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foreign exchange

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The foreign exchange market is a global, worldwide-decentralized financial market for trading currencies. Financial centers around the world function as anchors of trading between a wide range of different types of buyers and sellers around the clock, with the exception of weekends. The foreign exchange market determines the relative values of different currencies . The foreign exchange market assists international trade and investment, by enabling currency conversion. For example, it permits a business in the United States to import goods from the United Kingdom and pay pound sterling, even though its income is in United States dollars. It also supports direct speculation in the value of currencies, and the carry trade, speculation on the change in interest rates in two currencies. An important part of this market comes from the financial activities of companies seeking foreign exchange to pay for goods or services. Commercial companies often trade small amounts compared to those of banks or speculators, and their trades often have little short-term impact on market rates. Nevertheless, trade flows are an important factor in the long-term direction of a currency's exchange rate. Some multinational companies can have an unpredictable impact when very large positions are covered due to exposures that are not widely known by other market participants The financial instruments used in the foreign exchange are spot, future, forward, option, and swap. Risk aversion is a kind of trading behavior exhibited by the foreign exchange market when a potentially adverse event happens which may affect market conditions. This behavior is caused when risk averse traders liquidate their positions in risky assets and shift the funds to less risky assets due to uncertainty. The foreign exchange market is unique because of its huge trading volume representing the largest asset class in the world leading to high liquidity, its geographical dispersion, its continuous operation: 24 hours a day except weekends, i.e. trading from 20:15 GMT on Sunday until 22:00 GMT Friday, the low margins of relative profit compared with other markets of fixed income, and the use of leverage to enhance profit and loss margins and with respect to account size.



 To study the foreign exchange transaction of the future focus InfoTech private limited.

 To identify the use of various hedging tools in reducing risk.  To explore the means and methods to utilize foreign exchange effectively  To trace out the implication of various financial instrument in foreign exchange


 To monitor the foreign exchange exposure in the company.  To quantify the value of the foreign exchange flow in company.  To avoid the foreign exchange loss of the company.  To find out the benefit out of the hedging.

 To know about the export portfolio about the company.  Foreign exchange cover operations can be done.  To improve the profitability of the company through foreign exchange operations.


The Indian Government acquired the EVS EM computers from the Soviet Union, which were used in large companies and research laboratories. In 1968 Tata Consultancy Services—established in SEEPZ(Santacruz Electronics Export

Processing Zone), Mumbai,by the Tata Group—were the country's largest software producers during the 1960s. As an outcome of the various policies of Jawaharlal Nehru ,the economically beleaguered country was able to build a large scientific workforce, third in numbers only to that of the United States of America and the Soviet Union. On 18 August 1951 the minister of education Maulana Abul Kalam Azad, inaugurated the Indian Institute of Technology at Kharagpur in West Bengal. Possibly modeled after the Massachusetts Institute of Technology these institutions were conceived by a 22-member committee of scholars and entrepreneurs under the leadership of N. R. Sarkar. Relaxed immigration laws in the United States of America (1965) attracted a number of skilled Indian professionals aiming for research. By 1960 as many as 10,000 Indians were estimated to have settled in the US. By the 1980s a number of engineers from India were seeking employment in other countries. In response, the Indian companies realigned wages to retain their experienced staff. In the Encyclopedia of India, Kamdar (2006) reports on the role of Indian immigrants (1980 - early 1990s) in promoting technology-driven growth. The United States technological lead was driven in no small part by the brain power of brilliant immigrants, many of whom came from India. The inestimable contributions of thousands of highly trained Indian migrants in every area of American scientific and technological achievement culminated with the information technology revolution most associated with California’s Silicon Valley in the 1980s and 1990s. The National Informatics Centre was established in March 1975. The inception of The Computer Maintenance Company (CMC) followed in October 1976. During 1977-1980 the country's Information Technology companies Tata Infotech,


Patni Computer Systems and Wipro had become visible. The 'microchip revolution' of the 1980s had convinced both Indira Gandhi and her successor Rajiv Gandhi that electronics and telecommunications were vital to India's growth and development. MTNL underwent technological improvements. During 1986-1987, the Indian government embarked upon the creation of three wide-area computer networking schemes: INDONET (intended to serve the IBM mainframes in India), NICNET (the network for India's National Informatics Centre), and the academic research oriented Education and Research Network (ERNET).

India is now one of the biggest IT capitals in the modern world. The Indian Information Technology industry accounts for a 5.19% of the country's GDP and export earnings as of 2009, while providing employment to a significant number of its tertiary sector workforce. However, only 2.5 million people are employed in the sector either directly or indirectly. In 2010-11, annual revenues from IT-BPO sector is estimated to have grown over $54.33 billion compared to China with $35.76 billion and Philippines with $8.85 billion. It is expected to touch at US$225 billion by 2020. The most prominent IT hubs are Bangalore and Hyderabad. The other emerging destinations are Chennai, Coimbatore, Kolkata, Trivandrum, Pune, Mumbai, Ahmedabad. Technically proficient immigrants from India sought jobs in the western world from the 1950s onwards as India's education system produced more workers than its industry could absorb and dearth of opportunities. India's growing stature in the Information Age enabled it to form close ties with both the United States of America and the European Union. However, the recent global financial crises has deeply impacted the Indian IT companies as well as global companies. As a result hiring has dropped sharply, and employees are looking at different sectors like the financial service, telecommunications, and manufacturing industries, which have been growing phenomenally over the last few years. India's IT Services industry was born in Mumbai in 1967 with the establishment of Tata Group in partnership with Burroughs The first software export zone SEEPZ was set up here


way back in 1973, the old avatar of the modern day IT park. More than 80 percent of the country's software exports happened out of SEEPZ, Mumbai in 80s. The economic effect of the technologically inclined services sector in India accounting for 40% of the country's GDP and 30% of export earnings as of 2006, while employing only 25% of its workforce—is summarized by Sharma (2006): The share of IT (mainly software) in total exports increased from 1 percent in 1990 to 18 percent in 2001. IT-enabled services such as back office operations, remote maintenance, accounting, public call centers, medical transcription, insurance claims, and other bulk processing are rapidly expanding. Indian companies such as HCL, TCS, Wipro, and Infosys may yet become household names around the world. Today, Bangalore is known as the Silicon Valley of India and contributes 33% of Indian IT Exports. India's second and third largest software companies are headquartered in Bangalore. Mumbai too has its share of IT companies that are India's first and largest, like TCS and well established like Reliance Patni, LnT Infotech, i-Flex, WNS, Shine, Naukri, Jobspert etc. are head-quartered in Mumbai. And these IT and dot com companies are ruling the roost of Mumbai's relatively high octane industry of Information Technology. Such is the growth in investment and outsourcing, it was revealed that Cap Gemini will soon have more staff in India than it does in its home market of France with 21,000 personnel in India. On 25 June 2002 India and the European Union agreed to bilateral cooperation in the field of science and technology. A joint EU-India group of scholars was formed on 23 November 2001 to further promote joint research and development. India holds observer status at CERN while a joint India-EU Software Education and Development Center is due at Bangalore.


IT is the area of managing technology and spans wide variety of areas that include computer software, information systems, computer hardware, programming languages but are not limited to things such as processes, and data constructs. Information technology (IT) is concerned with technology to treat information. The acquisition, processing, storage and dissemination of vocal, pictorial, textual and numerical information by a microelectronics-based combination of computing and telecommunications are its main fields. The term in its modern sense first appeared in a 1958 article published in the Harvard Business Review, in which authors Leavitt and Whisler commented that "the new technology does not yet have a single established name. We shall call it information technology (IT). Some of the modern and emerging fields of Information technology are next generation web technologies, bioinformatics, cloud computing, global information systems, large scale knowledge bases, etc. Advancements are mainly driven in the field of computer science.

Infosys Media Centre in Electronic City, Bangalore.

Tidel Park—one of the largest software parks in Asia—was set up on the July 4, 2000 in Chennai, to aid the growth of Information Technology in Tamil Nadu.


Microsoft India Development Center, Hyderabad

Millenium Tower in Kolkata, Salt Lake Sector-5, a major IT hub in the city.

Patni Knowledge Park, Airoli, Navi Mumbai

Cognizant's Delivery Center in Pune.


Hilbert and Lopez identify the exponential pace of technological change (a kind of Moore's law) machines’ application-specific capacity to compute information per capita has roughly doubled every 14 months between 1986-2007; the per capita capacity of the world’s general-purpose computers has doubled every 18 months during the same two decades, the global telecommunication capacity per capita doubled every 34 months; the world’s storage capacity per capita required roughly 40 months to double (every 3 years); and per capita broadcast information has doubled roughly every 12.3 years.


Future Focus Infotech Pvt. Ltd. (FFI) is an IT services organization providing strategic IT HR and managed solutions. The company was established as Focus Infotech in Apr 1997; renamed to its present name in Oct of the same year. The company commenced operations from Chennai where the corporate office of the company is currently located. FFI initially ventured out as an IT training provider and gradually transitioned towards consulting in skill requirements for various technologies such as Web Technologies, ERP, Microsoft Client Server technologies, Java, Oracle, Mainframe, etc, which now forms its core business offering. FFI enhanced its services in the subsequent years and established its software development center (SDC) in Chennai in 1999. FFI offers technical services in software development and support for their international client through this STPI unit. The company established its wholly owned subsidiary, Focus America, in the subsequent year. Focus America addresses business in the North Americas, providing offshore software development and onsite technical consulting services. FFI received its ISO 9001:2001 certification from TUV-SUD for its Chennai operations in 2005. Since then, all FFI Delivery Centers located at nine locations across India viz. Mumbai, Delhi, Chennai, Kolkata, Pune, Hyderabad, Bengaluru and Kochi (its most recent addition), have been successfully certified. In Jun 2011, FFI enhanced its global foot print through the commencement of its business in the UAE. Future Focus InfoTech is based out of the Sharjah International Airport Free Zone, is the wholly owned subsidiary of FFI. FFI's IT Services encompassing pre-sales through delivery to consultant & customer process management are managed through FiQMS, an indigenously designed and developed solution for its consulting services.


       Established: April 1997 Registered as Private Limited company: October 1997 Selected as Business Associate by TCS: 1997; providing trained IT

consultants for TCS'Y2K projects SDC (Software Development Centre) inaugurated: March 1999, Chennai;

servicing domestic as well as US based clients Focus America, Inc. subsidiary of FIT, incorporated: Atlanta, USA in 2000; the marketing front end Ford Technology Services awards first "Managed services" assignment to FFI

- Data analytics for Global Analysis group of FMCC (Ford Motor Credit Corporation).          Revenue crosses INR 10 crore: 2003-04 IBM and Infosys added to National client list: 2004 ISO 9001:2000 certification for Chennai and Bangalore offices by TUV-Sud:

Feb 2005 Revenue exceeds INR 24 crore: 2006-07 Zinnov Awards for Process Excellence and IT Consulting Services: 2007 ISO 9001:2000 certification extended to Delhi and Mumbai offices: Feb 2008 Listed in Dun & Bradstreet's "India's Top IT Companies" 2007 & 2008 Deloitte Technology Fast 500 Asia Pacific winner 2008 Revenue INR 50 crores: 2008-09


2011 : Deloitte Technology Fast 50 India 2011

2010 : All World Network India Fast Growth 25 winner -A Michael Porter endorsed Harvard Univ. initiative


2008, 2009 & 2011 : A Deloitte Technology Fast 500 Asia Pacific Winner 2008 & 2009 : D&B India’s Top IT Co’s Listing

2009 : A NASSCOM Emerge 50 Company

2007 : Zinnov Process Excellence Award & Zinnov Recognition - Best IT Talent Consulting

Primarily, three core functional groups manage the domestic offerings Business Relations (BR), Business Delivery and Business Maintenance. The BR group develops and maintains the relationship with prospects and customers for contracts, requirements, fulfillment and purchase orders. The Delivery team work on the specifications received from BR to locate right profiles and follow through till the selection process. Business Continuity Services (BCS) carry forward the relationship with the consulting employees handling deployment & post deployment, and beyond also addressing re-deployment/reallocation needs. All regional locations Chennai, Bangalore, Hyderabad, Delhi, Mumbai and Pune are peopled with these functionaries headed by a Location Head or a Regional Manager. They are supported by identified Country Managers at the corporate level, who in turn are customer, technology or vertical aligned.

The FFI offshore (OSS) team consists of qualified Software professionals, viz. developers, testers, technical leads and Project managers.

The organization's Quality Management system, FiQMS, established and implemented in 2004 has well defined processes for all the above mentioned services. The QA system of reviews and audits at all stages ensures delivery conforming to customer specifications thereby ensuring higher levels of customer & consultant satisfaction. Over the last 5 years, continual improvement has been achieved by measurement of performance against objectives, data analysis and review, and suitable corrective action as required.


FiQMS automated ERP solution developed in house by FFI over the last three years covers all the critical operational processes and facilitates real time monitoring of key performance indices. Context sensitive email alerts generated by the intranet application right through the workflow from the receipt of customer requirement through fulfillment to billing ensure minimal delays and deviations.

This has several meanings. Sometimes, it means going the extra mile, doing the impossible. Often it means moving quickly. However, it always means identifying and meeting customer needs and measuring our performance by the standards they set. Building lasting relationships and collaborating with our customers, to deliver clear value for money, sets us apart from our competitors.








At Focus, personal and professional integrity is paramount. They trust and respect their customers and colleagues and actively defend their principles.

This translates to striving to be the best in whatever they do. This also means recruiting the best people. Their customers expect work of the highest quality, delivered on time, on budget with no surprises.

They support creativity and innovation. In an evolving industry with so many look-alikes, they have managed to set themselves apart through creativity, innovation and diversity of thought. They value thought-leaders, not hierarchy. They welcome new ideas and help people deliver services with a difference. They roll up our sleeves and attack problems with all the passion, resources and innovation the situation demands.


They learn and grow together. They share knowledge, ideas and solutions and collaborate with our customers to address the challenges that arise. And, most of all they enjoy their work and have fun doing it. Focus specializes in the IT domain, as we believes that the future of HCM services globally would be domain and knowledge-centric. More over, HCM and Delivery cannot be kept as separate deliverables for viable, "buy-able" business solutions! Founded almost a decade ago by a group of young and committed professionals, we have been growing steadily at a rate of 30% year on year, since inception. Managed by a board of eminent professionals, Focus is the first company in the IT Technical and HCM services domain in India, to be certified ISO 9001:2000 by TUV SUD, Germany.  Pioneers in IT Technical Services and among the top five IT

Technical/Professional Service providers in the Country - over 12 years in IT Technical/HR services.  Quality Certified Business Processes (ISO 9001-2000) with best in class

services in IT Technical Consulting, Human Capital Management and Career Management services in the IT technology domain.    True-blue IT domain focus. Value-add: The "extended Technical Delivery and HR arm" you can depend

on for effectively addressing you revolving IT resource needs and challenges. Onsite IT Technical Consulting services- USA: Facilitated through wholly

owned subsidiary, Focus America, Inc.

To become the most admired & sought-after IT Technical Consulting & Services organization for clients and employees in the industry.

Perseverance & commitment to the highest quality of Customer Service delivered with sensitivity, awareness, individual pride and Company Spirit.



A web portal or links page is a web site that functions as a point of access to information in the World Wide Web. A portal presents information from diverse sources in a unified way. Apart from the standard search engine feature, web portals offer other services such as e-mail, news, stock prices, information, databases and entertainment. Portals provide a way for enterprises to provide a consistent look and feel with access control and procedures for multiple applications and databases, which otherwise would have been different entities altogether. Examples of public web portals are AOL, Excite, iGoogle, MSN, Netvibes, and Yahoo

In the late 1990s the web portal was a hot commodity. After the proliferation of web browsers in the late-1990s many companies tried to build or acquire a portal to have a piece of the Internet market. The web portal gained special attention because it was, for many users, the starting point of their web browser. The portal craze, with old media companies racing to outbid each other for Internet properties, died down with the dot-com bust in 2000 and 2001. Disney pulled the plug on Go.com, Excite went bankrupt, and its remains were sold to iWon.com. Some portal sites such as Yahoo! and those others first listed in this article remain active.




Introduction Intranet is the kind of privatize computer network that make use of existing technologies and internet protocols for sharing and communicating with all the connected network of same organization. They are fundamentally designed for the intra networks for collaborating the work activities of all the people involved in one organization. Regardless of location intra networks are an effective way for information sharing. In these networks all the internal websites can be fully accessed by all the workers dealing win an organization. Many educational and governmental institutes are using intra network framework for communicating at different campuses of same institutions. Memos and circulars can be circulated easily by using the intra networks. Historical Background In the mid of 1990s this networking method was first introduced at California University and as the time passes it became famous allover the world because se before the intra networks there was zero existence of any reliable network technology for collaborating the information staying within the organization. Intra network fame highly targeted the commerce and business sector. One of the major advantages of this network is that it can host multiple website to be used by one organization with no geographical restrictions in small area networks.


Robert Dekle from University of Southern California(january 2005)1 , conducted a study on Exchange Rate Exposure and Foreign Market Competition: Evidence from Japanese Firms. The study is based on foreign competition on exposure, or the responsiveness of profits to fluctuations in exchange rates. He finds that, out of the 15 four‐digit level Japanese export industries in our sample, 10 industries are better characterized as Cournot competitors in foreign markets, rather than colluding firms. Depending on the industry, exposure elasticities range from 0.5% to 8.5%, with an average of around 2.5%. These elasticities, on the whole, are much higher than those found in earlier research. Collusive exporters tend to have higher elasticities than competitive exporters The profits—and stock market capitalization—of multinational firms usually depend significantly on the values of their home currencies. Exchange rate fluctuations can cause large shifts in relative costs among firms located in different countries and affects the prices of goods sold in domestic and foreign markets. Largely because of this responsiveness of profits to fluctuations in exchange rates, or corporate ―exposure,‖ countries try to control fluctuations in their currencies. For example, many countries adopt fixed exchange rates to reduce the risk of hurting the profitability of their firms. In this paper, he focus on the impact of foreign competition on exposure; it is widely believed that the ―exposure‖ of exporting firms is strongly influenced by the market structure and the type of competition prevailing in foreign markets. In foreign markets where the foreign good and the export good are easily substitutable, exporters are reluctant to raise export prices when their home currency appreciates, for fear of losing their foreign market share. When their currencies appreciate, these exporters suffer large declines in export earnings, compared to exporters producing goods with little foreign substitutability.


Robert Dekle from University of Southern California Journal of business January , 2005 volume

Vol.78 , No.7, pp.57-90


In addition, for a given substitutability, the type of competition among exporters may affect exposure. Colluding exporters have more control over export prices. When their currencies appreciate, these exporters can cut their domestic price‐cost margins to preserve their foreign market share, compared to exporters competing with each other. This effect should especially be strong when the substitutability with foreign products is high, since in these markets, foreign consumers can more easily switch to locally produced products.By cutting price‐cost margins, increases in foreign prices can be restrained and market share can be preserved. In contrast, if foreign consumers cannot switch easily (low

substitutability), the advantages of cutting domestic price‐cost margins are small. Both colluding and competing firms may then choose to raise their export prices. In sum, colluding exporters have higher exposure than competing exporters, especially when substitutability is high. In this paper, he finds a structural model of exchange rate exposure. Unlike most earlier empirical models of exchange rate exposure, which assume a representative single exporter, or leave the number of exporters unspecified, we allow for multiple exporters. Therefore, while earlier studies assume collusion by, say, Japanese exporters, we are able to test whether Japanese exporters collude or compete in foreign markets. It is important to test whether exporters collude or compete in foreign markets, because their market conduct strongly influences their exposure to exchange rates, especially when foreign and Japanese goods are highly substitutable. In particular, when exporters collude in foreign markets, they are more ―exposed‖ than when they compete.Finally, he finds that the impact of exchange rate fluctuations on the yen profit margins of studies, we find that the impact of time‐varying margins on profitability is small, although for exporters that collude, margins vary more,thus, a typical Japanese exporter's exposure elasticity arises almost entirely from the change in profits at the original profits margin. Simply put, the profits of Japanese firms fall when the yen appreciates, because foreign sales become smaller in yen terms.


Simi Kedia and Abon Mozumdar from Harvard University(October 2003),


conducted a study on Foreign Currency–Denominated Debt: An Empirical Examination .They examine the determinants of debt issuance in 10 major currencies by large U.S. firms. Using the fraction of foreign subsidiaries and tests exploiting the disaggregated nature of our data, we find strong evidence that firms issue foreign currency debt to hedge their exposure both at the aggregate and the individual currency levels. We also find some evidence that firms choose currencies in which information asymmetry between domestic and foreign investors is low. We find no evidence that tax arbitrage, liquidity of underlying debt markets, or legal regimes influence the decision to issue debt in foreign currency. In recent years, as the global economy has become increasingly integrated, there has been a dramatic increase in the number of firms that have some business activity outside their country of incorporation. Such foreign involvement ranges from simple import or export activity to more complicated decisions including integrated global sourcing, production, and competition. These multinationals face many different product and capital markets, a myriad of legal regimes, political risks, and exchange rate uncertainty. We have little understanding of how this affects the financing patterns of multinational firms. In this article, they study a sample of large U.S. firms and examine their decision to issue foreign currency–denominated debt. There has been a dramatic increase in the amount of debt finance raised in foreign currencies. Firms in the United States increased foreign currency–denominated debt from around $1 billion in 1983 to $62 billion in 1998. This increase can also be seen at the individual currency level. Over this period borrowing increased from $0.3 billion to $9.4 billion in German marks, from $0.6 billion to $22 billion in U.K. pounds, and from $0.2 billion to $2.5 billion in Japanese yen. Despite this increasing importance, there is little understanding of why firms issue foreign currency–denominated debt.


Simi Kedia and Abon Mozumdar from Harvard University Journal of business. October, 2003 volume

Vol. 76, No. 4, pp. 521-546


Choice of currency of debt is also important because it throws light on firms’ risk management activities. There has been a surge of interest in the hedging policies of firms and management of foreign exchange risk. Although most of this attention has been focused on the derivative usage of firms, issuing debt in a currency in which the firm has exposure is an alternate form of hedging. Anecdotal evidence from the testimony of top managers suggests that derivative usage is only one aspect of an integrated policy of managing foreign exchange risk. For example, in the 1995 Bank of America Round‐Table on Derivatives and Corporate Risk Management, Tom Jones, vice president and treasurer of Union Carbide, said: ― Use natural hedges any place we can—for example, funding in currencies where we produce and sell; or when possible, locating manufacturing and sourcing in countries where we sell. But there is still considerable room for financial solutions to risk management after the natural hedges are in place‖ Studying the role of foreign currency–denominated debt as a hedging instrument complements the current literature by developing a comprehensive understanding of a firm’s risk management activities. Prior work by Geczy, Minton, and Schrand (1997) and Allayannis and Ofek (2001) examines foreign currency– denominated debt at the aggregate level. In this article we study the role of foreign currency debt in hedging exposure at the individual currency level. Result of the study reported that We examine the issuance of debt in 10 major currencies by a sample of large U.S. firms and study the determinants of choice of currency of debt. We find strong evidence that debt issuance in foreign currency is related to foreign activity. This result holds for different proxies of foreign operations and at both the aggregate and individual currency levels. The significance of foreign operations in determining the probability of issuing foreign debt is consistent with both the role of foreign debt as a hedging instrument and the existence of information barriers. Both sets of tests provide significant evidence in favour of the hedging motive for issuing foreign debt. Firms issue debt in currencies in which they have exposure or in currencies that are positively correlated with currencies of exposure.


Stephen E. Christophe from George Mason University(January 2002) , conducted a study The Value of U.S. MNC Earnings Changes from Foreign and Domestic Operations . This study examines whether the stock return associated with changes in domestic and foreign earnings varies depending upon the sign of the change. Evidence is presented that negative foreign (vs. domestic) earnings changes are associated with significantly larger stock returns. In contrast, positive foreign and domestic earnings changes are associated with statistically indistinguishable returns. The large association coefficient corresponding to negative foreign earnings changes is especially pronounced for firms with substantial free cash flow and for firms with high anticipated growth opportunities. No evidence is found that positive foreign earnings changes result in high returns due to foreign market growth opportunities. A number of empirical studies examine the value of the U.S. multinational corporation (MNC) during the 1980s and 1990s and present evidence that investors do not generally value the foreign operations of the MNC as highly as they value its domestic operations (see, e.g., Boatsman, Behn, and Patz 1993; Christophe 1997; Christophe and Pfeiffer 2000; and Denis, Denis, and Yost 2000). In contrast, a study by Bodnar and Weintrop (1997) of the 1985–93 time period reports that changes in an MNC’s foreign earnings are associated with a larger abnormal stock return than changes in its domestic earnings. On its surface, a larger abnormal stock return associated with changes in foreign earnings seems inconsistent with the studies that find investors place a lower relative value on the MNC’s foreign operations. The purpose of this article is to attempt to reconcile these seemingly divergent results and to shed additional light on the relationship between firm value and international operations by examining the association between MNC stock returns and positive versus negative earnings changes. Over the past 30 years, there appears to have been a shift in the general relationship between international operations and the value of the MNC. Studies that focus on the relationship that obtained during the decade of the 1970s find that during that time period international operations enhanced firm value.
Stephen E. Christophe from George Mason University Journal of business. January , 2002 volume Vol. 75, No. 1, pp. 67-93.



In contrast, the relationship between international operations and firm value evolves during the 1980s. For example, I study the 1978–86 time period using the MNC’s foreign sales percentage to measure international involvement. I find that, although (similar to Morck and Yeung 1991) there is a positive relationship between the MNC’s Tobin’s q and its international operations during the late 1970s, during the early 1980s, as currency exchange rates moved adversely, the relationship shifts such that international operations result in a negative impact on Tobin’s q. Further, Boatsman et al. (1993) study the 1985–89 time period and employ foreign operating income disclosures (required by Statement of Financial Accounting Standards [SFAS] no. 14) to examine how foreign earnings surprises are reflected in abnormal returns. They report evidence that foreign surprises are associated with negative abnormal returns, which implies that foreign profits are capitalized into stock returns at lower multiples than domestic profits. This result is consistent with international operations not being as highly valued by investors as domestic operations.1 Denis et al. (2000) study the 1984–97 time period and find that global diversification (as measured using foreign sales and a dummy variable approach) by MNCs results in valuation discounts similar in magnitude to the discounts associated with industrial diversification. Finally, Christophe and Pfeiffer (2000) use foreign sales as their measure of MNC international operations and find, in both a Tobin’s q‐based levels empirical specification and in an excess returns‐based changes empirical specification, that during the 1990–94 time period, investors do not value the international operations of the MNC as highly as they value its domestic operations. Taken collectively, these studies provide evidence that, though investors during the 1970s valued the international operations of the MNC more highly than they valued its domestic operations, during more recent years the relationship has reversed. Therefore, the finding by Bodnar and Weintrop (1997) that foreign earnings changes during the 1985–93 time period are associated with a larger abnormal stock return (relative to domestic earnings changes) is surprising and warrants further attention.


The results of this study indicate that the stock return associated with domestic and foreign earnings changes vary along several dimensions. First, the results show that investors do not value positive domestic and foreign earnings changes differently.In contrast, however, strong evidence is presented that negative domestic and foreign earnings changes have dramatically different associations with stock returns whereby a negative foreign earnings change results in a significantly larger negative stock price reaction. Since a substantial number of MNCs (1,318 out of 3,041 total firm years for the sample considered in this study) report negative earnings changes from their foreign operations, these results should be considered consistent with findings presented in the prior studies by Boatsman et al. (1993), Christophe (1997), and Christophe and Pfeiffer (2000), that investors do not generally value the foreign operations of the MNC as highly as they value its domestic operations. In addition, the results presented herein indicate that the larger earnings response coefficient associated with negative foreign earnings changes is most pronounced for MNCs with substantial amounts of free cash flow. This finding is consistent with Jensen’s (1986) agency cost of free cash flow theory. The results also indicate that the larger earnings response coefficient associated with negative foreign earnings changes is most pronounced for MNCs with high anticipated growth opportunities. This finding is consistent with investors revising downward their future growth expectations for the MNC when the firm discloses poor foreign operating performance. Finally, no evidence is found that positive foreign earnings changes are associated with a large earnings response coefficient due to investor recognition of foreign market growth opportunities.


The study focuses on the foreign exchange transactions in future focus InfoTech. The project study mainly focuses with foreign exchange in export transaction and minimization of risk.

Research in common parlance refers to a search for knowledge .One can also define research as a scientific and systematic search for pertinent information on a specific topic. In fact, research is an art of scientific investigation .Research is an academic activity and as such, the term should be used in a technical sense.  Systematic and organized effort to investigate a scientific problem  Identify the problem  Gather information  Analyze the data  Take corrective action and solve the problem

Research can be defined as the search for knowledge, or as any systematic investigation, with an open mind, to establish novel facts, solve new or existing problems, prove new ideas, or develop new theories. The primary purposes of basic research (as opposed to applied research) are documentation, discovery, interpretation, or the research and development of methods and systems for the advancement of human knowledge. Approaches to research depend on

epistemologies, which vary considerably both within and between humanities and sciences.

Research is an organized activity focused on specific objective with the support of data collection involving tools for analysis deriving logically sound inferences. Research design is purely and simply the framework or plan for a study.

The research is analytical in nature



The researcher has to use information already available and analyze those details to make a serious assessment.

 NATURE OF DATA The data collected is secondary in nature. This is due to the nature of analysis, which only identify for secondary data.  SOURCES OF DATA The sources of data are the various year foreign exchange statements provided by the Future Focus InfoTech Private Limited .They were used for analysis and for preparing reports. The records maintained by the company where referred to get the required information .  SECONDARY DATA The secondary data are collected from the foreign exchange statements, and other broachers of the company.  METHOD OF COLLECTION The data for the analysis are collected from the official files, reports and other available material  PERIOD OF THE STUDY The period of the study will be carried out from the last five years of foreign exchange statements. i.e., from 2006-2007 to 2010-2011

The tool and technique which is used for the analysis is STATISTICAL TOOL: Standard Deviation



Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" exists from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. The standard deviation of a random variable, statistical population, data set, or probability distribution is the square root of its variance. It is algebraically simpler though practically less robust than the average absolute deviation. A useful property of standard deviation is that, unlike variance, it is expressed in the same units as the data.

Standard Deviation:


The process of evaluating data using analytical and logical reasoning to examine each component of the data provided .this form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered ,reviewed and then analyzed to form some sort of finding or conclusion.

Technically speaking, processing implies editing, coding classification and tabulation of collected data so that they are amenable to analysis. The term analysis refers to the computation of certain measures along with the searching for patterns of relationships that exist among data groups. Thus in the process of analysis ,relationships pr differences supporting or conflicting with the original or new hypthede should be subjected to statistical tests of significance to determine with what validity data can be said to indicate any conclusions.


The foreign exchange market assists international trade and investment, by enabling currency conversion. For example, it permits a business in the United States to import goods from the United Kingdom and pay pound sterling, even though its income is in United States dollars. It also supports direct speculation in the value of currencies, and the carry trade, speculation on the change in interest rates in two currencies. This company also applies the same methodology ,hence these are the various criteria used for the foreign exchange statement.  Invoice Date: Invoice date is where the spot rate is booked.  Invoice Rate : Invoice rate is where the spot rate of the exchange booked.  Received Rate: Received rate is where the spot rate is received; it can be higher or lower than the spot rate booked.  Invoice Amount :The amount which is multiplied with the invoice rate which is fixed by the company.  Received Amount: the amount, which is multiplied with received rate, which is fixed by the company.  Forward Rate: The rate which is calculated on the basis of RBI rates and which is taken on the basis on received dates of the company.  Amount based On forward Rate :The invoice amount which is multiplied with the forward rate.  Profit/Loss With Reference To The Exchange Rate Applied: the exchange profit/ loss which is faced by the company by subtracting received rate from the invoice rate  Profit/Loss With Reference To The Forward Contract: The forward profit/loss is the financial instrument which is applied which is calculated by subtracting the forward rates from the received rates.


PROFIT/LOSS WITH REFERENCE TO THE EXCHANGE RATE APPLIED 16,564.80 -405.00 2,632.50 8,032.50 -4,421.12 -900.90 -2,348.24 -505.44 -2,165.60 -34.32 -2,146.12 -836.91 -2,501.60 71.40 972.84 -5,096.52 -2,312.64 -2,590.00 -3,744.96 -12,273.80 -4,526.20 -2,072.00 -1,034.00 -9,668.12 -3,340.48 -924.11 -95.49 -56,496.00 -5,148.00 -911.68 -2,212.18 -9,724.00 -2,120.60 -9,113.40 -8,801.75 PROFIT/LOSS WITH REFERENCE TO THE FORWARD CONTRACT -10,648.80 3,273.75 236.25 -5,737.50 6,355.36 1,181.18 2,530.89 673.92 2,598.96 74.36 2,468.03 851.59 2,876.84 -49.98 -906.51 5,250.96 2,382.72 2,600.00 3,783.97 12,975.16 4,784.84 2,113.44 1,049.04 9,966.11 3,443.44 952.59 100.67 57,288.00 5,940.00 1,051.94 2,261.12 11,220.00 2,292.50 9,337.50 9,635.60


-8,732.00 -5,014.24 -7,312.68 -3,256.00 -25,868.00 -20,658.00 -34,830.00 -15,971.54 -16,023.51 2,119.74 -6,470.85 -10,425.08 -2,141.39 -2,384.91 -985.13 603.46 -845.63 3,997.51 458.35 -15,463.87 -14,505.00 -23,384.25 -24,547.96 -19,364.79 -22,942.21 -7,102.57 -14,142.58 -12,265.24 -19,645.35 -37,852.87 -28,206.23 -32,892.80 -33,543.67 -26,109.19 -18,176.81 -28,406.55 -5,727.00 -2,095.30 -11,688.96 -16,171.69

10,207.00 5,861.24 8,547.93 3,806.00 6,073.76 26,097.94 44,118.00 24,320.30 23,544.76 -1,462.16 6,593.71 10,583.64 2,188.62 2,601.72 1,779.58 953.85 4,112.82 -730.31 -83.74 16,666.62 14,780.41 23,474.54 24,905.02 19,768.22 23,952.88 6,570.67 13,610.67 11,733.34 20,525.17 40,230.56 35,062.51 39,749.09 40,624.12 33,189.64 27,899.29 38,129.03 17,679.00 325.74 2,253.29 10,693.92



-47,426.20 -44,450.24 -6,544.96 -30,337.47 -20,644.28 -46,397.00 -4,402.34 -39,045.81 -38,757.54 -2,744.80 -24,923.09 -4,412.91 -31,300.00 -30,469.80 -1,103.40 -33,600.00 -11,04,731.74

32,569.20 28,389.12 4,180.08 19,375.69 13,180.06 32,536.00 3,720.69 33,751.46 31,773.51 2,175.84 22,469.52 3,978.48 34,800.00 33,876.96 1,196.23 45,100.00 11,38,219.15

Inference :in the above table we can find that the company has faced loss during the year 2006,by applying the forward contract the company has overcome the loss. While comparing it with the received exchange amount.


PROFIT/LOSS WITH REFERENCE TO THE EXCHANGE RATE APPLIED -11576.84 -3805.90 4614.89 -4358.12 2620.34 7724.86 -16293.73 -25874.42 1364.35 736.61 -1911.36 -11.60 175.00 45.00 -1476.86 -651.00 5713.20 3942.40 13248.11 17887.65 8454.42 9242.55 10388.77 -131.00 4702.20 126.00 900.00 -35294.00 -15294.00 -22020.00 -20220.00 351.13 -20220.00 -220.00 -272.16 -186.88 -220.00 PROFIT/LOSS WITH REFERENCE TO THE FORWARD CONTRACT 63617.84 20914.45 5094.04 16530.80 3116.08 1879.02 40883.35 19939.92 3609.85 2102.40 18874.68 114.55 90.00 220.00 12658.80 5580.00 856.98 591.36 -954.56 -1288.85 2688.65 2939.29 3303.81 844.95 -3046.49 1064.00 630.00 92294.00 30694.00 38220.00 29420.00 85.41 40020.00 15220.00 2540.16 1051.20 7620.00



-200.96 -1600.00 -18.16 -1600.00 939.20 8000.00 766.00 18320.00 1598.42 16540.00 1501.83 -43554.05

1984.48 15800.00 179.33 12600.00 305.24 1200.00 114.90 -1320.00 -115.17 5260.00 477.61 516506.07

Inference :In the above table we can find that the company has faced loss during the year 2007,by applying the forward contract the company has overcome the loss. While comparing it with the received exchange amount.


PROFIT/LOSS WITH REFERENCE TO THE EXCHANGE RATE APPLIED 48318.29 12079.57 49709.72 4541.92 591.39 6305.87 1576.47 44284.65 281.24 -383.98 -4343.62 -1085.91 82623.69 -3920.28 6069.91 88623.69 6069.91 76735.65 2233.73 8511.55 69873.69 8511.55 57985.65 4026.93 27665.66 6916.42 16735.65 1691.33 12788.46 29017.89 10159.03 17379.41 4344.85 -17014.35 611.76 -7600.00 -7600.00 -206.72 PROFIT/LOSS WITH REFERENCE TO THE FORWARD CONTRACT -35118.29 -8779.57 -39809.72 -3301.12 700.29 7494.13 1873.53 -33934.65 334.24 1798.38 20343.62 5085.91 -70623.69 11120.28 -2469.91 -77823.69 -2469.91 -65935.65 -908.93 -5261.55 -60123.69 -5261.55 -48235.65 -2489.31 -9265.66 -2316.42 -2935.65 -1128.29 -8531.21 -19357.89 -6777.11 10220.59 2555.15 37714.35 359.76 28600.00 28600.00 777.92


22400.00 26925.56 4786.02 7925.56 3962.78 253.62 -1400.00 -700.00 -261.31 -62200.00 -31100.00 -1990.40 0.00 47361.59 34578.99 381.62 2199.49 1778.25 1993.29 -70.81 -2905.02 -2700.00 -473.02 -4176.00 72.00 13212.97 11035.09 13193.55 23331.86 7064.59 24257.92 6525.92 31979.63 34548.87 3366.83 6865.73 9845.43 -4138.20 -929.50 -1265.02 -2194.88 -4332.00 10019.52 7909.44

200.00 -4325.56 -768.87 -41325.56 -20662.78 -1322.42 23600.00 11800.00 4404.94 79800.00 39900.00 2553.60 0.00 -34422.95 -25132.41 451.90 2613.95 2113.35 2368.89 739.61 13605.82 12645.60 2215.42 5328.00 1080.00 -5376.49 -4490.29 -5368.59 -14422.96 -4367.09 -14995.42 -5090.20 -24944.03 -26948.03 1979.98 4037.65 5789.97 5454.90 2431.00 4760.47 8259.68 16302.00 89.46 70.62



3296.16 11439.32 3135.35 3000.62 3368.36 -228.83 -627.20 -345.10 -333.69 -8735.99 -10972.08 -33090.40 -21067.14 -4245.15 845644.89

29.43 -1837.71 -16348.39 -15645.86 -17563.36 3857.42 10572.80 5817.40 5625.06 11207.91 14076.72 42453.60 27028.26 5446.35 -259928.19

Inference :In the above table we can find that the company has faced profit during the year 2008,by applying the forward contract the company has faced the loss, while comparing it with the received exchange amount.


PROFIT/LOSS WITH REFERENCE TO THE EXCHANGE RATE APPLIED -47200 -23600 -528.64 -21893.72 -5546 -39062.72 2900 29000 15200.35 11618.85 9050.9 416 5600 523.32 2468.2 2496.2 3333.68 389.2 24400 6080 19612.72 7786.04 6612.4 3843 -15000 -780 -10240 -4188 -8790 -3281.25 -8016.75 -8200 -344.4 -8448 -4136.9 -7011.205 PROFIT/LOSS WITH REFERENCE TO THE FORWARD CONTRACT 64400 32200 721.28 29871.94 7567 53297.44 -1600 -16000 -8386.4 -6410.4 -4993.6 1952 9200 -259.88 4054.9 4100.9 5476.76 639.4 -9200 -1216 -7394.96 -2935.72 -2493.2 -1449 34600 1799.2 16512 9660.32 20275.6 7568.75 18491.97 25800 1083.6 14080 13016.1 22059.645


-602.7 -3263.19 -526.44 618.88 3803.52 1327.2 1876.59 30.387 9303.84 12124.56 1267.56 4903.92 1457.4 9826.56 292446.08 599.04 -4096 2953.08 6481.02 2473.38 1215.24 -567.45 9400 18.1 -7680 104.16 363.16 178.06 99.2 -9200 -374.9 -2833.6 -9791.1 -2982.64 -2371.3 -5760 -990.64 -24400 -6710 -18881.94 -5330.18 -4011.36 -7360 477.87

1896.3 10267.11 1656.36 15472 905.6 316 4628.922 120.101 2215.2 2886.8 301.8 1167.6 347 2456.64 3239.52 149.76 9856 3861.72 8475.18 3234.42 1589.16 6241.95 8200 778.3 13312 4478.88 15615.88 7656.58 4265.6 26600 1083.95 8192.8 28309.05 8623.72 6856.15 11328 1672.72 41200 11330 31882.62 9000.14 6773.28 12736 356.06



10200 0 2838.66 8581.77 2509.71 1409.13 206217.912

7600 5696 2115.08 6394.26 1869.98 1049.94 702351.778

Inference :In the above table we can find that the company has faced profit during the year 2009,by applying the forward contract the company has gained more profit, while comparing it with the received exchange amount


PROFIT/LOSS WITH REFERENCE TO THE EXCHANGE RATE APPLIED 71800 3213.05 55000 2268.75 7668.57 2599.57 482.3 -511 9400 413.6 -1918.4 -43600 -151.2 -3600 6398 14000 -26.92 -400 798 19000 -268.8 -6400 -464 -11600 11983.8 552 0 7744 21877.46 62214.7 27416.83 15480.08 -672 15125 38392.75 22929.5 5554.5 3420 PROFIT/LOSS WITH REFERENCE TO THE FORWARD CONTRACT -41800 -1870.55 2600 107.25 6800.43 2931.43 427.7 1241 9000 396 2833.6 64400 798 19000 3290.4 7200 1426.76 21200 -8.4 -200 1150.8 27400 1216 30400 7589.74 349.6 0 -2944 -12736.46 -36219.7 -15961.33 -9012.08 3456 660 1675.32 1000.56 952.2 380


3521.32 9949.69 2014 2864.12 -14820 3453.56 9122.23 1692 -100.74 -7667.06 -5120 -14388 -38527.14 -5450 -244.72 4608 -962.28 -3207.6 -450 1303.72 7360 2368 2772.84 6358 1782.17 4096.4 13111 1750 1642.2 -13685.76 -7744 -145.2 -196.24 -330.44 425.85 1408 6646.2 14187.3 13415.9 4910.55 -3840 -2126.72 -4347.84 -7556.8

3122.68 8823.31 1786 2539.88 21812 3306.6 8734.05 1620 1511.1 11324.74 11776 21252 56907.06 8050 9849.98 320 5078.7 16929 2375 5629.7 -576 -799.2 -786.8868 1570.8 1921.953 2106.72 6742.8 900 844.56 28062.72 14400 7695.6 10400.72 17513.32 2076.0012 4608 -69.96 -149.34 -141.22 -51.69 10560 9105.02 18614.19 32352.55



-5312 -3915.58 -8318.94 -4692.78 -151.32 6720 3862.2 12669 13459.8 765 1770 358.2 363186.23

11328 10261.52 21801.36 12298.32 14375.4 -448 2446.06 8023.7 8524.54 484.5 1121 226.86 559221.987

Inference :In the above table we can find that the company has faced profit during the year 2010,by applying the forward contract the company has gained more profit, while comparing it with the received exchange amount.


STANDARD DEVIATION OF THE FORWARD RATE FOR THE YEAR 2006-2007 DATE 01-MAR-06 01-APR-06 01-MAY-06 01-JUN-06 01-JUL-06 01-AUG-06 01-SEP-06 01-OCT-06 01-NOV-06 01-DEC-06 01-JAN-07 01-FEB-07 TOTAL X 44.35 44.61 44.9 46.22 45.98 46.65 46.53 45.84 44.93 44.67 44.2 44.11 542.99 X-M(45.25) ( X-M)2 0.81 -0.90 -0.64 0.41 -0.35 0.12 0.97 0.94 0.73 0.53 1.40 1.96 1.28 1.64 0.59 0.35 -0.32 0.10 -0.58 0.34 -1.05 1.10 -1.14 1.30 9.60 here ∑= summation M= mean

Standard deviation= M=542.99/12=45.25 √∑(X-M)2/n= √9.60/12 =√0.8 Standard deviation =.89

Inference : Here in this table standard deviation is done for twelve months for the year 2006-2007 .A low standard deviation indicates data points tend to be very close to mean. Hence the risk is very low here.


STANDARD DEVIATION OF THE FORWARD RATE FOR THE YEAR 2007-2008 Date 01-Mar-07 01-Apr-07 01-May-07 01-Jun-07 01-Jul-07 01-Aug-07 01-Sep-07 01-Oct-07 01-Nov-07 01-Dec-07 01-Jan-08 01-Feb-08 TOTAL X 44.27 43.13 41.18 40.54 40.66 40.55 40.88 39.73 39.37 39.56 39.42 39.36 488.65 X-M(40.72) 3.55 2.41 0.46 -0.18 -0.06 -0.17 0.16 -0.99 -1.35 -1.16 -1.30 -1.36 (X-M)2 12.60 5.80 0.21 0.03 0.00 0.03 0.03 0.98 1.82 1.35 1.69 1.85 26.40

Standard deviation= M=488.65/12=40.72 √∑(X-M)2/n= √26.40/12 =√2.2 Standard deviation =1.48

here ∑= summation M= mean

Inference : Here in this table standard deviation is done for twelve months for the year 2007-2008 .A low standard deviation indicates data points tend to be very close to mean. Hence the risk is moderate here.


STANDARD DEVIATION OF THE FORWARD RATE FOR THE YEAR 2008-2009 X Y X-M(44.73) 40.26 01-Mar-08 -4.47 39.98 01-Apr-08 -4.75 01-May-08 40.65 -4.08 42.24 01-Jun-08 -2.49 01-Jul-08 43.26 -1.47 01-Aug-08 42.38 -2.35 01-Sep-08 44.2 -0.53 01-Oct-08 46.96 2.23 01-Nov-08 48.95 4.22 01-Dec-08 50.06 5.33 01-Jan-09 48.86 4.13 01-Feb-09 49.01 4.28 536.81 TOTAL (X-M)2 20.02 22.60 16.68 6.22 2.17 5.54 0.29 4.95 17.77 28.36 17.02 18.28 159.92

Standard deviation= M=536.81/12=44.73 √∑(X-M)2/n= √159.92/12 =√13.32 Standard deviation =3.7

here ∑= summation M= mean

Inference : Here in this table standard deviation is done for twelve months for the year 2007-2008 .A high standard deviation indicates data are spread out over a large range. Hence the risk is very high here.


STANDARD DEVIATION OF THE FORWARD RATE FOR THE YEAR 2009-2010 X 01-Mar-09 01-Apr-09 01-May-09 01-Jun-09 01-Jul-09 01-Aug-09 01-Sep-09 01-Oct-09 01-Nov-09 01-Dec-09 01-Jan-10 01-Feb-10 TOTAL Y 51.75 50.28 49.68 46.99 48.09 47.86 48.88 47.86 47.03 46.45 46.64 46.34 577.83 X-M(48.15) 3.60 2.13 1.53 -1.16 -0.06 -0.30 0.72 -0.29 -1.12 -1.71 -1.52 -1.81 (X-M)2 12.94201 4.526256 2.333256 1.351406 0.003906 0.088506 0.522006 0.085556 1.260006 2.915556 2.302806 3.285156 31.61643

Standard deviation= M=577.83/12=48.15 √∑(X-M)2/n= √31.61/12 =√2.6 Standard deviation =1.62

here ∑= summation M= mean

Inference : Here in this table standard deviation is done for twelve months for the year 2009-2010 .A low standard deviation indicates data points tend to be very close to mean. Hence the risk is moderate here.


STANDARD DEVIATION OF THE FORWARD RATE FOR THE YEAR 2010-2011 X 01-MAR-10 01-APR-10 01-MAY-10 01-JUN-10 01-JUL-10 01-AUG-10 01-SEP-10 01-OCT-10 01-NOV-10 01-DEC-10 01-JAN-11 01-FEB-11 TOTAL Y 46.02 44.715 44.56 46.69 46.68 46.195 46.865 44.675 44.4 45.7 44.665 45.585 546.75 X-M(45.56) 0.46 -0.85 -1.00 1.13 1.12 0.63 1.30 -0.89 -1.16 0.14 -0.90 0.02 (X-M)2 0.21 0.72 1.01 1.27 1.25 0.40 1.70 0.79 1.35 0.02 0.81 0.00 9.51

Standard deviation= M=546.75/12=45.56 √∑(X-M)2/n= √9.51/12 =√0.79 Standard deviation =.89

here ∑= summation M= mean

Inference : Here in this table standard deviation is done for twelve months for the year 2010-2011 .A low standard deviation indicates data points tend to be very close to mean. Hence the risk is very low here.


STANDARD DEVIATION OF THE FOREIGN EXCHANGE RATE FOR THE PERIOD OF DEC 2011-MAY 2012(CURRENT SIX MONTHS) DATE 01-Dec-11 01-Jan-12 01-Feb-12 01-Mar-12 01-Apr-12 01-May-12 15-May-12 TOTAL X 51.12 53.31 49.09 49.52 51.09 52.62 55.39 362.14 X-M(51.73) -0.61 1.58 -2.64 -2.21 -0.64 0.89 3.99 (X-M)2 0.38 2.48 6.99 4.90 0.42 0.78 13.40 29.35 here ∑= summation M= mean

Standard deviation= M=362.14/7=51.73 √∑(X-M)2/n= √29.35/7 =√4.19 Standard deviation =2.05

Inference : Here in this table standard deviation is done for six months.A high standard deviation indicates data are spread out over a large range. Hence the risk is very high here


 In foreign exchange transactions ,Future Focus InfoTech company is dealing with export transactions only.  The company has faced exchange loss in the year 2006-2007, 2007-2008.  In the year 2008-2009 there is a loss even after applying the forward rates, but the loss has occurred while comparing the exchange received amount, the reason is in the year 2008 the rate had increased much more higher than expected compared to the forward rates than in the exchange.  In the standard deviation, the company has more data points tend to be very close to mean.  In the standard deviation, while comparing the recent six months study it is found that the data points are very spread out over large range. Here the risk is very high market can fall at any time. Its better to sell of the shares which is bought .  There is an increase in the profit from the year 2006-2007,2007-2008 and 2009-2010 and 2010-2011 by applying the forward rates.


 It is suggested that the foreign exchange transactions are to be fully covered through the forward contracts with the banks.  If the company goes for the future contracts, which is derived from the exchange rates it would be much more beneficial to, the company but high risk compared to forward.  The researcher suggests that the company should apply financial instruments such as forward contract to reduce the risk in foreign exchange.  The researcher suggests that the company should apply financial tool such as standard deviation to reduce the risk in foreign exchange which is helpful in future contracts  As it has been identified a high risk in the past 6 months currency rate fluctuation ,it is suggested to hedge the currency position through forward contracts/future contracts in the exchange.  If the company goes into the import transactions with overseas customers in future then also the company may resort to risk cover operations for the foreign exchange transaction by booking the forward contracts or the future contracts in the designated currencies.  The researcher suggests expanding the business in various currencies to earn more of foreign exchange profit.



 The company is dealing with only export transactions in their foreign exchange operations.
 The future contract is commenced only from the year 2008. Hence previous

years study could not be studied specifically.
 The company is dealing only with USD dollar currency hence there is no

scope to study other currency risk in this project.



The study titled ―An Analysis of Foreign Exchange Transactions of Software Company with Special Reference to Future Focus InfoTech Private Limited‖ helps to understand about foreign exchange operations and to understand the foreign currency risk in the export transactions of the company. The researcher has identified the reason to control the loss and to avoid the risk in the foreign exchange by applying forward contracts and also apply standard deviation tool to know the frequent fluctuations in the currency which can be applied in the future contract. The company is dealing with export transactions and if the company takes actions as suggested, company would be able to remain risk free in the currency fluctuations in future. The company would excel in IT Products by using risk free financial instruments, which could give excellent corporate results.

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