Ashvitha Complit Project God My Mothers

8/2/2019 Ashvitha Complit Project God My Mothers

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CHAPTER TITLE PAGE

I INTRODUCTION

II

REVIEW OF LITERATURE

III

ANALYSIS AND INTERPRETATION OF DATA

IV CONCLUSION

APPENDIX

BIBLIOGRAPHY


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CHAPTER I

INTRODUCTION


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INTRODUCTION

The nature of equity market in India has undergone profound change over the last

20 years. This effects the trend of capital market. The significant developments include

the introduction of screen-based electronic trading platforms and the dematerialization of

shares and shareholding.

These developments have permitted the implementation of a straight-through-

processing settlement as well as enabling risk management to develop the very

sophisticated automatic mechanisms. The capability and efficiency of trading and settling

large volumes of shares through this streamlined process have made Indias financial

markets significantly more attractive to global investors.

The Indian stock and investment market is mainly divided into two parts, namely

the capital market and the money market. The stock market is an important part of the

capital market in the country through which one can carry out the transaction of capital. Itis usually done through the means of direct financing by security and investment. The

investment markets classically classified as Primary market and Secondary market.

PrimaryMarket

In case of the primary market, the listed shares are traded for the first time which

is transferred to the investors from the listed company. In case of the primary market, the

stock issuers and the listed companies make use of the capital by offering the stocks to

the investors. The investors, in turn, buy the shares and supply the needed capital. In

simple terms, the primary market is a type of platform where new securities and stocks

are dealt with.

The primary market can be an ideal source of funding for various business

enterprises and companies, public sector units and government organizations. All these

organizations can make the funding by selling new bonds, stocks and other forms of

securities. The buying and selling of the securities are done through dealers.

SecondaryMarket

An important part of the Indian stock and investment market is the secondary market.

In simple terms, it is also known as the stock market. Mainly it is a type of continuous

market which offers a very good platform for trading and business of securities and

stocks. In most cases, the trading is done through a licensed broker, stock and securities

units, security firms and other financial institutions. The trading has to be done according

to the terms and conditions that are set by the specific stock exchanges.


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OBJECTIVESOFTHESTUDY

The major objectives of the study are

To study the price trend of selected commercial banks securities listed in NSE

from 1st January 2007 to December 31st 2009.

To examine the relationship between book value and price earnings ratio of

selected bank securities listed in NSE.

METHODOLOGY

This project work concentrates on 10 bank securities. The 10 bank securities are taken

during the period of 1st January 2007 to 31st December 2009.

Data collection

These 12 bank securities closing price and index details are collected from theNSE web site.

Major Data

No of bank securities

Closing index

Closing price

The following methods are followed for analyzing the data.

1. MovingAverage

Moving Averages are indicators of the underlying trends of the price movement.

Two types of Moving Averages (MA) are commonly used by analysts They are the

Simple Moving Average(SMA) and the Exponential Moving Average(EMA).

a) Simple Moving Average

An average is the sum of a share price for a specific number of days divided by

the number of days. In a simple moving average, a set of averages are calculated for a

specific number of days, each average being calculated by including a new price and

excluding an old price.


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b) Exponential Moving Average

EMA is a type of moving average that is similar to a simple moving average,

except that more weight is given to the latest data. The exponential moving average is

also known as "exponentially weighted moving average". Moving Average Convergence

and Divergence(MACD) is calculated on the basis of two exponential Moving Averages.This trend shares the relationship between average of prices.

2. KARL PEARSONS Coefficient of Correlation

KARL PEARSONS Coefficient of Correlation method is used to find out whether

the index price and the closing price of securities are related.

3. Calculation of PriceEarnings Ratio

The calculation of PriceEarnings ratio is by taking three years financial data of

10 bank securities of NSE i.e., the Earnings per share and Market per share

OVERVIEW OF STOCK MARKET

A stock market / share market is a public market for the trading of company stock and

derivatives at an agreed price; these are securities listed on a stock exchange as well as

those only traded privately.

The size of the world stock market was estimated at about $36.6 trillion US at the

beginning of October 2008.[1] The total world derivatives market has been estimated atabout $791 trillion face or nominal value, [2] 11 times the size of the entire world

economy. [3] The value of the derivatives market, because it is stated in terms of notional

values, cannot be directly compared to a stock or a fixed income security, which

traditionally refers to an actual value.

Market participants

A few decades ago, worldwide, buyers and sellers were individual investors, such as

wealthy businessmen, with long family histories to particular corporations. Over time,

markets have become more "institutionalized"; buyers and sellers are largely institutions

(e.g., pension funds, insurance companies, mutual funds, index funds, exchange-traded

funds, hedge funds, investor groups, banks and various other financial institutions). The

rise of the institutional investor has brought with it some improvements in market

operations. Thus, the government was responsible for "fixed" fees being markedly

reduced for the 'small' investor, but only after the large institutions had managed to break

the brokers' solid front on fees. However, corporate governance has been very much

adversely affected by the rise of institutional 'owners'.


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India in terms of market capitalization by 2009 end.[2]Though a number of other

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

exchanges in India, and between them are responsible for the vast majority of share

transactions. The NSE's key index is the S&P CNX Nifty, known as the Nifty, an index

of fifty major stocks weighted by market capitalization.

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

insurance companies and other financial intermediaries in India but its ownership and

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

Euro next and Goldman Sachs who have taken a stake in the NSE.[4] As of 2006, the

NSE VSAT terminals, 2799 in total, cover more than 1500 cities across India [5]. In

October 2007, the equity market capitalization of the companies listed on the NSE was

US$ 1.46 trillion, making it the second largest stock exchange in South Asia. NSE is the

third largest Stock Exchange in the world in terms of the number of trades in equities. It

is the second fastest growing stock exchange in the world with a recorded growth of

16.6%.

Origins

The National Stock Exchange of India was promoted by leading financial institutions

at the behest of the Government of India, and was incorporated in November 1992 as a

tax-paying company. In April 1993, it was recognized as a stock exchange under the

Securities Contracts (Regulation) Act, 1956. NSE commenced operations in the

Wholesale Debt Market (WDM) segment in June 1994. The Capital Market (Equities)

segment of the NSE commenced operations in November 1994, while operations in the

Derivatives segment commenced in June 2000.

Markets

Currently, NSE has the following major segments of the capital market:

Equity

Futures and Options

Retail Debt Market

Wholesale Debt Market

Currency futures

NSE became the first stock exchange to get approval for Interest rate futures as

recommended by SEBI-RBI committee, on 31 August,2009, a futures contract based on

7% 10 Year GOI bond (NOTIONAL) was launched with quarterly maturities.


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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 Bank Index

The Indian banking Industry has been undergoing major changes, reflecting anumber of underlying developments. Advancement in communication and information

technology has facilitated growth in internet-banking, ATM Network, Electronic transfer

of funds and quick dissemination of information. Structural reforms in the banking sector

have improved the health of the banking sector. The reforms recently introduced include

the enactment of the Securitization Act to step up loan recoveries,

In order to have a good benchmark of the Indian banking sector, India Index Service

and Product Limited (IISL) has developed the CNX Bank Index. CNX Bank Index is an

index comprised of the most liquid and large capitalized Indian Banking stocks. It

provides investors and market intermediaries with a benchmark that captures the capitalmarket performance of Indian Banks. The index will have 12 stocks from the banking

sector which trade on the National Stock Exchange.

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

approximately 96.46% of the traded value of the banking sector. CNX Bank Index stocks

represent about 87.24% of the total market capitalization of the banking sector as on

March 31, 2009.

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

constituents is approximately 15.26% of the traded value of all stocks on the NSE. CNX

Bank Index constituents represent about 7.74% of the total market capitalization as on

March 31, 2009.

Methodology

The index is a market capitalization weighted index with base date of January 01,

2000, indexed to a base value of 1000.


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Selection Criteria

Selection of the index set is based on the following criteria

1. Company's market capitalization rank in the universe should be less than 500

2. Company's turnover rank in the universe should be less than 500

3. Company's trading frequency should be at least 90% in the last six months.

4. Company should have a positive net worth.

5. A company which comes out with a IPO will be eligible for inclusion in the

index, if it fulfills the normal eligibility criteria for the index for a 3 month period

instead of a 6 month period.

Constituents list of selected CNX Bank

The following are the constituents list on

CNX Bank index in NSE

State Bank of India

Bank of Baroda

Bank of India

Canara Bank

Union Bank of India

Axis Bank Ltd

HDFC Bank Ltd.

ICICI Bank Ltd

IDBI Bank Ltd

Kotak Mahindra Bank Ltd

Bombay Stock Exchange


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The Bombay Stock Exchange Limited is the oldest stock exchange in Asia

and has the greatest number of listed companies in the world, with 4700 listed as of

August 2007.[1] It is located at Dalal Street, Mumbai, India. On 31 December 2007, the

equity market capitalization of the companies listed on the BSE was US$ 1.79 trillion,

making it the largest stock exchange in South Asia and the 12th largest in the world.[2]

With over 4700 Indian companies listed & over 7700 scripts on the stock exchange,[3] it

has a significant trading volume. The BSE SENSEX (sensitive index), also called the

"BSE 30", is a widely used market index in India and Asia. Though many other

exchanges exist, BSE and the National Stock Exchange of India account for most of the

trading in shares in India.

BSE indices

For the premier stock exchange that pioneered the securities transaction business in

India, over a century of experience is a proud achievement. A lot has changed since 1875

when 318 persons by paying a then princely amount of Re. 1, became members of what

today is called Bombay Stock Exchange Limited (BSE).

BSE, in 1986, came out with a Stock Index-SENSEX- that subsequently became the

barometer of the Indian stock marke The 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.

With a view to provide a better representation of the increasing number of listed

companies, larger market capitalization and the new industry sectors, BSE launched on

27th May, 1994 two new index series viz., the 'BSE-200' and the 'DOLLEX-200'. Since

then, BSE has come a long way in attuning itself to the varied needs of investors and

market participants. In order to fulfill the need for still broader, segment-specific and

sector-specific indices, BSE has continuously been increasing the range of its indices.

BSE disseminates information on the Price-Earnings Ratio, the Price to Book Value

Ratio and the Dividend Yield Percentage on day-to-day basis of all its major indices.


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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. ThisCommittee 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 conducts research on

development of new indices.

OVERVIEW OF BANKING SECTOR

Banking in India originated in the last decades of the 18th century. The oldest bank in

existence in India is the State Bank of India, a government-owned bank that traces its

origins back to June 1806 and that is the largest commercial bank in the country. Central

banking is the responsibility of the Reserve Bank of India, which in 1935 formally took

over these responsibilities from the then Imperial Bank of India, relegating it to

commercial banking functions. After India's independence in 1947, the Reserve Bank

was nationalized and given broader powers. In 1969 the government nationalized the 14

largest commercial banks; the government nationalized the six next largest in 1980.

Currently, India has 96 scheduled commercial banks (SCBs) - 27 public sector banks

(that is with the Government of India holding a stake), 31 private banks (these do not

have government stake; they may be publicly listed and traded on stock exchanges) and

38 foreign banks. They have a combined network of over 53,000 branches and 17,000

ATMs. According to a report by ICRA Limited, a rating agency, the public sector banks

hold over 75 percent of total assets of the banking industry, with the private and foreign

banks holding 18.2% and 6.5% respectively.

Nationalization

By the 1960s, the Indian banking industry had become an important tool to

facilitate the development of the Indian economy. At the same time, it had emerged as a

large employer, and a debate had ensued about the possibility to nationalize the banking

industry. Indira Gandhi, the-then Prime Minister of India expressed the intention of the

GOI in the annual conference of the All India Congress Meeting in a paper entitled "Straythoughts on Bank Nationalization." Thereafter, her move was swift and sudden, and the

GOI issued an ordinance and nationalized the 14 largest commercial banks with effect

from the midnight of July 19, 1969. Jayaprakash Narayan, a national leader of India,

described the step as a "masterstroke of political sagacity." Within two weeks of the issue

of the ordinance, the Parliament passed the Banking Companies and Transfer of Bill, and

it received the presidential approval on 9 August 1969.


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A second dose of nationalization of 6 more commercial banks followed in 1980.

The stated reason for the nationalization was to give the government more control of

credit delivery. With the second dose of nationalization, the GOI controlled around 91%

of the banking business of India. Later on, in the year 1993, the government merged New

Bank of India with Punjab National Bank. It was the only merger between nationalized

banks and resulted in the reduction of the number of nationalized banks from 20 to 19.

After this, until the 1990s, the nationalized banks grew at a pace of around 4%, closer to

the average growth rate of the Indian economy.

Liberalization

In the early 1990s, the then Narsimha Rao government embarked on a policy

of liberalization, licensing a small number of private banks. These came to be known as

New Generation tech-savvy banks, and included Global Trust Bank (the first of such newgeneration banks to be set up), which later amalgamated with Oriental Bank of

Commerce, Axis Bank(earlier as UTI Bank), ICICI Bank and HDFC Bank. This move,

along with the rapid growth in the economy of India, revitalized the banking sector in

India, which has seen rapid growth with strong contribution from all the three sectors of

banks, namely, government banks, private banks and foreign banks.

The next stage for the Indian banking has been setup with the proposed relaxation

in the norms for Foreign Direct Investment, where all Foreign Investors in banks may be

given voting rights which could exceed the present cap of 10%,at present it has gone up

to 74% with some restrictions.

The new policy shook the Banking sector in India completely. Bankers, till this time,

were used to the 4-6-4 method (Borrow at 4%;Lend at 6%;Go home at 4) of functioning.

The new wave ushered in a modern outlook and tech-savvy methods of working for

traditional banks.All this led to the retail boom in India. People not just demanded more

from their banks but also received more.

Currently (2007), banking in India is generally fairly mature in terms of supply,

product range and reach-even though reach in rural India still remains a challenge for the

private sector and foreign banks. In terms of quality of assets and capital adequacy,

Indian banks are considered to have clean, strong and transparent balance sheets relative

to other banks in comparable economies in its region. The Reserve Bank of India is an

autonomous body, with minimal pressure from the government. The stated policy of the

Bank on the Indian Rupee is to manage volatility but without any fixed exchange rate-and

this has mostly been true.


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With the growth in the Indian economy expected to be strong for quite some

time-especially in its services sector-the demand for banking services, especially retail

banking, mortgages and investment services are expected to be strong. One may also

expect M&As, takeovers, and asset sales.

In March 2006, the Reserve Bank of India allowed Warburg Pincus to increaseits stake in Kotak Mahindra Bank (a private sector bank) to 10%. This is the first time an

investor has been allowed to hold more than 5% in a private sector bank since the RBI

announced norms in 2005 that any stake exceeding 5% in the private sector banks would

need to be vetted by them.

In recent years critics have charged that the non-government owned banks are too

aggressive in their loan recovery efforts in connection with housing, vehicle and personal

loans. There are press reports that the banks' loan recovery efforts have driven defaulting

borrowers to suicide.

INVESTMENT OPPORTUNITIES TO INVESTORS

The three important characteristics of any financial asset are:

Returnthe potential return possible from an asset.

Risk the variability in returns of an asset from the chances of its value going

down/up

Liquiditythe case with which an asset can be converted into cash.

Investors tend to look at these three characteristics while deciding on theirindividual preference pattern of investment. Each financial asset wills a have a certain

level of each of these characteristics. These, in some way, determine the type of financial

asset.

Based on the preferred risk, return, and liquidity, each investor selects an

investment that matches his investment objective. The investment pattern of the

household sector in India gives a glimpse of the investment preference. The savings

pattern of the household sector in India can be differentiated in terms of currency;

fixed/savings instruments such as deposits, insurance/provident funds and small savings;

and securities market investment through mutual funds, government securities, and other

direct corporate investments.

INVESTMENT AVENUES


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There are a large number of investment avenues for savers in India. Some of

them are marketable and liquid, while others are non-marketable. Some of them are

highly risky while some others are almost riskless. The investor has to choose proper

avenues from among them, depending on his specific need, risk preference, and return

expectation.

Investment avenues can be broadly categorized under the following heads:

Corporate Securities

Equity shares

Debentures/Bonds

Warrants

Preference shares

GDRs/ADRs

Derivatives

Deposits in banks and non-banking companies

Post office deposits and certificates

Life insurance policies

Provident fund schemes

Government and semi-government securities

Mutual fund schemes

Real assets

LIMITATIONS

The study is confined to only the selected commercial banks securities in listed in

NSE.

The study is based on published data only.

The result of the study cannot be generalized.


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CHAPTERSCHEME

ChapterI

Introduction

The this chapter would deal with the scope and significances of the theme; an

introduction on stocks and stock market; an overview of stock market and banking

sectors and investment opportunities available to investors and the brief study of price

trend in the stock market.

ChapterII

Review of Literature

In this chapter, the reviews and the researches done by few authors on the related topics

are abstracted as reference

ChapterIII

Analysis and interpretation

This chapter deals with the analysis regarding index price and closing price of

bank securities and also 10-bank securities closing price are correlated with the index. A

study of a correlation between priceearnings ratio and banks book value.

ChapterIV

Findings, Suggestions and conclusion are presented in this chapter


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CHAPTER II

REVIEWS OF LITERATURE


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REVIEWS OF LETERATURE

I. In thE paper Modeling stock price behavior by financial ratios 1 the author Teppo

Martikainen purpose of this study is to find out which economic dimensions of the firm

are reflected in stock price behavior in the Finnish stock market. Twelve (10) financial

ratios are then selected to represent these four dimensions. All the firms common series

listed for the whole 19741986 period are included in the empirical analysis.

All of the dimensions above are found in the empirical classification pattern of

ratios. On the cross-sectional level, profitability and financial leverage are reported as

determinants of stock price behavior. Corporation growth is merely connected to the risk

of the common stock. Somewhat weaker results concerning the association between stock

price behaviors and operating leverage factor may be due to difficulties measuring

operating leverage on an empirical level.

When studying the intra-year explanatory power of financial ratios, it is reported

that the explanatory power of financial ratios tends to increase when the reporting day

approaches, and starts to decrease after that releasing day of financial statement numbers.

Empirical evidence strongly indicates that financial ratios represent pricing relationships

in a substantive manner.

The financial support by the Academy of Finland as well as the helpful comments

and suggestions of an anonymous referee are gratefully acknowledged.

II. In thEpaper Empirical Tests on the Stock Price trend of Privatized Enterprises 2 the

authors C. A. Alexakis, M. C. Kolomitsini, M. Cantharis examines the offer of shares

to the public, via the primary market of the stock exchange, is considered an efficient

way to privatize state owned companies. During the last decades, Greece went through a

privatization program and a number of state owned enterprises were listed on the Athens

Stock Exchange. In this paper, theystudy the price behavior of newly listed Greek

privatized companies, using data from 18 new issues over the period 1988- 2006.

1.Modeling stock price behavior by financial ratios by Teppo Martikainen, journal-

decisions in economics and finance, publisher-springer Milan, issue-volume 12,number

1/marc


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First, they examine if the market participants react to the listing price by buying or

selling significantly higher or lower; second, they test if the Greek market operates in

accordance to the prediction of the Efficient Market Hypothesis for instantaneous price

adjustment. From thar analysis we obtained strong statistical evidence that the majority of

the companies under examination traded at a price not significantly different than the

listing price; and the market behaved according to the predictions of the Efficient Market

Hypothesis.

III. In the paper Price trend of New Share Listings 3 the authors Olatunde Otaniyi,

Daniel Makina investigates whether new listings on the Nigerian Stock Exchange are

under-priced or not. On aggregate, they find that investors are able to make abnormal

gains from new listings on the first tier (main) market of the Nigerian Stock Exchange

(NSE).ther analyses show that up to one year after listing the average differences of real

share prices are positively significant to confirm the observation. The situation is

however different in the second (emerging) tier market. Ther analyses show that the real

prices of newly listed shares in the second tier market do fall. Such an observation could,

however, be attributed When ther thin trading of shares which phenomenon is

characteristic of second tier markets. e partition the data into pre-and post-deregulation

periods, we observe under- pricing of new equity listings to have been severe during the

pre-deregulation period, and hence more opportunity for abnormal gains.

2-Empirical Tests on the Stock Price trend of Privatized Enterprises in Greece by C. A.

Alexakis Assistant Professor, University of Piraeus, Department of Economics, M. C.

Kolomitsini University of Athens, Department of Economics, M. Xanthakis, Professor,

University of Athens, Department of Economics.

Ther find opportunities for making abnormal gains to be not as strong during the post-

deregulation period. When the data is analyzed on the basis of whether or not new listings

are financial institution firms, some interesting patterns of price behavior are found.

While we observe possibilities of making abnormal gains in new listings of non-financial

companies and insurance companies, these possibilities are absent in new listings of

banking sector shares indicating that they are efficiently priced relative to those of other

sectors.

IV. In this paper The trend of Stock-Market Prices[4] the author Eugene F. Fama

purpose of this paper will be to discuss first in more detail the theory underlying therandom-walk model and then to test the model's empirical validity

The main conclusion will be that the data seem to present consistent and for the

implies, of course, that chart reading, though perhaps an interesting pastime, is of no real

value to the stock market investor. This is an extreme statement and reader is certainly

free to take exception' We suggest, however, that since the empirical evidence produced


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by this and other studies in support of the random-wa1k is voluminous, the

counterarguments of the chart will be completely lacking in force if they are by empirical

work. The purpose of this paper has been to test empirically the random-walk model of

stock price behavior. The model makes two basic assumptions: (1) successive price

changes are independent, and (2) the price changes conform to some probability

distribution. We begin this section by summarizing the evidence concerning these

assumptions. Then the implications of the results will be discussed from various points of

view.

3- Price trend Of New Share Listings In Nigeria by Olatunde Otaniyi, University of

South Africa and Daniel Makina, University of South Africa

V. In this title Dividend Policy and Stock Price Behavior in Indian Corporate Sector [5]

policy and stock price behavior in Indian corporate sector. A sample of 500 listed

companies from BSE are examined for the years 1996-2006.Dividend policy has always

been a source of controversy despite years of theoretical and empirical research both in

developed countries and emerging economies.

4- The trend of Stock-Market Prices by Eugene F. Fama, the Journal of Business, Vol.

38, No. 1. (Jan., 1965), pp. 34-105, The Journal of Business is currently published by The

University of Chicago Press.

The present paper features a panel data approach to analyze the relationship

between dividend-retention ratio and stock-price behavior while controlling the variables

like size and long-term debt-equity ratio of the firm. The sample is taken across six

different industries namely electricity, food and beverage, mining, non-metallic, textile

and service sector. The results are based on the fixed-effect model, as these perform

statistically better than random effects and pooled OLS model.

Results of the fixed-effect models indicate that dividend-retention ratio along with

size and debt-equity ratio plays a significant role in explaining variations in stock returns.

The fixed effect models show the presence of firm level effect in explaining the possiblelinks between dividend policy and stock price behavior of the firm. In another words it

exhibits the possibility of clientele effect effect in case of some industries. Therefore

the model helps to understand the intricacies of dividend policy and stock-return behavior

in Indian corporate sector for the same period.


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Although the results are not robust enough as in the case of developed markets but

shades some more interesting facets to the existing corporate finance literature on

dividend policy in India.

VI. In this paper Stock market efficiency and random character of share price trend[6]

the author O. P. Guptastudy is aimed at testing the appropriateness of the random walkmodel in the Indian Stock Market for a recent period 197987. Using data of prices for

five shares indices from the Bombay Stock Exchange during this period, both the tests -

serial correlation and runs analysis, have generally supported the independence

assumption of the random walk model.

5- Dividend Policy and Stock Price trend in Indian Corporate Sector: A panel data

approach by Upananda Pani

VII. In this paper Stock price trend and operational risk management of banks in India

[7] the authors Ketty Vijay Parthasarathy, Dr. R Madhumathi examines Banks in India

work in a controlled regime similar to several other countries. The focus of the research is

to test the operational risk of sample banks operating in India and identify the extent to

which banks are capable of bearing operational risks.

6-Stock market efficiency and random character of share price behavior in India by O. P.

Gupta

The capital adequacy criteria to account for the operational risk using the Basic

Indicator Approach points out that several banks do not meet the regulatory requirements.

Further, the stock price movements of banks have been examined for randomness and it

has been proved that the bank stock prices do not follow a Geometric Brownian motion.

Risk management strategies of banks to reflect the price trend have been examined and

banks that have adequate exposure to risk cover have been contrasted with banks having

inadequate risk exposure cover.

VIII. In this paper Price trend in Emerging Stock Markets: Cases of Poland and

Slovakia [8] the authors Hranaiova, Jana analyzes serial correlation in stock returns,

and informational role of volume and volatility in Polish and Slovakian stock markets.

Results indicate that prices tend to overshoot to new information in the Slovakian market,

while new information gets impounded into prices with a one-day lag in the Polish


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market. In the context of feedback trading models, the Slovakian stock market seems to

be dominated by traders who sell high and buy low, while stop-loss or distress selling

type traders prevail in the Polish market.

7- Stock price trend and operational risk management of banks in India by Ketty Vijay

Parthasarathy, Dr. R Madhumathi, publisher-Springer Netherlands, volume-7th, Nov 2,

1990.

Traders became more sophisticated over time, as market efficiencies increased.

Informational role of volume and volatility appears to be consistent with that found in

developed stock markets.

IX. In this paper Stock price trend surrounding stock repurchase announcements [9] the

authors Takashi Hatakeda and Nobuyuki Isagawa examines stock price behavior

surrounding announcements of stock repurchases made by Japanese firms from 1995 to

1998. Our analysis shows that, much as in the case of the U.S. markets, stock prices in

Japan go up in response to stock repurchase announcements. We also find that there is no

significant difference between the market reaction to the announcement for intention of

repurchase execution and the market reaction to the announcement of an article alteration

to allow stock repurchases.

8- Price trend in Emerging Stock Markets: Cases of Poland and Slovakia by Hranaiova,

Jana

On the other hand, there is a significant difference in the pre-announcement

period returns motivating these two announcements. While a large decline in stock price

will motivate a firm to execute a stock repurchase, a smaller price decline will motivate a

firm to merely alter its articles of association to allow future repurchases.

X. In this paper Share Price trend around Buy Back and Dividend Announcements in

India[10] the authors P. Thirumalvalavan, K. Sunitha examines that over the past few

years, many firms have announced significant number of stock repurchases. Theoverwhelming reason given for stock repurchase announcements has been to reverse a

trend of declining stock prices. Share buy backs have become an important area in

financial research considering its strong implications for corporate policy. Indian

companies have been permitted to buy back shares after the provisions of the Companies

Act 1956 were suitably amended in 1999. Several studies have provided conclusive proof

of signaling effect of stock repurchase and dividends announcements. This paper


23/62

investigates and tests the following: 1) Signaling effect of a share buy - back and

dividend announcements 2) The market reaction and share price behavior to

announcements of stock repurchases and dividends 3) Abnormal Returns across various

repurchase levels. The analysis uses data of 22 firms in the BSE 500 index, which has

announced stock repurchase option and dividends during the period 2002-2004. An

examination of share price trend around stock repurchases and dividends prove the

signaling effect of these announcements.

Stock repurchase programs recorded a high cumulative abnormal return of 3.2 percent

within two days of the event whereas dividend announcement recorded a high cumulative

abnormal return of 2.1 percent within one day of the event. There is no significant

difference in abnormal returns as result of various repurchase levels. These results imply

the strong signaling power of stock repurchases announcements and that the market

reacts more favorably to repurchases compared to dividend announcements.

9- Stock price trend surrounding stock repurchases announcements by Takashi Hatakeda

and Nobuyuki Isagawa

10- Share Price trend around Buy Back and Dividend Announcements in India by P.

Thirumalvalavan , Bharathiar University K. Sunitha, Bharathiar University


24/62

CHAPTER IIIANALYSIS AND

INTERPRETATION OF

DATA


25/62

CHAPTER III

MEANING OF TECHNICAL ANALYSIS

Price trend of securities in the stock market fluctuates daily on account of

continuous buying and selling. Stock prices move in trends and cycles and are neverstable. An investor in the stock market is interested in buying securities at a low prices

and selling them at a high price so as to get a good return on his investment. He,

therefore, tries to analyze the movement of share prices in the stock market. Two

approaches are commonly used for this purpose. One of these is fundamental analysis and

other is technical analysis.

This approach is called technical analysis. Technical analysis is frequently used as

supplement to fundamental analysis rather than as a substitute for it. Thus, technical

analysis can, and frequently does, confirm findings based on fundamental analysis.

The technician does not consider value in the sense in which the fundamentalist

uses it. The technician believes the forces of supply and demand are reflected in patterns

of price and volume of trading. By examination of these patterns, we can predict whether

prices are moving higher or lower, and even by hoe much. In the narrowest sense, the

technician believes that price fluctuations reflect logical and emotional forces. And

further that price movements, whatever their cause, once in force persist for some period

of time and can be detected.

The technician must identify the trend and recognize when one trend comes to an

end and prices start in the opposite direction. The central problem is to distinguish

between reversals within a trend and real changes in the trend itself. This problem of

sorting out price changes is critical because prices do not change in a smooth,

uninterrupted fashion.

The technician views price changes and their significance mainly through price

and volumes statistics. The tools or indicators helps to measure price-volume, supply

demand relationships for the overall market as well as for individual stocks. Technicians

seldom rely upon a single indicator, as no one indicator is infallible; they place reliance

upon reinforcement provided by groups of indicators.

In this chapter, analysis concentratse upon some of the major technical indicatorsemployed to assess the direction of the general market and the direction of bank stocks.


26/62

CORRELATIO

The correlation is one of the most common and most useful statistics. A correlation is a

single number that describes the degree of relationship between two variables. Correlation

analysis permits the user for the goodness of fit between two variables. The advantage of

correlation analysis is that it permits the analyst to have a very specific measure of the

explanatory power of the regression equation; and thus the analyst has a means for assessing

the reliability of the point estimates. Correlation analysis tells the analyst how well the

independent variable explains the dependent variable in the regression equation.

Calculating the Correlation

The formula for the correlation is:

The symbol r to stand for the correlation. Through the magic of mathematics it turns out

that r will always be between -1.0 and +1.0. If the correlation is negative, we have a negative

relationship; if it's positive, the relationship is positive. But probably will need to know how the

formula relates to real data -- how you can use the formula to compute the correlation.


27/62

CORRELATION BETWEEN INDEX PRICE AND CLOSING PRICE OF

BANK SECURITIES

serial .no list of banks securities correlation

1 STATE BANK INDIA 0.962872

2 UNION BANK 0.703754

3 AXIS BANK 0.932722

4 BANK OF BARODA 0.808269

5 BANK OF INDIA 0.808561

6 CANARA BANK 0.885957

7 HDFC BANK 0.948336

8 ICICI BANK 0.819782

9 IDBI BANK 0.906643

10 KOTAK BANK 0.93113

INTERPRETATION

The correlation between index movement and the closing price of bank securities

are shown in the chart above. KARL PEARSONS COEFFICIENT OF CORRELATION

method is applied to find out the relationship between two variables i.e. index price

movement and closing price of bank securities and the coefficient of correlation (r) is

found positive. Therefore, it would mean that the correlation had the same relationship

between the variable. Thus, there is an effect on the Index price behavior whenever there

is change in closing price of bank securities.


28/62

PRICEEARNINGS RATIO

A price to earnings ratio, otherwise known as a P/E ratio, is a quick

calculation used to evaluate how expensive, or cheap, the stock market may be at any

given time. Just as an appraiser can come out and give you an estimate of the value of

your home, the P/E ratio is a tool you can use to estimate the fair value of the stock

market.

In simple terms, a P/E ratio is the price (P) divided by earnings (E). A stock

with a price of $10 a share, and earnings last year of $1 a share, would have a P/E ratio of

10.

In more complex terms, you have to decide whether to look at P/E ratios

based on last years earnings, forecasted earnings, or a ten year average of earnings. In

addition, P/E ratios for an individual stock must be interpreted much differently than P/E

ratios for the market as a whole.

DETERMINING A PRICE-EARNINGS RATIO

The most commonly used P/E multiplier is defined as the closing priceof the stock, divided by the report earnings of the most recent twelve months. Thus, if the

closing price of the stock was $50 and earnings for the last four quarters totaled $2, the

P/E multiplier would be 25. Generally, the P/E is based upon the current price that is,

the closing price of the stock on the day the analysis is being conducted. Thus, the P/E

can change daily.


29/62

PRICE EARNINGS RATIO AND BOOKVALUE OF 10 BANK SECURITIES

STATE BANK OF INDIA

Year Month Market Price Per Share Earnings Per Share P/E RATIO

2007 Jan-Mar 1104.551 28.37 38.93377

2007 Apr-Jun 1224.773 35.37 34.62745

2007 Jul-Sep 1614.678 40.86 39.51733

2007 Oct-Dec 2161.634 45.29 47.72873

2008 Jan-Mar 2112.412 34.62 61.0171

2008 Apr-Jun 1536.895 25.92 59.29379

2008 Jul-Sep 1410.511 37.48 37.6337

2008 Oct-Dec 1250.875 56.85 22.00308

2009 Jan-Mar 1088.141 43.23 25.17097

2009 Apr-Jun 1523.083 43.45 35.05369

2009 Jul-Sep 1799.845 48.06 37.44996

2009 Oct-Dec 2259.556 52.05 43.41126


30/62

UNION BANK


2007 Jan-Mar 107.1525 4.53 23.65397

2007 Apr-Jun 115.6637 4.46 25.93357

2007 Jul-Sep 144.8813 5.46 26.53504

2007 Oct-Dec 179.1452 7.23 24.77804

2008 Jan-Mar 185.1274 10.32 17.9387

2008 Apr-Jun 144.0352 4.52 31.86619

2008 Jul-Sep 134.2164 7.16 18.74531

2008 Oct-Dec 148.3805 13.3 11.15643

2009 Jan-Mar 141.2517 9.21 15.33678

2009 Apr-Jun 192.8475 8.75 22.03971

2009 Jul-Sep 228.8922 10 22.88922

2009 Oct-Dec 263.6074 10.57 24.93921


31/62

AXIS BANK

Year Month Market price Earnings price P/E RATIO

2007 Jan-Mar 502.462 7.56 66.4632

2007 Apr-Jun 533.49 6.2 86.0468

2007 Jul-Sep 637.975 7.14 89.3522

2007 Oct-Dec 903.129 9.09 99.3541

2008 Jan-Mar 987.99 9.89 99.8979

2008 Apr -Jun 794.924 9.03 88.0314

2008 Jul-Sep 686.449 11.07 62.0099

2008 Oct-Dec 533.131 13.78 38.6888

2009 Jan-Mar 401.648 16.1 24.9471

2009 Apr -Jun 657.38 15.5 42.4116

2009 Jul-Sep 877.43 14.38 61.0174

2009 Oct-Dec 985.405 15.98 61.6649


32/62

BANK OF BARODA

Year Month Market Price Per share Earnings Per Share P/E RATIO

2007 Jan- Mar 226.164 6.74 33.5555

2007 Apr - Jun 253.161 9.08 27.8811

2007 Jul - Sep 287.863 8.98 32.056

2007 Oct - Dec 363.206 13.75 26.415

2008 Jan -Mar 380.374 7.59 50.1152

2008 Apr - Jun 272.188 10.18 26.7375

2008 Jul - Sep 266.027 10.85 24.5186

2008 Oct - Dec 270.897 19.45 13.9279

2009 Jan t- Mar 234.748 20.66 11.3625

2009 Apr - Jun 371.663 18.82 19.7483

2009 Jul - Sep 433.28 17.41 24.8868

2009 Oct - Dec 516.292 22.85 22.5948


33/62

BANK OF INDIA


2007 Jan-Mar 178.173 9.18 19.4088

2007 Apr-Jun 197.514 6.47 30.5276

2007 Jul-Sep 246.469 8.73 28.2324

2007 Oct-Dec 337.789 10.5 32.1704

2008 Jan-Mar 347.657 14.95 23.2547

2008 Apr-Jun 298.642 10.7 27.9105

2008 Jul-Sep 270.005 14.53 18.5826

2008 Oct-Dec 265.459 16.61 15.9819

2009 Jan-Mar 233.813 15.43 15.1531

2009 Apr-Jun 291.19 11.13 26.1626

2009 Jul-Sep 340.762 6.16 55.3185

2009 Oct-Dec 390.802 7.72 50.622


34/62

CANARA BANK


200 Jan - Mar 226.915 12.32 18.41843

2007 Apr - Jun 232.3629 5.87 39.58482

2007 Jul - Sep 262.2383 9.79 26.78634

2007 Oct - Dec 283.0865 11.19 25.29817

2008 Jan - Mar 289.3976 11.32 25.56516

2008 Apr - Jun 218.1082 2.99 72.94589

2008 Jul - Sep 277.1383 12.91 21.46695

2008 Oct - Dec 174.6712 17.11 10.20872

2009 Jan - Mar 176.128 17.53 10.04723

2009 Apr - Jun 234.5822 13.54 17.32513

2009 Jul - Sep 277.1383 22.21 12.47809

2009 Oct - Dec 375.1361 25.67 14.61379


35/62

HDFC BANK


2007 Jan-Mar 1015.361 10.9 93.15237

2007 Apr-Jun 1049.427 10 104.9427

2007 Jul-Sep 1194.13 10.5 113.7267

2007 Oct-Dec 1603.194 11.9 134.7222

2008 Jan-Mar 1503.018 13.1 114.7342

2008 Apr-Jun 1325.892 10.8 122.7678

2008 Jul-Sep 1170.261 12.3 95.14317

2008 Oct-Dec 1006.614 14.6 68.94613

2009 Jan-Mar 909.9966 14.8 61.48626

2009 Apr-Jun 1295.984 14.1 91.91375

2009 Jul-Sep 1462.984 15.9 92.01155

2009 Oct-dec 1710.248 18.4 92.94828


36/62

ICICI BANK


2007 Jan - Mar 910.8733 6.23 146.2076

2007 Apr - Jun 903.1968 8.61 104.9009

2007 Jul - Sep 924.9656 9.08 101.8685

2007 Oct - Dec 1166.77 10.99 106.1665

2008 Jan - Mar 1104.585 5.68 194.4691

2008 Apr - Jun 817.7664 6.51 125.617

2008 Jul - Sep 641.4672 9.09 70.56845

2008 Oct - Dec 404.1407 11.42 35.38885

2009 Jan - Mar 377.6169 6.72 56.193

2009 Apr - Jun 684.6841 7.87 86.99926

2009 Jul - Sep 759.2008 9.3 81.63449

2009 Oct -Dec 879.1984 9.84 89.34943


37/62

IDBI BANK


2007 Jan-Mar 86.125 2.95 29.1949

2007 Apr-Jun 93.7653 2.11 44.4385

2007 Jul-Sep 123.234 2.15 57.3183

2007 Oct-Dec 156.325 2.43 64.3311

2008 Jan-Mar 121.029 3.38 35.8074

2008 Apr-Jun 90.2361 2.2 41.0164

2008 Jul-Sep 78.407 2.24 35.0031

2008 Oct-Dec 65.4958 3.07 21.3341

2009 Jan-Mar 53.0822 4.33 12.2592

2009 Apr-Jun 81.2407 2.37 34.2788

2009 Jul-Sep 103.657 3.5 29.6163

2009 Oct-Dec 126.273 3.96 31.8871


38/62

KOTAK BANK

YEAR MONTH market price per share earnings per share P/E RATIO

2007 Jan -Mar 449.2325 5.22 86.05987

2007 Apr - Jun 550.7411 4.47 123.2083

2007 Jul - Sep 732.5406 7.3 100.348

2007 Oct - Dec 1081.99 10.48 103.2433

2008 Jan - Mar 926.3669 6.86 135.0389

2008 Apr - Jun 682.3721 4.29 159.0611

2008 Jul - Sep 561.4078 4.62 121.5168

2008 Oct - Dec 380.2653 3.71 102.4974

2009 Jan - Mar 280.3669 6.09 46.03727

2009 Apr - Jun 542.8737 7.41 73.26231

2009 Jul - Sep 686.2039 8.57 80.07047

2009 Oct - Dec 786.6902 9.44 83.33582


39/62

P/E RATIO BOOKVALUE CORRELATION

NOLIST OFBANKS 2007 2008 2009 2007 2008 2009

AXIS BANK 31.23009 24.30795 14.65022 120.8 245.13 284.5 -0.9263

2 BANK BARODA 9.145456 6.999333 5.973331 237.46 303.18 352.37 -0.9930

3 BANK INDIA 10.59953 7.423063 5.3635 117.89 160.06 224.39 -0.9708

4 CANARA BANK 6.747925 5.033368 5.279542 197.83 202.33 244.87 -0.4593

5 HDFC BANK 33.56807 27.48836 25.6213 201.42 324.38 344.44 -0.9953

6 ICICI BANK 31.60831 23.28077 20.54747 270.37 417.64 445.17 -0.9957

7 IDBI BANK 13.25597 8.639395 8.658992 86.09 93.82 102.71 -0.8432

8 KOTAK BANK 162.2525 21.93077 30.6355 50.95 104.26 112.98 -0.9828

SBIN 12.67723 9.3824 9.701457 594.69 776.48 912.73 -0.8633

UNION BANK 8.19499 5.567351 6.073029 93.71 111.33 139.66-

0.6676


40/62

INTERPRETATION FOR THE PERIOD 2007

The correlation between P/E ratio and Book value of banks in 2007are

shown in theTable . KARL PEARSONS COEFFIDIENT OF CORRELATION method

is applied to find out the relationship between two variables i.e. P/E ratio and Book value

and the coefficient of correlation (r) is found negative. Therefore, it would mean thatcorrelation has a inverse relationship between variables. Thus, there is an effect on the

P/E ratio whenever there is change in book value.


The correlation between P/E ratio and Book value of banks in 2008 are

shown in the .Table KARL PEARSONS COEFFIDIENT OF CORRELATION method

is applied to find out the relationship between two variables i.e. P/E ratio and Book value

and the coefficient of correlation (r) is found negative. Therefore, it would mean that

correlation has a inverse relationship between variables. Thus, there is an effect on the

P/E ratio whenever there is change in books value.


The correlation between P/E ratio and Book value of banks are shown in

the chart above. KARL PEARSONS COEFFIDIENT OF CORRELATION method is applied to

find out the relationship between two variables i.e. P/E ratio and Book value and the

coefficient of correlation (r) is found negative. Therefore, it would mean that correlation

has a inverse relationship between variables. Thus, there is an effect on the P/E ratio

whenever there is change in book value.


41/62

MOVING AVERAGE CONVERGENCE AND DIVERGENCE ( MACD)

MACD is an oscillator that measures the convergence and divergence between

two exponential moving averages. A short-term exponential moving average and a long-

term exponential moving average are calculated with help of the closing price data. A 12

day and 48 day exponential moving average constitute a popular combination. Thedifference between the short-term EMA and the long-term EMA repr The MACD values

for different days are derived by deducting the long-term EMA for each day from the

corresponding short-term EMA for the day

These MACD values are plotted on an XY graph with MACD values on the Y axis

and time periods on X axis. The MACD line would oscillate across the zero line. If the

MACD line crosses the zero line from above, the trend can be considered to have turned

bearish, signaling a selling opportunity. On the other hand, if the MACD line moves

above zero line from below, the trend can be said to have turned bullish and indicates a

buying opportunity.

Sometimes, a simple moving average or an exponential moving average of the

MACD values is superimposed over the MACD graph. Then buy and sell signals are

generated by the cross over the average line and the MACD line. When the lines are

below the zero line. If the MACD line crosses the average line from below to above, it

indicates a buying opportunity. When the lines are above line, crossing of the, MACD

line from above to below the average line signals a selling opportunity.


42/62

MACD CHART FOR 14 AND 26 DAYS MOVING AVERAGE

A technical analysis is done on the Index price movement by using Simple

Moving Average (SMA). A simple moving average (SMA) is the unweighted mean of

the previous n data points. In all cases a moving average lags behind the latest data point,

simply from the nature of its smoothing. An SMA can lag to an undesirable extent, andcan be disproportionately influenced by old data points dropping out of the average. The

MACD (MACD means a trend-following momentum indicator that shows the

relationship between two moving averages of prices) is calculated by subtracting the 26-

day simple moving average (SM

In this study I have taken index price of 12 bank securities prices for the period of three

years from 1st January 2007 to 31st December 2009. Technical analysis is done on the

collected data available with the help of Simple Moving Average.

INTERPRETATION

As shown in the chart above it is technically found that

The above MACD chart shows that from the day one the closing price comes

down over the 14 SMA so it shows a bearish market till the 4th day and from 5th day it

shows an buy signal into the market .On the day 37th day it shows a price as went

downward trend shows a bearish market and signal of selling the securities. By watching

the MACD line it shows on 89th day a reverse trend from bearish to bullish showing a

signal to buy the securities which it is shows the expectation of investors for increasing

prices.

0

2000

4000

6000

8000

10000

12000

113

25

37

49

61

73

85

97

109

121

133

145

157

169

181

193

205

217

229

241

closingpriceindex

index days

MACD CHART 2007

Close

SMA 14

DAYS

SMA 26

DAYS


43/62

As similarly by watching the MACD line the prices shows an upward trend and

indicating the investors by showing buying signal on 123rd day, 207 Th day, and 225th

days respectively. And also MACD chart shows a reverse signal of bullish to bearish

market of indicating the investors of selling signal for the 94th day, 147th day and 210th

day respectively. So as shown above the 26 line SMA are the fastest moving trend in both

bullish and bearish market than 14 line SMA and closing price. The MACD chart above

indicates the downward trend in the market for 12 bank NSE securities.

INTERPRETATION


The above MACD chart shows that from the day one the closing price goes up

over the 14 SMA so it shows a bullish market till the 49th day and from 50th day it

shows an sell signal into the market .On the day 72nd day it shows a price as went

upward trend shows a bullish market and signal of buying the securities.

0

2000

4000

6000

8000

10000

12000

114

27

40

53

66

79

92

105

118

131

144

157

170

183

196

209

222

235

Closingpriceinde

x

INDEX DAYS

MACD CHART 2008

Close

SMA 14

DAYS

SMA 26

DAYS


44/62

By watching the MACD line it shows on 116th day a reverse trend from bullish to

bearish showing a signal to sell the securities that indicates the investors to sell the

securities as there was no demand for those securities. As similarly by watching the

MACD line the prices shows an upward trend and indicating the investors by showing

buying signal on 140th day, 160 Th day, and 222nd days respectively. And also MACD

chart shows a reverse signal of bullish to bearish market of indicating the investors of

selling signal for the 148th day and 213th day respectively. So as shown above the 26

line SMA are the fastest moving trend in both bullish and bearish market than 14 line

SMA and closing price. The MACD chart above indicates the downward trend in the

market for 12 bank NSE securities.

INTERPRETATION


The above MACD chart shows that from the day one the closing price comes

down over the 14 SMA so it shows a bearish market till the 31st day .On the day 88th day

it shows a price as went upward trend shows a bullish market and signal of buying the

securities. By watching the MACD line it shows on 32th day a reverse trend from bullish

to bearish showing a signal to sell the securities that indicates the investors to sell the

securities as there was no demand for those securities.

0

2000

4000

6000

8000

10000

12000

114

27

40

53

66

79

92

105

118

131

144

157

170

183

196

209

222

235

Closingpriceindex

INDEX DAYS

MACD CHART 2009

Close

SMA 14 DAYS

SMA 26 DAYS


45/62

As similarly by watching the MACD line the prices shows an upward trend and

indicating the investors by showing buying signal on 100th day, 129th day, 180th day and

206th days respectively.And also MACD chart shows a reverse signal of bullish to

bearish market of indicating the investors of selling signal for the 96th day, 113 day,

140th day and 190th day respectively. So as shown above the 26 line SMA are the fastest

moving trend in both bullish and bearish market than 14 line SMA and closing price. The

MACD chart above indicates the upward trend in the market for 12 bank NSE securities.

MACD CHART FOR INDEX AND CLOSING PRICE OF BANK SECURITIES

A technical analysis is done on the Index price movement and daily closing price

of bank securities in NSE.

MACD lines are often regarded as a trend following indicator designed to

identify trend changes. The MACD chart as drawn above is sometimes used as an

oscillator. Three types of trading signals are generated:

MACD line crossing the signal line.

MACD line crossing 0.

Divergence between price and chart, or between MACD line and price.

Positive divergence between MACD and price arises when price makes a new

selloff low, but the MACD doesn't make a new low (i.e. it remains above where it fell to

on that previous price low). This is interpreted as bullish, suggesting the downtrend may

be nearly over. Negative divergence is the same thing when rising (i.e. price makes a new

rally high, but MACD doesn't rise as high as before), this is interpreted as bearish.

Divergence may be similarly interpreted on the price versus the chart, where the

new price levels are not confirmed by new chart levels. Longer and sharper divergences

(distinct peaks or troughs) are regarded as more significant than small shallow patterns in

this case.

In this study I have taken index price movement and closing price of AXIS

BANK for the period of three years from 1st January 2007 to 31st December 2009.


46/62

STATE BANK OF INDIA

In this study I have taken index price movement and closing price of STATE BANK

OF INDIA for the period of three years from 1st January 2007 to 31st December 2009

INTERPRETATION


The MACD chart shows when a crossing occurs. When the MACD line crosses

through zero on the chart it is said that the MACD line has crossed the signal line.

The MACD chart can also help visualizing when the two lines are coming

together. Both may still be rising, but coming together, so a falling histogram

suggests a crossover may be approaching.

A crossing of the MACD line up through zero is interpreted as bullish, or down

through zero as bearish

0

5000

10000

15000

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715

Closingindexvalue

Index days

Close index

Close index

0

1000

2000

3000

134

67

100

133

166

199

232

265

298

331

364

397

430

463

496

529

562

595

628

661

694

727

Closingprice

Days

Close Price

Close Price


47/62

BANKOFBARODA

In this study I have taken index price movement and closing price of BANK

BARODA for the period of three years from 1st January 2007 to 31st December 2009.

INTERPRETATION









0

200

400

600

137

73

109

145

181

217

253

289

325

361

397

433

469

505

541

577

613

649

685

721

CLOSINGP

RICE

DAYS

Close Price

Close Price

0

5000

10000

15000

138

75

112

149

186

223

260

297

334

371

408

445

482

519

556

593

630

667

704

CLOSING

INDEXVALUE

INDEX DAYS

Close index

Close index


48/62

BANK OF INDIA

In this study I have taken index price movement and closing price of BANK

INDIA for the period of three years from 1st January 2007 to 31st December 2009.

INTERPRETATION









0

200

400

600

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715

CLOSINGP

RICE

DAYS

Close Price

Close Price

0

5000

10000

15000

138

75

112

149

186

223

260

297

334

371

408

445

482

519

556

593

630

667

704

CLOSINGI

NDEXVLAUE

INDEX DAYS

Close index

Close index


49/62

CANARA BANK

In this study I have taken index price movement and closing price of CANARA

BANK for the period of three years from 1st January 200 7 to 31st December 2009

INTERPRETATION








through zero as bearish.

0

5000

10000

15000

138

75

112

149

186

223

260

297

334

371

408

445

482

519

556

593

630

667

704

closingindexvalue

index days

Close index

Close index

0

200

400

600

137

73

109

145

181

217

253

289

325

361

397

433

469

505

541

577

613

649

685

721

closingprice

days

Close Price

Close Price


50/62

UNION BANK

In this study I have taken index price movement and closing price of UNION BANK

for the period of three years from 1st January 2007 to 31st December 2009

INTERPRETATION








0

2000

4000

6000

8000

10000

12000

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715C

losingindexvalue

Indexdays

Close index

Close index

0

100

200

300

134

67

100

133

166

199

232

265

298

331

364

397

430

463

496

529

562

595

628

661

694

727

Closingprice

Days

Close Price

Close Price


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AXIS BANK

In this study I have taken index price movement and closing price of AXIS

BANK for the period of three years from 1st January 2007 to 31st December 2009.

INTERPRETATION:-

As shown in the chart above it is technically found that: -








0

500

1000

1500

138

75

112

149

186

223

260

297

334

371

408

445

482

519

556

593

630

667

704

CLOSINGP

RICE

DAYS

Close Price

Close Price

0

2000

4000

6000

8000

10000

12000

138

75

112

149

186

223

260

297

334

371

408

445

482

519

556

593

630

667

704

CLOSINGI

NDEXVALUE

INDEX DAYS

Close index

Close index


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HDFC BANK

In this study I have taken index price movement and closing price of HDFC BANK


INTERPRETATION







A crossing of the MACD line up through zero is interpreted as bullish, or downthrough zero as bearish

0

500

1000

1500

2000

132

63

94

125

156

187

218

249

280

311

342

373

404

435

466

497

528

559

590

621

652

683

714

closingprice

days

Close Price

Close Price

0

5000

10000

15000

134

67

100

133

166

199

232

265

298

331

364

397

430

463

496

529

562

595

628

661

694

727c

losingindexvalue

index days

Close index

Close index


53/62

ICICI BANK

In this study I have taken index price movement and closing price of ICICI BANK


INTERPRETATION







A crossing of the MACD line up through zero is interpreted as bullish, or downthrough zero as beari

0

5000

10000

15000

132

63

94

125

156

187

218

249

280

311

342

373

404

435

466

497

528

559

590

621

652

683

714

closingindexvalue

index days

Close index

Close index

0

500

1000

1500

2000

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715

closingprice

Days

Close Price

Close Price


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IDBI BANK

In this study I have taken index price movement and closing price of IDBI BANK for

the period of three years from 1st January 2007 to 31st December 2009

INTERPRETATION








through zero as bearish.

0

50

100

150

200

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715

closingprice

Days

Close Price

Close Price

0

5000

10000

15000

137

73

109

145

181

217

253

289

325

361

397

433

469

505

541

577

613

649

685

721

closingindexvalue

index days

Close index

Close index


55/62

KOTAK BANK

In this study I have taken index price movement and closing price of KOTAK BANK


INTERPRETATION









0

5000

10000

15000

132

63

94

125

156

187

218

249

280

311

342

373

404

435

466

497

528

559

590

621

652

683

714

Closingindexvalue

index days

Close index

Close index

0

500

1000

1500

135

69

103

137

171

205

239

273

307

341

375

409

443

477

511

545

579

613

647

681

715

closingprice

Days

Close Price

Close Price


56/62

CHAPTER IV

SUMMARY


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Finding

The correlation of price earnings ratio and book value of bank securities in NSE

by collecting datas from financial statements of those banking securities shows

an inverse relation by negative results.

The MACD charts of 12 bank securities by analyzing closing price and closing

index of those banking securities indicates of bullish market and bearish market

and also shows a signal of buy and sell of securities.

The MACD charts for closing price of securities for simple moving averages of

14-SMA and 26-SMA line showing a securities position in the stock market. And

also indicates an speculation dealings in the bank securities in NSE


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Suggestions

The correlation of price - earnings ratio and book value as shows in the project are

negative so it shows an inverse relationship between these two variables results thatbanks have negative results of correlation less than 1. The MACD charts show a price

behavior of the banking securities in NSE by collecting data of closing price for three

years. This chart indicates a stock market trend and the securities value in the market.

This shows a bullish market or bearish market and the signal of buying and selling that

this year or day etc.

As comparing the moving averages of these banking securities it always shows

relationship of both upward trend and down ward trend the investors need to watch these

securities value and market movement before investing in these market securities and

also examining the past price behavior of these securities into the market by the investor.The keen watch on the market condition and past price helps the investors in guiding in

which securities to invest and what values it had.

This study indicates that the current condition in the banking sectors has an

increase trend in the share market. The analyses shows that the private sector banks

always show a high speculation and risky trend in investing .So it is better for the

investors to invest in public sector bank to ensure safety and earnings than private sector

banks.


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CONCLUSION

A stock market / share market is a public market (a loose network of economic

transactions not a physical facility or discrete entity) for the trading of company stockand derivatives at an agreed price; these are securities listed on a stock exchange as well

as those only traded privately.

The size of the world stock market was estimated at about $36.6 trillion US at the

beginning of October 2008. The total world derivatives market has been estimated at

about $791 trillion face or nominal value, 11 times the size of the entire world economy.

The value of the derivatives market, because it is stated in terms of notional values,

cannot be directly compared to a stock or a fixed income security, which traditionally

refers to an actual value. Moreover, the vast majority of derivatives 'cancel' each other

out (i.e., a derivative 'bet' on an event occurring is offset by a comparable derivative 'bet'on the event not occurring.). Many such relatively illiquid securities are valued as marked

to model, rather than an actual market price.

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

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

that captures the capital market performance of Indian Banks. The index will have 12

stocks from the banking sector which trade on the National Stock Exchange.

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

approximately 96.46% of the traded value of the banking sector. CNX Bank Index stocks

represent about 87.24% of the total market capitalization of the banking sector as on

March 31, 2009.

Constituents list of CNX Bank:-Axis Bank Ltd., Bank of Baroda, Bank of India,

Canara Bank, HDFC Bank Ltd., ICICI Bank Ltd., IDBI Bank Ltd., Kotak Mahindra Bank

Ltd.,


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APPENDIX

BIBLIOGRAPHY

REFERENCE

The Behavior of Stock-Market Prices

Author: - Eugene F. Fama

The Journal of Business, Vol. 38, No. 1. (Jan., 1965), pp. 34-105

Determinants of Equity Prices in the Stock Markets :-

Author: - Somoye, Russell Olukayode Christopher

Dept. of Banking & Finance, Faculty of Management Science Olabisi Onaban

University, Ago Iwoye, Nigeria

Stock market efficiency and random character of share price behavior in India

Author: - O. P. Gupt

Price Behavior in Emerging Stock Markets

Author: - Hranaiova, Jana

Security Analysis and Portfolio Management

Book Author: - V.K.Bhalla

Investment analysis and portfolio management

Book author: - Dr.M.Ranganatham and R.Madhumathi

Security Analysis and portfolio management

Book author: - Kevin

Share Price Behavior around Buy Back and Dividend Announcements in India

Author: - P. Thirumalvalavan , Bharathiar University K. Sunitha, Bharathiar

University


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THE STRUCTURE AND PRICE EFFICIENCY OF AN EMERGING MARKET

Author: - Raghbendra Jha, Hari K. Nagarajan, volume-10, year-2000, page-50-59.

Stock price behavior surrounding stock repurchases announcements

Author: - Takashi Hatakeda and Nobuyuki Isagawa

Stock price behavior and operational risk management of banks in India

Author: - Ketty Vijay Parthasarathy, Dr. R Madhumathi, publisher-Springer

Netherlands, volume-7th, Nov 2, 1990.

Modeling stock price behavior by financial ratios

Authour :- Teppo Martikainen,journal-decisions in economics and

finance,publisher- springer Milan,issue-volume 12,number 1/marc

Web sites

WWW.NSE.COM

WWW.GOOGLE.COM

WWW.SCRID.COM


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