a report on banking sector analysis- factors affecting indian banking sector

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Page | 1 SUMMER INTERNSHIP PROGRAM A REPORT ON FACTORS AFFECTING INDIAN EQUITY MARKET (BANKING SECTOR) INDIA INFOLINE LIMITED

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This is a research report which deals with a research done on the Banking Sector on how various factors affect the Banking Sector Share prices. A technical analysis is also done using SPSS and MS-Excel.

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Page | 1

SUMMER INTERNSHIP PROGRAM

A

REPORT

ON

FACTORS AFFECTING INDIAN

EQUITY MARKET

(BANKING SECTOR)

INDIA INFOLINE LIMITED

Page | 2

A

REPORT

ON

FACTORS AFFECTING INDIAN

EQUITY MARKET

(BANKING SECTOR)

A report submitted in partial fulfillment of the

requirement of MBA program of

ICFAI Business School, Ahmedabad

Submitted to:

Prof. Bharat Kantharia (Faculty Guide)

Mr. Chintan Shah (Company Guide)

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“No good work flows without the help from Faculty Members, Industry

Professionals, Colleagues, Organization and Friends.”

ACKNOWLEDGEMENT

Summer Internship is a nurturing period which is indispensable for joining any company. On the voyage of learning I came across many hurdles but each hurdle

was a good experience for me. At each step of my training, my mentor gave me full support which helped me in carrying positive attitude whenever I faced any

problem.

Firstly, I take this opportunity to thank Prof. P. Bala Bhaskaran (Director, IBS

Ahmedabad), who has always stood by me and encouraged me to embark on the path of learning.

I wish to convey my special thanks to Mr. Dhiraj Chaudhary (Associate Vice President), Mr. Ishwarsinh Rajpurohit (Territory Manager), my company

project guide Mr. Chintan Shah (Sales Manager) and all employees who have helped me directly or indirectly in my difficulties at India Infoline Securities Pvt.

ltd., Area Office, Surat who have been a constant source of inspiration and encouragement to me.

I wish to express my deepest and most sincere thanks to my Faculty Guide, Prof. Bharat Kantharia and especially to Dr. Himani Joshi and Prof. Mayank Patel

who have continuously guided me throughout this project.

Last but not the least I would like to thank my fellow management trainees from IBS, Ahmedabad. By interacting with them, I was able to generate more meaningful ideas that have enabled me to further complete this project

successfully.

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TABLE OF CONTENTS

ACKNOWLEDGEMENT ............................................................................................................. iii

ABSTRACT.................................................................................................................................... 5

INTRODUCTION .......................................................................................................................... 6

MARKETS DEFINED................................................................................................................ 6

OBJECTIVE OF THE STUDY ................................................................................................ 10

PURPOSE, SCOPE AND LIMITATIONS .............................................................................. 10

SOURCES AND METHODS OF COLLECTING DATA ...................................................... 12

REPORT ORGANIZATION .................................................................................................... 13

MAIN TEXT................................................................................................................................. 16

FACTORS AFFECTING BANKING SECTOR ...................................................................... 17

INTERNAL FACTORS:................................................................................................ 17

EXTERNAL FACTORS:............................................................................................... 19

THE MODEL................................................................................................................................ 26

What the MODEL is all about? ............................................................................................. 26

Methodology .......................................................................................................................... 26

Sources and Data Collection.................................................................................................. 27

Tool and Techniques.............................................................................................................. 28

MODEL ................................................................................................................................. 29

HDFC BANK ........................................................................................................................ 29

ICICI BANK.......................................................................................................................... 37

STATE BANK OF INDIA .................................................................................................... 43

FINDINGS AND CONCLUSION ............................................................................................... 49

APPENDIX ................................................................................................................................... 51

REFERENCES: ............................................................................................................................ 53

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ABSTRACT

Banking Sector in India is one of the growing sectors with great dynamics. There

are various factors which affect the share prices of Banking Companies. This

report is all about how various factors (Internal and External) affect the Banking

Sector Share Prices. In this report a detailed analysis of the factors affecting the

share prices is carried on and a model is developed to study the effect of various

factors on the share prices.

Here, various internal factors (Bank‟s Profitability, Income, Expenses, and News

about the Bank.) and external factors (Government policies, CRR, Repo Rate,

Reverse Repo Rate, Rules and Regulations.) are considered which affect the prices

of the shares of Bank. Data‟s are collected for all the quantifiable factors and for

the rest factors a theoretical explanation is given in detail. Using SPSS a model is

developed which shows the regression and correlation co-efficient between the

share prices and various factors affecting the same.

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INTRODUCTION

MARKETS DEFINED

STOCK MARKET IN INDIA

The Indian security market has become one of the most dynamic and efficient

security markets in Asia today. The Indian market now conforms to International

Standards in terms of operating efficiency.

During the latter half of 19th

century, shares of companies used to be floated in

India occasionally. There were share brokers in Bombay who assisted in the

floatation of shares of companies. A small group of stock brokers in Bombay

joined together in 1875 to form an association called Native Share & Stockbrokers

Association. The association drew up codes of conduct for brokerage business and

mobilizes private funds for investment in the corporate sector. It was this

association which later became the Bombay Stock Exchange, Mumbai or BSE

Later on in 1894 the brokers of Ahmedabad formed the Ahmedabad Stock

Exchange, the second stock exchange of the country. During the 1900s Kolkata

became another major center of share trading and as a result Kolkata Stock

Exchange was formed in 1908. Later on Chennai Stock Exchange was started in

1920. However, by 1923, it ceased to exist. Then the Madras Stock Exchange was

started in 1937. Three more stock exchanges were established before

independence, at Indore in 1930, at Hyderabad in 1943 and at Delhi in 1947.

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Thus along with the increase in number of stock exchanges, the number of listed

companies and the capital of listed companies grown tremendously after 1985

which results into growth and development of stock market in India.

ABOUT BSE SENSEX

BSE SENSEX or Bombay Stock Exchange Sensitive Index is a value-weighted

index composed of 30 stocks started in 01 of January, 1986. It consists of the 30

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

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

market capitalization of the BSE. The base value of the SENSEX is 100 on April 1,

1979, and the base year of BSE-SENSEX is 1978-79.

At irregular intervals, the Bombay Stock Exchange (BSE) authorities review and

modify its composition to make sure it reflects current market conditions. The

index is calculated based on a free-float capitalization method; a variation of the

market cap method. Instead of using a company's outstanding shares it uses its

float, or shares that are readily available for trading. The free-float method,

therefore, does not include restricted stocks, such as those held by company

insiders.

The index has increased by over ten times from June 1990 to the present. Using

information from April 1979 onwards, the long-run rate of return on the BSE

SENSEX works out to be 18.6% per annum, which translates to roughly 9% per

annum after compensating for inflation. There are five major indices in BSE,

thirteen sector specific indices and a BSE Dollex Index for dollar prices and

movements.

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ABOUT NSE AND NIFTY 50

The National Stock Exchange of India Limited (NSE) is a Mumbai-based stock

exchange. It is the largest stock exchange in India in terms of daily turnover and

number of trades, for both equities and derivative trading. Though a number of

other exchanges exist, NSE and the Bombay Stock Exchange are the two most

significant stock exchanges in India and between them are responsible for the vast

majority of share transactions. The NSE's key index is the S&P CNX Nifty, known

as the Nifty, an index of fifty major stocks weighted by market capitalization.

NSE is mutually-owned by a set of leading financial institutions, banks, insurance

companies and other financial intermediaries in India but its ownership and

management operate as separate entities. There are at least 2 foreign investors

NYSE Euro next and Goldman Sachs who have taken a stake in the NSE. As of

2006, the NSE VSAT terminals, 2799 in total, cover more than 1500 cities across

India. In October 2007, the equity market capitalization of the companies listed on

the NSE was US$ 1.46 trillion, making it the second largest stock exchange

in South Asia. NSE is the third largest Stock Exchange in the world in terms of the

number of trades in equities. It is the second fastest growing stock exchange in the

world with a recorded growth of 16.6%.

The Standard & Poor's CRISIL NSE Index 50 or S&P CNX Nifty nicknamed Nifty

50 or simply Nifty, is the leading index for large companies on the National Stock

Exchange of India. The Nifty is a well diversified 50 stock index accounting for 22

sectors of the economy. It is used for a variety of purposes such as benchmarking

fund portfolios, index based derivatives and index funds. There are seven major

Indices in NSE and fifteen sector specific Indices. CNX BANK INDEX or BANK

NIFTY is the index which has 17 banks listed on it and is a separate index to look

upon price movements of bank‟s share prices. A brief account of the same is given

below.

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CNX Bank Index

The Indian banking Industry has been undergoing major changes, reflecting a

number of underlying developments. Advancement in communication and

information technology has facilitated growth in internet-banking, ATM Network,

Electronic transfer of funds and quick dissemination of information. Structural

reforms in the banking sector have improved the health of the banking sector. The

reforms recently introduced include the enactment of the Securitization Act to step

up loan recoveries, establishment of asset reconstruction companies, initiatives on

improving recoveries from Non-performing Assets (NPAs) and change in the basis

of income recognition has raised transparency and efficiency in the banking

system. Spurt in treasury income and improvement in loan recoveries has helped

Indian Banks to record better profitability. In order to have a good benchmark of

the Indian banking sector, India Index Service and Product Limited (IISL) has

developed the CNX Bank Index.

CNX Bank Index is an index comprised of the most liquid and large capitalized

Indian Banking stocks. It provides investors and market intermediaries with a

benchmark that captures the capital market performance of Indian Banks. The

index will have 12 stocks from the banking sector which trade on the National

Stock Exchange.

The average total traded value for the last six months of CNX Bank Index stocks is

approximately 95.85% of the traded value of the banking sector. CNX Bank Index

stocks represent about 86.06% of the total market capitalization of the banking

sector as on January 30, 2009.

The average total traded value for the last six months of all the CNX Bank Index

constituents is approximately 14.86% of the traded value of all stocks on the NSE.

CNX Bank Index constituents represent about 8.63% of the total market

capitalization on January 30, 2009.

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OBJECTIVE OF THE STUDY

The objective of the project is to identify, understand and analyze the impact of

various factors that affect the Indian Equity Market (BANKING SECTOR). The

main focus will be on understanding, analyzing and providing a valid explanat ion

both theoretically and technically, that how various factors affect the share prices

of BNAKING SECTOR. By undertaking this study I would like to keep my first

step in the field of research. This project will help me in enhancing my analytical

skills and will give me a better understanding of how things move on and are to be

studied. At the same time with this study I will be providing the organization a list

of factors that affect the market, so that they can keep a watch on the same and use

the same for the benefit of clients and company and also increase their accuracy

and profits. This will be my contribution to this huge company.

PURPOSE, SCOPE AND LIMITATIONS

PURPOSE

The PURPOSE of the report is to analyze how various factors affect the prices of

a bank‟s share. The share prices are highly affected by various internal and

external factors. It is of great importance to understand, learn and analyze the

same. Thus, this report is a move in path of understanding those factors and

analyzing the impact of the same.

Banks are a major part of any economic system. They provide a strong base to

Indian economy too. Even in share markets, the performance of bank shares is of

great importance. This is justified by the proof that in both BSE and NSE we have

separate index for Banking Sector Shares. But for our study we have taken only

Bank Nifty which is a part of NSE. Thus, the performance of share market, the rise

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and the fall of market is greatly affected by the performance of Banking Sector

Shares and this report revolves around all those factors, their understanding and a

theoretical and technical analysis of the same.

SCOPE OF STUDY

It gave me an opportunity to study the banking sector in a detailed manner.

I got knowledge of prevailing Market Scenario.

It helped me in learning the market dynamics, study the movement of share prices

and to give a proper justification for the same, theoretically and technically.

It helped me in understanding and learning the corporate culture

And above all, the concerned organization can get some valuable

recommendations, which can definitely improve the performance of the

organization.

LIMITATIONS OF THE STUDY

Though the resources seem sufficient enough to achieve high standard for this

research, still we foresee the following limitations of study.

The Sector is very vast and it was not possible to cover every nook and corner of

this sector.

The variability and availability of data was also a limitation.

The data were linear and possessed multi collinearity, so each and every data was

not considered for analysis.

The objective which we want to fulfill in this project is really good, but the major

demerit to our study is the availability of time for our search and analysis, but then

also, I have tried my level best to show a glimpse of my Research in tune with the

objectives.

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SOURCES AND METHODS OF COLLECTING DATA

To meet the objective of the project, a lot of data was required to be collected from

varied sources. For the technical analysis, the data was required in respect of

Interest Income, Advances, Various rates, Share Prices, etc. For this, the data was

obtained from Balance Sheets, Quarterly results, Websites, News Papers, etc. A list

of same is provided in the references.

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REPORT ORGANIZATION

COMPANY PROFILE

“India Infoline Securities Pvt. Ltd.”

“Knowledge is power and power brings security. Risk is a very relative term

and changes with every individual and situation. Financial management is not just

about managing risk but also managing knowledge and finally deriving answers

that generate wealth, security and trust.”

VISION

Vision is to be the most respected company in the financial services space.

To be the premier provider of investment advisory and financial planning services

in India.

PUNCH LINE: “IT‟S ALL ABOUT MONEY, HONEY!”.

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HISTORY IN BRIEF

In 1995, a group of professionals formed a company called Probity Research &

Services Pvt. Ltd. The name was later changed to IndiaInfoline Ltd. The objective

was to provide unbiased and independent information to market intermediaries and

investors. The quality of research was so good that soon it caught the imagination

of all major participants in the financial marketing. In a very short period they

started providing research report to consulting firms like Mckinsey, companies like

HUL, banks like Citibank etc.

In 1999, the company made all the research report free on the web and as a result

the number of user increases from mere a thousand to lacks in a very short period

of time. The company got the financial support from venture capitalists and private

equity investors. They raised US $ 1 million in first round and in March 2000

again US $5 Million.

In 2001, the company faced the worst situation. The dot com suffix, which was

sexiest to them suddenly, became the worst stigma. The company was planning to

set up a TV channel but circumstances forced them to jettison the plan. IIL decided

to narrow its focus on businesses where it could leverage its core competencies to

the maximum. The key business lines that emerged were mutual funds, life

insurance and e-broking.

The company became heavily dependent on its e-broking businesses for survival.

The odds were against them. There was no money available from the private equity

investor at any valuation. All competitors were backed by institution or had

abundant capital. The core promoters of the company had little experience of

broking. To add to it, the market was hit by a scam. They also had their share of

price to pay and lessons to learn. It was difficult to retain people. Although

devastating for morale but not surprising, the most market observers had written

them off.

There was a core group who never lost hope. They cut all possible costs and

worked on a bare bones structure. They survived against all odds started capturing

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market share. Not broking alone but mutual fund life insurance business also grew

strongly. The company rose from strength to become the leading corporate agent in

life insurance and among top retail players in mutual fund and broking space.

In 2005, IIL came with an IPO and raised Rs. 75 crores from the market. The issue

price was Rs. 76.The IPO was 7.22 times oversubscribed. The company after that

never looked back and started entire gamut of investments products from risk free

RBI bonds to high-risk, high rewards equities and also mutual funds and life

insurance. They also forayed into portfolio management services and commodities

broking, again leveraging upon their core competencies in research and

technology.

In the last ten years, India Infoline has faced numerous ups and downs, but has

never compromised on integrity. They continue to ensure highest standards of

corporate governance.

BUSINESS DESCRIPTION

The India Infoline group, comprising the holding company, India Infoline Limited

and its wholly-owned subsidiaries, straddle the entire financial services space with

offerings ranging from Equity research, Equities and derivatives trading,

Commodities trading, Portfolio Management Services, Mutual Funds, Life

Insurance, Fixed deposits, Gold, bonds and other small savings instruments to loan

products and Investment banking. India Infoline also owns and manages the

websites www.indiainfoline.com and www.5paisa.com.

The company has a network of 596 branches spread across 345 cities and towns. It

has more than 500,000 customers.

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MAIN TEXT

Companies raise funds by issuing equity shares to the public. We have a well

developed equity market in our country for secondary dealing in various securities

of various denominations. We basically have BSE and NSE to see the dealings and

the price fluctuations of these securities. There are several factors like interest

rates, company‟s internal factors, profitability of company, any news about

company, major events of the company, country scenario, political factors,

economical factors, social factors, international events, trends in international

market, investor‟s own mentality, predictions and approach etc.. which affect the

market price of these securities.

Thus, my project basically revolves around how all these factors affect the equity

market. The project is based on a descriptive study of various factors that affect the

Indian equity market in various aspects.

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FACTORS AFFECTING BANKING SECTOR

Starting off with the project, in the initial phase of SIP, I learnt the basics of the

stock market. As I had to work here in this market for 3.5 months this was the

basic necessity. In that phase I had a nice exposure of how to deal with clients,

how to handle the queries of the investors, it was a practical exposure to learn the

working of the market, how the market moves and all about the corporate culture.

Also I had learnt what factors basically affect the equity market. Then I decided to

limit my project to just Banking Sector, because it is one of the most dynamic

sector and also availability of time was not permitting me to go beyond this.

There are N number of factors which affect the share prices. They can be broadly

classified into two:

INTERNAL FACTORS

EXTERNAL FACTORS

INTERNAL FACTORS: As the name suggests, Internal Factors are those

which affect the share prices internally, i.e. they are internal to the company or

more specifically bank. Some of the major internal factors that affect the share

prices of a bank are as follows:

EARNINGS OF THE COMPANY:

How much Profit a company earns acts as a significant factor in price movements.

If the quarterly results are good for a bank, then the price goes up, and if the results

are not good, the investors show no interest in such bank‟s share and thus price

falls. Investors invest money in the companies who earn well and in turn give good

return on investment. Thus, a wealthy and a profitable company have good

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investors and thus have positive price movements. Price/Earnings Ratio also gives

us idea about the same.

MARKET CAPITALIZATION:

Generally we commit one mistake that we guess the company‟s worth from the

price of its stock. It is the market capitalization of the company, rather than the

stock price, that is more important when it comes to determining the worth of the

company. We need to multiply the stock price with the total number of

outstanding stocks in the market to get the market capitalization of a company and

that is the worth of the company. Thus, a company or bank with high Market

Capitalization turns out to be more popular among investors. For example, HDFC

BANK, ICICI BANK and SBI are more popular among investors than other banks

because they have huge market share and market capitalization. As market

capitalization increases, the share price tends to increase and as market

capitalization decreases, the share price tends to decrease.

PRICE/EARNINGS RATIO:

Price/Earnings ratio or the P/E ratio gives us a fair idea of how a company's share

price compares to its earnings. If the price of the share is too much lower than the

earning of the company, the stock is undervalued and it has the potential to rise in

the near future. On the other hand, if the price is way too much higher than the

actual earning of the company and then the stock is said to overvalued and the

price can fall at any point. The earnings also have a direct relation with price which

is already explained above.

INTERNAL AFFAIRS OF THE COMPANY:

Any happening inside the company or any internal news does affect its share price.

For example any key person moving out of the company, acquisition or takeover or

merger news, share split, employee strike and any other thing internal to the affairs

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of the bank affects the share price. A positive note from the internal affairs takes

the price to new highs and a negative does vice versa.

INTERST RATES:

Interest rates play a major role in determining stock market trends. Bull markets

(those in an upward market) are usually associated with low interest rates and high

Capital Gains, and bear markets (those in a downward trend) with high interest

rates and low Capital gains. Interest rates are determined by the demand for capital

– pushes them up and normally indicates that the economy is thriving and that

shares probably expensive. Low interest indicate low demand for capital, thus

liquidity builds up on the economy, driving share price down. Other interest rates

like that of on Deposits and Borrowings also have impact on share prices.

OTHER FACTORS:

Other factors like Growth of the company, figures of deposits, advances, balance

sheet, Profit and Loss Account, etc.. also affect the share prices drastically. A

discussion for the same is done in later part of the report

EXTERNAL FACTORS: After studying the internal factors, lets take a

look at some External Factors which affect the Share Prices.

SENTIMENTS:

Investor sentiment is almost impossible to predict and can be infuriating if, for

example, you have bought shares in a company that you think is a good „buy‟ but

the price remains flat. Investor sentiment is influenced by a wide variety of factors.

Share prices can, for example, be flat during the summer simply because so many

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major investors are on holiday or attending major sporting events such as Royal

Ascot and Wimbledon, hence the adage „sell in May and go away‟.

Investor sentiment can lead to irrational buying or selling of shares and result in

bull and bear markets. A bull market is when share prices rise while a bear market

is when they fall. In the technology boom of the late 1990s, for example, investors

paid extremely high prices for shares and ignored traditional valuation measures,

such as P/E ratios. This carried on until 2000 when investors belatedly realized

these shares has risen too far and resulted in a three year bear market in shares.

Thus, Sentiments of investors affect the share prices a lot and this is something

unpredictable and immeasurable factor, but still the most important one.

COMPANY NEWS and OTHER NEWS:

The way investors interpret news coming out of companies is also a major

influence on share prices. If, for example, a company puts out a warning that

business conditions are tough, shares will often drop in value. If, however, a

director buys shares in the firm, it may be a signal that the company‟s prospects are

improving. Companies put out a great deal of news and most of the major

announcements are covered by the financial press. But some announcements not

regarded as so important and sometimes, particularly among smaller firms that are

monitored less by investors and financial journalists, indicators of the company‟s

health can be missed. Takeovers or even rumors of takeovers also have a big

influence on prices. This is because investors expect the bidder to pay a premium

to shareholders.

Also any other news or speculation about factors like change in Repo Rate, Cash

Reserve Ratio, Reverse Repo Rate, any change or likely change in the policies of

government or RBI or SEBI, any new guidelines issued by the concerned

authority, etc. affect the price of the share. A positive news in any of these respects

leads to a rise in price and a negative takes it to the other side.

Thus, news in any respect is undoubtedly a huge factor when it comes to stock

price. Positive news about a company can increase buying interest in the market

while a negative press release can ruin the prospect of a stock. Having sa id that, we

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must always remember that often times, despite amazingly good news, a stock can

show least movement. It is the overall performance of the company that matters

more than news. It is always wise to take a wait and watch policy in a volatile

market or when there is mixed reaction about a particular stock.

DEMAND AND SUPPLY:

This fundamental rule of economics holds good for the equity market as well. The

price is directly affected by the trend of stock market trading. When more people

are buying a certain stock, the price of that stock increases and when more people

are selling the stock, the price of that particular stock falls. Now it is difficult to

predict the trend. Thus, we should be very careful while dealing in stocks as

buying or selling pressure may lead to steep rise or fall in price of the shares.

ANALYSTS’ REPORTS:

Reports produced by independent analysts also influence share prices. If an analyst

changes their recommendation from „sell‟ to „buy‟, for example, the shares will

often rise in value. Analysts‟ reports are produced primarily by investment banks

for professional investors, although some stockbrokers will make their research

available to private investors. We may find summaries of some reports published

on financial news websites or in newspapers and magazines. Some investment

banks also publish their reports on their websites for free.

We should remember that the recommendation an analyst puts on a company will

affect its share price very quickly and can become irrelevant within hours. This is

because the analyst will usually say a stock is a „buy‟ within a particular price

range. If the price moves above their targets the improvements the analyst expects

may be „priced in‟ and so the shares are not worth buying.

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But analysts‟ reports are always worth reading, even if the recommendation is out

of date. The reports usually contain a great deal of useful information on the

company and how its business is developing. They also often look at how the

company rates against its competitors .

THE ECONOMY:

The health of the global economy has a fundamental influence on share prices

because it is ultimately responsible for driving company profits. Broadly speaking,

if the economy is growing, company profits improve and shares will become more

highly valued. If the economy is weakening, company profits will fall and share

prices will go down.

Investors look at a vast amount of data to try and work out what is going to happen

to the economy and shift their portfolios before the events occur. This is why we

will often see markets move well ahead of an actual event occurring. For example,

we could get little reaction from the stock market when interest rates rise. This is

because investors have already anticipated the shift months in advance and

adjusted their portfolios beforehand.

We can usually assume that the stock market will anticipate moves in the economy

by around six to nine months. So if we want to stay ahead of the game we need to

follow economic data as closely as the professionals.

The kind of information we need to play close attention to is: employment data, the

reports put out by the Monetary Policy Committee (to get an idea where interest

rates are headed), trade with other countries, retail sales and manufacturing.

Sentiment surveys produced by trade bodies such as the Confederation of British

Industry are also important indicators of where the economy is heading.

It is not only news about the US and UK economy that will impact on share prices.

The signals coming out of other major economies, particularly the US and UK‟s

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major trading partners, such as the Europe and Asia will also affect US and UK

shares as what happens in these economies will have an impact on our own.

When looking at economic data, we need to think not only how the wider economy

will be affected but whether certain areas will be more affected than others. A rise

in interest rates is, for example, often bad news for house builders as people feel

less confident about taking on debt. Retailers are often badly affected too as people

spend less. Pharmaceutical companies are, however, usually unaffected as people‟s

demand for drugs is not influenced by the state of the economy.

Companies whose profits are closely tied to the health of the economy are known

as „cyclical‟ stocks. Those businesses that aren‟t too affected by the economy are

called „defensive‟ stocks. If economic conditions deteriorate you will often see

investors shift from cyclical stocks to defensives. Thus, the economic health of an

Economy affects the Share Prices.

PRESS and BROKING HOUSE RECOMMENDATIONS:

The financial pages of most national newspapers and investment magazines

usually contain share tips. Like analysts‟ reports these tips can have a major

influence on share prices. If a journalist recommends a share, the price will usually

rise and if they write a negative story the price will fall. These moves usually

happen very quickly so if we follow the recommendation it often makes sense to

do so as soon as possible.

The Broking House also recommends BUY or SELL for particular shares based on

their own research analysis. They display these recommendations in leading media

such as Television and News Papers. Thus, these recommendations affect the price

of shares and lead the market in the direction these recommendations take.

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TECHNICAL INFLUENCES:

Share prices can rise and fall for a variety of technical reasons that may have

nothing to do with the actual outlook for an individual company or the outlook for

the market. It is, for example, a common occurrence for share prices to drop back

after a strong rally. This happens because investors take profits on some of the

shares that have risen in value, protecting their gains just in case the shares start to

slip back. Investors often refer to this as market consolidation.

Another technical reason for share prices to rise or fall is the quarterly adjustment

in the FTSE 100™ index. Shares that are expected to enter the FTSE 100™ may

experience a sharper rise than one would expect in the weeks beforehand while

shares that leave the index can fall more sharply. This happens because funds that

simply track the index have to match the composition of the index. Some

professional fund managers who hold the affected stocks also adjust their

portfolios as they do not want their holding to be too far above or below the

company‟s weighting in the index.

Share prices can also be affected by investors who use technical analysis to drive

their investment techniques. Technical analysis, also known as Chartism, is simply

the study of past share price movements and stock market index trends, which are

then used to forecast how shares and stock markets will behave in future.

Market makers can also influence prices. If they, for example, do not own enough

shares to balance their books they will have to buy more. Market makers also

influence prices if the market is looking flat, reducing prices to attract buyers.

Thus, technical reasons can also be a cause for the rise or fall in the prices of

shares.

Page | 25

OTHER FACTORS:

Some other factors which influence share prices are as follows:

Change in Rates by RBI: Looking at the changing scenario, RBI keeps on

changing rates like Repo Rate, Reverse Repo Rate and Cash Reserve Ratio. These

rates have a direct relation with the Bank‟s performance and in turn the share

prices are linked with Bank‟s Performance. Thus, a change in these rates or even a

speculation of change in these rates affects share prices.

Global Changes: Any change in the global economy or in other words global

changes also affects Indian economy. Thus, the performance of an economy and its

banks is affected by these global changes. For example: The recession was first

observed in the USA and later on it caught its lead in other countries too. When it

entered India, the share market crashed literally. So, a careful and logical investor

always keeps this in mind that what global changes affect the market and thus

leads to rise or fall in share prices.

Change in Government Policies: Keeping in mind the progress and well wishes

about the country, the government takes desired steps and keeps on reviewing its

policies, rules and regulations and procedures. A change in FDI and FII inflow

restrictions, entry exit barriers for foreign banks in India, EXIM regulations,

change in Basel Norms, etc form part of important government policies. Thus, a

change in these policies affects the market scenario. For example: if government

allows entry of foreign Banks in India, then the competition would rise and it

might happen that those foreign Banks may outperform and leave our own banks

far behind. Then in this case, the investors would be interested in investing in those

foreign Banks and a government would never like that the funds are invested in

some foreign banks rather than our own banks. Thus, some restriction would

follow and this will definitely affect the share prices.

Page | 26

THE MODEL

All the above stated factors are more or less for a theoretical explanation. There

has to be some practical or numerical aspect to understand the impact of factors on

share prices. Thus, to give a technical view to the analysis I developed a MODEL.

The details of this are as follows.

What the MODEL is all about?

The MODEL is all about a relation between the Share Prices and various other

factors which affect it. As I have already stated that the Banking Sector is affected

by N number of factors. A comprehensive explanation we have already discussed

earlier. Now, here I have tried to provide a technical view to the relation between

Share prices and the factors affecting it by developing a technical MODEL using

SPSS.

Methodology

To develop a MODEL, the first and the foremost requirement was to decide the

boundaries of study. As in this short time period a full fledged Analysis of whole

market was not possible so I chose to limit my project to certain boundaries.

Firstly, I decided on the sector to be studied and for that I chose BANKING

SECTOR. The reason being that the Bank stocks have out-performed the Sensex

and Nifty in this fiscal year. This out-performance can be attributed to favorable

macroeconomic conditions and banking sector specific development like quarterly

results and passing of the SBI Amendment Bill that paved the way for its

subsidiaries to list in stock markets. Bank credits have grown at an average of 30

percent in the past three years led by housing and retail sectors. Thus, on thus basis

I chose Banking Sector.

Page | 27

For a proper, detailed and valid study, I have chosen top three banks in the

Banking Sector viz. HDFC BANK, ICICI BANK and STATE BANK OF INDIA.

The reason behind choosing these 3 banks is their huge turnover in the stock

market, they have been given the highest weightage and they serve as top leading

banks in the sector. A small report of Market Capitalization for 31st March, 2009

is also shown here.

Index/Exchange Company Name Close Price Mkt. Cap. in Rs Mn Weightage CNX BANK INDEX Axis Bank Ltd. 414.95 148969.17 6.65 CNX BANK INDEX Bank of Baroda 234.35 85365.83 3.81 CNX BANK INDEX Bank of India 219.4 115222.91 5.14 CNX BANK INDEX Canara Bank 165.7 67937 3.03 CNX BANK INDEX HDFC Bank Ltd. 973.4 414062.52 18.47 CNX BANK INDEX ICICI Bank Ltd. 332.8 370343.67 16.52 CNX BANK INDEX IDBI Bank Ltd. 45.4 32902.6 1.47 CNX BANK INDEX Kotak Mahindra Bank Ltd. 282.2 97547.75 4.35 CNX BANK INDEX Oriental Bank of Commerce 110.1 27584.42 1.23 CNX BANK INDEX Punjab National Bank 411.45 129731.21 5.79 CNX BANK INDEX State Bank of India 1067.1 677480.68 30.23 CNX BANK INDEX Union Bank of India 146.85 74176.56 3.31 TOTAL 2241324.34 100

Sources and Data Collection

To carry out the analysis, I drilled down on the data part. As all the factors are not

quantifiable i.e. cannot be converted into numerical terms and an analysis cannot

be done on non-numerical data, thus I chose some specific factors which were into

numerical terms. For a proper analysis I chose factors like Share Price, Interest

Income, Advances, Operating Profit, Net Profit, Repo Rate, Reverse Repo Rate,

Cash Reserve Ratio, Close of Nifty, Close of Bank Nifty, Borrowings, Deposits,

Average Return and a Dummy variable to adjust for Acquisitions and mergers.

All these data were collected from the financial year 2001-02 till 2008-09. Again

these data were converted into Quarterly figures to make the study logical and

valid. These data were collected form varied sources like from the websites of

Page | 28

respective bank, some other websites, websites of NSE and BSE, News Papers,

etc..

Tool and Techniques

For the analysis I used two tools MS Excel and SPSS. Using these two tools, I

compiled the data and conducted the analysis. First of all the whole data was

collected and compiled in Excel. The Excel sheet is also attached here with. Then I

imported the data into SPSS and conducted the analysis. MULTIPLE

REGRESSION was the technique which best suited the analysis and gave best

results, so I used the same and conducted the research analysis.

ANALYSIS EXCEL SHEET

For using MULTIPLE REGRESSION, the basic conditions are that the data should

be on same time frame, should be Linear and should not possess correlation

between them. The first condition was fulfilled by all the data as the data was

collected on the same time frame. The next condition is that the data should be

linear, but this condition was not fulfilled by the factors like Repo Rate, Reverse

Repo Rate and Cash Reserve Ratio. So these factors were dropped for the analysis

as they were not linear. Again the factors like Operating Profit and Net Profit,

Close of Nifty and Close of Bank Nifty and Borrowings and Deposits possessed

correlation between them. Thus, Operating Profit, Close of Nifty and Borrowings

were dropped for the analysis part and Net Profit, Close of Bank Nifty and

Deposits were taken for the analysis. Though Borrowings is used in ICICI BANK

analysis as it did not possess correlation there. The sheets of correlation are also

provided separately.

There are some technical terms which are frequently used in the all the three

analysis. These are explained in the Appendix.

Page | 29

MODEL

Now using the AVERAGE SHARE PRICE as DEPENDENT VARIABLE and

taking INTEREST INCOME, ADVANCES, NET PROFIT, CLOSE OF BANK

NIFTY, DEPOSITS AND DUMMY VARIABLE as INDEPENDENT

VARIABLES I applied MULTIPLE REGRESSION on the data for all the three

BANKS. Thus, I got the regression coefficient from the analysis. Now let us talk

about the analysis for all the three BANKS separately.

The Hypothesis:

The hypothesis can be stated as follows

H0: Various Factors affect the Share Prices

H1: Various Factors do not affect the Share Prices.

Thus, we will conduct all the analysis keeping in mind the hypothesis and will try

to reach a conclusion whether or not to accept the Hypothesis.

Page | 30

HDFC BANK

To begin with the analysis part of HDFC BANK, I have taken AVERAGE SHARE

PRICE as DEPENDENT VARIABLE and INTEREST INCOME, ADVANCES,

NET PROFIT, CLOSE OF BANK NIFTY and DEPOSITS as INDEPENDENT

VARIABLES and have applied MULTIPLE REGRESSION to it.

The output summary tables are shown below:

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate Change Statistics

R Square

Change F Change df1 df2 Sig. F

Change

1 .995a .991 .989 43.03165 .991 565.170 5 26 .000

a. Predictors: (Constant), Deposits, Close of Bank Nifty, Net Profit, Advances, Interest Income

ANOVA b

Model Sum of Squares df Mean Square F Sig.

1 Regression 5232693.188 5 1046538.638 565.170 .000a

Residual 48144.793 26 1851.723

Total 5280837.981 31

a. Predictors: (Constant), Deposits, Close of Bank Nifty, Net Profit, Advances, Interest Income b. Dependent Variable: Average Price

Page | 31

Coefficients a

Model

Un-standardized Coefficients

Standardized Coeffici

ents t Sig. 95% Confidence

Interval for B Correlations Collinearity Statistics

B Std. Error Beta

Lower Bound

Upper Bound

Zero-order Partial Part

Tolerance

Std. Error

1 (Constant) 44.448 22.549 1.971 .059 -1.902 90.798

Interest Income .003 .001 .931 3.825 .001 .001 .005 .825 .600 .072 .006 168.785

Advances .003 .003 .196 .882 .386 -.004 .009 .853 .170 .017 .007 140.492

Net Profit -.001 .004 -.035 -.225 .824 -.009 .007 .860 -.044 -.004 .015 68.385

Close of Bank Nifty

.165 .007 .923 22.333 .000 .149 .180 .985 .975 .418 .205 4.875

Deposits -.010 .004 -.964 -2.713 .012 -.017 -.002 .854 -.470 -.051 .003 359.898

a. Dependent Variable: Average Price

MODEL FIT

Now, when we have applied MULTIPLE REGRESSION on the data, the time is to

explain the output after each summary table that what does the output says and

what can we infer and interpret from it. While applying MULTIPLE

REGRESSION, we first took the DEPENDENT and INDEPENDENT variables

and then from the statistics option I chose Estimate, Confidence Intervals,

Covariance Matrix, Model Fit, R Squared Change, Descriptives, part and Partial

Correlations and Collinearity Diagnostics. So we got the desired analysis. From all

the output tables coming out of the analysis only three are of major importance

which we need to understand and interpret from.

Page | 32

MODEL SUMMARY

First of all the MODEL SUMMARY. Here we can see that in this case of HDFC

BANK the value of R is .995. This shows that the Predictors have 99.5%

influences on the output.

In this case the value of R2

is .991 this means that the predictors account for 99.1%

variation in the Average Price of the shares.

Here the difference is 0.002 (.991-.989) which is very small. This shrinkage means

that if model is derived from the population rather than a sample it would account

for approximately 0.2% less variance in the Outcome.

We can see here that the R Square Change is .991. This is used for calculating the

F-ratio. Thus, the change in amount of variance that can be explained gives rise to

an F-ratio of 565.170, which is significant (p<.001).

ANOVA

The next table here shows the output, which contains an Analysis of Variance

(ANOVA). The Sum of Squares here is 5232693.188; the value of Residual Sum

of Squares is 48144.793 and represents the total difference between the model and

observed data. From the value of F which is 565.170 here we can conclude that the

value of F is highly significant and our ability to predict the Outcome Variable is

much better.

Page | 33

MODEL PARAMETERS: COEFFICIENTS

This part of model is concerned with the parameters of the model. The Coefficients

table shows us the parameters. We can define the equation here as follows:

Average Price = b0+b1(Interest Income)+b2(Advances)+b3(Net

profit)+b4(Close of Bank Nifty)+b5(Deposits)+b6(Borrowings)

Average Price = 44.448 + .003 (Interest Income) + .003 (Advances) +

(-.001) (Net profit) + .165 (Close of Bank Nifty) + (-.010) (Deposits)

Looking at the B value for HDFC BANK, we can see that INTEREST INCOME,

ADVANCES and CLOSE OF BANK NIFTY show positive relationship while

NET PROFIT and DEPOSITS show negative relationship. So, as Interest Income,

Advances and the Values of Bank Nifty increase the Average Price of Share

increases and as the value of Net Profit and Deposits increases, the Average Price

decreases.

The B values tell us more than this though. They tell us to what degree each

predictor affects the outcome if the effects of all other predictors are held constant.

Interest Income (b=.003): This value indicates that as the interest income

increases by Rs. 1 crore, the Average Price increases by Rs. 0.003. This

interpretation is only true if the effect of other predictors is held constant.

Page | 34

Advances (b=.003): This value indicates that as the Advances are increases by Rs.

1 crore, the Average Price increases by Rs. 0.003. This interpretation is only true if

the effect of other predictors is held constant.

Net Profit (b=-.001): This value indicates that as the Net Profit is increases by Rs.

1 crore, the Average Price decreases by Rs. 0.001. This interpretation is only true if

the effect of other predictors is held constant.

Close of Bank Nifty (b=.165): This value indicates that as the Close of Bank Nifty

increases by 1 point the Average Price increases by Rs.0.165. This interpretation is

only true if the effect of other predictors is held constant.

Deposits (b=-.010): This value indicates that as the Deposits are increases by Rs. 1

crore, the Average Price decreases by Rs. 0.010. This interpretation is only true if

the effect of other predictors is held constant.

For this model the value of t-statistic for different variables and their Sig. can be

seen from the above table.

From the magnitude of t-statistics we can see that the Sig. Value for INTEREST

INCOME (0.001<0.05), CLOSE OF BANK NIFTY (.000<0.05) and DEPOSITS

(.012<0.05) are less than 0.05, thus, they have significant contribution in the model

and as the value of Sig. for ADVANCES (.386>0.05) and NET PROFIT

(.824>0.05) is more than 0.05 thus, they don‟t have a significant contribution to the

model. We also look for t-values, which if are above +2 and below -2. Here in this

case Interest Income, Close of Bank Nifty and Deposits match the criteria, thus,

they have a significant contribution in the Model.

Page | 35

The Standardized Beta Values as shown in the above table can be interpreted as

follows:

Interest Income (β =0.931): This value indicates that as the interest income

increases by 1 Standard Deviation (122545.143), the Average Price increases by

0.931 Standard Deviation. As the Standard Deviation for Average Price is

412.734, thus, a change of 1 Standard Deviation would bring a change of .931 in

the price. This interpretation is only true if the effect of other predictors is held

constant.

Advances (β =.196): This value indicates that as the Advances are increases by 1

Standard Deviation (30031.43), the Average Price increases by .196 Standard

Deviation. As the Standard Deviation for Average Price is 412.734, thus, a change

of 1 Standard Deviation would bring a change of .196 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Net Profit (β =-.035): This value indicates that as the Net Profit is increases by 1

Standard Deviation (16390.82), the Average Price increases by -.035 Standard

Deviation. As the Standard Deviation for Average Price is 412.734, thus, a change

of 1 Standard Deviation would bring a change of -.035 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Close of Bank Nifty (β =.923): This value indicates that as the Close of Bank

Nifty increases by 1 Standard Deviation (2314.74), the Average Price increases by

.923 Standard Deviation. As the Standard Deviation for Average Price is 412.734,

thus, a change of 1 Standard Deviation would bring a change of .923 in the price.

This interpretation is only true if the effect of other predictors is held constant.

Page | 36

Deposits (β =-.964): This value indicates that as the Deposits are increases by 1

Standard Deviation (40435.96), the Average Price increases by -.964 Standard

Deviation. As the Standard Deviation for Average Price is 412.734, thus, a change

of 1 Standard Deviation would bring a change of -.964 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Now talking about the rest of the table, we have got zero-order correlations which

are nothing but simple Pearson Correlation Coefficients. The Partial Correlations

represent the relationship between each predictor and the outcome Variable,

controlling for the effect of other predictors. The Part Correlations represent the

relationship between each predictor and the outcome Variable, controlling for the

effect of other predictors on the outcome. In effect, these Part Correlations

represent the unique relationship that each predictor has with the outcome.

Page | 37

ICICI BANK

Starting off with the analysis part of ICICI BANK, I have taken AVERAGE

SHARE PRICE as DEPENDENT VARIABLE and INTEREST INCOME,

ADVANCES, NET PROFIT, CLOSE OF BANK NIFTY, DEPOSITS and

BORROWINGS as INDEPENDENT VARIABLES and have applied MULTIPLE

REGRESSION to it.

The output summary tables are shown below:

Model Summary

Model R R Square Adjusted R Square

Std. Error of the Estimate Change Statistics

R Square Change F Change df1 df2

Sig. F Change

1 .862(a) .744 .682 158.4107 .744 12.096 6 25 .000

a. Predictors: (Constant), Borrowings, Close of Bank Nifty, Net Profit, Deposits, Interest, Advances

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 1821275.597

6 303545.933 12.096 .000(a)

Residual 627348.562

25 25093.942

Total 2448624.159

31

a. Predictors: (Constant), Borrowings, Close of Bank Nifty, Net Profit, Deposits, Interest, Advances b. Dependent Variable: Average Price

Page | 38

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coeffici

ents t Sig. 95% Confidence

Interval for B Correlations Collinearity Statistics

B Std. Error Beta

Lower Bound

Upper Bound

Zero-order

Partial Part

Toleranc

e VIF

1 (Constant) 472.069 173.906 2.715 .012 113.903 830.235

Interest .079 .080 .738 .995 .329 -.085 .244 .746 .195 .101 .019 53.781

Advances .005 .004 1.413 1.185 .247 -.004 .015 .774 .231 .120 .007 138.882

Net Profit -.272 .263 -.325 -1.034 .311 -.815 .270 .709 -.203 -.105 .104 9.618

Close of Bank Nifty

.009 .041 .077 .226 .823 -.076 .094 .787 .045 .023 .089 11.275

Deposits -.002 .004 -.446 -.434 .668 -.009 .006 .805 -.086 -.044 .010 103.437

Borrowings -.016 .007 -.839 -2.415 .023 -.030 -.002 .443 -.435 -.244 .085 11.775

a. Dependent Variable: Average Price

MODEL FIT

First of all the MODEL SUMMARY. In this case of ICICI BANK the value of R

is .862. This shows that the Predictors have 86.2% influence on the output.

In this case the value of R2

is .744 this means that the predictors account for 74.4%

variation in the Average Price of the shares.

Here the difference between value of R2 and the Adjusted R

2 is 0.062 (.744-.682)

which is small. This shrinkage means that if model is derived from the population

rather than a sample it would account for approximately 6.2% less variance in the

Outcome.

Page | 39

We can see here that the R Square Change is .744. This is used for calculating the

F-ratio. Thus, the change in amount of variance that can be explained gives rise to

an F-ratio of12.096, which is significant (p<.001).

ANOVA

The next table here shows the output, which contains an Analysis of Variance

(ANOVA). The Sum of Squares here is 1821276; the value of Residual Sum of

Squares is 627348.6 and the value of F which is 12.096. Here we can conclude that

the value of F is significant and our ability to predict the Outcome Variable is

good.

MODEL PARAMETERS: COEFFICIENTS

This part of model is concerned with the parameters of the model. The Coefficients

table shows us the parameters. We can define the equation here as follows:

Average Price = b0 + b1 (Interest Income) + b2 (Advances) + b3 (Net profit) + b4

(Close of Bank Nifty) + b5(Deposits) + b6(Borrowings)

Average Price = 472.069 + .079 (Interest Income) + .005 (Advances) +

(-.272) (Net profit) + .009 (Close of Bank Nifty) +

(-.002) (Deposits) + (-.016) (Borrowings)

The B values tell us to what degree each predictor affects the outcome if the effects

of all other predictors are held constant. Here is the analysis.

Page | 40

Interest Income (b=.079): This value indicates that as the interest income

increases by Rs. 1 crore, the Average Price increases by Rs. 0.079. This

interpretation is only true if the effect of other predictors is held constant.

Advances (b=.005): This value indicates that as the Advances are increases by Rs.

1 crore, the Average Price increases by Rs. 0.005. This interpretation is only true if

the effect of other predictors is held constant.

Net Profit (b=-.272): This value indicates that as the Net Profit is increases by Rs.

1 crore, the Average Price decreases by Rs. 0.272. This interpretation is only true if

the effect of other predictors is held constant.

Close of Bank Nifty (b=.009): This value indicates that as the Close of Bank Nifty

increases by 1 point the Average Price increases by Rs.0.009. This interpretation is

only true if the effect of other predictors is held constant.

Deposits (b=-.002): This value indicates that as the Deposits are increases by Rs. 1

crore, the Average Price decreases by Rs. 0.002. This interpretation is only true if

the effect of other predictors is held constant.

Borrowings (b=-.016): This value indicates that as the Borrowings are increases

by Rs. 1 crore, the Average Price decreases by Rs. 0.016. This interpretation is

only true if the effect of other predictors is held constant.

For this model the value of t-statistic for different variables and their Sig. can be

seen from the above table.

Page | 41

From the magnitude of t-statistics we can see that the t-statistics for Borrowings

(.023<.05) is less than 0.05, thus, it has a significant contribution in the model and

the Sig. Value for INTEREST INCOME (0.329>0.05), CLOSE OF BANK NIFTY

(.823>0.05), DEPOSITS (.668>0.05), ADVANCES (.247>0.05) and NET PROFIT

(.311>0.05) is more than 0.05, thus, they don‟t have a significant contribution to

the model. We also look for t-values, which if are above +2 and below -2. Here in

this case only Borrowings match the criteria, thus, it has a significant contribution

in the Model.

The Standardized Beta Values as shown in the above table can be interpreted as

follows:

Interest Income (β =.738): This value indicates that as the interest income

increases by 1 Standard Deviation (2612.99), the Average Price increases by 0.738

Standard Deviation. As the Standard Deviation for Average Price is 281.0478,

thus, a change of 1 Standard Deviation would bring a change of .738 in the price.

This interpretation is only true if the effect of other predictors is held constant.

Advances (β =1.413): This value indicates that as the Advances are increases by 1

Standard Deviation (74660.49), the Average Price increases by 1.413 Standard

Deviation. As the Standard Deviation for Average Price is 281.0478, thus, a

change of 1 Standard Deviation would bring a change of 1.413 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Net Profit (β =-.325): This value indicates that as the Net Profit is increases by 1

Standard Deviation (335.05), the Average Price increases by -.325 Standard

Deviation. As the Standard Deviation for Average Price is 281.0478, thus, a

change of 1 Standard Deviation would bring a change of -.325 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Page | 42

Close of Bank Nifty (β =.077): This value indicates that as the Close of Bank

Nifty increases by 1 Standard Deviation (2314.74), the Average Price increases by

.077 Standard Deviation. As the Standard Deviation for Average Price is

281.0478, thus, a change of 1 Standard Deviation would bring a change of .077 in

the price. This interpretation is only true if the effect of other predictors is held

constant.

Deposits (β =-.446): This value indicates that as the Deposits are increases by 1

Standard Deviation (81172.88), the Average Price increases by -.446 Standard

Deviation. As the Standard Deviation for Average Price is 281.0478, thus, a

change of 1 Standard Deviation would bring a change of -.446 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Borrowings (β =-.839): This value indicates that as the Borrowings are increases

by 1 Standard Deviation (14793.88), the Average Price increases by -.839

Standard Deviation. As the Standard Deviation for Average Price is 281.0478,

thus, a change of 1 Standard Deviation would bring a change of -.839 in the price.

This interpretation is only true if the effect of other predictors is held constant.

Now talking about the rest of the table, we have got zero-order correlations which

are nothing but simple Pearson Correlation Coefficients. The Partial Correlations

represent the relationship between each predictor and the outcome Variable,

controlling for the effect of other predictors. The Part Correlations represent the

relationship between each predictor and the outcome Variable, controlling for the

effect of other predictors on the outcome. In effect, these Part Correlations

represent the unique relationship that each predictor has with the outcome.

Page | 43

STATE BANK OF INDIA

Now coming to the analysis part of SBI, I have taken AVERAGE SHARE PRICE

as DEPENDENT VARIABLE and INTEREST INCOME, ADVANCES, NET

PROFIT, CLOSE OF BANK NIFTY and DEPOSITS as INDEPENDENT

VARIABLES and have applied MULTIPLE REGRESSION to it.

The output summary tables are shown below:

Model Summary

Model R R Square Adjusted R

Square Std. Error of the Estimate Change Statistics

R Square Change F Change df1 df2

Sig. F Change

1 .991(a) .983 .979 79.93108 .983 293.337 5 26 .000

a Predictors: (Constant), Deposits, Interest, Close of Bank Nifty, Net Profit, Advances

ANOVA(b)

Model Sum of Squares df Mean Square F Sig.

1 Regression 9370611.027

5 1874122.205 293.337 .000(a)

Residual 166113.413

26 6388.977

Total 9536724.440

31

a. Predictors: (Constant), Deposits, Interest, Close of Bank Nifty, Net Profit, Advances b. Dependent Variable: Average Price

Page | 44

Coefficients a

Model

Unstandardized Coefficients

Standardized Coeffici

ents t Sig. 95% Confidence

Interval for B Correlations Collinearity Statistics

B Std. Error Beta Lower

Bound Upper Bound

Zero-order Partial Part Tolerance VIF

1 (Constant) 69.512 152.284 .456 .652 -243.514 382.537

Advances .001 .001 .348 2.836 .009 .000 .003 .877 .486 .073 .044 22.474

Net Profit .054 .104 .050 .520 .607 -.160 .269 .808 .101 .013 .072 13.847

Interest .047 .032 .057 1.482 .150 -.018 .113 .629 .279 .038 .446 2.242

Close of Bank Nifty

.195 .012 .812 15.96

0 .000 .170 .220 .979 .953 .413 .259 3.866

Deposits -.001 .001 -.219 -1.521 .140 -.003 .000 .889 -.286 -.039 .032 30.798

a. Dependent Variable: Average Price

MODEL FIT

First of all the MODEL SUMMARY. In this case of STATE BANK OF INDIA

the value of R is .991. This shows that the Predictors have 99.1% influence on the

output.

In this case the value of R2

is .983 this means that the predictors account for 98.3%

variation in the Average Price of the shares.

Here the difference between value of R2 and the Adjusted R

2 is 0.004 (.983-.979)

which is significantly small. This shrinkage means that if model is derived from

the population rather than a sample it would account for approximately 0.4% less

variance in the Outcome.

We can see here that the R Square Change is .983. This is used for calculating the

F-ratio. Thus, the change in amount of variance that can be explained gives rise to

an F-ratio of 293.337, which is significant (p<.001).

Page | 45

ANOVA

The next table here shows the output, which contains an Analysis of Variance

(ANOVA). The Sum of Squares here is 9370611; the value of Residual Sum of

Squares is 166113.4 and the value of F which is 293.337. Here we can conclude

that the value of F is highly significant and our ability to predict the Outcome

Variable is much better.

MODEL PARAMETERS: COEFFICIENTS

This part of model is concerned with the parameters of the model. The Coefficients

table shows us the parameters. We can define the equation here as follows:

Average Price= b0+b1(Interest Income)+b2(Advances)+b3(Net profit)+b4(Close

of Bank Nifty)+b5(Deposits)

Average Price= 69.512 + .047 (Interest Income) + .001 (Advances) +

(.054) (Net profit) + .195 (Close of Bank Nifty) + (-.001) (Deposits)

The B values tell us to what degree each predictor affects the outcome if the effects

of all other predictors are held constant. Here is the analysis.

Interest Income (b=.047): This value indicates that as the interest income

increases by Rs. 1 crore, the Average Price increases by Rs. 0.047. This

interpretation is only true if the effect of other predictors is held constant.

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Advances (b=.001): This value indicates that as the Advances are increases by Rs.

1 crore, the Average Price increases by Rs. 0.001. This interpretation is only true if

the effect of other predictors is held constant.

Net Profit (b=.054): This value indicates that as the Net Profit is increases by Rs.

1 crore, the Average Price increases by Rs. 0.054. This interpretation is only true if

the effect of other predictors is held constant.

Close of Bank Nifty (b=.195): This value indicates that as the Close of Bank Nifty

increases by 1 point the Average Price increases by Rs.0.195. This interpretation is

only true if the effect of other predictors is held constant.

Deposits (b=-.001): This value indicates that as the Deposits are increases by Rs. 1

crore, the Average Price decreases by Rs. 0.001. This interpretation is only true if

the effect of other predictors is held constant.

For this model the value of t-statistic for different variables and their Sig. can be

seen from the above table.

From the magnitude of t-statistics we can see that the t-statistics for ADVANCES

(.009<0.05) and CLOSE OF BANK NIFTY (.000<0.05) is less than 0.05, thus, it

has a significant contribution in the model and the Sig. Value for INTEREST

INCOME (0.150>0.05), DEPOSITS (.140>0.05), and NET PROFIT (.607>0.05) is

more than 0.05, thus, they don‟t have a significant contribution to the model. We

also look for t-values, which if are above +2 and below -2. Here in this case

Advances and Close of Bank Nifty match the criteria, thus, they have a significant

contribution in the Model.

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The Standardized Beta Values as shown in the above table can be interpreted as

follows:

Interest Income (β =.057): This value indicates that as the interest income

increases by 1 Standard Deviation (674.73), the Average Price increases by 0.057

Standard Deviation. As the Standard Deviation for Average Price is 554.65, thus, a

change of 1 Standard Deviation would bring a change of .057 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Advances (β =.348): This value indicates that as the Advances are increases by 1

Standard Deviation (131343.342), the Average Price increases by .348 Standard

Deviation. As the Standard Deviation for Average Price is 554.65, thus, a change

of 1 Standard Deviation would bring a change of .348 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Net Profit (β =.050): This value indicates that as the Net Profit is increases by 1

Standard Deviation (511.46), the Average Price increases by .050 Standard

Deviation. As the Standard Deviation for Average Price is 554.65, thus, a change

of 1 Standard Deviation would bring a change of .050 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Close of Bank Nifty (β =.812): This value indicates that as the Close of Bank

Nifty increases by 1 Standard Deviation (2314.74), the Average Price increases by

.812 Standard Deviation. As the Standard Deviation for Average Price is 554.65,

thus, a change of 1 Standard Deviation would bring a change of .812 in the price.

This interpretation is only true if the effect of other predictors is held constant.

Deposits (β =-.219): This value indicates that as the Deposits are increases by 1

Standard Deviation (98847.83), the Average Price increases by -.219 Standard

Deviation. As the Standard Deviation for Average Price is 554.65, thus, a change

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of 1 Standard Deviation would bring a change of -.219 in the price. This

interpretation is only true if the effect of other predictors is held constant.

Now talking about the rest of the table, we have got zero-order correlations which

are nothing but simple Pearson Correlation Coefficients. The Partial Correlations

represent the relationship between each predictor and the outcome Variable,

controlling for the effect of other predictors. The Part Correlations represent the

relationship between each predictor and the outcome Variable, controlling for the

effect of other predictors on the outcome. In effect, these Part Correlations

represent the unique relationship that each predictor has with the outcome.

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FINDINGS AND CONCLUSION

The analysis of all the various factors affecting the Indian Banking Sector leads us

to some findings and conclusion. While I was doing the project I came across so

many investors, I studied their behavior, their reactions, I studied various research

reports, news articles, and from all that I could find out that each and every thing,

whether a minute one or a big one, affects the Investors decision and thus affects

the share prices. I have listed some factors in the report which affect the share

prices, also I have done a technical analysis for the same, but what comes out at the

end is that there are still so many unnoticed factors which affect the share prices.

This list is not exhaustive; still there is so much which needs to be studied and I

tried to cover as much as I could.

From the analysis, I could find out and conclude that, the Share Prices are affected

by each and every factor in varying degree. The analysis shows that there is a very

small impact of Interest Income, Advances, Deposits, Borrowings and a slightly

more impact of Bank Nifty Index on Share Prices. It is so because there are N

number of factors and it was not possible to quantify each one of them and conduct

the analysis, there were some technical difficulties also which turn out to be the

limitation of the project. But at the end of the analysis we can ACCEPT THE

HYPOTHESIS, as most of the factors, do affect the Share Prices in some or other

manner.

From the three and half month training at India Infoline, I could get that

INVESTORS SENTIMENTS work out most for the market dynamics, this is the

most significant factor which affect Share Prices drastically in either of the

direction. A latest example I can quote is the post election result session on

Monday, 18 May, 2009, when Investors were happy that UPA government was

back into power and the market jumped thousand points up.

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Talking about the investors, what I can suggest them from my study is that they

should be very careful while investing in the Stock Market. The market is simply

UNPREDICTABLE. One should do a proper and detailed analysis before investing

in stocks. Bank‟s shares are pretty safe, as I could find from the analysis. The

Banking Sector is ever growing and thus money invested in it would always give

you good returns. But still one should beware of the Market‟s unpredictable up‟s

and down‟s.

This report is of great help to the company and investors. They can use the analysis

and draw conclusions. Also they can do their own analysis if they want keeping

this Analysis as a base. They can use the tools and techniques to take decision and

play safe in the market.

To conclude my report I would say that what I was able to do in these three and

half months, I did, but still, time was always a limitation and it restricted my work

to certain boundations.

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APPENDIX

TECHNICAL TERMINOLOGY

Some technical terms are frequently used in the all the three analysis.

First of all the MODEL SUMMARY TABLE. This table tells us the whole

story about the relationship of DEPENDENT Variable and INDEPENDENT

variable.

In the MODEL SUMMARY TABLE we can find one column labeled R

which is the value of Multiple Correlation Coefficient between the Predictors

and the Outcome.

In the next column we have R2, which is a measure of how much variability in

the Outcome is accounted for by the Predictors.

The Adjusted R2 gives some idea of how well the model generalizes and

ideally we would like its value to be the same, or very close to, the value of

R2.

The Change Statistics tells us whether the change in the R2

is significant or

not. The significance of R2 can actually be tested using F-ratio.

The R Square Change is used for calculating the F-ratio.

The second table contains an Analysis of Variance (ANOVA) that tests

whether the model is significantly better at predicting the outcome than using

the mean as a “best guess”.

F-ratio represents the ratio of the improvement in the Prediction that results

from fitting the model, relative to the inaccuracy that still exists in the model.

The Sum of Squares represents the improvement in prediction resulting from

fitting a regression line to the data rather than using mean as an estimate of the

Outcome.

The value of Residual Sum of Squares represents the total difference

between the model and observed data.

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The B values tell us about the relationship between Average Price and each

Predictor. If the value is Positive we can tell that there is a positive

relationship between the predictor and the outcome whereas if the value is

Negative than we can say that there is a negative relationship between the

predictor and the outcome.

Each of the Beta values has an associated Standard Error indicating to what

extent these values would vary across different samples, and these Standard

Errors are used to determine whether or not the b-value is significantly

different from zero.

The t-values are also given to test whether a b-value is significantly different

from zero.

The t-test is a measure of whether the predictor is making significant

contribution to the model. Therefore, if the t-test associated with a b-value is

significant (if the value in the column labeled SIG. is less than .05) then the

predictor is making a significant contribution to the model.

The smaller the value of Sig. the greater the contribution of the predictor.

The b-values and their significance are important statistics to look at;

however, the Standardized versions of the b-values are in many ways easier to

interpret.

The Standardized values are provided here under label BETA (β), and they

tell us the number of Standard Deviations that outcome will change as a result

of one Standard Deviation change in the Predictor.

The Standardized Beta Values are measured in Standard Deviation units and

so are directly comparable; therefore, they provide a better insight into

importance of a Predictor in the Model.

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REFERENCES:

The following articles from internet have been used for the study purpose:

(a) www.nseindia.com

(b) www.bseindia.com

(c) www.sharegyan.com

(d) www.moneycontrol.com

(e) www.statebankofindia.com

(f) www.hdfcbank.com

(g) www.icicibank.com

(h) www.economictimes.indiatiome.com

(i) www.business-standard.com

(j) www.wikepedia.com

(k) Guidance from company mentor Mr. Chintan Shah