1. A
REPORT
ON
ANALYSING THE EFFECT OF EXCHANGE RATE ON THE
STOCKS OF IT & ITES SECTOR IN INDIA
BY
VISHAL UGLE
2004S3P3563
Submitted in partial fulfillment of the course
ECON GC 491
SPECIAL PROJECTS
Under the guidance of
Dr.G.V.KUMARI
BITS- PILANI, GOA CAMPUS
April,2008
1

2. BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE
Special Projects: ECON GC 491
Station: BITS Pilani, Goa Campus
Duration: 120 Days
Date of Submission: 25 April 2008
Title of the Report: ANALYSING THE EFFECT OF EXCHANGE RATE ON
THE STOCKS OF IT & ITES SECTOR IN INDIA
Name of Faculty: Dr.G.V.Kumari
Faculty-In-Charge: Dr.Joy Anuradha
Signature:
2

3. Acknowledgement
I am deeply indebted to the BITS administration for giving such an opportunity to get exposed to
the practical application of the things learnt in the disciplinary courses, through this Special
Projects course.
I express my sincere thanks and profound sense of gratitude to my instructor Dr.G.V.Kumari for
rendering her full support and cooperation to this project, the Instructor-in-charge Dr.Joy
Anuradha
for
giving
us
an
opportunity
3
to
do
this
project
.

4. Abstract:
This report is divided in to two parts ,part1 gives a brief overview of the performance of the Indian IT
sector in the recent past ,its growth and its contribution to the GDP and exports.
In part2 relationship between CNXIT Index and exchange rates in India has been examined by using
monthly data form January 1997 to February 2008. The time series data of exchange rates and the Index
were tested for non stationary by running Dickey Fuller test, ACF and PACF. Exchange rates were found
to be non stationary while the IT Index was stationary, the logarithm of exchange rates and CNXIT were
non stationary. Hence, the two can be tested for co integration. The residuals of the regression of the
logCNXIT and logER were found to be stationary hence they are not co integrated.
4

5. TABLE OF CONTENTS
PART 1: PERFORMANCE OF IT AND ITES SECTOR IN INDIA
1.1 Introduction
7
PART 2: TESTING FOR COINTEGRATION BETWEEN CNXIT INDEX AND
EXCHANGE RATES FOR THE YEARS 1997-2008
2.1 Literature review of articles referred
2.2 Methodology
2.3 CNXIT index
2.4 Exchange rate
2.5 Basic concepts
2.6 Testing for non stationarity
2.7 Tools used for the test
2.8 Source of data
2.9 Results for unit root tests
2.10 Results for cointegration
12
13
13
14
14
16
16
16
17
20
References
24
5

6. PART1
PERFORMANCE OF THE IT & ITES SECTOR IN
INDIA
6

7. 1.1 Introduction:
The vision of Information Technology(IT) policy is to use IT as a tool for raising the living
standards of the common man and enriching their lives. Though, urban India has a high internet
density, the government also wants PC and Internet penetration in the rural India. In Information
technology (IT), India has built up valuable brand equity in the global markets. In IT-enabled
services (ITES), India has emerged as the most preferred destination for business process
outsourcing (BPO), a key driver of growth for the software industry and services sector.
India's most prized resource in today's knowledge economy is its readily available technical work
force. India has the second largest English-speaking scientific professionals in the world, second
only to the U.S.
According the data from ministry of communication and information technology, the ITES-BPO
industry has grown by about 54 per cent with export earnings of US$ 3.6 billion during 2003-04.
Output of the Indian electronics and IT industry is estimated to have grown by 18.2 per cent to
Rs. 1,14,650 crore in 2003-04.
The share of hardware and non-software services in the IT sector has declined consistently every
year in the recent past. The share of software services in electronics and IT sector has gone up
from 38.7 per cent in 1998-99 to 61.8 percent in 2003-04. However, there has been some
welcome acceleration in the hardware sector with a sharp deceleration in the rate of decline of
hardware's share in electronics and IT industry. Output of computers in value terms, for example,
increased by 36.0, 19.7 and 57.6 per cent in 2000-01,2002-03,and2003-04,respectively.
All the sub-sectors of the non-software component of electronic and IT industry grew at over 8
per cent in 2003-04, but this was far below the rate of growth of software services. Overall, after
7

8. declining precipitously from 61.4 per cent in 1998-99 to 40.9 percent in 2001-02, the share of
hardware in this important industry declined only marginally to 38.2 percent in the two
subsequent
years.
Export markets continue to dominate the domestic segment. The size of the domestic market in
software relative to the export markets for Indian software, which was 45.2 percent in 1998- 99,
after declining rapidly to 29.8 percent in 2001-02, fell only to 29.1 percent and 27.7 per cent in
the two subsequent
years.
Value of software and services export is estimated to have increased by 30 percent to US$12.5
billion in 2003-04. The Software Technology Parks of India have reported software exports of
Rs. 31,578 crore (US$ 6,947 million) during April - December 2004- 05 as against Rs. 22,678
crore (US$ 4,913) during the corresponding period lastyear.
The annual growth rate of India's software exports has been consistently over 50 percent since
1991. No other Indian industry has performed so well against the global competition. According
to a NASSCOM-McKinsey report, annual revenue projections for India’s IT industry in 2008 are
US $ 87 billion and market openings are emerging across four broad sectors, IT services,
software products, IT enabled services, and e-businesses thus creating a number of opportunities
for Indian companies. In addition to the export market, all of these segments have a domestic
market component as well.
The IT-enabled service industry in India began to evolve in the early nineties when companies
such as American Express, British Airways, GE and Swissair set up their offshore operations in
India.
The Indian software and services export is estimated at Rs 103200 crore (US$ 23.4 billion) in
2005-06, as compared to Rs 80180 crore (US$ 17.7 billion) in 2004-05, an increase of 32 per
8

9. cent in dollar terms.. The production of the Indian electronics and IT industry is estimated at Rs
185660 crore during 2005-06, as compared to Rs 152420 crore during the year 2004-05, a
growth of 21.8 per cent. The Industry’s contribution to the national GDP has risen from 1.2 per
cent during the year 1999-2000 to a 4.8 per cent during 2003-04.
Latest data (2006-07) of export of Services for India available mainly by broad categories shows
the high growth of miscellaneous services (including software services and business services)
which grew by 70.5% in 2004-05 and further by 47.6% in 2005-06 and 35.9% in 2006-07 . The
major category of export of services of India is the miscellaneous services category with a share
of 76.7% in total services exports in 2006-07. While software services is the major item under
miscellaneous services exports, since 2003-04, non-software miscellaneous services exports have
grown rapidly almost equaling the value of software services exports. The major contributors
among non-software miscellaneous services are business services (75.5% share and 82.4%
growth) and financial services (10.3% share and 88.6% growth).
9

10. Some more details are available for computer services exports of India as a result of the RBI’s
‘Survey on Software and IT services exports, 2002-03’ which shows that almost 50 per cent of
the companies reported ‘Development, production, supply and documentation of customized
software, including operating systems made on order for specific users’ as one of their activities
while the activity of ‘Analysis, design and programming of systems ready to use (including web
page development and design), and technical consultancy related to software’ occupied second
position with a share of 42 per cent as one of the activities of the companies. Majority of the
computer services exports were made to USA, Canada and Europe accounting for around 87 per
cent of total computer services exports. Exports toAsian countries were only around 9 per cent
of the total computer services exports. About 53 per cent of the computer services exports were
offshore exports, while the rest were onsite exports.
Today a large number of foreign affiliates operate IT-enabled services in India. The different
service lines of It enabled services off shored to India include customer care, finance, human
resources, billing and payment services, administration and content development.
10

11. PART2
TESTING FOR COINTEGRATION BETWEEN CNXIT
INDEX AND EXCHANGE RATES FOR THE YEARS
1997-2008
11

12. 2.1 Literature review of the articles referred
We had referred the following research papers for conducting the above mentioned tests for co
integration
Relationship Between Exchange Rates and Stock Prices Empirical Evidence from Bahrain’s
Financial Markets by Rizwan Tahir, Ahmed Abdul Ghani
The Relationship Between Exchange Rates and Stock Prices, A causality analysis by Saadet
Kasman
Volatility Spillover between the Stock Market and the Foreign Market in Pakistan by Abdul
Qayyum and A. R. Kemal
The above mentioned papers had followed the methodology of checking the relevant time
series data for non stationarity using the Dickey Fuller and Advanced Dickey Fuller tests,if
the tests were positive for non stationarity then they were tested for co integration by
regressing the variables and testing the residuals of the regression for non stationarity.If the
residuals were stationary ,the two series are co integrated and those are tested for causality
relationship using Engle Granger tests and EGARCH models.
12

13. 2.2 Methodology:
The basic steps for testing co integration for time series data involves first checking it for non
stationary, before describing the method in detail , we have mentioned few basic concepts and
the details regarding the variables exchange rate and CNXIT Index.
2.3 CNX IT Index
Information Technology (IT) industry has played a major role in the Indian economy during the
last few years. A number of large, profitable Indian companies today belong to the IT sector and
a great deal of investment interest is now focused on the IT sector. In order to have a good
benchmark of the Indian IT sector, IISL has developed the CNX IT sector Index. CNX IT
provides investors and market intermediaries with an appropriate benchmark that captures the
performance of the IT segment of the market .
Companies in this Index are those that have more than 50% of their turnover from IT related
activities like software development, hardware manufacture, vending, support and maintenance.
The Index is a market capitalization weighted Index with its base period being December 1995
and the base date and base value being January 1, 1996 and 1,000 respectively.
The Base Value of the Index is being revised from 1000 to 100 w.e.f. 28 May 2004.
Selection of the Index set is based on the following criteria:
1. Company's market capitalization rank in the universe should be less than 500
2. Company's turnover rank in the universe should be less than 500
3. Company's trading frequency should be at least 90% in the last six months
4. Company should have a positive net worth.
13

14. 5. A company which comes out with an IPO will be eligible for inclusion in the Index, if it
fulfills the normal eligibility criteria for the Index for a 3 month period instead of a 6
month period.
2.4 Exchange rate:
The exchange rate is considered to be the ratio of US dollar to Indian Rupee. The monthly
average for each month from Jan 1997 to Feb 2008 is calculated and used. The logarithm of
exchange rate is used for checking for unit root
2.5 Basic concepts:
Co-integration and error correction modeling technique involves three main steps. Testing the
relevant time series for stationarity (unit roots), testing for co-integration, and finally errorcorrection modeling. We shall use standard textbook notation to explain briefly the steps
involved.
A non-stationary time series Yt is said to be integrated of order d, [Yt ~ I(d)], if it achieves
stationarity after being differenced d times. To determine the order of integration, unit root tests
have been developed. The most common test is known as Dickey-Fuller (DF) or Augmented
Dickey-Fuller (ADF). To discuss the DF test, consider the model
Yt = β0 + β1t + ut
ut = αut-1 + εt
where εt is a covariance stationary process with zero mean. The reduced form for this model is
Yt = γ + δt + β1t + αYt-1 + εt -------------------------------------------------------------- (1)
14

15. Where γ = β0 (1 – α) + β1α and δ = β1 (1 – α). This equation is said to have a unit root if α = 1. The DF
test is based on testing the hypothesis α = 1 in (1) under the assumption that ε t are white noise errors. The
test statistics are:
k(1) = T(ά – 1)
t(1) = (ά – 1)/SE(ά)
Since these statistics do not have a standard t distribution, the critical values for k(1) and t(1) are tabulated
in Fuller (1976).
Suppose that Yt ~ I(d) and Xt ~ I(d). Then Yt and Xt are said to be co-integrated if there exists a β such
that Yt - β Xt is I(d-b) and b > 0. Thus testing for co-integration one must make sure that both series are
integrated of the same order in first step. Second step then involves estimating the following cointegration equation by Ordinary Least Squares (OLS):
Yt = a0 + bo Xt + μt ---------------------------------------------------------------------------(2)
X t = a0 + bo Yt + μ′t --------------------------------------------------------------------------- (3)
And testing for the stationarity of the residuals from Equations 2 & 3 to make sure that μt and μ′t
are I(d-b), b > 0.
If two variables are co-integrated, then the third step involves formulating the error-correction
model (ECM) as follows:
n
(1 L)Yt
C0
d0
n
eoi (1 L) Yt
t 1
f oi (1 L) X t
i
i 1
n
(1 L) X t
C1
d1
i 1
t
n
e1i (1 L) X t
t 1
i
(4)
i 1
f 1i (1 L) Yt
i
i
t
(5)
i 1
where L is the lag operator and the error correction terms (ECTs) μt and μ′t are the stationary
residuals from co-integration Equations 2 and 3, respectively. According to the standard Granger
15

16. causality test, X is said to Granger cause Y if foi’s are jointly significant. The inclusion of ECTs,
however, provide additional channel through which the Granger causality could be detected.
Thus, X is said to Granger cause Y, as long as the ECT carries a significant coefficient even if
foi’s are not jointly significant.
2.6 Testing for non stationarity:
We had conducted the following tests on the data to check for non stationarity.
1. Philips -Perron test which incorporates both Dickey Fuller and Advanced Dickey fuller
test
2. We have generated the autocorrelation and partial autocorrelation function for the data to
check for non stationarity.
2.7 Tools used for the tests:
The following software tools were used for performing tests
1. R- programming ,a statistical software for conducting PP test
2. Minitab14.0 for generating ACF and PACF
3. Microsoft Excel for storing data
2.8 Source of data:
The primary source of data was internet, the following links were used
1. www.nse.org.in for CNX IT Index
2. http://www.oanda.com/convert/fxhistory for exchange rates
16

17. 2.9 Results for the Unit Root tests
For CNX IT Index
1. Philips-Perron test
Data: logCNXITIndex_ts
Dickey-Fuller = -3.1783,
Truncation lag parameter = 4,
p-value =0.09471
2. Autocorrelation function and partial autocorrelation function
Autocorrelation Function for LOG NORMALIZEDCNXIT
(with 5% significance limits for the autocorrelations)
1.0
0.8
Autocorrelation
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
Lag
17
25
30

18. Partial Autocorrelation Function for LOG NORMALIZEDCNXIT
(with 5% significance limits for the partial autocorrelations)
1.0
Partial Autocorrelation
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
25
30
Lag
For Exchange rate:
1. Philips-Perron test
Data: logEr_ts
Dickey-Fuller = -2.2296, Truncation lag parameter = 4, p-value = 0.4811
2. Autocorrelation function and partial autocorrelation function
18

19. Autocorrelation Function for log ER
(with 5% significance limits for the autocorrelations)
1.0
0.8
Autocorrelation
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
25
30
Lag
Partial Autocorrelation Function for log ER
(with 5% significance limits for the partial autocorrelations)
1.0
Partial Autocorrelation
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
Lag
19
25
30

20. Conclusions:
The following conclusions can be drawn
Series
p-value
conclusion
logCNXIT
0.09471
Non stationary
logEr
0.4811
Non stationary
Hence it can be concluded that both the series are non stationary and can be tested for co
integration
2.10 Testing for co integration
To test for cointegration the two series i.e logCNXIT and logER have to be regressed on each
other and the residuals have to be tested for stationarity. The regression equations are as follows
LOG NORMALIZEDCNXIT = - 7.54 + 7.18 log ER ---------------------------------- (1)
log ER = 1.45 + 0.0452 LOG NORMALIZEDCNXIT-----------------------------------(2)
now the residuals of the above regressions have to be tested for stationarity,Philips Perron
test,the ACF and PACF for the residuals of equation (1),(2) are as follows
Phillips-Perron Unit Root Test
data: res_ts
Dickey-Fuller = -2.831,
Truncation lag parameter = 4,
20
p-value = 0.2308

21. Autocorrelation Function for residuals of equation 1
(with 5% significance limits for the autocorrelations)
1.0
0.8
Autocorrelation
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
25
30
Lag
Partial Autocorrelation Function for RESIDUALS OF EQUATION 1
(with 5% significance limits for the partial autocorrelations)
1.0
Partial Autocorrelation
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
Lag
21
25
30

22. Autocorrelation Function for RESIDUALS OF EQUATION 2
(with 5% significance limits for the autocorrelations)
1.0
0.8
Autocorrelation
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
25
30
Lag
Partial Autocorrelation Function for RESIDUALS OF EQUATION2
(with 5% significance limits for the partial autocorrelations)
1.0
Partial Autocorrelation
0.8
0.6
0.4
0.2
0.0
-0.2
-0.4
-0.6
-0.8
-1.0
1
5
10
15
20
Lag
22
25
30

23. Conclusions:
Series
p-value
conclusion
Residuals of regression
of equation 1,2
0.2308
Non stationary
It can be seen from the PP test results and the above graphs that the residuals are non stationary.
Hence, we conclude that both the series are not co integrated ,therefore we cannot perform the
Error correction Modeling to know the causality relationship.
23

24. References:
Relationship Between Exchange Rates and Stock Prices Empirical Evidence from Bahrain’s
Financial Markets by Rizwan Tahir, Ahmed Abdul Ghani
The Relationship Between Exchange Rates and Stock Prices, A causality analysis by Saadet
Kasman
Volatility Spillover between the Stock Market and the Foreign Market in Pakistan by Abdul
Qayyum and A. R. Kemal
Gujrati ,Basic econometrics 4th edition
Chandan sen gupta ,Financial Modeling using Excel
www.nse.org.in
http://www.oanda.com/convert/fxhistory
http://india.gov.in/sectors/communication/index.php
www.eximbank.in
Stock Prices and Exchange Rates: Are they Related? Evidence from South Asian Countries
By Naeem Muhammad and Abdul Rasheed
24

25. 25