091354 Dissertation Proposal Vaibhav Gupta

8/8/2019 091354 Dissertation Proposal Vaibhav Gupta

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DISSERTATION PROPOSAL

On

Testing Market Efficiency in relation to the company size

and company life-cycle stage

(October 11, 2010)

In partial fulfilment of the requirements of the course Dissertation Project of

MBA (Full Time) 2009 - 2011

Submitted to

Prof. Deepak Danak

Submitted By:

Vaibhav Gupta 091354

MBA (FT) 2009-11 Batch

Institute of management,

NIRMA University

DISSERTATION PROPOSAL

Institute of Management, Nirma University of Science and TechnologySG Highway, Ahmedabad 382 481, India; Ph: +91-02717-241900-04;

Email: [email protected]; Website: www.imnu.ac.inPage 1 of25


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Title of the project:

The title of the dissertation project is Testing Market Efficiency in relation to the company size

and company life-cycle stage.

Author of report: Vaibhav Gupta

Faculty Guide: Prof. Deepak Danak

Purpose of report: To identify the Efficiency of Indian Market according to:

Industry life cycle. The industries belong to some specific stage in their life cycle. Efficient

market hypothesis is to be tested in the industries categorizing in the respective industry life

cycle.

Company size in the industry. The companies of certain size are to be clubbed together in the

respective industry and market efficiency is to be tested in these respective industries.

Scope of the project: The companies under research are all the companies that are listed in BSE.

We are taking only Indian companies which are listed on BSE which have net

asset for 2009 above Rs. 10crore.

Deliverables from the project:

We are making a hypothesis that the market efficiency depends on the stage of

the industry (in the industry life cycle) in which they belong. The market

efficiency may depend on the phase of the industry life cycle. By this Research

we will able to state whether the market efficiency depends on the life cycle of

the industry.

We are also making a hypothesis that the market efficiency depends on the

company size. So we will test whether the market efficiency depends on the

company size.

Submitted to : Institute of Management, NIRMA University, and Ahmedabad




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Table of Contents

Introduction..................................................................................................................................... 4

PRELIMINARY SURVEY OF THE RELATED LITERATURE..................................................5

Efficient Market Hypothesis (EMH) ................................................................................................5

The Random Walk Hypothesis (RWH) ...........................................................................................8

Research in Different Markets (other than India) ............................................................................9

Comparative Studies on Indian market............ ...............................................................................11

Rationale for Research............ ........................................................................................................14

Scope of the research........................................................................................................................15

Research problem.............................................................................................................................17Research Questions..........................................................................................................................17

Research Objectives..................................................................................................................... ...17

Research technique...17

Research Hypothesis: ..................................................................................................................... 18

Statistical tools applied....................................................................................................................19

Research methodology: ................................................................................................................. 21

References....................................................................................................................................22




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Introduction

The origins of the EMH can be traced back to the work of two individuals in the 1960s: Eugene F.

Fama and Paul A. Samuelson.

The Efficient Market Hypothesis (EMH) is concerned with the informational efficiency of the

capita1 markets. Based on the type of information that is fully reflected in the security prices, three

forms of EMH have been propounded, namely the weak, the semi-strong and the strong. In the

weak form of efficiency, security prices fully reflect the information content of past prices. In the

semi-strong form all public information and in the strong form all information. Whether public or

private, respectively is fully reflected in the security prices. When the market is efficient with

respect to an information set, it means that no one can consistently make abnormal profits using

only that information set. Here, abnormal profits refer to the profits earned in excess of the profits

from a naive buy-and-hold strategy. However, on particular occasions, due to chance, it may be

possible for some to gain profits higher than from a naive buy-and-hold strategy. What the EMH

says is that no one can consistently make higher profits by trading than by following a naive buy-

and-hold strategy.

We are for the weak and semi-strong form of efficiency of the Indian capital market. Thatis, we are

testing for randomness using:

Three -standard-deviation limits

Runs Test for Detecting Non-randomness

Serial auto-correlation test (Durbin- Watson statistic).

Box-Ljung statistic(Autocorrelation)

Filter Rule Tests




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Based on the daily closing prices, sector-wise, for companies having net asset value greater than

Rs.10crore in 2009, traded on the Bombay Stock Exchange from April 2006 to September 2010.

Tests are performed on SPSS and MS EXCEL. Run tests is performed on the closing price for the

collected data ,while filter tests are performed using daily returns. Box-Ljung statistic

(Autocorrelation) is performed on the residuals.

This dissertation study will be conducted in the span of five months. The data required for the

purpose will be secondary source based on CMIE prowess.

PRELIMINARY SURVEY OF THE RELATED LITERATURE:

Efficient Market Hypothesis (EMH)

The efficient markets hypothesis (EMH) maintains that market prices fully reflect all available

information. Developed independently by Paul A. Samuelson and Eugene F. Fama in the 1960s, this

idea has been applied extensively to theoretical models and empirical studies of financial securities

prices, generating considerable controversy as well as fundamental insights into the price-discovery

process. The most enduring critique comes from psychologists and behavioural economists who

argue that the EMH is based on counterfactual assumptions regarding human behaviour, that is,

rationality. Recent advances in evolutionary psychology and the cognitive neurosciences may be

able to reconcile the EMH with behavioural anomalies.

It is disarmingly simple to state, EMH has far-reaching consequences for academic theories and

business practice, and yet is surprisingly resilient to empirical proof or refutation. Even after several

decades of research and literally thousands of published studies, economists have not yet reached a

consensus about whether markets particularly financial markets are, in fact, efficient.

The origins of the EMH can be traced back to the work of two individuals in the 1960s: Eugene F.

Fama and Paul A. Samuelson. Remarkably, they independently developed the same basic notion of

market efficiency from two rather different research agendas. These differences would propel them




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along two distinct trajectories leading to several other breakthroughs and milestones, all originating

from their point of intersection, the EMH.

The Efficient Market Hypothesis (EMH) is concerned with the informational efficiency of the

capital markets. Based on the type of information that is fully reflected in the security prices, three

forms of EMH have been propounded, namely the weak, the semi-strong and the strong. In the

weak form of efficiency, security prices fully reflect the information content of past prices. In the

semi-strong form all public information and in the strong form all information. Whether public or

private, respectively is fully reflected in the security prices. When the market is efficient with

respect to an information set, it means that no one can consistently make abnormal profits using

only that information set. Here, abnormal profits refer to the profits earned in excess of the profits

from a naive buy-and-hold strategy. However, on particular occasions, due to chance, it may be

possible for some to gain profits higher than from a naivebuy-and-hold strategy. What the EMH

says is that no one can consistently make higher profits by trading than by following a naive buy-

and-hold strategy.

Like so many ideas of modern economics, the EMH was first given form by Paul Samuelson(1965), whose contribution is neatly summarized by the title of his article: Proof that Properly

Anticipated Prices Fluctuate Randomly. In an information efficient market, price changes must be

unforecastable if they are properly anticipated, that is, if they fully incorporate the information and

expectations of all market participants. Having developed a series of linear-programming solutions

to spatial pricing models with no uncertainty, Samuelson came upon the idea of efficient markets

through his interest in temporal pricing models of storable commodities that are harvested and

subject to decay. Samuelsons abiding interest in the mechanics and kinematics of prices, with and

without uncertainty, led him and his students to several fruitful research agendas including solutions

for the dynamic asset allocation and consumption-savings problem, the fallacy of time

diversification and log optimal investment policies, warrant and option-pricing analysis and,

ultimately, the Black and Scholes (1973) and Merton (1973) option-pricing models. In contrast to

Samuelsons path to the EMH, Famas (1963; 1965a; 1965b, 1970) seminal papers were based on

his interest in measuring the statistical properties of stock prices, and in resolving the debate

between technical analysis (the use of geometric patterns in price and volume charts to forecast




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future price movements of a security) and fundamental analysis (the use of accounting and

economic data to determine a securitys fair value). Among the first to employ modern digital

computers to conduct empirical research in finance, and the first to use the term efficient markets

(Fama, 1965b), Fama operationalised the EMH hypothesis summarized compactly in the epigram

prices fully reflect all available information by placing structure on various information sets

available to market participants.

Driven by profit opportunities, an army of investors pounce on even the smallest informational

advantages at their disposal, and in doing so they incorporate their information into market prices

and quickly eliminate the profit opportunities that first motivated their trades. If this occurs

instantaneously, which it must in an idealized world of frictionless markets and costless trading,

then prices must always fully reflect all available information. Therefore, no profits can be garnered

from information-based trading because such profits must have already been captured (recall the

$100 bill on the ground). In mathematical terms, prices follow martingales.

Such compelling motivation for randomness is unique among the social sciences and is reminiscent

of the role that uncertainty plays in quantum mechanics. Just as Heisenbergs uncertainty principleplaces a limit on what we can know about an electrons position and momentum if quantum

mechanics holds, this version of the EMH places a limit on what we can know about future price

changes if the forces of economic self-interest hold. A decade after Samuelsons (1965) and Famas

(1965a; 1965b; 1970) landmark papers, many others extended their framework to allow for risk-

averse investors, yielding a neoclassical version of the EMH where price changes, properly

weighted by aggregate marginal utilities, must be unforecastable (see, for example, LeRoy, 1973;

M. Rubinstein, 1976; and Lucas, 1978). In markets where, according to Lucas (1978), all investors

have rational expectations, prices do fully reflect all available information and marginal-utility

weighted prices follow martingales. The EMH has been extended in many other directions,

including the incorporation of non-traded assets such as human capital, state-dependent preferences,

heterogeneous investors, asymmetric information, and transactions costs. But the general thrust is

the same: individual investors form expectations rationally, markets aggregate information

efficiently, and equilibrium prices incorporate all available information instantaneously.




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The principal issue from an academic viewpoint is market efficiency (Fama 1970, 1991). The

Efficient Market Hypothesis (EMH) assumes that stock prices adjust rapidly to the new information,

and thus, current prices fully reflect all available information. (Fama 1970), formalized the theory,

organized empirical evidence and divided the EMH into three sub-hypotheses depending on the

information set involved. It is an important concept, both in terms of an understanding of the

working of stock and in their performance and contribution to the development of a countrys

economy. If the stock market is efficient, the prices will represent the intrinsic values of the stocks

and in turn, the scarce savings will be optimally allocated to productive investments in a way that

benefits both individual investors and the country economy (Copeland and Weston, 1988).

The efficient market theory further asserts that if markets are efficient, then it should be virtually

impossible for an investor to outperform the market on a sustained basis. Even though deviations

will occur and there will be periods when securities are over or undervalued, these anomalies are

expected to disappear as quickly as they appeared, thus making it almost impossible to profit from

them consistently. The weak form of market efficiency theorizes that the current price does not

reflect fair value and is only a reflection of past prices. It further states that the future price cannot

be determined using past or current prices. The semi-strong form of market efficiency theorizes that

the current price reflects all readily available information. This information might include annualreports, annual filings, earnings reports, announcements, and other relevant information that can be

readily gathered. The strong form efficiency states that the stock prices reflect all information from

historical, public and private sources, so that no investor can realize abnormal rate of return. Though

theoretical literature talks of market efficiency, in practical terms the market is not perfectly

efficient. Anomalies do exist and there are investors and traders who outperform the market. So, the

EMH has very important implications for both investors and authorities that regulate and control the

market. Elango & Hussein 142 .

The Random Walk Hypothesis (RWH)

Filter Rule Tests Filter rule tests have a direct economic interpretation. We can, see the return

earned by using a certain trading rule and compare it with the buy-and-hold strategy in the same

stock. We can easily make inferences about whether the trading rule is profitable by adjusting the

excess returns for transaction costs. In the case of runs test and serial correlation test, we cannot




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easily determine whether the statistically significant results provide any profitable opportunities.

The filter rule has been defined with the assumption that short-sales are not allowed. The rules have

used can be stated as follows:

If theprice of a security rises at least x percent, buy and hold the security untilits price drops atleast x percent from a subsequent high. Then, liquidate the long position and retain cash until the

price reaches its next trough and then rises x percent. A filter rule test basically tests whether the

stock price series exhibits any momentum and if so whether it is profitable.

The prices series has been adjusted for stock splits and bonus issues where data was available, but

no adjustments have been made for dividends.

Initially, the trader was assumed to have a cash position. He will keep monitoring the price level for

troughs. When the price rises by x% from the trough (least price from April 1989 to date), he will

purchase the securities for a notional amount of Rs. 1,000. Then, he will monitor the peaks and

compare with the current price. When the price falls by x% from the high (the peak price from the

date of purchase), he will sell his holdings and retain cash. Then he will monitor the price and

compare with the troughs. When the price rises by x70 from the trough (lowest price since the

previous sale date), he will convert his cash position to a long position in the security.

It may be noted that the operator can also go short in the scrip, while retaining his holding. When

the rule gives a buy signal, he covers his short position andEfficiency of the Indian Capital Market

37reinvests the gain (or disinvests to cover the loss) in the scrip. In terms of return computation, his

procedure is the same as the procedure outlined earlier. We have assumed, however, that unlimited

short-sale is not allowed. It has been assumed that the trading strategy will be self-sufficient. We

have not considered separately the transactions of each settlement period falling within our study

period. It may mentioned that if carry-forward charges are incorporated then the excess returns will

be lower.

a. Research in Different Markets (other than India)

The empirical testing of this random walk hypothesis was initially mixed. Early studies by Working

1934, 1960; Samuelson, 1965; and Fama, 1965) examined it and could not refute a random walk.




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RWH were tested heavily in both developed and developing markets. The developed markets are

found to be weak-form efficient. That means that successive returns are independent and follow

random walk (Fama 1965, 1970). These results of weak-form efficiency are confirmed considering

a low degree of serial correlation and transaction cost (Kendall, 1943; 1953, Cootner; 1962,

Osborne, 1962; Fama 1965). All these research works support the proposition that price changes

were random and past changes were not useful in forecasting future price changes particularly after

transactions costs were taken into account. (Fama and French, 1988; Potera and Summers,

1988; Granger, 1975, Hawawini, 1984; Fama, 1991 and Lo, 1997). Though the studies confirmed

the weak-form, yet they could not guide the investors with any clear-cut trading rules to make

abnormal profits.

1)A HISTORICAL ANALYSIS OF MARKET EFFICIENCY:DO HISTORICAL RETURNS

FOLLOW A RANDOM WALK by Michael J. Seiler and Walter Rom,Journal Of Financial

And Strategic Decisions Volume 10 Number 2 Summer 1997

Historical stock returns are analyzed to test the efficiency of the NYSE from 1885 through 1962, the

period before the CRSP tapes were available. The Box-Jenkins methodology was employed in an

attempt to identify patterns which could be used to predict stock returns. The confidence intervals

associated with each of the three tables are consistently and significantly widened with

each successive forecasting period indicating that changes in historical stock prices are completely

random. Although monthly and weekly return patterns were found to be significant, they were still

unsuccessful in predicting future stock price movements. Since changes in stock prices are random,

we can do no better than to predict that the next periods price will be somewhere around where it

was the last time we knew it. This conclusion is not surprising, and moreover, is consistent with

modern efficient market studies.

2) Efficient market hypothesis and forecasting by Allan Timmermann, Clive W.J. Granger

Department of Economics, University of California San Diego, 9500 Gilman Drive, La Jolla,

CA 92093-0508, USA International Journal of Forecasting 20 (2004) 15 27




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suggestions have wider implications for security analysts, investing community, stock exchanges,

and other regulatory authorities in their policy decisions to improve their capital market functioning.

5) Efficient Market Hypothesis in European Stock Markets by Maria Rosa Borges ,

Department of Economics,School of Economics and Management, TECHNICAL UNIVERSITYOF LISBON WP 20/2008/DE/CIEF Draft Version: April 2008

This paper reports the results of tests on the weak-form market efficiency applied to stock market

indexes of France, Germany, UK, Greece, Portugal and Spain, from January 1993 to December

2007. Test used were serial correlation test, a runs test, an augmented Dickey-Fuller test and the

multiple variance ratio test proposed by Lo and MacKinlay (1988) for the hypothesis that the stock

market index follows a random walk. The tests are performed using daily and monthly data for the

whole period and for the period of the last five years, i.e., 2003 to 2007. Overall, convincing

evidence were found that monthly prices and returns follow random walks in all six countries.

Daily returns are not normally distributed, because they are negatively skewed and

leptokurtic. France, Germany, UK and Spain meet most of the criteria for a random walk behaviour

with daily data, but that hypothesis is rejected for Greece and Portugal, due to serial positive

correlation. However, the empirical tests show that these two countries have also been approaching

random walk behaviour after 2003.

b. Comparative Studies on Indian market:

While a few studies have tested the efficiency of individual markets, quite a few studies have

compared the efficiency of several markets. For example, (Solink, 1973) analyzed 234 stocks from

eight European stock markets; (Ang and Pohlman, 1978) studied 54 stocks from eight European

Stock markets. (Cooper, 1982) examined 50 stock markets scattered throughout the world. (Urrutia,

1995) tested the RWH in four Latin American emerging equity markets. (Huang, 1995) studied the

stock markets of nine Asian countries; and finally (Dahel and Laabas, 1999) examined the

efficiency of four GCC (Gulf Co-operation Council) markets.




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1) Efficiency of the Indian capital. Market - by R. VAIDYANATHN & KANT1

KUMARGALI INDlAN JOURNAL OF FINANCE AND RESEARCH VOL. v, NO. 2 ,LV

dated 1994

This study tested for the weak form of efficiency of the Indian capital market, tested randomness

using run test, serial correlation and filter rule test based on the daily closing prices of ten shares

actively traded on the Bombay stock Exchange. The evidence from all the three tests supported

the weak form of Efficient Market Hypothesis (EMH). However, with an unrealistic assumption

of zero transaction cost, it may be possible to identify profitable opportunities for using filter rules

provided the patterns are stable over time.This shows that foroperators with no transaction costs,

the filter rule is profitable for some scrip. However, the operator can only make a profit if he

knows, in advance, which scrip and which filter is profitable.

2) Market efficiency on the Indian equity derivatives market by Ajay Shah Ministry of

Finance, New Delhi and IGIDR, Bombay dated 1 December 2002

A study was conducted focused on questions of market efficiency, of the extent of mispricing on the

equity derivatives market ( Indian market). Using intra-day data for one week in September 2002,

accurately measured the returns available to three simple arbitrage strategies. It was found thatpervasive violations of market efficiency is existing, i.e. the existence of arbitrage opportunities

which systematically earn extremely supernormal rates of return.

3) DAY OF THE WEAK EFFECT AND MARKET EFFICIENCY EVIDENCE FROM

INDIAN EQUITY MARKET USING HIGH FREQUENCY DATA OF NATIONAL STOCK

EXCHANGE- by Golaka C Nath & Manoj Dalvi dated: December 2004

This study on Indian market examined empirically the day of the week effect anomaly in the Indianequity market for the period from 1999 to 2003 using both high frequency and end of day data for

the benchmark Indian equity market index S&P CNX NIFTY. Using robust regression with bi-

weights and dummy variables, the study found that before introduction of rolling settlement in

January 2002, Monday and Friday were significant days. However after the introduction of the

rolling settlement, Friday has become significant. This also indicates that Fridays, being the last

days of the weeks have become significant after rolling settlement. Mondays were found to




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have higher standard deviations followed by Fridays. The existence of market inefficiency is

clear. The market inefficiency still exists and market is yet to price the risk appropriately.

4) Weak Form Efficiency In Indian Stock Markets Rakesh Gupta, , Central Queensland

University, Australia Parikshit K. Basu, Charles Sturt University, AustraliaInternational

Business & Economics Research Journal March 2007 Volume 6, Number 3

With increased movement of investments across international boundaries owing to the integration of

world economies, the understanding of efficiency of the emerging markets is also gaining greater

importance. In this paper weak form efficiency was tested in the framework of random walk

hypothesis for the two major equity markets in India for the period 1991 to 2006. The evidence

suggested that the series do not follow random walk model and there is an evidence of

autocorrelation in both markets rejecting the weak form efficiency hypothesis.

5) Testing Random Walk Hypothesis for Indian Stock Market Indices by Bhanu Pant

Research Scholar Nirma Institute of Management, Ahmedabad , Dr. T. R. Bishnoi Faculty in

Finance Nirma Institute of Management, Ahmedabad

This study worked on the random walk hypothesis for daily and weekly market indices returns are

rejected for Indian context using heteroscedasticity corrected variance ratio test. There are

significant first order autocorrelation in daily returns, which are in general absent in weekly returns.

Autocorrelation if present is significant at lag one & two and it tends to die out for higher lags.

Heteroscedasticity is not a source of non-random behaviour of the indices. The problem of changing

variances is restricted to daily data for BSE-100. The rejection of null hypothesis of random walk

can be explained by the mean reverting tendency of stock market prices. In absence of

heteroscedasticity and non-trading problems, the variance ratio test turns out to be a test of stock

index means reversion behaviour. The results confirm the mean reverting behaviour of stock

indices and overreaction of stock prices in unitary direction in India. This provides an

opportunity to the traders for predicting the future prices and earning abnormal profits.

6) Empirical Evidence on Indian Stock Market Efficiency in Context of the Global Financial

Crisis by P K Mishra, K B Das and B B Pradhan, Global Journal of Finance and Management

ISSN 0975 - 6477 Volume 1, Number 2 (2009), pp. 149-157




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This paper focused on testing the efficient market hypothesis in its weak form in Indian stock

market in the context of global financial crisis. ByEmpirical Evidence on Indian Stock Market155

Embarking upon the popular unit root test, the study provides the weak form inefficiency of Indian

stock market in the sample period. This market inefficiency has several implications. First, theshare prices may not necessarily reflect the true value of stocks. So, companies with low true values

may be able to mobilise a lot of capital, while companies with high true values may find it difficult

to raise capital. This disrupts the investment scenario of the country as well as the total productivity.

7) AN EMPIRICAL TEST OF INDIAN STOCK MARKET EFFICIENCY IN RESPECT OF

BONUS ANNOUNCEMENT by M. Raja1Bharathidasan University College (Lalgudi), India.

J. Clement SudhaharKarunya University, India. Asia Pacific Journal of Finance and Banking

Research Vol. 4. No. 4. 2010

This study was an attempt to test the efficiency of Indian stock market with respect to bonus issue

announcement by IT companies.This study has empirically examined the informational efficiency

of capital market with regard to bonus issue announcement released by the IT companies. The

results of the study showed that the security prices reacted to the announcement of bonus issue.

Thus one can safely conclude from the foregoing discussions that the Indian capital market for

the IT sector, in general, are efficient, but not perfectly efficient, to the announcement ofbonus issue. This informational inefficiency can be used by the investors for making abnormal

returns at any point of the announcement period.

Rationale for Research:

The reason behind choosing the project is that the Indian market is still very little researched for

market efficiency. There has been studies on Indian market and other market, some of which are

supporting weak form of market efficiency while some are rejecting weak form of market

efficiency. The chosen project topic has not been researched for Indian market till now most of the

research which is done for market efficiency is done for the complete market and so I wanted to test

if the market is efficiency is same across all industries with different life cycle stage and whether

market efficiency is dependent on company size.




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Scope of the research:

The following industries are to be covered in the research paper. Companies having less than Rs.

10crore are not considered in the set.

1) Financial

Banking

Investment

Asset financing

2) Non- Financial

Manufacturing

Food and beverages

Textile

chemical

non-metallic

machinery

transport equipment

Mining

Coal

Crude oil

Minerals

Electricity

Construction

Services other than financial

Hotel

Health

Transport

IT




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Retail trading

Communication

3) Irrigation

These industries are taken for analysis for this research project.

The research is to analyse whether the market efficiency varies according to industry life cycle.

Under the production and market introduction phases, revenues and earnings are likely to be very

low, which makes investments during these phases more speculative in nature. Revenues and

earnings are likely to be low because there is little demand for the product, or the product is not

completed. Expenses are likely to be very large during these phases as a company or industry

spends a lot on marketing and research.

Through the growth phase, revenues and margins are likely to be on the rise due to an increase in

demand for a product and the pricing power the firm has due to a small number of competitors.

Stock prices are likely to rise during this phase.

During the maturity and stability phase, revenues and margins are likely to decline due to lower

sales demand and more competition. Stock prices are likely to decline during these phases.

*The above mentioned industries belong to different stages of the industry life cycle.




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I have studied research papers related to efficient market hypothesis , the names and brief

description of the papers are as follows:

RESEARCH PROBLEM:

The research problem can be defined as to identify the Efficiency of Indian equity Market according

to Industry life cycle and Company size in the industry.

Research Questions:

A research question is a question whose answer will help you in solving the research problem. On the

basis of this definition of a research problem, several research questions have been identified which are

as follows:

1) Does market efficiency in Indian equity market depend on industry life cycle?

2) Does market efficiency in Indian equity market depend on size of companies?

3) Does Indian equity market shows weak form of efficient market?

4) Does Indian equity market shows semi-strong form of efficient market?

OBJECTIVES OF RESEARCH:

The following research objectives have been identified for this research work:

1. To determine if stock returns in the Indian markets follow a normal distribution.

2. To determine the form of market efficiency in Indian equity market depending on industry life

cycle.




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3. To determine the form of market efficiency in Indian equity market depending on size of

companies.

4. To determine the form of market efficiency for total Indian equity market.

Research techniques:

1) First objective is performed by t test

2) Second objective is performed by:

a) Randomness in Indian equity market using run test.

b) Randomness in Indian equity market using Serial correlation test (Durbin- Watson

statistic).

c) Randomness in Indian equity market using autocorrelation.(Box-Ljung statistic).

d) Existence of momentum in the stock price series any and if so whether it is profitable.

3) Third objective is performed by:



statistic).



4) Fourth objective is performed by:





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statistic).



Research Hypothesis:

Any research always has some null hypothesis to start with. This hypothesis is assumed to be true

and then using primary and/or secondary data, attempt is made to check the validity of this null

hypothesis on the collected data. For the purpose of this research, the following null and alternate

hypothesis have been established:

1.) Ho: The stock returns in the Indian markets follow a normal distribution

Ha : The stock returns in the Indian markets do not follow a normal distribution

2.a) Ho: The stock returns in the Indian markets are random during the study period.

Ha: The stock returns in the Indian markets are not random during the study period.

2.b) Ho: The data is random

Ha: The data is not random.

2.c) Ho: The data is random (i.e. the correlations in the population from which the sample is taken

are 0, so that any observed correlations in the data result from randomness of the sampling

process).


2.d) Ho: stock price series does not exhibits any momentum

Ha: stock price series does exhibit momentum.

Similar hypothesis is developed for 3rd and 4th research objective. Tests are performed using

appropriate statistics.




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The null hypothesis for this test is for temporal independence in the series (or weak-form

efficiency). Because returns are not normally distributed, the presence of structural breaks or

outliers in the series can bias the test results. To control for such issues, I complete the runs test

using a mean and a median as the base. The latter can yield more reliable results when outliers

exist.

ii. Serial correlation:

There are different types of serial correlation. Withfirst-order serial correlation, errors in one time

period are correlated directly with errors in the ensuing time period. (Errors might also be lagged,

e.g. if data are collected quarterly, the errors in Fall of one year might be correlated with the errors

of Fall in the next year.) Withpositive serial correlation, errors in one time period are positively

correlated with errors in the next time period.

Tests for Serial Correlation. By far the most popular test for serial correlation is the Durbin- Watson

statistic:

T = the number of time periods.

The DW statistic will lie in the 0-4 range, with a value near two indicating no first-order serial

correlation. Positive serial correlation is associated with DW values below 2 and negative serial

correlation with DW values above 2.

Parametric Test:

Auto-Correlation and Partial Auto Correlation Function

The LjungBox test (named for Greta M. Ljung and George E. P. Box) is a type of statistical test of

whether any of a group of autocorrelations of a time series is different from zero. Instead of testing

randomness at each distinct lag, it tests the "overall" randomness based on a number of lags, and is

therefore a portmanteau test.

The LjungBox test can be defined as follows:




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H0: The data is random (i.e. the correlations in the population from which the sample is taken are 0,

so that any observed correlations in the data result from randomness of the sampling process).


The test statistic is:

Test Statistic:

where n is the sample size, r(j) is the autocorrelation at lagj, and his the

number of lags being tested.

Significance

Level:

Critical

Region:

The hypothesis of randomness is rejected if

QLB >

where is the percent point function of the chi-square distribution.

The Ljung-Box test is commonly used in ARIMA modeling. Note that it is applied to the residuals

of a fitted ARIMA model, not the original series.

Research methodology:Research Design: Descriptive

Population: Diversified equity Market in India

Sample Unit: Companies having net asset above Rs.10crore.

Data Sources: Secondary

www.ValueResearchOnline.com

Capitaline NAV

www.MoneyControl.com

CMIE PROWESS

Reference:

http://www.itl.nist.gov/


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MARKET EFFICIENCY EVIDENCE FROM INDIAN EQUITY MARKET USING

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Institute of Management, Nirma University of Science and Technology

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091354 Dissertation Proposal Vaibhav Gupta