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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
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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
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CHAPTER IIIANALYSIS AND
INTERPRETATION OF
DATA
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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.
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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.
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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.
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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.
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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
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UNION BANK
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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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
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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
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BANK OF INDIA
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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CANARA BANK
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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HDFC BANK
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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ICICI BANK
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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IDBI BANK
Year Month Market Price Per Share Earnings Per Share P/E RATIO
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
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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
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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
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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.
INTERPRETATION FOR THE PERIOD 2008
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.
INTERPRETATION FOR THE PERIOD 2009
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.
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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.
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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
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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
As shown in the chart above it is technically found that
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
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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
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 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
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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.
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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
As shown in the chart above it is technically found that
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
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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
As shown in the chart above it is technically found that
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
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
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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
As shown in the chart above it is technically found that
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
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
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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
As shown in the chart above it is technically found that
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
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
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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
As shown in the chart above it is technically found that
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
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: -
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
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
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
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 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
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ICICI BANK
In this study I have taken index price movement and closing price of ICICI 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
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 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
As shown in the chart above it is technically found that
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
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
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KOTAK BANK
In this study I have taken index price movement and closing price of KOTAK 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
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
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
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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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