self study 4

7/30/2019 Self Study 4

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ABM-953

Self Study

On

IMPACT OF TOP MOST BSE SECTORALINDICES ON SENSEX

Submitted By

Anuradha Agarwal

M.Phil.

DAYALBAGH EDUCATIONAL INSTITUTE

FACULTY OF COMMERCE(DEEMED UNIVERSITY)

Dayalbagh, Agra

2013


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ABSTRACT

The unusual rise and fall in of Bombay Stock Exchange (BSE) Sensitive Index (SENSEX) has

received a lot of media attention over last couple of decades in India. Even some policy analyst

has designated it as an indicator of Indias inevitable growth and development. In this p aperattempt has been made to explore the relation between BSE SENSEX and top most BSE sectoral

indices by using correlation and descriptive statistics. Quarterly data has been used from 2008-

2009 to 2012-2013 for both, SENSEX, and top most BSE sectoral indices viz., BSE AUTO, BSE

BANKEX, BSE FMCG and BSE IT. The study also explained the degree and direction of that

relationship as up to what extent quarterly reporting of constituents of sectoral indices have

laid their impact on sensex. And find that the stock prices are highly effected by selected top

most BSE sectoral indices especially by BSE AUTO, BSE BANKEX.

Introduction

In India, since independence the socialistic pattern of development was followed but in early

1990s due to the financial crunch that India faced, it had to afterwards follow on a strict

economic reform package as dictated by World Bank. One of the important components of this

package was financial liberalization. This financial liberalization paved a new way of growth and

development and volatile atmosphere to the Indian economy especially in terms of BSE SENSEX

which is credited as one of the main indicators of Indias financial health. Today stock market

has been one of the prime most sources for mobilizing household savings into upcoming

productive ventures and lends a helping hand in the countrys development.

Review of literature

A large number of empirical studies have been conducted about the determinants of stock

prices. To review the situation different studies have been undertaken on national and

international ground. Different researchers have conducted their researches with different

views and elucidated their findings by different parameters.

Halil kiymaz, Eric Girard (2009) have investigated the relationship between the daily

returns and trading volume. The study found that the persistency of conditional volatility is

high and very close to unity, implying that current information can be used to predict

future volatility.


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Santu Das, J.K. Pattanayak, promod pathak (2008) have judged the impact of quarterly

announcements on sensex. The study also examines the drifting up of shares prices with

references to good announcement and bad announcement.

Shurthi Tripathi (2008) has looked into the different aspects and judged the difference

between BSE 100 index and BSE sensitive index through the use of various times series

tools, and finally tries to find which series is better for the investors to base their decision

on.

Angela J. Black, Patricia Fraser, NIcolaas Groenewold (2001) have used 54 years of

quarterly data and a VAR model underpinned by a theoretical framework describing the

relationship between stock prices and the macro economy. This analyses the extent to

which prices deviate from economy wide fundamentals.

Research Methodology

Objective

To judge the impact of quarterly results on Sensex by the constituents of BSE sectoral

indices

Hypothesis

H0- The top most sectoral indices of BSE and Sensex are independent from each other.

Data and variables in the study

The study has been based on secondary data and information regarding the stock

prices, the sensex figures and quarterly reports has been taken from the different

authentic websites.

For the purpose of the study top 4 sectoral indices viz.BSE AUTO, BSE BANKEX, BSE

FMCG, BSE IT have been considered as the constituents of these four and have affected the

market mainly. It has taken the changes in the quarterly figures of both; Sectoral

indices and the sensex.


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Duration of the study-

2008 to 2013 on Quarterly basis

Tools

Descriptive Statistics, Correlation analysis, Coefficient of determination and t test

Data Analysis and Interpretation

Descriptive Statistics

Various descriptive statistics are calculated of the variables under study in order to

describe the basic characteristics of these variables. In this table various statistics are

calculated like mean, maximum and minimum value, standard deviation, skewness, and

kurtosis,

Table 1- Descriptive Statistics

BSE AUTO BSE BANKEX BSE FMCG BSE IT BSE SENSEX

Mean 5.626319 3.254907 5.187925 4.207641 1.565876

Mini. -0.72048 -1.03447 -0.74399 0.605074 0.05566

Maxi. 53.64647 62.53326 21.89464 41.99148 44.59682S.D 3.383319 5.750832 1.537468 3.901591 9.182943

Skewness 0.750807 1.510175 -0.22032 0.424403 0.870341

Kurtosis 2.156158 4.47834 0.297848 1.006978 4.607288

Interpretation: From the table above in which descriptive values of all the variables have

been calculated shows that S.D is very high in case of Sensex comparative to others which

explain that there is high volatility in its values. From the skewness measure we found that

only BSE FMCG is negatively skewed while BSE bankex is more positively skewed

compared to other variables. In case of kurtosis, all variables are positively skewed, thus

illustrating that all have peaked distribution comparative with normal distribution and as

almost in all cases it is lowest in BSE FMCG and highest in SENSEX.


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Next step is to check out the correlation between the variables in consideration of this study.

Table 2: Correlation Matrix

Interpretation: In the following correlation matrix almost all the variables are positively

high correlated to each other apart from Sensex and BSE FMCG which are less correlated to

each other.

Next step is to find that up to what extent quarterly reporting of constituents of

sectoral indices have laid their impact on sensex by calculating coefficient of

determination.

Table 3: coefficient of determination

Interpretation: In the following table of coefficient of determination the stock prices is

highly effected by BSE AUTO and BSE BANKEX whereas least affected by BSE FMCG.

Next step is to calculate the t-test and check that the top most Sectoral indices of BSE

and Sensex are independent from each other or not.


BSE AUTO 1 0.893561 0.650671 0.7902 0.949773

BSE BANKEX 1 0.482911 0.680312 0.946609

BSE FMCG 1 0.504418 0.588338

BSE IT 1 0.803805

BSE SENSEX 1


BSE AUTO 1 0.798451 0.423373 0.624417 0.902068

BSE BANKEX 1 0.233204 0.462824 0.896068

BSE FMCG 1 0.254437 0.346142

BSE IT 1 0.646103

BSE SENSEX 1


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Table 4: t- test

Variables BSE AUTO BSE BANKEX BSE FMCG BSE IT

Calculated Value 12.88 12.46 3.09 5.73

Interpretation:The table value of t at 5% level of significance for 19 degree of freedom

(n-1, where n= 20) is 1.96. Since the computed value oft of all the top most sectoral indices

is more than the table value, therefore the hypothesis is rejected and can say that stock

prices is effected by top most sectoral indices.

Findings & conclusion

There is high volatility in case of stock prices BSE FMCG is negatively skewed while BSE bankex is more positively skewed compared

to other variables.

In case of kurtosis, all variables are positively skewed, thus illustrating that all havepeaked distribution comparative with normal distribution and as almost in all cases it is

lowest in BSE FMCG and highest in SENSEX.

Correlation matrix almost all the variables are positively high correlated to each otherapart from Sensex and BSE FMCG which are less correlated to each other.

Stock prices is highly effected by BSE AUTO and BSE BANKEX whereas least affected by BSEFMCG.

Therefore, it can be concluded that the stock prices is highly affected by the top most sectoral

indices.


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Appendixes

Quarterly Reports


Q1 2008-2009 -11.0713 -21.3521 3.530413 16.23511 -7.28772

Q2 2008-2009 -10.3546 -10.8921 -6.51314 -16.8204 -11.4149

Q3 2008-2009 -34.2985 -24.4627 -12.1514 -28.8574 -31.7195

Q4 2008-2009 10.50198 -9.7944 6.785364 -13.4723 -1.76573

Q1 2009-2010 53.64647 62.53326 5.597848 35.20117 44.59682

Q2 2009-2010 44.12067 20.33327 21.89464 41.99148 19.59772

Q3 2009-2010 13.71336 10.31299 7.691545 13.09342 3.762646

Q4 2009-2010 4.989241 2.467577 -2.99873 7.098968 0.05566

Q1 2010-2011 9.303193 8.101909 10.58583 3.005616 3.754227

Q2 2010-2011 12.35155 15.89657 13.70882 5.966415 7.095747

Q3 2010-2011 13.00041 8.633246 5.200562 12.58562 7.430282

Q4 2010-2011 -12.5871 -9.29081 -4.38939 0.605074 -7.43608

Q1 2011-2012 3.226008 3.324633 12.16024 -4.13596 1.598576

Q2 2011-2012 -6.00107 -11.0253 2.524805 -11.3307 -9.13058

Q32011-2012 1.565992 -10.9493 2.673955 5.606929 -3.98288

Q4 2011-2012 12.7274 15.2939 3.761275 5.51177 6.223296

Q1 2012-2013 -1.34427 -1.40722 12.59621 -4.91153 -2.64204

Q2 2012-2013 -0.72048 5.612783 10.95063 -0.73496 4.82892

Q3 2012-2013 13.14069 12.79638 10.89305 1.655417 7.193749

Q4 2012-2013 -3.38326 -1.03447 -0.74399 15.859 0.559279


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References:

J.k Pattnayak, The effect of quarterly earnings announcement on sensex : a case with

clustering of events, Indian school of Mines, Dhanbad. Research report.

www.economictimes.com

www.bseindia.com

www.icai.org.in/resource_file/11054p449-oct04

www.ssrn.com
http://www.economictimes.com/http://www.economictimes.com/http://www.bseindia.com/http://www.bseindia.com/http://www.icai.org.in/resource_file/11054p449-oct04http://www.icai.org.in/resource_file/11054p449-oct04http://www.ssrn.com/http://www.ssrn.com/http://www.ssrn.com/http://www.icai.org.in/resource_file/11054p449-oct04http://www.bseindia.com/http://www.economictimes.com/

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