A

PROJECT REPORT

ON

“PERFORMANCE OF INITIAL PUBLIC OFFER"

AT

GURUKRUPA INVESTMENTS

BARDOLI.

SUBMITTED BY

KRUNAL.B.PATEL

06 MBA 33

GUIDED BY

MR.GOVIND DHINAIYA

MBA PROGRAMME

(YEAR 2006- 2008)

SHRIMAD RAJCHANDRA INSTITUTE OF

MANAGEMENT AND COMPUTER APPLICATION

DECLARATION

I, undersigned Mr.krunal .B. Patel, student of Shrimad Rajchandra Institute

Of Management & Computer Application, Bardoli, affiliated to Veer

Narmad South Gujarat University, Surat declare that report on

“PERFORMANCE OF IPO” is my own work. The research was carried out by

me as a part of summer training in the company for being evaluated for

the MBA degree.

Place:

Date:

__________

(Patel Krunal .B)

(06 MBA 33)

ACKNOWLEDGEMENT

I, the student of management, feel proud on successfully

completing the project on “PERFORMANCE OF IPO” at “GURUKRUPA

INVESTMENT” of Bardoli.

A project of this nature involves the support of many people. I

believe that I would be lacking in my duty if I did not express my sincere

gratitude to them.

I m heartily thankful to Mr. Nitin Prajapati for allow me to

undertake project work in his esteemed organization.

I would especially like to thank Mr. Paresh Patel, company

mentor, who has provides me the valuable guidance and support during

my training.

I am extremely thankful to Dr. Bankim Patel, director, and

Mr.Govind Dhinaiya, my project mentor for providing good guidance

and other facilities during my training program.

Krunal Patel

EXECUTIVE SUMMARY

This summer project report is prepared at Gurukrupa Investment Ltd.

Bardoli on “Performance of IPO” as a part of curriculum of the MBA

program.

I have selected this topic to measure the performance of IPO during

the period of 2004 – 2007. The performance is measured in terms of their

average return. Even I have tested that those IPO’s were efficient in

nature or not. The efficient market hypothesis states that it is not possible

to consistently outperform the market by using any information that the

market already knows, except through luck. Under the efficient market

hypothesis, any time you buy and sell securities, you’re engaging in a

game of chance, not skill. If markets are efficient and current, it means

that prices always reflects all information, so there are no way you will be

able to buy a stock at a bargain price.

Objectives:

To study the performance of IPO in India during 2004 -2007.

To evaluate top 5 IPO based on its performance (return).

To analyze likely trends of the price movement in IPO.

To analyze number of IPO’s were efficient.

To achieve these objectives, I have found out secondary data of closing

prices. These secondary data is gathered from various websites, majority

of data have been taken from NSE site. After collection of data I have

found out the logarithm return series of closing price, and derived top five

IPO’s. Then, I have applied RUN Test of Weak – form efficiency, which is

on the basis that no historical information is at all useful for the investors

to predict the future trend.

The hypotheses for RUNS Test are:

Null Hypothesis (HO) is the stock price series are random and the

alternative hypothesis (H1) is the stock price series are not random. I

have used SPPS software for the analysis.

Major Findings are:

Out of 55 IPO's 11 were not efficient i.e. there are not following random walk, so price of these 11 companies can be predicted using historical price movements. The technical analyst can get an abnormal return using these scripts.

For 44 companies the share prices are random it means that the Ho is accepted in these 44 companies so, these stocks can not be predicted by the historical price movements. Technical analyst not at all useful for predicting future trend.

We derived top 5 IPO’s on the basis of their average return of two year ended prices.

1. India Bulls - 50.4%

2. Tech.Mah. - 47.24%

3. Tulip - 36.38%

4. Shopper Stop - 34.55%

5. Provogue - 34.45%

We also come to know that those top 5 IPO’s who generate higher return are random in nature.

It was found that maximum number of IPO in list that does not follow randomness is from banking sector.

Thus my report conclude that majority of IPO’s (44) during the period

of 2004- 2007 were efficient in nature and the historical information is not

at all useful for predicting future trend while only 11 IPO’s are not efficient

so we can predict there future trend using the historical data.

INDEX

Chapter no. TOPIC Page no.

1 Industry profile 1

2 Company profile 5

3 Introduction 8

4 Research Methodology 20

5 Data analysis & Inferences 24

6 Findings 44

7 Conclusion 46

8 Recommendation 48

9 Bibliography 50

10 Annexure 52

INDUSTRY

PROFILE

INDUSTRY PROFILE

Capital Market:

The Capital market for financial assets which have a long or indefinite

maturity. Generally, it deals with long term securities which have a

maturity period of above one year. Capital market may be further divided

into three namely:

Industrial securities market

Government securities market

Long term loans market

(1) Industrial security market:

As the very name implies, it is a market for industrial securities namely

(1) Equity shares or ordinary shares, (2) Preference Shares (3) Debentures

or bonds.It is market where industrial concerns raise their capital or debt

by issuing appropriate instruments. It can be further subdivided into two.

They are,

(a)Primary market or New issue market

(b)Secondary market or Stock exchange

Primary market:

Primary market is a market for new issues or new or financial

claims. Hence, it is also called New Issue market. The primary market

deals with those securities which are issued to the public for the first time.

In the primary market, borrowers exchange new financial securities for

long-term funds. Thus, primary market facilitates capital formation.

There are three ways by which a company may raise capital in a primary

market. They are:

Public issue

Rights issue

Private placement

The most common method of raising capital by new companies is

through sale of securities to the public. It is called public issue. When

an existing company wants to raise additional capital, securities are

first offered to the existing shareholders on a pre-emptive basis. It is

called rights issue. Private placement is a way of selling securities

privately to a small group of investors.

Secondary market:

Secondary market is market for secondary sale of securities. In

other words, securities which have already passed through the new issue

market are traded in this market. Generally, such securities are quoted in

the stock exchange and it provides a continuous and regular market for

buying and selling of securities. This market consist of all stock exchanges

recognized by the government of India. The stock exchanges in India are

regulated under the securities contract (regulation) Act, 1956.the Bombay

stock exchange is the principle stock exchange in India which sets the

tone of the other stock market.

(2) Government Securities Market:

It is otherwise called Gilt- Edged securities market. It is market

where government securities are traded. In India there are many kinds of

government securities- short term and long-term. Long term securities

are traded in this market while short term securities are traded in money

market.

(3) Long – term Loans market:

Development banks and commercial banks play a significant role in

this market by supplying long term loans to corporate customers. Long-

term loans market may further divided into :

Term loans market

Mortgages market

Financial guarantees market

COMPANY

PROFILE

COMPANY PROFILE

Gurukrupa investment was setup in the year 2001 to serve the

investors, it offered stock broking in initial period.

It was within six months, it had become a ‘One step financial shop’

offering Insurance, Mutual Funds, D-mat, derivatives and commodities

apart from stock broking.

The business of Gurukrupa investment has three fold growths, touch

to the stock market become. Today in less than 4 years, it has more than

thousand countries in stock broking and close to three thousand in mutual

funds, it plans to provide research and portfolio analysis of clients

investment in mutual fund on its website. This would be a unique &

additional service, it plans to provide to customers.

VISION: we will become ‘One-Stop’ investment shop in our target

region by providing flowers transaction impeccable service, reliable

advice and unparallel reach.

OUR VALUES:

We shall go out of way to delight our customer’s- they are the

foundation of our business.

We shall focus on value addition through innovation in product,

process and technology.

We shall build team based organization by sharing knowledge and

empowering people.

We shall work with higher level of integrity and transparency.

We shall treat everyone with personal attention, honesty and

respect they deserve.

THEORETIC

AL

PERSPECTIV

E

About Topic

Initial Public Offer:

Corporate may raise capital in the primary market by way of an

initial public offer, rights issue or private placement. An Initial Public Offer

(IPO) is the selling of securities to the public in the primary market.

An IPO is defined as an exercise when an unlisted company makes

either a fresh issue of securities or an offer for sale of its existing

securities or both for the first time to the public.

The exercise refers the issue of shares to the public by the

promoters of the company. The shares are made available to the

investors at the face value of the share or with a premium as per the

perceived market value of the share by the promoters.

IPO’s can be a risky investment. For the individual investor, it is

tough to predict what the stock will do on its initial day of trading and in

the near future since there is often little historical data with which to

analyze the company. Also, most IPO’s are of companies going through a

transitory period, and therefore subject to additional uncertainty

regarding their future.

Why IPO?

The primary reason for a company going is to raise money, usually

for capital to fund growth of the business or to pay down existing debt.

Usually it is not possible to buy shares in a private company. A

potential investor can approach the owners, but they're not obliged to sell

any shares. However, public companies sell at least a portion of

themselves to the public and they also trade on stock exchanges.

Public companies have thousands of shareholders and are subject to

strict rules and regulations. They must have a board of director and they

must report financial information every quarter. Public companies are

regulated by governing bodies. The stock is traded in the open market

and any investor, who has got money, can invest in them. The CEO and

the owner can not prevent an investor from buying stock.

Going public provides an opportunity to raise cash for the

companies, while opening many financial doors as well. Public companies

can get better rates when they issue debts because of the increased

scrutiny involved. A public company can always issue more stock, as long

as there is market demand. Consequently, mergers and acquisitions

become easier to execute as stock can be issued as part of the deal.

Trading in the open markets also provides liquidity. This makes it

possible to implement things like employee stock ownership plans, which

help to attract top talent. Besides, being on a major stock exchange

carries a considerable amount of prestige. After all, an IPO is entirely a

sales job and if one can convince people to buy stock in the company, a

lot of money can be raised.

IPO Pricing:

Issue pricing is a complex exercise. Price is most important factor

for success of an IPO.

The market value of company’s share and the number of shares

outstanding influence the pricing decision. Setting of a right price is very

important to attract potential investors. A vary high price may make the

shares unaffordable for small investors. So the company may lose out on

many potential shareholders.

Indian primary market ushered in an era of free pricing in 1992.

Following this, the guidelines have provided that the issuer in consultation

with Merchant Banker shall decide the price. There is no price formula

stipulated by SEBI. SEBI does not play any role in price fixation. The

company and merchant banker however required to give full discloses of

the parameters which they had considered while deciding the issue price.

There are two types of issues one where company and Lead Manger(LM)

fix a price(call fix price) and other, where the company and Lead Manger

stipulate a floor price or a price band and leave it to market forces to

determine the final price(price discovery through book building process).

IPO price should be decided in two ways one is book building

method and another is fixed price method.

Fixed price offer:

An issuer company is allowed to freely price the issue. The basis of

issue price is disclosed in the offer document where the issuer discloses in

detail about the qualitative and quantitative factors justifying the issue

price. The Issuer company can mention a price band of 20% (cap in the

price band should not be more than 20% of the floor price) in the Draft

offer documents filed with SEBI and actual price can be determined at a

later date before filing of the final offer document with

SEBI/ROCs( Registrar of Companies).

Book Building :

It is a process undertaken by which a demand for the securities

proposed to be issued by a body corporate is elicited and built up and the

price for the securities is assessed on the basis of the bids obtained for

the quantum of securities offered for subscription by the issuer. This

method provides an opportunity to the market to discover price for

securities.

This process provides an opportunity to the market to discover price

for the securities on offer. In common words, book building is a method

for public offer of equity shares of a company. The process is named so

because it refers to collection of bids from investors, which is based on a

price range. The issue price is fixed after the closing date of the bid.

In the book building process, underwriting banks, in consultation

with institutional investors and the issuer, estimate a price band for the

stock to be put on sale. If there is oversubscription, allocations are now

made to institutional and retail investors as per quotas on a pro-rata

basis. Allocations in a fixed price IPO are mad on a purely pro-rata.

According to the book building process, three classes of investors

can bid for the shares:

Qualified Institutional Buyers: QIBs include mutual funds and

Foreign Institutional Investors. At least 50% of the shares are

reserved for this category.

Retail investors: Anyone who bids for shares under Rs.1, 00,000 is a

retail investor. At least 35% is reserved for this category.

The balance bids are offered to high net worth individuals and

employees of the company.

Difference between Book-building and Fixed

price offer of shares :

Feature

s

Fixed Price

process

Book Building process

Pricing Price at which the

securities are

offered/allotted is

known in advance to

the investor.

Price at which securities will

be offered/allotted is not

known in advance to the

investor. Only an indicative

price range is known.

Demand Demand for the

securities offered is

known only after the

closure of the issue

Demand for the securities

offered can be known

everyday as the book is built.

Payment Payment if made at

the time of

subscription wherein

refund is given after

allocation.

Payment only after allocation.

Efficient Market Hypothesis:

The Efficient market hypothesis (EMH) asserts that financial markets

are "informationally efficient", or that price on traded assets, e.g., stocks,

bonds, or property, already reflect all known information and therefore

are unbiased in the sense that they reflect the collective beliefs of all

investors about future prospects. Professor Eugene Fama at the University

Of Chicago Graduate School Of Business developed EMH as an academic

concept of study through his published Ph.D. thesis in the early 1960s at

the same school.

The efficient market hypothesis states that it is not possible to

consistently outperform the market by using any information that the

market already knows, except through luck. Information or news in the

EMH is defined as anything that may affect prices that is unknowable in

the present and thus appears randomly in the future.

Beyond the normal utility maximizing agents, the efficient market

hypothesis requires that agents have rational expectations; that on

average the population are correct (even if no one person is) and

whenever new relevant information appears, the agents update their

expectations appropriately.

Note that it is not required that the agents be rational (which is

different from rational expectations; rational agents act coldly and

achieve what they set out to do). EMH allows that when faced with new

information, some investors may overreact and some may under react. All

that is required by the EMH is that investors' reactions be random and

follow a normal distribution pattern so that the net effect on market prices

cannot be reliably exploited to make an abnormal profit, especially when

considering transaction costs (including commissions and spreads).

There are three common forms in which the efficient market hypothesis is

commonly stated — weak form efficiency, semi-strong form efficiency and

strong form efficiency, each of which have different implications for how

markets work.

Weak-form efficiency:

• No excess returns can be earned by using investment strategies

based on historical share prices or other financial data.

• There is no benefit-as far as forecasting the future is concerned-in

examining the historical sequence of prices

• Weak-form efficiency implies that Technical analysis techniques will

not be able to consistently produce excess returns, though some forms of

fundamental analysis may still provide excess returns.

• If there is no value in studying past prices and past prices changes,

there is no value in technical analysis.

• In a weak-form efficient market current share prices are the best,

unbiased, estimate of the value of the security. Theoretical in nature,

weak form efficiency advocates assert that fundamental analysis can be

used to identify stocks that are undervalued and overvalued. Therefore,

keen investors looking for profitable companies can earn profits by

researching financial statements.

• This weak form of the efficient market hypothesis is popularly

known as the random-walk theory.

Semi-strong form efficiency:

• The semi strong form of the efficient market hypothesis says that

current prices of stocks not only reflect all information content of

historical prices but also reflect all publicly available knowledge about the

corporations being studied.

• The semi strong form of the efficient market hypothesis maintains

that as soon as information becomes publicly available, it is absorbed and

reflected in stock prices.

• Even if this adjustment is not the correct one immediately, it will in

a very short time be properly analyzes by the market. Thus the analyst

would have great difficulty trying to profit using fundamental analysis

• Semi-strong form efficiency implies that Fundamental analysis

techniques will not be able to reliably produce excess returns.

• The semi strong form says that efforts by analysts and investors to

acquire and analyze public information will not yield consistently superior

returns to the analyst.

• Examples of the type of public information that will not be of value

on a consistent basis to the analyst are corporate reports, corporate

announcements, and information relating to corporate dividend policy,

forthcoming stock splits, and so forth.

Strong-form efficiency:

• The strong form of the efficient-market hypothesis maintains that

not only is publicly available information useless to the investor or analyst

but all information is useless. Specifically, no information that is available

is it public or “inside”, can be used to earn consistently superior

investment returns.

• Share prices reflect all information and no one can earn excess

returns.

• If there are legal barriers to private information becoming public, as

with insider trading laws, strong-form efficiency is impossible, except in

the case where the laws are universally ignored.

• To test for strong form efficiency, a market needs to exist where

investors cannot consistently earn excess returns over a long period of

time.

• To test the strong form of efficient market hypothesis, event more

indirect methods must be used. For the stronger form as has been already

mentioned, says that no type of information is useful. This implies that not

even security analysts and portfolio managers who have access to

information more quickly than the general investing public are able to use

this information to earn superior returns.

Random walk Theory:

Can a series of historical stock prices or rates of return be an aid in

predicting future stock prices or rates of return? This, in effect, is the

question posed by the random –walk theory.

The random walk hypothesis is a financial theory stating that stock

market prices evolve according to a random walk and thus the prices of

the stock market cannot be predicted. It has been described as 'jibing'

with the efficient market hypothesis. Investors, economists, and other

financial behaviorists have historically accepted the random walk

hypothesis. They have run several tests and continue to believe that stock

prices are completely random because of the efficiency of the market

Runs Test:

Runs test is used to find out whether the series of price movements

have occurred by chance or not. The runs test is a statistical technique

used to detect if a time series is random or not. It is a non-parametric test

so probability distribution of the series data need not be predefined.

One first forms the histogram of the difference between the two

histograms to be compared, or of the difference between the histogram

and the function to be compared, and then one counts the number of runs

in the difference. This numb er is then compared with that expected

under the null hypothesis, which is such that all orderings of sign are

equally probable ( Runs).

Runs test ignore the absolute values of the numbers in the series

and observe only their sign. The researchers then merely count the

number of runs-consecutive sequences of signs-in the same direction. For

example, the sequence - - - + 0 + has four runs. Next, the actual number

of runs observed is compared with the number that is to be expected

from a series of randomly generated price changes. It has been founds

that when this is done, no significant differences are observed. These

results the further strengthen the random work hypothesis.

The first step in the runs test is to compute the sequential

differences (Yi - Yi-1). Positive values indicate an increasing value and

negative values indicate a decreasing value.

The output shows a table of:

1. Runs of length exactly I for I = 1, 2, ..., 10

2. Number of runs of length I

3. Expected number of runs of length I

4. Standard deviation of the number of runs of length I

5. a z-score where the z-score is defined to be

Where,

is the sample mean and

S is the sample standard deviation.

The z-score column is compared to a standard normal table. That is,

at the 5% significance level, a z-score with an absolute value greater than

1.96 indicates non-randomness and Vice- Versa.

Data Distribution: The runs test is a non-parametric test, not assuming

the normal or any other particular distribution.

Research

Methodolog

y

Research Methodology:

Primary Objective:

To study the performance of IPO in India during 2004 -2007.

Secondary objectives:

To evaluate top 5 IPO based on its performance (return).

To analyze likely trends of the price movement in IPO.

To analyze number of IPO’s were efficient.

Research Benefits:

My research can help in following ways:

It provides answer to the question that whether one can predict the

prices of IPO's through historical price movements?

It helps to guide investor to take better decisions regarding their

investments.

It guides investors to go for the securities on the basis of there risk

appetite capacity.

Research Design:

Research design is the plan and structure of investigation so as to

obtain the answer to research questions. The plan is the overall program

of the research. It includes an outline of what the investigation will do

from writing the problems and their implication to final analysis of data.

I have used Descriptive Research Design, as I had try to describe

the situation of the selected IPO's whether there share prices are random

or not.

Data Collection Method:

I have used Secondary data Collection method.

Sample period:

I have taken the listed date price data and year ended data for all

IPO's. The duration consider between, 2004 – 2007.

Tools Used:

I have used SPSS (Statistical Package for Social Science) for RUNS

TEST.

Hypothesis:

In this study the hypothesis will be tested with the help of runs test.

Ho: The stock price series are random.

H1: The stock price series are not random.

Assumptions:

• Financial year consider 1st April to 31st march.

• Closing Price were consider for return findings.

DATA

ANALYSIS

&

INTERPRETATION

Data Analysis & Interpretation

Runs Test Results:

(1) Auto Sector:

Runs Test

TAC

Test Value(a) -.377358992100

Cases < Test Value 61

Cases >= Test Value 61

Total Cases 122

Number of Runs 67

Z .909

Asymp. Sig. (2-tailed) .363

Interpretation:

For analyzing the value of runs test we had taken a 5% significant

level. If Z value is 1.96<= than Ho is accepted i.e. there is random walk,

other wise alternative hypothesis is accepted.

In above table we can find Z value of TAC Scripts is less than 1.96

so we can say that there is random walk in this script and we cannot

predict those script trend using historical data.

(2) Aviation Sector:

Runs Test

Jet Airways Deccan

Test Value(a) -.189061219194 -.706716722309

Cases < Test Value 256 100

Cases >= Test Value 256 101

Total Cases 512 201

Number of Runs 247 111

Z -.885 1.344

Asymp. Sig. (2-tailed) .376 .179

Interpretation:

In the above table, we can say that as z values in both scripts are

less than 1.96 which accepts the Ho hypothesis i.e. there is random walk

prevails in the security prices.

(3) Banking Sector:

Runs Test

Maha - Bank

Orient Bank

Allahabad Bank

Dena Bank

YES Bank

Test Value(a) -.131319782496

-.108627547064

.00000000000

-.138792527485

-.06095702718

5Cases < Test Value

372 241 235 270 213

Cases >= Test Value

374 241 244 271 214

Total Cases 746 482 479 541 427Number of Runs 342 211 197 270 197Z -2.345 -2.827 -3.973 -.129 -1.696Asymp. Sig. (2-tailed)

.019 .005 .000 .897 .090

Interpretation:

From the above table we can interpret that the securities Maha.

Bank, Orient Bank, Allahabad Bank, are not accepting Ho hypothesis as

there Z value is more than 1.96, so we can conclude that there script

price movement will be predicted using historical data, where as the other

two scripts namely Dena bank and Yes bank are satisfying Ho hypothesis

so conclude that there are random walk in that security price movement.

(4) Construction Sector:

Runs Test

Parsvanath Akruti GMRTest Value(a) -

1.2881338534

-.831352125101

.405899623713

Cases < Test Value 40 17 75Cases >= Test Value 40 18 76Total Cases 80 35 151Number of Runs 28 16 70Z -2.925 -.682 -1.061Asymp. Sig. (2-tailed) .003 .495 .289

Interpretation:

In the above table we failed to accept null hypothesis for the

security Parsvanth b'coz its Z value exceeds 1.96, and other two scripts

Akruti and GMR are follows random walk which satisfy the Z value criteria.

(5) Energy Sector:

Runs Test

ONGC Petronet LNG

Gail IBP Cairn IPCL RPL

Test Value(a) .0887057492

88

0 .0000000000

00

-.017734879

008

-.067775337

248

.0835054990

29

-.148588437

442Cases < Test Value

376 378 385 387 27 387 111

Cases >= Test Value

376 378 389 387 27 387 112

Total Cases 752 756 774 774 54 774 223Number of Runs

387 373 391 370 26 375 95

Z .730 -.437 .217 -1.295 -.550 -.935 -2.349Asymp. Sig. (2-tailed)

.466 .662 .829 .195 .583 .350 .019

Interpretation:

In the above table the security RPL fails to accept the null

hypothesis as its Z value is more than 1.96. The remaining all other

scripts are accepts null hypothesis which means that they follows random

walk.

(6) Eng. Sector:

Runs Test

Punj Lloyd Patel eng

Test Value(a) .070655776841 -15.711019785747

Cases < Test Value 152 115

Cases >= Test Value 153 115

Total Cases 305 230

Number of Runs 149 155

Z -.516 5.154

Asymp. Sig. (2-tailed) .606 .000

Interpretation:

From the table above we can infer that the security Patel

Engineering didn’t match with the Z value criteria which rejects the null

hypothesis whereas the security Punj Lloyd accepts null hypothesis as its

Z value matches with desired criteria.

(7) Finance Sector:

Runs Test

India Bulls

IDFC IL & FS SMART

India Info line

M & M

Test Value(a) .211650792200

-.076238778822

-.025621832173

-.059281931578

.144901311352

Cases < Test Value

314 203 208 234 135

Cases >= Test Value

314 203 208 234 136

Total Cases 628 406 416 468 271Number of Runs 316 178 213 238 128Z .080 -2.584 .393 .278 -1.034Asymp. Sig. (2-tailed)

.936 .010 .695 .781 .301

Interpretation:

In the table given above we can derived that the security IDFC fails

to accept null hypothesis and all remaining securities in table accepts Z

value criteria which infer that there are random walk in this security

(8) Media Sector:

Runs TestNDTV PVR Shrin

gerUTV Sun

TVInox Jagra

nCinem-ax

Test Value(a) .064237785

373

-.217959981

667

-.117794836

271

-.087237203

474

.093006908

770

-.264257350

995

.000000000

000

.199042670

599Cases < Test Value

360 153 240 254 118 137 136 15

Cases >= Test Value

360 154 240 255 118 137 139 15

Total Cases 720 307 480 509 236 274 275 30

Number of Runs

353 152 249 276 126 147 136 22

Z -.597 -.286 .731 1.819 .913 1.089 -.300 2.044

Asymp. Sig. (2-tailed)

.551 .775 .465 .069 .361 .276 .764 .041

Interpretation:

In the above table only one company that is Cinemax has reject the

null hypothesis of randomness shows that the price of this company can

be predicted by the historical information as there is not random walk.

While other companies have accepted the null hypothesis means the

share prices of these companies are random.

(9) Pharma Sector:

Runs Test

Indoco Biocon

Test Value(a) -.166477526152 -.114099315718

Cases < Test Value 275 374

Cases >= Test Value 276 374

Total Cases 551 748

Number of Runs 294 349

Z 1.492 -1.903

Asymp. Sig. (2-tailed) .136 .057

Interpretation:

In the table given above we can interpret by using Z value that both

scripts prices are accepting null hypothesis so there are random walk in

there price movement.

(10) Power Sector:

Runs Test

NTPC Suzlon GVK Power Fin.cor

Info Edge

Test Value(a) .060295449520

-.007826553462

-.122980408348

-.419618816129

-.086206901891

Cases < Test Value

299 180 136 12 43

Cases >= Test Value

300 180 136 12 44

Total Cases 599 360 272 24 87Number of Runs 328 174 126 15 49Z 2.249 -.739 -1.336 .626 .972Asymp. Sig. (2-tailed)

.025 .460 .181 .531 .331

Interpretation:

In the table above the company NTPC fails to accepts null

hypothesis as its Z value criteria arte not matched, all reaming security in

table are accepting null hypothesis which shows that there are random

walk in that security price movement.

(11) Retailing Sector:

Runs Test

Piramyd Provogue

Shopper Stop

Emami

Test Value(a) -.43844447252

-.243384667386

.055830162497

-.241229256915

Cases < Test Value 164 164 232 81

Cases >= Test Value

164 164 232 81

Total Cases 328 328 464 162

Number of Runs 175 156 246 96

Z 1.106 -.995 1.208 2.207

Asymp. Sig. (2-tailed)

.269 .320 .227 .027

Interpretation:

In the table above the security Emami has rejected the null

hypothesis of randomness so we can infer from the Z value that we can

predict the price movement of that security using historical prices , all

other security are accepting null hypothesis which shows there are

random walk in that security.

(12) Shipping Sector:

Runs Test

Bharti Shipyard

Test Value(a) .12049645993Cases < Test Value 205Cases >= Test Value 206Total Cases 411Number of Runs 215Z .840Asymp. Sig. (2-tailed) .401

Interpretation:

In the above table, given the security Bharti shipyard matches the Z

value criteria , it means it accepts null hypothesis so we can infer that the

security prices are random.

(13) Software Sector:

Runs Test

TCS CMC Patni Computer

Tulip Prithvi

3i Infot

ec

Tanla

Tech Mah

First Sourc

e

Test Value(a)

.167619005805

-.01548373622

3

-.098723652

331

.004537834755

-.11904763310

8

-.08133388004

3

-.93439599764

7

.051367454998

.6265684658

93

Cases < Test Value

325 387 389 153 171 242 28 73 12

Cases >= Test Value

325 387 390 153 172 243 28 73 13

Total Cases 650 774 779 306 343 485 56 146 25

Number of Runs

329 374 374 167 186 250 9 75 16

Z .236 -1.007

-1.183 1.489 1.460 .591 -5.394

.166 .827

Asymp. Sig. (2-tailed)

.814 .314 .237 .137 .144 .555 .000 .868 .408

Interpretation:

In the table given above, Tanla fails to match with the Z value

criteria which means its failed to accept null hypothesis so we can predict

the security prices using historical data, where as rest of security are

matches with the Z value criteria so we can infer that those security

prices are random in nature.

(14) Textile sector:

Runs Test

House Perl

Test Value(a) -1.814108707065

Cases < Test Value 14

Cases >= Test Value 15

Total Cases 29

Number of Runs 12

Z -1.129

Asymp. Sig. (2-tailed) .259

Interpretation:

The security House Perl in the table matches with the criteria of Z

value so its accept null hypothesis which shows randomness of price

movement in the security.

Interpretation Of RUNS TEST

The results of Runs test shows that 11 out of total 55 IPO's have

statistically not significant Z value at 5% level. The lists of the companies

are given below:

The not significant stocks at 5% level are:

1. Bank of Maharashtra

2. Oriental Bank of Commerce

3. Allahabad Bank

4. Parsvnath Developers Ltd.

5. Reliance Petroleum Ltd.

6. Patel Engineering Ltd.

7. IDFC

8. Cinemax India Limited

9. NTPC

10.Emami Ltd.

11.Tanla Solutions

This analysis shows that we can reject the null hypothesis of

random walk in 11 out of 55 stocks form the total number of IPO's

list, it means that the stock prices series follow random has been

rejected. This shows that the share prices of these companies could

be predicted using historical information. Investors can be benefited

from the historical trend of the series. It suggests repetition of past

trends or pattern in future prices of the series which will help the

investors in their investment decision.

However, for the majority of companies 44 out of 55 companies, we

accept null hypothesis as the z value of run tests turn out to be

significant. It means that their stocks prices could not be predicted

using historical information.

For these 44 companies there stock price series are random. Thus,

in these 44 companies historical data would be of no use to design

any profitable investment strategy. In these 44 companies the past

trend can not repeat itself.

Following are the List of Companies following Random walk:

1. TAC Ltd

2. Jet Airways

3. Deccan Aviation Ltd.

4. Dena Bank

5. Yes Bank

6. Akruti Nirman Ltd.

7. GMR Infrastructure Ltd.

8. ONGC

9. Petronet LNG

10. GAIL

11. IBP Co. Ltd.

12. Cairn India

13. IPCL

14. Punj Lloyd Limited

15. Indiabulls

16. IL&FS Investsmart

17. India Infoline Ltd

18. Mahindra & Mahindra Fin. Ser. Ltd.

19. TCS

20. CMC Ltd.

21. Patni Computer

22. Tulip IT Services Ltd.

23. Prithvi Information Solutions Ltd.

24. 3i Infotech Ltd.

25. Tech Mahindra Ltd.

26. Firstsource Solutions Ltd.

27. NDTV

28. PVR Cinemas Ltd.

29. Shringar Cinemas Ltd.

30. UTV

31. Sun TV

32. INOX Leisure Ltd.

33. Jagran Prakashan Ltd.

34. Indoco Remedies Ltd.

35. Biocon Ltd

36. Suzlon Energy Ltd.

37. GVK Power Inf. Ltd.

38. Power Finance Corporation Ltd.

39. Info Edge

40. Piramyd Retail Ltd.

41. Provogue (India) Ltd.

42. Shoppers Stop Ltd

43. Bharati Shipyard Ltd.

44. House of Pearl Fashions Ltd.

Performance of IPO (Top Five IPO's):

Script Date High Low Close Offer price

Growth(%)

Average Return(

%)Indiabulls Sep '

0426.85 22 23.4 19 18.8

Mar ' 05

122.25 93.95 105.4 82 50.4

Tech . Mahindra Ltd

Aug ' 06

569 502 538.45 365 32.21

Mar ' 07

1533.7 1263 1427.1 62.27 47.24

Tulip IT Services Ltd

Jan' 06 261 100 237.3 120 49.43

Mar' 06 332.9 238.55 309.55 23.34 36.385

Shoppers Stop Ltd

may ' 05

419.8 335.5 385.9 238 38.33

Mar ' 06

615 494.9 557.45 30.77 34.55

Provogue (India) Ltd

July ' 05

299 200.5 205.8 150 27.11

Mar ' 06

363 258.2 353.5 41.78 34.445

Mar ' 07

468 431 453.9 22.12

Note:

Growth (%) = Closing Price – Offer Price / Closing Price *100

The detailed list of all is attached in annexure.

Graph:

Top 5 Ipo

50.4

47.24

36.38534.55 34.445

0

10

20

30

40

50

60

Indiabulls Tech . Mahindra Ltd Tulip IT Services Ltd Shoppers Stop Ltd Provogue (india) Ltd

Scripts

Ret

urn

Interpretation:

The above graph shows the list of top 5 IPO's. We can infer from

the graph that India Bulls were given ranked 1st in terms of its highest

return (50.4%). And Subsequent Rank is given out in accordance with

there return.

FINDINGS

FINDINGS

Out of 55 IPO's 11 were not efficient i.e. there are not following

random walk, so price of these 11 companies can be predicted

using historical price movements. The technical analyst can get an

abnormal return using these scripts.

For 44 companies the share prices are random it means that the Ho

is accepted in these 44 companies so, these stocks can not be

predicted by the historical price movements. Technical analyst not

at all useful for predicting future trend.

We derived top 5 IPO’s on the basis of their average return of two

year ended prices.

1. India Bulls - 50.4%

2. Tech.Mah. - 47.24%

3. Tulip - 36.38%

4. Shopper Stop - 34.55%

5. Provogue - 34.45%

We also come to know that those top 5 IPO’s who generate higher

return are random in nature.

It was found that maximum number of IPO in list that does not

follow randomness is from banking sector.

Conclusion

Conclusion

We can conclude that from the total number of IPO’s came in

duration of 2004- 2007, the majority of IPO’s(43) were efficient in

nature. Which implies that the technical analyst were not at all able

to get an abnormal return using there skills because historical

prices are not at all guide them for predicting future trends.

From the result that we had derived we conclude that substantial

amount of IPO's (11) follow random walk. This implies that these

stocks can be predicted by using historical information. In other

words, technical analysis plays an important role in devising

profitable trading strategy on the bases of historical information on

share price.

Even the performance of IPO based on the market timing, initial

offer price and Initial offer size.

Recommendations

Recommendation

We can recommend to the risk averse investors better to invest in

the IPO’s whose are not random in nature and Vice- versa case for

the risk taker investors.

We can recommend to the investor, better to invest in the IPO’s

after considering the sectorial growth.

It can be seen that the majority of the stocks i.e. 44 are pursuing

random-walk. They cannot earn abnormal return from their

investments in those companies. This finding assists them to take

wiser investment decisions.

We can recommend to the investor who wishes to invest in those 11

companies that better to take help of historical trend information to

predict there likely trend.

Bibliography

Bibliography

Books:

1. Punithavathy Pandean, “Security Analysis and Portfolio

Management”, vikas publishing House Pvt. Ltd. p.g.283-29

2. Donald E.Fischer and Ronald J. Jordan, “Security Analysis and

Portfolio Management” By, Sixth Edition (2006) p.g.538-558.

3. S.Kevin, Potfolio Management, second Eddition,Prenice-Hall of India

Private LTD.,New delhi-2007p.g.122-132

Web Links For Data used:

http://www.nseindia.com/

Home > Equities > Market Information > Historical Data > Security-wise

Price Volume Data

Sources of literature used:

1. http://en.wikipedia.org/wiki/Efficient_market_hypothesis

2. http://www.investorhome.com/emh.htm

3. http://en.wikipedia.org/wiki/Efficient_market_hypothesis#Assumptions

Annexure

Annexure

(1) Return Graph of Year 2004:

IPO Perfromance

12.95

23.965

14.655

50.4

-20.515

34.485

0.255

-14.545

31.7

3.96

11.415 12.105

-7.87

9.005

-4.17

-30

-20

-10

0

10

20

30

40

50

60

Scripts

Ret

urn

Return

Return 12.95 23.965 14.655 50.4 -20.515 34.485 0.255 -14.545 31.7 3.96 11.415 12.105 -7.87 9.005 -4.17

Indoco Remedi

es

Bharati shipyar

dNTPC

Indiabulls

TCS NDTVBiocon

LtdONGC

Petronet LNG

GAILBank of Mahara

stra

CMC. Ltd

IBP. Co. Ltd

IPCLPatni

Computer

(2) Return Graph of 2005:

Performance of IPO

-120

-100

-80

-60

-40

-20

0

20

40

60

Scripts

Ret

urn

Return

Return -107 36.39 14.32 24.91 14.27 36.89 -8.79 24.57 23.95 32.86 34.45 34.55 -3.24 30.21 -2.07 6.195 20.87 32.6 14.49 -6.26 7.7

Punj Lloyd Ltd

Tulip IT

Services

PVR Cinemas Ltd

Piramyd

Retail Ltd

Prithvi

Informatio

Suzlon

Energy

TAC Ltd(Talbro

s

IDFC

IL & FS

Investsmar

YES Bank

Provogue (india) Ltd

Shoppers Stop Ltd

Oriental

Bank Of

India Infoline Ltd

Allahabad Bank

Shringer

Cinemas

3i Infote

ch Ltd

Emami Ltd

UTV Jet

Airways

Dena Bank

s

(3) Return Graph Of Year 2006:

Performance of IPO

-40

-30

-20

-10

0

10

20

30

40

50

60

Scripts

Ret

urn

Return

Return -10.52 9.82 -30.1 28.205 47.24 21.28 -32.725 -14.73 8.295 23.555 6.83 -11.725 24.55 -18.73

Cairn india

Tanla Solution

Parsvnath

Developers Ltd

Info Edge

Tech . Mahindr

a Ltd

GMR Infrastructure Ltd

Deccan Aviation

Ltd

Patel Engineering Ltd

Reliance Petroleu

mSun TV

Mahindra &

Mahindra

GVK Power

INF. Ltd

Inox Leisure

Ltd

Jagran Prakashan Ltd

(4) Return Graph of Year 2007:

Performance OF IPO

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

Script

Ret

urn

Return

Return -15.905 -28.52 -10.41 4.905 8.435

Akruti Nirman LtdHouse Of Perl Fashion

LtdCinemax India Ltd Firstsource Solution Ltd

power Finanace Corporation Ltd