Hemant+Kumar+MBA G+Summer+Internship+Project+Report+2012

8/13/2019 Hemant+Kumar+MBA G+Summer+Internship+Project+Report+2012

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DECLARATION

Title of Project Report

INDIAN STOCK MARKET ANALYSIS AND FORECAST OF KOTAK

MAHINDRA BANK LTD.

I declare

(a)That the work presented for assessment in this Summer Internship Report is my

own, that it has not previously been presented for another assessment and that my

debts (for words, data, arguments and ideas) have been appropriately acknowledged

(b)That the work conforms to the guidelines for presentation and style set out in the

relevant documentation.

Date : ..

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CERTIFICATE

I Ms. Tavishi hereby certify that Hemant Kumar student of Masters of Business

AdministrationGeneral at Amity Business School, Amity University Uttar Pradesh

has completed the Project Report on INDIAN STOCK MARKET ANALYSIS

AND FORECAST OF KOTAK MAHINDRA BANK LTD.

under my guidance.

Ms. Tavishi

Assistant Professor

Department of Economics


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ACKNOWLEDGEMENT

I owe a great many thanks to a great many people who helped and supported me

during the writing of this project. My deepest thanks to Assistant Professor Ms.

Tavishi, Department of Economics., the guide of the project for guiding and

correcting various documents of mine with attention and care. She has taken pain to

go through the project and make necessary correction as and when needed. I express

my thanks to the Director of Amity University, Noida for extending his support. My

deep sense of gratitude to Mr. Krishan Pal Singh, Sales Manager, Kotak

Mahindra Bank for support and guidance. Thanks and appreciation to the helpful

people at Kotak Mahindra Bank, South Ex Branch, for their support. I would also

thank my Institution and my faculty members without whom this project would have

been a distant reality. I also extend my heartfelt thanks to my family and well wishers.

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Table Of Contents

Chapter 1- Introduction .................................................................................................. 7

1.1 About Kotak Mahindra......................................................................................... 7

1.2 Objective Of The Study ...................................................................................... 10

1.3 Theoretical Framework ...................................................................................... 11

Chapter 2- Review of the literature .............................................................................. 16

Chapter 3- Research methodology and procedures ..................................................... 26

3.1 Purpose Of The Study ........................................................................................ 33

3.2 Research Design ................................................................................................. 34

3.3 Research Questions ............................................................................................ 34

3.4 Data Collection, Instruments And Analysis ....................................................... 34

3.5 Limitations ......................................................................................................... 35

Chapter 4-Data analysis and interpretation .................................................................. 36

4.1 Analysis and interpretation for 1st objective ...................................................... 36

4.2 Analysis and interpretation for 2nd objective ................................................... 41

4.3 Analysis and interpretation for 3rd objective ..................................................... 48

4.4 Findings: ............................................................................................................. 52

Chapter 5-Conclusion and Recommendations ............................................................. 53

5.1 Summary Of findings ......................................................................................... 53

5.2 Discussion of Research Questions ..................................................................... 55

5.3 Recommendations .............................................................................................. 55

Reference Material ....................................................................................................... 56

References: ................................................................................................................... 57


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INDIAN STOCK MARKET ANALYSIS AND FORECAST OF KOTAK

MAHINDRA BANK LTD.

ABSTRACT

Kotak Mahindra Bank Ltd. has been growing in terms of stock and financial stability

in the recent years. The research analyzes the growth in share price and the financial

condition of the company. The research also identifies the crucial factors which affect

the Indian Stock market. The methodology for the research included various inputs to

achieve three main objectives which were to analyze the growth of KOTAK

Mahindra Bank Ltd in stock market using fundamental analysis, to identify and

analyze the Indian stock market (BSE) and crucial factors that contribute to rise

and fall in stock prices over a period of time and to predict and forecast the

share prices based on technical techniques. The research has been done by

secondary data which are collected through various archives, bank`s database, web

database and case studies. The data is analyzed by softwares such as SPSS and Excel

using statistical techniques such as Regression, Moving Averages, Ratio Analysis,

Correlation etc. The research is an exploratory and conclusive research and which

includes quantitative data. The conclusions and findings of the research conclude that

Kotak financial stability has led to its growth of share prices. There are several factors

which affect BSE Sensex but only certain factors such as Foreign exchange reserves,

Price of Oil Per Barrel, Price of Gold Per Ounce, and Inflation rates are considered to

be crucial factors. Kotak Mahindra Banksclose prices for the month of May, June

and July for 2012 were also predicted in the research and it shows the growth in the

prices. The investors are satisfied with the company`s returns. However, share market

of India is volatile and the company needs to work on it asset management.

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Chapter 1- Introduction

1.1 About Kotak Mahindra

Kotak Mahindra is one of India's leading banking and financial services organizations,

offering a wide range of financial services that encompass every sphere of life. From

commercial banking, to car finance, to stock broking, to asset management, to life

insurance, to investment banking, the group caters to the financial needs of

individuals and corporate identities. The group has a net worth of ` 12,901 crore and

has a distribution network through branches, franchisees, and satellite offices across

cities and towns in India and offices in New York, San Francisco, London, Dubai,

Mauritius and Singapore, servicing close to 10 million customer accounts.

Established in 1985, the Kotak Mahindra group has been one of India's most reputed

financial conglomerates. In February 2003, Kotak Mahindra Finance Ltd, the group's

flagship company was given the license to carry on banking business by the Reserve

Bank of India (RBI). This approval created banking history since Kotak Mahindra

Finance Ltd. is the first non-banking finance company in India to convert itself in to a

bank as Kotak Mahindra Bank Ltd. Today, the bank is one of the fastest growing bank

and among the most admired financial institutions in India.

The bank has over 323 branches and a customer account base of over 2.7 million.

Spread all over India, not just in the metros but in Tier II cities and rural India as well,

it is redefining the reach and power of banking. Presently it is engaged in commercial

banking, stock broking, mutual funds, life insurance and investment banking. It caters


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to the financial needs of individuals and corporate identities. The bank has an

international presence through its subsidiaries with offices in London, New York,

Dubai, Mauritius, San Francisco and Singapore that specialize in providing services to

overseas investors seeking to invest into India.

Products and Services

The bank offers complete financial solutions for infinite needs of all individual and

non-individual customers depending on the customer's need - delivered through a

state of the art technology platform. Investment products like Mutual Funds, Life

Insurance, retailing of gold coins and bars etc are also offered. The bank follows a

mix of both open and closed architecture for distribution of the investment products.

All this is backed by strong, in-house research on Mutual Funds.

The banks savings account goes beyond the traditional role of savings, and allows us

to put aside a lot more than just money. The worry-free feature of Savings Account

provides a range of services from funds transfer, bill payments, 2-way sweep throughour ActivMoney feature and much more. We can place standing instructions for

investment options that can be booked through Internet or through Phone banking

services. The Savings Account thus provides for attractive returns earned through a

comprehensive suite products and services that offer investment options, all delivered

seamlessly to the customer by well integrated technology platforms.

Apart from Phone banking and Internet banking, the Bank offers convenient banking

facility through Mobile banking, SMS services, Netc@rd, Home banking and Bill Pay

facility among others.

The Depository services offered by the Bank allows the customers to hold equity

shares, government securities, bonds and other securities in electronic or Demat

forms.

The Salary 2 Wealth offering provides comprehensive administrative solutions for

Corporates with features such as easy and automated web based salary upload process

thereby eliminating the paper work involved in the process, a dedicated relationship

manager to service the corporate account, customized promotions and tie - ups and


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1.2 Objective Of The Study

The research is undertaken for Kotak Mahindra Bank Ltd. It aims at three main

objectives:

1. To analyze the growth of the KOTAK Mahindra Bank Ltd. using fundamental

analysis.

2. To identify and analyze the stock market and crucial factors that contribute to rise and

fall in stock prices over a period of time.

3. To predict and forecast the stock market based on technical techniques.

The purpose of the study focuses on growth of Kotak Mahindra Bank Ltd. and in

addition, to identify the crucial factors which affect the rise and fall in stock prices of

BSE. The study also focuses on forecast of share prices of the company for the month

May 12, June 12 and July 12.


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1.3 Theoretical Framework

-

Due to low labour cost and skillful manpower sectors like textile, garments,

manufacturing, banking and insurance has made a significant contribution to foster

the growth potentials of the economy. The Structural Adjustment Program adopted in

1991 had focused on stabilization and structural reforms in this respect the

changeover from inward orientation to outward strategies has generated euphoria in

the stock market. Hence the opening up of the economy has been successful in

Price Per

Barrel

Inflation

rates

Price Of

Gold Per

Ounce

Per Dollar

Price

Cashreserve

ratio rates

Foreign

Exchange

reserves(Rs.)

Stock Prices


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spreading its tentacles over the economy. There are several factors which are directly

or indirectly related to stock prices. Here while observing stock market behaviour we

have taken into consideration Bombay Stock Exchange sensitive index (BSE) in our

database.

Due to the asymmetric information community companies and investors involved in

share Market are not aware of the information for Trading. The choice under

uncertainty has led to the issue of moral hazards in the capital markets. This research

tries to examine the interrelationship between different determinants affecting

Bombay Stock Exchange (BSE) in India. I considered the following determinants Oil

prices, Gold price, Cash Reserve Ratio, Food price inflation and Foreign Exchange

Reserves (Forex). Secondly the paper examines the financial stability of the company

using various fundamental parameters such as Financial stability ratios, Performance

indicators and Valuation parameters. Thirdly, technical techniques such as regression

and correlation have been used to predict the share prices of the company. I have

taken various factors such as Earning price per share, Market capitalization and P/e

ratio of the company which affect the closing price of the shares. The data taken for

BSE is quarterly i.e. from 2005-12, the data taken for the company`s fundamental

analysis is from 2007 to 2012 and the data taken to predict stock is monthly i.e. from

2009-12.

The paper is divided into two sections. In section one fundamental analysis has been

done to verify the growth of the company. In the second section technical analysis has

been carried out to analyze the crucial determinants of stock prices and predict the

share prices of the company.

The prices of oil and the stock market works in opposite direction, with the increase inoil price leads to the decrease of the return in the Indian stock market, likewise

decrease in oil prices leads to the increase in the return of Stock market. The great

decline of the oil prices is not the major cause of the Stock market clashes. Our profit

depends on the share which we are looking for. If the oil prices increase we can

switch over to other energy stocks. The most suffering countries in the oil price will

be the America. The world oil market is sgold and bought in terms of dollar, so if a

country wants to buy she has to change their currency to dollar first.


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There can be a great advantage for the investors regarding the oil price increase , if he

buys one barrel of oil for 30 dollar after few months if he price increases to 50 dollar

per barrel .So ,it shows that if he sells he will earn a profit of 20 dollar per barrel

,which will be great profit for the investor. Besides it is noted that daily oil

consumption will increase and since the largest oil producing countries Saudi Arabia

nearly meet its end it might be a great chance to buy shares in this sector.

CRR is Cash Reserve Ratio. It refers to keeping a portion of net demand and time

liabilities (NDTL) of banks with the central banks (In India its Reserve Bank of

India, RBI). Central bank fixes this percentage of NDTL. Central bank can change

this percentage as a monetary measure to control the availability of funds in the

economy i.e. to inject liquidity or to suck liquidity. RBI doesnt pay any interest on

such funds held with it.

The following are the demand liabilities of banks. Banks should pay these liabilities

on demand which may come at any time.

All liabilities which are payable on demand; they include current deposits, demand

liabilities portion of savings bank deposits, margins held against letters of

credit/guarantees, balances in overdue fixed deposits, cash certificates and

cumulative/recurring deposits, Demand Drafts (DDs),unclaimed deposits, credit

balances in the Cash Credit account and deposits held as security for advances which

are payable on demand.

Time Liabilities are those which are payable otherwise than on demand; they include

fixed deposits, cash certificates, cumulative and recurring deposits, time liabilities

portion of savings bank deposits, staff security deposits, deposits held as securities for

advances which are not payable on demand and Gold Deposits.

When a central bank increases CRR, the banks need to reduce the outflow of money

by reducing the loans to customers and keep additional amount with the central bank


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Inflation is a rise in prices of several items over a period of time. It is measured

through various indices and each provides specific information about the prices of

items that it represents. The index could be the Wholesale Price Index (WPI) or the

Consumer Price Index (CPI) for specified categories of people like agricultural

workers or urban non-manual employees. Each of the indices is created in a specific

manner with a certain year as the base year and they consider the price change over a

year. To tame inflation, the government usually hikes interest rates. This tends to

make debt instruments attractive relative to equities as the former carry a lower risk

(small savings instruments are risk free as they are guaranteed by the government).

This results in some amount of investments shifting from equity to debt. However,

high inflation is not always bad and low inflation need not always be good for equity

markets, as the impact will differ for companies and sectors across different time

horizons. The first thing to consider is the items where prices are rising. For example

a rise in oil prices will impact a wide range of items from food products to those that

require transportation.


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Chapter 2- Review of the literature

The nature of equity market in India has undergone profound change over the last 20

years. This affects 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 arge 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. It is usually done through the means of direct financing by security and

investment. The investment markets classically classified as Primary market and

Secondary market. Stock market is one of the major economic reflectors. Indian

economy is currently emerging as a global super power. The research paper by

(Choudhuri, Bandyopadhyay, Roy and Ghosh, 2006) examines the interrelationship

between different determinants affecting Bombay Stock Exchange (BSE) in India. In

this paper we considered the following determinants Oil prices, Gold price, Cash

Reserve Ratio, Food price inflation, Call money rate, Dollar price, F D I, Foreign

Portfolio Investment and Foreign Exchange Reserve (Forex). It is a well known fact

that Dollar price or money exchange rate has a great influence on BSE Sensex. Our

research identifies the level of influence of dollar price on BSE Sensex. The oil price

of India is dependent on International Oil market. Any developing economy like India

is dependent on Oil price, so we tried to find out if oil price influences the BSE

Sensex. The strength and stability of the host countrys currency is measured by the

level and volatility of call money rates. Gold price is included in the model as anadditional variable, to examine whether gold price contain any additional significant


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relation with share price movements. Since gold has an asset value it works as an

important savings material. The technology transfer in terms of innovation and

inventions to the developing country like India in phase of Globalization in terms of

FDI and Foreign Portfolio Investment has an impact on the volatility in the BSE

Sensex. The macroeconomic stability of any developing economy is highly dependent

on food price inflation. Its impact on BSE Sensex can be analyzed. The potentials of

the economy are strengthened by the foreign exchange reserve which has some impact

on Stock market. The authors have impressively carried out the relationship between

BSE Sensex and the variables effectively. The relationship has to be analysed by

using softwares. In the research article by (Shah and Bhingarkar, 2007) stock data has

been analyzed in softwares such as excel & SPSS and predicted.. Data-acquisition

involves gathering signals from measurement sources and digitizing the signal for

storage, analysis and presentation on a PC. Analysis and prediction is very necessary

in todays market for the accurate utilization of funds at hand. Foranalysis, there has

to a proper system where in the required data is first acquired from the destination.

This data then needs to be analysed using any analysis model. Currently there are

many analysis models available in the market. These models are based on the past

behaviour of the stocks. However, it is seen that there is no model which predicts the

future behaviour of the stocks. For this reason, a model is developed which not only

analyses the stocks but also predicts its future behaviour based on the past conduct.

Next, in the paper by (Martikainen, 2008), he investigates which economic

dimensions of the firm are reflected in stock price behaviour in the Finnish stock

market. Twelve financial ratios are then selected to represent these four dimensions.

All the firms common series listed for the whole 1974-1986 period are included in the

empirical analysis. All of the dimensions above are found in the empiricalclassification pattern of ratios. On the cross-sectional level, profitability and financial

leverage are reported as determinants of stock price behaviour. Corporation growth is

merely connected to the risk of the common stock. Somewhat weaker results

concerning the association between stock price behaviours 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


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economies .The paper features a panel data approach to analyze the relationship

between dividend-retention ratio and stock-price behaviour 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 possible

links between dividend policy and stock price behaviour 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 behaviour in Indian corporate sector for the same period. Stock market has

been considered volatile in nature. The research paper by (Raju and Ghosh, 2009)

examines the volatility of Indian stock market as compared to other markets.

Volatility estimation is important for several reasons and for different people in the

market. Pricing of securities is supposed to be dependent on volatility of each asset. In

this paper they not only extend the study period of the earlier paper but also expand

coverage in terms of number of countries and statistical techniques. Mature markets /

Developed markets continue to provide over long period of time high return with low

volatility. Amongst emerging markets except India and China, all other countries

exhibited low returns (sometimes negative returns with high volatility).

Comparatively, Indian market shows less of skewness and Kurtosis. Indian markets

have started becoming informationaly more efficient. Contrary to the popular

perception in the recent past, volatility has not gone up. Intraday volatility is also verymuch under control and has came down compared to past years. The hypothesis of

this research include the study of fundamental and technical analysis. The research

article by (Venkatesh and Tyagi), 2011 tends to figure out the use of fundamental and

technical analysis. The paper reports the results of a questionnaire survey in

September, October/November 2010 on the use of Fundamental and Technical

analysis by brokers/fund managers in Indian stock market to form their forecasts of

share price movements. The findings of the research reveal that more than 85 percent

of the respondents rely upon both Fundamental and Technical analysis for predicting


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future price movements at different time horizons. This paper envisages on different

trends of the stock market and it relates the trends towards the usage of Fundamental

and Technical analysis. The results show that when the market is bullish participants

rely more upon Technical analysis and when the market is bearish it is the other way

round the participants rely upon the Fundamental analysis.

This paper gives special emphasis on the usage of these tools while taking positions

in Large Cap, Mid cap and Small Cap companies. For this purpose various companies

across the sectors were chosen, which includes, Banking, Information Technology,

Manufacturing, Pharmacy etc. The study covers different Organizational set ups such

as, Licensed Broking firms, Licensed Banks, Mutual Fund Companies, Equity

research firms and others. The study was conducted in all major Indian cities by

serving a structured questionnaire to individuals such as, Directors, Fund Managers,

Research Analysts, Senior Brokers, Junior Brokers, Portfolio managers and others. In

relation to the research to predict stock price, the research paper by (Abirami and

Vijaya, 2009) state that stock price prediction depends on various factors such as

fundamental, technical and technological. Prediction of the stock price is an important

issue in finance. Since the predicted value is used decide whether to buy or leave the

share. The Stock price prediction is time varying and depends upon its past

information. It is used to determine the future value of a company stock or other

financial instrument traded on a financial exchange. The successful prediction of a

stock future price could yield significant profit. Also since the stock price varies every

day, stock price forecasting is a challenging and important task. Hence an efficient

automated prediction system is highly essential for stock forecasting. In this paper

online support vector regression is employed for predicting the stock price, as it is

required to incrementally learn the daily updates effectively without relearning the

historic data again. The stock data for the period of four years has been collected and

trained using OSVR with c and epsilon parameter settings. The performance of the

trained model is evaluated and found that the online support vector regression model

produced 96% accuracy with threshold. Next, the research paper by (Higgins, 2009)

develops a stock price prediction model based on quarterly earnings forecasts. The

prediction model is based on the residual income model by Ohlson (1995), and

adjustment for auto-correlation by Higgins (2009). Prior research has not used


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quarterly data out of concern for seasonality, however seasonality can be removed by

including four consecutive quarterly terms of abnormal earnings in each price

equation. The prediction results suggest that quarterly earnings forecasts can be useful

inputs to models of price forecasts. Several research papers have identified

determinants of stock prices. In contrast to it, the research article by (Balke, 2010)

shows that the data has difficulty distinguishing between a stock price decomposition

in which expectations of future real dividend growth is a primary determinant of stock

price movements and a stock price decomposition in which expectations of future

excess returns is a primary determinant. The inability of the data to distinguish

between these very different decompositions arises from the fact that movements in

the price-dividend ratio are very persistent while neither real dividend growth nor

excess returns are. From a market fundamentals perspective, most of the information

about low frequency movements in dividend growth and excess returns is contained in

stock prices and not the series themselves. As a result, the data is incapable of

distinguishing between the two competing decompositions. He further shows that this

inability to identify the source of stock price movements is not solely due to poor

power and size properties of our statistical procedure, nor is it due to the presence of a

rational bubble. Another aspect of the research aims at examining the stock market

efficiency and price tend which is examined by the research paper by (Gupta, 1990).

The study is aimed at testing the appropriateness of the random walk model 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. The research paper by (Janall, 2009) provides support to

it. It analyzes serial correlation in stock returns, and informational role of volume andvolatility 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 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. Also, the research article by (Sunitha, 2007) examines

that over the past few years, many firms have announced significant number of stock

repurchases. The overwhelming reason given for stock repurchase announcements has


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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 signalling effect of stock repurchase and dividends

announcements. This paper investigates and tests the following: 1) Signalling effect of

a share buy - back and dividend announcements 2) The market reaction and share

price behaviour 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 signalling 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

signalling power of stock repurchases announcements and that the market reacts more

favourably to repurchases compared to dividend announcements. Prediction of stock

prices can also be done on the basisi of fundamental analysis. The research paper by

(Elleuch, 2009) examines whether a simple fundamental analysis strategy based on

historical accounting information can predict stock returns. The papers goal is to

show that simple screens based on historical financial signals can shift the distribution

of returns earned by an investor by separating eventual winners stocks from losers.

Results show that historical accounting signals can be used to improve the entire

distribution of future returns earned by an investor. In fact, despite the overall downactivity of the market over the sample period chosen, results reveal that fundamental

accounting signals can be used to discriminate from an overall sample generating

future negative returns of -0,116 a winner portfolio that provide positive future return

of 0,019 from a loser one generating a negative return of -0,229. The over-

performance of the winner portfolio seems to be attributable to the ability of the

fundamental signals to predict future earnings. In fact, results show that fundamental

signals have a positive and significant correlation with future earnings performance

and that the winner portfolio have a future earnings realisation (0,100) that


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outperforms that of the loser portfolio (-0,012). Fundamental analyses also plays an

important role in arbitrage. The research paper by (Desai, Venkataraman and

Krishnamurthy, 2010) examines whether information arbitrageurs attempt to exploit

the return predictability in valuation and fundamental signals. Using a unique

database of short sell recommendations, we document that firm fundamentals, such as

magnitude of accruals, sales growth, gross margin, and SG&A expenses, and

valuation indicators, such as book-to-market ratio and return momentum, contain

valuable information correlated with the trading behaviour of short sellers. We show

that our empirical model explaining short seller recommendations is successful in

predicting both short interest and future returns for a broader sample in an out-of-

sample period. We present an important application of the model in distinguishing

between valuation and arbitrage motivated short selling. Overall, these findings

present additional insights into the decision process of short sellers and validate the

importance of fundamental analysis in the information arbitrage process. Also, the

research paper by (Das and Pattanayak, 2009)examines the various research studies

undertaken in the Indian and international context highlighting the effect of various

fundamental factors on the behaviour of the stock market. This paper tries to identify

the critical variables which have a significant effect on stock price movements and

influence the entire market's movement. The 30 shares constituting the Bombay Stock

Exchange-Sensitivity Index (BSE-SENSEX or SENSEX) are used as proxies to

capture the entire stock market's movement. Appropriate statistical techniques have

been used to establish a meaningful relationship among various explanatory variables

identified through the empirical analysis considering the available research studies.

The explanatory variables, which act as major determinants of stock price movements,

are condensed into a few critical factors by factor analysis and the relevance of thesefactors in influencing stock market movements is explained in detail. The analysis

shows that higher earning power, Returns on Investment (ROIs), growth possibility

and favourable valuation have a positive impact on the share price and stock market

movement, while higher risk and volatility have a negative impact. These factors can

be used as major analytical tools by investors, corporations and brokers to make

rational and intelligent investment decisions. Stock market is one of the most popular

investing places because of its expected high profit which is examined by the research

article by (Ravichandran, Thirunavukarasu, Nallaswamy and Babu, 2010).


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Traditionally, technical analysis approach, that predicts stock prices based on

historical prices and volume, basic concepts of trends, price patterns and oscillators, is

commonly used by stock investors to aid investment decisions. Advanced intelligent

techniques, ranging from pure mathematical models and expert systems to fuzzy logic

networks, have also been used by many financial trading systems for investing and

predicting stock prices. In recent years, most of the researchers have been

concentrating their research work on the future prediction of share market prices by

using Neural Networks. But, in this paper we newly propose a methodology in which

the neural network is applied to the investors financial decision making to invest all

type of shares irrespective of the high / low index value of the scripts, in a continuous

time frame work and further it is further extended to obtain the expected return on

investment through the Neural Networks and finally it is compared with the actual

value. The proposed network has been tested with stock data obtained from the Indian

Share Market BSE Index. The research shows the study of financial ratios of the

company which is explained by the research paper by (Nenide and Wisconsin, 2009).

The paper follows that a review of published research in the field of accounting and

finance reveals that the use of ratio calculations with multivariate analysis for

predicting the performance of business firms is common. However, much of this

research uses large database information without determining if needed sample

assumptions can be met for reliable conclusions to be drawn by the researchers. This

paper presents recommended adjustment techniques for researchers using large

databases for ratio calculation to allow for confidence that the results of analysis will

be meaningful and that inferences may be drawn from the data. Using a sample from

the Kauffman Center for Entrepreneurial Leadership Financial Statement Database,

Balance Sheet and Income Statement data of 250 firms is used to illustrate andexplain techniques for data error identification, handling the problem of denominators

being negative or approaching zero when calculating ratios, and effective techniques

for transforming the data to achieve approximation of normal distributions. The

application of these recommendations will allow researchers to use financial

statement data samples that will meet required characteristics for the use of valid

multivariate statistical analysis. The research is based on Bse index. The research

paper by (Verma, 2011) elaborates stock price indices are used extensively by

investors, brokers and portfolio managers as a general indicator of the stock market


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conditions. They are also used extensively in finance theory notably in

operationalizing the popular Capital Asset Pricing Model (CAPM). In recent years,

the indices published by the Bombay Stock Exchange (BSE) - the Sensitive Index

(Sensex) of 30 scrips in Bombay and the 100 share National Index (Natex) - have

become extremely popular with academics and practitioners alike. Anecdotal

evidence suggests that the Sensex is by far the more popular index among brokers and

lay investors while the Natex is the index of choice among mutual funds, professional

investors, foreign investment agencies and academics. This paper studies the two BSE

indices and their inter-relationship. The analysis in this paper indicates: Sensex is

more volatile than Natex, but this difference is accounted for by two factors - (a) the

autocorrelation of the Natex which conceals the true volatility of Natex, and (b) a

higher beta of Sensex relative to Sensex. Therefore, the excess volatility of Sensex is

not a matter of serious concern. In many applications, however, the higher beta of

Sensex is worrisome, but it is easy to correct for it. The conclusion, therefore, is that

those who follow the Natex because of its greater comprehensiveness and theoretical

appeal may be mistaken. The Sensex needs to be taken more seriously as a sound

market index. The observed deficiencies of the Natex raise several disturbing

questions for finance theorists and researchers. Prediction of stock is also the main

concern of this research. Therefore, in the research paper by (Sureshkumar and

Elango, 2010) , the authorstates forecasting accuracy is the most important factor in

selecting any forecasting methods. Research efforts in improving the accuracy of

forecasting models are increasing since the last decade. The appropriate stock

selections those are suitable for investment is a difficult task. The key factor for each

investor is to earn maximum profits on their investments. Numerous techniques used

to predict stocks in which fundamental and technical analysis are one among them. Inthis paper, prediction algorithms and functions are used to predict future share prices

and their performance will be compared. The results from analysis shows that isotonic

regression function offers the ability to predict the stock prices more accurately than

the other existing techniques. The results will be used to analyze the stock prices and

their prediction in depth in future research efforts.


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1.What is Fundamental Analysis?

The main goal of fundamental analysis is to find out intrinsic value of stock, means

primary assumption for fundamental analysis is that the price on the stock market

does not reflect the true value of stock (share). In a nutshell, focus of fundamental

analysis is to determine true value of stock by focusing on various factors like growth,

companys actual business, companys financial strength and its future prospects.

Attributes of fundamental analysis?

Fundamental analysis mainly in three parts:

1. Financial stability ratios

2. Performance indicators

3. Valuation parameters

1. Financial stability ratios:

These ratios are useful to check inherent financial strength of company and its cash

flow patterns.

a) Debt-Equity ratio:

This ratio provides leverage situation of company in the sense that it comparescompanys total liabilities to total shareholder equity.

b) Interest Coverage ratio:

This ratio indicates how easily can company pay interest on its outstanding debts.


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c) Current ratio:

Current ratio = Current Assets / Current Liabilities

This ratio indicates companys liquidity condition, in terms of paying of short-term

liabilities from its short-term assets.

2. Performance indicators:

These ratios are useful to check performance of the company.

a) Operating Margin:

Operating income indicates Earnings Before Depreciation, Interest and Taxes. This

ratio indicates net profitability of the operation of the business.

b) Net Margin:

Net Margin = Net Profit / Net Sales * 100

Net Profit is derived after depreciation and payment of interest and taxes. Higher the

margin better it is.

c) Return on Assets (ROA):


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This ratio indicates how profitable the company is relative to its assets and ability of

management in generating profits from assets.

d) Return on Equity (ROE):

Return on Equity = Net Income/Shareholder's Equity

This is perhaps Warren Buffets favourite parameter. This ratio provides percentage

return on shareholders equity.

e) Return on Capital Employed (ROCE):

ROCE = Net Profit / (Total Debt + Total Share Capital) * 100

This ratio indicates how profitable the company is relative to total capital employed

and ability of management in generating profit out of it.

f) EBIT Growth:

EBIT Growth = (This Years EBIT / Last Years EBIT 1) * 100

This ratio provides growth percentage in EBIT (Earnings Before Interest and Taxes)

term.

g) PAT Growth:

PAT Growth = (This Years PAT / Last Years PAT 1) * 100

PAT indicated Profit After Tax (Net Profit).

h) EPS Growth:

EPS Growth = (This Years EPS / Last Years EPS 1) * 100

EPS indicates Earnings Per Share.

i) BV Growth:


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BVPS indicates Book Value Per Share.

3. Valuation Parameters:

First of all, valuation ratios are related to CMP (Current Market Price). So, they are

quite volatile in general. As someone rightly said profits are made when you buy and

not when you sell, so in that regard valuations are key.

But in general, valuations have significance after particular stock is passed through

criteria of above two sections. (sometimes its easiest to ignore any scripts just on the

basis of valuations like, 100 PE stock with only around 15-20% growth)

a) PE:

Market Value per Share

Earnings per Share (EPS)

PE Price to Earnings, perhaps the most looked parameter. In general, stocks with

higher forecast earnings growth will have higher PE and those expected with lower

earnings growth will have lower PE.

b) P/B:


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P/BPrice to Book, very important ratio for value investors (historically, these groupof investors have made most money out of stock market).

c) Dividend Yield:

Dividend Yield = Dividend per share / CMP

This indicates dividend return in percentage terms of total investments.

d) PEG:

PEG = PE / Earnings Growth

PEGPE to Growth, Peter Lynchs parameter. This ratio provides relative values of

PE and growth projections.

2. Technical analysis

Technical analysis is all about studying stock price graphs and a few momentum

oscillators derived thereof. It must be understood that technical studies are based

entirely on prices and do not include balance sheets, P&L accounts ( fundamental

analysis ), the assumption being that the markets are efficient and all possible price

sensitive information is built into the price graph of a security / index. Therefore,

technical analysis supports the efficient market theory as against the

"random walk theory" which supports the belief that stocks can be bought / sold on

random events.

If the prices fluctuate ever often, is there a way to forecast them which is Technical

Analysis. It involves medley of science and art without any empirical formulae. It


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includes study of price charts and oscillators derived thereon. Capital management

techniques and no risk are the main elements of technical analysis.

The techniques that include in technical analysis and which were used in this study

are:

a) Regression analysis

b) Regression analysis is any statistical method where the mean of one or more

random variables is predicted based on other measured random variables. There are

two types of regression analysis, chosen according to whether the data approximate a

straight line, when linear regression is used, or not, when non-linear regression is

used.

A regression line is a line drawn through a Scatter plot of two variables. The line is

chosen so that it comes as close to the points as possible. Regression analysis, on the

other hand is more than curve fitting. It involves fitting a model with both

deterministic and stochastic components. The deterministic component is called the

predictor and the stochastic component is called the error term.

The simplest form of a regression model contains a dependent variable, also called the

"Y-variable" and a single independent variable, also called the "X-variable".

b) Karl Pearson Coefficient of Correlation

Pearson's correlation coefficient between two variables is defined as thecovariance ofthe two variables divided by the product of theirstandard deviations

c) Moving Averages
http://en.wikipedia.org/wiki/Covariancehttp://en.wikipedia.org/wiki/Standard_deviationshttp://en.wikipedia.org/wiki/Standard_deviationshttp://en.wikipedia.org/wiki/Covariance


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A simple, or arithmetic, moving average that is calculated by adding the closing price

of the security for a number of time periods and then dividing this total by the numberof time periods. Short-term averages respond quickly to changes in the price of the

underlying, while long-term averages are slow to react.

3.1 Purpose Of The Study

The research is undertaken for Kotak Mahindra Bank Ltd. It aims at three main

objectives:

1. To analyze the growth of the KOTAK Mahindra Bank Ltd. using fundamental

analysis.

2. To identify and analyze the stock market and crucial factors that contribute to rise and

fall in stock prices over a period of time.

3. To predict and forecast the stock market based on technical techniques.

The purpose of the study focuses on growth of Kotak Mahindra Bank Ltd. and in

addition, to identify the crucial factors which affect the rise and fall in stock prices

BSE. The study also focuses on forecast of share prices of the company for the month

May 12, June 12 and July 12.


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3.2 Research Design

Research designis considered as a "blueprint" for research, dealing with at least four

problems: which questions to study, which data are relevant, what data to collect, and

how to analyze the results.

The research conducted was an exploratory as well as a descriptive research as it

focuses on specific hypothesis and it is also conclusive. The information needed for

the research was more of quantitative in nature which included data regarding BSE

and variables such as gold prices, oil prices, dollar prices.........etc. The information

was collected through reading various research papers, archives and case studies. The

data used was secondary data. The method used for collecting data was direct

observation. Collected data was analysed using Spss and Ms excel. The research is

divided into 2 sections. The first section consists of fundamental analysis of the

company and second section consists of technical analysis of the stock of the

company.

3.3 Research Questions

The research questions were regarding the company itself:

-How has KOTAK grown in terms of stock market in the past years ?

- What will be the future market prices of the shares of the company ?

- What are the crucial factors that determine the rise and fall in the stock prices of

BSE?

3.4 Data Collection, Instruments And Analysis


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The data was collected through direct observation of the sources such bank archives,

internet and case studies. The source for each data has been mentioned in the report.

The data analysis was done on SPSS and Ms excel . The data analysis used techniques

like fundamental analysis of Financial stability ratios, Performance indicators and

Valuation parameters and technical analysis which included regression, correlation,

factor analysis and moving average forecast.

3.5 Limitations

The research included the following limitations:

The data included data over a period of 7 years. Hence the data would not be 100%

accurate

The data analysis includes ratio analysis which is subjected to historical data.

The prediction and conclusion of the research is feasible only if management works

effectively and efficiently.

Future uncertainties and crisis were not taken into the while conducting the research.

Stock prices keep on changing day by day. Hence the research does not give the exact

value but a rough idea about the companysstock.

.


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Chapter 4-Data analysis and interpretation

4.1 Analysis and interpretation for 1st objective

The first objective aims at analysis of Kotak Mahindra Bank Ltd. by using

fundamental techniques. The objective focuses to analyze the growth of the company

in the past 6 years.

The analysis involves calculation and examination of the Financial ratios, Valuation

parameters and performance standards which conclude that the company has grown in

the market.

Table 1 Ratios for the years 2007-2012

Particulars

Mar-

12

Mar 20

11

Mar 20

10

Mar 20

09

Mar 20

08

Mar 20

07

Operational & Financial

Ratios

Total Debt/Equity(x) 0.06 0.07 0.09 0.06 0.10 0.07

I nterest Coverage ratio: 1 1.00 1.00 1.00 1.00 1.00

Current Ratio(x) 0.87 0.59 0.52 0.58 0.56 0.62

Earnings Per Share (Rs) 13.7 11.10 16.12 7.99 8.53 4.33

DPS(Rs) 0.6 0.50 0.85 0.75 0.75 0.70

Book NAV/Share(Rs) 107.3 92.23

128.83 110.33 102.58

50.08

Performance Ratios

Operating Profit

Growth 42.87 41.98 54.79 22.31

-

709.54 450.97

Net Profit Growth 44.32 45.82

103.23

-6.07

107.92

19.57

BVPS Growth 16.3 -28.41 16.77 7.56 -97.95 81.65

Advances Growth 32.55 41.18 24.96 6.90 42.37 72.08

EPS Growth(%) 32.7 -31.11

101.79

-6.34 96.75 13.39

ROA(%) 1.9 1.85 1.70 0.97 1.22 0.94ROE(%) 15.05 14.50 13.52 7.51 11.37 11.37


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ROCE(%) 8.34 7.35 6.68 6.92 7.08 6.00

Valuation ParametersPER(x) 48.54 41.14 23.24 17.71 36.85 55.33

PCE(x) 43.08 36.73 40.05 28.30 62.83 88.83

Price/Book(x) 3.56 4.95 5.81 2.56 6.13 9.58

Yield(%) 0.12 0.11 0.11 0.27 0.12 0.15

Table 1 shows the three parameters to analyze the growth of Kotak Mahindra Bank

Ltd. The data have been calculated for the past 6 years starting from 2007 to 2012.

The ratios above have been calculated through the following approach:

Based on Operational and financial ratio:

Debt equity ratio of the company signifies proportion of equity and debt the companyis using to finance its assets.

The debt-equity ratio of the company for 6 years i.e. from 2007 to 2012 is less than.10 which indicates that a lot of debt has not been used to finance increased operations

(high debt to equity), the company. The company has been able to maintain more of

equity than liabilities which is a good sign.

The interest coverage ratio is calculated by dividing a company's earnings beforeinterest and taxes (EBIT) of one period by the company's interest expenses of the

same period:

An interest coverage ratio below 1 indicates the company is not generating sufficient

revenues to satisfy interest expenses.

The interest coverage ratio comes to be greater than 1 for 6 years for the company.

Hence the company is able to generate sufficient revenues in order to meet the interest

expenses.

A liquidity ratio that measures a company's ability to pay short-term obligations.

A ratio under 1 suggests that the company would be unable to pay off its obligations if


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they came due at that point. While this shows the company is not in good financial

health, it does not necessarily mean that it will go bankrupt - as there are many ways

to access financing.

The company`s current ratio is less than 1 for the past 6 years i.e. from 2007-2012.

Therefore the company needs to work to increase its current ratio. However the

company is not going to be bankrupt as other financial parameters are in favour of the

company.

A ratio used to measure a company's pricing strategy and operating efficiency.

Operating margin is a measurement of what proportion of a company's revenue is left

over after paying for variable costs of production such as wages, raw materials, etc.

Operating margin gives analysts an idea of how much a company makes (before

interest and taxes) on each rupee of sales. If a company's margin is increasing, it is

earning more per dollar of sales. The higher the margin the better.

Since, the growth operating profit for the company has been high since 2008, it shows

that the company has been earning well. It indicates that every rupee has been earning

well for the company.

Net Profit Growth

A ratio of profitability calculated as net income divided by revenues, or net profits

divided by sales. It measures how much out of every dollar of sales a company

actually keeps in earnings.

A higher profit margin indicates a more profitable company that has better control

over its costs compared to its competitors.

The company`s net profit growth has been exceptionally great except for 2009 which

is -6.07.Hence the company`s net profit to its sales relation has been impressive

which eventually indicates financial stability.

Return On Asset


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An indicator of how profitable a company is relative to its total assets. ROA gives an

idea as to how efficient management is at using its assets to generate

earnings. Calculated by dividing a company's annual earnings by its total assets, ROA

is displayed as a percentage. Sometimes this is referred to as "return on investment".

The company`s ROA for the years 2007-12 have been upto 2% which is not

impressive. The major reason would be the company is a service based company.

However there has been growth in the ROA over the years which implies good

condition of the company.

Return On Equity

The amount of net income returned as a percentage of shareholders equity. Return on

equity measures a corporation's profitability by revealing how much profit a company

generates with the money shareholders have invested.

The ROE for the company has been increasing since 2007 which states that the

company has been generating good returns on the shareholders wealth. It was nearly

8%, in 2009, but it rose to 15% approx. By 2012 it has been able to maintain its ROE

at 15%. Hence the company has been able to generate sufficient earnings on

shareholders wealth.

Book Value per Share

While book value of equity per share is one factor that investors can use to determine

whether a stock is undervalued, this metric should not be used by itself as it only

presents a very limited view of the firm's situation. BVPS provides a snap shot of a

firm's current situation

The company`s book value per share growth has been low in 2009 and 2010.However the rates have been significant in 2007, 2008, 2011 and 2012 which shows

that the company increased its book value in those years.

Earnings per Share Growth

The Eps growth rate has been positive for the company in 2008 and 2010 with an

impressive figure of over 90%. However the rate jumped to negative in 2007 and

2011. If we analyze the Eps for the years, it has been positive and in good figures as

seen in the table.


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P/E ratio

A valuation ratio of a company's current share price compared to its per-share

earnings.

In general, a high P/E suggests that investors are expecting higher earnings growth in

the future compared to companies with a lower P/E.

The P/E ratio for the company has been above 20 in most of the years which implies

that investors are ready to pay Rs. 20 for every 1 rupee of earning in the company. Itis the most looked parameter for an investor before investing in a company. P/e Of the

company has been increasing since 2007 which indicates that investors have been

getting increased earnings for the past 6 years.

P/B Ratio

A ratio used to compare a stock's market value to its book value. It is calculated bydividing the current closing price of the stock by the latest quarter's book value per

share.

A lower P/B ratio could mean that the stock is undervalued. However, it could also

mean that something is fundamentally wrong with the company. As with most ratios,

be aware that this varies by industry.

Since the P/b ratio of the company is higher than 1 in all the 6 years i.e. from 2007 to

2012, it indicates that the company`s stock is not undervalued.

The dividend yield(%) indicates how much the company is able to pay as dividend

to its investors.

The yield is greater than 10% for the past 6 years. Hence the company has been able

to earn sufficient profits. It also indicates that the company has been able to provide

its investors with regular dividend.


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4.2 Analysis and interpretation for 2nd objective

Table 2 Quarterly Data of Close Price and variables for the years 2005-12

YEAR CLOSEPRICE

Priceper

barrel(

USD)

CrrRATES

(%)

Inflation Rates

DollarPrice(

INR)

Forex Rs.(in crores)

Gold Per 1ounce( Rs.)

Q1

2005

6492.82 49.707 0.05 0.0417 43.58 6,20,943 18667

Q2

2005

7193.85 53.043 0.05 0.0332 43.71 6,08,413 19005

Q3

2005

8634.48 63.080 0.0525 0.0364 43.94 6,32,778 20806

Q42005

9397.93 60.033 0.0525 0.0533 45.97 6,50,909 23090

Q1

2006

11280 63.347 0.05 0.0457 44.35 6,49,253 25937

Q2

2006

10609.3 70.530 0.0525 0.0728 46.19 7,49,007 28246

Q3

2006

12454.4 70.443 0.05 0.064 46.38 7,65,218 27521

Q2006 13786.9 60.093 0.0525 0.0595 44.5 7,85,931 27972Q1

2007

13072.1 58.130 0.06 0.0672 44.11 8,64,573 28763

Q2

2007

14650.5 64.970 0.0625 0.0569 40.27 8,65,300 26493

Q3

2007

17291.1 75.500 0.07 0.064 40.63 9,41,247 29607

Q4

2007

20287 90.850 0.075 0.0552 39.39 10,79,243 32862

Q1

2008

15644.4 97.953 0.075 0.0788 40.33 12,31,832 37452

Q2200

8

13461.6 123.963 0.0775 0.077 42.38 13,42,380 40024

Q3

2008

12860.4 117.983 0.09 0.0977 43.25 13,50,213 41541

Q4

2008

9647.31 58.370 0.055 0.1045 49.94

11,98,239 42374


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Interpretation of Table 2:

Table 2 shows the quarterly historical data for BSE, Price of oil per barrel, Cashreserve ratio rates, Inflation rates, Value of a dollar in INR, Foreign exchange reserves

and Value of Gold per ounce from the year 2005 to 2012 .In order to analyze the

relationship between BSE and the variables, correlation technique and regression

analysis have been used in SPSS which gave the following results:

Q1

2009

9708.5 42.960 0.05 0.0803 51.88 12,73,257 47514

Q2

2009

14493.8 59.543 0.05 0.0929 46.96 12,68,147 44767

Q32009 17126.8 68.203 0.0525 0.1165 49.03 13,53,607 47901

Q4

2009

17464.8 76.067 0.05 0.1351 46.27 13,28,189 50607

Q1

2010

17527.8 78.627 0.055 0.1486 46.14 12,66,569 49915

Q2

2010

17700.9 77.890 0.0575 0.1372 47.95 12,73,921 57778

Q3

2010

20069.1 76.167 0.06 0.0981 46.81 13,24,937 58730

Q42010 20509.1 85.027 0.0625 0.0833 45.34 13,38,638 62847

Q1

2011

19445.2 93.980 0.06 0.0882 44.94 13,68,708 64172

Q2

2011

18845.9 102.553 0.055 0.0863 44.84 13,95,599 67300

Q3

2011

16453.8 89.710 0.055 0.1005 46.08 15,42,878 79339

Q4

2011

15454.9 94.063 0.0525 0.0934 53.36 15,84,605 81304

Q1

2012

17404.2 102.893 0.055 0.0689 49.27 14,97,000 85460

Q22012

16718.9 103.890 0.0525 0.0755 55.6 15,99,800 87504


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Table 3 Correlation of Stock Prices and variables

Correlations

CLOSE

Price per

barrel

Crr

RATES(%)

Inflation

Rates

Dollar

Price(

INR)

Forex

Rs.( in

crores)

Gold Per

1 ounce(

Rs.)

CLOSE Pearson

Correlation

1 .553** .288 .520

** .000 .675

** .629

**

Sig. (1-tailed) .001 .062 .002 .499 .000 .000

N 30 30 30 30 30 30 30

Price per

barrel

Pearson

Correlation

.553** 1 .631

** .258 -.037 .651

** .565

**

Sig. (1-tailed) .001 .000 .084 .424 .000 .001

N 30 30 30 30 30 30 30

Crr RATES(%) Pearson

Correlation

.288 .631** 1 .034 -.540** .217 -.061

Sig. (1-tailed) .062 .000 .430 .001 .125 .374

N 30 30 30 30 30 30 30

Inflation Rates Pearson

Correlation

.520** .258 .034 1 .357

* .677

** .519

**

Sig. (1-tailed) .002 .084 .430 .026 .000 .002

N 30 30 30 30 30 30 30

Dollar Price(

INR)

Pearson

Correlation

.000 -.037 -.540** .357

* 1 .478

** .625

**

Sig. (1-tailed) .499 .424 .001 .026 .004 .000

N 30 30 30 30 30 30 30

Forex Rs.( in

crores)

Pearson

Correlation

.675** .651

** .217 .677

** .478

** 1 .902

**

Sig. (1-tailed) .000 .000 .125 .000 .004 .000

N 30 30 30 30 30 30 30

Gold Per 1

ounce( Rs.)

Pearson

Correlation

.629** .565

** -.061 .519

** .625

** .902

** 1

Sig. (1-tailed) .000 .001 .374 .002 .000 .000


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N 30 30 30 30 30 30 30

**. Correlation is significant at the 0.01 level (1-tailed).

*. Correlation is significant at the 0.05 level (1-tailed).

Interpretation Of table 3:

Table 3 shows the correlation between the close prices of BSE Sensex and othervariables for every quarter from 2005 to 2012. The table shows that prices per barrel

of oil, inflation rates, forex and price of gold per ounce have a strong correlation with

the BSE. However factors like rupees per dollars and Crr rates does not have a strong

correlation with the dependent variable i.e. close price of BSE. The strongest relation

exist with forex and gold price per ounce with Karl Pearson correlation of .675 and

.629 respectively.

Table 4 Coefficient of Correlation

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .848a .719 .646 2387.07201

a. Predictors: (Constant), Gold Per 1 ounce( Rs.), Crr RATES(%),

Inflation Rates, Dollar Price( INR), Price per barrel, Forex Rs.( in

crores)

Interpretation Of table 4:

Table 4 shows the significance of R square, R and standard error of estimate. R

denotes that the factors have an overwhelming relationship with the dependent

variable i.e. close price. R square states that 72% of the variation in the close price is

explained by the factors. The deviation of actual y from predicted y comes to be2387.07201.


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Table 5 Annova Table

ANOVAb

Model Sum of Squares df Mean Square F Sig.

1 Regression 3.356E8 6 55939630.164 9.817 .000a

Residual 1.311E8 23 5698112.786

Total 4.667E8 29

a. Predictors: (Constant), Gold Per 1 ounce( Rs.), Crr RATES(%), Inflation Rates, Dollar Price(

INR), Price per barrel, Forex Rs.( in crores)

b. Dependent Variable: CLOSE

Table 6 Regression Table For Close Price and Variables

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 38103.354 11212.088 3.398 .002

Price per barrel -31.442 46.516 -.160 -.676 .506

Crr RATES(%) 330.400 1042.553 .082 .317 .754

Inflation Rates 427.656 241.902 .309 1.768 .090

Dollar Price( INR) -760.156 207.797 -.709 -3.658 .001

Forex Rs.( in crores) -.001 .006 -.092 -.201 .843

Gold Per 1 ounce( Rs.) .212 .084 1.090 2.537 .018

a. Dependent Variable: CLOSE


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Interpretation Of table 5 and table 6:

Table 5 shows that sig. Is .000 which tells that null hypothesis may be rejected as the

factors are strongly associated with the close price. Table 6 shows the inputs of

regression equation, Y= a+b(X1+X2+...+Xn)

Where,

Y= dependent variable i.e. close price

A=Constant

B= Unstandardized coefficient B

X=Independent variables

Table 3.2 shows the relationship between each variable and close price of BSE. Each

of the variable data can be used to forecast the close price.


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4.3 Analysis and interpretation for 3rd objective

The objective aims at forecasting Kotak Mahindra Ltd. Close prices for stock for the

month May 12, June 12 and July 12. The objective follows technical technique of

moving averages, correlation and regression to predict the close price of Kotak in

BSE. It uses monthly historical data of three variables i.e. P/E Ratio, Market

Capitalization and EPS of Kotak Mahindra Bank Ltd. from Jan 10 to Mar 12.

Table 7 Monthly historical data of stock prices of Kotak Mahindra Bank for the

years 2010-12

3-Month Moving

Average

YearHigh(

Rs.)

Low(R

s.)

Close(

Rs.)

P/E

Close

Mkt

Cap.

EP

SMkt. Cap.

Jan-

10439 372 389.95 98.25

27,112.

44

3.9

724449.33

Feb-

10398.75 350 371.05 93.52

25,806.

53

3.9

725733.23

Mar-

10407.5 361 374.53 46.32

26,077.

43

8.0

926114.49

Apr-

10398.35 353.18 368.9 45.64

25,693.

89

8.0

826332.13

May-

10394.95 354.33 378.35 46.83

26,369.

48

8.0

825859.28

Jun-

10424 365 385.4 47.72

26,869.

32

8.0

826046.93

Jul-

10399.13 372.5 384.63 47.68

26,847.

59

8.0

726310.90

Aug-10

438.88 386.4 414.28 53.86 30,325.76

7.69

26695.46

Sep-

10505.5 407.05 475.9 61.99

34,902.

51

7.6

828014.22

Oct-

10529.5 456 464.85 60.58

34,110.

69

7.6

730691.95

Nov-

10499.5 435.15 475.45 62.03

34,926.

56

7.6

633112.99

Dec-

10495 439.05 452.45 59.17

33,313.

89

7.6

534646.59

Jan-

11 463.95 371.2 384.5 50.29

28,313.

04

7.6

5 34117.05

Feb- 427.5 333.25 405.35 53.02 29,851. 7.6 32184.50


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11 60 5

Mar-

11463 405.45 456.85 41.14

33,663.

45

11.

1030492.84

Apr-

11 472.4 421.65 430.2 38.75

31,704.

88

11.

10 30609.36May-

11443.9 403.25 440.55 39.7

32,481.

75

11.

1031739.98

Jun-

11483.35 426 480.2 43.3

35,429.

16

11.

0932616.69

Jul-

11508.95 442.25 446.85 40.3

32,974.

85

11.

0933205.26

Aug-

11477.2 411.2 441.75 39.87

32,622.

35

11.

0833628.59

Sep-

11

485 435.55 459.65 41.533,951.

59

11.

08

33675.45

Oct-

11512.5 425 510.85 46.13

37,742.

62

11.

0733182.93

Nov-

11514.9 428.35 464.45 41.94

34,317.

28

11.

0734772.19

Dec-

11499.7 429.6 432.25 39.07

31,967.

48

11.

0635337.16

Jan-

12500 418.25 497.7 45

36,815.

86

11.

0634675.79

Feb-

12584.5 491.25 547.9 49.55

40,539.

12

11.

0634366.87

Mar-12

575.5 511 542.45 49.11 40,178.19

11.05

36440.82

Apr-

12603 531.2 583.05 52.79

43,190.

01

11.

0439177.72

May-

12552.024

2841302.44

Jun-

12555.077

5641556.88

Jul-

12560.592

3242016.44

Table 7 shows the forecasted close prices of Kotak Mahindra Bank Ltd for the months

May 12, June 12 and July 12. The forecast is done on the basis of regression analysis

in SPSS. The table shows that in May 12 the predicted close price of shares is

552.024, in June it is 555.077 and in July it is 560. 592.


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Calculation of predicted values:

Table 8 Correlation between close price and other variables

Correlations

Close Pe close Mkt Cap Eps

Close Pearson

Correlation

1 -.205 .995** .614**

Sig. (1-tailed) .147 .000 .000

N 28 28 28 28

Pe close Pearson

Correlation

-.205 1 -.247 -.846**

Sig. (1-tailed) .147 .102 .000

N 28 28 28 28

Met Cap Pearson

Correlation

.995** -.247 1 .647**

Sig. (1-tailed) .000 .102 .000

N 28 28 28 28

Eps Pearson

Correlation

.614** -.846** .647** 1

Sig. (1-tailed) .000 .000 .000

N 28 28 28 28

**. Correlation is significant at the 0.01 level (1-tailed).

Table 8 shows that the there is a strong linear relationship between the close price and

market cap of Kotak Mahindra Bank Ltd. Hence the independent variable here is the

market cap. The correlation is .995 which significant. However there is also strong

linear negative correlation between p/e ratio and Eps(earning price per share).


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Table 9 Correlation between Close Price and variables

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .995a .990 .990 5.78660

a. Predictors: (Constant), Met Capb. Dependent Variable: Close

Table 4.3 shows that 99% of the variation is explained by the independent variable

and standard error is also low i.e. 5.78660. Hence the relationship is strong and

regression analysis can be carried out effectively.

Table 10 Coefficient of Correlation

Coefficientsa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.B Std. Error Beta

1 (Constant) 56.395 7.694 7.329 .000

Met Cap .012 .000 .995 51.024 .000

a. Dependent Variable: Close

Table 4.4 shows the values of the variable and coefficients for the regression

equation:

Y= a+bx

Where,


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Y= dependent variable i.e. close price

A=Constant = 56.395

B= Unstandardized coefficient B = .012

X=Independent variable = market cap

Hence, the value of close price are predicted using the above values in the regression

formula.

Since the predicted values are increasing, it indicates that the close price of Kotak will

increase in the month of May, June and July for the year 2012.

4.4 Findings:

BSE Sensex is highly affected by several factors but there are certain factors whichsignificantly affect it. These factors were identified, inflation rate, foreign exchange

reserves , price of gold per ounce and price of oil per barrel.

The stock of Kotak Mahindra Bank Ltd. has a strong linear relationship with its

market capitalization and linear relationship with earning price per share. Hence the

market cap has been increasing for the company which indicates that the price of

shares would increase in the near future.

Kotak has been able to maintain its stability for the past 6 yrs in terms of financial

wealth and market survival. It has been able to maintain its growth.

The company`s financial evaluation points that except for current ratio and return on

assets, the company is financially stable.

The company`s shares price are able to satisfy its investors with good returns and

stability.

The stock of the company is not undervalued which makes it a grown company in the

market.


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The company tends to grow in terms of market in the future as its market

capitalization and p/e ratio increases.

Chapter 5-Conclusion and Recommendations

5.1 Summary Of findings

BSE Sensex is highly affected by several factors but there are certain factors which

significantly affect it. These factors were identified as price of oil per barrel, inflation

rates, foreign exchange reserves and price of gold per ounce.

The stock of Kotak Mahindra Bank Ltd. has a strong linear relationship with its

market capitalization and linear relationship with earning price per share. Hence the

market cap has been increasing for the company which indicates that the price of

shares would increase in the near future. Kotak Mahindra Bank Ltd. would grow in

terms of stock market based on technical analysis. The company has been able to

maintain its stability for the past 6 yrs in terms of financial wealth and market

survival. It has been able to maintain its growth. The company`s financial evaluation

points that except for current ratio and return on assets, the company is financially

stable. The company`s stock tend to increase in future as it is able to satisfy its

investors with good returns and stability. The company tends to grow in terms of

market in the future as its market capitalization and P/E ratio increases.


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5.2 Discussion of Research Questions

The research aimed at the following questions:

- How has KOTAK grown in terms of stock market in the past years?

- What will be the future market prices of the shares of the company?

- What are the crucial factors that determine the rise and fall in the stock prices?

The findings for the research have been able to answer the questions till a certain

extent subject to its limitations. Kotak Mahindra Bank has grown in terms of stock

market in the past 6 years. It has been able to maintain its stability and growth. The

main reason for its growth would be satisfaction of its investors and ability to survive

in the market. The research was able to predict the market prices of the company and

it was able to determine the crucial factors which affect the stock market and prices.

5.3 Recommendations

The company is financially stable but it has work on its current ratio and Return on

assets. The company should increase its current day to day operations to increase its

current assets.

Asset management should be the concern of the company. A bank`s assets are loans,

insurance policies, investment of their clients and customers.

The stock market is highly volatile in India. Hence it cannot be predicted accurately

but there are certain factors that determine the price of stocks for a company. These

factors come to be P/E Ratio, Market capitalization rate and Earning per share.

The overall stock market is affected by certain factors.

The company should focus on increasing its sales by their services and products.

The positive point is that the company has been able to satisfy its investors.


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The more the P/E ratio is more is the ability of the company to grow in the share

market. The less EPS is than the market price is better for the company`s stock.

When the market is bullish the company should rely on technical analysis of a stock

whereas when the market is bearish the company should go for fundamental analysis.

Reference Material

Sources:

http://www.x-rates.com/d/INR/table.html

http://ycharts.com/indicators/gold_price_in_indian_rupee

http://www.oecd.org/document/8/0,3746,en_2649_37439_40930184_1_1_1_37439,0

0&&en-USS_01DBC.html

www.indiainfoline.com

www.moneycontrol.com

www.rediff.com

www.yahoofinance.com

http://economictimes.indiatimes.com/kotak-mahindra-bank-ltd/fromdate-/todate-

/frequency-daily/arc-0/prices/companyid-12161,exchangeid-50,numberofdmw-

30,pagenumber-1,pagesize-25.cms

www.investopedia.com

Kotak Mahindra Bank Ltd. Annual Balance Sheet 2011-12 provided by the Bank.

www.financeglossary.com
http://www.x-rates.com/d/INR/table.htmlhttp://www.x-rates.com/d/INR/table.htmlhttp://ycharts.com/indicators/gold_price_in_indian_rupeehttp://ycharts.com/indicators/gold_price_in_indian_rupeehttp://www.oecd.org/document/8/0,3746,en_2649_37439_40930184_1_1_1_37439,00&&en-USS_01DBC.htmlhttp://www.oecd.org/document/8/0,3746,en_2649_37439_40930184_1_1_1_37439,00&&en-USS_01DBC.htmlhttp://www.oecd.org/document/8/0,3746,en_2649_37439_40930184_1_1_1_37439,00&&en-USS_01DBC.htmlhttp://www.indiainfoline.com/http://www.indiainfoline.com/http://www.moneycontrol.com/http://www.moneycontrol.com/http://www.rediff.com/http://www.rediff.com/http://www.yahoofinance.com/http://www.yahoofinance.com/http://economictimes.indiatimes.com/kotak-mahindra-bank-ltd/fromdate-/todate-/frequency-daily/arc-0/prices/companyid-12161,exchangeid-50,numberofdmw-30,pagenumber-1,pagesize-25.cmshttp://economictimes.indiatimes.com/kotak-mahindra-bank-ltd/fromdate-/todate-/frequency-daily/arc-0/prices/companyid-12161,exchangeid-50,numberofdmw-30,pagenumber-1,pagesize-25.cmshttp://economictimes.indiatimes.com/kotak-mahindra-bank-ltd/fromdate-/todate-/frequency-daily/arc-0/prices/companyid-12161,exchangeid-50,numberofdmw-30,pagenumber-1,pagesize-25.cmshttp://economictimes.indiatimes.com/kotak-mahindra-bank-ltd/fromdate-/todate-/frequency-daily/arc-0/prices/companyid-12161,exchangeid-50,numberofdmw-30,pagenumber-1,pagesize-25.cmshttp://www.investopedia.com/http://www.investopedia.com/http://www.financeglossary.com/http://www.financeglossary.com/http://www.finance

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