reliance power, tata power and suzlon energy

7/22/2019 Reliance Power, Tata Power and Suzlon Energy

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A

Research Project

On

Comparative analysis of financial performance of thepower sector (RELIANCE POWER, TATA POWER AND

SUZLON ENERGY) with reference of stock price,liquidity trends & risk factors

Submitted in partial fulfillment of the requirement

For the award of degree

Of

MASTERS OF BUSINESS ADMINISTRATION

SESSION (2009-2011)

SUBMITTED TO:- SUBMITTED BY:-ASTT.PROFF. M.B.A- 4th.SEMESTER

VAISH COLLEGE OF ENGINEERING

(Affiliated to M.D. University, Rohtak)


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CONTENTS Pg. No.1. INTRODUCTION

-COMPANY PROFILE

-TOPIC

2. THEORETICAL FRAMEWORK

-CONSTRUCT

-VARIABLES

3. LITERATURE REVIEW4. RESEARCH OBJECTIVE

5. RESEARCH METHODOLOGY

i. RESEARCH DESIGN

TYPE OF RESEARCH DESIGN

TIME HORIZON

STUDY SETTING

FLOW CHART FOR SELECTION OFSTATISTICAL TOOLS

LIMITATION OF STUDY

ii. HYPOTHESIS DEVELOPMENT AND TESTING

iii. SAMPLE & SAMPLING DESIGN

iv. DATA COLLECTION

v. ANALYTICAL TOOLS

vi. STATISTICAL TOOLS6. RESULTS & FINDINGS

7. POLICY IMPLICATIONS

8. SUGGESTIONS

9. BIBLIOGRAPHY

10. ANNEXURES


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INTRODUCTION OF INDUSTRY:-

Indias Power Generation capacity is 147403 MWDeficit is 20000 MW

As of December 2008,the Central Electricity Authority (CEA) reports that Indias Power

Generation Capacity is 147402.81 MW, up 8651 MW from 2007India continues to

reman a power deficit countryCurrent Deficit is 20000 MW.NTPC, a leading PSU, is

the biggest generator with 28333.99 MW from the Eleven Central Sector PSUsIt may

be recalled that Reliance Power, in the Private Sector, has plans to generate 28000 MWby 2016By Then NTPC capacity would have surged pass 65000 MWThe Eleventh

Five Year Plan 2007-2012 has a revised planned creation of 92000 MWBut with India

targeting high single digit GDP Growth Rate over the next several years, the demand for

power too will surgeIt will be only in the Twelth Five Year Plan 2012-2017 that the

power demand and supply curve will crossMckinsey in their report Powering India-Road

to 2017 estimates that the Power Demand will be 335000 MW in 2017 Interestingly

last year, amidst great controversy and opposition .both in India and in USA, both

countries signed a Nuclear Treaty to facilitate purchase of Uranium by India and setting

up of Nuclear Reactors for Civil Purposes The Breakup on various parameters of Indias

Installed Power Generating Capacity of 147402.81 MW makes interesting reading

INDIAS INSTALLED POWER GENERATING CAPACITY OF 147402.81 MW AT DEC

2008

By Mode By Sectors By State

Feed MW % Sector MW % State MW %

Coal 77458.88 52.55 State/UT 76185.57 51.69 Mah 10563.54 7.17

Gas 14734.01 10 Andhra P 7370.16 5


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Saturation in Capacities of Engineering Companies in Setting up of Power Plant

Infrastructure and delays in their increasing their Capacities

Delay in Allotment and Development of Coal Mineslargely on account of

delays in land acquisitions and in obtaining government clearances and multiple

mine allotted for the same mine

States Dominating the Distribution of PowerState Electricity Board ( SEB)

Losses are legendaryit impedes the States capability to invest further to

augment existing capacities and also discourages Private Investors from providing

Capital to do so.Distribution Losses are reportedly a criminal 40% of generated

and transmitted Power

If India has to Grow to be one of the top Three World Economies in the next Two

decades, as is expected, Power Capacities have to scale up significantly and fast

Government is well aware of this and has been introducing Power ReformsThe

Electricity Act of 2003,CERC,Exchanges for Power Trading, Privatization to highlight a

few Despite constraints, some due to coalition politics, the Power Sector has the Power

to create Multifold Gains for those who invest in this sector as a Business or even just as

an Investorbut these will play out over the Long TermTen Years and Beyond

The power sector has registered significant progress since the process of planned

development of the economy began in 1950. Hydro -power and coal based thermal power

have been the main sources of generating electricity. Nuclear power development is at

slower pace, which was introduced, in late sixties. The concept of operating power

systems on a regional basis crossing the political boundaries of states was introduced in

the early sixties. In spite of the overall development that has taken place, the power

supply industry has been under constant pressure to bridge the gap between supply anddemand.


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Power Supply Units in India:-

Thermal Power in India

Hydropower is India

Wind Power in India

Solar Power in India

Nuclear Power in India

Biogas Production in India

POWER INFRASTRUCTURE IN INDIA:-

The power industry in India derives its funds and financing from the government, some

private players that have entered the market recently, World Bank, public issues and

other global funds. The Power Ministry India has set up Power Finance Corporation of

India that looks after the financing of the power sector in India. The Power Finance

Corporation Limited provides finance to major power projects in India for power

generation and conversion, distribution and supply of power in India.

Power Finance Corporation (PFC) Ltd India also looks after the installation of any new

power projects as well as renovation of an existing power project India. The PFC in

association with central electricity authority and the ministry of power facilitates the

development in infrastructure of the power sector India. They have taken up construction

of mega power projects that will answer to the power shortage in various states through

power transmission through regional and national power grids.

FDI Inflows to Power:-

100% FDI is allowed in the power sector under the automatic route in India with the

exception of Atomic Energy. Important aspects of FDI in the power sector of India are -


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100 percent Foreign Direct Investment is allowed under automatic route in almost

all the power sectors in India except the Atomic Energy

Power projects involving generation and distribution tasks are allowed in all types

and sizes

As per the Electricity Act 2003, trading in power is activated

A duration of 30 years will given as a renewable license period

Thermal power plants will get a return of 16 percent on equity and will get 68.5

percent PLF

The import of equipments will be entitled to 20 percent of import duty

Power generating projects will have a five year tax holiday with five more years

which will have a deduction of 30 percent taxable profits.


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TATA POWER COMPANT LIMITED:-

Tata Power Company Limited (TPC), India's largest integrated Electric Power Utility in

private sector with a reputation for reliability, incorporated in the year 1919 at Mumbai.

TPC pioneered the generation of electricity in India nine decades ago. The core business

of Tata Power Company is to generate, transmit and distribute electricity. The Company

operates in two business segments: Power and Other. The Power segment is engaged in

generation, transmission and distribution of electricity. The other segment deals withelectronic equipment, project consultancy.

The Tata-Ebasco Consulting Engineering Services' was established based on

partnership with Ebasco India, Ltd for consulting engineering together with its two

associated companies in the year 1961. In the year 1969, a new company under the name

Chemical Terminal Trombay Ltd was formed in participation with other Tata Companies

and Elephanta India Private Ltd to installation of storage tanks on a part of the

Company's ash disposal area at Trombay and the laying of a pipeline connecting thestorage tanks with the Mumbai Port Trust's pier at Pir Pau. TPC sets up its new

manufacturing facility at Bangalore during the year 1980, for commercial production of

electronic items designed by its R&D laboratory. The company constructed a new double

circuit 22/110 KV transmission line in the year 1987 at North Mumbai from Borivli to

Malad to meet the requirements of Municipal Corporation of Greater Mumbai besides

meeting loads in Kandivili, Malad, etc.

TPC has undertaken a 180 MW combined cycle plant at Trombay using gas turbines. In

1989, six new outlets for BEST at 33 KV from Carnac receiving stations were

commissioned during the year. In the same year the company also associated with

Siemens in the erection and commissioned the mechanical and electrical equipment.

VISION AND MISSION:-

Strong values are the base of any laudable

mission and vision is vital to its realisation. Tata

Power's fundamentals have alwa s been ver


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VISION AND MISSION:-

Strong values are the base of any laudable mission and vision is vital to its realization.

Tata Power's fundamentals have always been very clear in this direction.

Vision:-

To be among the top three wind energy companies in the world

To be the most respected brand

To be the best team and place to work at

To be the fastest growing and most profitable business

Mission:-

Being the supplier and partner of choice Achieving excellence in safety, operations and project

management

Focusing on the culture of sustainability

Ensuring growth and delivering value to the stakeholders

Caring for the community

Values:-An organization is built over the values it stands for. At Suzlon we have inculcated values

that provide us the benchmark to carve our vision, develop our mission and lay a strong

foundation to energize the corporate objectives. Suzlons values are an end-to-end

cornerstone of all its commitments, endeavors and progress.

.

Vision:-

To be the most admired Integrated Power and Energy Company delivering

sustainable value to all stakeholders

Mission :-

We will become the most Admired Company delivering sustainable value by:

Being the supplier and partner of choice

Achieving excellence in safety, operations and project management

Focusing on the culture of sustainability

Ensuring growth and delivering value to the stakeholders

Caring for the community

Values:-

Integrity: Honesty, fairness and transparency in our conduct and transactions

Trust: Faith and belief in each other

Care: Being concerned about the well being of all employees

Collaboration: Excellence through teamwork, within employees and partners

Agility: Speedy, responsive and proactive, achieved through empowering

employees

Respect: Treat all stakeholders with respect and dignity

Excellence: Bettering standards continuously, with passion and pride

SUZLON ENERGY LIMITED:-

Suzlon Energy Limited (SEL) has its roots dating back to when it sets up in 10th April of


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Reliance Power Limited (RPL) is part of the Reliance Anil Dhirubhai Ambani Group and

it was incorporated in 17th January of the year 1995 as a private limited company underthe name of Bawana Power Private Limited to develop, construct and operate power

projects domestically and internationally. The Company on its own and through

subsidiaries is currently developing 13 medium and large sized power projects with a

combined planned installed capacity of 28,200 MW, one of the largest portfolios of

power generation assets under development in India.

As at 1st February of the year 1995, the company's name was changed to Reliance

Delhi Power Private Limited. The Company had started a 3740 MW at site Natural Gasbased Combined Cycle Power Plant at Dadri in the year 2003-04. In 23rd January of the

year 2004, again the name of the company was changed to Reliance EGen Private

Limited. Further, name of the company was changed from Reliance Egen Private Limited

to Reliance Energy Generation Private Limited in 5th March 2004. The Company's status

was converted into a public limited company through shareholder resolution in 19th

March of the year 2004 and the name was further changed to Reliance Energy Generation

Limited with effect from 19th March of the year 2004. In November of the year 2006,

RPL had acquired 100% shareholding in Rosa Power Supply Company Limited. The

acquired company, thus become the wholly owned subsidiary of the Company.

During the year 2006-07, the company signed a Joint Communique with Government

of Orissa to set up a 12000 MW coal based pithead power project at Hirma in Distt

Jharsuguda in Orissa. As at 4th July 2007, the company got its present name as Reliance

Power Limited. In January of the year 2008, the company had tapped the capital market

with an initial public offering (IPO) of 260 million equity shares. During March of the

year 2008, Reliance Power had entered into an agreement to buy a coalmine in Indonesia

located in South Sumatra, valued at Rs 200 billion.

capacity of just 3 MW. Now Suzlon is a pioneer in providing end-to-end wind power

solutions. The company's business model comprises the full spectrum of services

including the development, manufacturing, marketing, EPC Project delivery and

operations and maintenance of wind turbine generators around the world. The company

has gone from strength to strength in just a decade of operations, installing over 3

Gigawatt of wind turbine capacity in projects around the world. The Company has, as a

follow-up to its global expansion strategy, successfully entered into new markets such as

Spain, Nicaragua and Turkey with substantial orders, and consolidated its position in

other important markets such as the US, Australia and Brazil with large and repeat

orders, over the last year, Suzlon become a global corporation with operations across 5

continents and many more countries.

Det Norse Veritas (DNV) certifies Suzlon Group with the coveted ISO 9001/2

certificate in the year of 1997. In 1998, the company formed Suzlon Developers Pvt

Limited and Suzlon Wind Farm Services Pvt Limited; both are in under the group of the

company. In the same year 1998, Suzlon bagged its first order of Ghodawat Pan Masala

Products in the state of Maharashtra. The Company made its debut entry in Maharashtra

by commissioning its first Wind Turbine in Maharashtra at site: Vankhusavade, Dist

Satara.


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THEORETICAL FRAMEWORK:-

The theoretical framework is the foundation on which project is based. It is logically

developed, described & elaborated network association among variables deemed relevant

to the problem situation & identified through some processes.

Construct:-

Volatility of Share prices of SUZLON ENERGY, RELIANCE POWER, TATA

POWER

Financial Performance of power sector SUZLON ENERGY, RELIANCE

POWER, TATA POWER

Degree of risk involved in different projects

Variables:-

Dependent Variables:

Financial Performance of power sector(company consider)

- Profit After Tax (PAT)

- Net Worth

Independent Variables:

Share price

Risk Factor

Liquidity trends


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LITERATURE SURVEY:-

Once the area of interest is selected then the researcher should undertake extensive

literature survey connected with the problem or the topic of interest.For this problem, the

abstracting and indexing journals and published or unpublished bibliographic are the first

place to go to. Academic journals, conference proceedings, government reports, books

etc must be tapped depending upon nature of problem.

Conceptual literature:-

Conceptual literature is that which relates with concepts and theories. Help from different

books should be taken for different concepts and theories.

Empirical literature:-

Empirical literature consists of study made by other in the same field. The published data

in newspapers books & magazines available for discussion with people of organization.

Such as:

- Newspapers

- Journals

- Case Studies

- Websites


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Books & Magazines:-

Pandian Punithavathy, (2nd edition), Security analysis and portfoliomanagement Vikas publishing house pvt LTD.(1) , PP 45-48: It explains theGovt. securities and the feature of Govt. securities.

Bhole.L.M, (9th edition), Financial Institutions and Markets- Structure,Growth and Innovations (2), PP 179-214:- This book tells the benefit ofinvestment in debt funds.

Donald E. Fischer, (3th edition) Security Analysis and Portfolio Management,Kalyan Publishers (3), PP 79-92:- It tells the history of debt fund and debtschemes of mutual funds.

Ronald J. Jordan, (4th edition)Security Analysis and Portfolio Management,New Delhi (4),PP 112-132: Itexplains the history of mutual funds, meaning ofmutual funds and its type.

Beri G.C., (4th edition),Marketing Research publishing house, New Delhi (5),PP 68-72: This book helped in understanding the different research designs andanalytical tools used here.

Gupta Shashi.k, (5th edition), Management Accounting, KalyanPublishrs,New Delhi(6), PP 23.1-23.9 :- This book tells about the yield on money

market securities

Hooda R.P., (4th edition), Statistics for Business and Economics, V.K.publication 13 PP.88-92:- This text book helps me to understand the variousmethods of Calculation of multiple regressions and its interpretation.


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Schaums (2004) Statistical outline, Tata McGraw Hill Publishing CompanyLimited14, PP. 45-53: The information regarding the statistical tools and theirlimitations in different fields the research is given in this section. This section

explains why to use multiple regressions and what does correlation means what

are the situations in which correlation can be used.

Kothari, C.R, (2nd edition) Quantitative Techniques, New Age InternationalPublishers, Ansari Road, Daryaganj, New Delhi-11000215, PP.117-132:

JOURNALS: -

Karmakar Madhusudan (16) APRIL JUNE 2009 ., Price Discoveries and

Volatility Spillovers in S&P CNX Nifty Future and its Underlying Index CNX

Nifty,VIKALPA The Journal of Decision Makers, Volume 34, No. 2, , This

article gave me information about the lead lag relationship in return and

volatility between spot and future markets.

Mahakud Jitendera., Kumar Arun Misra (17), APRIL 2009 Effects of

Leverage and Adjustment Costs on Corporate Performance Evidence from

Indian Companies, Journal of Management Research, Volume 9, No. 1, This

article gave researcher information about the leverage ratio of the IndianCompanies that has increased significantly due to easy availability of various

means of finance in globalization period.

Siddiqui Saif. (18) , JANUARY MARCH 2009, Stock Market Integration :

Examining Linkage Between Selected World Markets VISION The Journal of

Business Perspective , volume 13 , No. 1,

This article gave researcher information about the interdependency among major

world stock markets.

Brav Omer (19), FEBRUARY 2009, Access to Capital, Capital Structure, and the

Funding of the Firm,The Journal of Finance Volume IXIV, No. 1, this article

gave researcher information that when compared with public counterparts, private

firms almost exclusively on debt financing, has higher leverage ratios and tend to


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avoid external capital market leading to a greater sensitivity of their capital

structures to fluctuations in performance.

Kaur Kuldip (23), Determinants of Debt Equity Mix Analysis from Indian

FirmsFINANCE INDIA, Volume XXII, No. 2, JUNE 2008 , PP 487 500,

This article threw light on the fact that the corporate finance managers while

deciding about the debt equity mix consider certain internal and external

parameters which seem to influence the capital structure decisions of the firm.

Khan Masood Ahmad, Shahid Ashraf, Shahid Ahmad (24). MARCH 2008,

Causality and Volatility in firm level stock returns and volume in India:

Evidence from National Stock ExchangeFINANCE INDIAvolume XXII No.1,

PP 99-110,

This article gave researcher information about the co movement in stock return

and volume change using NSE data.

Srivastava Sandeep, Yadav Surnedra, Jain P.K. (25) DECEMBER 2007 Effect

of derivative security on volatility A study in context of Indian stock market.

FINANCE INDIA, volume XXI No.4,PP 1271- 1295

This article gave researcher information about the impact of introduction of

derivatives securities on volatility of underlying stock and index.

Chittedi Reddy Krishna. (26) JULY 2009, SENSEX- the Dancing Beauty of

Indian Stock MarketINDIAN JOURNAL OF FINANCE VOLUME 3, No. 7, PP

10 15,

This article gave researcher information about the stock exchange and its history.

Dr. Iqbal, Dr. T. Mallikarjunappa. (27) JULY 2009, Indian stock market


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reaction to quarterly earnings informationINDIAN JOURNAL OF FINANCE,

VOLUME 3, No. 7, PP 43-50,

This article helped researcher to understand the reaction of quarterly information

on the stock exchange of India.

WEBSITES: -

http://money.rediff.com/companies31 this site provided me with balance sheets of

various companies.

http://capitaline.com32

, this website helped me to know about financial position ofcompanies for my study.

myiris.com/shares/company/financial.php?icode... 34, this website helped me to know

about the various RATIO of companies for my study.

demonstrations.wolfram.com/SimulatingAssetPricesWithAGARCH11Model/ 35, this

website helped me to know about GARCH Model for my study.

www.stanford.edu/~wfsharpe/art/djam/djam.htm36, this website helped me to know

about SHARPE Model for my study.

www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdf...37, this

website helped me to know additional information related about SHARPE Model

for my study.

www.statisticallysignificantconsulting.com/Anova.htm38, this website helped me to

know about ANOVA tools for my study.
http://money.rediff.com/companieshttp://capitaline.com/http://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.statisticallysignificantconsulting.com/Anova.htmhttp://www.statisticallysignificantconsulting.com/Anova.htmhttp://www.statisticallysignificantconsulting.com/Anova.htmhttp://www.statisticallysignificantconsulting.com/Anova.htmhttp://www.statisticallysignificantconsulting.com/Anova.htmhttp://money.rediff.com/companieshttp://capitaline.com/http://www.sharpe1.com/sharpe/sharpe.nsf/Files/RMC2RMC3/.../311288B.pdfhttp://www.statisticallysignificantconsulting.com/Anova.htm


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RESEARCH OBJECTIVES: -

PRIMARY OBJECTIVES:

To study the growth & return of various companies of Power sector.

To find out the liquidity position of top companies of power sector.

To study risk and return relationship associated with equity shares of these

companies

To study volatility in Share Price of various companies.

SECONDARY OBJECTIVES:

To study the share price movement of these companies

To study the financial performance of the consider company on the basis of PAT,

NET WORTH

To check out the growth prospect of the companies by SHARPE MODEL.


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RESEARCH METHODOLOGY:-

Research is a systematic and continuous method of defining a problem, collecting the

facts and analyzing them, reaching conclusion forming generalizations.

Research is defined as a scientific & systematic search for pertinent information on a

specific topic. Research is an art of scientific investigation. Research is a systemized

effort to gain new knowledge. It is a careful inquiry especially through search for new

facts in any branch of knowledge. The search for knowledge through objective and

systematic method of finding solution to a problem is a research.

THE RESEARCH PROCESS


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RESEARCH DESIGN: -A research design is the game plan or blue print and specifications for conducting a

research investigation.

As stated by Julian Simon:

There is never a single, standard, correct method of carrying out a piece of research. Do

not wait to start your research until you find out the proper approach, because there are

many ways to tackle a problem--some good, some bad, but probably several good ways.There is no single perfect design. A research method for a given problem is not like the

solution to a problem in algebra. It is more like a recipe for beef stroganoff; there is no

one best recipe.

Exploratory Qualitative Research

2

PRELIMINARY

DATA

GATHERING

Interviewing

Literature

Survey

3

PROBLEM

DEFINITION

Research

Problem

Delineated

4

THEORETICA

L

FRAMEWORK

Variables

clearly

identified andlabelled

5

GENERATION

OF

HYPOTHESE

S

6

SCIENTIFIC

RESEARCH

DESIGN

1

OBSERVATIO

N

Broad area of

research

interest

identified

7

DATA

COLLECTIO

ANALYSIS

INTERPRETA

8

DEDUCTIO

Hypothese

substantia

? Research

question

answered?

9

Report

writing

10

Report

Present

ation

11

Manag

erial

decisio

n

making

YesNO


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Descriptive Quantitative Research

Causal Quantitative Research

METHODOLOGY AND DATA ANALYSIS: -

Research Design:-Descriptive Design

Time Horizon: - Cross-Sectional Design

Type of Investigation: - Causal Study

Study Setting: - Contrived Setting

Research Place: - Yamuna Nagar

Sampling Design: - Judgment and Convenience Sampling.

Data: - Secondary data


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FLOW CHART: -


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LIMITATIONS OF THE STUDY: -

Time Constraints

During our dissertation report, the time allotted to us was not sufficient to

complete such a big report. So due time constraints I may not be able to give up to

my fullest.

Resource Constraints

Being a student, I was not having sufficient resources for conducting the

dissertation report.

Use of Statistical Tools

Being a student, the tools I have used in my study may not be sufficient for

analyzing the performance of top two players of the telecom companies.


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Chances of Errors

Chances of errors may be there since I have used secondary data for the study of

my dissertation report.

HYPOTHESIS DEVELOPMENT: -

There are two types of hypothesis:

Null hypothesis

Alternative hypothesis

Null hypothesis (H0): In test of hypothesis we always begin with an assumption or

hypothesis this is called null hypothesis. The null hypothesis asserts that there is no

significant difference between the sample static and the population parameter and

whatever the observed difference is there, is merely due to fluctuations in sampling from

same population.

Alternative hypothesis (H1): Any hypothesis different then the null hypothesis is called

an alternative hypothesis. The two hypothesis H0 & H1 are such that if one is accepted,

the other is rejected.


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HYPOTHESIS OF THE STUDY: -

H0: There is no significant impact of share prices on the PAT of the company.

H1: There is significant impact of share prices on the PAT of the company.

H0: There is no significant impact of Risk on the PAT of the company.

H1: There is significant impact of Risk on the PAT of the company.

H0: There is no significant impact of share prices on the Net Worth of the company.

H1: There is significant impact of share prices on the Net Worth of the company.

H0: There is no significant impact of Risk on the Net Worth of the company.

H1: There is significant impact of Risk on the Net Worth of the company.


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ANOVA: -

Variables:

PAT (Profit After Tax)

Net Worth

Risk

Share Price

Suzlon Energy Limited: -

H0 :There Is No Significance Impact Of Risk On PATANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 417727.320 1 417727.320 1.873 .402a

Residual 222985.098 1 222985.098

Total 640712.418 2

a. Predictors: (Constant), risk

b. Dependent Variable: pat

Interpretation

In the above table the value of sig. is greater than the standard significant level that is 5%

So as a result we reject the null hypothesis & accept the alternate which symbolises the

that predictors are quite significant. On the other hand if we compare the value of F with

the table value then the same result can be concluded as to reject h0 the null hypothesis.

H0: There Is No Significance Impact Of Share Price On PAT


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ANOVAb


1 Regression 143630.453 1 143630.453 .289 .686a

Residual 497081.966 1 497081.966

Total 640712.418 2

a. Predictors: (Constant), Shareprice


InterpretationIn the above table the value of sig. is greater than the standard significant level that is 5%

so as a result we reject the null hypothesis & accept the alternate which symbolises the

predictors are quite significant. On the other hand if we compare the value of F with the

table value then the same result can be concluded as to reject h0 the null hypothesis.

H0: There Is No Significance Impact Of Share Price On Net Worth

ANOVAb


1 Regression 4923364.154 1 4923364.154 3.526 .312a

Residual 1396341.856 1 1396341.856

Total 6319706.010 2


b. Dependent Variable: Networth

Interpretation





H0: There Is No Significance Impact of Risk on Net worth


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ANOVAb


1 Regression 9874.983 1 9874.983 1.186 .473a

Residual 8327.381 1 8327.381

Total 18202.365 2

a. Predictors: (Constant), shareprice


Interpretation





H0 :There Is No Significance Impact Of Risk On PAT

ANOVAb


1 Regression 6299.247 1 6299.247 .529 .600a

Residual 11903.117 1 11903.117

Total 18202.365 2






table value then the same result can be concluded as to reject h0 the null hypothesis

H0 :There Is No Significance Impact Of Risk On Net Worth

ANOVAb


1 Regression 4288.153 1 4288.153 .000 .996a

Residual 1.209E8 1 1.209E8

Total 1.210E8 2



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ANOVAb


1 Regression 4288.153 1 4288.153 .000 .996a

Residual 1.209E8 1 1.209E8

Total 1.210E8 2

b. Dependent Variable: networth

Interpretation





H0 :There Is No Significance Impact Of share Price On Net WORTH

ANOVAb


1 Regression 1.192E8 1 1.192E8 68.934 .076a

Residual 1729493.887 1 1729493.887

Total 1.210E8 2


b. Dependent Variable: networth

Interpretation

In the above table the value of sig. is greater than the standard significant level that is 5%So as a result we reject the null hypothesis & accept the alternate which symbolises the



Tata Power Limited: -

H0 :There Is No Significance Impact Of Risk On PAT


30/103

ANOVAb


1 Regression 17112.500 1 17112.500 1.358 .452a

Residual 12604.167 1 12604.167

Total 29716.667 2



Interpretation





H0 :There Is No Significance Impact Of Share Price On PAT

ANOVAb


1 Regression 12501.294 1 12501.294 .726 .551a

Residual 17215.373 1 17215.373

Total 29716.667 2

a. Predictors: (Constant), share price


Interpretation





H0: There Is No Significance Impact of Risk on Net Worth


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ANOVAb

Model Sum of Squares Df Mean Square F Sig.

1 Regression 1797408.000 1 1797408.000 .861 .524a

Residual 2088600.000 1 2088600.000

Total 3886008.000 2

Predictors: (Constant), risk

H0 :There Is No Significance Impact Of Share Price On Net Worth

ANOVAb


1 Regression 2075017.280 1 2075017.280 1.146 .478a

Residual 1810990.720 1 1810990.720

Total 3886008.000 2

a. Predictors: (Constant), share price

b. Dependent Variable: net worth





DATA COLLECTION: -

After the research problem has been identified and selected the next step is to gather the

requisite data. While deciding about the method of data collection to be used for the

researcher should keep in mind two types of data VIZ. primary and secondary


32/103

1. Primary Data: All primary data is given by my mentor and also discussing

certain concepts with its employees.

2. Secondary data: It is the data, which has already collected by some organization

for some purpose or research study. The data for my study has been collected

from various. Secondary data means that data that are already available i.e. refers

to data which has already been collected and analyzed by someone else. The

sources used in this case are-

Books

Journals

Magazines

Internet sources

Newspapers

ANALYTICAL TOOLS

RATIO ANALYSIS

FINANCIAL ANALYSIS:-


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Financial analysis is the process of identifying the financial strengths and weaknesses of

the firm and establishing relationship between the items of the balance sheet and profit &

loss account.

Financial ratio analysis is the calculation and comparison of ratios, which are derivedfrom the information in a companys financial statements. The level and historical trends

of these ratios can be used to make inferences about a companys financial condition, its

operations and attractiveness as an investment. The information in the statements is used

by

Trade creditors, to identify the firms ability to meet their claims i.e. liquidity

position of the company.

Investors, to know about the present and future profitability of the company and

its financial structure.

Management, in every aspect of the financial analysis. It is the responsibility of

the management to maintain sound financial condition in the company.

THE VIEW OF FUNCTIONAL CLASSIFICATION OF THE RATIOS IS:-

Liquidity ratio

Leverage ratio


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Activity ratio

Profitability ratio

LIQUIDITY RATIOS

Liquidity refers to the ability of a concern to meet its current obligations as & when there

becomes due. The short term obligations of a firm can be met only when there are

sufficient liquid assets. The short term obligations are met by realizing amounts from

current, floating (or) circulating assets The current assets should either be calculated

liquid (or) near liquidity. They should be convertible into cash for paying obligations of

short term nature. The sufficiency (or) insufficiency of current assets should be assessed

by comparing them with short-term current liabilities. If current assets can pay off current

liabilities, then liquidity position will be satisfactory.

To measure the liquidity of a firm the following ratios can be calculated

Current ratio

Quick (or) Acid-test (or) Liquid ratio

Absolute liquid ratio (or) Cash position ratio

(a) CURRENT RATIO: -

Current ratio may be defined as the relationship between current assets and current

liabilities. This ratio also known as Working capital ratio is a measure of general liquidity


35/103

and is most widely used to make the analysis of a short-term financial position (or)

liquidity of a firm.

Interpretation:-

This ratio indicates the current assets are fluctuating continuously and payment of

current liabilities is also fluctuating.

In the condition of SUZLON energy the current ration of company continuous

decreasing from 1.49 to 0.82 that is not good situation for SUZLON energy.

But in condition of RPOWER the current ratio is going upward. That is good for

business. Because in the year 2008, 2009 they are totally concentrate on maintaining

liquidity. So the current ratio in March 09 is 27.23

(b) QUICK RATIO: -

Quick ratio is a test of liquidity than the current ratio. The term liquidity refers to the

ability of a firm to pay its short-term obligations

Company Name March 07 March 08 March 09

Suzlon Energy 1.49 1.46 0.82

Rpower 0.44 12.60 27.23

Tata Power 2.25 2.04 2.10


36/103

Quick ratio = Quick or liquid assets / Current liabilities

Interpretation: -

This ratio indicates the liquid assets are fluctuating continuously and payment of

current liabilities is also fluctuating.

In the condition of SUZLON energy the quick ratio of company continuous

decreasing but in the year 09 that ratio is going down allot same as TATA POWER

But in condition of RPOWER the quick ratio is going upward. That is good for

business.

PROFIT AFTER TAX (PAT)

Company Name March 07 March 08 March 09

Suzlon Energy 2.40 2.12 2.19

Rpower 0.44 12.60 27.33

Tata Power 2.00 1.75 1.77


37/103

March 07 March 08 March 09

Suzlon Energy 1062.34 1520.01 394.43

Tata Power 692 877 922

Reliance Power 0.16 75.89 189.69

Interpretation: -

But in condition of Tata power the PAT is going upward. That is good for business.Because in the year 2009 they are totally concentrate on increasing the profit. So the

PAT in March 09 is 922 crore

But in condition of Suzlon Energy the PAT is going downward. That is not good for

business. Because in the year 2009 they are totally not concentrate on the profit. So

the PAT in March 09 is going down up to 394 crore for 1520 crore. that is not good

for business

Average Share Price


38/103


Suzlon Energy 261.92 152.69 85.76

Tata Power 952.71 951.56 1236.34

Reliance Power 0.00 174 154.26

NET WORTH


39/103


Suzlon Energy 3701.58 6947.66 6580.32

Tata Power 4467 6363 7185

Reliance Power 200.05 13542.68 13792.81

What Is GARCH?

GARCH stands for Generalized Autoregressive Conditional Heteroscedasticity. Loosely


40/103

speaking, you can think of heteroscedasticity as time-varying variance (i.e., volatility).

Conditional implies a dependence on the observations of the immediate past, and

autoregressive describes a feedback mechanism that incorporates past observations into

the present. GARCH then is a mechanism that includes past variances in the explanation

of future variances. More specifically, GARCH is a time-series technique that allows

users to model the serial dependence of volatility.

In this manual, whenever a time series is said to have GARCH effects, the series is

heteroscedastic, i.e., its variances vary with time. If its variances remain constant with

time, the series is homoscedastic.

Why Use GARCH?

GARCH modeling builds on advances in the understanding and modeling of volatility in

the last decade. It takes into account excess kurtosis (i.e., fat tail behavior) and volatility

clustering, two important characteristics of financial time series. It provides accurate

forecasts of variances and covariances of asset returns through its ability to model time-

varying conditional variances. Therefore, you can apply GARCH models to such diverse

fields as:

Risk management

Portfolio management and asset allocation

Option pricing

Foreign exchange

The term structure of interest rates

You can find highly significant GARCH effects in equity markets for: Individual stocks

Stock portfolios and indices

Equity futures markets


41/103

These effects are important in such areas as value-at-risk (VAR) and other risk

management applications that concern the efficient allocation of capital. You can use

GARCH models to examine the relationship between long- and short-term interest rates.

As the uncertainty for rates over various horizons changes through time, you can also

apply GARCH models in the analysis of time-varying risk premiums. Foreign exchange

markets, which couple highly persistent periods of volatility and tranquility with

significant fat-tail behavior , are particularly well-suited for GARCH modeling.

GARCH Limitations

Although GARCH models are useful across a wide range of applications, they do have

limitations:

GARCH models are only part of a solution. Although GARCH models are usually

applied to return series, financial decisions are rarely based solely on expected

returns and volatilities.

GARCH models are parametric specifications that operate best under relatively

stable market conditions .GARCH is explicitly designed to model time-varying

conditional variances. However, GARCH models often fail to capture highly

irregular phenomena. These include wild market fluctuations (e.g., crashes and

subsequent rebounds) and other highly unanticipated events that can lead to

significant structural change.

GARCH models often fail to fully capture the fat tails observed in asset return

series. Heteroscedasticity explains some of the fat-tail behavior, but not all of it.

To compensate for this limitation, fat-tailed distributions such as Student's t have

been applied to GARCH modeling.

http://www.coolavenues.com/forums/showthread.php?t=15134 - 76k

GARCH MODEL TO MEASURE VOLATILITY

(A.)VOLATILITY IN NSE INDEX & RELIANCE POWER INDEX:


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Coefficient Std. Error z-Statistic Prob.

Omega 5646.399 54238.69 0.104103 0.917088

alpha_1 0.000118 8.619786 1.36E-05 0.999989

beta_1 0.899101 7.881538 0.114077 0.909177

INTERPRETATION

In the above graphs there could be seen less fluctuations in the Volatility Of Daily

Settlement Prices Of reliance power in NSE & the same is represented by the value of

Alpha & Beta, the less fluctuations in the daily settlement prices represents & symbolises


43/103

the stability as well as the efficiency, which is a good symbol for the market efficiency.

But in the future time period there could be seen more fluctuations in the time period.

As the values in the table are around 1 which is a good symbol of efficiency in the NSE

market in India.

Some Highlights:

Value of Beta is very much less as near around .899 which is a good symbol of stability

in the market.

(B.) VOLATILITY IN NSE INDEX & SUZLON ENERGY INDEX:


44/103

INTERPRETATION

In the above graphs there could be seen high fluctuations in the Volatility Of Daily


Omega 5897.349 23752.2 0.248286 0.803913

alpha_1 0.000381 3.980189 9.57E-05 0.999924

beta_1 0.957987 3.930798 0.243713 0.807453


45/103

Settlement Prices Of suzlon energy in NSE & the same is represented by the value of

Alpha & Beta, the high fluctuations in the daily settlement prices represents &

symbolises the instability as well as the inefficiency, which is not a good symbol for the

market efficiency. But in the future time period there could be seen more stability in the

time period.


market in India.

Some Highlights:


in the market.

(C.) VOLATILITY IN NSE INDEX & TATA POWER INDEX:


46/103


Omega 55202.45 3185590 0.017329 0.986174

alpha_1 0.0127 20.37593 0.000623 0.999503

beta_1 0.934609 18.65871 0.05009 0.960051

INTERPRETATION

In the above graphs there could be seen high fluctuations in the Volatility Of Daily

Settlement Prices Of Tata power in NSE & the same is represented by the value of Alpha

& Beta, the high fluctuations in the daily settlement prices represents & symbolises the


47/103

instability as well as the inefficiency, which is not a good symbol for the market

efficiency. But in the future time period there could be seen more fluctuations in the time

period.


market in India.

Some Highlights:


in the market.

ALPHA ANALYSIS


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Suzlon Energy Tata Power Reliance Power

Alpha 0.00038 0.0127 0.00012

Interpretation:

According to ALPHA Analysis the reliance Power beta 0.00012 is very low as compare

to suzlon Energy Beta 0.00038 & Tata Power Beta 0.0127 so according to beta analysis

level of risk in Reliance power is very low. So its good to invest in Reliance Power

BETA ANALYSIS


49/103

Suzlon Energy Tata Power Reliance Power

Beta 0.957987 0.934609 0.899101

Interpretation:

According to Beta Analysis the reliance Power beta 0.899101 is very low as compare to

suzlon Energy Beta 0.957987 & Tata Power Beta 0.934609 so according to beta analysis

level of risk in Reliance power is very low. so its good to invest in Reliance Power

MEASURE FOR SHARPE'S PORTFOLIOS PERFORMANCE


50/103

The Sharpe's index measures the risk premium of the portfolio relative to the total amount of

risk in portfolio. The Sharpe's index is measured as

S = RP Rf/p

where,

S = Sharpe's Index

rp = average monthly return of fund. rf = risk free return *.

* risk free return (rf) is taken as 6.00% per annum

(A.) PERFORMANCE EVALUATION OF SUZLON ENERGY

(APR-07 TO MAR-08)


51/103

Nifty Index

Return(x)

X2 Suzlon Stock Return

(y)

Y2 xy

Apr-07 3633.6 160.37

May-

07

4150.85 14.23519375 202.640

7

200.39 24.95479204 622.741

6

355.236

3Jun-07 4297.05 3.522170158 12.4056

8

217.06 8.318778382 69.2020

7

29.3001

5

Jul-07 4313.75 0.388638717 0.15104 250.43 15.37362941 236.348

5

5.97478

8

Aug-07 4345.85 0.744132136 0.55373

3

205.73 -17.84929921 318.597

5

-

13.2822

Sep-07 4474.75 2.966048069 8.79744

1

211.61 2.858115005 8.16882

1

8.47730

6

Oct-07 5068.95 13.27895413 176.330

6

244.14 15.37261944 236.317

4

204.132

3Nov-07 5866.45 15.73304136 247.528

6

328.66 34.61948063 1198.50

8

544.669

7

Dec-07 5865 -0.024716822 0.00061

1

316.51 -3.69682955 13.6665

5

0.09137

4

Jan-08 6144.35 4.763000853 22.6861

8

326.23 3.070993018 9.43099

8

14.6271

4

Feb-08 5317.25 -13.46114723 181.202

5

314.49 -3.598688042 12.9505

6

48.4424

7

Mar-08 4953 -6.850345573 46.9272

3

260.15 -17.2787688 298.555

9

118.365

5

Total 58430.8

5

X

=35.29496

(X) =

1245.73

5

3035.7

7

(Y) =

62.14482233

(Y) =

3861.97

9

XY =

2193.4

X = 2.94

Y = 5.18

Standard Deviation

= yN


52/103

=17.93

Sharpe's index S = Rp Rf /p

Rf = 6.0%

p = 17.93

Rp = Y = 5.18

S = (5.18-.06)/17.93

S = 0.29


53/103

(B.)PERFORMANCE EVALUATION OF SUZLON ENERGY

(APR-08 TO MAR-09)

Nifty Index Return

(x)

X2 Suzlon Stock Return

(y)

Y2 xy

Apr-08 4739.55 275.35

May-08 5228.2 10.31005053 106.297

1

290.18 5.385872526 29.0076

2

55.52862

Jun-08 4739.6 -9.345472629 87.3378

6

265.54 -8.491281274 72.1018

6

79.35504

Jul-08 3896.75 -17.78314626 316.240

3

200.05 -24.66295097 608.261

2

438.5849

Aug-08 4413.55 13.262334 175.889

5

231.99 15.9660085 254.913

4

211.7465

Sep-08 4348.65 -1.470471616 2.16228

7

216.57 -6.646838226 44.1804

6

9.773987

Oct-08 3950.75 -9.149966081 83.7218

8

155.62 -28.14332548 792.046

8

257.5105

Nov-08 3043.85 -22.9551351 526.938

2

45.08 -71.03200103 5045.54

5

1630.549

Dec-08 2682.9 -11.8583373 140.620

2

39.45 -12.48890861 155.972

8

148.0977

Jan-09 3033.45 13.06608521 170.722

6

66.3 68.0608365 4632.27

7

889.2887

Feb-09 2766.65 -8.795266116 77.3567

1

44.45 -32.95625943 1086.11

5

289.8591

Mar-09 2674.6 -3.327128477 11.0697

8

38.55 -13.27334083 176.181

6

44.16211

Total 45518.5 X =-

48.04645385

(X) =

2308.46

2

1869.13 (Y) =

-108.2821883

(Y) =

11725.0

3

XY =

5202.575

X = 4.00

Y = -9.02

Standard Deviation


54/103

=31.25


Rf = 6.0%

p = 31.25

Rp = Y = -9.02

S = (-9.02-.06)/31.25

S = -0.29

= yN


55/103

(C.)PERFORMANCE EVALUATION OF SUZLON ENERGY

(APR-08 TO MAR-09)

Nifty Index Return

(x)

X2 Suzlon Share Return

(y)

Y2 xy

Apr-09 3060.35 46.55

May-09 3654 19.39810806 376.286

6

65.9 41.56820623 1727.91

6

806.3446

Jun-09 4529.9 23.9709907 574.608

4

113.75 72.61001517 5272.21

4

1740.534

Jul-09 4340.9 -4.172277534 17.4079 106.75 -6.153846154 37.8698

2

25.67555

Aug-09 4711.4 8.535096409 72.8478

7

95.65 -10.39812646 108.121 -88.749

Sep-09 4625.35 -1.826421021 3.33581

4

95.25 -0.418191323 0.17488

4

0.763793

Oct-09 5083.95 9.914925357 98.3057

4

92.25 -3.149606299 9.92002 -31.2281

Nov-09 4563.9 -10.22925088 104.637

6

58.25 -36.85636856 1358.39

2

377.013

Dec-09 5122 12.22857644 149.538

1

81.15 39.31330472 1545.53

6

480.7458

Jan-10 5232.2 2.151503319 4.62896

7

89.9 10.78250154 116.262

3

23.19859

Feb-10 4899.7 -6.354879401 40.3844

9

78.55 -12.62513904 159.394

1

80.23124

Mar-10 5017 2.394024124 5.73135

2

72.65 -7.511139402 56.4172

2

-17.9818

Total 54840.6

5

X

=56.01039557

(X) =

3137.16

4

996.6 (Y) =

87.16161042

(Y) =

7597.14

6

XY =

4881.956

X = 4.67

Y = 7.26

Standard Deviation


56/103

=25.16


Rf = 6.0%

p = 25.16

Rp = Y = 7.26

S = (7.26-.06)/25.16

S = 0.29

= yN


57/103

(D.)PERFORMANCE EVALUATION OF RELIANCE POWER

(APR-08 TO MAR-09)

Nifty Index Return

(x)

X2 Rpower Share Return

(y)

Y2 xy

Apr-08 4739.55 318.35

May-08 5228.2 10.31005053 106.297

1

398.77 25.26150463 638.143

6

260.4474

Jun-08 4739.6 -9.345472629 87.3378

6

233.32 -41.490082 1721.42

7

387.7444

Jul-08 3896.75 -17.78314626 316.240

3

131.88 -43.4767701 1890.23 773.1538

Aug-08 4413.55 13.262334 175.889

5

167.18 26.76675766 716.459

3

354.9897

Sep-08 4348.65 -1.470471616 2.16228

7

156.15 -6.597679148 43.5293

7

9.7017

Oct-08 3950.75 -9.149966081 83.7218

8

154.41 -1.11431316 1.24169

4

10.19593

Nov-08 3043.85 -22.9551351 526.938

2

107.06 -30.66511236 940.349

1

703.9218

Dec-08 2682.9 -11.8583373 140.620

2

112.04 4.651597235 21.6373

6

-55.1602

Jan-09 3033.45 13.06608521 170.722

6

122.37 9.219921457 85.0069

5

120.4683

Feb-09 2766.65 -8.795266116 77.3567

1

101.47 -17.07934951 291.704

2

150.2174

Mar-09 2674.6 -3.327128477 11.0697

8

98.1 -3.321178673 11.0302

3

11.04999

Total 45518.5 X =-

48.04645385

(X) =

2308.46

2

2101.1 (Y) =

-77.84470398

(Y) =

6059.79

8

XY =

3740.162

X = 4.00

Y = -6.49

Standard Deviation


58/103

=22.47


Rf = 6.0%

p = 22.47

Rp = Y = -6.49

S = (-6.49-.06)/22.47

S = -0.29

= yN


59/103

(E.)PERFORMANCE EVALUATION OF RELIANCE POWER

(APR-09 TO MAR-10)

Nifty Index Return

(x)

X2 Rpower Share Return

(y)

Y2 xy

Apr-09 3060.35 103.88

May-09 3654 19.39810806 376.2866 127.53 22.76665383 518.3205 441.63

Jun-09 4529.9 23.9709907 574.6084 183.63 43.98964949 1935.089 1054.475

Jul-09 4340.9 -4.172277534 17.4079 170.16 -7.335402712 53.80813 30.60534

Aug-09 4711.4 8.535096409 72.84787 169.55 -0.358486131 0.128512 -3.05971

Sep-09 4625.35 -1.826421021 3.335814 161.23 -4.907107048 24.0797 8.962443

Oct-09 5083.95 9.914925357 98.30574 167.38 3.814426596 14.54985 37.81975

Nov-09 4563.9 -10.22925088 104.6376 138.55 -17.22428008 296.6758 176.1915

Dec-09 5122 12.22857644 149.5381 146.03 5.398773006 29.14675 66.01931

Jan-10 5232.2 2.151503319 4.628967 155.53 6.505512566 42.32169 13.99663

Feb-10 4899.7 -6.354879401 40.38449 147.07 -5.439465055 29.58778 34.56714

Mar-10 5017 2.394024124 5.731352 139.89 -4.882028966 23.83421 -11.6877

Total 54840.65 X

=56.01039557

(X) =

3137.164

1810.43 (Y) =

42.3282455

(Y) =

1791.68

XY =

2370.822

X = 4.67

Y = 3.53

Standard Deviation

=12.22


Rf = 6.0%

p = 12.22

= yN


60/103

Rp = Y = 3.53

S = (3.53-.06)/12.22

S = 0.28


61/103

(F.)PERFORMANCE EVALUATION OF TATA POWER (APR-

07 TO MAR-08)

Nifty Index Return

(x)

X2 Tata

Power

Share return

(y)

Y2 xy

Apr-07 3633.6 506.79

May-07 4150.85 14.23519375 202.6407 605.82 19.54063813 381.8365 278.1648

Jun-07 4297.05 3.522170158 12.40568 589.03 -2.771450266 7.680937 -9.76152

Jul-07 4313.75 0.388638717 0.15104 672.75 14.21319797 202.015 5.523799

Aug-07 4345.85 0.744132136 0.553733 706.31 4.988480119 24.88493 3.712088

Sep-07 4474.75 2.966048069 8.797441 684.9 -3.031246903 9.188458 -8.99082

Oct-07 5068.95 13.27895413 176.3306 901.96 31.69221784 1004.397 420.8395

Nov-07 5866.45 15.73304136 247.5286 1230.44 36.41846645 1326.305 572.9732

Dec-07 5865 -0.024716822 0.000611 1257.29 2.182146224 4.761762 -0.05394

Jan-08 6144.35 4.763000853 22.68618 1517.8 20.71996119 429.3168 98.68919

Feb-08 5317.25 -13.46114723 181.2025 1322.09 -12.89432073 166.2635 173.5723

Mar-08 4953 -6.850345573 46.92723 1313.87 -0.621742847 0.386564 4.259153

Total 58430.85 X

=35.29496954

(X) =

1245.735

11309.05 (Y) =

110.4363472

(Y) =

12196.19

XY =

3897.848

X = 2.95

Y = 9.20

Standard Deviation

=31.88


Rf = 6.0%

p = 31.88

= yN


62/103

Rp = Y = 9.20

S = (9.20-.06)/31.88

S = 0.29

(G.)PERFORMANCE EVALUATION OF TATA POWER (APR-

08 TO MAR-09)

Nifty Index Return

(x)

X2 Tata

Power

Share Return

(y)

Y2 xy

Apr-08 4739.55 1171.86

May-08 5228.2 10.31005053 106.297

1

1428.24 21.87804004 478.648

6

225.5637

Jun-08 4739.6 -9.345472629 87.3378

6

1341.69 -6.059905898 36.7224

6

56.63268

Jul-08 3896.75 -17.78314626 316.240

3

1026.04 -23.52629892 553.486

7

418.3716

Aug-08 4413.55 13.262334 175.889

5

1132.27 10.35339753 107.192

8

137.3102

Sep-08 4348.65 -1.470471616 2.16228

7

1034.27 -8.655179418 74.9121

3

12.7272

Oct-08 3950.75 -9.149966081 83.7218

8

933.7 -9.723766521 94.5516

4

88.97213

Nov-08 3043.85 -22.9551351 526.938

2

701.22 -24.89878976 619.949

7

571.5551

Dec-08 2682.9 -11.8583373 140.620

2

656.71 -6.347508628 40.2908

7

75.2709

Jan-09 3033.45 13.06608521 170.722

6

770.34 17.3029191 299.391 226.0814

Feb-09 2766.65 -8.795266116 77.3567

1

751.81 -2.405431368 5.7861 21.15641

Mar-09 2674.6 -3.327128477 11.0697

8

711.52 -5.359066785 28.7196 17.8303

Total 45518.5 X =-

48.04645385

(X) =

2308.46

2

11659.67 (Y) =

-37.44159064

(Y) =

1401.87

3

XY =

1798.936


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X = 4.00

Y = -3.12

Standard Deviation

=10.80


Rf = 6.0%

p = 10.80

Rp = Y =- 3.12

S = (-3.12-.06)/10.80

S =- 0.29

(H.)PERFORMANCE EVALUATION OF TATA POWER (APR-

09 TO MAR-10)

Nifty Index

Return (x)

X2 Tata Power Share Return (y) Y2

Apr-09 3060.35 788.4

May-09 3654 19.39 376.2866 912.77 15.77498732 248.8502

Jun-09 4529.9 23.97 574.6084 1080.75 18.40332176 338.6823

Jul-09 4340.9 -4.172 17.4079 1152.06 6.598195697 43.53619

Aug-09 4711.4 8.53 72.84787 1337.44 16.09117581 258.9259

Sep-09 4625.35 -1.826 3.335814 1309.08 -2.120468956 4.496389

Oct-09 5083.95 9.91 98.30574 1294.98 -1.077092309 1.160128

Nov-09 4563.9 -10.22 104.6376 1337.34 3.27109299 10.70005

Dec-09 5122 12.22 149.5381 1357.26 1.48952398 2.218682

Jan-10 5232.2 2.15 4.628967 1390.34 2.43726331 5.940252

Feb-10 4899.7 -6.35 40.38449 1293.81 -6.942906052 48.20394

= yN


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Mar-10 5017 2.39 5.731352 1247.74 -3.560801045 12.6793

Total 54840.65 X

=56.01039557

(X)

=3137.164

14501.97 (Y) =50.364 (Y)

=2536.562

X = 4.67

Y = 4.20

Standard Deviation

=14.53


Rf = 6.0%

p = 14.53

Rp = Y = 4.20

S = (4.20-.06)/14.53

S = 0.28

SHARPE MODEL:-

= yN


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Suzlon Energy 0.29 -0.29 0.29

Tata Power 0.29 -0.29 0.28

Reliance Power 0.00 -0.29 0.28

Interpretation:-

The Sharpe Ratio is a measure of the risk-adjusted return of an investment.

Mathematically the Sharpe ratio is the returns generated over the risk free rate, per unit of

risk. Risk in this case is taken to be the fund's standard deviation. It is thus one single

number, which represents the tradeoff between risks and returns. A higher Sharpe ratio is

therefore better as it represents a higher return generated per unit of risk. As per this

SUZLON ENERGY has highest Sharpe Ratio this indicate SUZLON ENERGY stock

generate highest return per unit of risk.


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STATISTICAL TOOL

An educated citizen needs an understanding of basic statistical tool to function in a world

that is becoming increasingly dependent on quantitative information. Statistics means

numerical description to most people. In fact the term statistics is generally used to mean

numerical facts and figures such as agriculture production during a year, rate of inflation

and so on. However as a subject of study, statistics refers to the body of principles and

procedures developed for the collection, classification, summarization and interpretation

of numerical data and for the use of such data.

MEANING:-

Broadly speaking, the term statistics has been generally used in two senses:-

Plural Sense

Singular Sense

Plural sense refers to the numerical data. Singular Sense refers to a Science in which

we deals with the techniques of collecting, classifying, presenting, analyzing and

interpreting the data, the concept in its singular sense, refers to Statistical Method.


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PURPOSE:-

Without the assistance of Statistical Method, an organization would find it

impossible to make sense of the huge data. The purpose of statistics is to:-

Manipulate

Summarize

Investigate

The data so that useful decision making information results could be found out. In fact,

every business manager needs a sound background of statistics. Statistics is a set of

Decision Making techniques which aids businessman in drawing inferences from the

available data. Statistical tools are the basic measures, which helps in defining the

relation between different items, present, past and future trend of the future trend of the

particular business etc. A wide variety of statistical tools are available and any of them

can be used by any businessman depending upon the nature of his trade.

During my study the tools that I am likely to use are as follows:-

CORRELATION

REGRESSION

RELIABILTY ANALYSIS

GARCH MODEL

ANOVA

SHARPE MODEL


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CORRELATION

Correlation analysis deals with the association between two or more variables -Simpson and Kafka.

If two or more quantities vary in sympathy, so that movement in one tends to be

accompanied by corresponding movements in the other, then they are said to be

correlated-Conner.

Correlation analysis attempts to determine the degree of relationship between

variables.

WHY TO USE CORRELATION: Different type of statistical tool are available but my

main motive is to find out the relationship between reality index with Sensex, Nifty

thats why I use this Particular type of tool only

COEFFICIENT OF CORRELATION IS GIVEN BY:

R=x.yvx2.y2


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TOOLS APPLIED

(A.) CORRELATION

Variables:


Net Worth

Risk

Share Price

TATA POWER

Correlations

networth shareprice risk pat

Networth Pearson

Correlation1 .731 -.680 .994

Sig. (2-tailed) .478 .524 .072

N 3 3 3 3

shareprice Pearson

Correlation.731 1 .004 .649

Sig. (2-tailed) .478 .998 .551

N 3 3 3 3

Risk Pearson

Correlation-.680 .004 1 -.759

Sig. (2-tailed) .524 .998 .452

N 3 3 3 3

Pat Pearson

Correlation.994 .649 -.759 1

Sig. (2-tailed) .072 .551 .452

N 3 3 3 3

INTERPRETATION

To interpret the correlation coefficient, we examine the coefficient & its associated

significance value. It was hypothesized that


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there is a +ve Moderate degree of correlation between the Net Worth, Share

Prices is .731,

there is a ve Moderate degree of correlation between Net Worth & Risk is -.680,

there is a +ve high degree of correlation between the PAT & Net Worth is .994,

there is a +ve Moderate degree of correlation between Share Price & PAT is .649,

there is a +ve Low Degree Of correlation between the Share Price & Risk is .004,

SUZLON ENERGY


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Correlations

Networth Shareprice risk pat

Networth Pearson Correlation 1 -.883 -.587 -.004

Sig. (2-tailed) .312 .601 .998

N 3 3 3 3Shareprice Pearson Correlation -.883 1 .137 .473

Sig. (2-tailed) .312 .912 .686

N 3 3 3 3

Risk Pearson Correlation -.587 .137 1 -.807

Sig. (2-tailed) .601 .912 .402

N 3 3 3 3

Pat Pearson Correlation -.004 .473 -.807 1

Sig. (2-tailed) .998 .686 .402

N 3 3 3 3

INTERPRETATION



there is a -ve high degree of correlation between the Net Worth, Share Prices is

-.883,

there is a ve Moderate degree of correlation between Net Worth & Risk is -.587,

there is a -ve low degree of correlation between the PAT & Net Worth is -.004,


there is a +ve Low Degree Of correlation between the Share Price & Risk is .137,

RELIANCE POWER


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Correlations

networth shareprice risk pat

networth Pearson Correlation 1 .993 .006 .812

Sig. (2-tailed) .076 .996 .397

N 3 3 3 3shareprice Pearson Correlation .993 1 -.114 .737

Sig. (2-tailed) .076 .927 .473

N 3 3 3 3

risk Pearson Correlation .006 -.114 1 .588

Sig. (2-tailed) .996 .927 .600

N 3 3 3 3

pat Pearson Correlation .812 .737 .588 1

Sig. (2-tailed) .397 .473 .600

N 3 3 3 3

INTERPRETATION



there is a +ve High degree of correlation between the Net Worth, Share Prices is .

993,

there is a +ve low degree of correlation between Net Worth & Risk is .006,

there is a +ve high degree of correlation between the PAT & Net Worth is .812,


there is a -ve Low Degree Of correlation between the Share Price & Risk is -.114,

(B.) Reliability Analysis


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Cronbachs alpha is most commonly used reliability coefficients, which is based on the

average correlation of items within a test if the items are standardized. If the items are not

standardized, it is based on the average covariance among the items. Because Cronbachs

alpha can be interpreted as a correlation coefficient, it ranges in value from 0 to 1.

Variables:


Net Worth

Risk

Share Price

1. TATA POWER

Reliability Statistics

Cronbach's Alpha

Cronbach's Alpha

Based on

Standardized

Items N of Items

.547 .496 4

INTERPRETATION

In the above table the value of Cronbach alpha is .547 that is 54.7% the reliability of the

variables is good & which symbolizes the efficiency of study.

2. SUZLON ENERGY


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Cronbach's Alphaa

Cronbach's Alpha

Based on

Standardized

Itemsa N of Items

.599 .747 4

INTERPRETATION

In the above table the value of Cronbach alpha is .599 that is 59.9% the reliability of the

variables is good & which symbolizes the efficiency of study.

3. RELIANCE POWER


Cronbach's Alpha

Cronbach's Alpha

Based on

Standardized

Items N of Items

.571 .602 4

INTERPRETATION

In the above table the value of Cronbach alpha is .571 that is 57.1% the reliability of the variables is good & which

symbolizes the efficiency of study.

(D.)Regression Analysis

In statistics, regression analysis includes any techniques for modeling and analyzing

several variables, when the focus is on the relationship between a dependent variable and
http://en.wikipedia.org/wiki/Statisticshttp://en.wikipedia.org/wiki/Dependent_variablehttp://en.wikipedia.org/wiki/Statisticshttp://en.wikipedia.org/wiki/Dependent_variable


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one or more independent variables. More specifically, regression analysis helps us

understand how the typical value of the dependent variable changes when any one of the

independent variables is varied, while the other independent variables are held fixed.

Most commonly, regression analysis estimates the conditional expectation of the

dependent variable given the independent variables that is, the average value of the

dependent variable when the independent variables are held fixed. Less commonly, the

focus is on a quantile, or other location parameterof the conditional distribution of the

dependent variable given the independent variables. In all cases, the estimation target is a

function of the independent variables called the regression function. In regression

analysis, it is also of interest to characterize the variation of the dependent variable

around the regression function, which can be described by aprobability distribution.

Regression analysis is widely used forprediction and forecasting, where its use has

substantial overlap with the field ofmachine learning. Regression analysis is also used to

understand which among the independent variables are related to the dependent variable,

and to explore the forms of these relationships. In restricted circumstances, regression

analysis can be used to infercausal relationships between the independent and dependent

variables.

(1.)Suzlon Energy

VARIABLES:

Dependent Variable: PAT
http://en.wikipedia.org/wiki/Independent_variablehttp://en.wikipedia.org/wiki/Conditional_expectationhttp://en.wikipedia.org/wiki/Average_valuehttp://en.wikipedia.org/wiki/Quantilehttp://en.wikipedia.org/wiki/Location_parameterhttp://en.wikipedia.org/wiki/Function_(mathematics)http://en.wikipedia.org/wiki/Probability_distributionhttp://en.wikipedia.org/wiki/Predictionhttp://en.wikipedia.org/wiki/Forecasthttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Causalityhttp://en.wikipedia.org/wiki/Independent_variablehttp://en.wikipedia.org/wiki/Conditional_expectationhttp://en.wikipedia.org/wiki/Average_valuehttp://en.wikipedia.org/wiki/Quantilehttp://en.wikipedia.org/wiki/Location_parameterhttp://en.wikipedia.org/wiki/Function_(mathematics)http://en.wikipedia.org/wiki/Probability_distributionhttp://en.wikipedia.org/wiki/Predictionhttp://en.wikipedia.org/wiki/Forecasthttp://en.wikipedia.org/wiki/Machine_learninghttp://en.wikipedia.org/wiki/Causality


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VARIABLES:

Dependent Variable: PAT

Independent Variable: Share Price

Model Summaryb

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .473a .224 -.552 705.04040



Interpretation

In the above computer generated table of model summary, we consider the value of R

Square to know the level to which Share Price of the company effect on the PAT of the

company in last three year & the computer generated value is .224 which shows that up to

22.4% of fluctuations take place due to the values of Share Price & PAT.

VARIABLES:

Dependent Variable: Net Worth


Model Summaryb

Model R R Square Adjusted R Square Std. Error of the Estimate1 .883a .779 .558 1181.66910



Interpretation

In the above computer generated table of model summary, we

consider the value of R Square to know the level to which Share Price

of the company effect on the Net Worth of the company in last three

year & the computer generated value is .779 which shows that up to

77.9% of fluctuations take place due to the values of Share Price &

Net Worth.

VARIABLES:



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Interpretation


Square to know the level to which risk of the company effect the Net Worth of the

company in last three year & the computer generated value is .344 which shows that up

to 34.4% of fluctuations take place due to the values of Risk & Net Worth.

(2.)Reliance Power

VARIABLES:




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Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .993a .986 .971 1315.10223



Interpretation


Square to know the level to which Share Price of the company effect on the Net Worth of

the company in last three year & the computer generated value is .986 which shows that up

to 98.6% of fluctuations take place due to the values of Share Price & Net Worth.

VARIABLES:


Independent Variable: Risk

Model Summary


1 .737a .543 .085 91.25449

a. Predictors: (Constant), Risk


INTERPRETATION:

values of Risk & Net Worth. In the above computer generated table of model summary,

we consider the value of R Square to know the level to which Risk of the company effect

on the Net Worth of the company in last three year & the computer generated value is .543

which shows that up to 54.3% of fluctuations take place due to the


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Model Summary


1 .993a .986 .971 1315.10223



Interpretation





VARIABLES:



Model Summary


1 .737a .543 .085 91.25449



INTERPRETATION:






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Model Summary


1 .993a .986 .971 1315.10223



Interpretation





VARIABLES:



Model Summary


1 .737a .543 .085 91.25449



INTERPRETATION:






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Model Summary


1 .993a .986 .971 1315.10223



Interpretation





VARIABLES:



Model Summary


1 .737a .543 .085 91.25449



INTERPRETATION:



reliance power, tata power and suzlon energy

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