AN ANALYTICAL STUDY ON THE VOLATILITY OF SECURITIES TRADED ON BSE SENSEX”

A

COMPREHENSIVE PROJECT REPORT

ON

“AN ANALYTICAL STUDY ON THE VOLATILITY OF SECURITIES TRADED ON

BSE SENSEX”

Submitted to

SHREE R. R. TANTI INSTITUTE OF MANAGEMENT, ANKLESHWAR

IN PARTIAL FULFILLMENT OF THEREQUIREMENT OF THE AWARD FOR THE DEGREE OF

MASTER OF BUSINESS ADMINISTRATION

Under

Gujarat Technological University

UNDER THE GUIDANCE OF

MR.JAYDIP DESAISubmitted by

SAGAR PAREKH MANISH GOLE

M.B.A-SEMESTER III/IV

SHREE R. R. TANTI INSTITUTE OF MANAGEMENT, ANKLESHWAR

M.B.A-PROGRAMME

Affiliated to Gujarat Technological University

Ahmadabad

December 2011-12

1

DECLARATION

We Mr. SAGAR PAREKH & Mr. MANISH GOLE hereby declare that the reportfor

“Comprehensive Project” entitled AN ANALYTICAL STUDY ON THE

VOLATILITYOFSECURITIES TRADED ON BSE SENSEX”

is a result of our own work and our indebtedness to other work

Publications, references, if any, have been duly acknowledged.

PLACE:

DATE: SAGAR PAREKH

MANISH GOLE

2

INSTITUTIONAL CERTIFICATE

PREFACE

3

MBA is a stepping-stone to the management carrier and to develop good

manager it is necessary that the theoretical must be supplemented with exposure

to the real environment. Theoretical knowledge just provides the base and it‘s not

sufficient to produce a good manager that‘s why practical knowledge is needed.

The Professional training is the internal part of a MBA Program. It helps the

students understand practical aspects of Business Management in a better way

as a part of our MBA program at “Shree r.r.tanti institute of management”.

We were required to undertake a detailed study of the “AN ANALYTICAL STUDY

ON THE VOLATILITY OF SECURITIES TRADED ON BSE SENSEX”using

different statistical functions such as beta, Correlation, variance, standard deviation

The theoretical knowledge & conceptual ideas are the background for the career

development but project work has also equal contribution for occur. The

sentence ―experience is the best teacher is very true in every field & so project

work during the course is arranged to develop the skill & attitude.

It is rightly said that practice makes a man perfect. In order to achieve excellence

and success, theoretical knowledge must be supplemented with practical

knowledge and practical work i.e. is Project work. Among the numerous

interesting things concerned with changing the understanding of management

students, this project work plays an important role in development of us.

ACKNOWLEDGEMENT

4

Learning is a delightful experience and in the ocean of knowledge you can

acquire limitless understanding through your craving for it. And in our craving to

know more, it has been memorizing extravagance of memorable experience. At

this enlightening moment of completion of our project, we feel obliged to record

my heartfelt and deep gratitude to those who have helped me.

Firstly, we would like to thank the almighty GOD, who bestowed upon us this

opportunity for working on this project and generated the capacity to successfully

complete the project.

We are extremely indebted to our project mentor Mr.Jaydip Desai (Director

incharge) for his valuable suggestions and guidance, which ensured an in-depth

learning and understanding of the concepts. His inputs from past experiences

and practical interpretation of the problem helped us a lot in comprehending the

requirements of the project. This ensured great learning for us. He was always

helpful enough & was always able to take out some time off his busy schedule to

guide us in this project. Lastly, we say we are lucky enough that we trained under

his!

Words are insufficient to express our gratitude towards Miss.Bhumika Bhatt

(professor -finance) for their immense help and invaluable guidance in

conduction of this study from its conception to its completion.

TABLE OF CONTENT

5

Sr. no. Particulars Page No.

Chapter 1

General Information 8

1.1 Overview of World Market 8

1.2 Overview of Indian Capital market 9

1.3 Growth of the Stock Market 13

Chapter 2 About major industry 14

Chapter 3 Introduction of study18

3.1 Literature Review18

3.2 Background of the study21

3.3 Problem Statement24

3.4 Objective of the Study25

Chapter 4 Research Methodology26

4.1 Research Design26

4.2 Sources of Data26

4.3 Population26

4.4 Statistical tool27

Chapter 5 PROFILE OF THE INDUSTRY AND COMPANY

5.1 INDUSTRY PROFILE 29

5.2 COMPANY PROFILES 31

Chapter 6 DATA ANALYSIS AND INTERPRETATION 38

Chapter 7 Findings74

Chapter 8 Conclusion76

Chapter 9 Suggestion and recommendation77

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BIBILOGRAPHY79

LIST OF TABLES

Sr.no. TOPIC PAGE NO

1 Volatility of BHEL (Capital Goods) return

2 Volatility of ACC LTD. | (Housing related)

3 Volatility of Bharti Airtel (Telecom) return

4 Volatility of Grasim Industries ( Diversified) return

5 Volatility of HDFC Bank | Finance. Return

6 Volatility of Hindalco Industries | Metal, Metal Products &

Mining.. Return

7 Volatility of Hindustan Uni Lever | FMCG. Return

8 Volatility of Mahindra and Mahindra | Transport Equipments

Return

10 Volatility of NTPC | Power |Return

11 Volatility of Larsen & Toubro | Capital Goods Return

12 Volatility of Reliance Industries | Oil & GasReturn

13 Volatility of State Bank of India | Finance Return

14 Volatility of Ranbaxy Laboratories | Healthcare

15 Volatility of TCS | Information Technology

16 Volatility of ONGC | Oil and Gas

EXECUTIVE SUMMARY

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Master of Business Administration student is a matter of pride because we are in a

field, which helps us to develop from a normal human being into a disciplined, and

dedicated professional. One has to be a good learner to sharper knowledge in the

particular field to achieve and attain the desired goals and heights. Being M.B.A

finance student’s and the interest area towered the financial Market we are taking

the topic of “AN ANALYTICAL STUDY ON THE VOLATILITY OF SECURITIES

TRADED ON BSE SENSEX” for the research purpose. From this research we

actually fulfill our purpose of how the individual investee will look towards the

Financial Market and how he/she invest money in financial market.

In this topic our objective is to find out how we can make investment by analysis

of the bse sensex for only top traded 30 scrips which I selected 15 for analysis.

Volatility of securities price has important implications for firm’s investment and

financial decisions, valuations and investors sentiments. Price volatility of

securities has consequence for firm’s decisions on how much capital to issue,

type of instrument to be used when to use. Further high price volatility provides

opportunities for expropriations between various market players.

There for the study of volatility of security is very important contextual as well.

Here analytical study of volatility of securities traded on Bombay Stock Exchange

is the topic of this dissertation.

CHAPTER 1

8

1.1 Overview of World Market

Global Market Economy – Current Scenario

During last one-decade capital markets around the globe witnessed a series of

developments in terms of its movements, volatility and capitalization. Despite the

bearishness in the first half of 2003 due to war on terrorism, epidemic outbreaks,

and economic sluggishness, the markets in the advanced economies received

substantial benefits in terms of rise in Gross Domestic Product (GDP). For

example, in high-Income Countries, the market capitalization as a percentage of

GDP was as high as 103.9%, where as in low-income countries it was at 18.3%

(For India, it was 23.1% as against the world‘s percentage at 90.7). A number of

initiatives undertaken to attract cross border Investments through liberalized

trade policies globalised economic reforms, portfolio investments ranging from

24% to 100% of the paid-up capital with repatriation facility in certain cases were

the prime factors of Asia now being in focus in the capital market. At present the

Foreign Institutional Investors (FIIs) are concentrating in the emerging markets

due to the fact that the rate of return on investment as well inflation rate in the

emerging economies are slightly higher than the market to which they belong.

World Trade

The trade volume of the world is estimated at 3% for 2003, which is less the

growth rate 3.2% for the year2002. A sharp rise in oil prices has surged the

commodity prices. Consumer goods prices in the advanced countries reached

around 1.8% as compared to 1.5% in 2002 whereas it is 5% in developing

countries for both of the years. Increase in the volume of trade is one of the

potential causes for development of capital market of the economy. Ongoing

discussions among the member countries of the World Trade Organization

9

(WTO) have to be taken into account for overall development and integration of

global capital markets.

World stock market & Bullion Market

The sharp fall of US dollar as against the Euro, Sterling and yen have brought

worries to the international investors in the US market and therefore there was

lesser demand for US securities. This situation made US to start investing

elsewhere in the global market. As a result the Asian countries received

substantial increase in the foreign exchange reserves. The evolution of Euro

currency due to the coordinate efforts of member countries set a classic example

of how common currency can stabilize the economic growth. In the bullion

market, Gold is now commanding at its very high in its 13 years not track record

and other metals like silver and platinum are showing an upward trend.

1.2 Overview of Indian Capital market

Meaning of Capital Market

Capital Market may be defined as a market dealing in medium and longterm

funds. It is an institutional arrangement for borrowing medium and long-term

funds and which provides facilities for marketing and trading of securities. So it

constitutes all long-term borrowings from banks and financial institutions,

borrowings from foreign markets and raising of capital by issue various securities

such as shares debentures, bonds, etc. The market where securities are traded

known as Securities market. It consists of two different segments namely primary

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and secondary market. The primary market deals with new or fresh issue of

securities and is, therefore, also known as new issue market; Whereas the

secondary market provides a place for purchase and sale of existing securities

and is often termed as stock market or stock exchange.

1) PRIMARY MARKET

The Primary Market consists of arrangements, which facilitate the procurement of

long term funds by companies by making fresh issue of shares and debentures.

You know that companies make fresh issue of shares and/or debentures at their

formation stage and, if necessary, subsequently for the expansion of business. It

is usually done through private placement to friends, relatives and financial

institutions or by making public issue

2) SECONDARY MARKET

The secondary market known as stock market or stock exchange plays an

equally important role in mobilizing long-term funds by providing the necessary

liquidity to holdings in shares and debentures. It provides a place where these

securities can be encased without any difficulty and delay. It is an organized

market where shares, and debentures are traded regularly with high degree of

transparency and security. In fact, an active secondary market facilitates the

growth of primary market as the investors in the primary market are assured of a

continuous market for liquidity of their holdings. The major players in the primary

market are merchant bankers, mutual funds, financial institutions, and the

individual investors; and in the secondary market you have all these and the

stockbrokers who are members of the stock exchange who facilitate the trading.

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History of Indian Capital Markets

The history of the Indian capital markets and the stock market, in particular can

be traced back to 1861 when the American Civil War began. The opening of the

Suez Canal during the 1860s led to a tremendous increase in exports to the

United Kingdom and United States. Several companies were formed during this

period and many banks came to the fore to handle the finances relating to these

trades. With many of these registered under the British Companies Act, the Stock

Exchange, Mumbai, came into existence in 1875. It was an unincorporated body

of stockbrokers, which started doing business in the city under a banyan tree.

Business was essentially confined to company owners and brokers, with very

little interest evinced by the general public. There had been much fluctuation in

the stock market on account of the American war and the battles in Europe. Sir

Premchand Roychand remained a kingpin for many years.

Sir Phiroze Jeejeebhoy was another who dominated the stock market nscene

from 1946 to 1980. His word was law and he had a great deal of influence over

both brokers and the government. The planning process started in India in 1951,

with importance being given to the formation of institutions and markets. The

Securities Contract Regulation Act 1956 became the parent regulation after the

Indian Contract Act 1872, a basic law to be followed by security markets in India.

To regulate the issue of share prices, the stock markets have had many turbulent

times in the last 140 years of their existence. The imposition of wealth and

expenditure tax in 1957 by Mr. T.T.Krishnamachari, the then finance minister, led

to a huge fall in the markets. The dividend freeze and tax on bonus issues in

1958-59 also had a negative impact. War with China in 1962 was another

memorably bad year, with the resultant shortages increasing prices all round.

This led to a ban on forward trading in commodity markets in 1966, which was

again a very bad period, together with the introduction of the Gold Control Act in

1963. The markets have witnessed several golden times too. Retail investors

began participating in the stock markets in a small way with the dilution of the

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FERA in 1978. Multinational companies, with operations in India, were forced to

reduce foreign share holding to below a certain percentage, which led to a

compulsory sale of shares or issuance of fresh stock. There was no free pricing

and their formula was very conservative. The next big boom and mass

participation by retail investors happened in 1980, with the entry of Mr. Dhirubhai

Ambani.Dhirubhai can be said to be the Father of modern capital markets. The

Reliance public issue and subsequent issues on various Reliance companies

generated huge interest. The general public was so unfamiliar with share

certificates that Dhirubhai is rumored to have distributed them to educate people.

Mr. V.P.Singh’s fiscal budget in 1984 was path breaking for it started the era of

liberalization.

Source:http://www.bukisa.com/articles/442796_capital-markets-

anoverview#ixzz1KgqtH7su

India’s capital markets have experienced sweeping changes since the beginning

of the last decade. Its market infrastructure has advanced while corporate

governance has progressed faster than in many other emerging market

economies. But in contrast to several developed countries and Asian economies,

India’s capital markets are still shallow, implying that further reforms are needed

to make India a world-class financial centre. At nearly 40% of GDP, the size of

India’s government bond segment is comparable to many other emerging market

economies.

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1.3 Growth of the Stock Market

Despite the international disturbances like Iraq war, SARS, Bird flu in Asia,

terrorism threats and other natural calamities, capital market has shown steady

growth in 2003. There was an increased demand for the Asian equities. The

favorable liquidity conditions and macro environment factors accelerated further

growth in Asian markets. Indian sensex rose to 80% outperforming all the major

global indices. European markets have also shown remarkable progress.

Currently factors are encouraging FIIs to think about the investment proposals in

other countries. Another interesting factor in the global scenario is that the cross

border capital flow is largely flowing from FII‘s in the private sectors as compared

to public sectors of developing economies. There are few countries in the world,

which received mhigher turnover-ratio than India. The FII‘s investment in India as

on June 2003 was at US $ 17.39 billion with 509 registered FII‘s. India stood 19 th

place in terms of capitalization . In terms of turnover-ratio, India ranked 7th in

position. Emerging Economies: The year 2003 was the year for emerging

economies. These economies undertook a number of initiatives in relation to their

fiscal and economic policies, which have contributed, substantially to the stability

of the world economy. The current fiscal year 2004 is a year of prospects and

promises for higher economic growth and fruitful activity in the capital market.

Lower exchange reserves and it has been predicted that the largest economies

in 2050 would be China, India, Russia and Japan. China showed strong growth

of indication with a real GDP at 8.7%. It has a market capitalization of 220 billion

dollars Nearly 20 out of 25 emerging country economies stock prices rose by

25% and amongst eight countries it was more than 75%. Further, currencies of

these countries appreciated against the US dollar.

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CHAPTER 2: About major industry

ELECTRICAL EQUIPMENT

CEMENT PRODUCTS

BANKS

TELECOMMUNICATION – SERVICES

ELECTRICAL EQUIPMENT REFINERIES OIL

EXPLORATION/PRODUCTION

PHARMACEUTICALS CONSTRUCTION GAS

COMPUTERS – SOFTWARE

FINANCE – HOUSING BANKS

AUTOMOBILES – 2 AND 3 WHEELERS

ALUMINIUM ,

DIVERSIFIED

FINANCIAL INSTITUTION

CIGARETTES

STEEL AND STEEL PRODUCTS

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CHAPTER 3: Introduction of study

The Sensex falls by 36% in a day of hectic trading. The reserve Bank of

India lowers the repo rate by 25 basis points. The government of India raises

4500 crore rupees by issuing bonds with a maturity of 10 years. So on and so

forth all these are examples of securities market at work. Most people are aware

that this market has an important bearing on modern life and glibly speak of

“Dalal Street” the “gilt Edged Market” and the “Nifty” with a some what vague

understanding of these terms.

Factors responsible for price fluctuations

In a securities market, prices or returns show fluctuations for a variety of

reasons: changes in fundamental factors of firms, like, investors endowments,

tastes or alternatively the attitudes towards risk, correct or incorrect anticipations

or expectations of investor and other market participants, differences in

information and mode of evaluation, transient imbalances between demand for

and supply of securities, and the nature and number of stabilizing forces, among

others, cause prices to fluctuate either from one point of equilibrium to another or

above and below an equilibrium point.

The changes in fundamental factors cause prices or returns to shift from

one point of equilibrium to another. For instance, information regarding changes

in the economy, changes in policies, including industrial policy, as also the

political situation, and the social situation, influence the over all price behavior of

a market.

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Apart from fundamental factors, the transitory imbalances between supply

of and demand for securities may also cause price fluctuations. For instance, in

the absence of stabilizing forces, excess supply (demand) of securities in the

short- run causes the price to fall (rise). In the presence of stabilizing forces, such

as traditional speculators and value based investors, the extent of fluctuations

tend to be small, as these stabilizing forces act as buyers (sellers), when there is

excess of supply (demand), thus, arresting the magnitude of a fall (rise) in the

price. However, the stabilizing forces may not completely mitigate the price

change; as such acts may not bestow any benefit on them. These forces require

a minimum extent of price change in order to undertake the act of stabilization of

prices, which would give them scope to earn a responsible reward.

The expectations and foresight of investors as well as speculators

determine the magnitude of price fluctuations to a large extent. If market

participants anticipate changes.

In either fundamental factors or technical factors correctly, and if the

change or anticipated change comes about gradually, the prices move in a

smooth fashion from one point of equilibrium to another. On the contrary, when

the anticipations prove to be either too optimistic or too pessimistic, or the

changes in these factors or anticipations about them, undergo a sudden change,

the prices move erratically, rather than move in a smooth fashion resulting in

greater price fluctuations.

The numbers of speculations in relation to other traders also influences

the extent of fluctuations. The traditional role of a speculator is to act as a buyer

when there is excess supply and as a seller when there is excess demand.

Changes in fundamental and other factors as well as correct or incorrect

anticipations also determine the short- term and the long- term price changes. If

the changes takes place gradually and anticipations prove to be correct, the

short-term fluctuations tend to be similar in magnitude as that of average long-

term fluctuations, as in this case, the short-term fluctuations or price changes

17

tend to be one direction, which add up to determine long- term fluctuations. On

the contrary, if the anticipations are not correct, irrespective of mode of arrival of

information- whether gradual or not gradual the average long-term fluctuations

tend to be smaller than the short-term fluctuations.

It is clear that the fluctuation of prices or price volatility is influenced by the

arrival of information- gradual or otherwise- and the correct or incorrect

anticipation of market participants. Further, the role played by speculators either

corrects the situation by minimizing the extent of fluctuations, or further

accentuates fluctuations and thereby destabilizes prices.

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3.1 Literature Review

Seasonality or calendar anomalies such as month of the year and day of the

week effects has remained a topic of interest for research since long time in

developed as well as developing countries. Watchel (1942) reported seasonality

in stock returns for the first time. Rozeff andKinney (1976) documented the

January effect in New York Exchange stocks for the period 1904to 1974. They

found that average return for the month of January was higher than other month

simplying pattern in stock returns. Keim (1983) along with seasonality also

studied size effects in stock returns. He found that returns of small firms were

significantly higher than large firms in January month and attributed this finding to

tax-loss-selling and information hypothesis.

A similar conclusion was found by Reinganum (1983), however, he was of the

view that the entireseasonality in stock returns cannot be explained by tax-loss-

selling hypothesis. Gultekin andGultekin (1983) examined the presence of stock

market seasonality in sixteen industrial countries. Their evidence shows strong

seasonality’s in the stock market due to January returns, which is exceptionally

large in fifteen of sixteen countries. Brown et al. (1985) studied the Australian

stock market seasonality and found the evidence of December-January and July-

August seasonal effects, with the latter due to a June-July tax year. However, Raj

and Thurston(1994) found that the January and April effects are not statistically

significant in the NZ stock market. Mill and Coutts (1995) studied calendar effect

in FTSE 100, Mid 250 and 350 indices for the period 1986 and 1992. They found

calendar effect in FTSE 100. Ramcharan (1997),however, didn’t find seasonal

effect in stock returns of Jamaica. Choudhary (2001) reported January effect on

the UK and US returns but not in German returns. Fountas and

Segredakis(2002) studied 18 markets and reported seasonal patterns in returns.

The reasons for the January effect in stock returns in most of the developed

countries such as US, and UK attributed to the tax loss selling hypothesis,

19

settlement procedures, insider trading information. Another effect is window

dressing which is related to institutional trading. To avoid reporting to many

losers in their portfolios at the end of year, institutional investors tend to sell

losers in Decembers. They buy these stocks after the reporting date in January

to hold their desired portfolio structure again. Researchers have also reported

half- month effect in literature. Various studies have reported that daily stock

returns in first half of month are relatively higher than last half of the month.

Ariel(1987) conducted a study using US market indices from 1963 to 1981 to

show this effect. Aggarwal and Tandon (1994) found in their study such effect in

other international markets. Ziemba (1991) found that returns were consistently

higher on first and last four days of the month.

The holiday effect refers to higher returns around holidays, mainly in the pre-

holiday period as compared to returns of the normal trading days. Lakonishok

and Smidt (1988) studied DowJones Industrial Average and reported that half of

the positive returns occur during the 10 preholiday trading days in each year.

Ariel (1990) showed using US stock market that more than Exponential GARCH

(EGARCH) model was first developed by Nelson in 1991. The main purpose of

EGARCH model is to explain the asymmetrical response of the market under the

positive and negative shocks.

There are also evidences of day of the week effect in stock market returns. The

Monday effect was identified as early as the 1920s. Kelly (1930) based on three

years data of the US market found Monday to be the worse day to buy stocks.

Hirsch (1968) reported negative returns in his study. Cross (1973) found the

mean returns of the S&P 500 for the period 1953 and 1970 on Friday was higher

than mean return on Monday. Gibbons and Hess (1981) also studied the day of

the week effect in US stock returns of S&P 500 and CRSP indices using a

sample from 1962to 1978. Gibbons and Hess reported negative returns on

Monday and higher returns on Friday.

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Smirlock and Starks (1986) reported similar results. Jaffe and Westerfield (1989)

studied day of the week effect on four international stock markets viz. U.K.,

Japan, Canada and Australia. They found that lowest returns occurred on

Monday in the UK and Canada. However, in Japanese and Australian market,

they found lowest return occurred on Tuesday. Brooks and Persand (2001)

studied the five southeast Asian stock markets namely Taiwan, South Korea, The

Philippines ,Malaysia and Thailand. The sample period was from 1989 to 1996.

They found that neither South Korea nor the Philippines has significant calendar

effects. However, Malaysia and Thailand showed significant positive return on

Monday and significant negative return on Tuesday. Ajayi& al. (2004) examined

eleven major stock market indices on Eastern Europe using data from 1990 to

2002. They found negative return on Monday in six stock markets and positive

return on Monday in rest of them. Pandey (2002) reported the existence of

seasonal effect in monthly stock returns of BSE Sensex in India and confirmed

the January effect. Bodla and Jindal (2006) studied Indian and US market and

found evidence of seasonality. Kumari and Mahendra (2006) studied the day of

the week effect using data from 1979 to 1998 on BSE and

NSE. They reported negative returns on Tuesday in the Indian stock market.

Moreover, they found returns on Monday were higher compared to the returns of

other days in BSE and NSE.Choudhary and Choudhary (2008) studied 20 stock

markets of the world using parametric as well as non-parametric tests. He

reported that out of twenty, eighteen markets showed significant positive return

on various day other than Monday. The scope of the study is restricted to days

of- the week effect, weekend effect and monthly effect in stock returns of S&P

CNX Nifty and select firms. The half month effect and holiday effect are not

studied here.

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3.2 Background of the study

The study of volatility is always a serious concern for analysts and researchers

because high degree of volatility can affect the smooth functioning of any stock

market. It may also affect the economic growth and development of the economy

through its effect on investor's confidence and risk taking ability. The researchers

worldwide have attempted to identify the major factors affecting the level of

volatility in the stock markets.

Types of volatility

We can review volatility in three contexts:

Historical volatility

Implied volatility

Projected volatility

Historical volatility

It refers to the movements, which have been observed in a particular stock

price or index over a given period of time. The volatility can be measured by

using the past data on prices (or indices) and expressed by manner of the Beta,

and Coefficient Correlation. For this purpose, daily, monthly data may be taken.

Thus, we may determine volatility for any set of data and compare the

historical data with the prevailing conditions.

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Implied volatility

Implied volatility is a key variable required for determining premium on

option. While the entire input variable for a model like that of Black and Scholes

can be easily observed, the standard deviation of the instantaneous rate of return

on the stock can’t be observed. We may estimate its values from historical data,

but there is a second way in which its value can be inferred.

Projected volatility

This refer to the estimate of future volatility on the basis of past volatility,

current market analysis and perception of the investor. All trading in options is in

a large measure, on the basis of projected volatility.

Statistical Tools used for calculation of volatility

Beta

Beta measures the non diversifiable risk. Beta shows how the price of a

security responds to market forces. In effect, the more responsive the price of a

security is to changes in the market, the higher will be its Beta. Beta is calculated

by relating the returns on a security with the return for the market. It can be

positive or negative.

Beta for each stock calculated using daily opening and closing share price

each company and corresponding daily Bombay Stock Exchange Sensex. First,

rate of returns of companies and Bombay Stock Exchange Sensex are

calculated. The calculation as follows:

Rate of Return = share price in the closing – share price at the

opening

Share price in the opening

23

Computation of Beta:

β = N∑ XY−(∑ X ) (∑Y )

N ∑ X 2−(∑ X )2

Standard Deviation

This is the most commonly used measure of risk in fiancé. Its

square also is widely used to find out the risk associated with a security.

Computation of Variance = ∑i=1

n

(Ri−R )2

n−1

Standard Deviation = √σ2

Coefficient of Correlation

Coefficient of Correlation is a statistical technique, which measures the

degree or extent to which two or more variables fluctuate with reference to one

another. Correlation analysis helps in determining the degree of relationship

between two variables but correlation does not always imply cause and effect

relationship

The Coefficient of Correlation is essentially the covariance taken not as an

absolute value but relative to the standard deviations of the individual securities.

24

It indicates, in effect, how much x and y vary together as a proportion of their

combined individual variations, measured by SD of x multiplied by SD of Y

Coefficient of Correlation =

Ν∑ ΧΥ−∑ ( Χ )∑ (Υ )

[ {(Ν∑Υ 2)−(∑Υ )2} {Ν∑ Χ 2−(∑ Χ )2}]1/2

3.3 Problem Statement

The Indians securities market has always witnessed fluctuations, The

study attempts identify the volatility of securities listed in Bombay Stock

Exchange with special reference to 15 Sensex stocks from 30 scrips.

Moreover this study helps the potential investors make better investment

decision based on calculated beta of 15 shares from 30 listed in Bombay Stock

Exchange (BSE) Sensex

Need and importance of study

The stock market in India existed for a well over a century. Now its

importance in the mobilization, allocation and efficient use of scarce investment

recourses has not been recognized until the last decade. During the last decade

both secondary and primary markets have witnessed phenomenal qualitative and

quantitative developments. One of the important characteristics of well

functioning stock market is the stability of prices of securities traded on it, which

is price volatility.

Volatility of security price has important implications for firm’s investment

and financial decisions, valuations and investors sentiments. Price volatility of

securities has consequence for firm’s decisions on how much capital to issue,

type of instrument to be used when to use. Further high price volatility provides

opportunities for expropriations between various market players.

25

There for the study of volatility of security is very important contextual as

well. Hence analytical study of volatility of securities traded on Bombay Stock

Exchange is the topic of this project.

.

3.4 Objective of the Study

To study the volatility of securities listed in the Bombay Stock Exchange (BSE).

To analyze the present trend (Buying/Selling) of the company

To suggest better investment decision based on calculated statistical tools of fifteen companies.

To capture the trends, similarities and patterns in the activities and movements of the Indian Stock Market.

To suggest investors category like (hedgers and speculators) on the behalf of beta.

26

CHAPTER 4: Research Methodology

4.1 Research Design

Methodology

It covers the type of research used in this dissertation, sample size

chosen, sample description, data collection. Each will be described

separately under the following headings.

4.2 Sample size

For the study 15 companies have been selected. All these companies are

the major players in the economy and are part of Sensex. Only three

months duration has been taken from October to December (2011)  

4.3 Sample technique

The current study requires no sampling techniques. All the fifteen

companies in the Bombay Stock Exchange Sensex which appear from

October to December (2011) which consisting of 60 days observations are

selected

27

4.4 Sample description

Table 1. LIST OF 30 COMPANIES IN SENSEX

CODE NAME SECTOR

500103 Bharat Heavy Electricals Ltd. Capital Goods

500510 Larsen & Toubro Limited Capital Goods

500010 HDFC Finance

500180 HDFC Bank Ltd. Finance

532174 ICICI Bank Ltd. Finance

500112 State Bank of India Finance

500696 Hindustan Unilever Ltd. FMCG

500875 ITC Ltd. FMCG

500087 Cipla Ltd. Healthcare

532868 DLF Ltd. Housing Related

532532 Jaiprakash Associates Ltd. Housing Related

500209 Infosys Technologies Ltd. Information Technology

532540 Tata Consultancy Services Limited Information Technology

507685 Wipro Ltd. Information Technology

500440 Hindalco Industries Ltd. Metal, Metal Products & Mining

532286 Jindal Steel & Power Ltd. Metal, Metal Products & Mining

500900 Sterlite Industries (India) Ltd. Metal, Metal Products & Mining

500470 Tata Steel Ltd. Metal, Metal Products & Mining

500312 ONGC Ltd. Oil & Gas

500325 Reliance Industries Ltd. Oil & Gas

532555 NTPC Ltd. Power

500390 Reliance Infrastructure Ltd. Power

500400 Tata Power Company Ltd. Power

532454 Bharti Airtel Ltd. Telecom

532712 Reliance Communications Limited Telecom

532977 Bajaj Auto Limited Transport Equipments

500182 Hero Honda Motors Ltd. Transport Equipments

500520 Mahindra & Mahindra Ltd. Transport Equipments

532500 Maruti Suzuki India Ltd. Transport Equipments

500570 Tata Motors Ltd. Transport Equipments

28

Actual collection of data

Basically, the data used in this study are secondary Past three months

daily closing price of stock of all companies listed in BSE has been used

in this study. 60 daily stock prices have been used for each company to

test the applicability of Beta, SD, Variance and Coefficient Correlation,

which are used to measure volatility of shares.

Techniques used for data analysis

Basically whole data analysis has been performed using spreadsheet

in Excel by using different statistical functions inbuilt in Excel. The

following statistical functions have been employed during the data

analysis.

Correlation: Calculates the coefficient of correlation between

Market Return and companies’ return and

companies’return.

Sigma: Calculates the summation of data.

Standard Deviation: Calculates the standard deviation that Measures the risk of an asset from the Expected value of return.

Beta : The whole market is assigned a beta of 1. Stocks that have a beta greater than 1 have

greater price volatility than the overall market And are considered to have greater risk.

Stocks with a beta less than 1 have less price Volatility than the market as a whole and are

Considered to have less risk.

CHAPTER 5

29

PROFILE OF THE INDUSTRY AND COMPANY

5.1INDUSTRY PROFILE

The BSE Sensex or Bombay Stock Exchange Sensitive Index is a value-

weighted index composed of 30 stocks with the base April 1979. It consists of the

30 largest and most actively traded stocks, representative of various sectors, on

the Bombay Stock Exchange. These companies account for around one-fifth of

the market capitalization of the BSE.

The base value of the Sensex is 100 on April 1, 1979 and the base year of BSE-

SENSEX is 1978-79. At irregular intervals, the Bombay Stock Exchange

authorities review and modify its composition to make sure it reflects current

market conditions.

The abbreviated form "Sensex" was coined by Deepak Mohoni around 1990

while writing market analysis columns for some of the business newspapers and

magazines. It gained popularity over the next year or two.

The software industry comprises of businesses involved in the development,

maintenance and publication of computer software. The software industry started

in the mid-1970s at the time of the personal computer revolution. The industry

also includes software services, such as training and consultancy. The largest

and most profitable of software companies are located in the United States. As of

2006, the software industry is dominated by Microsoft. Software Magazine's 500

list in 2005 shows the total amount of revenue brought in by software companies

per locale, with the highest being California due to Silicon Valley and the amount

of Fortune 500 software companies residing in that area.

There are mainly two types of businesses in the software industry; those

developing proprietary software such as Microsoft, and those developing open

source software. Developing proprietary software is costly and involves software

licensing and the need to protect the software from cracking and piracy.

30

A pharmaceutical company, or drug company, is a commercial business licensed

to research, develop, market and/or distribute drugs, most commonly in the

context of healthcare. They can deal in generic and/or brand medications. They

are subject to a variety of laws and regulations regarding the patenting, Testing

and marketing of drugs, particularly prescription drugs. From its beginnings at the

start of the 19th Century, the pharmaceutical industry is now one of the most

successful and influential, attracting both praise and controversy

The oil industry operates on the petroleum market. Petroleum is vital to nearly all

other industries, if not industrialized civilization itself, and thus is critical concern

to many nations. Oil accounts for a large percentage of the world’s energy

consumption, ranging from a low of 32% for Europe and Asia, up to a high of

53% for the Middle East. Other geographic regions’ consumption patterns are as

follows: South and Central America (44%), Africa (41%), and North America

(40%). The world at large consumes 30 billion barrels (4.8 km) of oil per year,

and the top oil consumers largely consist of developed nations. In fact, 24% of

the oil consumed in 2004 went to the United States alone.

A public utility is a company that maintains the infrastructure for a public service

(often also providing a service using that infrastructure). Public utilities often

involve natural monopolies, and as a result are often government monopolies, or

if privately owned, treated as specially regulated sectors.

The manufacturing industry includes those economic sectors that create a

finished, usable product: manufacturing and construction. This sector of industry

generally takes the output of the primary sector and manufactures finished goods

or products to a point where they are suitable for use by other businesses, for

export, or sale to domestic consumers. This sector is often divided into light

industry and heavy industry. Many of these industries consume large quantities

of energy and require factories and machinery to convert the raw materials into

goods and products. They also produce waste materials and waste heat that may

pose environmental problems or cause pollution.

31

5.2 COMPANY PROFILES

The Associated Cement Companies Limited, an Indian company in

cement manufacturing business. Its registered office is called Cement House. It

is located on Maharishi Karve Road, Mumbai. It is a blue chip company. The

stock price of this company contributes in calculating BSE Sensex

The management control of the company was taken over by Swiss

cement major Holcim in 2004. On 1st September 2006 the name of The

Associated Cement Companies Limited was changed to ACC Limited. The

company is the only cement company to get the Super brand status in India

Bharti Airtel, formerly known as Bharti Tele-Ventures Limited (BTVL) is

among India's largest mobile phone and Fixed Network operators. With more

than 28.6 million subscriptions as of September 2006, the company is one of the

world's fastest growing telecom companies. It offers its mobile services under the

Airtel brand and is headed by Sunil Mittal, India's sixth richest men with a total

worth of US$6.9 billion. The company is the only operator to provide mobile

services in all the 23 circles in India. The company also provides telephone

services and Internet access over DSL in 14 circles. The company complements

its mobile, broadband & telephone services with national and international long

distance services.

BHEL or Bharat Heavy Electricals Limited is a Gas and Steam turbine

manufacturer in India. It is one of the nine large Public Sector Undertakings

known as navratnas or 'nine jewels'. Some of its manufacturing units are located

in Bhopal (Madhya Pradesh), Haridwar (UttarKhand), Hyderabad (Andhra

Pradesh), Trichi andRanipet (Tamil Nadu) and Bangalore (Karnataka). BHEL is a

key player in power sector through erection, commissioning and servicing of

power plants all over the world

32

Grasim industries limited, a flagship company of the Aditya Birla Group,

ranks among India's largest private sector companies, with consolidated net

revenues of Rs 102 billion (FY2006). Starting as a textiles manufacturer in 1948,

today Grasim's businesses comprise Viscose Staple Fibre (VSF), Cement,

Sponge Iron, Chemicals and Textiles — in all of which the company holds a

dominant position.

In July 2004, Grasim acquired a majority stake and management control in

UltraTech Cement Limited, the de-merged cement business of Larsen & Toubro

Limited (L&T). One of the largest of its kind, in the cement sector, this acquisition

catapulted the Aditya Birla Group at the top of the league in India. The Group's

combined capacity stands raised to 31 million tpa, of which 17.0 million tpa

capacity comes from UltraTech and 1.1 million tpa from Shree Digvijay Cement

Co. Ltd, another subsidiary of Grasim.

Ambuja Cements was set up in 1986. In the last decade the company

has grown tenfold. The total cement capacity of the company is 16 million

tonnes. Its plants are some of the most efficient in the world. With environment

protection measures that are on par with the finest in the developed world. The

company's most distinctive attribute, however, is its approach to the business.

Ambuja follows a unique homegrown philosophy of giving people the authority to

set their own targets, and the freedom to achieve their goals. This simple vision

has created an environment where there are no limits to excellence, no limits to

efficiency. And has proved to be a powerful engine of growth for the company. As

a result, Ambuja is the most profitable cement company in India, and the lowest

cost producer of cement in the world

HDFC or Housing Development Finance Corporation Limited, was

incorporated in 1977 with the primary objective of meeting a social need – that of

promoting home ownership by providing long-term finance to households for their

housing needs. HDFC was promoted with an initial share capital of Rs. 100

million.

33

Hindalco industries, Hindalco Industries Limited, a flagship company of

the Aditya Birla Group, is structured into two strategic businesses — Aluminium

and Copper — and is an industry leader in both. A non-ferrous metals

powerhouse with a turnover of Rs.11,396 crore (FY06), Hindalco's integrated

operations and operating efficiency have positioned the company as Asia's

largest integrated primary producer of aluminium and among the most cost

efficient producers globally. Its copper smelter is today the world's largest custom

smelter at a single location.

Established in 1958, Hindalco commissioned its aluminium facility at

Renukoot in eastern U.P. in 1962 and has today grown to become the country's

largest integrated aluminium producer and ranks among the top quartile of low

cost producers in the world.

With a strategic intent to achieve vertical integration in the copper

business, Hindalco acquired two captive copper mines in Australia — Nifty and

Mt. Gordon through Aditya Birla Minerals Limited

Hindustan Unilever Limited, erstwhile Hindustan Lever Limited (also called

HLL), headquartered in Mumbai, is India's largest consumer products company,

formed in 1933 as Lever Brothers India Limited. Its 41,000 employees are

headed by Mr.Harish

Manwani, the non-executive chairman of the board. HLL is the market

leader in Indian products such as tea, soaps, detergents, as its products have

become daily household name in India. The Anglo-Dutch company Unilever

owns a majority stake in Hindustan Lever Limited.

Recently in February 2007, the company has been renamed to "Hindustan

Unilever Limited" to provide the optimum balance between maintaining the

heritage of the Company and the future benefits and synergies of global

alignment with the corporate name of "Unilever". This decision will be put to the

Shareholdrs for approval in next "Annual General Meeting

34

Larsen & Toubro Limited is India's largest engineering and construction

conglomerate, with diverse interests such as Construction,hydraulic equipments,

power services electrical and electronics, fertilizer projects,medical electronics

and information technology. It generates almost 85% of its revenue from the

construction business. Founded in 1938, the company is currently headquartered

in Mumbai, India. A strong, customer-focussed approach and the constant quest

for top-class quality have enabled the Company to attain and sustain leadership

position for over six decades

L&T has made spectacular achievements in Indian industry. Many of the

engineering projects executed by L&T have set new benchmarks in terms of

scale, sophistication and speed. So do many buildings, highways, bridges and

civil structures around the country which are widely regarded as landmarks

Maruti Udyog Ltd is one of India's leading automobile manufacturers and

the market leader in the car segment, both in terms of volume of vehicles sold

and revenue earned. Untill recently, 18.28% of the company was owned by the

government, and 54.2% by Suzuki of Japan. The Indian government held an

Initial Public Offering of 25% of the company in June of 2003. As of May 10,

2007, govt. of India sold its complete share to other financial institutions. With

this, govt. of India no longer has any stake in Maruti Udyog.

Maruti Udyog Limited (MUL) was established in February 1981, though

the actual production commenced in 1983. Through 2004, Maruti has produced

over 5 Million vehicles. Marutis are sold in India and various several other

countries, depending upon export orders. Cars similar to Marutis (but not

manufactured by Maruti Udyog) are sold by Suzuki in Pakistan and other South

Asian countries.

The company annually exports more than 30,000 cars and has an extremely

large domestic market in India selling over five hundred thousand cars annually.

Maruti 800, till 2004, was the India's largest selling compact car ever since it was

launched in 1983.

35

More than a million units of this car have been sold worldwide so far.

Currently, Maruti Alto tops the sales charts.

National Thermal Power Corporation is the largest power generation

company in India. The Forbes Global 2000 ranking for 2005 ranks it as the 5th

leading company in India and the 486th leading company in the world. It is a

public listed (Bombay Stock Exchange) Indian public sector company, with

majority shares owned by the Government of India. At present, Government of

India holds 89.5% of the total equity shares of the company and the balance

10.5% is held by FIIs, Domestic Banks, Public and others. NTPC ranks amongst

the top five companies, in terms of market capitalisation

NTPC's core business is engineering, construction and operation of power

generating plants and also providing consultancy to power utilities in India and

abroad. As on date the installed capacity of NTPC is 26, 404 MW through its 14

coal based, 7 gas based and 4 Joint Venture Projects.

NTPC’s share on 31 Mar 2006 in the total installed capacity of the country

was 19.51% and it contributed 27.68% of the total power generation of the

country during 2005-06. Thus, every fourth home in India is enlightened by

NTPC. A total of 170.88 BUs of electricity was produced across all the stations of

the company in the financial year 2005-2006. The Net Profit after Tax on March

31, 2006 was INR 58, 202 million. Net Profit after Tax for the quarter ended June

30, 2006 was INR 15528 million, which is 18.65% more than the same quarter in

the previous financial year (2004-2005) where the profit was INR 13087 million

Oil and Natural Gas Corporation Limited (ONGC) (incorporated on

June 23, 1993) is a public sector petroleum company based in Dehradun, India.

It is a Fortune Global 500 company, and contributes 77% of India's crude oil

production and 81 % of India's natural gas production. It is the highest profit

making corporation in India. It was set up as a commission on August 14, 1956.

Indian government holds 74.14% equity stake in this company.

ONGC is engaged in exploration and production activities. It is involved in

exploring and exploiting hydrocarbons in 26 sedimentary basins of India. It

36

produces about 30% of India's crude oil. It owns and operates more than 11,000

kilometers of pipelines in India. Until recently it was the largest company in terms

of market cap in india.

Ranbaxy Laboratories Limited is an Indian company incorporated in

1961. It is India's largest pharmaceutical company. It exports its products to 125

countries with ground operations in 46 and manufacturing facilities in seven

countries. It is ranked among the top 10 generic companies worldwide. The CEO

of the company is Malvinder Mohan Singh.Ranbaxy went public in 1973

Reliance Industries is India's largest private sector company with a

turnover of US $19.976 billion and profit of US $2.033 billion for the fiscal year

ending in March 2006 making it India's first and only private sector Fortune 500

company. It was founded by the late Dhirubhai Ambani in the 1970s. After severe

differences between the two sons of the founder Dhirubhai Ambani, the group

was divided between the two sons Mukesh and Anil Ambani in 2006

State Bank of India (SBI) is the largest bank in India. If one measures by

the number of branch offices and employees, SBI is the largest bank in the world.

Established in 1806 as Bank of Bengal, it is the oldest commercial bank in the

Indian Subcontinent. SBI provides various domestic, international and NRI

products and services, through its vast network in India and overseas. With an

asset base of $126 billion and its reach, it is a regional banking behemoth. The

government nationalized the bank in 1955, with the Reserve Bank of India taking

a 60% ownership stake. In recent years the bank has focused on two priorities,

reducing its huge staff through Golden handshake schemes known as the

Voluntary Retirement Scheme, which saw many of its best and brightest defect to

the private sector, and, computerizing its operations

The State Bank of India traces its roots to the first decade of 19th century,

when the Bank of Calcutta, later renamed the Bank of Bengal, was established

on 2 June 1806. The government amalgamatted Bank of Bengal and two other

Presidency banks, namely, the Bank of Bombay (incorporated on 15 April 1840)

37

and the Bank of Madras on 27 January 1921, and named the the reorganized

banking entity the Imperial Bank of India

The State Bank of India Act 1955, enacted by the Parliament of India,

authorized the Reserve Bank of India, which is the central banking organization

of India, to acquire a controlling interest in the Imperial Bank of India, which was

renamed the State Bank of India on 30 April 1955

Tata Consultancy Services Limited (TCS Limited) is an Indian

information technology, consulting, services and business-process outsourcing

organization which commenced operations in 1968. As of 2007, it is Asia's

largest IT services firm with annualised revenues of over US $4 billion and has

the largest number of employees among all the Indian IT companies with

strength of over 95,000.For fiscal year 2005-06, it posted a net profit of Rs. 3,709

crore

TCS is part of one of Asia's largest conglomerates and most respected

groups, the Tata Group, which has interests in areas such as energy,

telecommunications, financial services, chemicals, engineering and materials

CHAPTER -6

38

DATA ANALYSIS AND INTERPRETATION

Table No. 1. 1

Volatility of BHEL (Capital Goods) return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 321.2516151.4

50.9805

-0.64710.4188

0.9615 -0.6345

04-Oct-11 322.715864.8

60.5578

-1.36721.8693

0.3111 -0.7626

05-Oct-11 315.115792.4

1-2.8245

-1.11011.2323

7.9778 3.1355

07-Oct-11 323.916232.5

40.3705

0.06190.0038

0.1373 0.0229

10-Oct-11 331.7516557.2

31.7332

1.73433.0080

3.0041 3.0060

11-Oct-11 326.516536.4

7-2.9096

-0.79630.6341

8.4661 2.3170

12-Oct-11 336.7516958.3

92.8656

1.75703.0871

8.2118 5.0349

13-Oct-11 333.8516883.9

2-1.5426

-0.97180.9444

2.3796 1.4991

14-Oct-11 333.3517082.6

9-0.1950

1.43922.0714

0.0380 -0.2806

17-Oct-11 326.317025.0

9-3.8308

-0.88670.7862

14.6753 3.3968

18-Oct-11 321.7516748.2

9-0.8547

-0.41250.1702

0.7305 0.3526

19-Oct-11 324.317085.3

4-0.4934

1.18221.3976

0.2434 -0.5833

20-Oct-11 317.916936.8

9-1.2583

0.14780.0219

1.5832 -0.1860

21-Oct-11 319.7516785.6

40.5473

-1.13281.2833

0.2995 -0.6200

24-Oct-11 318.3516939.2

8-2.0575

-0.42370.1796

4.2332 0.8719

25-Oct-11 314.9517254.8

6-1.6034

1.40291.9682

2.5710 -2.2495

26-Oct-11 316.617288.8

3-0.9002

-0.27480.0755

0.8103 0.2474

28-Oct-11 327.2 17804.8 1.8185 0.7467 0.5575 3.3068 1.3578

31-Oct-11 317.8517705.0

1-3.5079

-0.57160.3267

12.3057 2.0051

01-Nov-11 319.55 17480.8 0.7980 -0.3416 0.1167 0.6368 -0.2726

39

3

02-Nov-11 316.0517464.8

5-0.3006

0.67080.4499

0.0904 -0.2016

03-Nov-11 329.2517481.9

33.7206

0.29310.0859

13.8427 1.0905

04-Nov-11 333.6517562.6

10.1948

-0.63820.4073

0.0380 -0.1243

08-Nov-11 334.8517569.5

3-0.4629

-0.13740.0189

0.2143 0.0636

09-Nov-11 328.9 17362.1 -2.4628 -1.6120 2.5986 6.0652 3.9700

11-Nov-11 324.117192.8

2-1.1725

0.02870.0008

1.3747 -0.0336

14-Nov-11 317.417118.7

4-3.1821

-1.34231.8017

10.1258 4.2712

15-Nov-11 310.5516882.6

7-3.2684

-1.17841.3887

10.6824 3.8516

16-Nov-11 297.6516775.8

7-3.6452

-0.57480.3304

13.2876 2.095317-Nov-11

284.6516461.7

1-4.2333

-1.77973.1674

17.9206 7.534018-Nov-11

275.9516371.5

1-3.6420

-0.09890.0098

13.2639 0.360221-Nov-11 262.05 15946.1 -5.3043 -2.2007 4.8432 28.1359 11.673422-Nov-11

265.216065.4

2-0.5656

0.43400.1884

0.3199 -0.245523-Nov-11

255.715699.9

7-2.9918

-1.71742.9494

8.9508 5.138124-Nov-11

260.8515858.4

91.6676

0.89970.8095

2.7810 1.500425-Nov-11

269.8515695.4

32.9090

-0.54680.2990

8.4624 -1.590628-Nov-11

280.7516167.1

31.3357

1.70922.9214

1.7841 2.283029-Nov-11

282.4516008.3

40.1593

-1.26201.5927

0.0254 -0.201130-Nov-11

282.216123.4

60.2481

1.57842.4915

0.0615 0.391501-Dec

275.2516483.4

5-5.3588

-0.43970.1933

28.7164 2.356302-Dec

282.4516846.8

32.6376

2.09454.3868

6.9571 5.524405-Dec

28816805.3

31.9097

-0.04150.0017

3.6470 -0.079207-Dec

288.816877.0

6-0.4848

0.27860.0776

0.2350 -0.135108-Dec

273.5516488.2

4-5.4652

-2.01054.0422

29.8682 10.987909-Dec

264.116213.4

6-1.8554

-0.27740.0770

3.4424 0.514712-Dec

257.5515870.3

5-4.4457

-3.05369.3242

19.7646 13.575313-Dec

261.416002.5

12.4484

1.39911.9575

5.9944 3.425514-Dec

256.515881.1

4-0.6628

-0.52020.2706

0.4393 0.344815-Dec

250.1515836.4

7-1.0594

0.61520.3784

1.1223 -0.651716-Dec 240.45 15491.3 -5.2194 -2.4364 5.9360 27.2419 12.7165

40

519-Dec

228.7515175.0

8-5.5519

-0.39510.1561

30.8237 2.193420-Dec

234.0515685.2

1-0.2777

-1.72022.9590

0.0771 0.477721-Dec

237.6515813.3

6-0.1473

1.25891.5848

0.0217 -0.185422-Dec 241.95 15738.7 3.9884 1.6865 2.8444 15.9076 6.726723-Dec

243.615970.7

52.0936

-0.79250.6281

4.3831 -1.659226-Dec

240.815873.9

5-1.2458

1.18081.3942

1.5521 -1.471127-Dec

246.2515727.8

50.5076

-0.69310.4805

0.2577 -0.351928-Dec

237.415543.9

3-0.5055

-0.80440.6470

0.2555 0.406629-Dec

23915454.9

2-1.8619

-0.73990.5475

3.4668 1.377630-Dec-11

275.2516483.4

512.8065

-0.83230.6927

164.0075 -10.6588

                   SUM -

41.0524-

14.182285.0865 558.4909 104.9189

             BETA S.D VARIA

NCECORREL

ATION    1.164 2.800007706 7.8400 0.4573    

Interpretation of BHEL

Beta of BHEL company is 1.164 which means the BHEL company share price

fluctuate more than BSE Sensex because if BHEL beta is greater than 1 than it

represent the BHEL share price is more fluctuate compare to market return, if

BHEL beta is less than its represent that BHEL share price less fluctuate

compare to market return, if BHEL beta is equal to 1 than its shows that both

are fluctuate in same sense.

The value of correlation could be positive, negative or zero. It always varies

between the -1.0 (negative correlation) and +1.0 (positively correlation).so this is

Positive correlation so that It means that when market return increases, the

company’s return also increases.

41

Table No. 1. 2

Volatility of ACC LTD. | (Housing related)

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return      

Date close close Y (m) X X^2 Y^2 X*Y

3-Oct-11 1100.25 16151.45 0.9316 -0.6471 0.4187 0.8678 -0.6028

4-Oct-11 1100.25 15864.86 0.1136 -1.3672 1.8693 0.0129 -0.1553

5-Oct-11 1106.75 15792.41 0.5647 -1.1101 1.2323 0.3189 -0.6269

7-Oct-11 1111.75 16232.54 -0.2249 0.0619 0.0038 0.0506 -0.0139

10-Oct-11 1131.85 16557.23 1.5771 1.7343 3.0080 2.4871 2.7352

11-Oct-11 1133.25 16536.47 0.1103 -0.7963 0.6341 0.0122 -0.0878

12-Oct-11 1140.00 16958.39 0.7895 1.7570 3.0871 0.6233 1.3871

13-Oct-11 1121.10 16883.92 -2.1185 -0.9718 0.9444 4.4879 2.0587

14-Oct-11 1119.05 17082.69 0.3664 1.4392 2.0714 0.1342 0.5273

17-Oct-11 1109.55 17025.09 -0.2433 -0.8867 0.7862 0.0592 0.2158

18-Oct-11 1105.10 16748.29 0.4615 -0.4125 0.1702 0.2130 -0.1904

19-Oct-11 1126.40 17085.34 1.4560 1.1822 1.3976 2.1198 1.7212

20-Oct-11 1114.55 16936.89 -0.7492 0.1478 0.0219 0.5613 -0.1108

21-Oct-11 1117.80 16785.64 -0.5278 -1.1328 1.2833 0.2786 0.5979

24-Oct-11 1134.35 16939.28 0.4099 -0.4237 0.1796 0.1680 -0.1737

25-Oct-11 1181.15 17254.86 4.5845 1.4029 1.9682 21.0178 6.4317

26-Oct-11 1190.70 17288.83 1.2220 -0.2748 0.0755 1.4932 -0.3358

28-Oct-11 1221.20 17804.80 1.7155 0.7467 0.5575 2.9430 1.2809

42

31-Oct-11 1195.25 17705.01 -1.2466 -0.5716 0.3267 1.5540 0.7125

1-Nov-11 1183.95 17480.83 -1.3556 -0.3416 0.1167 1.8377 0.4631

2-Nov-11 1185.65 17464.85 0.4765 0.6708 0.4499 0.2271 0.3196

3-Nov-11 1210.25 17481.93 2.0863 0.2931 0.0859 4.3528 0.6115

4-Nov-11 1223.40 17562.61 0.6825 -0.6382 0.4073 0.4658 -0.4356

8-Nov-11 1218.45 17569.53 0.5171 -0.1374 0.0189 0.2673 -0.0710

9-Nov-11 1203.05 17362.10 -1.7414 -1.6120 2.5986 3.0325 2.8072

11-Nov-11 1218.45 17192.82 1.5388 0.0287 0.0008 2.3680 0.0441

14-Nov-11 1213.80 17118.74 -1.2317 -1.3423 1.8017 1.5170 1.6532

15-Nov-11 1205.80 16882.67 0.2986 -1.1784 1.3887 0.0891 -0.3518

16-Nov-11 1194.45 16775.87 -0.7744 -0.5748 0.3304 0.5997 0.445117-Nov-11 1156.60 16461.71 -2.0448 -1.7797 3.1674 4.1812 3.639118-Nov-11 1152.20 16371.51 0.1996 -0.0989 0.0098 0.0398 -0.019721-Nov-11 1133.10 15946.10 0.0838 -2.2007 4.8432 0.0070 -0.184522-Nov-11 1142.30 16065.42 0.2276 0.4340 0.1884 0.0518 0.098823-Nov-11 1131.80 15699.97 -0.2827 -1.7174 2.9494 0.0799 0.485624-Nov-11 1115.00 15858.49 -0.2735 0.8997 0.8095 0.0748 -0.246125-Nov-11 1119.40 15695.43 0.6745 -0.5468 0.2990 0.4549 -0.368828-Nov-11 1192.45 16167.13 5.0694 1.7092 2.9214 25.6988 8.664729-Nov-11 1159.95 16008.34 -2.8881 -1.2620 1.5927 8.3409 3.644830-Nov-11 1145.05 16123.46 0.0917 1.5784 2.4915 0.0084 0.14471-Dec-12 1170.75 16483.45 0.9268 -0.4397 0.1933 0.8589 -0.40752-Dec-12 1213.55 16846.83 3.5268 2.0945 4.3868 12.4386 7.38685-Dec-12 1205.75 16805.33 -0.0207 -0.0415 0.0017 0.0004 0.00097-Dec-12 1217.70 16877.06 1.7820 0.2786 0.0776 3.1757 0.49658-Dec-12 1201.65 16488.24 -1.2732 -2.0105 4.0422 1.6212 2.55999-Dec-12 1164.70 16213.46 -1.3179 -0.2774 0.0770 1.7370 0.3656

12-Dec-121122.70 15870.35

-4.2131-3.0536 9.3242 17.7499

12.8648

13-Dec-12 1136.45 16002.51 2.2262 1.3991 1.9575 4.9561 3.114714-Dec-12 1141.90 15881.14 0.5167 -0.5202 0.2706 0.2670 -0.268815-Dec-12 1141.20 15836.47 1.4196 0.6152 0.3784 2.0151 0.873316-Dec-12 1127.70 15491.35 -0.5720 -2.4364 5.9360 0.3271 1.393519-Dec-12 1129.85 15175.08 0.2478 -0.3951 0.1561 0.0614 -0.097920-Dec-12 1098.60 15685.21 -3.2041 -1.7202 2.9590 10.2661 5.511621-Dec-12 1138.80 15813.36 1.7475 1.2589 1.5848 3.0536 2.199922-Dec-12 1138.55 15738.70 0.4875 1.6865 2.8444 0.2376 0.822123-Dec-12 1139.55 15970.75 0.1229 -0.7925 0.6281 0.0151 -0.097426-Dec-12 1159.85 15873.95 1.9701 1.1808 1.3942 3.8812 2.326227-Dec-12 1173.95 15727.85 1.2735 -0.6931 0.4805 1.6217 -0.882728-Dec-12 1166.85 15543.93 -0.2914 -0.8044 0.6470 0.0849 0.2344

43

29-Dec-12 1150.25 15454.92 -0.8476 -0.7399 0.5475 0.7185 0.627230-Dec-11 1136.35 16483.45 -2.8556 -0.8323 0.6927 8.1546 2.3767

    SUM12.1981 -14.1822 85.0865 166.3395 78.114

8

               BETA S.D VARIANC

ECORRELATIO

N    0.9910 1.3239 1.7527 0.6999    

Interpretation of ACC LTD

Beta of ACC LTD. Company is 0.990992 which means the ACC LTD company

beta less than 1 means it tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of ACC Ltd. Is 1.323887846

So and variance is 1.7526 so this is Positive correlation so that It means that

when market return increases, the company’s return also increases.

Table No. 1. 3

Volatility of Bharti Airtel (Telecom) return

  STOCK

PRICE

SENSEX PRICE

Stock Return

Sensex Return

     Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 380.55 16151.45 1.5110 -0.6471 0.4188 2.2830 -0.9778

04-Oct-11 370 15864.86 -2.4324 -1.3672 1.8693 5.9167 3.3257

05-Oct-11 367.05 15792.41 -2.1387 -1.1101 1.2323 4.5739 2.3741

07-Oct-11 354.8 16232.54 -5.1437 0.0619 0.0038 26.4581 -0.3185

44

10-Oct-11 363.25 16557.23 3.0145 1.7343 3.0080 9.0869 5.2281

11-Oct-11 374.8 16536.47 2.2145 -0.7963 0.6341 4.9041 -1.7634

12-Oct-11 374.05 16958.39 -0.7619 1.7570 3.0871 0.5805 -1.3387

13-Oct-11 369.85 16883.92 -1.9197 -0.9718 0.9444 3.6852 1.8656

14-Oct-11 383.75 17082.69 3.8567 1.4392 2.0714 14.8740 5.5507

17-Oct-11 379.05 17025.09 -0.7123 -0.8867 0.7862 0.5074 0.6316

18-Oct-11 374.05 16748.29 -0.7352 -0.4125 0.1702 0.5405 0.3033

19-Oct-11 384.95 17085.34 2.8315 1.1822 1.3976 8.0176 3.3474

20-Oct-11 389.9 16936.89 2.3852 0.1478 0.0219 5.6893 0.3526

21-Oct-11 377.9 16785.64 -3.3342 -1.1328 1.2833 11.1170 3.7770

24-Oct-11 383.05 16939.28 -0.0653 -0.4237 0.1796 0.0043 0.0277

25-Oct-11 388.3 17254.86 1.1074 1.4029 1.9682 1.2263 1.5536

26-Oct-11 392.85 17288.83 1.1200 -0.2748 0.0755 1.2544 -0.3078

28-Oct-11 391.85 17804.8 -1.3781 0.7467 0.5575 1.8991 -1.0290

31-Oct-11 391.4 17705.01 -0.4216 -0.5716 0.3267 0.1777 0.2410

01-Nov-11 394.7 17480.83 1.2161 -0.3416 0.1167 1.4789 -0.4155

02-Nov-11 384.3 17464.85 -1.5222 0.6708 0.4499 2.3172 -1.0211

03-Nov-11 392.55 17481.93 2.1781 0.2931 0.0859 4.7440 0.6384

04-Nov-11 397.95 17562.61 2.2490 -0.6382 0.4073 5.0581 -1.4354

08-Nov-11 397.25 17569.53 0.0755 -0.1374 0.0189 0.0057 -0.0104

09-Nov-11 395.2 17362.1 -0.4428 -1.6120 2.5986 0.1961 0.7138

11-Nov-11 395.5 17192.82 1.1504 0.0287 0.0008 1.3235 0.0330

14-Nov-11 405.3 17118.74 1.8011 -1.3423 1.8017 3.2441 -2.4176

15-Nov-11 401.45 16882.67 -0.8718 -1.1784 1.3887 0.7601 1.0274

16-Nov-11 401.1 16775.87 -0.9723 -0.5748 0.3304 0.9454 0.5589

17-Nov-11 395.7 16461.71 -1.3394 -1.7797 3.1674 1.7940 2.3837

18-Nov-11 397.65 16371.51 1.4208 -0.0989 0.0098 2.0188 -0.1405

21-Nov-11 388.5 15946.1 1.1583 -2.2007 4.8432 1.3417 -2.5491

22-Nov-11 378.85 16065.42 -1.6233 0.4340 0.1884 2.6352 -0.7046

23-Nov-11 364.85 15699.97 -2.6449 -1.7174 2.9494 6.9956 4.5424

24-Nov-11 378.15 15858.49 3.4378 0.8997 0.8095 11.8184 3.0930

25-Nov-11 374.9 15695.43 -0.1600 -0.5468 0.2990 0.0256 0.0875

28-Nov-11 388.2 16167.13 2.7177 1.7092 2.9214 7.3857 4.6451

29-Nov-11 373.45 16008.34 -4.4450 -1.2620 1.5927 19.7584 5.6098

30-Nov-11 385.3 16123.46 2.6084 1.5784 2.4915 6.8035 4.1171

01-Dec-11 378.95 16483.45 -2.9028 -0.4397 0.1933 8.4260 1.2764

02-Dec-11 390.15 16846.83 2.4734 2.0945 4.3868 6.1177 5.1805

05-Dec-11 390.3 16805.33 -0.2818 -0.0415 0.0017 0.0794 0.0117

07-Dec-11 377.3 16877.06 -3.3660 0.2786 0.0776 11.3301 -0.9378

08-Dec-11 367.1 16488.24 -2.4244 -2.0105 4.0422 5.8778 4.8743

09-Dec-11 358.7 16213.46 -1.7563 -0.2774 0.0770 3.0847 0.4873

45

12-Dec-11 342.2 15870.35 -4.9094 -3.0536 9.3242 24.1023 14.9912

13-Dec-11 346.4 16002.51 1.7032 1.3991 1.9575 2.9010 2.3830

14-Dec-11 348.85 15881.14 0.5590 -0.5202 0.2706 0.3125 -0.2908

15-Dec-11 337 15836.47 -0.5935 0.6152 0.3784 0.3522 -0.3651

16-Dec-11 336.3 15491.35 -0.2825 -2.4364 5.9360 0.0798 0.6882

19-Dec-11 336.4 15175.08 0.7134 -0.3951 0.1561 0.5090 -0.2819

20-Dec-11 322.85 15685.21 -5.3121 -1.7202 2.9590 28.2180 9.1378

21-Dec-11 341.5 15813.36 2.7818 1.2589 1.5848 7.7387 3.5020

22-Dec-11 335.45 15738.7 -1.0583 1.6865 2.8444 1.1200 -1.7848

23-Dec-11 330.45 15970.75 -1.3920 -0.7925 0.6281 1.9378 1.1032

26-Dec-11 344.7 15873.95 3.1187 1.1808 1.3942 9.7260 3.6825

27-Dec-11 343.05 15727.85 -1.1514 -0.6931 0.4805 1.3258 0.7981

28-Dec-11 343.5 15543.93 -0.3785 -0.8044 0.6470 0.1432 0.3044

29-Dec-11 341.1 15454.92 -0.0586 -0.7399 0.5475 0.0034 0.0434

30-Dec-11 342.9 16483.45 0.5249 -0.8323 0.6927 0.2756 -0.4369

    SUM -9.0042-

14.1822 85.0865 297.1072 85.9658

               BETA S.D VARIA

NCECORREL

ATION    1.025732 1.982237773 3.9293 0.5392    

Interpretation of BHARTI AIRTEL

Beta of Bharti Airtel is 1.025732 which means the ACC LTD company beta

greater than 1 means it tends to be more volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of ACC Ltd. Is 1.982237773

So and correlation is 3.929266588 so this is Positive correlation so that It means

that when market return increases, the company’s return also increases.

46

Table No. 1. 4

Volatility of Grasim Industries ( Diversified) return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 2290.25 16151.45 -1.6483 -0.6471 0.4188 2.7169 1.0667

04-Oct-11 2292.2 15864.86 1.3175 -1.3672 1.8693 1.7358 -1.8014

05-Oct-11 2322.55 15792.41 0.9709 -1.1101 1.2323 0.9427 -1.0778

07-Oct-11 2336.45 16232.54 0.2054 0.0619 0.0038 0.0422 0.0127

10-Oct-11 2326.05 16557.23 1.0103 1.7343 3.0080 1.0207 1.7522

11-Oct-11 2330.95 16536.47 -0.1609 -0.7963 0.6341 0.0259 0.1281

12-Oct-11 2394.15 16958.39 2.6794 1.7570 3.0871 7.1794 4.7078

13-Oct-11 2326.05 16883.92 -2.9213 -0.9718 0.9444 8.5338 2.8389

14-Oct-11 2380.35 17082.69 2.3253 1.4392 2.0714 5.4070 3.3466

17-Oct-11 2334.15 17025.09 -1.5359 -0.8867 0.7862 2.3590 1.3619

18-Oct-11 2334.3 16748.29 0.0129 -0.4125 0.1702 0.0002 -0.0053

19-Oct-11 2353.35 17085.34 0.7372 1.1822 1.3976 0.5435 0.8716

20-Oct-11 2315.25 16936.89 -0.3347 0.1478 0.0219 0.1120 -0.0495

21-Oct-11 2291.15 16785.64 -1.3028 -1.1328 1.2833 1.6974 1.4759

24-Oct-11 2362.3 16939.28 2.0002 -0.4237 0.1796 4.0007 -0.8476

25-Oct-11 2458.35 17254.86 3.5939 1.4029 1.9682 12.9159 5.0419

26-Oct-11 2492.45 17288.83 1.5025 -0.2748 0.0755 2.2576 -0.4129

28-Oct-11 2541.85 17804.8 1.9435 0.7467 0.5575 3.7771 1.4511

31-Oct-11 2477.8 17705.01 -2.5446 -0.5716 0.3267 6.4750 1.4545

01-Nov-11 2492.15 17480.83 0.5658 -0.3416 0.1167 0.3201 -0.1933

02-Nov-11 2475.7 17464.85 -0.5796 0.6708 0.4499 0.3360 -0.3888

03-Nov-11 2503.45 17481.93 1.2183 0.2931 0.0859 1.4843 0.3571

04-Nov-11 2520.85 17562.61 0.4304 -0.6382 0.4073 0.1853 -0.2747

47

08-Nov-11 2522.15 17569.53 2.3849 -0.1374 0.0189 5.6876 -0.3277

09-Nov-11 2470.85 17362.1 -2.1106 -1.6120 2.5986 4.4547 3.4023

11-Nov-11 2469.3 17192.82 0.1701 0.0287 0.0008 0.0289 0.0049

14-Nov-11 2451.5 17118.74 -1.7744 -1.3423 1.8017 3.1486 2.3818

15-Nov-11 2455.05 16882.67 -0.5275 -1.1784 1.3887 0.2782 0.6216

16-Nov-11 2397.25 16775.87 -1.6874 -0.5748 0.3304 2.8472 0.9699

17-Nov-11 2332.6 16461.71 -1.9699 -1.7797 3.1674 3.8805 3.5059

18-Nov-11 2333.55 16371.51 1.3092 -0.0989 0.0098 1.7139 -0.1295

21-Nov-11 2275.45 15946.1 -1.8941 -2.2007 4.8432 3.5877 4.1685

22-Nov-11 2295.3 16065.42 0.6666 0.4340 0.1884 0.4443 0.2893

23-Nov-11 2260.15 15699.97 -1.0995 -1.7174 2.9494 1.2089 1.8882

24-Nov-11 2306.25 15858.49 0.2710 0.8997 0.8095 0.0734 0.2438

25-Nov-11 2262.35 15695.43 -1.5073 -0.5468 0.2990 2.2719 0.8242

28-Nov-11 2316.45 16167.13 0.8396 1.7092 2.9214 0.7050 1.4351

29-Nov-11 2314.6 16008.34 0.1555 -1.2620 1.5927 0.0242 -0.1963

30-Nov-11 2337.85 16123.46 1.6618 1.5784 2.4915 2.7615 2.6230

01-Dec-11 2426.95 16483.45 3.2160 -0.4397 0.1933 10.3425 -1.4141

02-Dec-11 2459.6 16846.83 1.2034 2.0945 4.3868 1.4483 2.5206

05-Dec-11 2455.75 16805.33 0.2341 -0.0415 0.0017 0.0548 -0.0097

07-Dec-11 2428.1 16877.06 -0.2945 0.2786 0.0776 0.0867 -0.0820

08-Dec-11 2405.9 16488.24 -1.3986 -2.0105 4.0422 1.9562 2.8120

09-Dec-11 2396 16213.46 0.4007 -0.2774 0.0770 0.1605 -0.1112

12-Dec-11 2316.1 15870.35 -4.1276 -3.0536 9.3242 17.0373 12.6039

13-Dec-11 2412.45 16002.51 2.6301 1.3991 1.9575 6.9175 3.6798

14-Dec-11 2398.65 15881.14 -0.0563 -0.5202 0.2706 0.0032 0.0293

15-Dec-11 2363.55 15836.47 -0.6960 0.6152 0.3784 0.4844 -0.4281

16-Dec-11 2368.2 15491.35 0.2196 -2.4364 5.9360 0.0482 -0.5350

19-Dec-11 2376.9 15175.08 1.0265 -0.3951 0.1561 1.0538 -0.4056

20-Dec-11 2347.25 15685.21 -1.1822 -1.7202 2.9590 1.3977 2.0337

21-Dec-11 2383.3 15813.36 0.9776 1.2589 1.5848 0.9558 1.2307

22-Dec-11 2407.95 15738.7 1.0362 1.6865 2.8444 1.0736 1.7475

23-Dec-11 2453.95 15970.75 1.9947 -0.7925 0.6281 3.9790 -1.5808

26-Dec-11 2477.85 15873.95 1.0029 1.1808 1.3942 1.0058 1.1842

27-Dec-11 2473.7 15727.85 0.3355 -0.6931 0.4805 0.1126 -0.2326

28-Dec-11 2462.85 15543.93 -0.2903 -0.8044 0.6470 0.0843 0.2335

29-Dec-11 2517.2 15454.92 2.3915 -0.7399 0.5475 5.7195 -1.7695

30-Dec-11 2508.55 16483.45 0.3408 -0.8323 0.6927 0.1162 -0.2837

    SUM 13.3376-

14.1822 85.0865 151.2227 63.7437

48

BETA S.D VARIANCE

CORRELATION    

0.818461 1.212832762 1.4710 0.6077    

Introduction of GRASIM

Beta of Grasim industries is 0.818461 which means the Grasim industry ompany

beta less than 1 means it tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of Grasim. Is

1.212832762So and correlation is 0.607702558so this is Positive correlation so

that It means that when market return increases, the company’s return also

increases.

Table No. 1. 5

Volatility of HDFC Bank | Finance . Return

  STOCK

PRICE

SENSEX PRICE

Stock Return

Sensex Return

   Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 458.45 16151.45 -1.4287 -0.6471 0.4188 2.0413 0.9246

04-Oct-11 450.3 15864.86 -1.0215 -1.3672 1.8693 1.0435 1.3967

05-Oct-11 438.35 15792.41 -2.7261 -1.1101 1.2323 7.4318 3.0263

07-Oct-11 449.8 16232.54 -1.1561 0.0619 0.0038 1.3365 -0.0716

10-Oct-11 454.55 16557.23 0.3630 1.7343 3.0080 0.1318 0.6296

11-Oct-11 457.65 16536.47 -0.0765 -0.7963 0.6341 0.0058 0.0609

12-Oct-11 467.15 16958.39 1.5306 1.7570 3.0871 2.3426 2.6892

13-Oct-11 470.45 16883.92 0.1169 -0.9718 0.9444 0.0137 -0.1136

14-Oct-11 474.15 17082.69 0.7276 1.4392 2.0714 0.5294 1.0472

17-Oct-11 477.85 17025.09 0.4813 -0.8867 0.7862 0.2317 -0.4268

18-Oct-11 476.8 16748.29 0.3775 -0.4125 0.1702 0.1425 -0.1557

19-Oct-11 491.1 17085.34 1.8530 1.1822 1.3976 3.4335 2.1906

20-Oct-11 489.5 16936.89 -0.0919 0.1478 0.0219 0.0085 -0.0136

49

21-Oct-11 486.3 16785.64 -0.6683 -1.1328 1.2833 0.4466 0.7571

24-Oct-11 484.1 16939.28 -1.4253 -0.4237 0.1796 2.0316 0.6040

25-Oct-11 468.75 17254.86 -3.2533 1.4029 1.9682 10.5842 -4.5641

26-Oct-11 471.9 17288.83 -0.5510 -0.2748 0.0755 0.3036 0.1514

28-Oct-11 482.5 17804.8 0.0000 0.7467 0.5575 0.0000 0.0000

31-Oct-11 489.05 17705.01 1.2371 -0.5716 0.3267 1.5304 -0.7071

01-Nov-11 481.95 17480.83 -0.6328 -0.3416 0.1167 0.4005 0.2162

02-Nov-11 483.05 17464.85 0.8591 0.6708 0.4499 0.7381 0.5763

03-Nov-11 480.8 17481.93 -0.2496 0.2931 0.0859 0.0623 -0.0732

04-Nov-11 482.1 17562.61 -0.8090 -0.6382 0.4073 0.6544 0.5163

08-Nov-11 484.7 17569.53 0.1444 -0.1374 0.0189 0.0209 -0.0198

09-Nov-11 477.45 17362.1 -1.7908 -1.6120 2.5986 3.2068 2.8867

11-Nov-11 463.95 17192.82 -1.0561 0.0287 0.0008 1.1154 -0.0303

14-Nov-11 470.7 17118.74 0.3612 -1.3423 1.8017 0.1304 -0.4848

15-Nov-11 471.8 16882.67 0.3815 -1.1784 1.3887 0.1456 -0.4496

16-Nov-11 465.95 16775.87 -1.2984 -0.5748 0.3304 1.6859 0.7464

17-Nov-11 458.85 16461.71 -1.3403 -1.7797 3.1674 1.7964 2.3854

18-Nov-11 457.7 16371.51 -0.0218 -0.0989 0.0098 0.0005 0.0022

21-Nov-11 444.9 15946.1 -3.1468 -2.2007 4.8432 9.9022 6.9252

22-Nov-11 443.8 16065.42 -1.1717 0.4340 0.1884 1.3729 -0.5086

23-Nov-11 426.7 15699.97 -3.5857 -1.7174 2.9494 12.8569 6.1580

24-Nov-11 429.95 15858.49 0.4535 0.8997 0.8095 0.2057 0.4081

25-Nov-11 431.5 15695.43 1.2051 -0.5468 0.2990 1.4523 -0.6589

28-Nov-11 440.8 16167.13 0.1815 1.7092 2.9214 0.0329 0.3102

29-Nov-11 434.4 16008.34 -1.9797 -1.2620 1.5927 3.9194 2.4985

30-Nov-11 441.45 16123.46 2.3899 1.5784 2.4915 5.7114 3.7723

01-Dec-11 453.45 16483.45 -0.5624 -0.4397 0.1933 0.3162 0.2473

02-Dec-11 465.75 16846.83 2.0934 2.0945 4.3868 4.3823 4.3845

05-Dec-11 462.25 16805.33 -0.5949 -0.0415 0.0017 0.3539 0.0247

07-Dec-11 465.95 16877.06 -0.2253 0.2786 0.0776 0.0508 -0.0628

08-Dec-11 453.9 16488.24 -2.7539 -2.0105 4.0422 7.5840 5.5368

09-Dec-11 444.8 16213.46 -0.7419 -0.2774 0.0770 0.5504 0.2058

12-Dec-11 431.9 15870.35 -4.1908 -3.0536 9.3242 17.5627 12.7968

13-Dec-11 436.4 16002.51 1.9248 1.3991 1.9575 3.7050 2.6930

14-Dec-11 433.85 15881.14 -1.4175 -0.5202 0.2706 2.0094 0.7374

15-Dec-11 431.35 15836.47 -0.1275 0.6152 0.3784 0.0163 -0.0784

16-Dec-11 415.95 15491.35 -4.5799 -2.4364 5.9360 20.9753 11.1584

19-Dec-11 406.05 15175.08 -1.8840 -0.3951 0.1561 3.5495 0.7443

20-Dec-11 414.1 15685.21 1.9802 -1.7202 2.9590 3.9212 -3.4063

21-Dec-11 435.3 15813.36 2.1365 1.2589 1.5848 4.5645 2.6896

22-Dec-11 443 15738.7 2.4831 1.6865 2.8444 6.1656 4.1878

50

23-Dec-11 437.6 15970.75 -0.7998 -0.7925 0.6281 0.6397 0.6339

26-Dec-11 443.45 15873.95 -0.0113 1.1808 1.3942 0.0001 -0.0133

27-Dec-11 439.6 15727.85 -1.0009 -0.6931 0.4805 1.0018 0.6938

28-Dec-11 439.65 15543.93 -0.0796 -0.8044 0.6470 0.0063 0.0640

29-Dec-11 430.65 15454.92 -1.8925 -0.7399 0.5475 3.5815 1.4003

30-Dec-11 427.05 16483.45 -0.9250 -0.8323 0.6927 0.8555 0.7698

    SUM-

27.9876 -14.1822 85.0865 160.7920 78.0086

               BETA S.D VARIAN

CECORRELATION    

0.873478831 1.2092483 1.4623 0.6497    

Interpretation of HDFC BANK

Beta of HDFC bank is 0.873478831 which means the HDFC bank beta is less

than 1 means it tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of HDFC bank Is

1.2092483So and correlation is 0.649695732 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.6

Volatility of Hindalco Industries | Metal, Metal Products & Mining .. Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

   Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 124.15 16151.45 -4.2690 -0.6471 0.4188 18.2246 2.7626

04-Oct-11 124.7 15864.86 1.8444 -1.3672 1.8693 3.4019 -2.5218

05-Oct-11 120.15 15792.41 -5.7012 -1.1101 1.2323 32.5038 6.3289

07-Oct-11 125.95 16232.54 0.3573 0.0619 0.0038 0.1277 0.0221

10-Oct-11 127.45 16557.23 1.1377 1.7343 3.0080 1.2944 1.9732

51

11-Oct-11 130.25 16536.47 0.5758 -0.7963 0.6341 0.3316 -0.4585

12-Oct-11 132.85 16958.39 0.8656 1.7570 3.0871 0.7493 1.5209

13-Oct-11 128.85 16883.92 -4.3073 -0.9718 0.9444 18.5531 4.1859

14-Oct-11 128.65 17082.69 0.6607 1.4392 2.0714 0.4365 0.9509

17-Oct-11 130.1 17025.09 0.1537 -0.8867 0.7862 0.0236 -0.1363

18-Oct-11 125.45 16748.29 -1.4747 -0.4125 0.1702 2.1747 0.6083

19-Oct-11 127.65 17085.34 0.2742 1.1822 1.3976 0.0752 0.3241

20-Oct-11 124.75 16936.89 -0.2806 0.1478 0.0219 0.0787 -0.0415

21-Oct-11 121.65 16785.64 -3.1648 -1.1328 1.2833 10.0161 3.5851

24-Oct-11 123.45 16939.28 -1.0936 -0.4237 0.1796 1.1959 0.4634

25-Oct-11 125.5 17254.86 0.9163 1.4029 1.9682 0.8397 1.2855

26-Oct-11 128.25 17288.83 1.2865 -0.2748 0.0755 1.6552 -0.3536

28-Oct-11 142.2 17804.8 5.5556 0.7467 0.5575 30.8642 4.1481

31-Oct-11 136.35 17705.01 -3.9971 -0.5716 0.3267 15.9765 2.2847

01-Nov-11 135.85 17480.83 0.9569 -0.3416 0.1167 0.9157 -0.3269

02-Nov-11 136.2 17464.85 1.9090 0.6708 0.4499 3.6441 1.2805

03-Nov-11 135.7 17481.93 0.4053 0.2931 0.0859 0.1643 0.1188

04-Nov-11 139 17562.61 0.1799 -0.6382 0.4073 0.0323 -0.1148

08-Nov-11 139.65 17569.53 -0.1790 -0.1374 0.0189 0.0320 0.0246

09-Nov-11 134.5 17362.1 -4.5353 -1.6120 2.5986 20.5691 7.3110

11-Nov-11 128.7 17192.82 -5.6721 0.0287 0.0008 32.1728 -0.1627

14-Nov-11 125.85 17118.74 -4.1716 -1.3423 1.8017 17.4025 5.5995

15-Nov-11 125.5 16882.67 -0.0398 -1.1784 1.3887 0.0016 0.0469

16-Nov-11 123.25 16775.87 -1.7850 -0.5748 0.3304 3.1862 1.0260

17-Nov-11 122.75 16461.71 -1.4257 -1.7797 3.1674 2.0325 2.5373

18-Nov-11 123.7 16371.51 1.5764 -0.0989 0.0098 2.4850 -0.1559

21-Nov-11 119.1 15946.1 -2.8128 -2.2007 4.8432 7.9116 6.1901

22-Nov-11 121.8 16065.42 1.4778 0.4340 0.1884 2.1840 0.6414

23-Nov-11 119.5 15699.97 -0.5858 -1.7174 2.9494 0.3431 1.0060

24-Nov-11 118 15858.49 -1.3136 0.8997 0.8095 1.7254 -1.1818

25-Nov-11 113.6 15695.43 -3.2130 -0.5468 0.2990 10.3236 1.7568

28-Nov-11 124.05 16167.13 7.1745 1.7092 2.9214 51.4738 12.2628

29-Nov-11 122.6 16008.34 -1.5498 -1.2620 1.5927 2.4017 1.9558

30-Nov-11 122.65 16123.46 1.3453 1.5784 2.4915 1.8098 2.1235

01-Dec-11 131.2 16483.45 1.2957 -0.4397 0.1933 1.6789 -0.5698

02-Dec-11 135.3 16846.83 3.7694 2.0945 4.3868 14.2084 7.8949

05-Dec-11 136.25 16805.33 1.7248 -0.0415 0.0017 2.9748 -0.0715

07-Dec-11 137.55 16877.06 0.1818 0.2786 0.0776 0.0330 0.0506

08-Dec-11 130.65 16488.24 -4.0949 -2.0105 4.0422 16.7683 8.2329

09-Dec-11 131.95 16213.46 3.7514 -0.2774 0.0770 14.0732 -1.0407

12-Dec-11 123.55 15870.35 -8.2962 -3.0536 9.3242 68.8275 25.3330

52

13-Dec-11 129.45 16002.51 5.5620 1.3991 1.9575 30.9358 7.7817

14-Dec-11 127.3 15881.14 -1.5711 -0.5202 0.2706 2.4683 0.8172

15-Dec-11 127.2 15836.47 2.3192 0.6152 0.3784 5.3786 1.4267

16-Dec-11 125.6 15491.35 -1.7118 -2.4364 5.9360 2.9302 4.1706

19-Dec-11 124.7 15175.08 0.5613 -0.3951 0.1561 0.3151 -0.2218

20-Dec-11 119.15 15685.21 -5.3294 -1.7202 2.9590 28.4027 9.1676

21-Dec-11 123 15813.36 -0.8943 1.2589 1.5848 0.7998 -1.1258

22-Dec-11 122.55 15738.7 1.2648 1.6865 2.8444 1.5997 2.1331

23-Dec-11 121.75 15970.75 -1.1910 -0.7925 0.6281 1.4184 0.9438

26-Dec-11 121.1 15873.95 -1.2799 1.1808 1.3942 1.6382 -1.5113

27-Dec-11 119.6 15727.85 -1.1288 -0.6931 0.4805 1.2741 0.7824

28-Dec-11 116.6 15543.93 -2.3156 -0.8044 0.6470 5.3620 1.8626

29-Dec-11 117.2 15454.92 1.4505 -0.7399 0.5475 2.1040 -1.0732

30-Dec-11 115.75 16483.45 -2.2462 -0.8323 0.6927 5.0455 1.8695

    SUM-

31.0970-

14.1822 85.0865 507.5706 135.7237

               BETA S.D VARIA

NCECORRELATION    

1.570618156 2.681583867 7.1909 0.6405    

Interpretation OF HINDALCO INDUSTRIES

Beta of Hindalco Industries is 1.570618156 which means the Hindalco Industries

beta is greater than 1 means it tends to be more volatile than the market BSE

Sensex.

So it is a less risky for investment. Standard deviation of Hidalco Industries Is

2.681583867 and correlation is 0.640518221 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

53

Table No. 1.7

Volatility of Hindustan Uni Lever | FMCG . Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

   Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 334.45 16151.45 -1.3604 -0.6471 0.4188 1.8508 0.8804

04-Oct-11 327.05 15864.86 -2.0486 -1.3672 1.8693 4.1968 2.8009

05-Oct-11 322.05 15792.41 -1.2265 -1.1101 1.2323 1.5043 1.3616

07-Oct-11 329.2 16232.54 0.3645 0.0619 0.0038 0.1329 0.0226

10-Oct-11 332.4 16557.23 0.4212 1.7343 3.0080 0.1774 0.7305

11-Oct-11 326.55 16536.47 -2.0058 -0.7963 0.6341 4.0233 1.5972

12-Oct-11 329.65 16958.39 1.2589 1.7570 3.0871 1.5849 2.2119

13-Oct-11 326.75 16883.92 -1.0099 -0.9718 0.9444 1.0200 0.9815

14-Oct-11 332.1 17082.69 1.5357 1.4392 2.0714 2.3583 2.2102

17-Oct-11 333.1 17025.09 -0.4953 -0.8867 0.7862 0.2454 0.4392

18-Oct-11 330.55 16748.29 -0.2420 -0.4125 0.1702 0.0586 0.0998

19-Oct-11 331.55 17085.34 -0.1056 1.1822 1.3976 0.0111 -0.1248

20-Oct-11 331.35 16936.89 0.1056 0.1478 0.0219 0.0112 0.0156

21-Oct-11 326.1 16785.64 -1.8093 -1.1328 1.2833 3.2734 2.0496

24-Oct-11 336.35 16939.28 2.2447 -0.4237 0.1796 5.0386 -0.9512

25-Oct-11 340.4 17254.86 1.5570 1.4029 1.9682 2.4242 2.1843

26-Oct-11 342.85 17288.83 0.3938 -0.2748 0.0755 0.1550 -0.1082

28-Oct-11 349.45 17804.8 1.5310 0.7467 0.5575 2.3439 1.1431

31-Oct-11 375.25 17705.01 6.4624 -0.5716 0.3267 41.7621 -3.6938

01-Nov-11 135.85 17480.83 0.9569 -0.3416 0.1167 0.9157 -0.3269

02-Nov-11 136.2 17464.85 1.9090 0.6708 0.4499 3.6441 1.2805

03-Nov-11 135.7 17481.93 0.4053 0.2931 0.0859 0.1643 0.1188

04-Nov-11 139 17562.61 0.1799 -0.6382 0.4073 0.0323 -0.1148

08-Nov-11 139.65 17569.53 -0.1790 -0.1374 0.0189 0.0320 0.0246

09-Nov-11 134.5 17362.1 -4.5353 -1.6120 2.5986 20.5691 7.3110

11-Nov-11 128.7 17192.82 -5.6721 0.0287 0.0008 32.1728 -0.1626

14-Nov-11 125.85 17118.74 -4.1716 -1.3423 1.8017 17.4025 5.5995

15-Nov-11 125.5 16882.67 -0.0398 -1.1784 1.3887 0.0016 0.0470

16-Nov-11 123.25 16775.87 -1.7850 -0.5748 0.3304 3.1862 1.0260

17-Nov-11 122.75 16461.71 -1.4257 -1.7797 3.1674 2.0325 2.5373

18-Nov-11 123.7 16371.51 1.5764 -0.0989 0.0098 2.4850 -0.1559

21-Nov-11 119.1 15946.1 -2.8128 -2.2007 4.8432 7.9116 6.1901

22-Nov-11 121.8 16065.42 1.4778 0.4340 0.1884 2.1840 0.6414

54

23-Nov-11 119.5 15699.97 -0.5858 -1.7174 2.9494 0.3431 1.0060

24-Nov-11 118 15858.49 -1.3136 0.8997 0.8095 1.7254 -1.1818

25-Nov-11 113.6 15695.43 -3.2130 -0.5468 0.2990 10.3236 1.7568

28-Nov-11 124.05 16167.13 7.1745 1.7092 2.9214 51.4738 12.2628

29-Nov-11 122.6 16008.34 -1.5498 -1.2620 1.5927 2.4017 1.9558

30-Nov-11 122.65 16123.46 1.3453 1.5784 2.4915 1.8098 2.1235

01-Dec-11 131.2 16483.45 1.2957 -0.4397 0.1933 1.6789 -0.5698

02-Dec-11 135.3 16846.83 3.7694 2.0945 4.3868 14.2084 7.8949

05-Dec-11 136.25 16805.33 1.7248 -0.0415 0.0017 2.9748 -0.0715

07-Dec-11 137.55 16877.06 0.1818 0.2786 0.0776 0.0330 0.0506

08-Dec-11 130.65 16488.24 -4.0949 -2.0105 4.0422 16.7683 8.2329

09-Dec-11 131.95 16213.46 3.7514 -0.2774 0.0770 14.0732 -1.0407

12-Dec-11 123.55 15870.35 -8.2962 -3.0536 9.3242 68.8275 25.3330

13-Dec-11 129.45 16002.51 5.5620 1.3991 1.9575 30.9358 7.7818

14-Dec-11 127.3 15881.14 -1.5711 -0.5202 0.2706 2.4683 0.8173

15-Dec-11 127.2 15836.47 2.3192 0.6152 0.3784 5.3786 1.4267

16-Dec-11 125.6 15491.35 -1.7118 -2.4364 5.9360 2.9302 4.1706

19-Dec-11 124.7 15175.08 0.5613 -0.3951 0.1561 0.3151 -0.2218

20-Dec-11 119.15 15685.21 -5.3294 -1.7202 2.9590 28.4027 9.1676

21-Dec-11 123 15813.36 -0.8943 1.2589 1.5848 0.7998 -1.1258

22-Dec-11 122.55 15738.7 1.2648 1.6865 2.8444 1.5997 2.1331

23-Dec-11 121.75 15970.75 -1.1910 -0.7925 0.6281 1.4184 0.9439

26-Dec-11 121.1 15873.95 -1.2799 1.1808 1.3942 1.6382 -1.5113

27-Dec-11 119.6 15727.85 -1.1288 -0.6931 0.4805 1.2741 0.7824

28-Dec-11 116.6 15543.93 -2.3156 -0.8044 0.6470 5.3620 1.8626

29-Dec-11 117.2 15454.92 1.4505 -0.7399 0.5475 2.1040 -1.0732

30-Dec-11 115.75 16483.45 -2.2462 -0.8323 0.6927 5.0455 1.8695

    SUM-

14.8655-

14.1822 85.0865 441.2202 122.6420

               BETA S.D VARIA

NCECORRELATION    

1.457506 2.508442833 6.2923 0.6299    

Interpretation of HUL

55

Beta of Hindustan Uni Lever is 1.457506which means the Hindustan Uni Lever

beta is greater than 1 means it tends to be more volatile than the market BSE

Sensex.

So it is a more risky for investment.standard deviation of Hindustan Uni Lever Is

2.508442833 and correlation is 0.629948332 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.8

Volatility of Mahindra and Mahindra | Transport Equipments Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 809.35 16151.45 1.1552 -0.6471 0.4188 1.3346 -0.7476

04-Oct-11 777.9 15864.86 -3.4837 -1.3672 1.8693 12.1364 4.7631

05-Oct-11 784.45 15792.41 0.4398 -1.1101 1.2323 0.1934 -0.4882

07-Oct-11 795.95 16232.54 0.4334 0.0619 0.0038 0.1879 0.0268

10-Oct-11 806.1 16557.23 1.9352 1.7343 3.0080 3.7452 3.3564

11-Oct-11 798.5 16536.47 -1.6281 -0.7963 0.6341 2.6506 1.2964

12-Oct-11 808.05 16958.39 1.1076 1.7570 3.0871 1.2268 1.9461

13-Oct-11 798.9 16883.92 -1.7649 -0.9718 0.9444 3.1150 1.7152

14-Oct-11 805.6 17082.69 1.0675 1.4392 2.0714 1.1396 1.5364

17-Oct-11 810.55 17025.09 0.5367 -0.8867 0.7862 0.2880 -0.4759

18-Oct-11 805.65 16748.29 -0.1552 -0.4125 0.1702 0.0241 0.0640

19-Oct-11 810.4 17085.34 0.0494 1.1822 1.3976 0.0024 0.0584

20-Oct-11 800.2 16936.89 -1.3497 0.1478 0.0219 1.8216 -0.1995

21-Oct-11 801.1 16785.64 0.0125 -1.1328 1.2833 0.0002 -0.0141

24-Oct-11 808.8 16939.28 0.0989 -0.4237 0.1796 0.0098 -0.0419

25-Oct-11 853.2 17254.86 5.0340 1.4029 1.9682 25.3411 7.0622

26-Oct-11 849.45 17288.83 -0.0647 -0.2748 0.0755 0.0042 0.0178

28-Oct-11 868.5 17804.8 0.9787 0.7467 0.5575 0.9579 0.7307

31-Oct-11 863.2 17705.01 -0.7878 -0.5716 0.3267 0.6206 0.4503

01-Nov-11 834.05 17480.83 -2.5118 -0.3416 0.1167 6.3093 0.8581

02-Nov-11 838.7 17464.85 0.5604 0.6708 0.4499 0.3140 0.3759

56

03-Nov-11 838.3 17481.93 -0.5607 0.2931 0.0859 0.3143 -0.1643

04-Nov-11 835.05 17562.61 -0.7125 -0.6382 0.4073 0.5077 0.4548

08-Nov-11 833.65 17569.53 -0.7977 -0.1374 0.0189 0.6363 0.1096

09-Nov-11 813 17362.1 -3.3210 -1.6120 2.5986 11.0293 5.3536

11-Nov-11 838.4 17192.82 3.1489 0.0287 0.0008 9.9153 0.0903

14-Nov-11 790.4 17118.74 -6.9079 -1.3423 1.8017 47.7190 9.2723

15-Nov-11 759 16882.67 -4.3478 -1.1784 1.3887 18.9036 5.1236

16-Nov-11 773.35 16775.87 0.4332 -0.5748 0.3304 0.1876 -0.2490

17-Nov-11 758.55 16461.71 -2.1686 -1.7797 3.1674 4.7029 3.8595

18-Nov-11 737.8 16371.51 -3.0089 -0.0989 0.0098 9.0538 0.2976

21-Nov-11 717.7 15946.1 -2.7031 -2.2007 4.8432 7.3066 5.9487

22-Nov-11 709.6 16065.42 -1.4656 0.4340 0.1884 2.1480 -0.6361

23-Nov-11 695.55 15699.97 -1.3730 -1.7174 2.9494 1.8852 2.3580

24-Nov-11 713.4 15858.49 1.8783 0.8997 0.8095 3.5281 1.6899

25-Nov-11 706.3 15695.43 -0.0991 -0.5468 0.2990 0.0098 0.0542

28-Nov-11 713.65 16167.13 -0.1822 1.7092 2.9214 0.0332 -0.3114

29-Nov-11 725.05 16008.34 0.9723 -1.2620 1.5927 0.9455 -1.2271

30-Nov-11 723.85 16123.46 0.4283 1.5784 2.4915 0.1834 0.6760

01-Dec-11 729.8 16483.45 -1.8224 -0.4397 0.1933 3.3212 0.8013

02-Dec-11 748.05 16846.83 1.7713 2.0945 4.3868 3.1374 3.7099

05-Dec-11 750.05 16805.33 0.2733 -0.0415 0.0017 0.0747 -0.0113

07-Dec-11 757.45 16877.06 0.9836 0.2786 0.0776 0.9674 0.2740

08-Dec-11 730.15 16488.24 -3.8143 -2.0105 4.0422 14.5488 7.6687

09-Dec-11 703.75 16213.46 -2.0249 -0.2774 0.0770 4.1001 0.5617

12-Dec-11 684.05 15870.35 -3.7936 -3.0536 9.3242 14.3913 11.5839

13-Dec-11 700.3 16002.51 2.4989 1.3991 1.9575 6.2446 3.4962

14-Dec-11 675.55 15881.14 -3.6193 -0.5202 0.2706 13.0991 1.8827

15-Dec-11 665.55 15836.47 -0.5184 0.6152 0.3784 0.2687 -0.3189

16-Dec-11 659.3 15491.35 -1.0162 -2.4364 5.9360 1.0327 2.4759

19-Dec-11 652.45 15175.08 -1.5403 -0.3951 0.1561 2.3727 0.6086

20-Dec-11 650.95 15685.21 -0.4685 -1.7202 2.9590 0.2195 0.8060

21-Dec-11 689.8 15813.36 4.0302 1.2589 1.5848 16.2421 5.0735

22-Dec-11 693.3 15738.7 4.0819 1.6865 2.8444 16.6621 6.8844

23-Dec-11 696.4 15970.75 0.4882 -0.7925 0.6281 0.2384 -0.3869

26-Dec-11 702.1 15873.95 0.3632 1.1808 1.3942 0.1319 0.4289

27-Dec-11 703.6 15727.85 -0.0426 -0.6931 0.4805 0.0018 0.0296

28-Dec-11 686.75 15543.93 -2.3662 -0.8044 0.6470 5.5990 1.9033

29-Dec-11 686.6 15454.92 0.3787 -0.7399 0.5475 0.1434 -0.2802

30-Dec-11 683.05 16483.45 -0.9882 -0.8323 0.6927 0.9766 0.8225

    SUM -26.2694 -14.1822 85.0865 284.2057 103.0044

57

               BETA   S.D   VARIAN

CECORREL

ATION    1.184265   1.882836062   3.5451 0.6483    

Interpretation of MAHIDRA & MAHINDRA

Beta of Mahindra and Mahindra is 1.1842653 which means the Mahindra and

Mahindra beta is greater than 1 means it tends to be more volatile than the

market BSE Sensex.

So it is a more risky for investment.standard deviation of Mahindra and Mahindra

Is 1.882836062and correlation is 0.648343438 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.9

Volatility of NTPC | Power | Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 164.7 16151.45 -1.2143 -0.6471 0.4188 1.4746 0.7858

04-Oct-11 163.95 15864.86 -0.2135 -1.3672 1.8693 0.0456 0.2919

58

05-Oct-11 163.9 15792.41 -0.2746 -1.1101 1.2323 0.0754 0.3048

07-Oct-11 166.6 16232.54 -0.8403 0.0619 0.0038 0.7062 -0.0520

10-Oct-11 170.5 16557.23 1.9941 1.7343 3.0080 3.9766 3.4585

11-Oct-11 176.45 16536.47 3.3437 -0.7963 0.6341 11.1805 -2.6626

12-Oct-11 177.1 16958.39 0.6211 1.7570 3.0871 0.3858 1.0913

13-Oct-11 173.7 16883.92 -2.1877 -0.9718 0.9444 4.7859 2.1260

14-Oct-11 173 17082.69 0.0000 1.4392 2.0714 0.0000 0.0000

17-Oct-11 168.45 17025.09 -2.7011 -0.8867 0.7862 7.2959 2.3950

18-Oct-11 168.45 16748.29 0.2671 -0.4125 0.1702 0.0714 -0.1102

19-Oct-11 171.9 17085.34 2.0942 1.1822 1.3976 4.3858 2.4758

20-Oct-11 171.4 16936.89 -0.1750 0.1478 0.0219 0.0306 -0.0259

21-Oct-11 169.25 16785.64 -1.0340 -1.1328 1.2833 1.0691 1.1713

24-Oct-11 171.15 16939.28 -0.2921 -0.4237 0.1796 0.0853 0.1238

25-Oct-11 173.6 17254.86 1.3537 1.4029 1.9682 1.8325 1.8991

26-Oct-11 174.25 17288.83 0.1148 -0.2748 0.0755 0.0132 -0.0315

28-Oct-11 178.6 17804.8 0.1960 0.7467 0.5575 0.0384 0.1463

31-Oct-11 179.35 17705.01 0.1951 -0.5716 0.3267 0.0381 -0.1115

01-Nov-11 177.6 17480.83 -0.5068 -0.3416 0.1167 0.2568 0.1731

02-Nov-11 176.05 17464.85 -0.5396 0.6708 0.4499 0.2912 -0.3620

03-Nov-11 178 17481.93 1.0955 0.2931 0.0859 1.2001 0.3211

04-Nov-11 179.55 17562.61 -0.0278 -0.6382 0.4073 0.0008 0.0178

08-Nov-11 177.75 17569.53 -0.3094 -0.1374 0.0189 0.0957 0.0425

09-Nov-11 174.4 17362.1 -2.6376 -1.6120 2.5986 6.9570 4.2519

11-Nov-11 173.7 17192.82 -0.1727 0.0287 0.0008 0.0298 -0.0050

14-Nov-11 172.65 17118.74 -1.3322 -1.3423 1.8017 1.7747 1.7881

15-Nov-11 169.95 16882.67 -1.7946 -1.1784 1.3887 3.2208 2.1149

16-Nov-11 169.25 16775.87 -0.4431 -0.5748 0.3304 0.1964 0.2547

17-Nov-11 165.25 16461.71 -1.7852 -1.7797 3.1674 3.1868 3.1771

18-Nov-11 162.8 16371.51 -1.9656 -0.0989 0.0098 3.8636 0.1944

21-Nov-11 156.4 15946.1 -3.5806 -2.2007 4.8432 12.8204 7.8798

22-Nov-11 155.75 16065.42 -1.5730 0.4340 0.1884 2.4744 -0.6828

23-Nov-11 156.65 15699.97 0.6064 -1.7174 2.9494 0.3678 -1.0415

24-Nov-11 158.65 15858.49 1.0085 0.8997 0.8095 1.0171 0.9074

25-Nov-11 156.95 15695.43 -1.2743 -0.5468 0.2990 1.6238 0.6968

28-Nov-11 159.55 16167.13 -0.2194 1.7092 2.9214 0.0481 -0.3749

29-Nov-11 158.25 16008.34 -1.1058 -1.2620 1.5927 1.2229 1.3956

30-Nov-11 162.05 16123.46 2.5609 1.5784 2.4915 6.5584 4.0423

01-Dec-11 166.3 16483.45 0.7517 -0.4397 0.1933 0.5650 -0.3305

02-Dec-11 172.2 16846.83 3.4262 2.0945 4.3868 11.7392 7.1761

05-Dec-11 175.9 16805.33 2.3309 -0.0415 0.0017 5.4330 -0.0967

07-Dec-11 170.25 16877.06 -2.7900 0.2786 0.0776 7.7842 -0.7773

08-Dec-11 166.35 16488.24 -1.6531 -2.0105 4.0422 2.7329 3.3237

09-Dec-11 166.15 16213.46 1.2940 -0.2774 0.0770 1.6745 -0.3590

59

12-Dec-11 163.15 15870.35 -2.9727 -3.0536 9.3242 8.8371 9.0774

13-Dec-11 166.7 16002.51 2.3395 1.3991 1.9575 5.4734 3.2732

14-Dec-11 163.1 15881.14 -1.1649 -0.5202 0.2706 1.3571 0.6060

15-Dec-11 166.4 15836.47 2.0433 0.6152 0.3784 4.1749 1.2569

16-Dec-11 161.05 15491.35 -3.1357 -2.4364 5.9360 9.8324 7.6397

19-Dec-11 160.5 15175.08 -0.9034 -0.3951 0.1561 0.8162 0.3569

20-Dec-11 154.85 15685.21 -4.2622 -1.7202 2.9590 18.1663 7.3318

21-Dec-11 160.3 15813.36 2.3082 1.2589 1.5848 5.3277 2.9057

22-Dec-11 163.8 15738.7 1.7094 1.6865 2.8444 2.9221 2.8830

23-Dec-11 158.5 15970.75 -1.5773 -0.7925 0.6281 2.4878 1.2500

26-Dec-11 160.6 15873.95 0.9963 1.1808 1.3942 0.9925 1.1764

27-Dec-11 156.95 15727.85 -1.9433 -0.6931 0.4805 3.7764 1.3470

28-Dec-11 161.15 15543.93 1.6755 -0.8044 0.6470 2.8072 -1.3477

29-Dec-11 160.8 15454.92 -0.4353 -0.7399 0.5475 0.1895 0.3221

30-Dec-11 160.6 16483.45 0.5915 -0.8323 0.6927 0.3499 -0.4923

    SUM-

14.1207-

14.1822 85.0865 182.1366 84.5896

               BETA S.D VARIA

NCECORREL

ATION    0.9940986 1.407204178 1.9802 0.6721    

Interpretation of NTPC

Beta of NTPC is 0.9940986which means the NTPC beta is less than 1 means it

tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of NTPC Is

1.407204178and correlation is 0.672096314is Positive correlation so that It

means that when market return increases, the company’s return also increases

60

Table No. 1.10

Volatility of Larsen & Toubro | Capital Goods Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 1318.2516151.4

5 -2.1809 -0.6471 0.4188 4.7564 1.4113

04-Oct-11 133715864.8

6 1.3912 -1.3672 1.8693 1.9354 -1.9021

05-Oct-11 1343.6515792.4

1 -0.6810 -1.1101 1.2323 0.4637 0.7560

07-Oct-11 1393.4516232.5

4 0.9652 0.0619 0.0038 0.9317 0.0598

10-Oct-11 1386.316557.2

3 -0.4833 1.7343 3.0080 0.2336 -0.8382

11-Oct-11 1409.716536.4

7 0.7519 -0.7963 0.6341 0.5654 -0.5988

12-Oct-11 1443.4516958.3

9 1.7216 1.7570 3.0871 2.9638 3.0248

13-Oct-11 1418.316883.9

2 -2.2351 -0.9718 0.9444 4.9955 2.172114-Oct-11 1407.8 17082.6

9-0.6535 1.4392 2.0714 0.4271 -0.9405

17-Oct-11 1379.917025.0

9 -2.6886 -0.8867 0.7862 7.2286 2.3840

18-Oct-11 1349.1516748.2

9 -1.3082 -0.4125 0.1702 1.7115 0.5397

19-Oct-11 1399.617085.3

4 2.9616 1.1822 1.3976 8.7708 3.5011

20-Oct-11 1385.0516936.8

9 0.3646 0.1478 0.0219 0.1329 0.0539

21-Oct-11 133616785.6

4 -3.7425 -1.1328 1.2833 14.0064 4.2396

24-Oct-11 1294.416939.2

8 -4.2954 -0.4237 0.1796 18.4507 1.8202

25-Oct-11 1336.7517254.8

6 2.9138 1.4029 1.9682 8.4901 4.0878

26-Oct-11 1350.6517288.8

3 0.3591 -0.2748 0.0755 0.1289 -0.0987

28-Oct-11 1413.25 17804.8 2.1263 0.7467 0.5575 4.5212 1.5876

31-Oct-11 1413.2517705.0

1 -0.0531 -0.5716 0.3267 0.0028 0.0303

01-Nov-11 1390.217480.8

3 -0.4999 -0.3416 0.1167 0.2499 0.1708

02-Nov-11 1387.317464.8

5 1.1605 0.6708 0.4499 1.3468 0.7785

03-Nov-11 1380.8517481.9

3 -0.4454 0.2931 0.0859 0.1984 -0.1305

04-Nov-11 1392.8517562.6

1 -0.2980 -0.6382 0.4073 0.0888 0.1902

08-Nov-11 1391.6517569.5

3 -0.6000 -0.1374 0.0189 0.3600 0.0824

09-Nov-11 1376 17362.1 -1.5988 -1.6120 2.5986 2.5563 2.5774

11-Nov-11 1330.65 17192.8 -2.2170 0.0287 0.0008 4.9149 -0.0636

61

2

14-Nov-11 1326.117118.7

4 -1.7269 -1.3423 1.8017 2.9821 2.3179

15-Nov-11 1288.816882.6

7 -2.9562 -1.1784 1.3887 8.7394 3.4837

16-Nov-11 1236.716775.8

7 -3.2587 -0.5748 0.3304 10.6189 1.8731

17-Nov-11 1232.516461.7

1 -0.0974 -1.7797 3.1674 0.0095 0.1733

18-Nov-11 124316371.5

1 1.4401 -0.0989 0.0098 2.0738 -0.1424

21-Nov-11 1226.3 15946.1 -1.9082 -2.2007 4.8432 3.6412 4.1994

22-Nov-11 1226.2516065.4

2 -0.0612 0.4340 0.1884 0.0037 -0.0266

23-Nov-11 1191.3515699.9

7 -2.4048 -1.7174 2.9494 5.7832 4.1300

24-Nov-11 1224.215858.4

9 2.7120 0.8997 0.8095 7.3548 2.4400

25-Nov-11 1265.815695.4

3 3.7447 -0.5468 0.2990 14.0225 -2.0475

28-Nov-11 1279.316167.1

3 -0.1798 1.7092 2.9214 0.0323 -0.3073

29-Nov-11 1273.3516008.3

4 -0.6636 -1.2620 1.5927 0.4404 0.8375

30-Nov-11 1268.816123.4

6 0.3783 1.5784 2.4915 0.1431 0.5971

01-Dec-11 1294.716483.4

5 -0.7956 -0.4397 0.1933 0.6329 0.3498

02-Dec-11 1310.7516846.8

3 0.9346 2.0945 4.3868 0.8734 1.9574

05-Dec-11 1314.416805.3

3 0.9282 -0.0415 0.0017 0.8615 -0.0385

07-Dec-11 133116877.0

6 0.7663 0.2786 0.0776 0.5873 0.2135

08-Dec-11 1262.9516488.2

4 -5.2298 -2.0105 4.0422 27.3510 10.5147

09-Dec-11 122716213.4

6 -1.6300 -0.2774 0.0770 2.6569 0.4522

12-Dec-11 1194.8515870.3

5 -4.0214 -3.0536 9.3242 16.1719 12.2796

13-Dec-11 1171.6516002.5

1 -1.3699 1.3991 1.9575 1.8765 -1.9166

14-Dec-11 1159.515881.1

4 -0.5606 -0.5202 0.2706 0.3143 0.2916

15-Dec-11 1136.3515836.4

7 -1.1968 0.6152 0.3784 1.4324 -0.7362

16-Dec-11 1075.815491.3

5 -6.8042 -2.4364 5.9360 46.2977 16.5778

19-Dec-11 1032.115175.0

8 -3.6721 -0.3951 0.1561 13.4845 1.4508

20-Dec-11 979.115685.2

1 -5.1680 -1.7202 2.9590 26.7083 8.8900

21-Dec-11 1001.1515813.3

6 0.1149 1.2589 1.5848 0.0132 0.1446

22-Dec-11 1009.35 15738.7 1.4217 1.6865 2.8444 2.0213 2.3978

23-Dec-11 1008.715970.7

5 -0.8328 -0.7925 0.6281 0.6935 0.6600

26-Dec-11 1025.7515873.9

5 0.7555 1.1808 1.3942 0.5709 0.8921

27-Dec-11 1028.8 15727.8 -0.2819 -0.6931 0.4805 0.0795 0.1954

62

5

28-Dec-11 1029.7515543.9

3 0.4904 -0.8044 0.6470 0.2405 -0.3945

29-Dec-11 1000.515454.9

2 -2.3388 -0.7399 0.5475 5.4701 1.7305

30-Dec-11 995.116483.4

5 -0.9949 -0.8323 0.6927 0.9898 0.8280

    SUM -43.7317 -14.1822 85.0865 295.6040 99.1632

               BETA S.D VARIAN

CECORRELATION    

1.086769653 1.842685257 3.3955 0.6050    

Interpretation of L & T

Beta of Larsen & Toubro is 1.086769653 which means the Larsen & Toubro beta

is more than 1 means it tends to be more volatile than the market BSE Sensex.

So it is a more risky for investment.standard deviation of Larsen & Toubro Is

1.842685257 and correlation is 0.605006976is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.11

Volatility of Reliance Industries | Oil & Gas Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 788.2 16151.45 -0.7866 -0.6471 0.4188 0.6187 0.5090

04-Oct-11 772.4 15864.86 -1.6831 -1.3672 1.8693 2.8327 2.3011

05-Oct-11 767.25 15792.41 -0.8667 -1.1101 1.2323 0.7512 0.9622

07-Oct-11 801.45 16232.54 1.9278 0.0619 0.0038 3.7162 0.1194

63

10-Oct-11 827.9 16557.23 2.9774 1.7343 3.0080 8.8650 5.1639

11-Oct-11 825.85 16536.47 -1.2290 -0.7963 0.6341 1.5105 0.9787

12-Oct-11 849.5 16958.39 2.4132 1.7570 3.0871 5.8235 4.2400

13-Oct-11 846.85 16883.92 -0.3720 -0.9718 0.9444 0.1384 0.3615

14-Oct-11 866.8 17082.69 2.9072 1.4392 2.0714 8.4521 4.1842

17-Oct-11 833.2 17025.09 -4.2967 -0.8867 0.7862 18.4615 3.8098

18-Oct-11 820 16748.29 -0.6098 -0.4125 0.1702 0.3718 0.2515

19-Oct-11 842.3 17085.34 2.0658 1.1822 1.3976 4.2674 2.4421

20-Oct-11 838.4 16936.89 0.5844 0.1478 0.0219 0.3416 0.0864

21-Oct-11 835.4 16785.64 -0.4309 -1.1328 1.2833 0.1857 0.4882

24-Oct-11 846.25 16939.28 -0.1950 -0.4237 0.1796 0.0380 0.0826

25-Oct-11 875 17254.86 2.5143 1.4029 1.9682 6.3216 3.5273

26-Oct-11 873.35 17288.83 -0.4179 -0.2748 0.0755 0.1747 0.1148

28-Oct-11 898 17804.8 0.1114 0.7467 0.5575 0.0124 0.0831

31-Oct-11 877.75 17705.01 -2.3754 -0.5716 0.3267 5.6425 1.3577

01-Nov-11 860.55 17480.83 -0.9819 -0.3416 0.1167 0.9642 0.3355

02-Nov-11 871.45 17464.85 1.8877 0.6708 0.4499 3.5633 1.2662

03-Nov-11 884.6 17481.93 1.8257 0.2931 0.0859 3.3331 0.5351

04-Nov-11 879.6 17562.61 -2.4443 -0.6382 0.4073 5.9746 1.5600

08-Nov-11 881.85 17569.53 0.2098 -0.1374 0.0189 0.0440 -0.0288

09-Nov-11 864.55 17362.1 -2.9553 -1.6120 2.5986 8.7338 4.7640

11-Nov-11 883.85 17192.82 2.8229 0.0287 0.0008 7.9686 0.0809

14-Nov-11 875.15 17118.74 -1.6454 -1.3423 1.8017 2.7074 2.2086

15-Nov-11 862.7 16882.67 -0.9621 -1.1784 1.3887 0.9256 1.1338

16-Nov-11 848.95 16775.87 -1.3369 -0.5748 0.3304 1.7874 0.7685

17-Nov-11 810.65 16461.71 -4.2373 -1.7797 3.1674 17.9551 7.5412

18-Nov-11 808.05 16371.51 0.9900 -0.0989 0.0098 0.9802 -0.0979

21-Nov-11 786.85 15946.1 -1.7856 -2.2007 4.8432 3.1884 3.9296

22-Nov-11 795.05 16065.42 1.0628 0.4340 0.1884 1.1296 0.4613

23-Nov-11 773.75 15699.97 -1.9709 -1.7174 2.9494 3.8845 3.3848

24-Nov-11 774.2 15858.49 -0.1033 0.8997 0.8095 0.0107 -0.0930

25-Nov-11 754 15695.43 -1.9761 -0.5468 0.2990 3.9051 1.0805

28-Nov-11 783 16167.13 2.4266 1.7092 2.9214 5.8882 4.1475

29-Nov-11 765 16008.34 -2.3268 -1.2620 1.5927 5.4140 2.9365

30-Nov-11 778.8 16123.46 2.8505 1.5784 2.4915 8.1256 4.4994

01-Dec-11 798.5 16483.45 -0.0063 -0.4397 0.1933 0.0000 0.0028

02-Dec-11 810.8 16846.83 1.5787 2.0945 4.3868 2.4923 3.3065

05-Dec-11 807.35 16805.33 -0.0372 -0.0415 0.0017 0.0014 0.0015

07-Dec-11 809.2 16877.06 0.2286 0.2786 0.0776 0.0523 0.0637

08-Dec-11 779.2 16488.24 -3.0416 -2.0105 4.0422 9.2512 6.1152

09-Dec-11 755.45 16213.46 -1.8863 -0.2774 0.0770 3.5581 0.5233

64

12-Dec-11 727.9 15870.35 -4.5611 -3.0536 9.3242 20.8033 13.9275

13-Dec-11 742.6 16002.51 2.7067 1.3991 1.9575 7.3263 3.7869

14-Dec-11 741.7 15881.14 0.5123 -0.5202 0.2706 0.2625 -0.2665

15-Dec-11 748.7 15836.47 2.1905 0.6152 0.3784 4.7981 1.3475

16-Dec-11 723 15491.35 -3.9557 -2.4364 5.9360 15.6479 9.6377

19-Dec-11 735.85 15175.08 2.1676 -0.3951 0.1561 4.6983 -0.8564

20-Dec-11 713.55 15685.21 -3.7068 -1.7202 2.9590 13.7405 6.3764

21-Dec-11 747.25 15813.36 2.4423 1.2589 1.5848 5.9648 3.0746

22-Dec-11 754.75 15738.7 1.6827 1.6865 2.8444 2.8314 2.8379

23-Dec-11 746.45 15970.75 -1.6813 -0.7925 0.6281 2.8267 1.3324

26-Dec-11 760.95 15873.95 1.4390 1.1808 1.3942 2.0707 1.6991

27-Dec-11 753.25 15727.85 -1.5732 -0.6931 0.4805 2.4749 1.0904

28-Dec-11 738.55 15543.93 -1.7399 -0.8044 0.6470 3.0272 1.3995

29-Dec-11 712.9 15454.92 -2.9457 -0.7399 0.5475 8.6772 2.1795

30-Dec-11 692.9 16483.45 -2.9009 -0.8323 0.6927 8.4149 2.4144

    SUM-

19.4993-

14.1822 85.0865 273.9289 131.4715

               BETA S.D VARIA

NCECORRELATION    

1.552133406 1.860071268 3.4599 0.8578    

Interpretation OF Reliance Industries

Beta of Reliance Industries is 1.552133406 which means the Reliance Industries

beta is more than 1 means it tends to be more volatile than the market BSE

Sensex.

So it is a more risky for investment.standard deviation of Reliance Industries Is

1.860071268 and correlation is 0.857817022 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

65

Table No. 1.12

Volatility of State Bank of India | Finance Return

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y (m) X X^2 Y^2 X*Y

03-Oct-11 1862.75 16151.45 -1.1891 -0.6471 0.4188 1.4140 0.7695

04-Oct-11 1786.7 15864.86 -3.6380 -1.3672 1.8693 13.2350 4.9740

05-Oct-11 1715.3 15792.41 -5.1711 -1.1101 1.2323 26.7403 5.7404

07-Oct-11 1751.85 16232.54 -0.6365 0.0619 0.0038 0.4051 -0.0394

10-Oct-11 1754.55 16557.23 -0.3106 1.7343 3.0080 0.0965 -0.5387

11-Oct-11 1765.1 16536.47 -0.4476 -0.7963 0.6341 0.2003 0.3564

12-Oct-11 1872.25 16958.39 4.9272 1.7570 3.0871 24.2776 8.6572

13-Oct-11 1886.95 16883.92 0.2623 -0.9718 0.9444 0.0688 -0.2549

14-Oct-11 1882.5 17082.69 0.4515 1.4392 2.0714 0.2039 0.6499

17-Oct-11 1891.8 17025.09 -0.4334 -0.8867 0.7862 0.1879 0.3843

18-Oct-11 1863.4 16748.29 -0.3918 -0.4125 0.1702 0.1535 0.1616

19-Oct-11 1919.1 17085.34 1.5215 1.1822 1.3976 2.3151 1.7987

20-Oct-11 1934.45 16936.89 2.1582 0.1478 0.0219 4.6580 0.3191

21-Oct-11 1948.6 16785.64 0.4208 -1.1328 1.2833 0.1771 -0.4767

24-Oct-11 1907.55 16939.28 -3.5359 -0.4237 0.1796 12.5029 1.4984

25-Oct-11 1840.45 17254.86 -4.3223 1.4029 1.9682 18.6824 -6.0638

26-Oct-11 1866.95 17288.83 0.4794 -0.2748 0.0755 0.2298 -0.1317

28-Oct-11 1907 17804.8 -0.7918 0.7467 0.5575 0.6270 -0.5912

31-Oct-11 1906.7 17705.01 -0.6451 -0.5716 0.3267 0.4161 0.3687

01-Nov-11 1902.2 17480.83 0.4311 -0.3416 0.1167 0.1858 -0.1473

02-Nov-11 1908.95 17464.85 1.2546 0.6708 0.4499 1.5741 0.8416

03-Nov-11 1934.5 17481.93 1.6800 0.2931 0.0859 2.8225 0.4924

04-Nov-11 1964.25 17562.61 0.3335 -0.6382 0.4073 0.1112 -0.2128

08-Nov-11 1997.55 17569.53 1.3166 -0.1374 0.0189 1.7335 -0.1809

09-Nov-11 1862.5 17362.1 -8.1450 -1.6120 2.5986 66.3405 13.1298

11-Nov-11 1797.65 17192.82 -3.4684 0.0287 0.0008 12.0299 -0.0995

14-Nov-11 1753.05 17118.74 -4.1613 -1.3423 1.8017 17.3166 5.5856

15-Nov-11 1729.9 16882.67 -0.9307 -1.1784 1.3887 0.8662 1.0968

66

16-Nov-11 1764.9 16775.87 1.9973 -0.5748 0.3304 3.9891 -1.1481

17-Nov-11 1757.5 16461.71 -0.3528 -1.7797 3.1674 0.1244 0.6278

18-Nov-11 1725.5 16371.51 -1.7096 -0.0989 0.0098 2.9229 0.1691

21-Nov-11 1673.05 15946.1 -3.0394 -2.2007 4.8432 9.2377 6.6888

22-Nov-11 1688.65 16065.42 0.5122 0.4340 0.1884 0.2624 0.2223

23-Nov-11 1654.3 15699.97 -0.9490 -1.7174 2.9494 0.9007 1.6299

24-Nov-11 1653.25 15858.49 -0.2268 0.8997 0.8095 0.0515 -0.2041

25-Nov-11 1690.7 15695.43 2.5374 -0.5468 0.2990 6.4385 -1.3874

28-Nov-11 1776.9 16167.13 2.9208 1.7092 2.9214 8.5312 4.9923

29-Nov-11 1756.5 16008.34 -1.6225 -1.2620 1.5927 2.6327 2.0477

30-Nov-11 1762.85 16123.46 0.8424 1.5784 2.4915 0.7096 1.3297

01-Dec-11 1819.25 16483.45 0.3985 -0.4397 0.1933 0.1588 -0.1752

02-Dec-11 1886.5 16846.83 3.4190 2.0945 4.3868 11.6898 7.1610

05-Dec-11 1908.6 16805.33 1.3937 -0.0415 0.0017 1.9424 -0.0578

07-Dec-11 1936.7 16877.06 1.2754 0.2786 0.0776 1.6266 0.3553

08-Dec-11 1865.85 16488.24 -3.8133 -2.0105 4.0422 14.5411 7.6667

09-Dec-11 1863.95 16213.46 1.8268 -0.2774 0.0770 3.3371 -0.5068

12-Dec-11 1773.1 15870.35 -6.0854 -3.0536 9.3242 37.0319 18.5821

13-Dec-11 1787.2 16002.51 1.5779 1.3991 1.9575 2.4897 2.2076

14-Dec-11 1784.65 15881.14 0.0364 -0.5202 0.2706 0.0013 -0.0189

15-Dec-11 1744.5 15836.47 -0.6019 0.6152 0.3784 0.3623 -0.3703

16-Dec-11 1680.45 15491.35 -4.3709 -2.4364 5.9360 19.1044 10.6491

19-Dec-11 1631.55 15175.08 -2.2892 -0.3951 0.1561 5.2406 0.9044

20-Dec-11 1582.8 15685.21 -3.1084 -1.7202 2.9590 9.6622 5.3471

21-Dec-11 1623.1 15813.36 0.0062 1.2589 1.5848 0.0000 0.0078

22-Dec-11 1668.45 15738.7 3.2635 1.6865 2.8444 10.6505 5.5041

23-Dec-11 1648.35 15970.75 -1.7381 -0.7925 0.6281 3.0210 1.3775

26-Dec-11 1664.65 15873.95 1.3606 1.1808 1.3942 1.8514 1.6066

27-Dec-11 1642.9 15727.85 -1.5887 -0.6931 0.4805 2.5238 1.1012

28-Dec-11 1609.7 15543.93 -0.9691 -0.8044 0.6470 0.9392 0.7795

29-Dec-11 1627.05 15454.92 1.7854 -0.7399 0.5475 3.1878 -1.3211

30-Dec-11 1619.5 16483.45 -1.1670 -0.8323 0.6927 1.3620 0.9713

    SUM -31.4604 -14.1822 85.0865 376.0958 114.8265

               BETA S.D VARIAN

CECORRELATION    

1.313894344 2.234576313 4.9933 0.6264    

67

Interpretation of SBI

Beta of State Bank of India is 1.313894344 which means the State Bank of India

beta is more than 1 means it tends to be more volatile than the market BSE

Sensex.

So it is a more risky for investment.standard deviation of State Bank of India Is

2.234576313and correlation is 0.626401482 is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.13

Volatility of Ranbaxy Laboratories | Healthcare

  STOCK

PRICE

SENSEX PRICE

Stock Return

Sensex Return

   Date close close Y X X^2 Y^2 X*Y

03-Oct-11 513.35 16151.45 0.8474 -0.6471 0.4188 0.7180 -0.548404-Oct-11 516.25 15864.86 0.6295 -1.3672 1.8693 0.3963 -0.860705-Oct-11 519.5 15792.41 -0.8085 -1.1101 1.2323 0.6536 0.897507-Oct-11 517.5 16232.54 -0.8696 0.0619 0.0038 0.7561 -0.053810-Oct-11 516.6 16557.23 -0.2323 1.7343 3.0080 0.0540 -0.402911-Oct-11 516.2 16536.47 -0.3487 -0.7963 0.6341 0.1216 0.277712-Oct-11 516.55 16958.39 -0.6679 1.7570 3.0871 0.4461 -1.173513-Oct-11 502.35 16883.92 -2.5779 -0.9718 0.9444 6.6455 2.505214-Oct-11 502.5 17082.69 0.9950 1.4392 2.0714 0.9901 1.432117-Oct-11 497.85 17025.09 -1.4362 -0.8867 0.7862 2.0626 1.273418-Oct-11 501.4 16748.29 1.4759 -0.4125 0.1702 2.1782 -0.608819-Oct-11 514.45 17085.34 1.8369 1.1822 1.3976 3.3743 2.171620-Oct-11 501.4 16936.89 -1.5257 0.1478 0.0219 2.3278 -0.225621-Oct-11 496.6 16785.64 -1.2888 -1.1328 1.2833 1.6609 1.459924-Oct-11 505.05 16939.28 1.5939 -0.4237 0.1796 2.5405 -0.675425-Oct-11 509.9 17254.86 0.8727 1.4029 1.9682 0.7616 1.224326-Oct-11 516 17288.83 0.7752 -0.2748 0.0755 0.6009 -0.213028-Oct-11 514.4 17804.8 -1.2830 0.7467 0.5575 1.6462 -0.9580

68

31-Oct-11 501.1 17705.01 -2.4546 -0.5716 0.3267 6.0251 1.403001-Nov-11 504.95 17480.83 0.9803 -0.3416 0.1167 0.9610 -0.334902-Nov-11 511.85 17464.85 2.3151 0.6708 0.4499 5.3598 1.552903-Nov-11 513.6 17481.93 0.5062 0.2931 0.0859 0.2563 0.148404-Nov-11 503.6 17562.61 -2.6608 -0.6382 0.4073 7.0801 1.698208-Nov-11 496.8 17569.53 -2.4557 -0.1374 0.0189 6.0305 0.337409-Nov-11 475.4 17362.1 -3.9125 -1.6120 2.5986 15.3076 6.307011-Nov-11 468.1 17192.82 -1.4740 0.0287 0.0008 2.1728 -0.042314-Nov-11 483.9 17118.74 1.6326 -1.3423 1.8017 2.6653 -2.191415-Nov-11 468.5 16882.67 -3.3191 -1.1784 1.3887 11.0164 3.911316-Nov-11 473.05 16775.87 -0.2008 -0.5748 0.3304 0.0403 0.115417-Nov-11 453.25 16461.71 -3.9934 -1.7797 3.1674 15.9471 7.107018-Nov-11 458.4 16371.51 1.8325 -0.0989 0.0098 3.3579 -0.181221-Nov-11 447.4 15946.1 -2.3692 -2.2007 4.8432 5.6133 5.214122-Nov-11 445.9 16065.42 -1.5923 0.4340 0.1884 2.5354 -0.691123-Nov-11 429.4 15699.97 -3.1905 -1.7174 2.9494 10.1793 5.479324-Nov-11 428.95 15858.49 -0.2448 0.8997 0.8095 0.0599 -0.220225-Nov-11 440.6 15695.43 1.2710 -0.5468 0.2990 1.6154 -0.695028-Nov-11 449.4 16167.13 0.9791 1.7092 2.9214 0.9586 1.673529-Nov-11 452.35 16008.34 -1.8901 -1.2620 1.5927 3.5726 2.385430-Nov-11 434.8 16123.46 -4.1858 1.5784 2.4915 17.5212 -6.607101-Dec-11 444.1 16483.45 -6.1247 -0.4397 0.1933 37.5125 2.693102-Dec-11 442.4 16846.83 -0.8024 2.0945 4.3868 0.6439 -1.680705-Dec-11 436.4 16805.33 -1.0541 -0.0415 0.0017 1.1111 0.043707-Dec-11 437.75 16877.06 -0.9595 0.2786 0.0776 0.9205 -0.267308-Dec-11 418.65 16488.24 -4.8609 -2.0105 4.0422 23.6280 9.772909-Dec-11 415.9 16213.46 0.5771 -0.2774 0.0770 0.3330 -0.160112-Dec-11 405.75 15870.35 -3.3272 -3.0536 9.3242 11.0701 10.159713-Dec-11 406.2 16002.51 0.8124 1.3991 1.9575 0.6600 1.136614-Dec-11 400.85 15881.14 -1.2848 -0.5202 0.2706 1.6506 0.668315-Dec-11 383.95 15836.47 -2.8780 0.6152 0.3784 8.2828 -1.770416-Dec-11 380.25 15491.35 -1.5122 -2.4364 5.9360 2.2866 3.684219-Dec-11 383.5 15175.08 1.1604 -0.3951 0.1561 1.3464 -0.458420-Dec-11 395.35 15685.21 2.6306 -1.7202 2.9590 6.9200 -4.525121-Dec-11 406.95 15813.36 1.3392 1.2589 1.5848 1.7935 1.685922-Dec-11 421.55 15738.7 4.4004 1.6865 2.8444 19.3638 7.421523-Dec-11 405.5 15970.75 -3.2182 -0.7925 0.6281 10.3571 2.550526-Dec-11 401.65 15873.95 -1.3320 1.1808 1.3942 1.7742 -1.572827-Dec-11 410.75 15727.85 2.3737 -0.6931 0.4805 5.6345 -1.645328-Dec-11 405 15543.93 -0.3704 -0.8044 0.6470 0.1372 0.297929-Dec-11 403.65 15454.92 -0.3344 -0.7399 0.5475 0.1119 0.247530-Dec-11 405.25 16483.45 -0.8267 -0.8323 0.6927 0.6834 0.6880

69

    SUM-

42.0306-

14.1822 85.0865 282.4315 60.8613BETA S.D VARI

ANCECorrelation    

0.62304 2.0707 4.2879 0.3542    

Interpretation Ranbaxy Laboratories

Beta of Ranbaxy Laboratories is 0.62304 which means the Ranbaxy

Laboratories beta is less than 1 means it tends to be less volatile than the

market BSE Sensex.

So it is a less risky for investment. Standard deviation of Ranbaxy Laboratories Is

2.070734721 and correlation is 0.354153414is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.14

Volatility of TCS | Information Technology

  stock STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date open close close Y X X^2 Y^2 X*Y

03-Oct-11 1024.95 1044 16151.45 1.824713 -0.64712 0.41877 3.329576 -1.18082

04-Oct-11 1036 1045.95 15864.86 0.951288 -1.36724 1.869333 0.904949 -1.30064

05-Oct-11 1052.25 1043.5 15792.41 -0.83852 -1.11009 1.2323 0.703123 0.930838

07-Oct-11 1070 1048.7 16232.54 -2.03109 0.061913 0.003833 4.125311 -0.12575

10-Oct-11 1048.3 1065.3 16557.23 1.595795 1.734348 3.007963 2.54656 2.767663

11-Oct-11 1071.05 1041.2 16536.47 -2.86688 -0.7963 0.634095 8.219026 2.282902

12-Oct-11 1064 1079.35 16958.39 1.422152 1.757006 3.087072 2.022517 2.498731

13-Oct-11 1095 1090.8 16883.92 -0.38504 -0.97181 0.944419 0.148255 0.374185

14-Oct-11 1088.6 1134.5 17082.69 4.045835 1.439235 2.071396 16.36878 5.822906

17-Oct-11 1150 1119.8 17025.09 -2.69691 -0.88669 0.786222 7.273324 2.391327

18-Oct-11 1062 1033.5 16748.29 -2.75762 -0.41252 0.170173 7.604467 1.137573

19-Oct-11 1043.5 1048.7 17085.34 0.495852 1.182183 1.397557 0.245869 0.586188

20-Oct-11 1036 1044.7 16936.89 0.832775 0.147843 0.021858 0.693514 0.12312

21-Oct-11 1052 1048.25 16785.64 -0.35774 -1.13281 1.283266 0.127977 0.405252

24-Oct-11 1057 1079.35 16939.28 2.070691 -0.42375 0.179563 4.28776 -0.87745

70

25-Oct-11 1086.1 1099.3 17254.86 1.200764 1.402909 1.968154 1.441834 1.684563

26-Oct-11 1101 1095.55 17288.83 -0.49747 -0.2748 0.075516 0.247473 0.136705

28-Oct-11 1116.5 1119.65 17804.8 0.281338 0.746653 0.55749 0.079151 0.210062

31-Oct-11 1118 1114.2 17705.01 -0.34105 -0.57159 0.326715 0.116316 0.194942

01-Nov-11 1100 1107.5 17480.83 0.677201 -0.34163 0.116712 0.458601 -0.23135

02-Nov-11 1095.05 1106.3 17464.85 1.016903 0.670776 0.44994 1.034092 0.682114

03-Nov-11 1100 1103.45 17481.93 0.312656 0.293103 0.085909 0.097754 0.09164

04-Nov-11 1117.2 1099.1 17562.61 -1.6468 -0.63823 0.407339 2.711957 1.05104

08-Nov-11 1100.95 1103.5 17569.53 0.231083 -0.1374 0.018878 0.053399 -0.03175

09-Nov-11 1111 1123 17362.1 1.068566 -1.61202 2.598599 1.141834 -1.72255

11-Nov-11 1102 1130.8 17192.82 2.546869 0.028675 0.000822 6.486544 0.073031

14-Nov-11 1136 1126.5 17118.74 -0.84332 -1.34227 1.801693 0.711189 1.131965

15-Nov-11 1127.8 1122.95 16882.67 -0.4319 -1.17843 1.388691 0.186536 0.508961

16-Nov-11 1122.2 1116.2 16775.87 -0.53754 -0.57481 0.330411 0.288947 0.308984

17-Nov-11 1114.7 1113 16461.71 -0.15274 -1.77971 3.167353 0.02333 0.271833

18-Nov-11 1109.95 1088.05 16371.51 -2.01278 -0.09889 0.009779 4.051264 0.199046

21-Nov-11 1085 1064.95 15946.1 -1.88272 -2.20073 4.843196 3.544625 4.143346

22-Nov-11 1068 1084.55 16065.42 1.525979 0.434038 0.188389 2.32861 0.662332

23-Nov-11 1083 1062.4 15699.97 -1.93901 -1.71739 2.949435 3.759744 3.330033

24-Nov-11 1069.75 1089.25 15858.49 1.790223 0.899707 0.809473 3.204897 1.610676

25-Nov-11 1088.4 1062.95 15695.43 -2.39428 -0.54678 0.298972 5.732577 1.309153

28-Nov-11 1074 1089.15 16167.13 1.390993 1.709209 2.921395 1.934861 2.377497

29-Nov-11 1094.4 1090.7 16008.34 -0.33923 -1.26203 1.592719 0.115078 0.42812

30-Nov-11 1089 1113.1 16123.46 2.165124 1.578445 2.49149 4.687764 3.417531

01-Dec-11 1135 1134.75 16483.45 -0.02203 -0.43971 0.193348 0.000485 0.009687

02-Dec-11 1130 1175.5 16846.83 3.870693 2.094459 4.38676 14.98227 8.10701

05-Dec-11 1172 1179.55 16805.33 0.640075 -0.04147 0.00172 0.409695 -0.02655

07-Dec-11 1177.2 1179.1 16877.06 0.16114 0.278603 0.07762 0.025966 0.044894

08-Dec-11 1166.3 1177.3 16488.24 0.934341 -2.01052 4.042206 0.872994 -1.87852

09-Dec-11 1170.95 1171.7 16213.46 0.06401 -0.27742 0.076964 0.004097 -0.01776

12-Dec-11 1174.2 1179.9 15870.35 0.483092 -3.05356 9.324203 0.233378 -1.47515

13-Dec-11 1169 1179.7 16002.51 0.90701 1.399093 1.957461 0.822668 1.268992

14-Dec-11 1179 1179.8 15881.14 0.067808 -0.52018 0.270584 0.004598 -0.03527

15-Dec-11 1170 1182.6 15836.47 1.065449 0.615162 0.378425 1.135182 0.655424

16-Dec-11 1180.5 1143.5 15491.35 -3.23568 -2.43639 5.936006 10.46962 7.883384

19-Dec-11 1143.5 1142.55 15175.08 -0.08315 -0.39508 0.156085 0.006913 0.032849

20-Dec-11 1141 1133.1 15685.21 -0.6972 -1.72019 2.959049 0.486091 1.19932

21-Dec-11 1149 1159.9 15813.36 0.939736 1.258893 1.584811 0.883104 1.183027

22-Dec-11 1148 1149 15738.7 0.087032 1.686549 2.844446 0.007575 0.146784

23-Dec-11 1150 1156.3 15970.75 0.544841 -0.79251 0.628064 0.296852 -0.43179

26-Dec-11 1152.3 1187.9 15873.95 2.996885 1.180784 1.39425 8.981321 3.538673

27-Dec-11 1186 1176.75 15727.85 -0.78606 -0.69315 0.480454 0.617896 0.544858

28-Dec-11 1169.9 1169.15 15543.93 -0.06415 -0.80437 0.64701 0.004115 0.0516

71

29-Dec-11 1161.1 1165.35 15454.92 0.364697 -0.7399 0.547456 0.133004 -0.26984

30-Dec-11 1175 1161.25 16483.45 -1.18407 -0.83229 0.692709 1.402019 0.985491

      SUM 9.548638 -14.1822 85.08652 144.8192 59.19107BETA S.D VARIAN

CECorrelati

on    0.751803 0 0 0.567785    

Interpretation of TCS

Beta of TCS is 0.751803 which means the TCS beta is less than 1 means it

tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment. Standard deviation of TCS Is

1.545421337and correlation is 0.567784783  is Positive correlation so that It

means that when market return increases, the company’s return also increases.

Table No. 1.15

Volatility of ONGC | Oil and Gas

  STOCK PRICE

SENSEX PRICE

Stock Return

Sensex Return

Date close close Y X X^2 Y^2 X*Y

03-Oct-11 268.55 16151.45 1.9736 -0.6471 0.4188 3.8949 -1.2771

04-Oct-11 264.4 15864.86 -1.2670 -1.3672 1.8693 1.6053 1.7323

05-Oct-11 264.2 15792.41 0.3028 -1.1101 1.2323 0.0917 -0.3361

07-Oct-11 264.45 16232.54 -1.3424 0.0619 0.0038 1.8021 -0.0831

10-Oct-11 273.5 16557.23 3.4735 1.7343 3.0080 12.0651 6.0242

11-Oct-11 268.35 16536.47 -0.9875 -0.7963 0.6341 0.9752 0.7864

12-Oct-11 270.5 16958.39 0.5545 1.7570 3.0871 0.3075 0.9743

13-Oct-11 265 16883.92 -3.0566 -0.9718 0.9444 9.3428 2.9704

14-Oct-11 266.65 17082.69 0.6188 1.4392 2.0714 0.3829 0.8906

17-Oct-11 269.5 17025.09 0.5566 -0.8867 0.7862 0.3098 -0.4935

18-Oct-11 263.6 16748.29 -1.8778 -0.4125 0.1702 3.5263 0.7746

19-Oct-11 268.35 17085.34 1.5838 1.1822 1.3976 2.5083 1.8723

72

20-Oct-11 266.8 16936.89 -0.0750 0.1478 0.0219 0.0056 -0.0111

21-Oct-11 265.4 16785.64 -0.6217 -1.1328 1.2833 0.3865 0.7043

24-Oct-11 276.25 16939.28 2.4796 -0.4237 0.1796 6.1486 -1.0507

25-Oct-11 276.7 17254.86 0.1626 1.4029 1.9682 0.0264 0.2282

26-Oct-11 276.2 17288.83 -0.2896 -0.2748 0.0755 0.0839 0.0796

28-Oct-11 284.6 17804.8 1.6163 0.7467 0.5575 2.6124 1.2068

31-Oct-11 278.2 17705.01 -2.8037 -0.5716 0.3267 7.8609 1.6026

01-Nov-11 277.95 17480.83 0.7016 -0.3416 0.1167 0.4922 -0.2397

02-Nov-11 278.25 17464.85 0.4852 0.6708 0.4499 0.2354 0.3254

03-Nov-11 277.95 17481.93 0.0899 0.2931 0.0859 0.0081 0.0264

04-Nov-11 277.65 17562.61 -1.2966 -0.6382 0.4073 1.6812 0.8275

08-Nov-11 278 17569.53 -3.0576 -0.1374 0.0189 9.3486 0.4201

09-Nov-11 271.25 17362.1 -3.0415 -1.6120 2.5986 9.2506 4.9029

11-Nov-11 265.8 17192.82 -2.3326 0.0287 0.0008 5.4409 -0.0669

14-Nov-11 261.2 17118.74 -1.9142 -1.3423 1.8017 3.6643 2.5694

15-Nov-11 258.8 16882.67 -1.2365 -1.1784 1.3887 1.5289 1.4571

16-Nov-11 263.3 16775.87 1.2533 -0.5748 0.3304 1.5708 -0.7204

17-Nov-11 257.35 16461.71 -2.5840 -1.7797 3.1674 6.6772 4.5988

18-Nov-11 259.25 16371.51 0.5786 -0.0989 0.0098 0.3348 -0.0572

21-Nov-11 252.25 15946.1 -3.6472 -2.2007 4.8432 13.3019 8.0264

22-Nov-11 251.85 16065.42 -0.4566 0.4340 0.1884 0.2085 -0.1982

23-Nov-11 246.3 15699.97 -2.3143 -1.7174 2.9494 5.3558 3.9745

24-Nov-11 253.45 15858.49 2.5449 0.8997 0.8095 6.4764 2.2896

25-Nov-11 251.85 15695.43 -1.1713 -0.5468 0.2990 1.3720 0.6405

28-Nov-11 261.65 16167.13 2.2358 1.7092 2.9214 4.9989 3.8215

29-Nov-11 257.9 16008.34 -1.5898 -1.2620 1.5927 2.5273 2.0063

30-Nov-11 265.8 16123.46 3.6870 1.5784 2.4915 13.5938 5.8197

01-Dec-11 266.05 16483.45 -1.9733 -0.4397 0.1933 3.8940 0.8677

02-Dec-11 268.05 16846.83 0.3731 2.0945 4.3868 0.1392 0.7814

05-Dec-11 268.6 16805.33 -0.1489 -0.0415 0.0017 0.0222 0.0062

07-Dec-11 273 16877.06 1.8315 0.2786 0.0776 3.3544 0.5103

08-Dec-11 266.8 16488.24 -1.9490 -2.0105 4.0422 3.7987 3.9186

09-Dec-11 261.7 16213.46 -0.8407 -0.2774 0.0770 0.7067 0.2332

12-Dec-11 257.45 15870.35 -2.5053 -3.0536 9.3242 6.2767 7.6502

13-Dec-11 255.35 16002.51 -0.6462 1.3991 1.9575 0.4175 -0.9041

14-Dec-11 252 15881.14 -1.0714 -0.5202 0.2706 1.1480 0.5573

15-Dec-11 251.25 15836.47 0.4975 0.6152 0.3784 0.2475 0.3061

16-Dec-11 250.1 15491.35 -1.4794 -2.4364 5.9360 2.1886 3.6044

19-Dec-11 247.3 15175.08 -1.6983 -0.3951 0.1561 2.8844 0.6710

20-Dec-11 253.2 15685.21 1.2441 -1.7202 2.9590 1.5477 -2.1400

21-Dec-11 260.65 15813.36 1.5922 1.2589 1.5848 2.5350 2.0044

22-Dec-11 264.75 15738.7 2.5496 1.6865 2.8444 6.5003 4.3000

23-Dec-11 261.55 15970.75 -1.7014 -0.7925 0.6281 2.8947 1.3484

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26-Dec-11 262.25 15873.95 0.4766 1.1808 1.3942 0.2272 0.5628

27-Dec-11 263.55 15727.85 0.3984 -0.6931 0.4805 0.1587 -0.2762

28-Dec-11 260.55 15543.93 -0.5565 -0.8044 0.6470 0.3097 0.4476

29-Dec-11 258.45 15454.92 -0.9867 -0.7399 0.5475 0.9735 0.7300

30-Dec-11 256.95 16483.45 -0.4281 -0.8323 0.6927 0.1833 0.3563

    Sum -19.0875 -14.1822 85.0865 182.4121 82.5542

BETA S.D VARIANCE

Correlation  

  0.954831914 0.0000 0.0000 0.6501  

Interpretation of ONGC

Beta of ONGC is 0.954831914 which means the ONGC beta is less than 1

means it tends to be less volatile than the market BSE Sensex.

So it is a less risky for investment.standard deviation of ONGC Is 1.728818046

and correlation is 0.650060411is Positive correlation so that It means that when

market return increases, the company’s return also increases

CHEPTER -7

FINDINGS

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Company Name Beta

S.D Correlation

Rank (beta wise)

Bharat Heavy Electricals Ltd. 1.164 2.8 0.4573 10

Larsen & Toubro Limited 1.08671.8427 0.605 9

HDFC Bank 0.87351.2092 0.6497 4

ACC LTD 0.99091.3239 0.6999 6

State Bank of India 1.31392.2346 0.6264 12

Hindustan Unilever Ltd. 1.45752.5084 0.6299 13

Tata Consultancy Services Limited

0.75181.5454 0.5678 2

Hindalco Industries Ltd. 1.57062.6816 0.6405 15

ONGC Ltd. 0.95481.7288 0.65 5

Reliance Industries Ltd. 1.55211.86 0.8578 14

NTPC Ltd. 0.99411.4072 0.6721 7

Mahindra & Mahindra Ltd. 1.18431.8828 0.6483 11

Grasim Industry 0.81851.2128 0.6077 3

Ranbaxy Laboratories 0.6232.0707 0.3542 1

Bharti Airtel 1.026 1.9822 5392 8

Beta of BHEL company is 1.164 which means the BHEL company share price fluctuate more than BSE Sensex because if BHEL beta is greater than 1 than it represent the BHEL share price is more fluctuate compare to market return, if BHEL beta is less than its represent that BHEL share price less fluctuate

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compare to market return, if BHEL beta is equal to 1 than its shows that both are fluctuate in same sense.

The value of correlation could be positive, negative or zero. It always varies between the -1.0 (negative correlation) and +1.0 (positively correlation).so this is Positive correlation so that It means that when market return increases, the company’s return also increases.

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CHEPTER - 8

Conclusion

There are number of factors which have an influence on the price

movements. The volatility is depends on the internal and external factors.

Some of them are controllable and others are non controllable.

In the year 1978, the base year, the Sensex was 100 and now its more

than 17316. it shows that the volatility is very high. When compared with

“Nifty” of NSE. The price volatility is very high in Sensex.

Fluctuation ratio of Sensex: Nifty is nearly 3:1.

The study also shows that most of the companies in the Sensex are less

volatile that Sensex movement.

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CHEPTER-9

SUGGESTION & RECOMMANDATION

The company stock was highly volatile in the last 3 month and the stock

price was moving up and down based on the industry fluctuation. To keep

it as the company must try to improve the financial performance which will

improve the company's performance as a whole.

By applying the statistical analysis it is found that we can buy the

company's stock as a speculator and also as an investor.

• We suggest investors category as per them investment purpose.

• Hedger-: as per price volatility of various securities who's beta is show in

green box those securities are useful to investors for heading them

portfolio.

• Specially beta rank from 1 to 5 are those securities which heading portfolio

risk.

• Securities rank in yellow box which show that securities are move with

market return (Sensex) , it denoted that if market id positive then securities

return is also positive and vice versa market return is negative then

securities return is also negatives.

• Beta rank from 6 to 10 is those securities it may can be use for hedging

portfolio.

• Speculators -: those investors whose main purpose is to take high risk

and gain short term profit.

• as per price volatility of various securities who's beta is show in RED box

those securities are useful to investors for speculate them portfolio.

• specially beta rank from 11 to 15 are those securities which speculating

portfolio .

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Limitations of the study

The most important limitation of this study is that it considers only Sensex

companies listed in Bombay Stock Exchange.

Only three months duration has been taken for the study.

The indices taken as benchmark have their own limitations. The BSE sensex

consist of 30 scripts. So it does not truly reflect as a whole. Hence there is a

limitation that the true returns from the market is not reflected indices

Generalization of findings and conclusions of the study are likely to be

disputed as security prices are determined by so many factors. However the

findings and conclusions drawn upon the secondary data collected is

expected to through some new light on volatility of share prices during public

issues.

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BIBILOGRAPHY

Book refer :-

1. Reilly/Brown, Investments- Analysis and Portfolio Management, Cengage

Learning Eighth Edition.

2. Fischer and Jordon, Security analysis and Portfolio Management Pearson

Latest Edition.

3. Business statistics

Authors-: ken black

Internet source :-

http://www.financeresearch.net

http://www.finance.indiamart.com

http://www.bseindia.com

http://www.moneycontrol.com

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