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Exchange is professionally managed under the overall direction of the Board of

Directors. The Board comprises eminent professionals, representatives of Trading

Members and the Managing Directors of the Exchange.

The Board is inclusive and is designed to benefit from the participation of market

intermediaries. In terns of organization structure, the Board formulates larger policy

issues and exercises over-all control. The committee constituted by the board is broad-

based. The day-to-day operations of the exchange are managed by the Managing Director

& CEO and a Management team of professionals.

The exchange has a nation-wide reach with a presence in 417 cities and towns of

India. The systems and processes of the Exchange are designed to safeguard market

integrity and enhance transparency in operations.

About the national stock exchange of India:

Capital market reforms in India and the launch of the Securities and Exchange

Board of India (SEBI) accelerated the incorporation of the second Indian stock exchange

called the National Stock Exchange (NSE) in 1992. After a few years of operations, the

NSE has become the largest stock exchange in India.

Three segments of the NSE trading platform were established one after another. The

Wholesale Debt Market (WDM) commenced operations in June 1994 and the Capital

Market (CM) segment was opened at the end of 1994. Finally, the Futures and Options

segment began operating in 2000. Today the NSE takes the 14th position in the top 40

futures exchanges in the world.

In 1996, the National Stock Exchange of India launched S&P CNX Nifty and CNX

Junior Indices that make up 100 most liquid stocks in India. CNX Nifty is a diversified

index of 50 stocks from 25 different economy sectors. The Indices are owned andmanaged by India Index Services and Products Ltd (IISL) that has a consulting and

licensing agreement with Standard & Poor's.

In 1998, the National Stock Exchange of India launched its web-site and was the

first exchange in India that started trading stock on the Internet in 2000. The NSE has

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also proved its leadership in the Indian financial market by gaining many awards such as

'Best IT Usage Award' by Computer Society in India (in 1996 and 1997) and CHIP Web

Award by CHIP magazine (1999).

1.2 STATEMENT OF THE PROBLEM

The need for the study is to analyze portfolio management service in various share

price movements of various companies belonging to various sectors of National Stock

Market, which is also funneled down to the NIFTY stocks.

There is always an expectation of the stock holders to get an optimum return for

the risk being beard by the investors in investing in such stocks. The returns are expected

in the form of appreciation of the share values and in the form of dividends declared by

the companies.

There is a need to analyze whether the equity and other instruments issued by the

companies is playing a major role in the price movements of the stocks. The portfolio

management service is having an impact in prices changes of the s tocks market.

1.3 OBJECTIVES OF THE STUDY

Primary objectives

To construct a portfolio on selected scrips in S&P CNX Nifty.

Secondary objectives

To observe the rate of fluctuations of selected scrips.

To determine the share price movement of the selected scrips.

To find out the risk and return of the sample scrips.

To find out suitable portfolio from scrips in Nifty.

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1.4 SCOPE OF THE STUDY

The purpose of the study is to find out whether the company share prices

movements depends on the companys profit and their dividend issues. The research

reveals a general study related to the investment patterns of investors relate to the price

changes. The researches reveal the results regarding the investment details of investors in

various companies during that period. Data are collected from the web sites helped to

find out the impact and causes of price changes.

1.5 LIMITATIONS OF THE STUDY

Though there are many industries listed in the National Stocks

Exchange only 5 sectors and 20 companies have been selected for the

analysis due to lack of time.

An in-depth analysis on the cause of changes in industrys performance

is not being made.

The analysis results can be used for predicting the future results to

some extent.

1.6 CHAPTERIZATION OF THE STUDY

The first chapter is about Introduction which contains Introduction, Statement of

the problem, Objectives of the study, Scope of the study, and Limitations of the study and

Cauterization of the study.

The second chapter is about

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CHAPTER2

Company Profile

India Infoline Limited is listed on both the leading stock exchanges in India, viz. the

Stock Exchange, Mumbai (BSE) and the National Stock Exchange (NSE) and is also a

member of both the exchanges. It is engaged in the businesses of Equities broking,

Wealth Advisory Services and Portfolio Management Services. It offers broking services

in the Cash and Derivatives segments of the NSE as well as the Cash segment of the

BSE. It is registered with NSDL as well as CDSL as a depository participant, providing a

one-stop solution for clients trading in the equities market. It has recently launched itsInvestment banking and Institutional Broking business.

A SEBI authorized Portfolio Manager; it offers Portfolio Management Services to

clients. These services are offered to clients as different schemes, which are based on

differing investment strategies made to reflect the varied risk-return preferences of

clients.

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India infoline media and research services limited:

The content services represent a strong support that drives the broking,commodities, mutual fund and portfolio management services businesses. Revenue

generation is through the sale of content to financial and media houses, Indian as well as

global.

It undertakes equities research which is acknowledged by none other than Forbes as

'Best of the Web' and 'a must read for investors in Asia'. India Infoline's research is

available not just over the internet but also on international wire services like Bloomberg

(Code: IILL), Thomson First Call and Internet Securities where India Infoline is amongst

the most read Indian brokers.

India Infoline Commodities Limited:

India Infoline Commodities Pvt Limited is engaged in the business of commodities

broking. Our experience in securities broking empowered us with the requisite skills and

technologies to allow us offer commodities broking as a contra-cyclical alternative to

equities broking. We enjoy memberships with the MCX and NCDEX, two leading Indian

commodities exchanges, and recently acquired membership of DGCX. We have a multi-

channel delivery model, making it among the select few to offer online as well as offline

trading facilities.

India Infoline Marketing & Services:

India Infoline Marketing and Services Limited is the holding company of India

Infoline Insurance Services Limited and India Infoline Insurance Brokers Limited.

(a) India Infoline Insurance Services Limited is a registered Corporate Agent

with the Insurance Regulatory and Development Authority (IRDA). It is

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the largest Corporate Agent for ICICI Prudential Life Insurance Co

Limited, which is India's largest private Life Insurance Company. India

Infoline was the first corporate agent to get licensed by IRDA in early

2001.

(b) India Infoline Insurance Brokers Limited is a newly formed subsidiary

which will carry out the business of Insurance broking. We have applied

to IRDA for the insurance broking licence and the clearance for the same

is awaited. Post the grant of license, we propose to also commence the

general insurance distribution business.

India Infoline Investment Services Limited:

Consolidated shareholdings of all the subsidiary companies engaged in loans and

financing activities under one subsidiary. Recently, Orient Global, a Singapore-based

investment institution invested USD 76.7 million for a 22.5% stake in India Infoline

Investment Services. This will help focused expansion and capital raising in the said

subsidiaries for various lending businesses like loans against securities, SME financing,

distribution of retail loan products, consumer finance business and housing finance

business. India Infoline Investment Services Private Limited consists of the following

step-down subsidiaries.

(a) India Infoline Distribution Company Limited (distribution of retail loan

products)

(b) Moneyline Credit Limited (consumer finance)

(c) India Infoline Housing Finance Limited (housing finance)

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Equities:

India Infoline provided the prospect of researched investing to its clients, which was

hitherto restricted only to the institutions. Research for the retail investor did not exist

prior to India Infoline. India Infoline leveraged technology to bring the convenience of

trading to the investors location of preference (residence or office) through computerized

access. India Infoline made it possible for clients to view transaction costs and ledger

updates in real time.

Commodities

India Infolines extension into commodities trading reconciles its strategic intent to

emerge as a one stop solutions financial intermediary. Its experience in securities broking

has empowered it with requisite skills and technologies. Increased offering: The

Companies commodities business provides a contra-cyclical alternative to equities

broking. The Company was among the first to offer the facility of commodities trading in

Indias young commodities market (the MCX commenced operations only in 2003).

Average monthly turnover on the commodity exchanges increased from Rs 0.34 bn to Rs

20.02 bn. The commodities market has several products with different and non-correlated

cycles. On the whole, the business is fairly insulated against cyclical gyrations in the

business.

Insurance

An entry into this segment helped complete the client's product basket;

concurrently, it graduated the Company into a one stop retail financial solutions provider.

To ensure maximum reach to customers across India, we have employed a multi pronged

approach and reach out to customers via our Network, Direct and Affiliate channels.

Following the opening of the sector in 1999-2000, a number of private sector insurance

service providers commenced operations aggressively and helped grow the market.

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The Companys entry into the insurance sector derricked the Company from a

predominant dependence on broking and equity-linked revenues. The annuity based

income generated from insurance intermediation result in solid core revenues across the

tenure of the policy.

Invest Online In Mutual Funds & Ipo

India Infoline has made investing in Mutual funds and primary market so effortless.

All you have to do is register with us and thats all. No paperwork no queues and No

registration charges.

If you are 5p customer use your existing login ID and Ledger (fund transfer)

password. Indiainfoline offers you a host of mutual fund and IPO choices under one roof;

backed by in-depth information and research to help you invest effortlessly.

Invest In Mf

Indiainfoline offers you a host of mutual fund choices under one roof, backed by in-

depth research and advice from research house and tools configured as investor friendly.

Investing in Mutual Funds has never been easier.

APPLY IN IPOs

You could also invest in Initial Public Offers (IPOs) online without going through

the hassles of filling ANY application form/ paperwork.

Loans

They say you mustn't trust a man till you know his house. Everyone likes hearing

people say Wow, what a beautiful house you have! From cave dwelling, we have evolved

and now a house provides far more than just shelter...it also becomes a source of pride. A

Housing Loan is used as finance to help you buy or modify that perfect home.

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The different Housing Loan products can be classified as:

Home Loans & Home Extension Loans

NRI Loans Land Loans

Home Equity Loans

Portfolio Management:

You get recessions. You have stock market declines. If you don't understand that's

going to happen, then you're not ready; you won't do well in the markets. No need to

worry. We at India Infoline would take care of all issues related to managing your hard

earned money.

Our Portfolio Management Service is a product wherein an equity investment

portfolio is created to suit the investment objectives of a client. We at India Infoline

invest your resources into stocks from different sectors, depending on your risk-return

profile. This service is particularly advisable for investors who cannot afford to give time

or don't have that expertise for day-to-day management of their equity portfolio.

It is all about your money, being managed by the experts, while you continue with

your routine life. Isn't it simple and totally hassle free.What's more, you can keep track of your dividends / bonus / rights issues with

paperless tracking. So you always know how fast your investment is growing. It basically

means assigning the right job to the right person.

Salient Features of India Infoline PMS:

Expert team of Research Analysts

Stock Picking done by the Investment Committee

Dedicated Relationship Manager

Technology and Service driven Back-Office

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CHAPTER4

4.1 Analysis Of Data

4.1.1 BetaCalculation

Stock Beta is a great gauge to understand market risk in a particular investment.

And it is important to calculate, assess and analyze the beta of any mid to long term hold.

Beta is a calculation of stocks volatility in relation to its index. It can

be used as a measure of risk. If the beta is greater than 1 it is more volatile

than the index. If beta is less than 1 it is less volatile than the index.

Using beta, you can calculate the expected return of your portfolio using Sharpes index

model theory. However beta is based upon historical data. That may have nothing to

do with future price movements of the stock or the market. Beta also doesn't

tell us if the stock's movements were more volatile during bear markets or bull

markets. It doesn't distinguish between large upswing or downside movements.

So while beta provides information about the past risk of a security, it tells

us very little about the attractiveness or the value of the investment.

Beta () =

N = No of Months

X = Change in percentage of Nifty

Y = Change in percentage of Companies

X2 = Square of Change in percentage of Nifty

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SUMMARY OF VALUES OF BETA AND THE RELATIONSHIP TO MARKET

MOVEMENTS:

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TABLE 1: COMPARE WITH NIFTY AND TATA STEEL

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change inpercentage

5

Tatasteel6

Change

inTatasteel

7

Change in

percentage

8=7/6*100

Square of

change inpercentage

9

Percentageon Nifty

and

Tatasteel

4=3/2*100 10=4*8

MAR-APR084839.18

6(99.849) (2.0633) 4.257 718.493 117.296 16.325 266.518 (33.684)

MAY-JUN084739.33

7(478.68) (10.100) 102.012 835.790 (202.558) (24.235) 587.364 244.783

JUL-AUG084260.65

7(540.051) (12.675) 160.663 633.231 (234.076) (36.965) 1366.439 468.547

SEP-OCT08 3720.606

(852.968) (22.925) 525.579 399.155 (205.515) (51.487) 2650.977 1180.380

NOV-DEC082867.63

8(30.403) (1.060) 1.124 193.639 (2.452) (1.266) 1.603 1.342

JAN-FEB092837.23

5221.212 7.796 60.789 191.187 19.657 10.281 105.714 80.164

MAR-APR093058.44

71150.11 37.604 1414.089 210.844 165.739 78.607 6179.156 2955.990

MAY-JUN094208.55

7243.365 5.782 33.438 376.584 52.093 13.833 191.358 79.992

JUL-AUG094451.92

2474.786 10.664 113.736 428.678 75.677 17.653 311.655 188.272

SEP-OCT09

4926.70

8 101.715 2.064 4.262 504.356 47.164 9.351 87.448 19.306

NOV-DEC095028.42

3(34.585) (0.687) 0.473 551.520 43.103 7.815 61.080 (5.375)

JAN-FEB104993.83

8594.624

Total 14.401 2420.426 39.913 11809.318 5179.72

Beta calculation,

BETA =

=

= 2.135046

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Interpretation

From the above table 4.1, we got the beta value of Tatasteel compare with NIFTYvalue as 2.135046. From beta value one can identify that the investment is more volatile

than the market, because beta value is more than one. Based on this, high investment can

be made.

TABLE 2: COMPARE WITH NIFTY AND SBIN

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change inpercentage

5

SBIN 6

Change

in SBIN

7

Change in

percentage

8=7/6*100

Square of

change inpercentage

9

Percen

on Ni

and SB

4=3/2*100 10=4

MAR-APR08 4839.186

(99.849) (2.063) 4.257 1714.716

(253.017) (14.755) 217.728 30.44

MAY-JUN084739.33

7(478.68) (10.100) 102.012

1461.699

(103.807) (7.101) 50.435 71.72

JUL-AUG084260.65

7(540.051) (12.675) 160.663

1357.89

282.541 6.078 36.949 (77.04

SEP-OCT083720.60

6(852.968) (22.925) 525.579

1440.43

3(244.864) (16.999) 288.977 389.7

NOV-DEC082867.63

8(30.403) (1.060) 1.124

1195.569

(57.014) (4.768) 22.741 5.05

JAN-FEB092837.23

5221.212 7.796 60.789

1138.55

5(40.241) (3.534) 12.491 (27.55

MAR-APR093058.44

7 1150.11 37.604 1414.0891098.31

4 545.042 49.625 2462.673 1866.

MAY-JUN094208.55

7243.365 5.782 33.438

1643.35

674.891 4.557 20.768 26.35

JUL-AUG094451.92

2474.786 10.664 113.736

1718.24

7399.312 23.239 540.074 247.8

SEP-OCT094926.70

8101.715 2.064 4.262

2117.559

143.85 6.793 46.147 14.02

NOV-DEC095028.42

3(34.585) (0.687) 0.4730

2261.40

9(210.501) (9.308) 86.646 6.40

JAN-FEB104993.83

8

2050.908

Total 14.401 2420.426 33.825 3785.634 2553.0

BETA =

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=

= 1.044655

Interpretation

From the above table 4.2, we got the beta value of SBIN compare with NIFTY valueas 1.044655. From beta value one can identify that the investment is more volatile than the

market, because beta value is more than one. Based on this, high investment can be made.

TABLE 3: COMPARE WITH NIFTY AND ICICI BANK

Date1

Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage 5

ICICI

BANK

6

Change in

ICICI

BANK7

Change in

percentage

8=7/6*100

Square of

change in

percentage 9

Percenta

On Nift

And

Iciciban

4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 845.321 (35.689) (4.221) 17.825 8.711

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 809.631 (163.255) (20.164) 406.591 203.660JUL-AUG08 4260.657 (540.051) (12.675) 160.663 646.376 (121.674) (18.824) 354.345 238.600

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 524.702 (124.928) (23.809) 566.883 545.840

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 399.774 6.861 1.716 2.945 (1.819)

JAN-FEB09 2837.235 221.212 7.796 60.789 406.635 (42.380) (10.422) 108.622 (81.259

MAR-APR09 3058.447 1150.11 37.604 1414.089 364.255 316.476 86.882 7548.654 3267.18

MAY-JUN09 4208.557 243.365 5.782 33.438 680.731 50.781 7.459 55.648 43.137

JUL-AUG09 4451.922 474.786 10.664 113.736 731.512 126.812 17.335 300.525 184.880

SEP-OCT09 4926.708 101.715 2.064 4.262 858.325 11.440 1.332 1.776 2.751

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 869.765 (29.640) (3.407) 11.613 2.343

JAN-FEB10 4993.838 840.125

Total 14.401 2420.426 33.878 9375.431 4414.02

BETA =

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=

= 1.819506

Interpretation

From the above table 4.3, we got the beta value of ICICIBANK compare with NIFTY

value as 1.819506. From beta value one can identify that the investment is more volatile


be made.

TABLE 4: COMPARE WITH NIFTY AND HDFC BANK

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage5

HDFC

BANK 6

Change in

Hdfc Bankl

7

Change in

percentage

8=7/6*100

Square of

change in

percentage9

Percen

On N

An

Hdfcb

4=3/2*100 10=4

MAR-APR08 4839.186 (99.849) (2.063) 4.257 1367.342 (74.586) (5.454) 29.755 11.2

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 1292.756 (167.073) (12.923) 167.024 130.5JUL-AUG08 4260.657 (540.051) (12.675) 160.663 1125.683 51.328 4.559 20.791 (57.7

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 1177.011 (212.264) (18.034) 325.233 413.4

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 964.746 (35.555) (3.685) 13.582 3.90

JAN-FEB09 2837.235 221.212 7.796 60.789 929.191 35.571 3.828 14.655 29.8

MAR-APR09 3058.447 1150.11 37.604 1414.089 964.762 421.385 43.677 1907.740 1642.

MAY-JUN09 4208.557 243.365 5.7826 33.438 1386.148 52.161 3.763 14.160 21.7

JUL-AUG09 4451.922 474.786 10.664 113.736 1438.309 156.7 10.894 118.695 116.1

SEP-OCT09 4926.708 101.715 2.064 4.262 1595.009 133.531 8.371 70.087 17.2

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 1728.54 (66.118) (3.825) 14.631 2.63

JAN-FEB10 4993.838 1662.422

Total 14.401 2420.426 31.172 2696.355 2331.

BETA =

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=

= 0.953841

Interpretation

From the above table 4.4, we got the beta value of HDFCBANK compare with

NIFTY value as 0.953841. From beta value one can identify that the investment is lessvolatile than the market, because beta value is less than one.

TABLE 5: COMPARE WITH NIFTY AND RELIANCE CAPITAL

BETA =

Page 18 of77

Date1 Nifty2Changein Nifty

3

Change in

percentage

Square of

change in

percentage

5

RELCAPI

TAL 6

Change inRelcapital

7

Change inpercentage

8=7/6*100

Square of

change in

percentage

9

Percen

On Ni

And

Relcap

4=3/2*100 10=4

MAR-APR08 4839.186 (99.849) (2.063) 4.257 1325.996 (120.698) (9.102) 82.854 18.78

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 1205.298 11.662 0.967 0.936 (9.77

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 1216.96 (209.706) (17.231) 296.940 218.4

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 1007.254 (476.501) (47.306) 2237.949 1084.5

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 530.752 (109.344) (20.601) 424.436 21.84

JAN-FEB09 2837.235 221.212 7.796 60.789 421.407 (18.745) (4.448) 19.787 (34.68

MAR-APR09 3058.447 1150.11 37.604 1414.089 402.662 441.886 109.741 12043.145 4126.7

MAY-JUN09 4208.557 243.365 5.7826 33.438 844.548 2.896 0.342 0.1176 1.98

JUL-AUG09 4451.922 474.786 10.664 113.736 847.445 48.017 5.666 32.104 60.42

SEP-OCT09 4926.708 101.715 2.064 4.262 895.462 (59.761) (6.673) 44.539 (13.77

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 835.701 (21.649) (2.590) 6.711 1.78

JAN-FEB10 4993.838 814.051

Total 14.401 2420.426 8.762 15189.523 5476.2


19/77

=

= 2.275518

Interpretation

From the above table 4.5, we got the beta value of RELCAPITAL compare with

NIFTY value as 2.275518. From beta value one can identify that the investment is more

volatile than the market, because beta value is more than one. Based on this, high

investment can be made.

TABLE 6: COMPARE WITH NIFTY AND IDFC

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square ofchange in

percentage

5

IDFC 6

Change

in IDFC

7

Change in

percentage

8=7/6*100

Square ofchange in

percentage

9

percentage

on nifty

and IDFC

4=3/2*100 10=4*8

MAR-APR084839.18

6(99.849) (2.063) 4.257

159.413(15.071) (9.454) 89.387 19.507

MAY-JUN084739.33

7(478.68) (10.100) 102.012

144.341(44.807) (31.042) 963.662 313.537

JUL-AUG084260.65

7(540.051) (12.675) 160.663

99.533(28.620) (28.754) 826.814 364.470

SEP-OCT08 3720.606

(852.968) (22.925) 525.579 70.913 (8.989) (12.676) 160.685 290.607

NOV-DEC082867.63

8(30.403) (1.060) 1.1240

61.924(4.162) (6.722) 45.190 7.127

JAN-FEB092837.23

5221.212 7.796 60.789

57.7611.956 3.386 11.467 26.402

MAR-APR093058.44

71150.11 37.604 1414.089

59.71760.858 101.910 10385.851 3832.299

MAY-JUN094208.55

7243.365 5.782 33.438

120.57613.238 10.979 120.548 63.490

JUL-AUG094451.92

2474.786 10.664 113.736

133.81414.015 10.473 109.695 111.698

SEP-OCT09

4926.70

8 101.715 2.064 4.262

147.83

14.798 10.010 100.203 20.666

NOV-DEC095028.42

3(34.585) (0.687) 0.473

162.628(9.258) (5.693) 32.412 3.915

JAN-FEB104993.83

8

153.369

Total 14.401 2420.426 42.417 12845.919 5053.723

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BETA =

=

= 2.081216

Interpretation

From the above table 4.6, we got the beta value of IDFC compare with NIFTY value

as 2.081216. From beta value one can identify that the investment is more volatile than the


TABLE 7: COMPARE WITH NIFTY AND INFOSYSTCH

Date

1

Nifty

2

Change

in Nifty

3

Change inpercentage

Square of

change in

percentage

5

INFOSYS

TCH 6

Change

in

Infosys

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percentag

on Niftyand Infos

4=3/2*100 10=4*8

MAR-APR084839.18

6(99.849) (2.063) 4.257 1498.262 353.973 23.625 558.167 (48.747

MAY-JUN084739.33

7(478.68) (10.100) 102.012 1852.235 (190.119) (10.264) 105.355 103.671

JUL-AUG084260.65

7(540.051) (12.675) 160.663 1662.116 (195.649) (11.771) 138.558 149.202

SEP-OCT083720.60

6(852.968) (22.925) 525.579 1466.467 (273.018) (18.617) 346.607 426.813

NOV-DEC082867.63

8

(30.403) (1.060) 1.124 1193.449 42.436 3.555 12.643 (3.769)

JAN-FEB092837.23

5221.212 7.796 60.789 1235.885 102.027 8.255 68.151 64.365

MAR-APR093058.44

71150.11 37.604 1414.089 1337.912 321.075 23.998 575.914 902.437

MAY-JUN094208.55

7243.365 5.782 33.438 1658.987 303.606 18.301 334.915 105.825

JUL-AUG094451.92

2474.786 10.664 113.736 1962.593 289.14 14.732 217.048 157.118

Page 20 of77


21/77

SEP-OCT094926.70

8101.715 2.064 4.262 2251.733 163.008 7.239 52.406 14.945

NOV-DEC095028.42

3(34.585) (0.687) 0.473 2414.741 125.342 5.191 26.943 (3.570)

JAN-FEB104993.83

82540.083

Total 14.401 2420.426 64.245 2436.711 1868.29

BETA =

=

= 0.740425

Interpretation

From the above table 4.7, we got the beta value of INFOSYSTCH compare with

NIFTY value as 0.740425. From beta value one can identify that the investment is lessvolatile than the market, because beta value is less than one.

TABLE 8: COMPARE WITH NIFTY AND TCS

Page 21 of77


22/77

BETA =

=

= 0.645238

Interpretation

From the above table 4.8, we got the beta value of TCS compare with NIFTY valueas 0.645238. From beta value one can identify that the investment is less volatile than the

market, because beta value is less than one.

TABLE 9: COMPARE WITH NIFTY AND WIPRO

Page 22 of77

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage

5

TCS

6

Change in

TCS

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percenta

on Nift

and TC

4=3/2*100 10=4*

MAR-APR08 4839.186 (99.849) (2.063) 4.257 872.468 59.358 6.803 46.287 (14.037

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 931.826 (107.035) (11.486) 131.943 116.01

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 824.791 (162.391) (19.688) 387.646 249.56

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 662.4 (152.047) (22.954) 526.886 526.23

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 510.352 (9.194) (1.801) 3.246 1.910

JAN-FEB09 2837.235 221.212 7.796 60.789 501.157 37.331 7.449 55.488 58.078

MAR-APR09 3058.447 1150.11 37.604 1414.089 538.489 64.815 12.036 144.878 452.62

MAY-JUN09 4208.557 243.365 5.782 33.438 603.304 (123.327) (20.441) 417.874 (118.20

JUL-AUG09 4451.922 474.786 10.664 113.736 479.977 111.304 23.189 537.7496 247.30

SEP-OCT09 4926.708 101.715 2.064 4.262 591.281 98.637 16.681 278.286 34.44

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 689.918 61.199 8.871 78.686 (6.101

JAN-FEB10 4993.838 751.117

Total 14.401 2420.426 (1.342) 2608.975 1547.82


23/77

BETA =

=

= 1.390466

Interpretation

From the above table 4.9, we got the beta value of WIPRO compare with NIFTY


than the market, because beta value is more than one. Based on this, high investment canbe made.

TABLE 10: COMPARE WITH NIFTY AND HCL

Page 23 of77


3

Change in

percentage

Square of

change in

percentag

e 5

WIPRO

6

Change inWipro

7

Change inpercentage

8=7/6*100

Square of

change in

percentage

9

Percenta

On Nif

And Wip

4=3/2*100 10=4*MAR-APR08 4839.186 (99.849) (2.063) 4.257 421.982 68.057 16.127 260.111 (33.277

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 490.040 (70.484) (14.383) 206.881 145.27

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 419.555 (76.281) (18.181) 330.565 230.45

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 343.274 (101.535) (29.578) 874.895 678.10

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 241.738 (14.882) (6.156) 37.899 6.526

JAN-FEB09 2837.235 221.212 7.796 60.789 226.856 27.476 12.111 146.691 94.43

MAR-APR09 3058.447 1150.11 37.604 1414.089 254.332 129.996 51.112 2612.509 1922.06

MAY-JUN09 4208.557 243.365 5.782 33.438 384.328 83.375 21.693 470.625 125.44

JUL-AUG09 4451.922 474.786 10.664 113.736 467.704 107.614 23.009 529.415 245.38

SEP-OCT09 4926.708 101.715 2.064 4.262 575.318 68.358 11.881 141.176 24.53

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 643.676 36.079 5.605 31.418 (3.855

JAN-FEB10 4993.838 679.756

Total 14.401 2420.426 73.243 5642.193 3435.08


24/77

BETA =

=

= 1.542903

Interpretation

From the above table 4.10, we got the beta value of HCL compare with NIFTY valueas 1.542903. From beta value one can identify that the investment is more volatile than the


TABLE11: COMPARE WITH NIFTY AND L&T

Page 24 of77

Date1 Nifty2

Change

in Nifty

3

Change inpercentage

Square of

change in

percentage

5

HCLTE

CH 6

Change in

HCLTech 7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percent

on Nifty

HCLTe

4=3/2*100 10=4*

MAR-APR08 4839.186 (99.849) (2.063) 4.257 260.463 29.533 11.338 128.565 (23.39

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 289.996 (65.631) (22.631) 512.195 228.58

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 224.365 (23.896) (10.651) 113.441 135.00SEP-OCT08 3720.606 (852.968) (22.925) 525.579 200.468 (65.745) (32.795) 1075.565 751.86

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 134.723 (21.489) (15.951) 254.437 16.91

JAN-FEB09 2837.235 221.212 7.796 60.789 113.233 (2.469) (2.181) 4.757 (17.00

MAR-APR09 3058.447 1150.11 37.604 1414.089 110.763 62.427 56.360 3176.519 2119.4

MAY-JUN09 4208.557 243.365 5.782 33.438 173.190 64.927 37.489 1405.438 216.78

JUL-AUG09 4451.922 474.786 10.664 113.736 238.118 79.293 33.299 1108.882 355.13

SEP-OCT09 4926.708 101.715 2.064 4.262 317.411 21.649 6.821 46.522 14.08

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 339.061 20.345 6.001 36.006 (4.127

JAN-FEB10 4993.838 359.406

Total 14.401 2420.426 67.098 7862.331 3793.2


25/77

BETA =

=

= 2.18874

Interpretation

From the above table 4.11, we got the beta value of L&T compare with NIFTY value

as 2.18874. From beta value one can identify that the investment is more volatile than themarket, because beta value is more than one. Based on this, high investment can be made.

TABLE 12: COMPARE WITH NIFTY AND DLF

Page 25 of77


3

Change in

percentage

Square of

change in

percentage

5

L&T 6Change in

L&T 7

Change inpercentage

8=7/6*100

Square of

change in

percentage

9

Percent

on Nif

and L&

4=3/2*100 10=4*MAR-APR08 4839.186 (99.849) (2.063) 4.257 2900.214 (148.847) (5.132) 26.340 10.58

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 2751.367 (179.13) (6.510) 42.387 65.75

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 2572.237 (809.633) (31.475) 990.728 398.96

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 1762.604 (977.382) (55.451) 3074.817 1271.2

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 785.221 (96.646) (12.308) 151.490 13.04

JAN-FEB09 2837.235 221.212 7.796 60.789 688.575 24.832 3.606 13.005 28.11

MAR-APR09 3058.447 1150.11 37.604 1414.089 713.408 624.116 87.483 7653.424 3289.7

MAY-JUN09 4208.557 243.365 5.782 33.438 1337.525 145.343 10.866 118.082 62.83

JUL-AUG09 4451.922 474.786 10.664 113.736 1482.868 144.826 9.766 95.386 104.15

SEP-OCT09 4926.708 101.715 2.064 4.262 1627.694 8.551 0.525 0.275 1.084

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 1636.245 (104.644) (6.395) 40.901 4.398

JAN-FEB10 4993.838 1531.601

Total 14.401 2420.426 (5.025) 12206.84 5249.9


26/77


3

Change in

percentage

Square of

change in

percentage

5

DLF 6Change in

DLF

7

Change inpercentage

8=7/6*100

Square of

change in

percentage

9

Percenta

on Niftyand DL

4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 653.135 (94.498) (14.468) 209.337 29.853

MAY-JUN08 4739.337 (478.68) (10.100) 102.013 558.636 (77.311) (13.839) 191.524 139.778

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 481.325 (119.725) (24.874) 618.722 315.287

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 361.6 (113.089) (31.274) 978.113 716.990

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 248.510 (67.142) (27.017) 729.969 28.644

JAN-FEB09 2837.235 221.212 7.796 60.789 181.367 9.480 5.227 27.324 40.756

MAR-APR09 3058.447 1150.11 37.604 1414.089 190.848 140.437 73.585 5414.841 2767.14

MAY-JUN09 4208.557 243.365 5.782 33.438 331.285 31.413 9.482 89.912 54.832

JUL-AUG09 4451.922 474.786 10.664 113.736 362.698 61.308 16.903 285.726 180.271

SEP-OCT09 4926.708 101.715 2.064 4.262 424.007 (52.911) (12.478) 155.721 (25.763

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 371.096 (34.548) (9.309) 86.675 6.403

JAN-FEB10 4993.838 336.547

Total 14.401 2420.426 (28.065) 8787.869 4254.19

BETA =

=

= 1.78672

Interpretation

From the above table 4.12, we got the beta value of DLF compare with NIFTY value

as 1.78672. From beta value one can identify that the investment is more volatile than themarket, because beta value is more than one. Based on this, high investment can be made.

TABLE 13: COMPARE WITH NIFTY AND UNITECH

Page 26 of77


27/77

BETA =

=

= 2.803783

Interpretation

From the above table 4.13, we got the beta value of UNITECH compare with NIFTY



TABLE 14: COMPARE WITH NIFTY AND JINDAL STEL

Page 27 of77

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage

5

UNITECH

6

Change

in

Unitech

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

PercentaOn Nift

And

Unitech4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 280.707 (46.327) (16.503) 272.374 34.052

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 234.380 (69.495) (29.651) 879.167 299.477

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 164.884 (55.399) (33.598) 1128.885 425.875

SEP-OCT08 3720.606 (852.968) (22.9250 525.579 109.485 (71.039) (64.884) 4210.021 1487.51

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 38.446 (6.484) (16.866) 284.486 17.882

JAN-FEB09 2837.235 221.212 7.796 60.789 31.961 3.941 12.330 152.052 96.141

MAR-APR09 3058.447 1150.11 37.604 1414.089 35.902 38.669 107.707 11600.917 4050.27

MAY-JUN09 4208.557 243.365 5.782 33.438 74.572 10.513 14.098 198.772 81.527

JUL-AUG09 4451.922 474.786 10.664 113.736 85.086 18.519 21.766 473.761 232.129

SEP-OCT09 4926.708 101.715 2.064 4.262 103.606 (19.642) (18.959) 359.449 (39.142

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 83.963 (6.559) (7.812) 61.033 5.373

JAN-FEB10 4993.838 77.403

Total 14.401 2420.426 (32.373) 19620.922 6691.10


28/77

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change inpercentage

5

JINDAL

STEL

6

Change in

Jindalstel

7

Change in

percentage

8=7/6*100

Square of

change inpercentage

9

PercentaOn Nifty

And

Jindalste

4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 2038.058 137.616 6.752 45.593 (13.932

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 2175.674 (266.743) (12.260) 150.313 123.830

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 1908.931 (704.103) (36.884) 1360.479 467.524

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 1204.828 (392.247) (32.556) 1059.911 746.369

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 812.5808 144.792 17.818 317.510 (18.891

JAN-FEB09 2837.235 221.212 7.796 60.789 957.3731 305.335 31.893 1017.169 248.662

MAR-APR09 3058.447 1150.11 37.604 1414.089 1262.709 869.414 68.853 4740.746 2589.17

MAY-JUN09 4208.557 243.365 5.782 33.438 2132.123 720.737 33.803 1142.691 195.474

JUL-AUG09 4451.922 474.786 10.664 113.736 2852.86 (1603.847) (56.218) 3160.566 (599.560

SEP-OCT09 4926.708 101.715 2.064 4.262 1249.013 (546.571) (43.760) 1914.961 (90.345

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 702.441 (48.156) (6.855) 46.999 4.715

JAN-FEB10 4993.838 654.284

Total 14.401 2420.426 (29.415) 14956.944 3653.02

BETA =

=

= 1.537131

Interpretation

From the above table 4.14, we got the beta value of JINDAL STEEL compare with


volatile than the market, because beta value is more than one. Based on this, high

investment can be made.

TABLE 15: COMPARE WITH NIFTY AND STER

Page 28 of77


29/77

BETA =

=

= 1.932968

Interpretation

From the above table 4.15, we got the beta value of STER compare with NIFTY



TABLE 16: COMPARE WITH NIFTY AND SAIL

Page 29 of77

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square ofchange in

percentage

5

STER 6Change in

Sterlite 7

Change in

percentage

8=7/6*100

Square ofchange in

percentage

9

Percenta

On Nift

And Sterl

4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 773.061 61.041 7.895 62.346 (16.292MAY-JUN08 4739.337 (478.68) (10.100) 102.012 834.102 (209.111) (25.070) 628.5111 253.21

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 624.991 (223.439) (35.751) 1278.118 453.15

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 401.552 (148.857) (37.071) 1374.222 849.860

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 252.694 12.674 5.015 25.156 (5.317)

JAN-FEB09 2837.235 221.212 7.796 60.789 265.369 76.502 28.828 831.091 224.769

MAR-APR09 3058.447 1150.11 37.604 1414.089 341.871 240.178 70.253 4935.621 2641.85

MAY-JUN09 4208.557 243.365 5.782 33.438 582.05 47.353 8.135 66.188 47.045

JUL-AUG09 4451.922 474.786 10.664 113.736 629.403 139.476 22.160 491.071 236.332

SEP-OCT09 4926.708 101.715 2.064 4.262 768.88 72.274 9.400 88.360 19.406

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 841.154 (36.088) (4.290) 18.406 2.951JAN-FEB10 4993.838 805.066

Total 14.401 2420.426 49.508 9799.095 4706.97


30/77


3

Change in

percentage

Square of

change in

percentage

5

SAIL 6Changein SAIL

7

Change inpercentage

8=7/6*100

Square of

change in

percentage

9

Percentage

on Niftyand SAIL

4=3/2*100 10=4*8

MAR-APR084839.18

6(99.849) (2.063) 4.257 188.381 (24.519) (13.015) 169.411 26.856

MAY-JUN08 4739.337

(478.68) (10.100) 102.012 163.862 (23.823) (14.538) 211.380 146.845

JUL-AUG084260.65

7(540.051) (12.675) 160.663 140.038 (18.156) (12.965) 168.104 164.341

SEP-OCT083720.60

6(852.968) (22.925) 525.579 121.881 (47.091) (38.637) 1492.851 885.782

NOV-DEC082867.63

8(30.403) (1.060) 1.124 74.7897 6.115 8.176 66.859 (8.669)

JAN-FEB092837.23

5221.212 7.796 60.789 80.905 15.417 19.056 363.157 148.580

MAR-APR093058.44

71150.11 37.604 1414.089 96.322 55.350 57.463 3302.087 2160.890

MAY-JUN09

4208.55

7 243.365 5.782 33.438 151.673 12.601 8.308 69.024 48.042

JUL-AUG094451.92

2474.786 10.664 113.736 164.275 8.838 5.380 28.949 57.381

SEP-OCT094926.70

8101.715 2.064 4.262 173.113 26.778 15.468 239.288 31.936

NOV-DEC095028.42

3(34.585) (0.687) 0.473 199.892 21.902 10.956 120.055 (7.536)

JAN-FEB104993.83

8221.794

Total 14.401 2420.426 45.654 6231.17 3654.452

BETA =

=

= 1.496804

Interpretation

From the above table 4.16, we got the beta value of SAIL compare with NIFTY valueas 1.496804. From beta value one can identify that the investment is more volatile than the


Page 30 of77


31/77

TABLE 17: COMPARE WITH NIFTY AND M&M

BETA =

=

= 1.671474

Interpretation

From the above table 4.17, we got the beta value of M&M compare with NIFTYvalue as 1.671474. From beta value one can identify that the investment is more volatile


be made.

Page 31 of77

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage

5

M&M 6Change in

M&M 7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percenta

on Nift

and M&

4=3/2*100 10=4*

MAR-APR08 4839.186 (99.849) (2.063) 4.257 651.435 (43.323) (6.650) 44.228 13.722

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 608.112 (69.620) (11.448) 131.070 115.63

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 538.491 (48.667) (9.037) 81.681 114.55

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 489.824 (185.741) (37.919) 1437.921 869.33

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 304.083 (7.474) (2.457) 6.041 2.605

JAN-FEB09 2837.235 221.212 7.796 60.789 296.609 100.305 33.817 1143.626 263.66

MAR-APR09 3058.447 1150.11 37.604 1414.089 396.914 260.683 65.677 4313.537 2469.76

MAY-JUN09 4208.557 243.365 5.782 33.438 657.598 131.623 20.015 400.633 115.74

JUL-AUG09 4451.922 474.786 10.664 113.736 789.222 93.569 11.855 140.563 126.44

SEP-OCT09 4926.708 101.715 2.064 4.262 882.792 147.966 16.7611 280.937 34.604

NOV-DEC09 5028.423 (34.585) (0.687) 0.4731030.75

932.854 3.187 10.159 (2.192

JAN-FEB10 4993.8381063.61

3

Total 14.401 2420.426 83.801 7990.401 4123.87


32/77

TABLE 18: COMPARE WITH NIFTY AND TATAMOTOR

Date1 Nifty2

Change

in Nifty

3

Change in

percentageSquare of

change in

percentage 5

TATA

MOTOR

6

Change in

Tatamotor

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percen

On N

An

Tatam

4=3/2*100 10=4

MAR-APR08 4839.186 (99.849) (2.063) 4.257 643.157 (62.996) (9.794) 95.941 20.2

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 580.161 (162.907) (28.079) 788.469 283.6

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 417.253 (88.021) (21.095) 445.021 267.3

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 329.231 (174.798) (53.092) 2818.847 1217.

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 154.433 (7.475) (4.841) 23.432 5.13

JAN-FEB09 2837.235 221.212 7.796 60.789 146.957 47.573 32.372 1047.957 252.3

MAR-APR09 3058.447 1150.11 37.604 1414.089 194.531 131.250 67.470 4552.212 2537.

MAY-JUN09 4208.557 243.365 5.782 33.438 325.781 57.695 17.710 313.644 102.4

JUL-AUG09 4451.922 474.786 10.664 113.736 383.477 182.259 47.527 2258.908 506.8

SEP-OCT09 4926.708 101.715 2.064 4.262 565.736 109.374 19.333 373.771 39.9

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 675.111 61.258 9.073 82.333 (6.24

JAN-FEB10 4993.838 736.369

Total 14.401 2420.426 76.584 12800.539 5226.

BETA =

=

2.134346

Interpretation

From the above table 4.18, we got the beta value of TATAMOTOR compare with


volatile than the market, because beta value is more than one. Based on this, highinvestment can be made.

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TABLE 19: COMPARE WITH NIFTY AND HERO HONDA

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage

5

HERO

HONDA

6

Change

in Hero

Honda

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percentage

On Nifty

And

Herohonda

4=3/2*100 10=4*8

MAR-APR08 4839.186 (99.849) (2.063) 4.257 740.175 40.087 5.415 29.332 (11.174)

MAY-JUN08 4739.337 (478.68) (10.100) 102.012 780.262 -26.372 (3.379) 11.424 34.138

JUL-AUG08 4260.657 (540.051) (12.675) 160.663 753.889 73.339 9.728 94.637 (123.307)

SEP-OCT08 3720.606 (852.968) (22.925) 525.579 827.229 -59.084 (7.142) 51.014 163.744

NOV-DEC08 2867.638 (30.403) (1.060) 1.124 768.144 97.747 12.725 161.928 (13.491)

JAN-FEB09 2837.235 221.212 7.796 60.789 865.892 168.091 19.412 376.846 151.354

MAR-APR09 3058.447 1150.11 37.604 1414.089 1033.984 322.321 31.172 971.738 1172.231

MAY-JUN09 4208.557 243.365 5.782 33.438 1356.305 156.07 11.506 132.411 66.540

JUL-AUG09 4451.922 474.786 10.664 113.736 1512.375 111.41 7.366 54.266 78.562

SEP-OCT09 4926.708 101.715 2.064 4.262 1623.785 31.594 1.945 3.785 4.017

NOV-DEC09 5028.423 (34.585) (0.687) 0.473 1655.379 -6.47 (0.391) 0.152 0.268

JAN-FEB10 4993.838 1648.909

Total 14.401 2420.426 88.361 1887.538 1522.883

BETA =

=

= 0.58595

Interpretation

From the above table 4.19, we got the beta value of HERO HONDA compare with

NIFTY value as 0.58595. From beta value one can identify that the investment is less

volatile than the market, because beta value is less than one.

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TABLE 20: COMPARE WITH NIFTY AND MARUTI

Date1 Nifty2

Change

in Nifty

3

Change in

percentage

Square of

change in

percentage

5

MARUTI

6

Change in

Maruti

7

Change in

percentage

8=7/6*100

Square of

change in

percentage

9

Percentage

On Nifty

And Marut

4=3/2*100 10=4*8

MAR-APR084839.18

6(99.849) (2.063) 4.257 803.161 (50.184) (6.248) 39.042 12.892

MAY-JUN084739.33

7(478.68) (10.100) 102.012 752.975 (144.386) (19.175) 367.696 193.674

JUL-AUG084260.65

7(540.051) (12.675) 160.663 608.589 59.719 9.812 96.288 (124.378)

SEP-OCT083720.60

6(852.968) (22.925) 525.579 668.308 (138.898) (20.783) 431.955 476.473

NOV-DEC08 2867.638

(30.403) (1.060) 1.124 529.410 58.971 11.138 124.075 (11.809)

JAN-FEB092837.23

5221.212 7.796 60.789 588.381 169.138 28.746 826.353 224.128

MAR-APR093058.44

71150.11 37.604 1414.089 757.518 233.461 30.819 949.820 1158.935

MAY-JUN094208.55

7243.365 5.782 33.438 990.979 288.254 29.087 846.099 168.203

JUL-AUG094451.92

2474.786 10.664 113.736 1279.234 258.407 20.200 408.045 215.429

SEP-OCT094926.70

8101.715 2.064 4.262 1537.641 10.96 0.712 0.508 1.471

NOV-DEC095028.42

3 (34.585) (0.687) 0.473 1548.601 (144.498) (9.331) 87.065 6.417

JAN-FEB104993.83

81404.103

Total 14.401 2420.426 74.980 4176.951 2321.437

BETA =

=

= 0.925758

Interpretation

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From the above table 4.20, we got the beta value of MARUTI compare with NIFTY

value as 0.925758. From beta value one can identify that the investment is less volatilethan the market, because beta value is less than one.

Beta

Beta is sensitivity of security to the market movement of variance companies of

founded.

If Beta < 1 than If Beta > 1 than

Less volatile for the More

volatile for the

Market movement Market movement

Page 35 of77

Company

Beta

()

Herohonda 0.586

Tcs 0.645

Infosys 0.74

Maruti 0.926

Hdfc 0.954

X

Beta

()

Sbin 1.045

Wipro 1.39

Sail 1.496

Jindalsteel 1.537

Hcl 1.543

M&M 1.671

Dlf 1.787

Icici 1.82

Ster 1.932

Idfc 2.081

Tatamotor 2.134

Tatasteel 2.135

L&T 2.189

Relcapital 2.276

Unitech 2.804


36/77

Chart-1

If Beta < 1 than, Less volatile for the Market movement

Chart-2

If Beta > 1 than, More volatile for the Market movement

Page 36 of77


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Beta ()

1.045

1.39

1.496

1.537

1.543

1.671

1.787

1.821.9322.081

2.134

2.135

2.189

2.276

2.804

Sbin

Wipro

Sail

Jindalst

HclM&M

Dlf

Icici

Ster

Idfc

Tatamot

Tataste

L&T

Relcapit

4.1.2 Measures of Systematic & Unsystematic Risk

Any rational investor, before investing his or her investable wealth in the stock,

analysis the risk associated with the particular stock. The actual return he receives from a

stock may vary from his expected in terms of return. The down side risk may be caused

by several factors, either common to all stocks or specific to a particular stock. Investor

in general would like to analyze the risk factor and a thorough knowledge of the risk

helps him to plan his portfolio in such a manner so as minimize the risk associated with

the investment.

Therefore, we can see there is some degree of risk involved in financial assets in thesense that there is always a chance that the expected return from the asset will not

materialize. It is important to find out more about the risks involved in financial assets

in greater details. These risks, by their nature, can be divided into two main categories;

namely, systematic risk and unsystematic risk.

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Systematic Risk

Systematic risks affect almost all assets in the economy at least to some degree

while unsystematic risks usually affect a small number of assets. When we discuss theprinciple of diversification at the bottom part of this article, you can see that highly

diversified portfolios will tend to have almost no unsystematic risk. Systematic Risks are

general market conditions that affect large number of assets (or companies), each to a

greater or lesser extent and are sometimes called market risks. Uncertainties about

general economic conditions such as GNP, interest rates, exchange rates, inflation or

unemployment levels are some of the examples of systematic risks.

Let us assume that there is an unanticipated increase in inflation which would affect

cost of supplies, wages, and the value of the raw materials and affect the prices of the

finished products leading to a fall in the real purchasing power of the individuals. Forces

such as these, which all companies are susceptible, are the essence of systematic risks.

You might wonder whether it is possible to avoid systematic risk. The answer is no

because these types of risks affect the whole economy and which would adversely affect

the values of the financial assets irrespective of the different types of assets in the

portfolio.

Systematic Risk = i2 i2

i2 = beta

i2 = variance of index

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Unsystematic Risk

Unsystematic Risks is the risk that a borrower or an issuer of securities (such as

bonds) will default on the obligations to repay the principal and/or interest payments.

This type of risk affects a single asset or a small group of assets and they are unique to

individual companies or assets. The various types of unsystematic risks can be

subdivided into several categories depending on the root causes. Business Risk is where

the revenues of the company are insufficient to cover the fixed cost of the operations.

Business Risk is where the revenues of the company are insufficient to cover the

fixed cost of the operations.

Financial Risk occurs when the revenues are insufficient to cover fixed charges

such as interest rate payments on debt. High- geared companies (companies that

are more reliance on borrowed funds than equity) are more exposed to this type

of risk.

Management Risk is where the managers of the company are unable to manage

the business at a profit may be due to inexperience or incompetences or where

there is evidence of organized fraud by the management.

Finally, there is Collateral Risk, which refers to the inadequacy of the claims

(security) that a lender may have on a borrower. In the case of a company going into

liquidation, an ordinary shareholder faces a much higher Collateral Risk than a secured

creditor. We can see from the above points that unsystematic risk does not depend on

economic activities and therefore it can be reduced and essentially eliminated by applying

a diversification strategy. This means, if you have a number of assets in your portfolio,

and as long as the unsystematic risk associated with these assets are not correlated (not

Page 39 of77


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moving in the same direction), the positive and negative events should largely cancel out

each other.

Unsystematic Risk = Total variance of security return

Systematic Risk

Systematic Risk vs. Unsystematic Risk

Systematic Risk

Systematic risk is the general ebb and flow of the market as a whole - or the

tendency for all stocks to increase or decrease in value at the same time with a certain

degree of positive correlation. For example, Black Monday on October 19th, 1987 was

a Systematic event in that almost all stocks fell in value on that single day. Macro-

economic events and stimuli can be expected to have broad systematic effects on capital

markets - positive or negative - on an on-going basis such as interest rate levels, political

events, war, etc. It is important to note that systematic risk cannot be diversified away. In

other words, you could have a portfolio that is diversified with 1000 different stocks from

a given market and there will always be a base level of return variance (shown as the

asymptote in the figure below).

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Non-Systematic Risk

Non-Systematic risk is the element of price risk than can be largely eliminated

through sufficient diversification within a particular asset class. The best way to describe

it is to build an analogy. Let us assume you owned one stock - if that company went

Bankrupt you will have lost 100% of your portfolio. If you owned one hundred stocks,

and one company went bankrupt you would have lost 1% of your portfolio. Conversely,

what if that one company doubled in value? You either doubled your money or only

gained 1% if you held 1 stock or 100, respectively. Non-Systematic risk is the individual

business risk associated with the underlying stock - if this company goes bankrupt - this

is a non-systematic risk event and generally has very little to do with the general ebb and

flow of the overall markets.

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http://www.executivefinancialplanning.com/wp-content/uploads/2008/07/systematicrisk.gif


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It is generally debated as to how many securities one needs to hold to eliminate

non-systematic risk. Research has shown that between thirty and forty securities are

enough to eliminate non-systematic risk.

A rational investor would be expected to take measures to eliminate non-systematic

risk from ones portfolio by increasing the number of holdings within each distinct asset

class a task that is easily accomplished through asset class indexing products which may

routinely hold hundreds of asset class constituent.

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CALCULATION OF SYSTEMATIC &UNSYSTEMATIC RISK

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF TATASTEEL

Beta = 2.135046

Systematic risk = 2variance of market index= (2.135046)2218.316

= 995.176

Unsystematic risk = (Total variance of security return)-(systematic risk)

= 1060.473-995.176= 65.296

Total risk = Systematic risk + Unsystematic risk

= 995.176+65.296= 1060.473

Page 43 of77

DateNifty

percentageVariance

fromaverage

Squareof

varianceTatasteel

Variancefrom

average

Square ofvariance

MAR-APR08 (2.063) (3.372) 11.370 16.325 12.997 168.922

MAY-JUN08 (10.100) (11.409) 130.165 -24.235 (27.563) 759.719

JUL-AUG08 (12.675) (13.984) 195.552 -36.965 (40.293) 1623.526

SEP-OCT08 (22.925) (24.234) 587.287 -51.487 (54.815) 3004.684

NOV-DEC08 (1.060) (2.369) 5.612 -1.266 (4.594) 21.105

JAN-FEB09 7.796 6.487 42.081 10.281 6.953 48.344

MAR-APR09 37.604 36.295

1317.32

7 78.607 75.279 5666.928

MAY-JUN09 5.782 4.473 20.008 13.833 10.505 110.355

JUL-AUG09 10.664 9.355 87.516 17.653 14.325 205.206

SEP-OCT09 2.064 0.755 0.570 9.351 6.023 36.277

NOV-DEC09 (0.687) (1.996) 3.984 7.815 4.487 20.133

JAN-FEB10

TOTAL 14.4012401.47

3 39.913 11665.198

AVG 1.309 3.628

S.D 218.316 1060.473


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TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF SBIN

Date

Nifty

percentageVariance

from

average

Square

ofvariance

SBINVariance

from

average

Square

ofvariance

MAR-APR08 (2.063) (3.263) 4.257

(14.755

) (17.574) 308.845

MAY-JUN08 (10.100) (11.300) 102.010 (7.101) (9.920) 98.406

JUL-AUG08 (12.675) (13.875) 160.656 6.078 3.259 10.621

SEP-OCT08 (22.925) (24.125) 525.556 (16.999) (19.818) 392.753

NOV-DEC08 (1.060) (2.260) 1.124 (4.768) (7.587) 57.563

JAN-FEB09 7.796 6.596 60.778 (3.534) (6.353) 40.361

MAR-APR09 37.604 36.404

1414.06

1 49.625 46.806 2190.802

MAY-JUN09 5.782 4.582 33.432 4.557 1.738 3.021

JUL-AUG09 10.664 9.464 113.721 23.239 20.420 416.976

SEP-OCT09 2.064 0.864 4.260 6.793 3.974 15.793

NOV-DEC09 (0.687) (1.887) 0.472 (9.308) (12.127) 147.064

JAN-FEB10

TOTAL 14.401

2420.32

5 33.825 368.483

AVG 1.309 3.075

S.D 218.316 334.680

Beta = 1.045


= 238.249

Unsystematic risk = (Total variance of security return)-(systematic risk)= 334.745-238.249

= 96.431

Total risk = Systematic risk + Unsystematic risk = 96.431+96.431

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= 334.680

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF ICICI

Date

Nifty

percentageVariance

from

average

Square

ofvariance

iciciVariance

from

average

Square

ofvariance

MAR-APR08 (2.063) (3.372) 11.370 (4.221) (7.301) 53.305

MAY-JUN08 (10.100) (11.409) 130.165 (20.164) (23.244) 540.284

JUL-AUG08 (12.675) (13.984) 195.552 (18.824) (21.904) 479.785

SEP-OCT08 (22.925) (24.234) 587.287 (23.809) (26.889) 723.018

NOV-DEC08 (1.060) (2.369) 5.612 1.716 (1.364) 1.860

JAN-FEB09 7.796 6.487 42.081 (10.422) (13.502) 182.304

MAR-APR09 37.604 36.295

1317.32

7 86.882 83.802 7022.775

MAY-JUN09 5.782 4.473 20.008 7.459 4.379 19.176

JUL-AUG09 10.664 9.355 87.516 17.335 14.255 203.205

SEP-OCT09 2.064 0.755 0.570 1.332 (1.748) 3.056

NOV-DEC09 (0.687) (1.996) 3.984 (3.407) (6.487) 42.081

JAN-FEB10

TOTAL 14.401

2401.47

3 33.878 9270.849AVG 1.309 3.080

S.D 218.316 842.804

Beta = 1.820

Systematic risk = 2variance of market index

= (1.820)2218.316= 722.7574


= 842.804-722.7574= 120.047


= 120.047+120.047

= 842.804

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TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF HDFC

Date

Nifty

percentageVariance

from

average

Square

ofvariance

HdfcVariance

from

average

Square

ofvariance

MAR-APR08 (2.063) (3.372) 11.370 -5.454 (8.288) 68.691

MAY-JUN08 (10.100) (11.409) 130.165 -12.923 (15.757) 248.283

JUL-AUG08 (12.675) (13.984) 195.552 4.559 1.725 2.976

SEP-OCT08 (22.925) (24.234) 587.287 -18.034 (20.868) 435.473

NOV-DEC08 (1.060) (2.369) 5.612 -3.685 (6.519) 42.497

JAN-FEB09 7.796 6.487 42.081 3.828 0.994 0.988

MAR-APR09 37.604 36.295

1317.32

7 43.677 40.843 1668.151

MAY-JUN09 5.782 4.473 20.008 3.763 0.929 0.863

JUL-AUG09 10.664 9.355 87.516 10.894 8.060 64.964

SEP-OCT09 2.064 0.755 0.570 8.371 5.537 30.658

NOV-DEC09 (0.687) (1.996) 3.984 -3.825 (6.659) 44.342

JAN-FEB10

TOTAL 14.401

2401.47

3 31.172 2607.886AVG 1.309 2.834

S.D 218.316 237.081

Beta = 0.954


= (0.954)2218.316= 198.6267


= 237.081-198.6267= 38.454


= 198.6267+38.454

= 237.136

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TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF RELCAPITAL

Date

Nifty

percentageVariance

from

average

Square

ofvariance

RelcapitalVariance

from

average

Square of

variance

MAR-APR08 (2.063) (3.372) 11.370 (9.102) (9.899) 97.990

MAY-JUN08 (10.100) (11.409) 130.165 0.967 0.170 0.029

JUL-AUG08 (12.675) (13.984) 195.552 (17.231) (18.028) 325.009

SEP-OCT08 (22.925) (24.234) 587.287 (47.306) (48.103) 2313.899

NOV-DEC08 (1.060) (2.369) 5.612 (20.601) (21.398) 457.874

JAN-FEB09 7.796 6.487 42.081 (4.448) (5.245) 27.510

MAR-APR09 37.604 36.295

1317.32

7 109.741 108.944 11868.795

MAY-JUN09 5.782 4.473 20.008 0.342 (0.455) 0.207

JUL-AUG09 10.664 9.355 87.516 5.666 4.869 23.707

SEP-OCT09 2.064 0.755 0.570 (6.673) (7.470) 55.801

NOV-DEC09 (0.687) (1.996) 3.984 (2.590) (3.387) 11.472

JAN-FEB10

TOTAL 14.401

2401.47

3 8.762 15182.293AVG 1.309 0.797

S.D 218.316 1380.208

Beta = 2.276


= 1130.436

Unsystematic risk = (Total variance of security return)-(systematic risk)= 1380.208 -1130.435

= 249.772


= 1130.436+249.772= 1380.208

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TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF IDFC

Date

Niftypercentage

Variance

from

average

Squareof

varianceIDFC

Variance

from

average

Square ofvariance

MAR-APR08 (2.063) (3.372) 11.370 (9.454) (13.310) 177.156

MAY-JUN08 (10.100) (11.409) 130.165

(31.042

) (34.898) 1217.870

JUL-AUG08 (12.675) (13.984) 195.552

(28.754

) (32.610) 1063.412

SEP-OCT08 (22.925) (24.234) 587.287

(12.676

) (16.532) 273.307

NOV-DEC08 (1.060) (2.369) 5.612 (6.722) (10.578) 111.894

JAN-FEB09 7.796 6.487 42.081 3.386 (0.470) 0.221

MAR-APR09 37.604 36.2951317.32

7 101.910 98.054 9614.587

MAY-JUN09 5.782 4.473 20.008 10.979 7.123 50.737

JUL-AUG09 10.664 9.355 87.516 10.473 6.617 43.785

SEP-OCT09 2.064 0.755 0.570 10.010 6.154 37.872

NOV-DEC09 (0.687) (1.996) 3.984 (5.693) (9.549) 91.183JAN-FEB10

TOTAL 14.4012401.47

3 42.417 12682.024

AVG 1.309 3.856

S.D 218.316 1152.911

Beta = 2.081


= (2.081)2218.316= 945.627


= 1152.911-945.626= 207.284


Page 48 of77


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= 945.626+207.286

= 1152.911

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF INFOSYS

Date

Nifty

percentageVariance

from

average

Square

of

varianceInfosys

Variancefrom

average

Square

of

variance

MAR-APR08 (2.063) (3.372) 11.370 23.625 17.785 316.306

MAY-JUN08 (10.100) (11.409) 130.165 (10.264) (16.104) 259.339

JUL-AUG08 (12.675) (13.984) 195.552 (11.771) (17.611) 310.147

SEP-OCT08 (22.925) (24.234) 587.287 (18.617) (24.457) 598.145

NOV-DEC08 (1.060) (2.369) 5.612 3.555 (2.285) 5.221

JAN-FEB09 7.796 6.487 42.081 8.255 2.415 5.832

MAR-APR09 37.604 36.2951317.32

7 23.998 18.158 329.713

MAY-JUN09 5.782 4.473 20.008 18.301 12.461 155.277

JUL-AUG09 10.664 9.355 87.516 14.732 8.892 79.068

SEP-OCT09 2.064 0.755 0.570 7.239 1.399 1.957

NOV-DEC09 (0.687) (1.996) 3.984 5.191 (0.649) 0.421

JAN-FEB10

TOTAL 14.401

2401.47

3 64.245 2061.426

AVG 1.309 5.840

S.D 218.316 187.402

Beta = 0.740


= (0.740)2218.316= 119.687


= 187.402-119.687

= 67.715Total risk = Systematic risk + Unsystematic risk

= 119.687+67.715

= 187.402

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TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF TCS

Date

Nifty

percentageVariance

from

average

Square

of

varianceTcs

Variancefrom

average

Square

of

variance

MAR-APR08 (2.063) (3.372) 11.370 6.803 6.925 47.956

MAY-JUN08 (10.100) (11.409) 130.165

(11.486

) (11.364) 129.140

JUL-AUG08 (12.675) (13.984) 195.552(19.688

) (19.566) 382.828

SEP-OCT08 (22.925) (24.234) 587.287

(22.954

) (22.832) 521.300

NOV-DEC08 (1.060) (2.369) 5.612 (1.801) (1.679) 2.819

JAN-FEB09 7.796 6.487 42.081 7.449 7.571 57.320

MAR-APR09 37.604 36.295

1317.32

7 12.036 12.158 147.817

MAY-JUN09 5.782 4.473 20.008

(20.441

) (20.319) 412.862

JUL-AUG09 10.664 9.355 87.516 23.189 23.311 543.403

SEP-OCT09 2.064 0.755 0.570 16.681 16.803 282.341

NOV-DEC09 (0.687) (1.996) 3.984 8.871 8.993 80.874

JAN-FEB10

TOTAL 14.401

2401.47

3 (1.342) 2608.660

AVG 1.309 (0.122)

S.D 218.316 237.151

Beta = 0.645


= (0.645)2218.316= 90.892


= 237.151-90.892

Page 50 of77


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= 146.259


= 90.892+146.259= 237.151

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF WIPRO

Date

Niftypercentage

Variance

from

average

Square

of

variance

wipro

Variance

from

average

Square

of

variance

MAR-APR08 (2.063) (3.372) 11.370 16.127 9.469 89.662

MAY-JUN08 (10.100) (11.409) 130.165(14.383

) (21.041) 442.724

JUL-AUG08 (12.675) (13.984) 195.552

(18.181

) (24.839) 616.976

SEP-OCT08 (22.925) (24.234) 587.287

(29.578

) (36.236) 1313.048

NOV-DEC08 (1.060) (2.369) 5.612 (6.156) (12.814) 164.199

JAN-FEB09 7.796 6.487 42.081 12.111 5.453 29.735

MAR-APR09 37.604 36.295

1317.32

7 51.112 44.454 1976.158

MAY-JUN09 5.782 4.473 20.008 21.693 15.035 226.051

JUL-AUG09 10.664 9.355 87.516 23.009 16.351 267.355

SEP-OCT09 2.064 0.755 0.570 11.881 5.223 27.280

NOV-DEC09 (0.687) (1.996) 3.984 5.605 (1.053) 1.109

JAN-FEB10

TOTAL 14.401

2401.47

3 73.243 5154.296

AVG 1.309 6.658S.D 218.316 468.572

Beta = 1.390


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= 422.091


= 468.572- 422.091= 46.481


= 422.091+46.481= 468.572

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF HCLTECH

DateNifty

percentageVariance

fromaverage

Squareof

varianceHcltech

Variancefrom

average

Squareof

variance

MAR-APR08 (2.063) (3.372) 11.370 11.338 5.238 27.437

MAY-JUN08 (10.100) (11.409) 130.165

(22.631

) (28.731) 825.470

JUL-AUG08 (12.675) (13.984) 195.552(10.651

) (16.751) 280.596

SEP-OCT08 (22.925) (24.234) 587.287

(32.795

) (38.895) 1512.821

NOV-DEC08 (1.060) (2.369) 5.612(15.951

) (22.051) 486.247

JAN-FEB09 7.796 6.487 42.081 (2.181) (8.281) 68.575

MAR-APR09 37.604 36.2951317.32

7 56.360 50.260 2526.068

MAY-JUN09 5.782 4.473 20.008 37.489 31.389 985.269

JUL-AUG09 10.664 9.355 87.516 33.299 27.199 739.786

SEP-OCT09 2.064 0.755 0.570 6.821 0.721 0.520

NOV-DEC09 (0.687) (1.996) 3.984 6.001 (0.099) 0.010

JAN-FEB10

TOTAL 14.4012401.47

3 67.098 7452.798

AVG 1.309 6.100

S.D 218.316 677.527

Beta = 1.543

Page 52 of77


53/77


= (1.543)2218.316= 519.712


= 677.527-519.712= 157.815


= 519.712+157.815= 677.527

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF L&T

Date

Nifty

percentageVariance

from

average

Square

ofvariance

L&TVariance

from

average

Square of

variance

MAR-APR08 (2.063) (3.372) 11.370 (5.132) (5.589) 31.237

MAY-JUN08 (10.100) (11.409) 130.165 (6.510) (6.967) 48.539

JUL-AUG08 (12.675) (13.984) 195.552 (31.475) (31.932) 1019.653

SEP-OCT08 (22.925) (24.234) 587.287 (55.451) (55.908) 3125.704NOV-DEC08 (1.060) (2.369) 5.612 (12.308) (12.765) 162.945

JAN-FEB09 7.796 6.487 42.081 3.606 3.149 9.916

MAR-APR09 37.604 36.295

1317.32

7 87.483 87.026 7573.525

MAY-JUN09 5.782 4.473 20.008 10.866 10.409 108.347

JUL-AUG09 10.664 9.355 87.516 9.766 9.309 86.657

SEP-OCT09 2.064 0.755 0.570 0.525 0.068 0.005

NOV-DEC09 (0.687) (1.996) 3.984 (6.395) (6.852) 46.950

JAN-FEB10

TOTAL 14.401

2401.47

3

(5.025

) 12213.478

AVG 1.309

(0.457

)

S.D 218.316 1110.316

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Beta = 2.189

Systematic risk = 2variance of market index= (2.189)2 218.316

= 1045.861


= 64.455


= 1110.316

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF DLF

Date

Niftypercentage

Variance

from

average

Squareof

varianceDLF

Variance

from

average

Squareof

variance

MAR-APR08 (2.063) (3.372) 11.370

(14.468

) (11.917) 142.015

MAY-JUN08 (10.100) (11.409) 130.165(13.839

) (11.288) 127.419

JUL-AUG08 (12.675) (13.984) 195.552

(24.874

) (22.323) 498.316

SEP-OCT08 (22.925) (24.234) 587.287

(31.274

) (28.723) 825.011

NOV-DEC08 (1.060) (2.369) 5.612

(27.017

) (24.466) 598.585

JAN-FEB09 7.796 6.487 42.081 5.227 7.778 60.497

MAR-APR09 37.604 36.295

1317.32

7 73.585 76.136 5796.690

MAY-JUN09 5.782 4.473 20.008 9.482 12.033 144.793

JUL-AUG09 10.664 9.355 87.516 16.903 19.454 378.458

SEP-OCT09 2.064 0.755 0.570

(12.478

) (9.927) 98.545

NOV-DEC09 (0.687) (1.996) 3.984 (9.309) (6.758) 45.671

JAN-FEB10

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TOTAL 14.4012401.47

3(28.065

) 8716.001

AVG 1.309 (2.551)

S.D 218.316 792.364

Beta = 1.787


= (1.787)2 218.316= 696.9451


= 792.364-696.945= 95.419


= 696.9451+95.419= 792.364

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF UNITECH

Date

Nifty

percentageVariance

fromaverage

Squareof

varianceUnitech

Variance

fromaverage

Square of

variance

MAR-APR08 (2.063) (3.372) 11.370

(16.503

) (13.560) 183.874

MAY-JUN08 (10.100) (11.409) 130.165

(29.651

) (26.708) 713.317

JUL-AUG08 (12.675) (13.984) 195.552

(33.598

) (30.655) 939.729

SEP-OCT08 (22.925) (24.234) 587.287(64.884

) (61.941) 3836.687

NOV-DEC08 (1.060) (2.369) 5.612(16.866

) (13.923) 193.850

JAN-FEB09 7.796 6.487 42.081 12.330 15.273 233.265

MAR-APR09 37.604 36.295

1317.32

7 107.707 110.650 12243.423

MAY-JUN09 5.782 4.473 20.008 14.098 17.041 290.396

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JUL-AUG09 10.664 9.355 87.516 21.766 24.709 610.535

SEP-OCT09 2.064 0.755 0.570

(18.959

) (16.016) 256.512

NOV-DEC09 (0.687) (1.996) 3.984 (7.812) (4.869) 23.707

JAN-FEB10

TOTAL 14.4012401.47

3(32.373

) 19525.294

AVG 1.309 (2.943)

S.D 218.316 1775.027

Beta = 2.804


= (2.804)2 218.316= 1716.226


= 1775.027-1716.226= 58.801


= 1716.226+58.801= 1775.027

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF JINDALSTEEL

Date

Nifty

percentageVariance

fromaverage

Square

of

varianceJindalsteel

Variance

fromaverage

Square of

variance

MAR-APR08 (2.063) (3.372) 11.370 6.752 9.426 88.849MAY-JUN08 (10.100) (11.409) 130.165 (12.260) (9.586) 91.891

JUL-AUG08 (12.675) (13.984) 195.552 (36.884) (34.210) 1170.324

SEP-OCT08 (22.925) (24.234) 587.287 (32.556) (29.882) 892.934

NOV-DEC08 (1.060) (2.369) 5.612 17.818 20.492 419.922

JAN-FEB09 7.796 6.487 42.081 31.893 34.567 1194.877

MAR-APR09 37.604 36.2951317.32

7 68.853 71.527 5116.112

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MAY-JUN09 5.782 4.473 20.008 33.803 36.477 1330.572

JUL-AUG09 10.664 9.355 87.516 (56.218) (53.544) 2866.960

SEP-OCT09 2.064 0.755 0.570 (43.760) (41.086) 1688.059

NOV-DEC09 (0.687) (1.996) 3.984 (6.855) (4.181) 17.481

JAN-FEB10

TOTAL 14.401

2401.47

3 (29.415) 14877.982

AVG 1.309 (2.674)

S.D 218.316 1352.544

Beta = 1.537


= (1.537)2 218.316

= 515.8309


= 836.713


= 1352.544

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF STER

Date

Nifty

percentageVariance

from

average

Squareof

varianceSter

Variance

from

average

Squareof

variance

MAR-APR08 (2.063) (3.372) 11.370 7.895 3.394 11.519

MAY-JUN08 (10.100) (11.409) 130.165

(25.070

) (29.571) 874.444

JUL-AUG08 (12.675) (13.984) 195.552

(35.751

) (40.252) 1620.224

SEP-OCT08 (22.925) (24.234) 587.287(37.071

) (41.572) 1728.231

NOV-DEC08 (1.060) (2.369) 5.612 5.015 0.514 0.264

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JAN-FEB09 7.796 6.487 42.081 28.828 24.327 591.803

MAR-APR09 37.604 36.295

1317.32

7 70.253 65.752 4323.326

MAY-JUN09 5.782 4.473 20.008 8.135 3.634 13.206

JUL-AUG09 10.664 9.355 87.516 22.160 17.659 311.840

SEP-OCT09 2.064 0.755 0.570 9.400 4.899 24.000 NOV-DEC09 (0.687) (1.996) 3.984 (4.290) (8.791) 77.282

JAN-FEB10

TOTAL 14.401

2401.47

3 49.508 9576.139

AVG 1.309 4.501

S.D 218.316 870.558

Beta = 1.932


= 814.8915


= 870.558-814.8915= 55.667


= 814.8915+55.667= 870.558

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF SAIL

Date

Nifty

percentage

Variance

fromaverage

Square

ofvariance Sail

Variance

fromaverage

Square

ofvariance

MAR-APR08 (2.063) (3.372) 11.370

(13.015

) (17.165) 294.637

MAY-JUN08 (10.100) (11.409) 130.165(14.538

) (18.688) 349.241

JUL-AUG08 (12.675) (13.984) 195.552 (12.965 (17.115) 292.923

Page 58 of77


59/77

)

SEP-OCT08 (22.925) (24.234) 587.287

(38.637

) (42.787) 1830.727

NOV-DEC08 (1.060) (2.369) 5.612 8.176 4.026 16.209

JAN-FEB09 7.796 6.487 42.081 19.056 14.906 222.189

MAR-APR09 37.604 36.2951317.32

7 57.463 53.313 2842.276

MAY-JUN09 5.782 4.473 20.008 8.308 4.158 17.289

JUL-AUG09 10.664 9.355 87.516 5.380 1.230 1.513

SEP-OCT09 2.064 0.755 0.570 15.468 11.318 128.097

NOV-DEC09 (0.687) (1.996) 3.984 10.956 6.806 46.322

JAN-FEB10

TOTAL 14.401

2401.47

3 45.654 6041.423

AVG 1.309 4.150S.D 218.316 549.220

Beta = 1.496


= 488.594



= 488.594+60.626

= 549.220

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF M&M

Date

Niftypercentage

Variance

fromaverage

Squareof

varianceM&M

Variance

fromaverage

Squareof

variance

MAR-APR08 (2.063) (3.372) 11.370 (6.650) (14.268) 203.576

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MAY-JUN08 (10.100) (11.409) 130.165(11.448

) (19.066) 363.512

JUL-AUG08 (12.675) (13.984) 195.552 (9.037) (16.655) 277.389

SEP-OCT08 (22.925) (24.234) 587.287

(37.919

) (45.537) 2073.618

NOV-DEC08 (1.060) (2.369) 5.612 (2.457) (10.075) 101.506JAN-FEB09 7.796 6.487 42.081 33.817 26.199 686.388

MAR-APR09 37.604 36.2951317.32

7 65.677 58.059 3370.847

MAY-JUN09 5.782 4.473 20.008 20.015 12.397 153.686

JUL-AUG09 10.664 9.355 87.516 11.855 4.237 17.952

SEP-OCT09 2.064 0.755 0.570 16.761 9.143 83.596

NOV-DEC09 (0.687) (1.996) 3.984 3.187 (4.431) 19.634

JAN-FEB10

TOTAL 14.401 2401.473 83.801 7351.704

AVG 1.309 7.618

S.D 218.316 668.337

Beta = 1.671


= (1.671)2 218.316

= 609.936


= 58.400


= 668.337

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF TATAMOTOR

Date

Niftypercentage

Variance

from

average

Square

ofvariance

Tatamotor

Variance

from

average

Square ofvariance

Page 60 of77


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MAR-APR08 (2.063) (3.372) 11.370 (9.794) (16.756) 280.764

MAY-JUN08 (10.100) (11.409) 130.165 (28.079) (35.041) 1227.872

JUL-AUG08 (12.675) (13.984) 195.552 (21.095) (28.057) 787.195

SEP-OCT08 (22.925) (24.234) 587.287 (53.092) (60.054) 3606.483

NOV-DEC08 (1.060) (2.369) 5.612 (4.841) (11.803) 139.311

JAN-FEB09 7.796 6.487 42.081 32.372 25.410 645.668

MAR-APR09 37.604 36.295

1317.32

7 67.470 60.508 3661.218

MAY-JUN09 5.782 4.473 20.008 17.710 10.748 115.520

JUL-AUG09 10.664 9.355 87.516 47.527 40.565 1645.519

SEP-OCT09 2.064 0.755 0.570 19.333 12.371 153.042

NOV-DEC09 (0.687) (1.996) 3.984 9.073 2.111 4.456

JAN-FEB10

TOTAL 14.401

2401.47

3 76.584 12267.047AVG 1.309 6.962

S.D 218.316 1115.186

Beta = 2.134


= (2.134)2 218.316

= 994.5239



= 994.5239+120.662

= 1115.186

TABLE 21: SYSTEMATIC & UNSYSTEMATIC RISK OF HERO HONDA

Date

Nifty

percentageVariance

from

average

Squareof

varianceHero

Honda

Variance

from

average

Squareof

variance

Page 61 of77


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MAR-APR08 (2.063) (3.372) 11.370 5.415 (2.617) 6.849

MAY-JUN08 (10.100) (11.409) 130.165 (3.379) (11.411) 130.211

JUL-AUG08 (12.675) (13.984) 1

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