1.1 INTRODUCTION ABOUT THE TOPIC

1.1.1 Indian economy - overviewThe Economy of India is the tenth largest in the world by nominal GDP and the fourth largest by

purchasing power parity (PPP). The country's per capita GDP (PPP) is $3,339 (IMF, 129th) in

2010. Following strong economic reforms from the post-independence socialist economy, the

country's economic growth progressed at a rapid pace, as free market principles were initiated in

1991 for international competition and foreign investment. Despite fast economic growth India

continues to face massive income inequalities, high unemployment and malnutrition.

1.1.2GDP contribution of stock market to the economyHowever, as a result of the financial crisis of 2007–2010, coupled with a poor monsoon, India's

gross domestic product (GDP) growth rate significantly slowed to 6.7% in 2008–09, but

subsequently recovered to 7.4% in 2009–10, while the fiscal deficit rose from 5.9% to a high

6.5% during the same period. India’scurrent account deficit surged to 4.1% of GDP during Q2

FY11 against 3.2% the previous quarter. The unemployment rate for 2009–2010, according to

the state Labour Bureau, was 9.4% nationwide, rising to 10.1% in rural areas, where two-thirds

of the 1.2 billion populations live.

India's large service industry accounts for 57.2% of the country's GDP while the industrial and

agricultural sectors contribute 28.6% and 14.6% respectively. Agriculture is the predominant

occupation in India, accounting for about 52% of employment. The service sector makes up a

further 34%, and industrial sector around 14%.However, statistics from a 2009-10 government

survey, which used a smaller sample size than earlier surveys, suggested that the share of

agriculture in employment had dropped .

1.1.3Stock market

The Indian Equity market is divided in to two parts Primary market - where the share is first

issued in the form of IPO (Initial Public Offering) and after issuing the share it is listed on

exchange and share is traded on exchange where shares can be bought and sold this is secondary

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market. In India mainly there are two exchanges -NSE (National Stock Exchange) BSE-Bombay

Stock Exchange. The BSE is the oldest exchange in India(started in 1875).NSE started operation

on 1994.Before 2000 shares was held in Physical form But the main difficulty with Physical

shares is method of transaction which is open outcry system and process is not transparent to

investor also Physical shares were prone to duplication and fraud. So in 2000 NSE introduced the

electronic screen based trading system further the introduction of Dematerialization(Conversion

of physical share in to electronic form) and depository(where the electronic form of share is

kept) revolutionized the Indian Stock market. Currently there are mainly two Depository (DP) -

NSDL and CDSL and these DP are like bank of share. Individual/Firm can deal through Broker

(who is registered and having membership in Exchanges and Depository) for buying and selling

securities. Today NSE outpaced BSE in volume of trade. Then what is the purpose of stock

market? Stock market serves the company by providing company the finance for long term needs

and for investor an opportunity to park their savings in corporate world and in turn give their

hand in Nation's development so stock exchange have a very vital role in country's economic

development.

1.1.4The behavior of the stock market

Investors may 'temporarily' move financial prices away from their long term aggregate price

'trends'. (Positive or up trends are referred to as bull markets; negative or down trends are

referred to as bear markets.) Over-reactions may occur—so that excessive optimism (euphoria)

may drive prices unduly high or excessive pessimism may drive prices unduly low. Economists

continue to debate whether financial markets are 'generally' efficient.

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1.2 INTRODUCTION ABOUT THE STOCK MARKET AND SCRIPT

1.2.1 The Bombay stock exchangeBombay Stock Exchange (BSE) SENSEXis the benchmark index for the Indian stock market. It is

the most frequently used indictor while reporting on the state of the market. Sensex is not only

scientifically designed but also based on globally accepted construction and review

methodology. First compiled in 1986, SENSEX is a basket of 30 constituent stocks representing

a sample of large, liquid and representative companies. The base year of SENSEX is 1978-79

and the base value is 100. The index is widely reported in both domestic and international

markets through print as well as electronic media.

1.2.2 Technology of Bombay stock exchangeThe Index was initially calculated based on the “Full Market Capitalization” methodology but

was shifted to the free-float methodology with effect from September 1, 2003. The “Free-float

Market Capitalization” methodology of index construction is regarded as an industry best

practice globally. All major index providers like MSCI, FTSE, STOXX, S&P and Dow Jones use

the Free-float methodology.

1.2.3 IndicesThe launch of SENSEX in 1986 was later followed up in January 1989 by introduction of BSE

National Index (Base: 1983-84 = 100). It comprised 100 stocks listed at five major stock

exchanges in India - Mumbai, Calcutta, Delhi, Ahmedabad and Madras. The BSE National Index

was renamed BSE-100 Index from October 14, 1996 and since then, it is being calculated taking

into consideration only the prices of stocks listed at BSE. BSE launched the dollar-linked version

of BSE-100 index on May 22, 2006. BSE launched two new index series on 27 May 1994: The

'BSE-200' and the 'DOLLEX-200'. BSE-500 Index and 5 sectorial indices were launched in

1999. In 2001, BSE launched BSE-PSU Index, DOLLEX-30 and the country's first free-float

based index - the BSE TECk Index. Over the years, BSE shifted all its indices to the free-float

methodology (except BSE-PSU index).BSE disseminates information on the Price-

EarningsRatio, the Price to Book Value Ratio and the Dividend Yield Percentage on day-to-day

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basis of all its major indices. The values of all BSE indices are updated on real time basis during

market hours and displayed through the BOLT system, BSE website and news wire agencies. All

BSE Indices are reviewed periodically by the BSE Index Committee. This Committee which

comprises eminent independent finance professionals frames the broad policy guidelines for the

development and maintenance of all BSE indices. The BSE Index Cell carries out the day-to-day

maintenance of all indices and conduct researchon development of new indices.

1.2.4 The National Stock Exchange The National Stock Exchange (NSE) is a stock exchange located at Mumbai, India. It is the 9th

largest stock exchange in the world by market capitalization and largest in India by daily

turnover and number of trades, for both equities and derivative trading. NSE has a market

capitalization of around US$1.59 trillion and over 1,552 listings as of December 2010. 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 NSE NIFTY

(National Stock Exchange Fifty), 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. 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%.

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1.2.5 Indices

NSE also set up as index services firm known as India Index Services & Products Limited (IISL)

and has launched several stock indices, including:

S&P CNX Nifty(Standard & Poor's CRISIL NSE Index)

CNX Nifty Junior

CNX 100 (= S&P CNX Nifty + CNX Nifty Junior)

S&P CNX 500 (= CNX 100 + 400 major players across 72 industries)

CNX Midcap (introduced on 18 July 2005 replacing CNX Midcap 200)

CNX it

Bank Nifty

India Vix

S&P CNX Defty

Nifty Midcap 50

CNX Infra

CNX Realty

1.2.6 CNX Nifty Junior

The CNX Nifty Junioris an index for companies on the National Stock Exchange of India. It represents the next rung of liquid securities after S&P CNX Nifty. It consists of 50 companies representing approximately 10% of the traded value of all stocks on the National Stock Exchange of India. The CNX Nifty Junior is owned and operated by India Index Services and Products Ltd. It is quoted using the symbol NSMIDCP.

As with the S&P CNX Nifty, stocks in the CNX Nifty Junior are filtered for liquidity, so they are the most liquid of the stocks excluded from the S&P CNX Nifty. The maintenance of the S&P CNX Nifty and the CNX Nifty Junior are synchronized so that the two indices will always be disjoint sets; i.e. a stock will never appear in both indices at the same time. Hence it is always meaningful to pool the S&P CNX Nifty and the CNX Nifty Junior into a composite 100 stock indexes.

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CNX Nifty Junior represents about 11.99 % of the Free Float Market Capitalization as on Mar 31, 2011.

The traded value for the last six months of all Junior Nifty stocks is approximately 14.37% of the traded value of all stocks on the NSE.

Impact cost for CNX Nifty Junior for a portfolio size of Rs.25 lakhs is 0.09%. From May 04, 2009, CNX Nifty Junior is computed based on free float methodology.

1.2.7 Market Capitalisation

This is a chart of companies listed in the CNX Nifty Junior index by market capitalisation as on June 2011 with figures in Indian Rupees.

Security name Industry Equity capital (In Rs.)

Adani Enterprises Ltd. trading 1099810083Aditya Birla Nuvo Ltd. textiles - synthetic 1135097290Andhra Bank banks 5595803640Ashok Leyland Ltd. automobiles - 4wheelers 1330338317Asian Paints Ltd. paints 959197790Bank of Baroda banks 3915460790Bank of India banks 5464803700Bharat Electronics Ltd. electronics - industrial 800000000Bharat Forge Ltd. castings/forgings 465588632Biocon Ltd. pharmaceuticals 1000000000Canara Bank banks 4430000000Coal India Ltd. mining 63163644000Colgate Palmolive (India) Ltd. personal care 135992817Container Corporation of IndiaLtd. travel and transport 1299827940Crompton Greaves Ltd. electrical equipment 1282983072Cummins India Ltd. diesel engines 396000000Exide Industries Ltd. auto ancillaries 850000000Federal Bank Ltd. banks 1712115340GMR Infrastructure Ltd. construction 3892434782Glaxosmithkline Pharmaceuticals Ltd. pharmaceuticals 847030170Glenmark Pharmaceuticals Ltd. pharmaceuticals 270323853Hindustan Petroleum Corporation Ltd. refineries 3386272500Housing Development and Infrastructure Ltd.

construction4150039860

IDBI Bank Ltd. banks 9845532150IFCI Ltd. financial institution 7378373310Indian Hotels Co. Ltd. hotels 759472787Indian Overseas Bank banks 6187493430IndusInd Bank Ltd. banks 4659608850JSW Steel Ltd. steel and steel products 2231172000LIC Housing Finance Ltd. finance - housing 949326000Lupin Ltd. pharmaceuticals 892595198

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MphasiS Ltd. computers - software 2100020560Mundra Port and Special Economic Zone Ltd.

travel and transport4006788200

Oracle Financial Services Software Ltd.

computers - software419510760

Patni Computer Systems Ltd. computers - software 267715336Power Finance Corporation Ltd. financial institution 13199317050Punj Lloyd Ltd. construction 664191490Rural Electrification Corporation Ltd. financial institution 9874590000Shriram Transport Finance Co. Ltd. finance 2261606680Syndicate Bank banks 5732856710Tata Chemicals Ltd. chemicals - inorganic 2547562780Tech Mahindra Ltd. computers - software 1260553760Titan Industries Ltd. gems, jewellery and

watches 887786160Torrent Power Ltd. power 4724483080UltraTech Cement Ltd. cement and cement

products 2740458750Union Bank of India banks 5243324150United Phosphorus Ltd. pesticides and

agrochemicals 923608548United Spirits Ltd. brew/distilleries 1307949680Yes Bank Ltd. banks 3479787240Zee Entertainment Enterprises Ltd. media & entertainment 978076130

Total 203,106,525,365

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1.2.8 LIC housing finance limitedLIC Housing Finance Ltd., the largest Housing Finance Company in India was established on

19th June 1989 under the Companies Act, 1956. The company is promoted by LIC of India. The

company is recognized by National Housing Bank and listed on the National Stock Exchange

(NSE) & Bombay Stock Exchange Limited (BSE) and its shares can be traded only in

Dematformat. The company provides long term finance to individuals for purchase,

construction, repair and renovation of new, existing flats, houses. Company also provides

finance for business, personal needs against existing property. It also gives loans to

professionals for purchase, construction of Clinics, Nursing Homes, Diagnostic Centers, and

Office Space and also for purchase of equipments.

Over its existence of around 50 years, Life Insurance Corporation of India, which commanded a

monopoly of soliciting and selling life insurance in India, created huge surpluses, and

contributed around 7 % of India's GDP in 2006.

The Corporation, which started its business with around 300 offices, 5.6 million policies and a

corpus of INR 459 million (US$ 92 million as per the 1959 exchange rate of roughly Rs. 5 for a

US $ [4], has grown to 25000 servicing around 350 million policies and a corpus of over 8

trillion (US$178.4 billion).

The recentEconomic Times Brand Equity Survey rated LIC as the No. 1 Service Brand of the

Country. The slogan of LIC is "Zindagikesaathbhi, Zindagikebaadbhi"in Hindi. In English it

means "during life and after life”.

In 2009 LIC Housing Finance cut interest rates for new loans by 0.5% where for customers

opting for floating rate loans between Rs.30 lakh andRs.75 lakh, the new rates will be 8.755

against 9.25%.

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1.2.9 Products of LIC housing finance limited Home Loans- It provides a range of services serving various needs of individuals,

NRIs and pensioners related to housing.

Corporate Loans- TheCompany offers financial assistance to corporate for purchasing,

constructing, renovating and repair of housing property.

Builders/Developers- It provides loans to builders or developers for construction of

housing projects for commercialization.

1.2.10 Income of the company Interest on housing loans

Processing fees & service charges

Income from sale of share & securities

Interest

Fes & other charges

Finance & service charges

Other service charges.

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1.3 PROBLEM DEFINITION

The small and medium investors can be motivated to save and invest in the capital market only if

their securities in the market are appropriately priced. The information content of events and its

dissemination determine the efficiency of the capital market. That is how quickly and correctly

security prices reflect these information show the efficiency of the capital market. In the developed

countries, many research studies have been conducted to test the efficiency of the capital market with

respect to information content of events. Whereas in India, very few studies have been conducted to

test the efficiency of the capital market with respect to scam, stock split and profit booking

announcements, even after these studies have been conducted with different industries with different

period. Hence present study is an attempt to test the efficiency of the Indian stock market with

respect to information content of LIC housing finance limited.

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1.3 NEED OF THE STUDY

Stock market has been subjected to speculations and inefficiencies, which are beachedto the

rationality of the investor. Traditional finance theory is based on the two assumptions. Firstly,

investors’ make rational decisions; and secondly investors areunbiased in their predictions about

future returns of the stock. However financialeconomist have now realized that the long held

assumptions of traditional financetheory are wrong and found that investors can be irrational and

make predictableerrors about the return on investment on their investments.

This empirical study on Individual Investors’ Behavior is an attempt to know the profile of the

market and also know the characteristics of the market so as to know their preference with

respect to their investments. The study also tries to unravel the influence of demographic factors

like gender and age on risk tolerance level of the investor.

1.4 SCOPE OF THE STUDY

This study covers all types of investor in Indian stock market and taken to major information

passed in the market due to high and low movement of the price fluctuation related to the

market.Also, this research study is made based on efficient market hypotheses (semi-strong form

of efficient market hypotheses) to know the impact of events occurred in the market. Such as,

1. Scam

2. Stock split

3. Profit booking

In future, this study helps the researchers to measure the impact of those events will happened in

the stock market and suggest the investor to earn superior risk-adjusted return.

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1.6 OBJECTIVES OF THE STUDY

To assess the pricing behavior of the events in LIC HOUSING FINANCE LIMITED.

To evaluate the risk of the stocks in in particular index.

To identify the effect of those events in the whole market.

To estimate the future price for the script and market.

To suggest the appropriate alternative for investor.

To suggest investors to buy, hold and sell stock in the market.

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2. LITERATURE REVIEW

A study by George E. Pinches (1970) found that the random walk hypothesis implies that the

price movements are virtually independent of past price movement. The study reveals that the

random – walk hypothesis may be incorrect or, at least incomplete.

McEnally (1971) and Beaver, Clarke and Wright (1979) report significant contemporaneous

correlations between the magnitude and sign of unexpected annual earnings changes and the

magnitude and sign of abnormal returns in the period preceding the annual earnings release.

Edward M. Miller (1979) in his study argues that any non-random fluctuation in price (other

than a steady upward drift approximating the risk adjusted rate of returns) would be exploited by

speculators who would buy before an expected fall, eliminating any predictable functions and

making all price changes random

Obaidullah (1990) studied 33 securities which performed well. The author has reported that

earnings showed an increasing trend much before the announcement week. The study entitled

“Random Walks in Stock Market Prices.

Elroy Dimson and MassoudMussavian (1998), in their study narrated that the efficient markets

hypothesis is simple in principle but remains elusive. It is hard to profit from even the most.

AbhijitDutta (2001) has examined the investors‟ reaction to information using primary data

collected from 600 individual investors and observes that the individual investors are less

reactive to bad news as they invest for longer period.

Prabina Das, S. SrinivasanandA. K. Dutta (2000) have studied the reaction of GDR prices and

the underlying share prices to the announcement of dividends and found that the CAR for the

GDR is mostly negative irrespective of the rate of dividend whereas the domestic share prices

react in a more synchronous manner.

An attempt was made by Kun Shin Im, Kevin E. Dow and Varun Grover (2001) in their study,

examined the changes in the market value of the firm as reflected in the stock price in response

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to IT investment announcements. Reactions of price and volume were negatively related to firm

size and became more positive over time.

JijoLukose and Narayan Rao (2002) examined the security price behaviour around the

announcement of stock splits and around ex-split date.

Horvath and Zuckerman (1993) suggested that one’s biological, demographic and

socioeconomic characteristics; together with his/her psychological makeup affects one’s risk

tolerance level.

Mittra (1995) discussed factors that were related to individuals risk tolerance, which included

years until retirement, knowledge sophistication, income and net worth.

Cohn, Lewellen et.al found risky asset fraction of the portfolio to be positively correlated with

income and age and negatively correlated with marital status.

Lewellen et.al while identifying the systematic patterns of investment behavior exhibited by

individuals found age and expressed risk taking propensities to be inversely related with major

shifts taking place at age 55 and beyond.

Yoo (1994) found that the change in the risky asset holdings were not uniform. He found

individuals to increase their investments in risky assets throughout their working life time,

and decrease their risk exposure once they retire.

The NCAER's studies brought out the frequent form of savings of individuals and the

components of financial investments of rural households. The Indian Shareowners Survey

brought out a volley of information on shareowners.

Rajarajan V (1997, 1998, 2000 and 2003) classified investors on the basis of their

demographics. He has also brought out the investors' characteristics on the basis of their

investment size. He found that the percentage of risky assets to total financial investments had

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declined as the investor moves up through various stages in life cycle. Also investors' lifestyles

based characteristics has been identified.

Al – Tamimi (2007) identified company fundamental factors (performance of the company,

achange in board of directors, appointment of new management, and the creation of new assets,

dividends, earnings), and external factors (government rules and regulations, inflation, and other

economic conditions, investor behavior, market conditions, money supply, competition,

uncontrolled natural or environmental circumstances) as influencers of asset prices. He

developed a simple regression model to measure the coefficients of correlation between the

independent and dependent variables.

Rigobon and Sack (2004) discovered that increases in war risk caused declines in Treasury

yields and equity prices, a widening of lower-grade corporate spreads, a fall in the dollar, and a

rise in oil prices. A positive correlation exists between the price of oil and war. They argue that

war has a significant impact on the oil price.

Tymoigne (2002) argue that in the financial market, banking convention and financial

convention work together to fix the assets’ market prices. According to him the financial

convention creates a speculative sentiment of whether capitalists are more prone to sell, or to buy

assets while the banking convention determines the state of credit as evidenced by the confidence

of the banking sector and ability of investors accessing credit leverage for asset acquisition

purpose. He concluded that “conventions do not determine asset-price, it is the “law of supply

and demand” that does so, conventions“only” influence the behaviors of financial actors”

Inflation as an external factor exerts a very significant negative influence on the stock prices.

Molodovsky (1995) believes that dividends are the hard core of stock value. The value of any

asset equals the present value of all cash flows of the asset.

Blume (1971) used monthly prices data and successive seven-year periods and shown that the

portfolio betas are very stable where as individual security betas are highly unstable in nature.

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He shows that, the stability of individual beta increases with increase in the time of estimation

period.

Allen et al. (1994) have considered the subject of comparative stability of beta coefficients for

individual securitiesand portfolios. The usual perception is that the portfolio betas are more

stable than those for individualsecurities. They argue that if the portfolio betas are more stable

than those for individual securities, thelarger confidence can be placed in portfolio betaestimates

over longer periods of time. But, their studyconcludes that larger confidence in portfolio betas is

not justified

Alexander and Chervany (1980) show empirically that extreme betas are less stable compared

to interior beta. They proved it by using mean absolute deviation as a measure of stability.

According to them, best estimation interval is generally four to six years. They also showed that

irrespective of the manner portfolios are formed, magnitudes of inter-temporal changes in beta

decreases as the number of securities in the portfolio.

Haddad (2007) examine the degree of return volatility persistence and time-varying nature of

systematic risk of two Egyptian stock portfolios. He used the Schwert and Sequin (1990) market

model to study the relationship between market capitalization and time varying beta for a sample

of investable Egyptian portfolios during the period January, 2001 to June, 2004.

According to Haddad, the small stocks portfolio exhibits difference in volatility persistenceand

time variability. The study also suggests that the volatility persistence of each portfolio and its

systematic risk are significantly positively related. Because of that, the systematic risks of

different portfolios tend to move in a different direction during the periods of increasing market

volatility.

McNulty et al (2002) highlight the problems with historical beta when computing the cost of

capital, and suggest as an alternative- the forward-looking market-derived capital pricing model

(MCPM), which uses option data to evaluate equity risk.

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Siegel (1995) notes the improvement of a beta based on forward-looking option data,

and proceeds to propose the creation of a new derivative, called an exchange option, which

would allow for the calculation of what he refers to as “implicit” betas. Unfortunately the

exchange options discussed by Siegel (1995) are not yet traded, and therefore his method cannot

be applied in practice to compute forward-looking betas.

Scott & Brown (1980) show that when returns of the market are subjected to measurement

errors, the concurrent auto correlated residuals and inter-temporal correlation between market

returns and residual results in biased and unstable estimates of betas. This is so even when true

values of betas are stable over time.

Vipul (1999) examines the effect of company size, industry group and liquidity of the scrip on

beta. He considered equity shares of 114 companies listed at Bombay Stock Exchange from July

1986 to June 1993 for his study. He found that size of the company affects the value of betas and

the beta of medium sized companies is the lowest which increases with increase or decrease in

the size of the company. The study also concluded that industry group and liquidity of the scrip

do not affect beta.

Gupta &Sehgal (1999) examine the relationship between systematic risk and accounting

variables for the period April 1984 to March 1993. There is a confirmation of relationship in the

expected direction between systematic risk and variables such as debt-equity ratio, current ratio

and net sales. The association between systematic risk and variables like profitability, payout

ratio, earning growth and earnings volatility measures is not in accordance with expected sign.

In Canada Ikenberry et.al (2000) found that the Canadian experience is similar to the earlier

evidence obtained for US buyback and the initial market reaction to repurchase programs is

small.

The abnormal return is less than 1 % in the announcement month. They also found that the

market on average seems to under estimate the information contained in repurchase

announcements. Further using a three-factor model, abnormal performance over a three year

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holding period is about seven percent per year. Their finding is consistent with well documented

findings in the United States, that long run abnormal stock returns for these cases are negative

Ikenberry and Vermaelen (1996) found that announcement returns are directly related to the

volatility of the stock and the fraction of shares to be purchased. They also found that the market

reaction is negatively related with the correlation co-efficient between stock returns and market

returns.

McNally. W, (1998), suggests that the two types of offers generate roughly the same total

returns (about 10–11%, on average, during the offering period) to shareholders who do not

tender. Fixed-price offers involve considerably larger premiums (over the new, "full-

information" price) and wealth transfers than Dutch auctions. Reflecting the higher premiums,

shareholders tendering into fixed-price offers receive higher returns than those tendering into

Dutch auctions (13.8% vs. 11.3% during the announcement period). He also finds some evidence

of fixed-priceoffers involve a considerably larger wealth transfer from non-tendering to

tendering shareholders, fixed-price repurchases compensate the non-tendering shareholders for

the larger wealth transfer with larger increases in "intrinsic value," thus generating the same total

return as Dutch auctions.Moreover, despite the large premiums offered in both types of offers,

the wealth transfer implicit in the premium represents a small cost (less than 1% in fixed-price

offers, and less than 0.1% in Dutch auctions) to non-tendering shareholders.

Isagawa (2002) examined corporate open market repurchase strategy and stock price behavior.

He establishes a signaling equilibrium with the assumption that the firm is committed to an

announcement of open-market repurchase intention. He also found that positive long run stock

returns as well as positive announcement effects following open-market repurchase

announcements.

Schaub, Mark (2008), provides some evidence that debt buybacks may have beneficial impacts

on stockholders’ holding period returns and cash flows. His analysis is based on the ‘all things

constant’ model popularized by Modigliani and Miller in the capital structure and dividend

policy papers. He concludes, firms can obviously benefit by repurchasing their debt when market

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values have decreased. His study also suggests debt buybacks may be valuable to stockholders in

and of themselves, not just in times of rising interest rates and downgraded bond ratings.

Schaub, Mark (2009) finds some evidence of wealth effects associated with debt buyback

announcements. He observed significant positive average returns on the announcement date

reflect investors’ opinion that the event is considered ‘good’ news. He also suggest further

research to find out whether there are long-term positive effects or even intra-industry

information effects associated with such announcements.

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3. RESEARCH METHODOLOGY

3.1 Research methodology Research methodology is a way to systematically solve the research problem. Thus when we

talk of research method but also consider the logic behind the methods we use in the context of

our research study and explain why we are capable of being evaluated either by the researchers

himself or by others.

3.2 Research designResearch design is the arrangement of conditions for collection and analysis of data in a manner

that aims to combine relevance to the research purpose with economy in procedure. The research

design used in the this study is empirical in nature the procedure which researchers has to use act

or information already available, andanalyze these to make a critical evaluation of the

performance.

3.2.1 Type of research Empirical research which is used appropriate when proof is sought, that certain variables affect

another variable in some way. Evidence gathered through experiment or empirical studies is

today considered to be the most powerful support possible for a given hypothesis.

3.2.2 Method of data collectionThis research is conducted by using secondary data which are obtained from the journals and

official websites like www.nseindia .com,www.bseindia.com, www.sebi etc.

3.2.3 Steps in event study

i) Semi-strong form of efficient market hypothesesThe SEMI-STRONG form efficient market hypothesis holds that stock price adjust rapidly to all

publically available information. This implies that using publicly available information investor

will not be able to earn superior risk-adjusted returns.

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ii) Event study An Event study examines the market reactions to and the excess market returns around a specific

information event like acquisition announcement or stock split.

iii) Steps involvedin event study,

a) Identify the event date

Event studies presume that the timing of the event can be specified with a fair degree of

precision. Because financial markets react to the announcement date of the event.

b) Collect return data around the announcement date

In this context two issues have to be resolved: What should be the period for calculating

returns ---- Weekly, daily, or some other interval? For how many periods should returns be

calculated before and after the announcement date?

Rj,- n -------------------------- Rj,0 ------------------------Rj,+n

|________________________|_____________________|

Return window: -n to +n

Rj, t = return for firm j for period t (t = -n … 0… +n)

c) Calculate the excess return

The excess return is calculated as:

E Rjt = Rjt – Beta j × Rmt

d) Compute the average excess return

The average excess return is

ERt= ∑j=1

j=m ERjtm

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e) T statistics

d =∑ d /n

sd2=∑ d−(∑ d /n)2n−1

Sd = √sd2

T = dsd / √ n

f) Future price estimation

a) Pivot point analysisMarket analysts or experienced traders talking about an equity price nearing a certain support or

resistance level, each of which is important because it represents a point at which a major price

movement is expected to occur. Pivot point is calculated using the following formula,

PP =H+L+C 3 R1 = (2×PP)-L R2=PP+ (H-L) S1 = (2×PP)-H S2=PP-(H-L)

3.3 Limitations of the Study

The present study is confined to only the three events announcement.

This study is restricted with only selected securities in financial sector.

All the limitation of the tools is applicable to this study.

The study based on the past data, which may not guarantee to the future of the market.

22

4. ANALYSIS AND INTERPRETATIONS

Table 4.1.1

Calculation of returns during the event of Scam

AN

DR

A

BA

NK

BO

I

BO

B

CA

N B

AN

K

FEDER

AL

IDB

I

IFCI

IND

USIN

D

IOB

LICH

OU

SING

FIN

AN

CE

PFC

SHR

I RA

M

TRO

NS

SYN

DIC

ATE

UN

ION

BA

NK

YES B

AN

K

6.173285

-0.61947

1.117164

1.585678

0.11236

0.988061

-1.72414

-0.7381

5.720824

0.718774

2.243887

1.659892

4.897959

0.138037

0.235571

1.596877

0.293112

2.56987

-1.19625

-0.45997

0.421941

-3.25581

1.013848

1.669596

-1.59793

1.82984

4.660121

0.714286

0.279503

3.192568

2.533784

0.194784

1.220779

1.759353

1.91358

0.666667

2.006689

-0.33408

-0.7657

4.764228

2.618831

-2.8951

0.901713

1.16106

-0.42188

-2.73189

-3.91398

-2.32852

-2.86322

-0.8046

-2.8366

-2.82158

0.328947

-1.25

-1.19028

2.31441

-1.9

-3.1654

-1.57879

-1.73913

3.6875

1.010101

2.588652

1.804577

-0.92246

0.25

-0.74257

-2.57785

-1.61801

0.529166

1.390071

-1.76617

-2.95483

-0.22849

-0.99398

-2.15569

-0.89641

-0.37585

0.693842

-0.23033

-0.38911

-1.11111

0.869061

-0.11042

2.611781

0.220523

-0.34884

-0.29991

-0.19481

3.672566

0.665054

-0.71809

2.164021

-0.16008

1.394799

0.763845 0

-3.23944

2.196339

-0.66549

-2.61905

-2.58125

-0.57471

-0.58132

4.598738

2.762431

-3.74074

0.136959

-1.32653

-0.82155

-1.19534

-1.00806

-0.79422

2.686203

0.083636

-0.95745

0.784695

0.105634

0.942029

1.568365

23

-2.18328

-1.38441

1.989418

-0.0387

0.857143

-1.3764

-1.82349

3.36375

-15.9722

-17.6769

-2.81223

0.552022

-3.66197

-3.89037

-2.3141

-3.50257

-3.91494

-1.57579

1.26087

-3.44828

-3.66071

-2.90196

0.647986

-2.10339

-3.29659

-0.43269

-5.0964

-3.46048

-2.64438

-2.8871

-1.75831

-1.85083

-0.5958

0.366412

-1.40652

-0.68534

-6.71429

0.804505

-0.83045

-0.83069

0.890625

0.006418

-0.57427

0.570547

-0.27331

-1.84995

-0.06821

-0.30182

-4.46071

-2.96438

-3.06843

-2.87009

-2.61975

-0.74733

-3.4748

-1.69799

-3.13482

-3.375

-1.27988

-3.3959

3.452381

-1.85079

1.207108

7.103321

0.493333

0.694444

-0.78534

-2.25564

4.2

2.832694

2.383038

2.83241

3.612073

2.269821

0.922509

0.507246

2.080977

1.612138

0.675439

-1.7227

0.901226

3.32681

-0.51043

-3.27103

-0.81164

-2.69084

-0.81618

-5.83116

-0.15106

-3.11693

2.374491

0.403226

1.30521

1.271402

-0.20795

1.972963

-2.65082

2.041722

-2.23607

-4.25267

-6.23197

0.039891

-2.14818

-3.79154

0.67352

-1.99301

-0.35714

2.655742

-1.67229

1.773683

0.143472

0.385356

1.401274

-0.54348

-0.46308

-0.05702

-1.38618

-1.12896

-1.89132

-1.18613

0.325851

-3.93692

0.38108

-3.30684

0.77027

-2.81433

-2.99345

-1.09778

0.983837

-1.79949

-3.88455

-0.22925

-3.91823

0.270433

-0.27273

2.456839

1.4375

0.005258

1.382962

0.0356

1.673497

-0.9688

1.986507

-1.41892

0.214133

1.253596

-1.2037

1.672787

1.222142

0.143426

24

Inference

The above table depicts that the market return of can bank is highest return 7.10% among the selected securities. And the securities of IFCI have a lowest market during the period of scam. The stock of LIC housing finance has an average decreasing. The returns of can bank and bank of Baroda are moderate. The return of IFCI shows most of negative return that indicates the in efficient transaction on it stock. The market return of Andhra bank is moderate level.

Figure 4.1.1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

-20

-15

-10

-5

0

5

10

ANDRA BANK

BOI

BOB

CAN BANK

FEDERAL

IDBI

IFCI

INDUSIND

IOB

LIC HOUSING IFNANCE

PFC

SHRI RAM TRONS

SYNDICATE

UNION BANK

YES BANK

25

Table 4.1.2

Calculation of returns during the event of Stock split

AN

DH

AR

A

BA

NK

BA

NK

OF

IND

IA

BA

NK

OF

BA

RO

DA

CA

N B

AN

K

FEDER

AL

BA

NK

IDB

I

IFCI

IND

USIN

D

IOB

LIC

HO

USIN

G

FINA

NC

E

PFC

SHR

I RA

M

TRA

NSPO

SYN

DIC

AE

UN

ION

B

AN

K

YES B

AN

K

-2.07039

1.148649

-1.62533

-0.17818

-2.50742

-1.20232

-5.68

-1.38756

0.239234

1.244315

0.078125

1.853448

-0.61234

-0.54688

-1.23333

-1.43162

-0.71455

0.072289

-1.54649

-0.37969

0.880551

0.566343

-1.9569

0.516796

-0.88403

-0.28443

4.586471

1.807229

-0.41322

-2.84291

-1.17759

-0.52632

-0.95438

1.642145

-0.14409

-4.77778

-0.2461

2.302632

-0.33383

0.371901

-0.61924

-2.55663

-0.38793

0.172662

-0.73209

-0.50595

-1.57388

1.218391

-0.79324

-1.29288

1.267606

0.895037

0.150801

-0.35398

0.758491

-1.32645

2.416667

-0.64103

1.527022

0.347432

1.766467

1.000435

1.606742

-0.74576

-0.74506

1.352201

1.796407

1.204593

8.852584

-1.44422

0.868347

-0.53934

3.237705

0.44287

-0.74647

-0.05882

0.30303

2.407138

0.465839

1.272265

-1.67702

0.206897

-2.71628

-0.65441

-2.79856

-0.26027

0.483029

-1.49645

2.807108

1.954023

0.502793

1.725936

-0.20059

2.210744

3.04814

-0.73851

2.642857

6.538748

0.464109

-1.04558

0.511898

-3.06054

0.353357

-0.98727

2.739917

0.509554

1.449275

3.449227

3.417015

1.071225

2.1875

0.163934

-0.56122

6.666667

5.452632

6.297348

5.252591

1.360294

1.177484

-1.55949

0.395778

0.512243

0.813824

0.305742

-0.84534

1.122544

2.396694

0.299177

1.028807

0.374137

2.458761

7.715278

2.34533

0.434783

-1.00162

26

1.325629

0.62379

0.399775

0.68567

0.278975

0.15625

0.474308

0.297147

0.248315

0.832405

-3.00126

-0.72575

0.198649

1.658551

0.146628

0.664452

0.515002

0.375587

-0.22852

0.907895

1.671123

4.227783

3.275202

1.081686

-0.02941

-0.57054

1.853418

0.571429

3.234375

0.218579

-4.6858

1.6

-1.40853

-2.38786

-4.64466

-7.36156

-6.27119

-4.58065

-1.20155

0.516304

-3.91304

-0.64036

-3.74307

-4.19259

-5.03674

1.397059

-0.23596

-0.22005

0.660377

3.414634

2.065131

-1.12474

2.857143

6.666667

5.452632

6.297348

5.252591

1.360294

1.177484

-1.55949

-0.27759

-2.01064

-4.38846

-0.02626

-2.80172

-4.78163

-6.18956

-2.52723

1.028807

0.374137

2.458761

7.715278

2.34533

0.434783

-1.00162

-1.9971

2.860697

-1.31106

0.801653

-2.10456

-1.28064

-0.84746

-0.68196

0.248315

0.832405

-3.00126

-0.72575

0.198649

1.658551

0.146628

0.702001

-6.31166

2.524862

0.228758

0.666144

0.867052

0.560748

0.904194

1.081686

-0.02941

-0.57054

1.853418

0.571429

3.234375

0.218579

-3.90323

0.054705

-2.4856

-1.31045

-0.18863

-3.23333

-3.48432

-0.96522

-0.88496

-2.24424

-4.71876

0.506273

1.336634

-0.88258

3.168191

1.25261

5.486746

0.025251

0.229008

1.662791

-0.36304

-1.48976

-1.88053

-0.41322

-0.26247

-0.58952

-1.31731

0.971267

-0.04376

-0.3942

Inference

The securities of Indian overseas bank IOB performed in a profitable way based on its highest market return as 8.85% and 6.66% respectively during the study period.Shriram transport finance

27

has obtained a high rate of return on a particular period during the period of stock split The Lic housing finance has earned an average market return during the stock split due to decision by the company towards to acquire the market capitalization.Andhrabank, yes bank has earned negative return during the event of stock split.

Figure 4.1.2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

-10

-8

-6

-4

-2

0

2

4

6

8

10

ANDHARA BANKBANK OF INDIABANK OF BARODACAN BANKFEDERAL BANKIDBIIFCIINDUSINDIOBLIC HOUSING FINANCEPFCSHRI RAM TRANSPORTSYNDICATEUNION BANKYES BANK

Table 4.1.3

Calculation of returns for profit booking

28

AN

DH

RA

B

AN

K

BA

NK

OF

IND

IA

BA

NK

OF

BA

RO

DA

CA

N B

AN

K

FEDER

AL

BA

NK

IDB

I

IFCI

IND

USIN

D

BA

NK

IOB

LIC H

OU

SING

FIN

AN

CE

PFC

SHR

IRA

N

TRA

NSPO

RT

FINA

NC

E

SYN

DIC

ATE

UN

ION

BA

NK

YES B

AN

K

1.73

5.93

0.94

2.89

-0.14

0.7

-0.42

3.58

0.85

12.17

-0.94

-1.28

2.29

1.6

-1.64

1.38

0.99

6.35

7.85

5.57

1.83

0.19

-2.82

-0.55

-4.84

-4.16

-4.02

2.79

-0.93

-2.08

-0.39

-2.31

0.16

-0.04

1.92

-2.24

1.89

-2.52

1.51

2.62

2.95

1.47

5.69

1.85

2.08

2.5

0.15

7.73

1.65

4.53

4.51

2.98

-0.62

-2.83

-3.84

-1.31

-1.24

-2.59

-0.64

-4.02

-1.62

-2.23

-2.66

-3.33

-3.63

-4.51 -5

-0.51

-2.73

0.31

-1.84 1

1.14

2.01

-0.48

-5.04

2.8

0.03

2.55

-1.73

0.12

2.44

-2.53

-3.58

-1.67

0.41

2.71

-1.36

0.23

-2.1

0.26

1.29

1.93

3.09

7.51

1.25

4.62

2.22

3.21

1.56

2.26

2.19

-1.45

0.92

-0.13

Inference

Above table shows that the return of selected securities .bank of Baroda had given a most return at 7.73% during the period of profit booking. The second most highest returns were belongs to

29

stock of federal bank due to a careful prediction about the stock market on future trend. The most lowest returns generated by the securities of yes bank, power Finance Corporation, induslnd bank respectively Most of the return of induslnd bank, IOB, power finance corporation, shriram transport corporation and that of yes bank are negative because of the poor performance in the capital market during the study period.

Figure 4.1.3

Table1 4.2.1

Beta calculation for selected companies in the event of scam

30

S.no Stock name Beta

1 Andhra bank 1.029923

2 Bank of India 1.350379

3 Bank of Baroda 0.962825

4 Can bank 1.288502

5 Federal bank 1.093431

6 IDBI 1.300076

7 IFCI 1.625507

8 Indusind bank 1.065066

9 IOB 1.425511

10 LIC housing finance 1.637331

11 Power finance corporation. 0.988274

12 Shriram Transport finance 0.715974

13 Syndicate bank 1.42934

14 Union bank 1.128751

15 Yes bank 1.319713

Inference The above table states that beta of selected companies like Andhrabank,bank of india,can

bank, federal bank,IDBI, IFCI,Inussind bank,IOB,ILC housing finance, syndicate bank union

bank, yes bank are1.03, 1.35, 1.29, 1.09, 1.3, 1.62, 1.07, 1.43, 1.64, 1.421, 1.13, 1.32

respectively . It shows theis companies are over performed during scam due to announcement of

bonus. So these stocks are shows a good sign for purchase. And the beta of bank of Baroda,

power Finance Corporation, shriram transport finance are respectively 0.96, 0.99, 0.72 during the

scam. These stock are shows a good sign for sell.

Figure 4.2.1

Andra

bank

bank

india

bank

of baro

da

can ba

nkk

fedral

bank

idbi

ifci

indusin

d ban

k iob

lic ho

using

finan

ce

powerf

inanc

e corp

shrira

m tarnsport

finan

ce

syndic

ate ba

nk

union b

ankk

yes b

ank

00.20.40.60.8

11.21.41.61.8 BETA

beta

31

Table 4.2.2

Excess return calculation for selected companies in the event of scam

32

Inference

33

S.no. Stock name Excess return

1 Andhra bank 3.891552

2 Bank of India 18.14882

3 Bank of Baroda 62.84973

4 Can bank 4.449102

5 Federal bank -13.4756

6 IDBI -1.87858

7 IFCI -56.5818

8 Indusind bank -41.9157

9 IOB -5.4815

10 LIC housing finance -17

11 Power finance corporation -56.0239

12 Shriram Transport finance -24.93

13 Syndicate bank -12.7413

14 Union bank -14.0824

15 Yes bank -5.48838

The above table states that the excess of selected companies like Andhra bank, bank of India,

Bank of Baroda can bank, are3.89, 18.15, 62.85, 4.45 respectively It shows this stock are moved

frequently in the market during the scam due to announcement of bonus . So these stocks are

shows a good sign for sell .and the excess return of federal bank, IDBI, IFCI, Inussind bank,

IOB, LIC housing finance, power finance corporation,shriram transport syndicate bank union

bank, yes bankare -13.48, -188, -56.58, -41.92, -5.48, -17, -56.02, -24.93, -12.74, -14.08, -

5,488 (negative) respectively. this stock are poorly moved in the market during the scam. These

stock are shows a good sign for purchase.

Figure 4. 2.2

Andra

bank

bank

of india

bank

of baro

da

can ba

nkk

fedral

bank

idbi

ifci

indusin

d ban

k iob

lic ho

using

finan

ce

powerf

inanc

e corp

shrira

m tarnsport

finan

ce

syndic

ate ba

nk

union b

ankk

yes b

ank

-80

-60

-40

-20

0

20

40

60

80EXCESS RETURN

Excess return

Table 4.2.3

34

Average excess returns calculation for selected companies in the event of scam

Inference

This table states that the average excess return of selected companies like Andhra bank, bank of

India, Bank of Baroda can bank, are0.08, 0.36, 1.26,0.09 respectively. It shows thisstock is

35

S.no Stock name Average excess return

1 Andhra bank 0.077831

2 Bank of India

0.362976

3 Bank of Baroda 1.256995

4 Can bank 0.088982

5 Federal bank -0.26951

6 IDBI -0.03757

7 IFCI -1.13164

8 Indusind bank -0.83831

9 IOB -0.10963

10 LIC housing finance -0.34

11 Power finance corporation -1.12048

12 Shriram Transport finance -0.4986

13 Syndicate bank -0.25483

14 Union bank -0.28165

15 Yes bank -0.10977

performed in a positive way because of bonus announcement during the scam. So these stocks

are shows a good sing for sell. By selling these stocks the investor earn more return than

expected return. and the average excess return of Federal bank, IDBI, IFCI, Inussind bank, IOB,

LIC housing finance, power finance corporation,shriram transport, syndicate bank, union bank,

yes bankare -0.27, -0.04, -1,13, -0.84, -0,11, -0.34 -1.12, -0.5, -0.25, -0.28, -0.11, (negative)

respectively. This stock are earn less return than expected due to the effect of the event known as

scam. These stock are shows a good sign for purchase.

Figure 4.2.3

Andra

bank

bank

of baro

da

fedral

bank ifc

iiob

powerf

inanc

e corp

syndic

ate ba

nk

yes b

ank

-1.5

-1

-0.5

0

0.5

1

1.5

AVERAGE EXCESS RETURN

Average Excess return

Table 4.3.1

36

Beta calculation for selected companies in the event of stock split

Inference

37

S.no Stock name Beta

1 Andhra bank 1.046955

2 Bank of India 0.104408

3 Bank of Baroda 0.977864

4 Can bank 1.212785

5 Federal bank 1.095953

6 IDBI 1.292549

7 IFCI 1.627631

8 Indusind bank 1.0701

9 IOB 1.418358

10 LIC housing finance 1.63267

11 Power finance corporation 0.99346

12 Shriram Transport finance 0.691975

13 Syndicate bank 1.457935

14 Union bank 1.114052

15 Yes bank 1.360864

The above table states that beta of selected companies like Andhra bank, Can bank, Federal

bank, IDBI, IFCI, Inussind bank, IOB, LIC housing finance, Syndicate bank, Union bank, Yes

bank are 1.04, 1.21, 1.10, 1.29, 1.62, 1.07, 1.41, 1.73, 1.46, 1.11, 1.36, respectively. It shows

these companies are over performed during stock split due to announcement of bonus. So these

stocks are shows a good sign for purchase. and the beta of Bank of India, Bank of Baroda, power

finance corporation, Shriram transport finance are respectively 0.10, 0.98, 0.99, 0,69 during the

stock split. It shows these stocks arenormally valued and these stocks are shows a good sing for

sell.

Figure 4.3.1

00.20.40.60.8

11.21.41.61.8

BETA

beta

Table 4.3.2

Excess return calculation for selected companies in the event of stock split

38

S.no Stock name Excess return

1 Andhra bank -1.55373

2 Bank of India 1.666099

3 Bank of Baroda 56.78525

4 Can bank 11.56024

5 Federal bank -2.36441

6 IDBI 4.898998

7 IFCI -73.2035

8 Indusind bank -40.742

9 IOB -16.399

10 LIC housing finance -25.2452

11 Power finance corporation -55.6487

12 Shriram Transport finance -39.8258

13 Syndicate bank -12.9175

14 Union bank -14.1196

15 Yes bank -6.79178

InferenceThe above table indicates that the excess of selected companies like, bank of India, bank of

Baroda, can bank, IDBI are1.67, 56.78, 11.56, 4.90 respectively It shows this stock are moved

frequently in the market during the stock split due to announcement of bonus . So these stocks

39

are shows a good sign forsell. And the Excess return of Andhra bank, Federal bank, IDBI, IFCI,

Inussind bank, IOB, LIC housing finance, power finance corporation,shriram transport syndicate

bank union bank, yes bankare -1.55, -2.36, -73.20, -40.74, -16.40, -25.25, -55.65, -39.83, -

12.92, -14.12, -6.80 (negative) respectively. This stock is poorly moved in the market during the

stock split. These stock are shows a appropriate sing for purchase.

Figure 4.3.2

Andra

bank

bank

india

bank

of baro

da

can ba

nkk

fedral

bank

idbi

ifci

indusin

d ban

k iob

lic ho

using

finan

ce

powerf

inanc

e corp

shrira

m tarnsport

finan

ce

syndic

ate ba

nk

union b

ankk

yes b

ank

-80

-60

-40

-20

0

20

40

60

80

EXCESS RETURN

Excess Rturn

Table 4.3.3

Average excess returns calculation for selected companies in the event of stock

split

40

InferenceThis table states that the average excess return of selected companies like Bank of India, Bank

of Baroda, can bank, IDBI are0.03, 0.1.14, 0.23, 0.10 respectively. It shows these stocks are

performed in a positive way because of bonus announcement during the stock split. So these

41

S.no Stock name Average Excess return

1 Andhra bank -0.03107

2 Bank of India 0.033322

3 Bank of Baroda 1.135705

4 Can bank 0.231205

5 Federal bank -0.04729

6 IDBI 0.09798

7 IFCI -1.46407

8 Indusind bank -0.81484

9 IOB -0.32798

10 LIC housing finance -0.5049

11 Power finance corporation -1.11297

12 Shriram Transport finance -0.79652

13 Syndicate bank -0.25835

14 Union bank -0.28239

15 Yes bank -0.13584

stocks are shows a good sign for sell. By selling these stocks the investor earn more return than

expected return. and the average excess return of Andhra bank, Federal bank, IFCI, Inussind

bank, IOB, LIC housing finance, power finance corporation, shriram transport, syndicate bank,

union bank, yes bankare -0.03, -0.05, -1.46, -0.81, -0.32, -0.50 -1.11, -0.80, -0.26, -0.28, -0.14,

(negative) respectively. This stock are earn less return than expected due to the effect of the

event known as stock split. These stock are shows a good sign for purchase.

Figure 4.3.3

Andra

bank

bank

of baro

da

fedral

bank ifc

iiob

powerf

inanc

e corp

syndic

ate ba

nk

yes b

ank

-2

-1.5

-1

-0.5

0

0.5

1

1.5

AVERAGE EXCESS RETURN

Average Excess Return

Table 4.4.1

Beta calculation for selected companies in the event of profit booking

42

Inference

The above table states that beta of selected companies like Andhra bank, Bank of Baroda, Can

bank, Federal bank, IDBI, IFCI, IOB, LIC housing finance, shriram transport finance, Syndicate

bank, Union bank, Yes bank are 0.67, 0.17, 0.37, 0.64, 0.43, 0.83, 0.50, 0.37, 0.62, 0.39, 0.76,

respectively. It shows these companies are over performed during profit booking due to

announcement of bonus. So these stocks are shows a good sing for purchase. and the beta of

43

S.no Stock name Beta

1 Andhra bank 0.67

2 Bank of India -0.13

3 Bank of Baroda 0.17

4 Can bank 0.37

5 Federal bank 0.64

6 IDBI 0.43

7 IFCI 0.83

8 Indusind bank -0.66

9 IOB 0.5

10 LIC housing finance 0.37

11 Power finance corporation -0.07

12 Shriram Transport finance -0.08

13 Syndicate bank 0.62

14 Union bank 0.39

15 Yes bank 0.76

Bank of india, Indusind Bank, power finance corporation, Shriram transport finance are

respectively -0.13, -0.66, -0.07, -0.08 during the profit booking. It shows these stocks are

normally valued and these stocks are shows a good sing for sell.

Figure 4.4.1

Andha

ra ba

nk

Bank o

f baro

da

Fede

ral ba

nk IFCI

IOB

PFC

syndic

ate

yes b

ank

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

ANERAGE EXCESS RETURN

ANERAGE EXCESS RETURN

Table 4.4.2

Excess returns calculation for selected companies in the event profit bookingS.no Stock name Excess return

1 Andhra bank 2.53

2 Bank of India -6.85

44

3 Bank of Baroda 3.24

4 Can bank 4.35

5 Federal bank 8.17

6 IDBI -2.63

7 IFCI -13.33

8 Indusind bank -25.17

9 IOB 2.12

10 LIC housing finance 14.65

11 Power finance corporation -15.99

12 Shriram Transport finance -6.43

13 Syndicate bank 7.84

14 Union bank 7.6

15 Yes bank 4.15

InferenceThe above table indicates that the excess of selected companies like,Andhara bank, bank of

baroda,can bank, Federal bank, IOB, LIC housing finance, syndicate bank, Union bank, Yes

bank are2.53, 3,24, 4,35, 8.17, 2.12, 14.65, 7.84, 7.60, 4.15 respectively It shows this stocks are

moved frequently in the market during the profit booking due to announcement of bonus. So

these stocks are shows a good sign forsell. And the Excess return of Bank of India, IDBI, IFCI,

45

Inussind bank, power finance corporation,shriram transport finance syndicate bank, union bank,

yes bankare -6.85, -2.63, -13.33, -25.17, -15.99, -6.43, (negative) respectively. This stock is

poorly moved in the market during the profit booking. These stock are shows a appropriate sing

for purchase.

Figure 4.4.2

Andha

ra ba

nk

Bank o

f baro

da

Fede

ral ba

nk IFCI

IOB

PFC

syndic

ate

yes b

ank

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

ANERAGE EXCESS RETURN

ANERAGE EXCESS RETURN

Table 4.4.3

Average excess returns calculation for selected companies in the event of

profit booking

46

InferenceThis table states that the average excess return of selected companies like Andhra Bank, Bank of

Baroda, can bank, Federal Bank, IDBI, IOB, LIC housing finance, union bank, Yes bank are0.5,

0.06, 0.09, 0.17, 0.04, 0.29, 0.15, and 0.08, respectively. It shows this stock is performed in a

positive way because of bonus announcement during the profit booking. So these stocks are

shows a good sign for sell. by selling this stocks the investor earn more return than expected

47

S.no Stock name Average excess return

1Andhra bank 0.05

2 Bank of India -0.14

3 Bank of Baroda 0.06

4 Can bank 0.09

5 Federal bank 0.17

6 IDBI -0.05

7 IFCI -0.27

8 Indusind bank -0.01

9 IOB 0.04

10 LIC housing finance 0.29

11 Power finance corporation -0.32

12 Shriram Transport finance -0.13

13 Syndicate bank -0.04

14 Union bank 0.15

15 Yes bank 0.08

return. and the average excess return of Bank of India, IDBI, IFCI, Inussind bank, power

finance corporation, shriram transport, syndicate bank, are -0.14, -0.05, -0.27, -0.01, -0.32, -

0.13, -0.04 (negative) respectively. This stock are earn less return than expected due to the effect

of the event known as profit booking. these stock are shows a good sign for purchase.

Figure 4.4.3

Andha

ra ba

nk

Bank o

f baro

da

Fede

ral ba

nk IFCI

IOB

PFC

syndic

ate

yes b

ank

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

ANERAGE EXCESS RETURN

ANERAGE EXCESS RETURN

Table 4.5.1

Prediction of price using pivot point analysis from July, 2010 to April 2011

48

NAME OF STOCK R2 R1 PP S1 S2

LIC HOUSING FINANCE 1964.4 1099.2 624.9 - -CNX NIFTY JUNIOR 14988.47 13242.03 11639.97 9893.533 8291.467S&P CNX NIFTY

6969.017 6438.733 5808.217 5277.933 4647.417

InferenceThe above table demonstrates the future price of stock as well as index which has been tested. A

pivot point indicates the information like and sells below that particular level. If the

LIC housing finance is moving above of 624.9 it is suggest buying above pivot point and selling

the next resistance level like 2437.5 for mid-term. If LIC housing finance is moving above 624.9

it suggested buying above pivot point and selling the next resistance level 1964.4. For mid-term.

The above table demonstrates the future price of stock as well as index which has been tested. A

pivot point indicates the information like and sells below that particular level. If the CNX NIFTY

JUNIOR is moving above of 13386.41 it is suggest buying above pivot point and selling the next

resistance level like 12168.45 for mid-term. If CNX NIFTY JUNIORfinance is moving above

16590.47, it suggested buying above pivot point and selling the next resistance level 14988.47

formid-term.

The above table demonstrates the future price of stock as well as index which has been tested. A pivot point indicates the information like and sells below that particular level. If the S&P CNX NIFTY is moving above of 6338.50 it is suggest buying above pivot point and selling the next resistance level like 7598.72 for mid-term. If S&P CNX NIFTY is moving above 6143.38, it suggested buying above pivot point and selling the next resistance level 6969.017formid-term.

Table 4.5.2

Pivot point analysis for the period of April 2011

49

R2 R1 PP S1 S2LIC HOUSING FINANCE 263.5167 241.3833 219.4667 197.3333 175.4167CNX NIFTY JUNIOR 11963.3 11670 11464.85 11171.55 10966.4 S&P CNX NIFTY

6044.017 5892.383 5792.817 5641.183 5541.617

InferenceThe above table demonstrates the future price of stock as well as index which has been tested. A

pivot point indicates the information like and sells below that particular level. If the LIC

housing finance is moving above of 241.6it is suggest buying above pivot point and selling the

next resistance level like 285.376 for mid-term.if LIC housing finance is moving above 263.52, it

suggested to buy above pivot point and sell the next resistance level 263. 52. formid-term.

The above table demonstrates the future price of stock as well as index which has been tested. A

pivot point indicates the information like and sells below that particular level. If theCNX NIFTY

JUNIORis moving above of 11758.15 it is suggest buying above pivot point and selling the next

resistance level like 12168.45 for mid-term. If CNX NIFTY JUNIOR is moving above 11963.3,

it suggested buying above pivot point and selling the next resistance level 11963.3 formid-term.

The above table demonstrates the future price of stock as well as index which has been tested. A

pivot point indicates the information like and sells below that particular level. If the

S&P CNX NIFTYis moving above of 5944.46 it is suggest buying above pivot point and selling

the next resistance level like 6143.58 for mid-term. If S&P CNX NIFTYis moving above

6143.38, it suggested buying above pivot point and selling the next resistance level 6044.02

formid-term.

Figure 4.5.1& 4.5.2

50

1964.4 1099.2 624.9 Nil NilR2 R1 Pivit

pointS1 S2

0

2000

4000

6000

8000

10000

12000

14000

16000

July 2010-April 2012 CNX Nfty juniorJuly 2010-April 2013 S&P CNX NiftyApr-11 LIC housing financeApr-11 CNX Nfty juniorApr-11 S&P CNX Nifty

Table 4.6.1

T- Statistics for scam

51

Period Correlation t-value Sig. (2-tailed)

+90 days to -90 days .128 .198 .843

+80 days to -80 days -.016 .551 .583

+70 days to -70 days -.128 -.644 .522

+60 days to -60 days .006 -.713 .478

+50 days to -50 days .095 -.757 .453

+40 days to -40 days -.358 -.480 .634

+30 days to -30 days -.126 -.762 .452

+20 days to -20 days -.064 -.385 .705

+10 days to -10 days -.238 .152 .882

Inference

From the above table inferred that the period of scam compared with the returns is not having significance relationship with before and after effect.-30 days to +30 days (t= -.762) of scam having negative reaction over the market. -40 days to +40 days (correlation= -.358) the relationship of before and after event provides negative returns in the market.

Table 4.6.2

T- Statistics for stock split

52

Period Correlation t-valueSig.

(2-tailed)

-90 days to +90 days .057 -.862 .391

-80 days to +80 days -.085 -.995 .323

-70 days to +70 days -.086 .330 .742

-60 days to +60 days .085 .425 .673

-50 days to +50 days -.050 .719 .476

-40 days to +40 days .077 .469 .642

-30 days to +30 days -.332 .271 .789

-20 days to +20 days -.430 .062 .952

-10 days to +10 days -.171 .336 .745

Inference

From the above table depicts that the period of stock split compared with the returns is not having significance relationship with before and after effect. -80 days to +80 days (t= -.995) of stock split having negative reaction in the market. -10 days to +10 days (correlation= -.171) the relationship of before and after event provides negative returns in the market.

Table 4.6.3

T- Statistics for Profit booking

53

Period Correlation t-value Sig. (2-tailed)

-15 days to +15 days .625 -.928 .369

-9 days to +9 days .157 -1.040 .329

-6 days to +6 days .278 -1.148 .303

-3 days to +3 days -.223 -1.615 .248

Inference

From the above table depicts that the period of profit booking compared with the returns is not having significance relationship with before and after effect. -3 days to +3 days (t=-1.615) of profit booking having negative reaction in the market. -3 days to +3 days (correlation= -.223) the relationship of before and after event provides negative returns in the market.

5.1 FINDINGS OF THE STUDY

The market return of Yes bank during November 2010 is high (4.6%) among the selected stocks .It shows the good movement for sell it in the market.

54

Indian overseas bank has identified the high return security (8.9%) during the period of December 2010. It indicates a positive movement for make sales decision.

The security of LIC housing finance limited has earned high market return among the selected securities during February 2011(profit booking).

The Risk behavior of LIC housing finance limited has shown high return before the scam (November 2010). It implies that risk of the stock towards its market return.

The excess return of yes bank during the November 2010 goes negative. So the has been poorly performed in the market.

Average returns of bank of Baroda shows high during November 2010. It infer that the positive movement of the stock towards to make sales decision.

The market risk of Shri ram transport financeis very low on December 2010. This shows a good movement towards to make the purchase decision.

The excess return of yes bank (-6.79%) is very low (negative) in selected stocks during 2010. Therefore the stock having a good movement to make the sales decision.

Union bank is better when compared with other scripts based on its risk pattern (0.39) during the event of profit booking (February 2110).

LIC housing finance limited can be placed at a better position in terms of its excess market return(14.65%) than other stocks on profit booking (February 2011).

Federal bank is very sound position because of highest average excess return(0.15%) in the selected stocksduring the same period.

When the LIC housing finance is moving above of 241.6 it is suggest to buying above

pivot point and selling the next resistance level like 285.376 for mid-term. If LIC housing

finance is moving above 263.52, it suggested buying above pivot point and selling the

next resistance level 263.52. for mid-term.

55

If the CNX NIFTY JUNIOR is moving above of 13386.41 it is suggest buying above pivot

point and selling the next resistance level like 12168.45 for mid-term. If CNX NIFTY

JUNIOR finance is moving above 16590.47, it suggested buying above pivot point and

selling the next resistance level 14988.47 for mid-term.

If S&P CNX NIFTY is moving above of 6338.50 it is suggest buying above pivot point and selling the next resistance level like 7598.72 for mid-term. If S&P CNX NIFTY is moving above 6143.38, it suggested buying above pivot point and selling the next resistance level 6969.017 for mid-term.

5.2 SUGGESTIONS AND RECOMMENDATIONS

Based on the analysis the yes bank performed well and produced high return (4.6%). Therefore it is suggested to buy.

56

Indian bank has obtained 8.9% of market return among the selected scripts during same period. Hence the stock suggested buying.

LIC housing finance limited has identified as high return security (12.7%) in season of profit booking (February 2011) its suggested to buy.

IFCI (0%), Can bank (0.026%), Yes bank (0.13%) are founded that poor performed stocks based on its market return during November 2010, December 2010, February 2011 respectively. this stocks are suggested to sell immediately.

The risk averse investors would not be consider the stock of LIC housing finance limited because of risk associated with the stock in November 2010.

The poor performed stock (negative) during November 2010 founded the script of yes bank is recommended to sell.

The market return of bank of Baroda has shown averagely increased trend during the November 2010. Therefore it is suggested to buy.

Risk averse investors can be concentrate the script of shri ram transport finance limited towards low risk pattern in the period of December 2010.

Yes bank shows the most negative excess return among the selected securities during December 2010. It is a right a right time of investor to switch other stock.

Union bank is suggested to buy during February 2011 in the aspect of its risk pattern (low risk).

The average excess return of federal bank is moderate among the stocks .so it is suggested to buy.

The aggressive stocks are LIC housing finance limited and syndicate bank (beta value more than 1).

The defensive stock is Shriram transport finance (beta value less than 1).

CNX Nifty junior has varied gap on its both resistance and support level. Therefore it’s suitable to make decision on first level of both resistance and support.

57

The market is affected during the scam particularly in the interval in between -30 days to +30 days and -40 days to + days. It implies the investor have to much more aware about the market during the period.

The announcement of stock split has made impact on the market in interval of -80 days to +80 days and -10 days to +10 days. This infer that the investors are has to avoid the transaction of buying and selling securities among the period.

The impact of profit booking is identified in the interval of -3 days to +3 days. It shows positive trend of market to buy and sell the securities.

5.3 CONCLUSION

The CNX NIFTY JUNIOR index of 50 companies. Exhibits event anomalies in returns the event anomalies examined in this study is an Empirical study on pricing behavior of Indian stock market with the event happened in LIC housing finance limited. The main purpose of study was

58

to find out whether Indian stock market affect from event effects. To test these issues, the researcher selected the CNX NIFTY JUNIOR index for the study.

With investing security market gaining much importance these days, a good strategy adopted to gain from the market movements will give sure returns to the investors.Return on securities is entirely depending on separate interest of investor towards the stock market.The major findings of the study are Indian overseas bank has identified the high return security during the period of December 2010, The security of LIC housing finance limited has earned high market return among the selected securities during February 2011(profit booking).

The major suggestion the study are the risk averse investors would not be consider the stock of LIC housing finance limited because of risk associated with the stock in November 2010.The poor performed stock (negative return) during November 2010 founded the script of yes bank is recommended to sell immediately.

The present study has concluded that the announcement of corporate events belongs to the LIC housing finance limited like scam, stock split, profit booking are made a slight impact on the stock market during the study period. Also this research study will be help the researchers to analyze the similar event will happen in the market.

BIBLIOGRAPHY

1. Books

59

Investment analysis and portfolio management

- Prasanna Chandra

Securities analysts and portfolio management

-Punithavathi pandian

Research methodology

-C.R Kothari

2. Journals

Stock price responses to the announcement of buyback of shares in India(2010)-Dr.P.Ishwar

An empirical test of Indian stock market efficiency in respect of bonus announcement (2010)-M. Raja.

A brief history of market efficiency (1998) -Elroy Dimson and MassoudMussavian.

Stability of Beta over Market Phases: An Empirical Study on Indian Stock Market (2010)-KoustubhKanti Ray.

The Behaviour of Stock-Market Prices (2010) -Eugene F. Fama

Finding of Day of the Week Effect in the Indian Stock Market, co-authored by Dr.M A Curious Carmaker, (Ed. 2000) Indian Capital Market: Trends and Dimensions, TataMcGraw-Hill Publishing Co. Ltd., New Delhi.

3. WEBSITES

www.google.comwww.nseindia.com

60

www.bseindia.comwww.jstoe.orgwww.eurojournals.comwww.fep.up.ptwww.scholarshub.net

61