International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

i-Xplore International Research Journal Consortium www.irjcjournals.org

32

The Correlation of Hedging Risk and Volatility to Facilitate

the Optimal Portfolio Choice of Infosys Ltd, Wipro Ltd and

Tata Consultancy Services- A Study

Shruti Aggarwal, Asst. Profesor, finance CMRIT, Bangalore.

ABSTRACT

Portfolio is the diversification of group of investments and

management of portfolio consists of risk and return trade

off. The prices of securities fluctuate due to volatility and

risk, that can cause you great loss. Therefore, this

research paper is made to focus on hedging those risks

and volatility to facilitate the optimal portfolio choice. The

researcher has taken three IT companies that is: infosys,

Wipro, TCS, to support this descriptive study. The data

has been taken as secondary data for this contrived study

and hypothesis is tested through t-test. To support the

study, the statistical tools used in the study are CAPM,

Logit Regression. This Research paper would put an

insight into the hedging of risk and volatility to facilitate

the optimal portfolio choice with respect to Infosys, Wipro

and TCS.

Keywords: Portfolio, diversification, investments, risk, return,

volatility, hedging, optimal portfolio choice.

INTRODUCTION

COMPANY PROFILE

INFOSYS Ltd

Infosys Technologies Ltd. (NASDAQ: INFY) was started

in 1981 by seven people with US$ 250. Today, we are a

global leader in the "next generation" of IT and consulting

with revenues of US$ 5.4 billion (LTM Sep-10) .Infosys

defines, designs and delivers technology-enabled business

solutions that help Global 2000 companies win in a Flat

World. Infosys also provides a complete range of services

by leveraging our domain and business expertise

and strategic alliances with leading technology providers

WIPRO Ltd

Wipro Ltd is an Indian IT giant that offers integrated IT

solutions to its clients worldwide. It offers total

outsourcing, business solutions, consulting services and

professional services to plan, deploy, sustain and maintain

the IT lifecycle of its clients.Wipro Infotech is a part of

US$ 5 billion Wipro Limited with US$ 24 billion market

capitalization. Wipro is known for its quality. It is the first

global software company to attain Level 5 SEI-CMM as

well as the first IT Company in the world to achieve Six

Sigma and Level 5 PCMM.

TATA CONSULTATION SERVICES Tata Consultancy Services, the key player in the IT

services and business solutions area has attained for

themselves a quality that none can match. Their services

are mainly consulting based, with an integrated IT and

ITes portfolio. They have a unique Global Network

Delivery Model – which is supposed to be the yardstick of

superiority in software development. Tata Consultancy

Services is a part of the Tata group (the largest industrial

conglomerate of India).

RISK, VOLATILITY AND PORTFOLIO

"risks" are simply future issues that can be avoided or

mitigated, rather than present problems that must be

immediately addressed. The simple fact is that risk is

always a probability issue. Possibility is a binary condition

– either something is possible, or it’s not – 100% or 0%.

In risk management, the term "hazard" is used to mean an

event that could cause harm and the term "risk" is used to

mean simply the probability of something happening.

Financial risk is often defined as the unexpected

variability or volatility of returns and thus includes both

potential worse-than-expected as well as better-than-

expected returns.

In finance, volatility most frequently refers to the standard

deviation of the continuously compounded returns of

a financial instrument within a specific time horizon. It is

used to quantify the risk of the financial instrument over

the specified time period. Volatility is normally expressed

in annualized terms, and it may either be an absolute

number ($5) or a fraction of the mean (5%).

In finance, a portfolio is a collection of investments held

by an institution or an individual.

Holding a portfolio is a part of an investment and risk-

limiting strategy called diversification. By owning several

assets, certain types of risk (in particular specific risk) can

be reduced. The assets in the portfolio could include bank

accounts, stocks, bonds, options, warrants, gold

certificates, real estate, futures contracts, production

facilities, or any other item that is expected to retain its

value.

Portfolio management involves deciding what assets to

include in the portfolio, given the goals and risk tolerance

of the portfolio owner. Selection involves deciding which

assets to acquire/divest, how many to acquire/divest, and

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

i-Xplore International Research Journal Consortium www.irjcjournals.org

33

when to acquire/divest them. These decisions always

involve some sort of performance measurement, most

typically the expected return on the portfolio, and the risk

associated with this return (e.g., the expected standard

deviation of the expected return).

Portfolio formation : Many strategies have been

developed to form a portfolio;

equally-weighted portfolio

capitalization-weighted portfolio

price-weighted portfolio

optimal portfolio (for which Risk-Adjusted

Return is highest)

THEORETICAL FRAMEWORK

CONSTRUCT:

To study the Correlation of hedging risk and volatility to

facilitate the optimal portfolio choice of Infosys Ltd,

Wipro Ltd and Tata Consultancy Services

DEPENDENT VARIABLE:

Investment portfolio

INDEPENDENT VARIABLES:

Cost of investments

Risk (beta)

Returns on investment (ROI)

Volatility

LITERATURE REVIEW

frey, thorsten and buxmann, peter, "IT project

portfolio management - a structured literature

review" (2012). ecis 2012 proceedings. paper 167.

http://aisel.aisnet.org/ecis2012/167

Wheelwright and Clark, 1992; cooper, edgett et

al,2000; says that a portfolio is balanced if there is

suitable distribution of projects on the basis of risk,

return, volatility and efficiency.

Welling and Kamann, 2001; says that cooperation

can be improved, if the same individuals deals with

each other in the series of projects, rather than

different individuals with different projects.

Pinto, 2002; suggests that the successful application

of risk evaluation in portfolio is the proper

assessment of risk and quantification be uniformely

applied over the projects.

RESEARCH OBJECTIVES

To understand the risk and volatility in the

companies and their effect on the portfolio

structure.

To know the asset allocation in the companies so as

to have proper investments in assets.

To study the returns in the company to maintain the

portfolio fruitful.

To study the asset pricing through CAPM model in

order to devote legible cash for assets, reserves for

its depreciation and to decide upon its proper

selection.

To study the debt and equity composition mix of

the companies and the returns on it with respect to

capital so as to make well diversified portfolio with

minimise risk.

To find out the measures to hedge the risk and

volatility so as to facilitate the optimal portfolio

choice.

To find out the optimal portfolio structure for the

companies that can generate the maximum of return

with negligible risk and volatility

To find out the importance of variables for the

selection of optimal portfolio.

To study whether the estimated return is more than

the expected return or vice versa, in order to

eliminate the loss generating securities from the

portfolio.

To study the ways and means to invest either in

govt. securities or in other securities where risk

persists for the investor.

To provide pragmatic suggestions for improvement

of the investment pattern by the prospective

investor in order to hedge themselves from the

market risk.

RESEARCH METHODOLOGY

SOURCE FOR DATA COLLECTION

The data is collected through the secondary sources

RESEARCH DESIGN IN STUDY

In the study I will apply descriptive research design. As

descriptive research design is a design where the data is

collected through secondary sources and the study is

already being done by someone before.

TIME HORIZON

The time horizon in my study is “CROSS-SECTIONAL”

study because the data is being collected at once from the

the secondary sources and not at two or more points in

time to answer my research question.

STUDY SETTING IN MY STUDY:

The study setting used by me is CONTRIEVED STUDY

because the organization research conducted by me is not

in natural environment.

HYPOTHESIS DEVELOPMENT AND TESTING

DEPENDENT VARIABLE: investment portfolio

INDEPENDENT VARIABLE: cost of investment

NULL HYPOTHESIS (H0):There is no significant

relation between the cost of investment and the optimal

portfolio choice.

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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ALTERNATE HYPOTHESIS (H1): There is a

significant relation between the cost of investment and the

optimal portfolio choice.

TESTING: one sample t-test

One-Sample Statistics

N Mean

Std.

Deviatio

n Std. Error Mean

Investment

portfolio 4 1.5910E2 52.13025 26.06513

Cost of

investment 4 8.1292 7.10034 3.55017

One-Sample Test

Test Value = 0

T Df

Sig. (2-

tailed)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

Inves

tment

portf

olio

6.104 3 .009 159.09500 76.1441 242.0459

Cost

of

inves

tment

2.290 3 .106 8.12925 -3.1690 19.4275

INTERPRETATION:As the calculated value i.e.2.290 is

greater than the table value i.e. 1.967, we accept the

alternate hypothesis and reject the null hypothesis.

Therefore, there is a significant relation between the cost

of investment and the optimal portfolio choice.

DEPENDENT VARIABLE: investment

portfolio

INDEPENDENT VARIABLE: risk (beta)

NULL HYPOTHESIS (H0): There is no significant

relation between the risk and the optimal portfolio choice.

ALTERNATE HYPOTHESIS (H2): There is a

significant relation between the risk and the optimal

portfolio choice

TESTING: ONE SAMPLE t-TEST

One-Sample Statistics

N Mean

Std.

Deviation

Std.

Error

Mean

Investment

portfolio 4 1.5910E2 52.13025 26.06513

Risk 4 2.5770 .64157 .32078

One-Sample Test

Test Value = 0

T Df

Sig.

(2-

tailed

)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

Investm

ent

portfolio

6.104 3 .009 159.09500 76.1441 242.0459

Risk 8.033 3 .004 2.57700 1.5561 3.5979

INTERPRETATION: As the calculated value i.e.8.033 is

greater than the table value i.e. 1.967, we accept the

alternate hypothesis and reject the null hypothesis.

Therefore, there is a significant relation between the risk

and the optimal portfolio choice.

DEPENDENT VARIABLE: investment portfolio

INDEPENDENT VARIABLE: return on

investment

NULL HYPOTHESIS ( H0): There is no significant

relation between the ROI and the optimal portfolio choice

ALTERNATE HYPOTHESIS (H3): There is a

significant relation between the ROI and the optimal

portfolio choice.

TESTING: ONE SAMPLE t-TEST

One-Sample Statistics

N Mean

Std.

Deviation Std. Error Mean

Investment

portfolio 4 1.5910E2 52.13025 26.06513

Return on

investment 4 1.7182E3 294.91953 147.45977

One-Sample Test

Test Value = 0

T Df

Sig.

(2-

taile

d)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

Investment

portfolio 6.104 3 .009 159.09500 76.1441 242.0459

Return on

investment 11.652 3 .001 1718.15250 1248.8697 2187.4353

INTERPRETATION: As the calculated value i.e.11.652

is greater than the table value i.e. 1.967, we accept the

alternate hypothesis and reject the null hypothesis.

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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Therefore, there is a significant relation between the ROI

and the optimal portfolio choice.

DEPENDENT VARIABLE: investment portfolio

INDEPENDENT VARIABLE: volatility

NULL HYPOTHESIS ( H0): There is no significant

relation between the volatility and the optimal portfolio

choice.

ALTERNATE HYPOTHESIS (H4): There is a

significant relation between the volatility and the optimal

portfolio choice.

TESTING: ONE SAMPLE t-TEST

One-Sample Statistics

N Mean

Std.

Deviation

Std. Error

Mean

Investment

portfolio 4 1.5910E2 52.13025 26.06513

Volatility 4 27.1050 26.11765 13.05883

One-Sample Test

Test Value = 0

T

D

f

Sig.

(2-

taile

d)

Mean

Difference

95% Confidence

Interval of the

Difference

Lower Upper

Invest

ment

portfoli

o

6.104 3 .009 159.09500 76.1441 242.0459

Volatili

ty 2.076 3 .130 27.10500

-

14.4540 68.6640

INTERPRETATION: As the calculated value i.e.2.076 is

greater than the table value i.e. 1.967, we accept the

alternate hypothesis and reject the null hypothesis.

Therefore, there is a significant relation between the

volatility and the optimal portfolio choice.

STATISTICAL TOOLS CAPM MODEL

CAPITAL ASSET PRICING MODEL: A model to

price risky assets

Main points of CAPM theory:

1. Diversify to eliminate non-systematic risk.

2. Hold only the risk-free asset and the tangent portfolio.

3. An asset’s systematic risk is measured by contribution

to the

risk of the tangent portfolio – its beta βiT.

4. An asset’s risk premium is proportional to its systematic

risk:

¯ri − rF = βiT (¯rT − rF) .

STRATEGY TO INTERPRET THE RESULTS:

if estimated return is greater than expected return

then there is high returns and less risk.

If expected return is greater than expected return

then there is low returns and high risk

INFOSYS Ltd

Year end 2010

units quoted

INTERPRETATION:

Here, only 8 out of 13 securities have more estimated

return than expected return. Therefore the portfolio

generates moderate returns of 20.53 and risk of 1.16.

EQUITY UNQUOTED

INTERPRETATION:

Here, only 4 out of 10 securities have more estimated

return than expected return. Therefore the portfolio

generates less returns of 18.1and risk of 1.39.

WIPRO Ltd

Year 2010

Debentures unquoted

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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INTERPRETATION:

Here, only 1 out of 2 securities have more estimated

return than expected return. Therefore the portfolio

generates less returns of 9.40 and risk of .48

Equity unquoted

INTERPRETATION:

Here, only 14 out of 21 securities have more estimated

return than expected return. Therefore the portfolio

generates good returns of 33.85 and risk of 3.35

Pref shares

INTERPRETATION:

Here, only 2 out of 2 securities have more estimated

return than expected return. Therefore the portfolio

generates good returns of 9.77 and risk of .46

Units quoted

INTERPRETATION:

Here, only 6 out of 9 securities have more estimated

return than expected return. Therefore the portfolio

generates very good returns of 24.73 and risk of 2.4

TATA CONSULTANCY SERVICES Ltd

Year end 2010

Equity quoted

INTERPRETATION:

Here, only 0 out of 1 securities have more estimated return

than expected return. Therefore the portfolio generates less

returns of 12.61and risk of .98

Debentures quoted

INTERPRETATION:

Here, only 1 out of 4 securities have more estimated return

than expected return. Therefore the portfolio generates less

returns of 14.05 and risk of 1.08

Debentures unquoted

INTERPRETATION:

Here, only 2 out of 2 securities have more estimated

return than expected return. Therefore the portfolio

generates good returns of 11.1and risk of .82

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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Equity unquoted

INTERPRETATION:

Here, only 11 out of 19 securities have more estimated

return than expected return. Therefore the portfolio

generates less returns of 17.89 and risk of 1.36

Pref shares

INTERPRETATION:

Here, only 2 out of 4 securities have more estimated return

than expected return. Therefore the portfolio generates less

returns of 11.56and risk of .76

Units unquoted

INTERPRETATION:

Here, only 12 out of 19 securities have more estimated

return than expected return. Therefore the portfolio

generates good returns of 21.54and risk of 1.93

LOGIT REGRESSION

It is a univariate or multivariate technique which allows

for estimating the probability that an event occurs or not,

by depicting a binary dependent outcome from a set of

independent variables.

ASSUMPTION: The roi is high with respect to given

level of risk.

INFOSYS Ltd

Year end 2010

INTERPRETATION:

The expected counts, observed counts does not implying

high variable constitution and adjusted residuals are highly

deviated, therefore, assumption proved wrong and returns

are less with respect to given level of risk.

WIPRO Ltd

Year end 2010

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INTERPRETATION:

In this the observed and expected counts are same but

adjusted residuals are in high concentrations , forming a

same line of pattern, appearing in complementary with

expected normal value with not high deviations and likely

closely associated, thus there are moderate returns with

respect to given level of risk and volatility.

TATA CONSULTANCY SERVICES

Year end 2010

INTERPRETATION:

A great pattern of adjusted residuals is visible, an

overlapping variables, each with a very less deviation ,

resulting into high returns expected and observed with

given level of risk and volatility.

LIMITATION OF THE STUDY

Except the supreme power, the Almighty, no one is

impeccable and prowess enough to accomplish anything

without any faults and limitations. A research is no

exception. No study is devoid of certain shortcomings.

Some problems encountered in this study are under

mentioned:

Time Constraints:

Time is a bit short to fathom into the depth of the study.

But still all efforts to the best possible extent will be made

to collect the data.

Data collection Constraints:

Since data to be use is secondary in nature, this poses the

constraints on the validity and reliability of the data.

Secrecy of Internal Data

In today’s day the companies are very sensitive regarding

their internal data, this proved a hindrance to my study.

Period of Analysis

Sample size of one year is taken -2010, which is sufficient,

but a bigger sample will be more effective.

RESULTS AND FINDINGS

The stochastic moments of returns results more into

volatility and the need for hedging.

It is projected that beta factor and the estimated

returns are the major factors affecting the optimal

portfolio choice.

The portfolio of INFOSYS Ltd is not well

diversified and hence more risky.

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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The Infosys ltd has to focus on quoted securities

rather than unquoted in order to earn stable returns

with less risk.

The INFOSYS Ltd must eliminate these securities

from the portfolio to seek high returns with less

risk. These are:

UNITS QUOTED: The units of KOTAK, RELIANCE,

ICICI PRUD.,HDFC, SBI are generating low returns with

high risk channel i.e. estimated returns are less than

expected returns, therefore they should be eliminated.

EQUITY UN QUOTED: The equities of INFOSYS

BPO,INFOSYS TECH CHINA, INFOSYS SWEDEN,

INFOSYS AUSTRALIA, ON MOBILE SYS, INFOSYS

PUBLIC are generating low returns with high risk channel

i.e. estimated returns are less than expected returns,

therefore they should be eliminated.

The portfolio of wipro ltd is diversified but not so

well and can prove risky in future if not undergone

any changes.

Wipro ltd have to focus more on units quoted as it

can prove beneficial for it in future.

The WIPRO Ltd must eliminate these securities

from the portfolio to seek high returns with less

risk. These are:

DEBENTURES UNQUOTED: the debentures of CITI

CORP. FINANCE should be eliminated as the debenture

is producing less estimated returns than expected returns

and generating less returns.

EQUITY UNQUOTED: the equity of WIPRO

CHANDRIKA, WIPRO SHANGHAI, WMNET SERVE,

WIPRO JAPAN, SPECTRAMIND, WEP

PHERIPHERALS should be eliminated, the equity is

producing less estimated returns than expected returns and

generating less returns.

PREFERENCE SHARES: nothing is to be eliminated as

both the pref. shrea are generating good returns.

UNITS QUOTED: the units of LIC MF, ICICI PRUD.

MF, UTI MF should be eliminated ,the units are producing

less estimated returns than expected returns and generating

less returns.

The portfolio of TCS is highly diversified and

stable, thus imposing less threat to tcs.

The returns are fairly good but some securities have

to be eliminated majorly from the portfolio as

causing threat due to low returns regularly, but

overall TCS is generating high returns from its

portfolio with very less deviations thereof.

The TCS Ltd must eliminate these securities from

the portfolio to seek high returns with less risk.

These are:

EQUITY QUOTED: the equity CMC is overpriced,

generating less returns , therefore should be eliminated.

DEBENTURES QUOTED: the bonds IDBI BONDS

2018, HUDCO BONDS 2014 are overpriced, generating

less returns , therefore should be eliminated.

DEBENTURES UNQUOTED: nothing is to be

eliminated but the check has to be made on TAT SONS

Ltd 2014.

EQUITY UNQUOTED: the equity of TCS

NETHERLANDS, TCS SVERIGE, TCI FNS, TCS

MOROCCO, TCS CANADA, TCS AFRICA, TCS E-

SERVE are overpriced, generating, therefore should be

eliminated.

PREFERENCE SHARES: the pref shares of TCS

CANADA, AP ONLINE are overpriced , generating less

returns , therefore should be eliminated.

UNITS UNQUOTED: the units of HDFC CASH

MNGMT, BSL INTERVAL, IDFC, KOTAK FLEXI,

TATA LIQUID are overpriced, generating less returns ,

therefore should be eliminated

It is being projected that volatility in the market is

not following the same pattern and is highly

fluctuating, thus affecting the prices and the returns

thereof.

The investments in asset should be such that the

long term investments should be less than short

term investments as the future is uncertain.

The better would be to keep reserves from the short

term investment gains for the future contingencies

as compared with investing in the long term

portfolio.

POLICY IMPLICATIONS

The Infosys should diversify their portfolio so as to

generate risk-return trade off.

The Infosys, wipro and tcs should eliminate the

securities from their portfolio that are generating

less returns due to the estimated return be less than

the expected returns.

The risk factor should be regularly assessed so as to

find the expected returns to make it clear in advance

that whether the portfolio will generate the good

returns or not.

The Infosys ltd should not go for the securities are

unquoted due to high risk probability and

uncertainity of values.

The investments should more in the units or

securities of the subsidiaries of the companys as it

would enhance its own capital and rotation of the

fund within its company pertaining to high returns

and very low risk.

The debt should not be taken in high amount so that

if loss occurs, you will not be affected at high

concentration.

The companies should avoid investing in unquoted

securities so as to avoid the risk and to enhance

returns.

The portfolio should regularly be revised so as to grab new

investment oppurtunities in the market.

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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ANNEXURES

units quoted

investment co YEAR END COI returns beta leverage(debt) volatility

tata FI.FUND-WEEKLY 2010 275 310 0.23 101 0.02

KOTAK FI LTP WEEKLY 2010 211 190 0.87 87 0.054

RELIANCE MTF WEEKLY 2010 234 259 0.76 45 0.43

BIRLASUNLIFE SAVING 2010 267 276 0.73 48 0.032

ICICI PRUDENTIAL. FLEXI IP 2010 310 300 0.66 12 0.01

IDFC MONEY MANAGER FD 2010 390 347 0.98 23 0.005

UTI. TRE-ADVANCE 2010 389 372 0.24 0 0.045

HDFC FI RT. INC 2010 122 100 0.11 0 0.67

DWS ULTRA STF 2010 40 49 0.11 0 0.08

SBI. SHF ULTRA- STF 2010 35 70 0.34 0 0.099

FRANKLIN TEMPLETON 2010 11 23 0.54 2 0.001

DSP BLACKROCK.FI 2010 10 2 0.45 2.5 0.0001

RELIGARE ULTRA STF 2010 23 18 0.56 3 0.03

TOTAL 2317 2316 . 323.5 0.023

equity unquoted

on mobile systems inc 2010 4 5.32 0.87 1.8 0.009

mera sport tech p ltd 2010 2 2.89 0.88 1 0.098

infosys bpo ltd 2010 659 723 0.56 234 0.63

infosys tech china 2010 65 56 0.53 21 0.025

infosys tech australia 2010 66 44 0.49 30 0.001

infosys cons inc USA 2010 243 276 0.998 137 0.00001

infosys tech sde rld 2010 40 59 0.65 0 0.022

infosys tech sweden 2010 0 0.01 1.87 0 0.065

infosys tech do bras 2010 28 56 1.56 0 0.077

infosys public ser i 2010 24 45 1 0 0.018

total 1131 1267.2 424.8

WIPRO

debenture un quoted

investment co year end COI returns beta leverage volatility

morgan stanley 2010 48.1 56.74 0.46 20.01 0.0012

citi corp finance ltd 2010 24.1 30.01 0.53 2.98 0.0032

total 72.2 86.75 22.99

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equity unquoted

wipro consumer care 2010 0.1 4.7 0.88 0 0.367

wipro chandrika ltd 2010 0.7 2.6 0.76 0 0.076

wipro trademarks 2010 2.2 4.8 0.55 0 0.026

wipro travels 2010 0.1 2.1 0.84 0 0.002

wipro techno service 2010 620.5 750 0.9 213 0.044

wipro holdings mauratious 2010 139.1 140 1 92.09 0.052

wipro australia pty 2010 0.1 0.6 0.21 0 0.041

wipro inc 2010 1610 1401 0.54 675.98 0.11

wipro japan kk 2010 1 0.54 0.66 0 0.011

wipro shanghai ltd 2010 0.9 0.64 0.73 0 0.023

wipro cyprus p ltd 2010 3322 3209 0.72 1543.9 0.064

3d networks pvt ltd 2010 127.1 150.98 0.79 0 0.094

planet psg pte ltd 2010 9.4 11.28 1.2 0 0.099

Cmango pte ltd 2010 1.6 3.51 1.89 0 0.008

WMNETSERVE ltd 2010 8.3 10.72 2 0 0.0867

spectramind inc 2010 0 0.98 1.9 0 0.073

wipro chengdu ltd 2010 2.4 3.87 1 0 0.0782

wipro airport it 2010 3.7 7.65 1 0 0.0421

lornmaede personal ca 2010 7.7 8 1 0 0.033

wipro ge healthcare 2010 22.7 25.01 0.93 0 0.0666

WeP peripherals ltd 2010 4.1 8.09 0.6 0 0.001

total 5883 5746.1 2524.97

pref shares

lornamaede personal ca p ltd 2010 5.72 7.89 0.46 0 0.09

wipro trademarks holdings ltd 2010 0 0.654 0.11 0 0.075

total 5.72 8.544 0

units quoted

birla mutual fund 2010 152.4 189.01 0.67 25.54 0.0012

DWS mutual fund 2010 56.7 65.32 0.68 0 0.013

kotak mutual fund 2010 94.3 101 0.87 0 0.0033

LIC mutual fund 2010 1120 1200 1 503.76 0.0028

ICICI prud MF 2010 15.8 20.98 1 0 0.0039

reliance MF 2010 79.3 100.54 0.71 0 0.01

IDFC MF 2010 284.1 303.61 1.01 43.98 0.099

Fr templeton MF 2010 52.1 60.12 1.66 0 0.0003

UTI mf 2010 0.5 1.25 0.02 0 0.04

total 1855 2041.8 573.28

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

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TCS

equity quoted

invest co year end COI returns beta leverage volatility

CMC 2010 379.9 452.82 0.971 100 0.0091

TOTAL 379.9 452.82 100

deb. Quoted

HUDCO bonda 2012 2010 0.25 4.56 0.74 0 0.0012

IDBI bonds 2018 2010 0.1 0.023 0.666 0 0.0003

IDBI bonds 2013 2010 1.8 3.61 0.438 0 0.0651

HUDCO bonds 2014 2010 1.5 3 0.91 0 0.066

total 3.65 11.193 0

deb. Unquoted

panatone finvest ltd 2013 2010 200 250 0.12 0 0.037

tat sons ltd 2014 2010 1000 876 0.947 600 0.028

total 1200 1126 600

equity un quoted

TCS ibercamerica S.A 2010 165.2 203.89 0.313 56.78 0.0087

APonline Ltd 2010 0 0 0.345 0 0.0099

TCS Belgium S.A 2010 1.06 1 0.882 0 0.0122

TCS Netherlands B.V 2010 402.9 209 0.563 200 0.002

TCS Sverige AB 2010 18.89 42.09 0.667 10.09 0.075

TCS Deutscheland Gmb 2010 1.72 2.38 0.487 0 1

Tata America Intl.Co 2010 452.9 505.05 0.887 120.5 0.094

TCS Asia Pacific Pte 2010 18.69 15.62 0.909 0 0.0043

WTI Advanced Tech.lt 2010 38.52 30.17 0.29 0 0.001

TCI FNS Pty ltd 2010 3.38 5.12 0.111 0 0.0033

Diligenta Ltd UK 2010 199.9 210.19 0.109 0 0.0098

TCS Canada Inc 2010 31.25 25.87 0.287 0 0.056

C-Edge Technolog.Ltd 2010 5.1 6 0.549 0 0.049

MP Online Ltd 2010 0.89 1.01 0.984 0 0.0032

TCS Morocco SARL AU 2010 8.17 12.72 0.324 0 0.0061

TCS (Africa)Pty Ltd 2010 4.92 5.0034 0.452 0 0.066

TCS e-Serve Ltd 2010 2454 2762.8 0.099 1500.5 0.069

National Power Excha 2010 2.5 3 0.913 0 0.038

Yodlee Inc 2010 0 0 0.666 0 0.0001

total 3810 4040.9 1887.87

International Journal of Management and Social Sciences Research (IJMSSR) ISSN: 2319-4421 Volume 2, No. 4, April 2013

i-Xplore International Research Journal Consortium www.irjcjournals.org

43

pref shares

Tata Autocomp Systems Ltd 2010 5 12.09 0.097 0 0.009

APOnline Ltd 2010 2.8 4.5 0.965 0 0.019

Tata Consultancy Services Canada Inc. 2010 6.02 7.02 0.436 0 0.0034

Diligenta Ltd 2010 363 400.05 0.773 100 0.066

total 376.9 423.66 . 100

units un quoted

Birla Sunlife Saving 2010 100 99 0.532 50 0.0098

Birla Sunlife STF-In 2010 306.98 301.98 0.983 120 0.0023

BSL Interval Inc.Fud 2010 25.14 30.42 0.672 0 0.012

BSL Interval Inc.Ins 2010 30.2 50.09 0.909 0 0.066

HDFC Cash Mgmt Fund- 2010 75.05 82.31 0.123 0 0.0043

ICICI Pru.Ultra STP 2010 306.7 320.1 0.537 112 0.0589

ICICI Pru FIP Premiu 2010 230.4 200 0.782 99 0.0265

IDFC Money Manager F 2010 202.67 201 1 43 0.0772

IDFC Money Mg Fd-TP 2010 130.93 150.91 1 0 0.0011

IDFC Lq Pls Fund-TP 2010 1 0 1.02 0 0.0008

Kotak Flexi Debt Sch 2010 230.73 200 1.36 45 0.0909

Kotak Qtrly Inverval 2010 25.18 21.1 0.009 0 0.0467

SBI-SHF Ultra STF-In 2010 50.64 62.32 0.027 0 0.0042

Tata Fltr Fd-Dialy D 2010 260.85 273.81 0.44 156 0.0003

TATA Treas.Manager S 2010 40.51 32.08 0.665 0 0.0021

TATA Fixed Inc.Porto 2010 10.03 15.86 0.723 0 0.059

TATA Liquid Super Hi 2010 6.42 8.29 0.621 0 0.0091

UTI-Treasury Advanta 2010 50 40 0.926 0 0.00534

UTI-Fixed Inc.Interv 2010 40.03 40 0.823 0 0.0032

Total 2123 2129.3 625