CONTRIBUTOR NAME: DR. DEEPAK JAIN
Research Paper
on
“EFFECTS OF FLUCTUATION IN DOLLARS ON IT COMPANIES”
AREA: FINANCE
DESIGNATION:
LECTURER (MARKETING),
COLLEGE OF MANAGEMENT,
SCHOOL OF BUSINESS,
SHRI MATA VAISHNO DEVI UNIVERSITY, J&K, INDIA
POSTAL ADDRESS:
DR. DEEPAK JAIN (LECTURER)
C/o SH. S.K. JAIN,
64/2, K.K. GUPTA LANE,
TRIKUTA NAGAR, JAMMU TAWI (J&K) – 180018
EMAIL ADDRESS: deepakjain274191629@yahoo.co.in
PHONE NUMBER: 09419112922
EFFECTS OF FLUCTUATION IN DOLLARS ON IT COMPANIES
Dr. Deepak Jain (Lecturer, Shri Mata Vaishno Devi University, J&K, INDIA)
Exchange rate is a key determinant in international finance and turning of world into a Global village.
Different factors at macro-economic environment were identified and studied that affects demand and
supply of a currency and in return affects the exchange rate. Some identified factors are: Interest Rates,
Rate of Inflation, Political or Military Unrest, Domestic Financial Market, Strong Domestic Economy,
Business Environment, Stock Markets, Economic data, Balance of trade, Government budget
deficits/surpluses, and Rumours. Recently another factor added is “Terrorism”.
Paper discusses the merits and demerits of rupee getting appreciated or depreciated. The main reason for
the INR's appreciation since late 2006 has been a flood of foreign-exchange inflows, especially US
dollars. The paper tries to identify the correlation between fluctuations of exchange rate on turnover of
Indian based IT companies. Analysis was conducted on 12 different Indian IT companies. As the
objective is to find out whether the fluctuation in exchange rate of dollars affects the turnover of the IT
sector, correlation technique was used.
Positive correlation is seen between the fluctuations in Exchange rate of dollars (acting as independent
variable) and revenue value (acting as dependent variable) as the average correlation value of 12 IT
companies is 0.690423305 which is higher than 0.5 representing the overall impact of exchange risk on
IT industry. The companies are not seems to be taking hedging risk cover which is reflected in their
decrease in revenues.
Keywords
Exchange Rate, Forex Markets, Inflation, Demand & Supply, Revenue, Turnover, RBI, US$, Interest
Rates, Currency, Stock Markets, and Economies etc.
Introduction
Exchange rate is a key determinant in international finance and turning of world into a Global village has
just made this variable all the more important. Forex markets have undergone many changes from setting
up of Bretton Woods System in 1944 according to which each country had to fix its currency exchange
rate plus or minus 1 percent to its abandonment in 1984 due to increased Balance of Trade deficit of U.S.
Then it has witnessed East Asian crisis of 1997 when majority of the currencies of East Asian countries
depreciated.
Now most of the countries follow a free floating exchange rate system. India's approach can be
characterized as intermediate since it follows a system between a freely floating and fully managed
system. This type of system is known as managed float system. Exchange rates are allowed to float freely,
but RBI intervenes when it feels necessary in the way it considers suitable. For e.g. in order to curb
appreciation of INR, it may buy US$ from the market or it may increase the interest rates.
Price determination
The Forex market like any other market is essentially governed by the law of supply and demand.
According to the law of supply, as prices rise for a given commodity (in this case currency), the quantity
of the item that is supplied will increase; conversely, as the price falls, the quantity provided will fall. The
law of demand states that as the price for an item rises, the quantity demanded will fall. As the price for
an item falls, the quantity demanded will rise. In the case of currency, it is the demand and supply of both
domestic and foreign currency that is considered. It is the interaction of these basic forces that results in
the movement of currency prices in the Forex market.
Factors affecting the demand and supply
There are various factors in a macro-economic environment which affect the demand and supply of a
currency and in return affects the exchange rate.

Interest Rates
If there are higher interest rates in home country then it will attract investments from abroad in
the form of FII, FDI and increased borrowings. This leads to increased supply of foreign
currency. On the other hand, if the interest rates are higher in the other country, investments will
flow out leading to decreased supply of foreign currency.

Rate of Inflation
If inflation rates are high, central bank will have to reduce the supply of domestic currency in
order to curb it. This would ultimately lead to strong currency and vice versa.

Political or Military Unrest
All exchange rates are susceptible to political instability and anticipations about the new
government. All the market players get worried about the policies and may start unwinding their
positions thereby affecting the demand and supply.

Domestic Financial Market
Strong domestic financial markets will also lead to the strengthening of domestic currency as
investors will be less worried about their investments and vice versa.

Sound Domestic Economy
If the domestic economy is strong then there will be lots of investments from abroad which will
lead to increased supply of foreign currency, ultimately leading to strengthening of domestic
currency; and vice versa is also true if there domestic economy is weak.

Business Environment
Positive indications (in terms of government policy, competitive advantages, market size, etc.)
increase the demand for currency, as more and more enterprises want to invest there. Any
positive indications abroad will lead to strengthening of foreign currency.

Stock Markets
The major stock indices also have a correlation with currency rates as investors link the growth in
markets to the economic growth of a country.

Economic data
Economic data such as labour reports (payrolls, unemployment rate and average hourly earnings),
Consumer Price Indices (CPI), Gross Domestic Product (GDP), International Trade, Productivity,
Industrial Production, Consumer Confidence etc, also affect fluctuations in currency exchange
rates.

Balance of trade
If the exports to other countries are more than the exchange rate will be stronger as there will be
inflow of foreign currency. More one relies on imports, weaker will be the exchange rate because
there will be outflow of domestic currency. A large, consistent government deficit will lead to
outflow of domestic borrowing.

Government budget deficits/surpluses
If a government runs into deficit, it has to borrow money (by selling bonds). If it can't borrow
from its own citizens, it must borrow from foreign investors. That means selling more of its
currency, increasing the supply and thus driving the prices down.

Rumours
Any rumour in the markets also leads to fluctuation in the values. Any favourable news will lead
to strengthening of domestic currency and any negative rumour will lead to weakening of the
currency.

Terrorism
Instances of Afghanistan war and 9/11 attack on World Trade Centre of America affected the
trades between America and Asian countries.
To understand how the currency risk plays out, let us consider a hypothetical outsourcing contract
between a US based buyer (functional currency is US$) and a supplier with India based service delivery
(functional currency is INR) with the following contract specifics:
 Start date: 2003
 Term of contract: 5 years

Total Contract Value (TCV): US$50 million with equal annual payouts
Let us assume for the sake of simplicity, that the supplier bears all the currency exchange risk. Under
such a scenario, the supplier in 2003 is facing five years of paying out wages and other costs in INR;
therefore, the supplier is "short" the rupee. At the same time, the supplier is holding an accounts
receivable of five years of revenues in dollars; therefore, it is "long" the dollar. Being long the dollar and
short the rupee, the supplier is hurt when the rupee rises relative to the dollar. Given the rupee
appreciation that we have seen over the last five years, under such an agreement, the supplier would have
experienced INR 94 million currency exchange loss if you compare the actual realized fee versus the
expected supplier fees. This translates into a net negative currency impact of four percent on the top line
(see Exhibit 1).
Exhibit 1: Impact of rupee appreciation on supplier fees (hypothetical case)
This is a lose-lose situation for the buyer and supplier because while the buyer pays out as per the
contract, the supplier margins are hurt, which may result in a drop in quality of service and lack of
investment in continuous improvement.
In 1999, Goldman Sachs (BRIC Report) predicted that India's GDP at current prices will overtake that of
France and Italy by 2020 and that Germany, UK and Russia by 2025. By 2035, India is expected to be of
3rd largest economy in the world behind US and China overtaking Japan. Goldman Sachs had made these
predictions based on India's expected growth rate of 5.3% to 6.1% in various periods in the past, at
present India is registering 8.6% growth rate. Jim O'Neal, head of the Global Economics Team at
Goldman Sachs, had said on the BBC, "In thirty years, India's workforce could be as big as that of the
United States and China combined". He added that "India could overtake Britain and be the world's fifth
largest economy within a decade as the country's growth accelerates".
Presently, India is the third largest economy in the world as measured by Purchasing Power Parity (PPP)
and twelve largest in the world as measured in US$ exchange-rate terms, with a GDP of US $1.0 trillion.
Amongst the major economies of the world, India is the second fastest growing economy with a GDP
growth of 9.4% for fiscal year 2006-2007 and 8.6% in current year. The main reason for this is its diverse
economy which encompasses agriculture, handicrafts, textile, manufacturing and a multitude of services.
However, the BRIC (Brazil, Russia, India, China) report ignored the effect of rapid decline in Purchasing
Power Parity ratios of economies as they approach maturity, resulting in PPP that eventually tends toward
1.0 (as compared to nearly 5.0 for India and China in this current year i.e. the value of 1 US$ in India and
China after conversion into local currency at currency exchange rates was 5 times of that in the US due to
their cheaper currencies).
This decline is attributed to the following:
 Inflation
 Appreciation of the local currency
Normally, currencies appreciate when the economies are doing well and the rise in their value is a cause
for celebration. The high value of the Deutsche Mark when Germany was the trendsetter for the world
economy in the 1960s and the 1970s, the high value of yen in the 1980s when Japan seemed set to take
over the world and the dollar's high value in the late 1990s when the US economy brooked no
competition were sources of immense pride for their respective countries.
The Indian journey from 1990s to the mid 2000s:
The Indian rupee (INR) has appreciated by nearly 10% since late 2006, posing an acute dilemma for
Indian policymakers. In some ways, the present strength of the currency, this is now hovering just above
the symbolic Rs. 40: US $1 exchange rate is an enviable position. It suggests that the country's
attractiveness to foreign investors is increasing and signals optimism about the future of Indian economy
in general. However, the concerns of export intensive corporations, who have a crucial role of India's
economic resurgence, and whose goods become more and more expensive for overseas buyers need to be
examined critically and addressed in a timely and effective manner.
The recent strengthening of the rupee is a dramatic departure from the past trends. The currency
depreciated steadily for a decade after being floated in 1993, dropping from an average annual rate of Rs.
31.37: US $1 in the 1993-94 fiscal years (April-March) to Rs. 48.40: US $1 in 2002-03 (an average
annual depreciation of nearly 5%). Between 2003-04 and 2005-06, however, the rupee appreciated
against the dollar by 3% an on average a year—although there was considerable two-way
movement of the rupee from month to month. The trend of steady month-on-month appreciation
began in September 2006 and has been continuous since then.
Although the Indian rupee-US dollar exchange rate has a significant impact on the Indian economy and
business sector, the rupee has also appreciated against other currencies as well. In January-July 2007, the
rupee's value in terms of Pounds, Euros and Yen rose by 8%, 6.9% and 11.2%, respectively. According to
the Reserve Bank of India (RBI) during 2005-06, 86% of Indian exports and 89% of imports were
invoiced in US dollars. The Euro was a distant second, with shares of 8% in exports and 7% in imports.
Background for Research Work
Introduction
The global devaluation of the U.S. dollar against other currencies is a major cause of concern for the
outsourcing industry all over the world. The impact of the weakening of the dollar against currencies of
major outsourcing destinations, particularly India, has actually overshadowed other serious concerns like
wage inflation. Let us review the impact of these currency movements and wage inflation on the
outsourcing business in leading offshore destinations.
India
The Indian rupee has significant strengthened over the last year against the U.S. dollar, falling from 45
rupees to 39 rupees per dollar. This huge strengthening of 13 percent coupled with significant pay
increases has shaved part of the Indian cost advantage. Further, most economists are expecting further
strengthening of the Indian rupee in 2008, which not happened because of world recession.
The outsourcing businesses hit hardest by the dollar's slide as small and midsize Indian programming
companies not have any option of shifting work around the world. Many of them work with a limited
number of clients under contracts often fixed at rates for a year or more.
The rupee appreciation impacts BPO companies more than it does to IT companies. One percent rise in
the value of the rupee against the dollar has a 75 to 80 basis points impact on the operating margins for
BPO companies, unlike IT companies where the impact is about 40 basis points. This is due to the fact
that a significant chunk of expenses for BPO companies remain in India while IT companies have some
expenses in dollars due to onsite sales force and development centres in other countries.
Many North American and European companies that started their own offshore set-up in India to lower
the cost of product development or back-office struggled due to spiralling costs, rising attrition, lack of
integration and management support. In fact, the rupee's appreciation against the dollar has claimed its
first victim in the business process outsourcing space. US-based Spectrum Global Fund Administration
that provides back-office operations to hedge funds in the U.S. and the U.K. is closing its facilities in
India. The company had started its operations there only two years ago.
In an effort to combat these threats, Indian outsourcing giants in the technology sector, such as Tata
Consultancy Services, Wipro and Infosys Technologies, hedged their bets by expanding in countries such
as China where costs are lower. Further, these companies expanded business with European and Latin
American countries whose currencies stayed relatively stable compared with the rupee. Indian IT giants
had already set up base in Latin American and East European nations to capture the emerging near
shoring trend.
The domestic IT-BPO firms have devised
many strategies to combat the approximately
15 percent annual climb in wages. Some of
the strategies include hiring fresher’s, students
with
non-engineering
backgrounds,
establishment of operations in tier-II and tierIII cities, increased billing and employee
utilization rates, and improving the business
mix to increase productivity and to beat the
heat of the rising salaries. Industry analysts
believed that with these strategies, coupled
with an indexed wage differential, the ITBPO firms should be able to retain their
competitive edge in outsourcing for at least
another 10-15 years.
The currency appreciation of major outsourcing destinations is indeed a cause of concern and is expected
to erode the attractiveness of these destinations as a preferred outsourcing destination. The currency
appreciation, coupled with wage inflation in many of these destinations, has already started taking its toll
on both large and small players in IT and BPO industries. Leading companies in these nations have
already started establishing new centers in nations where wage growth is still under control and currency
movements are relatively stable. Although countries like India still hold an advantage over others, the
forecasted trend of the weakening dollar and spiraling salaries does not provide a good picture for these
outsourcing destinations.
Objectives of Study
1. To find out the reason behind the fluctuation in dollars by studying the past trend.
2. To find out whether the fluctuation in dollars over rupee affects revenue turnover of IT
companies, or not.
3. To find whether the hedging technique can proves as solution in handling the exchange financial
risks in the IT industry.
Time period considered to study
Time period taken into consideration is from April 2006 to October 2007. There are mainly three reasons
behind choosing the time period:

2008 world recession impacted the trade, globally. India does not enjoy any exemption from
impact of world recession.

Time period considered had seen extremes value of dollar, highest of Rs. 46.5 as well as lowest
of Rs. 39.5.

As we know that the exchange risk is not only the factor affecting the revenues of export
companies. There are many factors contributing the shrinkage of revenue of IT firms already
explained that affects value of revenue generation in different period of time. In selected period,
almost all the IT companies showed similar kind of revenue generation.
Research Methodology
Research Design
Research design can be defined as the plan and structure of inquiry, formulated in order to obtain answer
to research question on business aspects. It constitutes the overall program of the business research
process. Research design used in this research work is both exploratory and causal research.
Exploratory research design is used to answer the Objective Number 1:
 To find out the reason behind the fluctuation in exchange rate by studying the past trend.
Causal research design is used to answer the Objective Number 2:
 To find out whether the fluctuation in exchange rate affects revenue turnover of IT company,
or not.
Dependant and independent variables:
A variable is a concept that take on different quantitative values like height, weight, age and so on. If a
variable is dependent on the result of some other variable it is then called a dependent variable. An
independent variable is one that is not dependent on any other variable with reference to that particular
study. In this paper, independent variables are fluctuation in exchange rate of dollor and the dependent
variable is the foreign revenue turnover in Rupee.
Nature of Data
Research is based on secondary data available in form of books, articles, jounals and stock indexes. 12
india based IT companies were surveyed to answer the Research Objective No.: 2
As the objective is to find out whether the fluctuation in exchange rate affects the revenue turnover of
the IT sector, correlation technique was used for data analysis.
Objective1: To find out the reason behind the fluctuation in dollars by studying the past trend.
Consider a situation where an Indian company moves in software deal with American company, America
based company will pay $100 billion (Rs. 1000 crore in Indian currency). It must be noted that when they
entered in deal, the exchange rate value of $1 was Rs. 46.
After 1 year, at the time of delivery of software, rupees appreciates against dollar, assume $1 = Rs. 42.
Based on current exchange rate, Indian company will receive amount less by 4000 Cr. and suffers heavy
Losses. Inference is drawn that rupee appreciation will create loss for Indian based software company.
Reason why the Indian rupee appreciated?
The main reason for the INR's appreciation since late 2006 has been a flood of foreign-exchange inflows,
especially US dollars. The surge of capital and other inflows into India has taken a variety of forms,
ranging from FDIs to remittances sent home by Indian expatriates. In each case, the flow seems unlikely
to slacken. The main impact of these various types of flows is examined below:

Foreign Direct Investment (FDI)
India's outstanding economic growth has created a large domestic market that offers promising
opportunities for foreign companies. Moreover, the country's rising competitiveness in many
sectors has made it an attractive export base. These factors have boosted FDI inflows into the
country. For example, in 2006-07, FDI amounted to around US $16bn, almost three times the
previous year's figure. More than half of these inflows arrived in the final four months of the
fiscal year (December 2006-March 2007).

External Commercial Borrowings (ECBs)
Indian companies have borrowed enormous amounts of money overseas to finance investments
and acquisitions at home and abroad. India's balance-of-payments data reveals that inflows
through ECBs amounted to an enormous US $12.1bn during April-December 2006, a year-onyear jump of 33%. The flood of borrowed money is likely to grow in 2007. In the first three
months of the year, Indian companies have notified the RBI of their plans to raise nearly US
$10bn in overseas debt markets.

Foreign portfolio inflows
India's booming stock market embodies the confidence of investors in the country's corporate
sector. Foreign portfolio inflows have played a key role in fuelling this boom. Between 2003-04
and 2006-07, the net annual inflow of funds by Foreign Institutional Investors (FIIs) averaged US
$8.1bn. Trends during the first five months of 2007 indicate that this flood is continuing, with net
FII inflows amounting to US $4.6 billion. Another major source of portfolio capital inflows has
been overseas equity issues of Indian companies via Global Depositary Receipts (GDRs) and
American Depositary Receipts (ADRs). Inflows from GDRs and ADRs amounted to US $3.8bn
in 2006-07, a year-on-year increase of 48%.

Investments and remittances
Indians settled in other countries have also been a major source of capital inflows, with many
non-resident Indians (NRIs) investing large amounts in special bank accounts. While NRIs
emotional connection to their country of origin is part of the explanation for this, the attractive
interest rates offered on such deposits have also provided a powerful incentive. In 2006-07, NRI
deposits amounted to US $3.8bn, a 35% increase over the previous year; the outstanding value of
NRI deposits as of end-March 2007 was US $39.5bn. Another large source of foreign-exchange
inflows has been remittances from the huge number of Indians working overseas temporarily.
Such remittances amounted to a colossal US $19.6bn in April-December 2006, a 15% year-onyear increase.
Is it is advantageous to have appreciating rupee always?
No it is not always advisable to have always appreciating rupee. It must be another way round also.
Reasons why it is preferred to have appreciating rupee value.

Foreign debt service
Appreciation of the rupee helps in easing the pressure, related to foreign debt servicing (interest
payments on debt raised in foreign currency), on India and Indian companies. With Indian
companies taking advantage of the United States soft interest rate regime and raising foreign
currency loans, known as external commercial borrowings (ECBs), this is a welcome
phenomenon from the point of view of their interest commitments on the loans raised. This will
help them avoid taking a bigger hit on their bottom-line, which is beneficial for its shareholders.

Outbound tourists/student bonanza
The appreciating rupee is a big positive for tourists travelling or wanting to travel abroad.
Considering that the rupee has appreciated by over 10% against the US dollar since mid-2002,
travelling to the US is now cheaper by a similar quantum in rupee terms. The same applies to
students who are still in the process of finalizing their study plans abroad. For example, a
student's enrolment for a $1,000 course abroad would now cost only Rs.44, 000 instead of the
earlier Rs 49,000.

Government reserves
Considering that the government has been selling its stake aggressively in major public sector
units in the recent past, and with a substantial chunk of this being subscribed by FII’s, the latter
will have to invest more dollars to pick up a stake in the company being divested, thus aiding the
governments build up of reserves.
Reasons why it is not preferred to have appreciating rupee value.

Exporters' disadvantage
The exporters are at a disadvantage owing to the currency appreciation as this renders their
produce expensive in the international markets as compared to other competing nations whose
currencies haven't appreciated on a similar scale. This tends to take away a part of the advantage
from Indian companies, which they enjoy due to their cost competitiveness. However, it must be
noted that despite the sharp currency appreciation in recent times, Indian exports have continued
to grow. This is vindicated from the fact that while in the month of February 2004, India's exports
were higher by 35% over the same month previous year, in the first 11 months of the current
fiscal, Indian exports have been higher by 15% year-on-year.

Dollar denominated earnings hurt
The strengthening rupee has an adverse impact on various companies/sectors, which derive a
substantial portion of their revenues from the US markets (or in dollar denominations). Software
and BPO are typical examples of the sectors adversely impacted by the appreciation of rupee.
Data Analysis & Interpretations
Figure1: Variation in Value of Rupee Against $
48
Ruppee per 1USD
46
44.9
45.4
46
46.2
46.5
45.7
45.5
44.9 44.8
44.3 44.2
44
44
42.2
42
40.7
40.8
40.4
40.8
40.3
40
39.5
38
36
Months
Figure2: Aftek Computers Ltd.
1.6E+10
13799140987
1.4E+10
Turnover in Ruppees
1.2E+10
12008705530
10979944048
10985709752
9660232171
1E+10
9530559432
8E+09
7631264173
6465767812
6E+09
4627487104
4E+09
3937612119
2E+09
2107681409
3289317532
3466251344
3067227407
3248718273
2202129447
2210198537
1653055009
0
185596620
Months
Correlations
Exchange
Rate
Revenue
Turnover
Pearson Correlation
Exchange Rate
Revenue Turnover
1
.793**
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.793**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.793.
This infers that revenue turnover of
Aftek Computers is affected by
79.3% because of fluctuation in
exchange rate.
4.5E+10
40396617276
4E+10
Total turnover in (Rs.)
3.5E+10
33052878781
33187016506
3E+10
30176122837
28031574936
25501467909
2.5E+10
2E+10
Figure3: INFOSYS
39096129278
25152130990
19962285896
19343184965
21092246495
19711450578
18684715340
18715493047
1.5E+10
16209046179
13736975830
11781532480
1E+10
10980249385
11630281584
5E+09
0
Months
Correlations
Exchange
Rate
Revenue
Turnover
Exchange Rate
Revenue Turnover
1
.766**
Pearson Correlation
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.766**
Sig. (2-tailed)
.000
N
19
19
1
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.766.
This infers that revenue turnover of
Infosys is affected by 76.7% because
of fluctuation in exchange rate.
19
**. Correlation is significant at the 0.01 level (2-tailed).
Figure4:Tata Consultancy Services
1.2E+10
11358497887
11091703588
Turnovers in Ruppees
1E+10
8E+09
7519573186
6860803142
7257036657
6E+09
6429868218
6276745421
6646799909
5969400779
5545469812
5681572609
4922071205
5547330775
5144670406
4E+09
4434513667
4311629503
3358894818
3046562271
3075678270
2E+09
0
Months
Correlations
Exchange
Rate
Revenue
Turnover
Pearson Correlation
Exchange Rate
Revenue Turnover
1
.797**
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.797**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.797.
This infers that revenue turnover of
TCS is affected by 79.7% because of
fluctuation in exchange rate.
Figure5:Wipro
1.2E+10
1E+10
9732301123
Turnover in (Rs.)
8685955743
8905597889
8683481311
8E+09
7538971790
6040409835
6E+09
5960749713
5126679386
5171470031
4658310328
4627134996
4E+09
5316744258
4186674755
3981111110
2286685248
2726008230
2E+09
2296473466
2159567240
1954909436
0
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
.864**
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.864**
Sig. (2-tailed)
.000
N
19
19
1
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.864.
This infers that revenue turnover of
Wipro is affected by 86.4% because
of fluctuation in exchange rate.
19
**. Correlation is significant at the 0.01 level (2-tailed).
Figure6: Polaris Software Lab Ltd.
4E+09
3560753809
3.5E+09
3E+09
2623231704
Turnover in Ruppees
2.5E+09
2E+09
1.5E+09
1073808544
1177410836
991565269
1E+09
949356636
770635836
991241540
622704766
500000000
689903450
764443258
706222936
574781814
463904206
383430426
389137594
376934053
400005739
294390007
0
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
Sig. (2-tailed)
.528**
.000
N
Pearson Correlation
19
.528**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.528.
This infers that revenue turnover of
Polaris Softwares Lab Limited is
affected only by 52.8% because of
fluctuation in exchange rate.
Figure7: Mastek Softwares Ltd.
3E+10
26593533104
Turnovers in Ruppees
2.5E+10
2E+10
24127075849
22762187906
19029204308
19969849085
18915090909
15684050286
1.5E+10
13886145289
1E+10
8493228790
5E+09
6742531754
4198604793
3442901350
5710470477
2476742597
5563505543
3584450500
2982295897
1048317875
0
895932735
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
.831**
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.831**
Sig. (2-tailed)
.000
N
19
19
1
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover i.e.
0.831.
This infers that revenue turnover of
Mastek Softwares Linited is affected by
83.1% because of fluctuation in
exchange rate.
19
**. Correlation is significant at the 0.01 level (2-tailed).
Figure8: Hexaware Technologies Ltd.
1.2E+10
10152493322
1E+10
8E+09
Turnover in Ruppees
6869243313
6E+09
4575421387
4187626062
4323724483
4E+09
2774140286
2937285474
3721535225
3064409125
2E+09
2444031305
1926790676
2069344239
1815413514
1439809758
1380014996
1032617367
1105012417
709707863
0
528937586
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
Sig. (2-tailed)
.519**
.000
N
Pearson Correlation
19
.519**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.519.
This infers that revenue turnover of
Hexaware Technologies Limited is
affected by 51.9% because of
fluctuation in exchange rate.
Figure9: CMC Ltd.
1.2E+09
1E+09
953061823
Turnover in Ruppees
800000000
600000000
473628558
396202001
400000000
396202001
328644792
200000000
304608913
304608913
257152826
182000421
155946533
182718078
135032798
99088296
111971789
0
58861291
66863191
30520041
84182666
38096352
Months
Correlations
Exchange Rate Revenue Turnover
Pearson Correlation
Exchange
Rate
1
.649**
Sig. (2-tailed)
Revenue
Turnover
.000
N
Pearson Correlation
19
.649**
Sig. (2-tailed)
.000
N
19
19
1
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.649.
This infers that revenue turnover of
CMC Ltd is affected by 64.9%
because of fluctuation in exchange
rate.
19
**. Correlation is significant at the 0.01 level (2-tailed).
Figure10: HCL Technologies Ltd.
9E+09
8E+09
7622917235
7E+09
Turnover in Ruppees
6E+09
4909325131
5E+09
4E+09
3E+09
3634389603
2994952763
3379920881
2972467716
2702600602
2791973878
2289192314
2E+09
1479595919
1436617481
1609597689
1E+09 1025650571
1003803420
1411406404
1253705359
1026296865
1471479728
1000328438
0
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
Sig. (2-tailed)
.418**
.000
N
Pearson Correlation
19
.418**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.418.
This infers that revenue turnover of
HCL Technologies Ltd is affected
by 41.8% because of fluctuation in
exchange rate.
Figure11: Patni Computer Systems (P) Ltd.
2.5E+09
2122549804
Turnover in ruppees
2E+09
1.5E+09 1449344861
1325866099
1E+09
1080244041
877027912
905325178
748022016
799380597
668885137
606912747
500000000
354310391
494344837
401055719
370105529
392206447
217933544
147176569
0
481592551
201861845
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
.710**
Sig. (2-tailed)
.000
N
Pearson Correlation
19
.710**
Sig. (2-tailed)
.000
N
19
19
1
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.710.
This infers that revenue turnover of
Patni Computers (P) Ltd is affected
by 71% because of fluctuation in
exchange rate.
19
**. Correlation is significant at the 0.01 level (2-tailed).
Figure12: Satyam Computer Services Ltd.
4.5E+10
39963498247
4E+10
38530494040
35801602322
3.5E+10
32179872246
Turnover in Ruppees
3E+10
27061354437
25301398938
2.5E+10
24514452394
24648316900
22294443088
22034854910
22034854910
2E+10
19541374597
19373368636
18474826187
1.5E+10
15530498478
14758107133
11957091363
1E+10
13925949228
11555526857
5E+09
0
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
Sig. (2-tailed)
.753**
.000
N
Pearson Correlation
19
.753**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.753.
This infers that revenue turnover of
Satyam Computers Services Ltd is
affected by 75.3% because of
fluctuation in exchange rate.
Figure13: Nucleus Software ltd.
800000000
742495523
704390913
700000000
600000000
504118285
Turnover in Ruppees
500000000
407647674
400000000
300000000
296682811
417249203
392724552
400295832
373941371
332600525
323072635
255675098
200000000
176548950
131199917
99960542
129708800
100000000
111285674
73904590
26576118
0
Months
Correlations
Exchange Rate Revenue Turnover
Exchange
Rate
Revenue
Turnover
Pearson Correlation
1
Sig. (2-tailed)
.657**
.000
N
Pearson Correlation
19
.657**
Sig. (2-tailed)
.000
N
19
19
1
19
**. Correlation is significant at the 0.01 level (2-tailed).
There exists high degree of positive
correlation between fluctuation in
exchange rate and revenue turnover
i.e. 0.657.
This infers that revenue turnover of
Nucleus Software Ltd is affected by
65.7% because of fluctuation in
exchange rate.
Analysis Summary
MONTH
Apr-06
May-06
Jun-06
Jul-06
Aug-06
Sep-06
Oct-06
Nov-06
Dec-06
Jan-07
Feb-07
Mar-07
Apr-07
May-07
Jun-07
Jul-07
Aug-07
Sep-07
Oct-07
Correlation
Average
Turnover
Lowest /
Highest
Turnover
Degree of
Correlation
$ Value
44.9
45.4
46
46.2
46.5
45.7
45.5
44.9
44.8
44.3
44.2
44
42.2
40.7
40.8
40.4
40.8
40.3
39.5
Table1: Foreign Revenue Turnover (in Rupees)…contd..
AFTEK
INFOSYS
TCS
WIPRO
POLARIS
10979944048 19343184965 7519573186 8685955743 463904206
9660232171
18715493047 5969400779 8683481311 991565269
7631264173
28031574936 6429868218 7538971790 383430426
9530559432
33187016506 11091703588 8905597889 2623231704
13799140987 39096129278 11358497887 9732301123 3560753809
12008705530 40396617276 7257036657 5960749713 1177410836
10985709752 25152130990 6646799909 4627134996 949356636
6465767812
21092246495 5545469812 5126679386 1073808544
4627487104
33052878781 5547330775 5316744258 770635836
3937612119
30176122837 6276745421 5171470031 389137594
2107681409
16209046179 6860803142 4658310328 622704766
2210198537
25501467909 5144670406 6040409835 991241540
3289317532
19962285896 5681572609 3981111110 574781814
3067227407
10980249385 4311629503 4186674755 689903450
1653055009
11781532480 3046562271 2726008230 376934053
3466251344
18684715340 3358894818 2296473466 764443258
2202129447
19711450578 4922071205 2286685248 706222936
3248718273
13736975830 4434513667 1954909436 400005739
185596620
11630281584 3075678270 2159567240 294390007
0.793293886
0.766382615 0.796693709 0.864349643 0.527763087
5845084142
22970600015
185596620 /
13799140987
10980249385 / 3046562271 / 1954909436 / 294390007 / 895932735 /
40396617276 11358497887 9732301123 3560753809 26593533104
High
High
6025201164
MASTEK
19029204308
13886145289
15684050286
24127075849
26593533104
22762187906
19969849085
18915090909
8493228790
5710470477
6742531754
2476742597
3442901350
4198604793
2982295897
5563505543
3584450500
1048317875
895932735
0.83124443
High
5265222941 937045390.7 10847690476
High
Moderate
High
Table1: Foreign Revenue Turnover (in Rupees)
MONTH DOLLAR
HEXAWARE
VALUE
Apr-06
May-06
Jun-06
Jul-06
Aug-06
Sep-06
Oct-06
Nov-06
Dec-06
Jan-07
Feb-07
Mar-07
Apr-07
May-07
Jun-07
Jul-07
Aug-07
Sep-07
Oct-07
Correlation
Average
Turnover
Lowest /
Highest
Turnover
Degree of
Correlation
44.9
45.4
46
46.2
46.5
45.7
45.5
44.9
44.8
44.3
44.2
44
42.2
40.7
40.8
40.4
40.8
40.3
39.5
CMC
HCL
PATNI
4187626062
2937285474
1815413514
2774140286
10152493322
6869243313
4323724483
3064409125
2069344239
1439809758
1380014996
2444031305
3721535225
4575421387
1105012417
1926790676
1032617367
709707863
528937586
0.519423931
257152826
473628558
182718078
328644792
953061823
396202001
304608913
396202001
304608913
111971789
155946533
30520041
99088296
66863191
135032798
58861291
38096352
182000421
84182666
0.648995857
1025650571
2994952763
2791973878
3379920881
7622917235
4909325131
2702600602
1609597689
1003803420
1026296865
2289192314
1411406404
1253705359
1436617481
1471479728
3634389603
2972467716
1479595919
1000328438
0.417719079
1449344861
1080244041
905325178
1325866099
2122549804
748022016
877027912
668885137
799380597
606912747
147176569
354310391
494344837
370105529
401055719
217933544
481592551
392206447
201861845
0.709928617
3003029389
239967962.3
2421906421
718112938.1 23130625522 310530474.4
528937586 /
10152493322
30520041 /
953061823
1000328438 /
7622917235
147176569 / 11555526857 /
2122549804 39963498247
Moderate
Moderate
Moderate
Moderate
SATYAM
NUCLEUS
25301398938 131199917
24514452394 129708800
24648316900 296682811
38530494040 704390913
39963498247 742495523
35801602322 323072635
32179872246 407647674
19373368636 504118285
22034854910 400295832
22034854910 392724552
27061354437 373941371
15530498478 332600525
11957091363 255675098
19541374597 417249203
18474826187 111285674
22294443088 176548950
14758107133
99960542
11555526857
73904590
13925949228
26576118
0.752749906 0.656534905
High
26576118 /
742495523
Moderate
Objective2: To find out whether the fluctuation in exchange value of dollars affects revenue turnover
of IT company, or not.
Figure1 shows variation in value of rupee against 1 US$. Figure2-13 shows the change in the terms of
revenue generation over the selected period of time. It can be noted from Table1 that as the value of
dollar is highest in August 2006, all company’s revenue turnover is also maximum in the same month,
except that of Infosys.
Table1 also reveals that as the value of dollar is lowest in October 2007, even then only 6 companies
suffer maximum losses in the month of October 2007. Six other companies have lowest turnover in
different months where value of dollar is better if compared with that of October 2007.
One must note that impact of different external variables present at both macro and micro level cannot be
ignored while making interpretation. We can further interpret that though the turnover of those six
companies may not be lowest in October 2007 when value of dollar is lowest, but there turnover reduced
significantly if compared with there highest turnover value during the period of study. This trend simply
favours and proves that the fluctuation in dollars has a severe impact on the IT industry.
Positive correlation is seen between the fluctuation in dollars (acting as independent variable) and
revenue value (acting as dependent variable) as the average correlation value of 12 IT companies is
0.690423305 which is higher than 0.5 representing the overall impact of exchange risk on IT industry.
Objective3: To find whether the hedging technique can proves as solution in handling the exchange
financial risks in the IT industry.
The hedging techniques used by Major IT giants are not sufficient to handle the currency exchange risk. It
means the predictions of amount of exposure to the exchange risk for which the hedging option are taken
are less than what actually faced.
Suggestions
Analysis revealed a positive correlation exists between the independent variable and the dependent
variable. Suggestion to companies is that they should use the combination of hedging instruments like
Option along with forward hedging instruments to save them against exchange risk and will also help
them to raise more debt as hedged firm are considered safer than unhedged firm.
Limitations
The study is restricted to only 12 organizations only. Moreover, there are many factors present at both
macro and micro level that impacts revenue turnover and there impact cannot be ignored while making
interpretation. Analysis was conducted assuming all those factors as constant and studied the impact of
fluctuation in dollars on revenue turnover of IT companies.
References
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