), we should

look at numbers calculated on a per share basis. Earnings per share are profit after tax

(adjusted for preference dividend if any) divided by number of outstanding shares.

Similarly, you can calculate cash profit per share, sales per share, etc. This will facilitate

valuation and comparison with other companies. The most famous of the valuation ratios

is the Price earnings ratio (P/E ratio), which the current market is priced of the share

divided by the earnings per share. Also see the chapter on investing for a detailed

discussion of the same



Dividend per share

The owner can allow profits to remain within business or can withdraw it for other or his

personal use. When he withdraws, it is analogous to dividend payout. In a company, the

management decides on behalf of the owner, whether or not to retain a part of profits

within the company (that is called retained earnings) and gives back a part of profits to

the owners called dividends.

Dividend per share is the total dividend paid per equity share. In case there was a fresh

issue of equity capital in the year, most companies make pro rata payment, i.e. supposing

in a financial year (April to March) there was an issue of equity shares on October 1. The

new shares, which were issued on Oct 1, will be entitled for only 50% dividend as

compared to other shareholders who were there for the full year.

Trends in Some Key Ratios

By trends we mean progress year after year. So one can look at trends in sales, fixed

assets, working capital and trends in various ratios. Trends in some key performance

ratios such as operating margin, return on net worth also convey meaningful results. For

instance, operating margin that was 8% last year and 9% this year.

Comparison One can make comparisons across years in terms of trends in margins,

growth or comparison across companies within a sector or across a sector, by comparing

large companies in both the sectors and sector aggregates. And firms of the same industry

are compared on various parameters. One can look at aggregate numbers of one industry

and compare them with aggregate numbers of another industry to understand the

differences in performance of various industries. For instance, if you look at the

consumer durable industry which might be generating a return on networth of 8-10%,

whereas software industry may be generating a return on networth of 40-50%. So one can

easily conclude that software industry is doing significancely better than the consumer

durables industry.



CCHHAAPPTTEERR IIII

LLIITTEERRAATTUURREE

SSUURRVVEEYY



PAPER I DETERMINANTS OF STOCK PRICE IN INDIA

An empirical study by M. A. Zahir & Yakesh khanna.

INTRODUCTION

Maximization of shareholder�s wealth, determined by the market price if equity

shares, has been universally accepted as the major financial objectives of the firm.

Obviously, there are number of factors that affect the market price of shares. And in this

case it had attempted to analyse the relationship between share and some of the share

these factor.

OBJECTIVE OF THE STUDY

To know the empirical relationship between equity share price and factors like

book value per share, dividend per share, earning rate, yield and coverage?

They assumed for the purpose of analysis, share price has been assumed to be dependent

variables, while the other five factors listed above have been taken as explanatory or

independent variables. An attempt has also been made to study the interrelationship

among these independent variables, as some of these are expected to influence one

another.

METHODOLOGY

The study is fully based on the secondary source of data. For the purpose of

analysis, the relevant data have been taken from the various issues of the economic times.

The study relates to 101 industrial giant in the private sector. But only 62 company�s

information was fully available. There fore sample size consists of 62 of these private

giant

Data relating to independent/explanatory variables have been collected for the

years 1976-78, market prices (high-low) of equity shares of the sample companies have

been noted for the relevant years and the arithmetic average of the highest prices and

lowest prices calculated for the years 1977-78 and 1978-79.



To explain the share prices in the year �n�, the data used to calculate the values of

explanatory variable related to the year proceeding year �n�. Since the paid up values of

equity shares are differed from one company to another company so it was decided to

convert the values of dividend per share and market price of share to the share to

common base of 100. Thus the paid-up values of shares of each company are taken as Rs

100 and other values were adjusted accordingly. However, wherever the values were

expressed in terms of percentages or ratios such adjustments were not necessary.

1. Statistical tools

The following statistical tools have been used to analyse the data

Coefficient of correlation (r) has been used to study the association between the

market price of shares and independent (explanatory) variables, as also among the

independent variables themselves. The significance of r has been tested directly with the

help of Coefficient of correlation (r).

The regression equation has been estimated along with the standard errors of the

coefficient. The significance of the regression co efficient is tested using t distribution.

The coefficients of multiple determinations (R) indicating the proportion of variation in

the dependent variable explained by the independent variable is also worked out for each

regression relationship. Its significance is tested with the help of f-test.

The sum up, the independent variable chosen for the present study is:

Market price of equity shares (P): The arithmetic average of the highest and the

lowest share price over the years under study.

To study their impact on the above dependent variable, they have chosen the

following independent /explanatory variables (with one year lag):

A. Book Value per Share (X1)

B. Dividend per share (X2)

C. Earning Rate (X3)

D. Yield: dividend-Price Ratio (X4)

E. Coverage: Earning �Dividend Ratio (X5)



ANALYSIS

Multiple corrélation coefficients (R)

The values of R, determined by the F-test, are highly significance in the

both years. This means that the selected explanatory variables in combination have got a

very significance relationship with the market price of shares.

PERFORMANCE OF INDEPENDENT VARIABLES:

To access the performance of independent variables, in terms of its impact on

share prices as well as on other variables, they have used (a) coefficient of correlation,

and (b) regression equation.

Coefficient Correlation (r)

The coefficient of correlation for both the series (1976-770 and (1977-78). In the

case of first series it maybe observed, the most significance correlation existed between

the X2 (dividend per share) and the share price. Moreover, the coefficient of the book

values X1 and coverage (X5) were also significance at 1% level. The correlation between

share price and yield(X4), on the other hand, was negative, albeit significance. Almost

the same situation existed during 1977-78, though the coefficient of coverage variables

(X5) was not significance in that year.

Multiple Regression Equation

For regression analysis, they used the linear relationship of the form:

P = a + b1X1 + b2X2 + b3X3 + b4X4 + b5X5

The vales of regression coefficient have been found with the help of t-values both 1% and 5% level.



IMPLICATION AND CONCLUSION

The findings of the study may provides some broad guidelines for share valuation

in India, particularly relating to large industrial organization

A comparison correlation coefficient and regression coefficient reveals that has

emerged highly significance in all the series. The implication of overwhelming

importance of dividend in comparison to other variable is that with in the frame

work of investment and financing constraints, a firm can enhance the market

value of its equity capital by pursuing a more liberal dividend payment policy

Another highly significance coefficient in all the series pertains to that of yield

(dividend �price ratio). Its association with market price of share is, however,

negative � that is, higher the share pieces, lower the yield, and vice versa. It also

suggests that decline yield, overt a period of time, with the increase in dividend

because increase in share price relatively larger than the increase in dividend per

share coupled with the other factors.

The third important variable affecting share price is book value per share. The

coefficient of book value is positive throughout and highly significance in all the

series except one. Higher book value is perhaps perceived by investors to be an

index of sound financial position of a firma and a good risk.

Dividend coverage comes out with significance correlation coefficient ( r ) in one

series, but depicts very weak, influence on the share prices far as the second series

as well s regression coefficient are concerned

The influence of earning rate on share price appears to be very weak, though it

has a strong positive influence on the size of dividend per share. The strong

association between earning per share (EPS) and dividend per share (DPS) is

quite obvious.



PAPER II: DETERMINANTS OF PRICE-EARNINGS RATIO.

An empirical study by Nishi Tuli & R. K. Mittal

INTRODUCTION

A systematic analysis of securities for investments is important for making sound

investment decision. It helps investors select those securities that conform to their

expected risk-return requirements. Security analysis plays an important role in efficient

stock market as well as stock markets, which are not claimed to be efficient. Fundamental

analysis is concerned foremost. It has been prime concern of the fundamental analysts to

determine the appropriate capitalization rate or equivalently the appropriate multiplier to

be used in valuing particular securities

In one of the early studies, showed that the impact of projected earnings growth,

expected dividend payout ratio, and variability in rates of earnings growth and concluded

that P/E is an increasing function of earning growth and payout and inversely related to

variations in growth of earnings

P/E ratios of firms are compared using the accelerated depreciation with those

firms using straight-line depreciation. With that they found average P/E ratios were larger

for accelerated depreciation firms and also suggested that the investors are forecasting

only short-lived earnings expectations. They also find that P/E ratio are can vary

positively or negatively with market risk depending upon the market condition there fore

risk also doesn�t supply the explanation for P/E differences across firms. They conclude

that differences in P/E ratios are not because of growth or risk but because of difference

accounting methods

Purpose of the study

The primary purpose of the study is to explain the variability of P/E ratio of Indian

corporate equities in terms of fundamental factors

The factors covered in this study are corporate size, variability in earnings per share,

variability in market price, debt equity ratio, dividend payout ratio etc.



METHODOLOGY

The sample is based on the Indian private corporate sector and was selected on the

basis of availability of data

A data relating to the market price annual high and low of its shares were not

available for all the years are excluded

The figures of earning per share were negative in any year. 105 companies are

covered in this study.

The data was collected from the Bombay stock exchange official directory, in the

present study multiple regression technique has been adopted to examine the

determinants of P/E ratio corporate size, variability in earnings per share, variability in

market price, debt equity ratio, dividend payout ratio and growth rate in market price.

Under two different classifications. Under the first classification, the impact of above

explanatory variables on P/E ratios are has been examined by the taking sample as whole.

And at the second stage, the influence above explanatory variables on P/E has been

examined at industry level. This criterion was adopted to examine whether there are

differences in the determinants of P/E ratio in different industries.

The following log linear multiple regression equation is used for the studying the

influence of explanatory variables on P/E ratio.

Log P/E = Log a + b1 Log CS + b2 Log VEPS + b3 Log VMP +

b4 Log DER + b5 Log GMP + E

Where P/E = price earning ratio

CS = corporate size

VEPS = variability in earning per share

VMP = variability in market price

DER = debt equity ratio

DPR = dividend payout ratio

GMP = growth rate in market price

The specification and measurement of those variables is given below:



Price earnings ratio: The measure of this ratio is adopted in the is average of annual

high and low of market prices in the numerator and cross sectional year�s earning per

share in the denominator the reason for using each year average share price has the

advantage of smoothing out short term fluctuation in share prices and consequently in

P/E ratio An incidental advantage of relying year average share price, instead of prices at

a particular point of time, was the economy of cost and efforts. And they preferred to use

cross section year�s earning per share in calculating P/E ratio,

Corporate size: Size is expected to influence P/E ratio positively this variable is

measured in terms of total assets and is the arithmetic mean of the value of total assets for

two years proceeding and including cross section year.

Variability in earnings: It is a measure of risk. Risk is expected to have negative

relationship with the P/E ratio of a share. Variability in earnings per share for five years

for proceeding and including cross section year.

Variability in market price: It was hypothesized that higher variation in the market price

should influence P/E ratio in positive way. This variable was obtained by calculating the

standard deviation of mean of annual high and low of market price of equity shares for

five years proceeding and including cross section year

Debt equity ratio: Debt equity ratio is a measure financial risk. It was expected that the

higher the leverage (debt equity), higher is the risk and lower is the price of equity share

in terms of its earnings.

Dividend payout ratio: It has expected to have positive impact on P/E ratio of a firm.

Dividend payout ratio is calculated as percentage of dividend paid to equity share holders

out of earnings available and is the average of dividend payout ratio of two years

preceding and including cross section years.



Growth rate in market price: Growth variable is expected to have positive influence on

P/E ratio of corporate equities. Growth in market price is calculated from a regression of

logarithms of market price against time. The value of market price is arithmetic mean of

higher and lower of market price of a share. The advantage of using regression to

calculate growth rates is that all the observations in time series are considered, as

opposed to calculating the geometric mean growth rate by considering only beginning

and ending values

REGRESSION RESULTS: TOTAL SAMPLE COMPANIES

Dividend payout ratio and variability in market price are the most important

determinants of P/E ratio as their respective coefficients are positively significance in

each of the years covered. The value of coefficient of variability in earnings per share has

the negative sign in all years but significance in three out of five years.

The corporate size measure has the right sign all through. Although, it is

significance in two out of five years, the general consistency of the signs would suggest

that investor�s value the shares of large companies more than those of smaller ones. The

coefficients associated with growth rate in market price and debt-equity ratio are not

found to be significance while positive direction of growth rate in market price supports

the hypothesis and positive direction of debt-equity ratio is contrary to expectation.

The observed relationship of these variables explained on average 35 percent (R2)

of variability in P/E ratios of company�s equities over a period of 1989-93. The relevance

of (R2) is further supported by F-values being significance at 1 percent level throughout

the study period. All this leads us to conclude that explanatory determinants used in the

study have strong influence on P/E ratio except debt-equity ratio and growth rate in

market price.



Results

The results o parametric ANOVA, it contains mean P/E ratio by ownership

pattern, their corresponding standard deviation, computed F-ratio and critical F-ratio

needed for testing the significance at 5 percent level. /the mean P/E ratio for particular

ownership pattern

Conclusion

The empirical study has attempted to examine the varying importance of different

factors influencing the P/E ratio of equity shares. In the context of Indian stock market, it

appears that variability in market price and dividend payout ratio are the most important

determinants of P/E ratio, followed by variability in earnings per share. The corporate

size, debt-equity ratio and growth rate in market price being insignificance variable find

no evidence to support the theoretical work. Industry class and ownership pattern

classifications do not have significance impact on P/E ratio.



PAPER III DETERMINANTS OF SHARE PRICE: study on modified model

Bipul Malakar & Rajnarayan Gupta

Various types of single equation model have been tried to weed out the

unnecessary explanatory variables to find out the significance one. Variables attempted

differed across studies. The most commonly used variables in the literature are dividend

per share, earning per share, book value per share, company size, yield etc.

The single equation technique suffers from the basic lacuna in treating

explanatory variables as exogenous �completely disregarding the factual world.

Interwoven nature of capital market and the product market is closer to reality. This is in

order to avoid the restrictive presumption a simultaneous equation model was

investigated.

In the attempted mode, the share price equation fitted well, but some of the

relationships of the system required modified including more variables and excluding

some of existing statically insignificance variables is investigated.

Section I: The Modified Simultaneous Equation

The process of explaining share price movement the interconnection between

explanatory variables is ignored. In reality, however the interwoven nature of the capital

market and product market is closer to reality.

Earlier simultaneous equation model of share price determination is given below

Share price equation : Pt = ß10 + ß11 + Dt +u1t

Dividend equation : Dt = ß20 + ß21Et-1 + ß22 It + u2t

Earning per share : Et = ß30 + ß31 St + u3t

Investment equation : It = ß40 + ß41 Ä St-1 + u 4t

Volume of sales equation : St = ß50 + ß51 Pt + u5t



This model was tested with data on eight companies in India for a period of 1968

-1988. Since the model over identified. Two stage least square methods were applied for

estimation purpose. And the empirical findings suggests that the model was a close a

approximation of factual world; explanatory power of each companies was high

SECTION II: Information Sources and Estimation

This model has been tested for 8-cement industry in India. Product homogeneity

is the primary reason for choosing cement industry. Eight dominant companies have been

chosen for the purpose, availability of quantitative information has influence the

selection. The period considered ranges from 1968-1988. Thus the present paper carries

out a time cross study.

Data on share prices and company fundamentals are collected from the Bombay

stock exchanges official directories and data on the prices of cement and interest rates are

taken and compiled from RBI bulletin and report on currency and finance. The purpose

of the study is to explain the long run trend; therefore, only annual data have been

analyses. The best-fitted equation of the model expected, as expected is the equation,

which explains the sales proceed, by product price. (R2) has median as high as 0.81 and F

�vales are significance for all companies

The share price equation has behaved nicely explanatory power of companies (the

value of the (R2) is remarkably high with median 0.60 and F-statistics are significance

except one company.

Pt = ß 10 + ß11 D t + ß12 Dt-1 + u1t

The next important relationship of this model is undoubtedly the dividend

equation.

Dt = ß20 + ß21Et + ß22 Rt + u t2



The empirical results are however, not so assertive for other two relationships of

the model, namely the earning per share equation and the equation for the retained

earnings. It perhaps indicates the complicacy of functional relationship among the

considered variables. Similarly incorporation of the industry specific macro � variables

may be suggested for the better fit of the equation for retained earnings.

The fourth equation of the model has been substantially modified; thus it may not

sound meaningfully to compare the fourth equation of the modified model with that of

the older one. The endogenous variable- investment has been made exogenous in the

modified in the system and retained earning is considered as a dependent variable. The

median value of (R2) for the investment equation of the earlier model was as low as 0.03.

The corresponding figure for the retains earning equation in the modified system stands

at 0.28. Thus, the retained earning equation is better fit to the factual word than

investment-sales relationship formulation.

Thus they reiterate-

That system approach is closer to reality than single equation technique.

Comparison of empirical results of the two versions of the models, the earlier simplified

and the present modified, further supports attempted modification. There is however,

scope-e for further improvement in modeling. The present exercise has considered

linkage between share market and product market. Macro aspects have not been

adequately accommodated in the model formulation. The two markets are again

interwoven in a much more complicated manner than postulated. Thus more refined

structural equation and model formulation are essential.



CCHHAAPPTTEERR IIIIII

RREESSEEAARRCCHH

MMEETTHHOODDOOLLOOGGYY



RESEARCH METHODOLOGY

OBJECTIVES AND SCOPE OF STUDY

The main objective of the study is to determine the determinants of equity share

prices in Indian corporate sector

To study the empirical relationship of explanatory variables namely, dividend

per share, earning per share, price earning ratio, book value per share, size.

Cover return on capital employed and payout ratio on the market price of the

shares in the past-reform era.

To know the relationship between dependent and independent variables of 104

companies over a period of six years spanning from 2000 to 2005

SAMPLE AND PERIOD OF STUDY

The data employed in the study relates to manufacturing companies listed in on

Bombay Stock Exchange. A sample of 104 companies covering the following industries

have been finally selected for the purpose of the study.

TABLE 3

INDUSTRY NO OF COMPANIES Banking & Financial 30 Hotel & Resorts 30 Petroleum &Lubricant 14 Drugs & pharmaceuticals 30 TOTAL 104



While selecting the sample of the companies from six industries, the following criteria are adopted:

The necessary financial data required for calculating the measures of dependent

and independent variable pertaining to all the years 2000-2005 is available.

The companies did not skip dividend for any two successive years are included in

the sample.

The companies whose average earning per share of any three successive years is

not zero or negative is also considered.

Further only those companies whose price data is available are retained in the

sample size.

The listed shares on Bombay Stock Exchange are considered.

SOURCES OF DATA

The data relating to the companies was taken from the �PROWESS� database of the

Centre for Monitoring Indian Economy (CMIE) and Bombay Stock Exchange Official

Directory. The supplementary sources of data were:

Financial journals/ dailies like capital market, business India, fortune India, and

others financial news papers like economic times and financial express were also

used

Data regarding the share prices were taken from the website: www.bseindia.com

Coefficient of determination for various industries were calculated with the help

of SPSS10 software

PERIOD OF DATA

The study has been conducted for the period of past five years i.e. 2001 to 2005

and the total sample were of sixty companies mainly of manufacturing sectors divided

into six different categories as mentioned above.

http://www.bseindia.com



STATISTICAL PROCEDURE

To analyze the determinants of equity the following model has been used.

Regression model: �the linear multiple regression� approach has been applied primarily

to minimize the problem of multicollinearity. This technique of multivariate analysis was

selected because it is the most appropriate tool evaluating the individual and combined

effect of set of independent variables on dependent variable. The significance of

coefficient of various explanatory variables was tested at 1% and 5% by computing t-

values. To determine the proportion of explained variation in dependent variables,

coefficient of multiple determinations R2 was worked out. The overall significance of

regression equation was tested with the help of F-values.

VARIABLES USED IN DETERMINIG THE EQUITY SHARE PRICES

For the purpose of empirical analysis, share price has been assumed to be

dependent variable while other factors have been taken as independent variable. To

explain the share prices in the year �t�, data used to calculate the values of explanatory

variables relate to the year �t� (t refers to the year, the share price of which is being

explained). This is based on the assumption that the dividend decisions made by a

company in a given year as well as other variables are apt to affect the market price of its

share in the following year when the data is publicly made available.

Share Price (SP)

The forces of demand and supply in the market mainly determine the market price of the

share it is the balance struck between the buyer and seller.

SP = (PH + PT) / 2 PH is the highest market price

PL is the lowest market price

t is the time period



Book Value (BV)

It also known as net asset value per share because it measures the amount of

assets, which the corporation has on behalf of each equity share. BV shows the

investment per share made in the business by the shareholder�s .a high book value usually

indicates that the company has a good record of past performance. i.e., high reserves

therefore high market price

Book value per share = equity share capital + shareholders reserves

Total no. of equity shares outstanding.

Cover (C)

It shows the extent to which the dividend per share is purchased by the earning of

the company. Cover has negative relationship with markets price.

Cover = profit after tax and preference dividend / equity dividend

Or

Cover = earning per share /dividend per share.

Dividend per share (DPS)

This relates to the amount of dividend declared per share. The net profit after

taxes belong to shareholders but the income that they really receive is the amount of

earnings distributed and paid as cash dividend. The dividend generally influence the

share price in positive direction

Dividend per share = Total amount (dividend) paid to equity shareholder

Number of equity shares outstanding



Earnings per share (EPS)

The equity shareholders are the sole claimants of the net earnings of the

corporation after making payments of dividend to the preference shareholder. The

significance of this ratio flows from the fact that higher the earnings per share, the more

is the scope for a higher rate of dividend and also of retained earning, to built up the inner

strength of the company, there fore higher EPS would increase the market price and vice

versa.

Earnings per share = net income after interest, income tax and preference dividend

Number of equity shares outstanding.

Dividend payout ratio (P)

Shows the percentage share of the net profit after taxes and preferences dividend

paid out as dividend to equity shareholders. The below formula predicts relation between

payout ratio and the price earning multiple. Conversely it means that there is an inverse

relation between payout ratio and share price changes.

Dividend payout ratio = Total dividend to equity shareholders *100

Total net profit belonging to equity shareholders

Or

Dividend payout ratio = Dividend per share /Earning per share.



Price / earning ratio (P/E)

It expresses the relationship between the market price of company share and its

earning per share. It indicates the extent to which the earnings of each share are covered

by its price. The ratio helps an investor to make an approximate calculation of the time

required to recover his investment in a companies share. The price-earning ratio has

positive relationship with market price.

P/E = market price per share / earnings per share.

Return on capital employed (ROCE)

It indicates the efficiency with which a company utilizes invested in it. This ratio

reveals how well the resources of a firm are being used, higher the ratio better are the

results. The inter-firm comparison of this ratio determines whether the investments are

attractive or not as the investor would like invest only where return is high. It has

generally positive relationship with market price

ROCE = Profit after Tax + Interest *100

Total Capital Employed

LIMITATIONS OF THE STUDY Some limitations of the stydu are..

The main draw back of the study is time constraint and availability of the data.

And only study covers four sectors and rest of them are not taken under it.

Only hundread and four companies are under the study.



CCHHAAPPTTEERR IIVV

AANNAALLYYSSIISS OOFF DDAATTAA

&& DDEESSCCRRIIPPTTIIOONN



DATA ANALYSIS AND INTERPRETATION

To determine the equity share prices the explanatory variables namely, dividend

per share, earnings per share, cover, dividend payout ratio, return on capital employed,

price earning ratio, book value and size these variables are treated as independent

variable. And the market price is considered to be dependent variable.

For the determinants of equity share prices the data has been collected for four

different sectors for five years from 2000-2005.

To analyze the determinants of equity the following model has been used.

Regression model:

�The linear multiple regression� approach has been applied primarily to

minimize the problem of multicollinearity. This technique of multivariate analysis was

selected because it is the most appropriate tool evaluating the individual and combined

effect of set of independent variables on dependent variable. The significance of

coefficient of various explanatory variables was tested at 10% and 5% by computing t-

values. To determine the proportion of explained variation in dependent variables,

coefficient of multiple determinations R2 was worked out. The overall significance of

regression equation was tested with the help of F-values



AGGREGATE COMPANIES YEAR WISE REGRESSION RESULTS YEAR 2000 (TABLE 4)

Model Summary

.755a .570 .539 311.939974

.753b .567 .541 311.420014

.750c .563 .541 311.335837

Model1

2

3

R R SquareAdjustedR Square

Std. Error ofthe Estimate

Predictors: (Constant), ROCE, DPR, BV, PE, COVER,DPS, EPS

a.

Predictors: (Constant), ROCE, BV, PE, COVER, DPS,EPS

b.

Predictors: (Constant), BV, PE, COVER, DPS, EPSc.

ANOVAd

12398379 7 1771196.937 18.202 .000a

9341429 96 97306.548

21739807 103

12332512 6 2055418.646 21.194 .000b

9407295 97 96982.425

21739807 103

12240667 5 2448133.358 25.257 .000c

9499140 98 96930.003

21739807 103

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Model1

2

3

Sum ofSquares df Mean Square F Sig.

Predictors: (Constant), ROCE, DPR, BV, PE, COVER, DPS, EPSa.

Predictors: (Constant), ROCE, BV, PE, COVER, DPS, EPSb.

Predictors: (Constant), BV, PE, COVER, DPS, EPSc.

Dependent Variable: SPd.



Coefficientsa

-195.794 62.488 -3.133 .002

.849 .622 .299 1.365 .176

60.614 13.078 .369 4.635 .000

72.250 10.977 .981 6.582 .000

-13.795 2.842 -.895 -4.854 .000

-96.103 116.809 -.067 -.823 .413

3.973 .917 .301 4.331 .000

-1.27E-03 .001 -.061 -.882 .380

-212.233 59.109 -3.591 .001

1.079 .556 .380 1.942 .055

61.244 13.033 .373 4.699 .000

67.954 9.639 .923 7.050 .000

-14.331 2.762 -.930 -5.188 .000

3.798 .891 .288 4.263 .000

-1.39E-03 .001 -.066 -.973 .333

-214.328 59.054 -3.629 .000

1.033 .553 .364 1.867 .065

59.723 12.936 .364 4.617 .000

68.735 9.603 .933 7.158 .000

-14.273 2.761 -.926 -5.170 .000

3.837 .890 .291 4.313 .000

(Constant)

BV

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

PE

Model1

2

3

B Std. Error

UnstandardizedCoefficients

Beta

Standardized

Coefficients

t Sig.

Dependent Variable: SPa.



YEAR 2001 (TABLE 5)

Model Summary

.788a .621 .593 183.749881

.788b .621 .597 182.800526

.787c .619 .600 182.221002

Model1

2

3



Predictors: (Constant), ROCE, PE, DPS, COVER, DPR,EPS, BV

a.

Predictors: (Constant), ROCE, PE, DPS, COVER, DPR,EPS

b.

Predictors: (Constant), PE, DPS, COVER, DPR, EPSc.

ANOVAd

5302190 7 757455.736 22.434 .000a

3241346 96 33764.019

8543536 103

5302181 6 883696.806 26.445 .000b

3241355 97 33416.032

8543536 103

5289496 51057899.116 31.860 .000c

3254040 98 33204.494

8543536 103

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Model1

2

3


Predictors: (Constant), ROCE, PE, DPS, COVER, DPR, EPS, BVa.

Predictors: (Constant), ROCE, PE, DPS, COVER, DPR, EPSb.

Predictors: (Constant), PE, DPS, COVER, DPR, EPSc.




Coefficientsa

14.150 34.323 .412 .681

-7.91E-03 .476 -.005 -.017 .987

23.918 6.077 .270 3.936 .000

63.133 10.021 1.380 6.300 .000

-7.229 1.648 -.939 -4.385 .000

-406.671 128.622 -.254 -3.162 .002

4.690 1.106 .276 4.241 .000

-6.18E-04 .001 -.039 -.602 .549

14.014 33.149 .423 .673

23.911 6.031 .269 3.964 .000

63.010 6.703 1.377 9.400 .000

-7.249 1.115 -.941 -6.503 .000

-406.130 123.787 -.254 -3.281 .001

4.692 1.091 .276 4.300 .000

-6.21E-04 .001 -.039 -.616 .539

13.449 33.031 .407 .685

23.607 5.992 .266 3.940 .000

63.313 6.664 1.384 9.501 .000

-7.317 1.106 -.950 -6.617 .000

-410.523 123.190 -.256 -3.332 .001

4.676 1.088 .275 4.300 .000

(Constant)

BV

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

COVER

DPS

EPS

DPR

PE

Model1

2

3

B Std. Error


Beta

Standardized

Coefficients

t Sig.




YEAR 2002 (TABLE 6) Model Summary

.765a .586 .555 174.198712

.765b .586 .559 173.309480

.761c .580 .558 173.636349

.759d .575 .558 173.612706

.753e .567 .554 174.445099

Model1

2

3

4

5



Predictors: (Constant), ROCE, PE, DPS, COVER, DPR,BV, EPS

a.

Predictors: (Constant), PE, DPS, COVER, DPR, BV,EPS

b.

Predictors: (Constant), DPS, COVER, DPR, BV, EPSc.

Predictors: (Constant), DPS, COVER, BV, EPSd.

Predictors: (Constant), DPS, BV, EPSe.

ANOVAf

4032469 7 576066.932 18.984 .000a

2852448 94 30345.191

6884916 101

4031480 6 671913.298 22.370 .000b

2853437 95 30036.176

6884916 101

3990557 5 798111.329 26.472 .000c

2894360 96 30149.582

6884916 101

3961203 4 990300.857 32.855 .000d

2923713 97 30141.372

6884916 101

3902669 3 1300889.806 42.749 .000e

2982247 98 30431.093

6884916 101

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Model1

2

3

4

5


Predictors: (Constant), ROCE, PE, DPS, COVER, DPR, BV, EPSa.

Predictors: (Constant), PE, DPS, COVER, DPR, BV, EPSb.

Predictors: (Constant), DPS, COVER, DPR, BV, EPSc.

Predictors: (Constant), DPS, COVER, BV, EPSd.


Dependent Variable: SPf.



Coefficients a

50.784 29.471 1.723 .088

-1.720 .308 -1.448 -5.578 .000

6.909 5.594 .095 1.235 .220

58.817 7.460 1.553 7.885 .000

2.718 1.814 .405 1.499 .137

-65.604 49.237 -.096 -1.332 .186

.835 .718 .084 1.162 .248

1.249E-04 .001 .012 .181 .857

50.959 29.305 1.739 .085

-1.714 .305 -1.443 -5.620 .000

7.078 5.487 .097 1.290 .200

58.662 7.373 1.549 7.957 .000

2.716 1.805 .405 1.505 .136

-65.721 48.982 -.096 -1.342 .183

.834 .715 .084 1.167 .246

48.187 29.264 1.647 .103

-1.751 .304 -1.474 -5.765 .000

7.829 5.459 .108 1.434 .155

59.524 7.349 1.572 8.099 .000

2.781 1.807 .415 1.539 .127

-45.192 45.801 -.066 -.987 .326

39.257 27.825 1.411 .161

-1.726 .303 -1.453 -5.702 .000

7.600 5.454 .104 1.394 .167

58.546 7.281 1.546 8.041 .000

2.798 1.807 .417 1.549 .125

62.899 22.161 2.838 .006

-1.751 .304 -1.474 -5.767 .000

56.096 7.100 1.481 7.901 .000

3.609 1.719 .538 2.100 .038

(Constant)

BV

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

DPR

PE

(Constant)

BV

COVER

DPS

EPS

DPR

(Constant)

BV

COVER

DPS

EPS

(Constant)

BV

DPS

EPS

Model1

2

3

4

5

B Std. Error


Beta

Standardized

Coefficients

t Sig.




YEAR 2003 (TABLE 7) Model Summary

.644a .414 .372 150.7263

.644b .414 .378 149.9475

.644c .414 .385 149.1879

.643d .414 .390 148.4836

.643e .413 .396 147.8333

Model1

2

3

4

5



Predictors: (Constant), ROCE, DPR, COVER, DPS, PE,BV, EPS

a.

Predictors: (Constant), ROCE, COVER, DPS, PE, BV,EPS

b.

Predictors: (Constant), COVER, DPS, PE, BV, EPSc.

Predictors: (Constant), DPS, PE, BV, EPSd.


ANOVAf

1543937 7 220562.497 9.709 .000a

2180969 96 22718.424

3724906 103

1543935 6 257322.419 11.445 .000b

2180972 97 22484.244

3724906 103

1543717 5 308743.440 13.872 .000c

2181189 98 22257.031

3724906 103

1542215 4 385553.805 17.488 .000d

2182691 99 22047.384

3724906 103

1539439 3 513146.404 23.480 .000e

2185467 100 21854.670

3724906 103

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Model1

2

3

4

5


Predictors: (Constant), ROCE, DPR, COVER, DPS, PE, BV, EPSa.

Predictors: (Constant), ROCE, COVER, DPS, PE, BV, EPSb.

Predictors: (Constant), COVER, DPS, PE, BV, EPSc.

Predictors: (Constant), DPS, PE, BV, EPSd.


Dependent Variable: SPf.



Coefficientsa

25.864 19.793 1.307 .194

.683 .278 .955 2.458 .016

-3.73E-06 .000 -.021 -.260 .795

21.275 4.004 1.048 5.313 .000

-4.415 1.261 -1.459 -3.502 .001

.104 9.101 .001 .011 .991

3.880E-02 .114 .027 .339 .735

-4.17E-05 .000 -.008 -.098 .922

25.863 19.691 1.313 .192

.683 .276 .955 2.473 .015

-3.73E-06 .000 -.021 -.262 .794

21.278 3.974 1.048 5.355 .000

-4.416 1.252 -1.459 -3.527 .001

3.895E-02 .113 .027 .345 .731

-4.16E-05 .000 -.008 -.098 .922

25.530 19.298 1.323 .189

.681 .274 .953 2.484 .015

-3.69E-06 .000 -.020 -.260 .796

21.311 3.939 1.050 5.410 .000

-4.416 1.245 -1.459 -3.546 .001

3.931E-02 .112 .027 .350 .727

25.177 19.159 1.314 .192

.673 .271 .942 2.482 .015

21.383 3.911 1.053 5.467 .000

-4.391 1.236 -1.451 -3.553 .001

3.967E-02 .112 .027 .355 .723

26.201 18.858 1.389 .168

.676 .270 .945 2.503 .014

21.307 3.888 1.049 5.480 .000

-4.394 1.230 -1.452 -3.572 .001

(Constant)

BV

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

PE

(Constant)

BV

DPS

EPS

PE

(Constant)

BV

DPS

EPS

Model1

2

3

4

5

B Std. Error


Beta

Standardized

Coefficients

t Sig.




YEAR 2004 (TABLE 8)

Model Summary

.700a .490 .458 248.655287

.700b .490 .464 247.415568

Model1

2



Predictors: (Constant), ROCE, PE, DPS, COVER, BV,EPS

a.

Predictors: (Constant), ROCE, DPS, COVER, BV, EPSb.

ANOVAc

5755834 6959305.591 15.515 .000a

5997457 97 61829.452

11753290 103

5754273 51150854.595 18.800 .000b

5999017 98 61214.463

11753290 103

Regression

Residual

Total

Regression

Residual

Total

Model1

2


Predictors: (Constant), ROCE, PE, DPS, COVER, BV, EPSa.

Predictors: (Constant), ROCE, DPS, COVER, BV, EPSb.

Dependent Variable: SPc.



Coefficientsa

-39.835 41.281 -.965 .337

1.114 .447 1.121 2.492 .014

33.402 10.554 .262 3.165 .002

44.480 7.062 1.890 6.299 .000

-9.945 1.694 -2.695 -5.870 .000

1.157E-03 .007 .012 .159 .874

-1.10E-03 .001 -.136 -1.794 .076

-39.584 41.045 -.964 .337

1.102 .438 1.108 2.516 .014

33.520 10.476 .263 3.200 .002

44.203 6.809 1.879 6.492 .000

-9.858 1.595 -2.671 -6.182 .000

-1.10E-03 .001 -.136 -1.802 .075

(Constant)

BV

COVER

DPS

EPS

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

ROCE

Model1

2

B Std. Error


Beta

Standardized

Coefficients

t Sig.




YEAR 2005 (TABLE 9)

Model Summary

.673a .454 .413 230.806493

.672b .452 .418 229.868999

.670c .449 .420 229.421399

Model1

2

3



Predictors: (Constant), ROCE, PE, DPS, DPR, COVER,EPS, BV

a.

Predictors: (Constant), PE, DPS, DPR, COVER, EPS,BV

b.

Predictors: (Constant), PE, DPS, COVER, EPS, BVc.

ANOVAd

4199923 7 599989.058 11.263 .000a

5060806 95 53271.637

9260729 102

4188112 6 698018.714 13.210 .000b

5072617 96 52839.757

9260729 102

4155214 5 831042.728 15.789 .000c

5105515 97 52634.178

9260729 102

Regression

Residual

Total

Regression

Residual

Total

Regression

Residual

Total

Model1

2

3


Predictors: (Constant), ROCE, PE, DPS, DPR, COVER, EPS, BVa.

Predictors: (Constant), PE, DPS, DPR, COVER, EPS, BVb.

Predictors: (Constant), PE, DPS, COVER, EPS, BVc.




Coefficientsa

63.673 39.965 1.593 .114

-.732 .307 -.960 -2.387 .019

21.988 9.025 .211 2.436 .017

37.281 6.802 1.866 5.481 .000

-2.099 1.020 -.591 -2.058 .042

108.712 135.933 .080 .800 .426

-1.567 .568 -.223 -2.759 .007

-2.32E-04 .000 -.037 -.471 .639

63.784 39.802 1.603 .112

-.750 .303 -.984 -2.474 .015

21.251 8.853 .204 2.401 .018

37.598 6.741 1.882 5.577 .000

-2.080 1.015 -.586 -2.050 .043

106.775 135.319 .078 .789 .432

-1.567 .566 -.223 -2.770 .007

79.503 34.391 2.312 .023

-.845 .277 -1.109 -3.049 .003

22.642 8.658 .217 2.615 .010

40.827 5.347 2.044 7.635 .000

-2.188 1.004 -.616 -2.180 .032

-1.492 .557 -.212 -2.681 .009

(Constant)

BV

COVER

DPS

EPS

DPR

PE

ROCE

(Constant)

BV

COVER

DPS

EPS

DPR

PE

(Constant)

BV

COVER

DPS

EPS

PE

Model1

2

3

B Std. Error


Beta

Standardized

Coefficients

t Sig.




ANLYSIS AND INTERPRETATION OF AGGREGATE COMPANIES REGRESSION RESULTS TABLE 10

It is clearly shows from the regression results from various years that in the

aggregate industry earning per Share is the most important determinant of market price

among the different variables. And the coefficient of respective years is positively

significance at 5% level. Dividend per share is also significance in all the years. And their

respective coefficients are positively significance at 5% level

The coefficient of book value per share is positively significance at 55 level in the

year 2003 and 2004.but in the year 2000 it is positive significance at 10% level. And in

case of 2002 and 2005 negatively significance at 5% level, in 2001 it is not significance.

Cover is also found to be positive significance at 5% in all the year except 2002

and 2003.Dividend per ratio is negatively significance at 5% level in the 2001 and not

significance in the rest of the years. Price Earning ratio which is positively significance at

5% level in 2000, 2001 and negative significance in the year 2005. Return on capital

Employed has negative significance in the year 2004 and rests of the year are not

significance.

AGG IND BV COVER DPS EPS DPR PE ROCE Adj R2 F-Value 2000 Y** Y* Y* Y* Y* Y* N 0.539 18.202* 2001 N Y* Y* Y* Y* Y* N 0.593 22.434* 2002 Y* N Y* Y* N N N 0.555 18.984* 2003 Y* N Y* Y* N N N 0.372 9.709*

2004 Y* Y* Y* Y* N N Y** 0.458 15.515* 2005 Y* Y* Y* Y* N Y* N 0.413 11.263*



The coefficient of determination (R2) is increased in the year 2001, 2004

respectively but decreases in 2005 at the level of 5% significance. And the R2 is

explained 41.3% in the 2005 which was lower than compared to 53.9% in 2000 which

has decrease in variation. All these leads that the Earning per Share is the most

determinant of share price followed by the Dividend Per share and cover

The average R2 of all sample companies is 51.7% of significance in the study but

rest of 49% was not significance so study shows that there are some other determinants

which are directly affects on share price our study din�t focused on it. Considering into

the earning per share has negative value in all the year except in 2002 hence the earning

per share also has a negative relation with share price. If there is positive increase in

earning per share there will be higher the market price.

Dividend per share has more significance in its value in all the year which

generally influences the share price in positive direction higher the dividend higher would

be the share price. And rest of the variables dint shows the positive reaction all the years.

SECTOR WISE ANALYSIS BANKING AND FINANCIAL INSTITUTION

As far as industry/institution wise analysis is concerned, banking and financial

institutions price earning ratio has a positively significance at 5% level in all the year

except for 2005 and even book value per share is positively significance at 5% level

except in 2000.

Where as concerned with the cover and earnings per share, which is not

significance in all the years and cover has negatively significance in the year2002 at 10 %

level. Dividend per share also shown positive significance at 5% in 2000 Dividend per



ratio results in 5% level of significance in 2002 and return on capital employed also in

2000 and 2003.

The coefficient of determination R2 indicates the variable could explain 71.4 in

2005, but it was 91.9 compared with 2000 the computed F-Values found to be

significance at 5% level of significance in all the year in this sector nearly 80% of the

share price determined by the variables enter and in study shows that the in most of the

year dividend payout ratio has negatively significance this may effect on determing the

market share price

Hence the analysis says that the price earning ratio is the most important factor

followed by the book value per share that affects the share prices in banking and financial

institutions.

HOTEL AND RESORTS SERVICE INDUSTRIES

In hotel and service industries, the book value per share found to be positive

significance at 5% level in all the year except in 2000 which was not significance at 5%

as well as 10% level of significance. Cover has positive significance at 5% level in 2000.

And negatively significance at 10% level in 2002.

Dividend per share has positive at 5% level in the year 2000, 2002, and 2003. And

has 10% level of significance in the year2001. Earning per share, dividend per share and

return on capital employed has no significance.

The coefficient of determination R2 was 94% in 2005, which was 58.8% in 2000.

And the F �Value found to be significance at 5%level in all the years. Hence the result

proved excessively high book value often raises the expectations for bonus issue

significance affects the market price of share.



PETROLEUM AND LUBRICANT INDUSTRIES

In petroleum and lubricant industries book value per share is treated as the most

important determinant of share price. It has a positive significance at 5% level of in 2003,

2004 and 2005. Cover has positive significance at 5% and 10% in 2000 and 2001

respectively.

Dividend per share only significance at 5% level in 2002 and 2003.earning price

per ratio has positive significance in 2000 and 2001. And rest of the variables in the study

for the remaining years is not significance

The coefficient of determination R2 varies from 77.3% that of in 2000 to 74.1% in

2005.and F-values to be found positive significance at 5% level in all the respective

years. Hence the book value per share is the main determinant factor, which affects on

market price in petroleum and lubricant industries.

PHARMACEUTICALS AND DRUG INDUSTRIES

In pharmaceutical and drug industries, dividend per share has the most

significance at 5% level in all the year except in 2001.book value per share also has

positive significance in first two years and last year. Price earning ratio also has positive

significance at 5% level in first two years and 2003. Cover, which also has positive

significance at 5% level in first two years and 2004. Rest of the variables is not

significance

The coefficient of determination R2 found in 2000 was 96.7% but it declines to

76.5% in 2005. And F � values to be found positively significance in all the year.



TABLE 11: SUMMARY OF ALL REGRESSION RESULTS

DETERMINANTS OF EQUITY SHARE PRICE IN VARIOUS REGRESSION RESULTS

VARI/YEAR INDUSTRY BV COVER DPS EPS DPR PE ROCE 2000 B & F N N Y* N Y* Y* Y*

H & R N Y* Y* N Y* Y* Y* P & L Y* Y* N Y* N N N P & D Y** Y* Y* Y* Y* Y* N AGGREGATE Y** Y* Y* Y* Y* Y* N

2001 B & F Y* N Y** N N Y* N H & R Y* N Y** N Y** N N P & L Y* Y** N Y* N N N P & D Y* Y* N N Y* Y* Y* AGGREGATE N Y* Y* Y* Y* Y* N

2002 B & F Y* Y** N N Y* Y* Y* H & R Y* N Y* N Y** N N P & L N N Y* N Y* Y* N P & D N N N Y* N N N AGGREGATE Y* N Y* Y* N N N

2003 B & F Y* N N N Y* Y* Y* H & R Y* N Y* N Y* Y* N P & L Y* N Y* Y* N N N P & D N N Y* N Y* Y* N AGGREGATE Y* N Y* Y* N N N

2004 B & F Y* N N N N Y* Y* H & R Y* N N N N N N P & L Y* N N N N N N P & D N Y* Y* N N N N AGGREGATE Y* Y* Y* Y* N N Y**

2005 B & F Y* N N N N N Y* H & R Y* N N N N N N P & L Y* N N N N N N P & D Y* N Y* N N Y* N AGGREGATE Y* Y* Y* Y* N Y* N Y* & Y** INDICATES SIGNIFICANCE AT 5% & 10% LEVEL respectively. B & F banking and financial: H & R hotel and resorts: P & L petroleum and lubricant: P & D pharmaceuticals and drug companies.



TABLE 12 F-values and adjusted R2

COEFFICIENT OF DETERMINATION OF VARIOUS INDUSTRY REGRESSION RESULTS

YEAR/INDUSTRY VALUES 2000 2001 2002 2003 2004 2005 AVG

Adj R2 0.919 0.552 0.582 0.73 0.825 0.714 0.801 BANKING &FINANCIAL F- value 48.128* 6.108* 6.763* 12.179* 20.494* 10.989* 17.659*

Adj R2 0.588 781 0.789 0.854 0.819 0.903 0.946 HOTELS & RESORTS F- value 6.92* 15.755* 16.488* 25.307* 19.75* 39.426* 73.647*

Adj R2 0.773 0.64 0.853 0.826 0.768 0.741 0.56 PETRLOLEUM &LUBRICANTS F- value 7.321* 4.296* 10.944* 9.806* 7.133* 6.312* 3.366*

Adj R2 0.967 0.95 0.601 0.761 0.846 0.765 0.775

PHARMACEUTICALS F- value 120.9* 79.499* 7.229* 14.183* 27.5* 14.451* 17.835*

Adj R2 0.539 0.593 0.555 0.372 0.458 0.413 0.517 AGGREGATE INDUSTRY F- value 18.202* 22.434* 18.984* 9.709* 15.515* 11.263* 16.78*

Y* INDICATES AT 5% LEVEL



CCHHAAPPTTEERR VV

SSUUMMMMAARRYY

&& CCOONNCCLLUUSSIIOONN



CONCLUSION

The present study attempts to examine the empirical relationship of explanatory

variables namely, dividend per share, earning per share ,price earning ratio, book value

per share, cover, return on capital employed and payout ratio on market price of shares in

the post reform era of liberalization. The relationship between independent variables and

dependent variable of 104 companies is studied over six years ranging from 2000-2005.

The result revealed that book value per share are important determinants of share

price as they are an index of sound financial position of the companies.but practically if

we looked that book value to market price is not important or highly significance in

determination of market price.

The result revealed Dividend per share is important determinant of share price,

which shows that the companies should adopt a liberal dividend policy to activate the

primary as well secondary market. A high dividend rate may also help in increasing the

market price and result in high capital appreciation to the shareholders as depicted by

payout ratio but practically growing companies and companies which have high potential

future growth rate they may not give high dividend and they reserved for future

expansion.

Our statistical study reveal that Price earning ratio not highly affected to market

price but practically since earning per share highly affecting in determination of market

price. Since earning per share and market price are essential variables while calculating

the price earning ratio so the price earning ratio is highly significance in determination of

market price.

Our statistical study reveal that ROCE is not significanclly affecting the

determination of share prices. But investors who are looking for long term investment

ROCE is the cut off rate. It means that they are looking minimum appreciation of market

price.



CCHHAAPPTTEERR VVII

BBIIBBIILLOOGGRREEAAPPHHYY

&&AANNNNEEXXUURREESS



BIBILOGRAPHY

JOURNLAS:

Downs T W. (1991) �An alternative approach to fundamental analysis: The asset

side of the equation�, journal of portfolio management, vol 17, No. 2, pp 6-17.

Dutta S K, (2004), �The share Price and its Valuation�, The Management

Accountant, vol. 39, No. 4, pp 274-282.

Malkar B and Gupta R (2002),� Determinants of Share Price-A system approach:

The modified Model�, finance India, vol. 16, No. 4, pp 1409-1418.

Tuli Nishi and Mittal R K ,(2001),�Determinants of price Earning Ratio�, finance

India, val.15, No. 4, pp. 1235-1250.

Zahir M A and Khanna, Y, (1982),� Determinants of stock prices in India�, The

Chartered Accountant, vol. 30, No. 8, pp. 521-523.

SOFTWARE USED:

Prowess software

Capitaline

SPSS 10

WEBSITES:

www.nseindia.com

www.google.com

www.yahoo.com/finance

www.equitymaster.com

http://www.nseindia.com

http://www.google.com

http://www.yahoo.com/finance

http://www.equitymaster.com



ANNEXURES LIST OF COMPANIES UNDER THE STUDY

BANKING AND FINANCIAL DRUGS AND PHARMACEUTICALS

Bank Of Baroda Aarti Drugs Ltd.

Bank Of India Alembic Ltd.

Bank Of Madura Ltd. [Merged] Arvind Remedies Ltd.

Bank Of Punjab Ltd. [Merged] Aurobindo Pharma Ltd.

Bank Of Rajasthan Ltd. Aventis Pharma Ltd.

Centurion Bank Of Punjab Ltd. Burroughs Wellcome (India) Ltd. [Merged]

City Union Bank Ltd. Cipla Ltd.

Corporation Bank D I L Ltd.

Dena Bank Dr. Reddy'S Laboratories Ltd.

Dhanalakshmi Bank Ltd. Glaxosmithkline Pharmaceuticals Ltd.

Federal Bank Ltd. Glenmark Pharmaceuticals Ltd.

Global Trust Bank Ltd. [Merged] J B Chemicals & Pharmaceuticals Ltd.

H D F C Bank Ltd. Jagsonpal Pharmaceuticals Ltd.

I C I C I Bank Ltd. Merck Ltd.

I D B I Bank Ltd. [Merged] Morepen Laboratories Ltd.

I N G Vysya Bank Ltd. Nicholas Piramal India Ltd.

Indusind Bank Ltd. Novartis India Ltd.

Industrial Development Bank Of

India Ltd.

Orchid Chemicals & Pharmaceuticals Ltd.

Jammu & Kashmir Bank Ltd. Panacea Biotec Ltd.

Kotak Mahindra Bank Ltd. Pfizer Ltd.

Nedungadi Bank Ltd. [Merged] Pharmacia Healthcare Ltd. [Merged]

Oriental Bank Of Commerce Ranbaxy Laboratories Ltd.

South Indian Bank Ltd. Shasun Chemicals & Drugs Ltd.

State Bank Of Bikaner & Jaipur Sun Pharmaceutical Inds. Ltd.

State Bank Of India Syncom Formulations (India) Ltd.

State Bank Of Mysore Torrent Pharmaceuticals Ltd.

State Bank Of Travancore Unichem Laboratories Ltd.

Syndicate Bank Wockhardt Ltd.

U T I Bank Ltd. Wyeth Ltd.

United Western Bank Ltd. Zandu Pharmaceutical Works Ltd.



HOTEL AND RESORTS PETROLEUM AND LUBRICANTS

Advani Hotels & Resorts (India)

Ltd.

Bharat Petroleum Corpn. Ltd.

Asian Hotels Ltd. Bongaigaon Refinery & Petrochemicals Ltd.

Benares Hotels Ltd. Castrol India Ltd.

Blue Coast Hotels & Resorts Ltd. Chennai Petroleum Corpn. Ltd.

Cindrella Hotels Ltd. Crazy Infotech Ltd.

E I H Associated Hotels Ltd. Goa Carbon Ltd.

E I H Ltd. Hindustan Petroleum Corpn. Ltd.

Fomento Resorts & Hotels Ltd. Indian Oil Corpn. Ltd.

G L Hotels Ltd. Kochi Refineries Ltd.

Gujarat Hotels Ltd. Mangalore Refinery & Petrochemicals Ltd.

H S India Ltd. Panama Petrochem Ltd.

Hotel Leelaventure Ltd. Rain Calcining Ltd.

I T C Hotels Ltd. [Merged] Reliance Industries Ltd.

Indian Hotels Co. Ltd. Savita Chemicals Ltd.

Indian Resort Hotels Ltd.

Jaypee Hotels Ltd.

Jindal Hotels Ltd.

Kamat Hotels (India) Ltd.

Khyati Multimedia Entertainment

Ltd.

Mac Charles (India) Ltd.

Oriental Hotels Ltd.

Ras Resorts & Apart Hotels Ltd.

Royale Manor Hotels & Inds. Ltd.

Savera Hotels Ltd.

Sayaji Hotels Ltd.

Sinclairs Hotels Ltd.

Sterling Holiday Resorts (India)

Ltd.

U G Hotels & Resorts Ltd.

Velan Hotels Ltd.

Viceroy Hotels Ltd.

Documents

Determinants of Equityshare Prices-BandiPrasad Sangappa-0467