pricing_behaviour_in_indian_stock_market.doc

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 20072010, coupled with a poor monsoon, India's gross domestic product (GDP) growth rate significantly slowed to 6.7% in 200809, but subsequently recovered to 7.4% in 200910, while the fiscal deficit rose from 5.9% to a high 6.5% during the same period. Indiascurrent account deficit surged to 4.1% of GDP during Q2 FY11 against 3.2% the previous quarter. The unemployment rate for 20092010, 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 marketThe 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 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 marketInvestors 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 occurso 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.

1.2 INTRODUCTION ABOUT THE STOCK MARKET AND SCRIPT1.2.1 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 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[update], 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%.

1.2.5 IndicesNSE 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 JuniorThe 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.

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 nameIndustryEquity capital (In Rs.)

Adani Enterprises Ltd.trading1099810083

Aditya Birla Nuvo Ltd.textiles - synthetic1135097290

Andhra Bankbanks5595803640

Ashok Leyland Ltd.automobiles - 4wheelers1330338317

Asian Paints Ltd.paints959197790

Bank of Barodabanks3915460790

Bank of Indiabanks5464803700

Bharat Electronics Ltd.electronics - industrial800000000

Bharat Forge Ltd.castings/forgings465588632

Biocon Ltd.pharmaceuticals1000000000

Canara Bankbanks4430000000

Coal India Ltd.mining63163644000

Colgate Palmolive (India) Ltd.personal care135992817

Container Corporation of IndiaLtd.travel and transport1299827940

Crompton Greaves Ltd.electrical equipment1282983072

Cummins India Ltd.diesel engines396000000

Exide Industries Ltd.auto ancillaries850000000

Federal Bank Ltd.banks1712115340

GMR Infrastructure Ltd.construction3892434782

Glaxosmithkline Pharmaceuticals Ltd.pharmaceuticals847030170

Glenmark Pharmaceuticals Ltd.pharmaceuticals270323853

Hindustan Petroleum Corporation Ltd.refineries3386272500

Housing Development and Infrastructure Ltd.construction4150039860

IDBI Bank Ltd.banks9845532150

IFCI Ltd.financial institution7378373310

Indian Hotels Co. Ltd.hotels759472787

Indian Overseas Bank banks6187493430

IndusInd Bank Ltd.banks4659608850

JSW Steel Ltd.steel and steel products2231172000

LIC Housing Finance Ltd.finance - housing949326000

Lupin Ltd.pharmaceuticals892595198

MphasiS Ltd.computers - software2100020560

Mundra Port and Special Economic Zone Ltd.travel and transport4006788200

Oracle Financial Services Software Ltd.computers - software419510760

Patni Computer Systems Ltd.computers - software267715336

Power Finance Corporation Ltd.financial institution13199317050

Punj Lloyd Ltd.construction664191490

Rural Electrification Corporation Ltd.financial institution9874590000

Shriram Transport Finance Co. Ltd.finance2261606680

Syndicate Bankbanks5732856710

Tata Chemicals Ltd.chemicals - inorganic2547562780

Tech Mahindra Ltd.computers - software1260553760

Titan Industries Ltd.gems, jewellery and watches887786160

Torrent Power Ltd.power4724483080

UltraTech Cement Ltd.cement and cement products2740458750

Union Bank of Indiabanks5243324150

United Phosphorus Ltd.pesticides and agrochemicals923608548

United Spirits Ltd.brew/distilleries1307949680

Yes Bank Ltd.banks3479787240

Zee Entertainment Enterprises Ltd.media & entertainment978076130

Total203,106,525,365

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%.

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

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.

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. Scam2. Stock split 3. Profit bookingIn 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.

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.

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 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 ones biological, demographic and socioeconomic characteristics; together with his/her psychological makeup affects ones 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 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 othereconomic 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, conventionsonly 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. 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 justifiedAlexander and Chervany (1980) show empirically that extreme betas are less stable comparedto 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.

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 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 1011%, 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 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.

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 studyi) 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.

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 dateEvent 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 dateIn 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 +nRj, t = return for firm j for period t (t = -n 0 +n)c) Calculate the excess returnThe excess return is calculated as:E Rjt = Rjt Beta j Rmtd) Compute the average excess returnThe average excess return is =

e) T statistics d =

=

Sd = s

T =

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 = (2PP)-L R2=PP+ (H-L) S1 = (2PP)-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.

4. ANALYSIS AND INTERPRETATIONS

Table 4.1.1

Calculation of returns during the event of Scam

ANDRA BANK BOIBOBCAN BANKFEDERALIDBIIFCIINDUSINDIOBLICHOUSING FINANCEPFCSHRI RAM TRONSSYNDICATEUNION BANKYES BANK

6.173285-0.619471.1171641.5856780.112360.988061-1.72414-0.73815.7208240.7187742.2438871.6598924.8979590.1380370.235571

1.5968770.2931122.56987-1.19625-0.459970.421941-3.255811.0138481.669596-1.597931.829844.6601210.7142860.2795033.192568

2.5337840.1947841.2207791.7593531.913580.6666672.006689-0.33408-0.76574.7642282.618831-2.89510.9017131.16106-0.42188

-2.73189-3.91398-2.32852-2.86322-0.8046-2.8366-2.821580.328947-1.25-1.190282.31441-1.9-3.1654-1.57879-1.73913

3.68751.0101012.5886521.804577-0.922460.25-0.74257-2.57785-1.618010.5291661.390071-1.76617-2.95483-0.22849-0.99398

-2.15569-0.89641-0.375850.693842-0.23033-0.38911-1.111110.869061-0.110422.6117810.220523-0.34884-0.29991-0.194813.672566

0.665054-0.718092.164021-0.160081.3947990.7638450-3.239442.196339-0.66549-2.61905-2.58125-0.57471-0.581324.598738

2.762431-3.740740.136959-1.32653-0.82155-1.19534-1.00806-0.794222.6862030.083636-0.957450.7846950.1056340.9420291.568365

-2.18328-1.384411.989418-0.03870.857143-1.3764-1.823493.36375-15.9722-17.6769-2.812230.552022-3.66197-3.89037-2.3141

-3.50257-3.91494-1.575791.26087-3.44828-3.66071-2.901960.647986-2.10339-3.29659-0.43269-5.0964-3.46048-2.64438-2.8871

-1.75831-1.85083-0.59580.366412-1.40652-0.68534-6.714290.804505-0.83045-0.830690.8906250.006418-0.574270.570547-0.27331

-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

3.452381-1.850791.2071087.1033210.4933330.694444-0.78534-2.255644.22.8326942.3830382.832413.6120732.2698210.922509

0.5072462.0809771.6121380.675439-1.72270.9012263.32681-0.51043-3.27103-0.81164-2.69084-0.81618-5.83116-0.15106-3.11693

2.3744910.4032261.305211.271402-0.207951.972963-2.650822.041722-2.23607-4.25267-6.231970.039891-2.14818-3.791540.67352

-1.99301-0.357142.655742-1.672291.7736830.1434720.3853561.401274-0.54348-0.46308-0.05702-1.38618-1.12896-1.89132-1.18613

0.325851-3.936920.38108-3.306840.77027-2.81433-2.99345-1.097780.983837-1.79949-3.88455-0.22925-3.918230.270433-0.27273

2.4568391.43750.0052581.3829620.03561.673497-0.96881.986507-1.418920.2141331.253596-1.20371.6727871.2221420.143426

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

Table 4.1.2

Calculation of returns during the event of Stock split

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

-2.070391.148649-1.62533-0.17818-2.50742-1.20232-5.68-1.387560.2392341.2443150.0781251.853448-0.61234-0.54688-1.23333

-1.43162-0.714550.072289-1.54649-0.379690.8805510.566343-1.95690.516796-0.88403-0.284434.5864711.807229-0.41322-2.84291

-1.17759-0.52632-0.954381.642145-0.14409-4.77778-0.24612.302632-0.333830.371901-0.61924-2.55663-0.387930.172662-0.73209

-0.50595-1.573881.218391-0.79324-1.292881.2676060.8950370.150801-0.353980.758491-1.326452.416667-0.641031.5270220.347432

1.7664671.0004351.606742-0.74576-0.745061.3522011.7964071.2045938.852584-1.444220.868347-0.539343.2377050.44287-0.74647

-0.058820.303032.4071380.4658391.272265-1.677020.206897-2.71628-0.65441-2.79856-0.260270.483029-1.496452.8071081.954023

0.5027931.725936-0.200592.2107443.04814-0.738512.6428576.5387480.464109-1.045580.511898-3.060540.353357-0.987272.739917

0.5095541.4492753.4492273.4170151.0712252.18750.163934-0.561226.6666675.4526326.2973485.2525911.3602941.177484-1.55949

0.3957780.5122430.8138240.305742-0.845341.1225442.3966940.2991771.0288070.3741372.4587617.7152782.345330.434783-1.00162

1.3256290.623790.3997750.685670.2789750.156250.4743080.2971470.2483150.832405-3.00126-0.725750.1986491.6585510.146628

0.6644520.5150020.375587-0.228520.9078951.6711234.2277833.2752021.081686-0.02941-0.570541.8534180.5714293.2343750.218579

-4.68581.6-1.40853-2.38786-4.64466-7.36156-6.27119-4.58065-1.201550.516304-3.91304-0.64036-3.74307-4.19259-5.03674

1.397059-0.23596-0.220050.6603773.4146342.065131-1.124742.8571436.6666675.4526326.2973485.2525911.3602941.177484-1.55949

-0.27759-2.01064-4.38846-0.02626-2.80172-4.78163-6.18956-2.527231.0288070.3741372.4587617.7152782.345330.434783-1.00162

-1.99712.860697-1.311060.801653-2.10456-1.28064-0.84746-0.681960.2483150.832405-3.00126-0.725750.1986491.6585510.146628

0.702001-6.311662.5248620.2287580.6661440.8670520.5607480.9041941.081686-0.02941-0.570541.8534180.5714293.2343750.218579

-3.903230.054705-2.4856-1.31045-0.18863-3.23333-3.48432-0.96522-0.88496-2.24424-4.718760.5062731.336634-0.882583.168191

1.252615.4867460.0252510.2290081.662791-0.36304-1.48976-1.88053-0.41322-0.26247-0.58952-1.317310.971267-0.04376-0.3942

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 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

Table 4.1.3

Calculation of returns for profit booking

ANDHRA BANKBANK OF INDIABANK OF BARODACAN BANKFEDERAL BANKIDBIIFCIINDUSIND BANK IOBLIC HOUSING FINANCEPFCSHRIRAN TRANSPORT FINANCESYNDICATEUNION BANKYES BANK

1.735.930.942.89-0.140.7-0.423.580.8512.17-0.94-1.282.291.6-1.64

1.380.996.357.855.571.830.19-2.82-0.55-4.84-4.16-4.022.79-0.93-2.08

-0.39-2.310.16-0.041.92-2.241.89-2.521.512.622.951.475.691.852.08

2.50.157.731.654.534.512.98-0.62-2.83-3.84-1.31-1.24-2.59-0.64-4.02

-1.62-2.23-2.66-3.33-3.63-4.51-5-0.51-2.730.31-1.8411.142.01-0.48

-5.042.80.032.55-1.730.122.44-2.53-3.58-1.670.412.71-1.360.23-2.1

0.261.291.933.097.511.254.622.223.211.562.262.19-1.450.92-0.13

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 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 scamS.no Stock name

Beta

1Andhra bank1.029923

2Bank of India1.350379

3Bank of Baroda0.962825

4Can bank

1.288502

5Federal bank

1.093431

6IDBI

1.300076

7IFCI

1.625507

8Indusind bank

1.065066

9IOB1.425511

10LIC housing finance1.637331

11Power finance corporation.0.988274

12Shriram Transport finance0.715974

13Syndicate bank1.42934

14Union bank1.128751

15Yes bank1.319713

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

Table 4.2.2 Excess return calculation for selected companies in the event of scamS.no. Stock name

Excess return




4Can bank

4.449102

5Federal bank

-13.4756

6IDBI

-1.87858

7IFCI

-56.5818

8Indusind bank

-41.9157

9IOB-5.4815

10LIC housing finance-17

11Power finance corporation-56.0239

12Shriram Transport finance-24.93

13Syndicate bank-12.7413

14Union bank-14.0824

15Yes bank-5.48838

InferenceThe 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

Table 4.2.3Average excess returns calculation for selected companies in the event of scamS.noStock name

Average excess return




4Can bank

0.088982

5Federal bank

-0.26951

6IDBI

-0.03757

7IFCI

-1.13164

8Indusind bank

-0.83831

9IOB-0.10963

10LIC housing finance-0.34





15Yes bank-0.10977

InferenceThis 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 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

Table 4.3.1S.no Stock name

Beta




4Can bank

1.212785

5Federal bank

1.095953

6IDBI

1.292549

7IFCI

1.627631

8Indusind bank

1.0701

9IOB1.418358


11Power finance corporation0.99346

12Shriram Transport finance0.691975


14Union bank1.114052

15Yes bank1.360864

Beta calculation for selected companies in the event of stock split

Inference

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

Table 4.3.2Excess return calculation for selected companies in the event of stock splitS.no Stock name

Excess return

1Andhra bank-1.55373



4Can bank

11.56024

5Federal bank

-2.36441

6IDBI

4.898998

7IFCI

-73.2035

8Indusind bank

-40.742

9IOB-16.399






15Yes 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 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

Table 4.3.3Average excess returns calculation for selected companies in the event of stock splitS.no Stock name

Average Excess return

1Andhra bank-0.03107



4Can bank

0.231205

5Federal bank

-0.04729

6IDBI

0.09798

7IFCI

-1.46407

8Indusind bank

-0.81484

9IOB-0.32798






15Yes bank-0.13584

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 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

Table 4.4.1 Beta calculation for selected companies in the event of profit booking

S.no Stock name

Beta

1Andhra bank0.67

2Bank of India-0.13

3Bank of Baroda0.17

4Can bank

0.37

5Federal bank

0.64

6IDBI

0.43

7IFCI

0.83

8Indusind bank

-0.66

9IOB0.5





14Union bank0.39

15Yes bank0.76

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 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

Table 4.4.2Excess returns calculation for selected companies in the event profit bookingS.no Stock name

Excess return

1Andhra bank2.53

2Bank of India-6.85

3Bank of Baroda3.24

4Can bank

4.35

5Federal bank

8.17

6IDBI

-2.63

7IFCI

-13.33

8Indusind bank-25.17

9IOB2.12





14Union bank7.6

15Yes bank4.15

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, 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

Table 4.4.3Average excess returns calculation for selected companies in the event of profit booking

S.no Stock nameAverage excess return

1Andhra bank0.05

2Bank of India-0.14

3Bank of Baroda0.06

4Can bank

0.09

5Federal bank

0.17

6IDBI

-0.05

7IFCI

-0.27

8Indusind bank

-0.01

9IOB0.04





14Union bank0.15

15Yes bank0.08

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 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

Table 4.5.1

Prediction of price using pivot point analysis from July, 2010 to April 2011 NAME OF STOCKR2R1PPS1S2

LIC HOUSING FINANCE1964.41099.2624.9--

CNX NIFTY JUNIOR14988.4713242.0311639.979893.5338291.467

S&P CNX NIFTY

6969.0176438.7335808.2175277.9334647.417

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 2011R2R1PPS1S2

LIC HOUSING FINANCE263.5167241.3833219.4667197.3333175.4167

CNX NIFTY JUNIOR11963.31167011464.8511171.5510966.4

S&P CNX NIFTY

6044.0175892.3835792.8175641.1835541.617

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

Table 4.6.1

T- Statistics for scam

PeriodCorrelationt-valueSig. (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


-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


-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.

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.

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.

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 its suitable to make decision on first level of both resistance and support.

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 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

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

61

Date post:	17-Nov-2015
Category:	Documents
Upload:	vankishkhosla
View:	219 times
Download:	0 times

pricing_behaviour_in_indian_stock_market.doc

Documents