Testing of Weak-Form Efficiency in Indian Stock Market_2

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Testing of Weak-Form Efficiency in Different

sectors of Indian Capital Market

Mayank Chaturvedi

IPG_2007 31



Motivation

• My area of Interest is finance and want to pursue my professional

career in this area . So it would be better to opt for a topic in finance

stream.

• Secondly, the topic is related to market efficiency of Indian market

.With the current market situation and the recent recession in the

market , I think this topic would help me in gaining some in-depth

knowledge about the present stock market not only in India but alsoglobally.



Introduction

• India is considered as one of the fastest emerging markets in the world. It

has a well established stock market with a long history of organized

trading in securities.

• However, the dominant presence of stock markets by itself does notguarantee growth of the market. The markets have to be efficient in order

to provide sustainable growth in a long run( Mukherjee 1971).

•

Efficient market hypothesis explain that all of the information, which areoffered to the public in the markets, reflected in the price of traded on the

stock markets so that investors cannot use this information to obtain

abnormal gains(Keane, 1983).



Fama (1970) has been the first to develop the efficient markets

hypothesis. Fama (1991) classifies market efficiency into three forms —

weak, semi-strong and strong.

Weak-form efficient market is the one that reflects all information of

the assets in its current prices hence past prices are not useful for

identifying mispriced assets.

This paper examines the ―weak form efficiency of the Indian Stock

Markets by applying the Random walk hypothesis on the share prices of

various companies included in the S&P CNX Nifty.”

The Random Walk theory presupposes that the stock markets are so

efficient and competitive that there is immediate price adjustment. Thus

the random walk theory is based on the hypothesis that the stock

markets are efficient. Hence ,this theory later came to known as the

efficient market hypothesis(EMH).(Kevin,2001)



International Research

Research Title Publishing Date Objective

A study of the predictive performance of

the moving average trading rule as applied

to NYSE, the Athens Stock Exchange and

the Vienna Stock Exchange: sensitivity

analysis and implications for weak-form

market efficiency testing

Applied Financial

Economics, 2009

Alexandros E. Milionis

,and

Evangelia Papanagiotou

This work examines the variation of the

simple Moving Average (MA) trading rule

performance as a function of the MA

length in New York Stock Exchange

(NYSE), Athens Stock Exchange (ASE)

and Vienna Stock Exchange (VSE) using

daily data from May 1993 to April 2005.

Weak-Form Efficiency of Textile Sector:

An Empirical Evidence from Pakistan.

Interdisciplinary journal of

contemporary research in

business, April 2011

Prof. Dr. MehboobAhmad,

Dr. Muhammad Ilyas

The study investigates the behavior of

stock prices in KSE, also tests and

analyzes the weak form efficiency of

textile sector for improving the

understanding of small investors.

The weak form market efficiency

investigation of American, European and

Asian stock markets.

Chinese business review

,October 2010

Nuray Ergül

This paper investigates the empirical

validity of the Weak Form Efficient

Market Hypothesis for American,

European and Asian stock markets.

Random Walk Hypothesis is used to prove

weak form efficiency in American,

European and Asian stock indices



National Research

Research Title Publishing Date Objective

Weak-Form Market Efficiency in India

and Its Emerging Asian Counterparts

IUP journal of behavioural

finance , 2010

B J Queensly Jeyanthi

In this study, the existence of weak-form

efficiency of Asian emerging stock markets is

analyzed. The sample includes the daily price

indices namely China (SSEC), Indonesia (JKSE),

Kuala Lumpur (KLSE), Korea (KS11), Taiwan(TWII) and India (Nifty) for the period of April

1, 1998 to March 31, 2009.

Efficiency of the Indian foreign

exchange market: An empirical

analysis

International Journal of

Finance,2007

N. Mishra, V. Narisimhan,

K.N. Murty

The present study was designed to analyze

and empirically verify the efficiency of the

Indian foreign exchange market



Gap Analysis

After the review of International and National review paper ,following gapare found in these papers.

The study on market efficiency is not done on the various sector of the market.

Overall study has been done at national and international level are all based onoverall market test.

Implication of the efficiency of various sectors has not been find out likewhich economic factors are responsible for the efficiency or inefficiency of that

specific sector.

Studies has been done on long time interval(10 years) , analysis can be done bybreaking the initial duration into 2-3 smaller intervals.



Objectives

The study is focused towards finding the efficiency of the IndianStock Market.

To test the Weak-Form Efficiency hypothesis onIndian stock market taken S&P CNX Nifty as thereference index from 2001-2011.

To test the Weak-Form Efficiency hypothesis onvarious sectors in BSE Index like – FMGC,Telecom,IT etc.

Find out the importance and implication of

different sectors on the Indian market on the basisof their efficiency .

Find out the major economic factor responsiblefor the efficiency calculated above.



Methodology proposed

For the analysis of Weak-Form efficiency ,stock prices of thevarious companies listed in the NSE Index is required.

• Data Sources – S&P CNX Nifty.

• Data – Only secondary data is required for the study .The stock

prices of various companies can be found from the NSE website.

• Tools – E-VIEWS, MATLAB, MS-Excel are used for the research .

• Techniques – For the Weak-form efficiency testing, random

walk(unit test) testing of stock prices is analyzed using following

techniques -• Augmented Dickey-Fuller (ADF) Test.

• The Phillips-Perron (PP)Test.



Augmented Dickey Fuller (ADF) Test:

It is an extension of Dickey -Fuller test and it can be shown as

The number of lagged difference terms is determined empirically. The nullhypothesis is that p=a i.e. there exists a unit root.

The ADF is limited by its number of lags. It reduces the power of the test to rejectthe null of a unit root, because the increased number of lags necessitates theestimation of additional parameters and a loss of degree Dickey -Fuller test and itcan be shown as



The Phillips-Perron(PP) Test

PP test is an alternative (non-parametric) method of controlling

for serial correlation while testing for a unit root.The PP test

procedure is based on the following ADF regression wit the

same critical values used for ADF:

One advantage of the PP tests over the ADF tests is that the PPtests are robust to general forms of heteroskedasticity in the errorterm. Another advantage is that the user does not have to specifya lag length for the test regression.



ADF test Analysis

Null Hypothesis: H0 = Indian Stock Market does not follows random walk.

Alternative hypothesis : H1 = Indian Stock Market follow random.

• Now for the Analysis of Random Walk of Various Stock prices Taken, We

use the following Test also known as Unit root Test.• For the First Part of this Research, S&P CNX Nifty Index data is used. The

shares included in the S&P CNX Nifty Index cover nearly 23 sectors of the

economy with almost 60% of the total market Capitalization of the Indian

stock market.

• The data are collected for 20 out of 50 companies which are traded from1st April 2000 – 31st March 2005.The Data is collected from NSE website.



Table 1 Result of Augmented Dickey Fuller Test under three different

situations for all the variables included in the study

Name of the Company None Intercepts Intercepts and Trend

ABB 56.40061 56.39226 56.39398

ACC 58.47580 58.47711 58.39398

BHEL 57.31245 57.32474 57.32036

BPCL 55.07392 57.32474 57.32036

CIPLA 55.07392 55.06612 55.05822

DR REDDY 56,91431 56.90696 56.90169

GRASIM 52.79314 52.79070 52.81547AMBUJACEM 58.86179 58.85933 58.85193

HDFC 63.26520 63.25656 63,25955

DLF 58.02795 58,2295 58.01456

INFOSYS 56.52152 56.51722 56.53476

ITC 57.61564 57.60826 57.60753

MARUTI 53.23198 53.22448 53.2276

M&M 56.52322 56.53043 56.54093RANBAXY 55.07392 55.06612 55.06612

SAIL 56.58297 56.57750 55.64018

SBIN 54.54849 54.56312 24.55871

SIEMEN 55.01150 55.00383 54.99595

TATAPOWER 56,36670 56.35869 56.433545

LT 54.46746 54.46465 54.41958



ADF test Analysis contd.

• The test is tested at 1% level of significance such as 2.56650

for none,3.432107 for intercepts and 3.960770 for both none

and intercepts respectively.

• From the Table 1, It is clear that in all the three cases – (

none, intercept, and none & intercept),all the companies

reject null hypothesis as the value is greater than the value

calculated from the table.

• From the ADF test shows that there is a random walk in the

Indian stock market





Name of the Company None. Intercepts None and Intercepts

ABB 56.39398 56.38558 56.37872

ACC 58.47626 58.47746 58.49651

BHEL 57.30455 57.31744 57,31302

BPCL 55.03788 55.2994 55.24316

CIPLA 55.03788 55.2994 55.02192

DR REDDY 56,89900 56.89142 56.88605

GRASIM 52.95140 52.94708 52.96090

AMBUJACEM 58.87929 58.87727 58.86987

HDFC 62.43401 63.4251,1 63.43283

DLF 58.02744 58.02243 58.1396

INFOSYS 56.52495 56.52082 56.54710

ITC 57.61122 57.60373 57.60309

MARUTI 53.11389 53.10606 53.10302

M&M 56.54093 56,54640 56.64917RANBAXY 55.03788 55,02992 55.02192

SAIL 56.55567 56.54999 56.61318

SBIN 54.55776 54.56761 54.56232

SIEMEN 54.99913 54.99137 54.98343

TATAPOWER 56.33121 56.32290 56.40147

LT 54,41184 54.41438 54.41438

Table 2 Result of Phillips-Perron(PP) Test with closing prices of all the

companies considered in the study





ADF and PP test Results

• From 2000-2005 , The Indian stock market

shows random walk .

• The Result is based on the NSE index and

Major market capitalization companies are

taken for the analysis.



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Testing of Weak-Form Efficiency in Indian Stock Market_2