1.1 INTRODUCTION TO THE STUDY

The Foreign Exchange Market is the largest financial market in the world with an

estimated $1.5- $4 trillion in currencies traded daily. To grasp the vast size of the volume in this

market, it would take the (NYSE) New York Stock Exchange at least three months to reach the

amount traded in one day on the Forex market. One of the reasons for this vast volume is that

unlike other financial markets, forex is not tied to an actual stock exchange, it is an over the

counter (OTC) market. Also, this is a 24 hour market, meaning there is no closing time or

opening time and individuals/institutions can trade the whole day.

Money exchange has been around in different forms for thousands of years. Evidently, its

practice has been evolving throughout time. The first currency traders were the moneychangers

from the Middle East introducing the coin exchange between cultures. A different form of

currency was first utilized by the Babylonians who utilized paper bills and receipts. However,

this idea was later implemented during the middle ages in order to ease the foreign money

exchange trading for merchants. Long before the foreign exchange market was created in 1973

as it is known today, it went through several alterations during its early stages. At the end of

World War I it stopped being a quite stable market. The volatility as well as the speculative

activity increased which was not as promising for many institutions at the time. The elimination

of the gold standard in 1913 along with the Great Depression caused the market to lose activity.

Changes made to the market from 1931 to 1973 extremely affected the global economies and

speculative activity was nearly null. The World War II had an enormous effect in the

development of the forex market and some currencies. After the stock market crash of 1929 the

US dollar was but an unsuccessful currency until the World War II turned it around making it the

most popular benchmarking currency. While on the contrary, the Great British Pound was

tremendously affected by the Nazis losing its popularity as a major currency. It was not until the

end World War II that in efforts to support the global economies Great Britain, France and the

United States joined forces. Due to the United States was the only untouched country by war, the

three nations met in Bretton Woods, New Hampshire, at was it was called the United Nations

Monetary and Financial Conference. At the conference the Bretton Woods Accord was

established to provide a safe setting in which global economies could reinstate them. The

pegging of currencies and the International Monetary Fund (IMF) were established by the

Bretton Woods Accord. Major currencies pegged to the 8 United States currencies given its

strength at the time, and fluctuation of one percent on both sides of the set standard was allowed

for these currencies. In case a currency’s exchange rate would reach the limit on either side of

the standard, the banks were responsible for bringing the rate back into the range. The agreement

failed eventually, but brought back stability for Europe and Japan’s economy. Similar

agreements were established with a greater fluctuation band for currencies such as the

Smithsonian Agreement in 1971 and The European Joint Float in 1972. This last agreement was

an attempt by the European society to be independent form the United States currency. Yet, in

1973 both agreements failed committing similar mistakes to the Bretton Woods Accord and the

free floating system emerged as a result. This system was officially accredited in 1978 allowing

currencies to freely peg or float. During the same year a second effort for independence from the

US dollar was made by Europe presenting the European Monetary System which shared the

same faith of prior agreements failing in 1993.Since then the free-floating system has been used

world-wide allowing currencies to move freely from other currencies and letting anyone to

become a trader. Speculative activity has increased from all types of traders, from bank to just an

individual trader. Sporadically central banks would interfere to move currencies to their levels.

However the forex market working on supply and demand has been the main factor that caused

its success since the global free-floating system. This great market was only open to banks and

big corporations; nevertheless thanks to the advances in technology it became available to

everyone in 1995. Unlike traditional trading in which traders were required to meet in a single

location called trading rooms to perform the 9 transactions, the Internet allowed individuals to

trade from home at any time. These advantages allowed the foreign exchange market to become

the fastest and most profitable trading market world-wide.

1.2 INDUSTRY PROFILE

1.2.1 FINANCIAL SYSTEM: INTRODUCTION

The development of any country depends upon the existence of a well-organized

financial system. It is the financial system which supplies the necessary financial input for

production of goods and services which in turn promote the wellbeing and standard of living of

the people of a country.

Financial system is a boarder term which brings under its fold the financial market and

financial institution which support the system. Generally speaking there is no specific place or

location to indicate a financial market. Wherever a financial transaction takes place, it is deemed

to have taken place in the financial market. So it can be said as the mechanism or system through

which financial assets are created and transferred is known as financial market.

When the financial asset transferred are corporate securities and government securities,

such mechanism of transfer is known as securities market. Some serious attention was paid to the

development of a sound financial system in India only after the launching of planning era in the

country. At the time of independence in 1947, there was no strong financial institutional

mechanism in the country. There was absence of issuing institution and nonparticipation of

intermediary financial institutions. The industrial sector also had no access to the saving of the

community. The capital market was very primitive and shy. The private as well as the

unorganized sector played a key role in the provision of in the provision of ‘liquidity’. On the

whole, chaotic conditions prevailed in the system.

With the adoption of theory of mixed economy, the development of the financial system

took a different turn so as to fulfill the socio-economic and political objectives. The Government

started creation of new financial institution to supply finance both for agricultural and industrial

development and it also progressively started nationalizing some important financial institution

so that the flow of finance might be in the right direction.

1.2.2 FINANCIAL MARKET

Wherever a financial transaction takes place, it is deemed to have taken place in the

financial market. So it can be said as the mechanism or system through which financial assets are

created and transferred is known as financial market. Hence, financial markets are pervasive in

nature since, financial transactions are themselves very pervasive throughout the economic

system. For instance, issue of equity shares, granting of loan by term lending institutions, deposit

of money into bank, purchase of debentures, sale of share and so on.

The financial market may be classified as primary market and secondary market

depending on whether the securities traded are newly issued securities or securities already

outstanding and owned by investors. The market mechanism for the buying and selling of new

issue of securities is known as primary market. This market is also termed as new issue markets

because it deals with new issue of securities. The secondary market, on the other hand, deals

with securities which have already being issued and are owned by investors. The buying and

selling of securities already issued and outstanding take place in stock exchange. Hence, stock

exchange constitutes the secondary market in securities.

Participants in financial market

A financial market is essentially a system by which financial securities are exchanged.

This system is composed of participants, securities, markets, trading arrangements and

regulations. The major participants are the buyers and sellers of securities or the investors and

issuer. Financial intermediaries are the second major class of participants in the financial market.

The term financial intermediary includes all kinds of organization which intermediate and

facilitate financial transaction of both individuals and corporate customers. Thus, it refers to all

kinds of financial institutions and investing institutions which facilitate financial transaction in

financial market.

1.2.3 FOREIGN EXCHANGE

The word FOREX is derived from the words foreign exchange and is the largest financial

market in the world. Foreign Exchange is a type of financial trading in which the currency of a

country is exchanges for that of another. With a daily turnover of over$4.9 trillion, the forex

market is the largest financial trading market in the world. The market is open 24 hours a day,

five and a half days a week across almost every time zone. For instance, when the trading day in

the US ends, the Forex market begins a new in Tokyo and Hong Kong. As such, the Forex

market can be extremely active any time of the day, with price quotes changing constantly.

The Forex market started evolving in the 1970s when international trade switched from a

fixed rate (set by the Bretton Woods Agreement) to a floating exchange rate. Since then, the

relative rates of currencies have been determined by buying and selling activity within the

international foreign exchange market. When more of a currency is bought, its relative price goes

up, and when more is sold its price goes down.

History of Foreign Exchange

Before money became the official standard of exchange people exchanged goods and

services through barter. It wasn’t until the establishment of paper money and a set of standard

characteristics for money in all countries was introduced that a refined international commerce

system was developed. Early examples of money were gold and silver coins and when paper

money began circulating it was backed by the concept that the holder of paper could at any time

request convertibility into gold. If a dollar holder found that his dollar holdings were falling in

value he could exchange them for gold and essentially reduce the amount of dollars in circulation

which in turn stabilized the dollar and then caused it to appreciate. The exchange into gold from

dollars was then reserved. Although the gold standard seemed and sounded ideal nevertheless it

was ended in the 1930’s.

At Bretton Woods in 1944 a new International Monetary System was established. This

system set a gold based value for the dollar and the British pound and linked all other currencies

to the dollar. Gold was set at $35 an ounce and the international monetary fund was founded with

a purpose to help member countries who needed monetary assistance. As economies grew after

the war the supply of dollars in Europe was soon worth more than the amount of gold in the

USA.

In 1956, the Eurodollar market was formed. Eurodollars were dollars held by non-US

banks outside the USA therefore they were not regulated by the US. As these dollars were not

regulated they bore a higher risk premium and their yield was higher than domestic dollars. It

was from this liquid market that Forex forwards and Forex swaps were born. In the early

seventies due to the pressure on the dollar convertibility into gold was suspended and the

German mark was allowed to revalue. Later the price of gold was again fixed but this time at $38

per ounce in 1963 the dollar was under immense pressure again and it was devalued by 10%. The

Bretton Woods system had finally collapsed and the dollar was allowed to freely float against

other currencies. The era of fixed exchange rates had ended and the era of floating exchange

rates was ushered in. With it came the European Monetary System (EMS) formed in 1979 where

European currencies were floating in a band against the dollar and eventually in the introduction

of the single currency in 1999.

History of Foreign Exchange Markets

At the end of World War II, the major countries of the world set up the International

Monetary Fund (IMF). The IMF is an international organization that monitors balance of

payments and exchange rate activities. In July 1944, at Bretton Woods, new Hampshire, 44

countries signed the Articles of Agreement of the IMF. At the centerpiece of those agreements

were the establishments of a worldwide system of fixed exchange rates between countries. The

anchor for this fixed exchange rate system was gold. One ounce of gold was defined to be worth

35 US dollars. All other currencies were pegged to the US dollar at a fixed exchange rate.

Although the fixed exchange system served well during the 1950 and early 1960, it came

under increasing strain in the late 1960s and by 1971 the order was almost collapsed. Most

economists’ trace the breakup of the fixed exchange rate system to the US macroeconomic

policy package of 1965-68 to finance both the Vietnam conflict and its welfare programs,

President Johnson backed an increase in us government spending that was not financed by an

increase in taxes. Instead, it was financed by an increase in money supply, which in turn, led to

rise in price inflation from less than 4% in 1966 to close to 9% by 1968. With more money in

their pockets the American spent more, particularly on imports, from here the US trade balance

started to deteriorate rapidly.

The rise in inflation and the worsening of US trade position gave support to the

speculation in the foreign exchange market that the dollar would be devalued. Things came to a

head on spring 1971, when US trade figures were released, which showed that for the first time

since 1945, the United States was importing more than it was exporting. This set off the massive

purchases of Deutsche Marks by the speculators who guessed that the DM would revalue against

the dollar. On a single day may, 4, 1971 the Bundesbank had to buy $1billion to hold the

dollar/DM rate at its fixed exchange rate given the great demand for DMs. On the morning of

May 5, the Bundesbank purchased another $1 billion during the first hour of the trading. At that

point, the Bundesbank faced the inevitable and allowed its currency to float.

Gold Standard System

The creation of the gold standard monetary system in 1875 is one of the most important

events in the history of the Forex market. Before the gold standard was created, countries would

commonly use gold and silver as method of international payment. The main issue with using

gold and silver for payment is that the value of these metals is greatly affected by global supply

and demand. For example, the discovery of a new gold mine would drive gold prices down.

The basic idea behind the gold standard was that governments guaranteed the conversion

of currency into a specific amount of gold, and vice versa. In other words, a currency was backed

by gold. Obviously, governments needed a fairly substantial gold reserve in order to meet the

demand for currency exchanges. During the late nineteenth century, all of the major economic

countries had pegged an amount of currency to an ounce of gold. Over time, the difference in

price of an ounce of gold between two currencies became the exchange rate for those two

currencies. This represented the first official means of currency exchange in history.

The gold standard eventually broke down during the beginning of World War I. Due to

the political tension with Germany, the major European powers felt a need to complete large

military projects, so they began printing more money to help pay for these projects. The financial

burden of these projects was so substantial that there was not enough gold at the time to

exchange for all the extra currency that the governments were printing off.

After Bretton Woods

Switching away from the fixed currency system after 27 years out of necessity, not by

choice was a difficult task. The Smithsonian Agreement reached in Washington in December

1971 had a transactional role to the free-floating markets. This agreement failed to address the

real cause behind the international economic and financial pressure, focusing instead on

increasing the range of currency fluctuation. From 1% the band of foreign currencies fluctuation

was expanded to 4.5%.

Parallel to Washington’s efforts, the European Economic Community, established in

1957, tried to move away from the US dollar block toward the deutsche mark block, by

designing its own monetary system. In April 1972, West Germany, France, Italy, the

Netherlands, Belgium and Luxembourg developed the European joint float. Under this system

the member countries were allowed to move between 2.25 % band, known as the snake, against

each other, and collectively within 4.5% band, known as the tunnel, against the US dollar.

Unfortunately, both the Smithsonian institution agreement and the European joint float

did not address the independent domestic problems of the member countries from the bottom up,

attempting instead to focus solely on the large international picture and maintain it by artificially

enforcing the intervention points. By 1973, both systems collapsed under heavy market

pressures.

The idea of regional currency stability with the goal of financial independence from the

US dollar block persisted. By July 1978, the members of the European community approved the

plans for the European Monetary System: West Germany, France, Italy, Netherlands, Belgium,

Great Britain, Denmark, Ireland and Luxembourg. The system was launched in March 1979, as a

revamped European joint float, or a mini Bretton Woods Accord. Additional features, such as the

threshold of divergence, were designed to protect this monetary system from the fate of the

previous ones. Judging from its expended life span, until 1993 at least the European Monetary

System was obviously better. Until it proved to be devastating in 1992, when the Pound fell

against the dollar from 2.01 to 1.4000 with days.

The Beginning of the Free-Floating System

After the Bretton Woods Accord came the Smithsonian Agreement in December of 1971.

This agreement was similar to the Bretton Woods Accord, but allowed for a greater fluctuation

band for the currencies. In 1972, the European community tried to move from its dependency on

the dollar. The European Joint Float was established by West Germany, France, Italy,

Netherlands, Belgium and Luxemburg. The agreement was similar to the Bretton woods accord,

but allowed a greater range of fluctuation in the currency values.

Both agreements made mistakes similar to the Bretton Woods Accord and in 1973

collapsed. The collapse of the Smithsonian Agreement and the European Joint Float in 1973

signified the official switch to the free-floating system. This occurred by default as there were no

new agreements to take their place. Governments were now free floating system was officially

mandated.

In a final effort to gain independence from the dollar, Europe created the European

Monetary System in July of 1978. Like all of the previous agreements, it failed in 1993.

The major currencies today move independently from other currencies. The currencies

are traded by anyone who wishes. This has caused a recent influx of speculation by banks, hedge

funds, brokerage houses and individuals. Central banks intervene on occasion to move or attempt

to move currencies to their desired levels. The underlying factor that drives today’s Forex

markets, however, is supply and demand. The free-floating system is ideal for today’s Forex

markets. It will be interesting to see if in the future our planet endures another war similar to

those of the early 20th century.

Time Line of Foreign Exchange

1944 Bretton Woods Accord is established to help stabilize the global

economy after World War 11

1971 Smithsonian Agreement established to allow for greater

fluctuation band for currencies

1972 European Joint Float established as the European Community tried

to move away from its dependency on the US dollar

1973 Smithsonian Agreement and European Joint Float failed and

signified the official switch to a Free-Floating System

1978 The European Monetary System was introduced so other countries

could try to gain independence from the US dollar

1978 Free-Floating System officially mandated by the IMF

1993 European Monetary System fails making way for a world-wide

Free- Floating System

Forex Market in India

The evolution of India’s foreign exchange market may be viewed in line with the shifts in

India’s exchange rate policies over the last few decades from a par value system to a basket-peg

and further to a managed float exchange rate system. During the period from 1947to 1971, India

followed the par value system of exchange rate. Initially the rupee’s external par value was fixed

at 4.15 grains of fine gold. The reserve bank maintained the par value of the rupee within the

permitted margin of +1 or -1 percent using pound sterling as the intervention currency. Since the

sterling-dollar exchange rate was kept stable by the US monetary authority, the exchange rates of

rupee in terms of gold as well as the dollar and other currencies were indirectly kept stable. The

devaluation of rupee in September 1949 and June 1966 in terms of gold resulted in the reduction

of the par value of rupee in terms of gold to 2.88 and 1.83 grains of fine gold, respectively. The

exchange rate of the rupee remained unchanged between 1966 and 1971.

Given the fixed exchange regime during this period, the foreign exchange market for all

practical purposes was defunct. Banks were required to undertake only cover operations and

maintain a ‘square’ or ‘near square’ position at all times. The objective of exchange controls was

primarily to regulate the demand for foreign exchange for various purposes, within the limit set

by the available supply. The Foreign Exchange Regulation Act initially enacted in 1947 was

placed on a permanent basis in 1957. In terms of the provisions of the act, the reserve bank, and

in certain cases, the central government controlled and regulated the dealings in foreign

exchange payments outside India, export and import of currency notes and bullion, transfers of

securities between residents and non-residents, acquisition of foreign securities, etc.

With the breakdown of the Bretton Woods System in1971 and the floatation of major

currencies, the conduct of exchange rate policy posed a serious challenge to all central banks

world wide as currency fluctuations opened up tremendous opportunities for market players to

trade in currencies in a borderless market. In December 1971, the rupee was linked with pound

sterling. Since sterling was fixed in terms of us dollar under the Smithsonian agreement of 1971,

the rupee also remained stable against dollar. In order to overcome the weakness associated with

a single currency peg and to ensure stability of the exchange rate, the rupee, with effect from

September 1975, was pegged to a basket of currencies. The currency selection and weights

assigned were left to the discretion of the reserve bank. The currencies included in the basket as

well as their relative weights were kept confidential in order to discourage speculation. It was

around this time that banks in India became interested in trading in foreign exchange.

Foreign Exchange Market in India: Historical Perspective

Indian Forex market since independence can be grouped in three distinct phases.

1947-1977: During 1947 to 1977, India exchange rate system followed the par value

system. RBI fixed rupee’s external par value at 4.15 grains of fine gold. 15.432 grains of gold is

equivalent to 1 gram of gold. RBI allowed the par value to fluctuate within the permitted margin

of +1 or -1 percent. With the breakdown of the Bretton Woods System in 1971 and the floatation

of major currencies, the rupee was linked with pound-sterling. Since pound-sterling was fixed in

terms of US dollar under the Smithsonian Agreement of 1971, the rupee also remained stable

against dollar.

1978-1992: During this period, exchange rate of the rupee was officially determined in

terms of a weighted basket of currencies of India’s major trading partners. During this period,

RBI set the rate by daily announcing the buying and selling rates to authorized dealers. In other

words, RBI instructed authorized dealers to buy and sell foreign currency at the rate given by the

RBI on daily basis. Hence exchange rate fluctuated but within a certain range. RBI managed the

exchange rate in such a manner so that it primarily facilitates imports to India.

India’s perennial trade deficit widened during this period. By the beginning of 1991,

Indian foreign exchange reserve had dwindled down to such a level that it could barely be

sufficient for three-week’s worth of imports. During June 1991, India airlifted 67 tons of gold,

pledged these with Union Bank of Switzerland and Bank of England, and raised US $ 605

million to shore up its precarious Forex reserve. At the height of the crisis, between 2 nd and 4th

June 1991, rupee was officially devalued by 19.5%from 20.5 to 24.5 to 1 US $. This crisis paved

the path to the famed “liberalization program” of government of India to make rules and

regulations pertaining to foreign trade, investment, public finance and exchange rate

encompassing a broad gamut of economic activities more market oriented.

1992 onwards: 1992 marked a watershed in India’s economic condition. During this

period, it was felt that India needs to have an integrated policy combining various aspects of

trade, industry, foreign investment, exchange rate, public finance and the financial sector to

create a market-oriented environment. Many policy changes were brought in covering different

aspects of import-export, FDI, Foreign Portfolio Investment etc.

One important policy changes pertinent to India’s Forex exchange system was brought in

rupees was made convertible in current account. This paved to the path of foreign exchange

payments/receipts to be converted at market-determined exchange rate. However, it is

worthwhile to mention here that changes brought in by government of India to make the

exchange rate market oriented have not happened in one big bang. This process has been gradual

A Brief History of FOREX Trading

The creation of the gold standard monetary system in 1875 marked one of the most

significant events in the history of the Forex currency market. As countries each attached an

amount of their currency to be equal to an ounce of gold the changing price of gold between two

currencies became the first standardized means of currency exchange in history.

World War I brought with it the breakdown of the gold standard due to the major

European powers not having enough gold to exchange for all the currency that the governments

were printing off at the time in order to complete large military projects. The gold standard was

used again between the wars, but by the start of World War II most countries had again dropped

it, however gold never lost its spot as the ultimate form of monetary value.

In 1944 the Bretton Woods System was implemented and led to the formation of fixed

exchange rates that resulted in the U.S. dollar replacing the gold standard as the primary reserve

currency. This also meant that the U.S. dollar became the only currency that would be backed by

gold. In 1971 the U.S. declared that it would no longer exchange gold for U.S. dollars that were

held in foreign reserves, this market the end of the Bretton Woods System.

It was this break down of the Bretton Woods System that ultimately led to the mostly

global acceptance of floating foreign exchange rates in 1976. This was effectively the “birth” of

the current foreign currency exchange, although it did become widely electronically traded until

about the mid 1990s.

Uses of Forex Market

Forex trading involves transactions in which one party purchases a quantity of one

currency by paying in a quantity of another currency. The Forex market is a global decentralized

financial market for the exchange of currencies. Around the world various financial centers act

as hubs for trading between a wide range of different types of buyers and sellers 24 hours a day,

except weekends. It is the foreign exchange market that determines the value of one country’s

currency relative to another. The primary reason the Forex market exists is to facilitate

international trade and investment by giving businesses the ability to convert one currency into

another.

Benefits of Trading the Forex market

Trading can be done from anywhere in the world through internet facility.

Huge trading volume, this leads to dense liquidity making it easier to get in and out of

positions at the price seller want.

Greater availability of leverage to enhance profit margins relative to account size than

compare to other markets.

Fewer variables to consider as compared to stock or commodity trading.

No inherent market bias like the bullish bias stocks, this means greater opportunities to

profit from the volatility in both rising and falling markets.

Ease of accessibility and low start-up costs.

Advantages like the ones listed above and others are the reason why the Forex market has

been referred to as the market closest to the ideal of “perfect competition”. According to the

Bank for International Settlements, average daily turnover in global foreign exchange

markets is estimated at $3.98 trillion, as of April 2010 a growth of approximately 20% over

the $3.21 trillion daily volume recorded in April 2007.

The Most Traded Forex Currencies

United States dollar = 84.9%

Euro = 39.1%

Japanese yen = 19.0%

Pound Sterling = 12.9%

Australian dollar = 7.6%

Swiss franc = 6.4%

Canadian dollar = 5.3%

Hong Kong dollar = 2.4%

New Zealand = 1.6%

1.2.4 MARKET PARTICIPANTS

Unlike a stock market, the foreign exchange market is divided into levels of access. at the

top is the inter-bank market, which is made up of the largest commercial banks and securities

dealers. Within the inter-bank market, spreads, which are the difference between the bids and ask

prices, are razor sharp and not known to players outside the inner circle. The difference between

the bid and ask prices widens (for example from 0-1 pip to 1-2 pips for a currencies such as the

euro) as you go down the levels of access. This is due to volume. If a trader can guarantee large

numbers of transactions for large amounts, they can demand a smaller difference between the bid

and ask price, which is referred to as a better spread. The levels of access that make up the

foreign exchange market are determined by the size of the "line" (the amount of money with

which they are trading). The top-tier interbank market accounts for 53% of all transactions. From

there, smaller banks, followed by large multi-national corporations (which need to hedge risk

and pay employees in different countries), large hedge funds, and even some of the retail FX

market makers. Central banks also participate in the foreign exchange market to align currencies

to their economic needs.

Banks

The interbank market caters for both the majority of commercial turnover and large

amounts of speculative trading every day. Many large banks may trade billions of dollars, daily.

Some of this trading is undertaken on behalf of customers, but much is conducted by proprietary

desks, which are trading desks for the bank's own account. Until recently, foreign exchange

brokers did large amounts of business, facilitating interbank trading and matching anonymous

counterparts for large fees. Today, however, much of this business has moved on to more

efficient electronic systems. The broker squawk box lets traders listen in on ongoing interbank

trading and is heard in most trading rooms, but turnover is noticeably smaller than just a few

years ago.

Commercial companies

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 fairly 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.

Central banks

National central banks play an important role in the foreign exchange markets. They try

to control the money supply, inflation, and/or interest rates and often have official or unofficial

target rates for their currencies. They can use their often substantial foreign exchange reserves to

stabilize the market. Nevertheless, the effectiveness of central bank "stabilizing speculation" is

doubtful because central banks do not go bankrupt if they make large losses, like other traders

would, and there is no convincing evidence that they do make a profit trading.

Forex fixing

Forex fixing is the daily monetary exchange rate fixed by the national bank of each

country. The idea is that central banks use the fixing time and exchange rate to evaluate behavior

of their currency. Fixing exchange rates reflects the real value of equilibrium in the forex market.

Banks, dealers and online foreign exchange traders use fixing rates as a trend indicator. The mere

expectation or rumour of central bank intervention might be enough to stabilize a currency, but

aggressive intervention might be used several times each year in countries with a dirty float

currency regime. Central banks do not always achieve their objectives. The combined resources

of the market can easily overwhelm any central bank. Several scenarios of this nature were seen

in the 1992–93 erm collapse and in more recent times in Southeast Asia.

Hedge funds as speculators

About 70% to 90% of the foreign exchange transactions are speculative. In other words,

the person or institution that bought or sold the currency has no plan to actually take delivery of

the currency in the end; rather, they were solely speculating on the movement of that particular

currency. Hedge funds have gained a reputation for aggressive currency speculation since 1996.

They control billions of dollars of equity and may borrow billions more, and thus may

overwhelm intervention by central banks to support almost any currency, if the economic

fundamentals are in the hedge funds' favor.

Investment management firms

Investment management firms (who typically manage large accounts on behalf of

customers such as pension funds and endowments) use the foreign exchange market to facilitate

transactions in foreign securities. For example, an investment manager bearing an international

equity portfolio needs to purchase and sell several pairs of foreign currencies to pay for foreign

securities purchases. Some investment management firms also have more speculative specialist

currency overlay operations, which manage clients' currency exposures with the aim of

generating profits as well as limiting risk. Specialist firms is quite small, many have a large value

of assets under management (AUM), and hence can generate large trades.

Non-bank foreign exchange companies

Non-bank foreign exchange companies offer currency exchange and international

payments to private individuals and companies. these are also known as foreign exchange

brokers but are distinct in that they do not offer speculative trading but rather currency exchange

with payments (i.e., there is usually a physical delivery of currency to a bank account).it is

estimated that in the UK, 14% of currency transfers/payments are made via foreign exchange

companies. These companies' selling point is usually that they will offer better exchange rates or

cheaper payments than the customer's bank. These companies differ from money

transfer/remittance companies in that they generally offer higher-value services.

1.2.5 FINANCIAL INSTRUMENTS

SPOT MARKET

A foreign exchange spot market is a market for trading one currency against another in

such a way that the delivery takes place within 2 days of the execution of the trade. It usually

takes two days to transfer cash from one bank to the other. 

The price is based on the ongoing exchange rate i.e. the current value of one country's currency

relative to another. The foreign exchange spot market is the largest market in the world with

a transaction of more than US $ 1 trillion in a single day. The forex futures market is a minor

derivative of this market and its size is 1/100th of that of the foreign exchange spot market. 

Nature of Foreign Exchange Spot Market

A currency's spot rate is expressed as its value relative to the US dollar i.e. the number of

US dollars needed to buy one unit of the other currency. A foreign exchange spot market allows

a company to buy or sell a foreign currency according to its requirements. But even the daily

movements in spot exchange rates are characterized by a number of vagaries. 

So those operating in this market are speculators rather than trend-followers. For this

reason, it exposes an entrepreneur's cash management to a number of unpleasant alterations in

foreign currencies. 

The spot rate of a currency can be affected by various reasons such as the current

and future expectations about the inflation rate, BOP (Balance Of Payments) situation, policies

created by government and central bank and other economic indicators of the country. 

Reasons for the trades to be settled 'on the spot':

Foreign exchange spot market is the most common form of currency trade because if the

contracts are settled afterwards, then the traders might ask for compensation against the value

that the money has gained over the duration of delivery. So these contracts are settled

instantaneously using the electronic forex systems.

FUTURE MARKET

A currency future, also FX future or foreign exchange future, is a futures contract to

exchange one currency for another at a specified date in the future at a price (exchange rate) that

is fixed on the purchase date; see Foreign exchange derivative. Typically, one of the currencies is

the US dollar. The price of a future is then in terms of US dollars per unit of other currency. This

can be different from the standard way of quoting in the spot foreign exchange markets.

The trade unit of each contract is then a certain amount of other currency, for instance €125,000.

Most contracts have physical delivery, so for those held at the end of the last trading day, actual

payments are made in each currency. However, most contracts are closed out before that.

Investors can close out the contract at any time prior to the contract's delivery date.

Currency futures were first created in 1970 at the International Commercial Exchange in

New York. But the contracts did not "take off" due to the fact that the Bretton Woods

system was still in effect. They did so a full two years before the Chicago Mercantile Exchange

(CME) in 1975, less than one year after the system of fixed exchange rates was abandoned along

with the gold standard. Some commodity traders at the CME did not have access to the inter-

bank exchange markets in the early 1970s, when they believed that significant changes were

about to take place in the currency market. The CME actually now gives credit to the

International Commercial Exchange (not to be confused with the ICE for creating the currency

contract, and state that they came up with the idea independently of the International

Commercial Exchange). The CME established the International Monetary Market (IMM) and

launched trading in seven currency futures on May 16, 1975. Today, the IMM is a division of

CME. In the fourth quarter of 2009, CME Group FX volume averaged 754,000 contracts per

day, reflecting average daily notional value of approximately $100 billion. Currently most of

these are traded electronically

Foreign exchange future market refers to a type of financial derivative in which two

parties enter into a contract to buy/sell a particular currency at a pre-determined price on a

specific future date.  A foreign exchange future market provides an opportunity to hedge risk and

speculate against the exchange rate fluctuations. 

Evolution of Foreign Exchange Future Market:

Foreign exchange future market was introduced in 1972 by the IMM (International

Monetary Market) of the CME (Chicago Mercantile Exchange). It basically replaced the notion

of 'par value exchange rates' which was followed under the Bretton Woods System. This

approach of foreign exchange future market was then adopted by many other exchanges in U.S.

and abroad. Financial instruments like futures are nowadays also used in hedging stock

exchanges and interest rates. 

Foreign Exchange Future Market gains over Traditional futures because:

Foreign exchange future market, also popularly known as forex futures market,

constitutes only 1% of the US$ 1 trillion traded in the global foreign exchange market. Foreign

exchange future market is same as that of traditional futures contract in the sense that both are

used to buy or sell an asset (a specific amount) at an agreed price on a particular future date. The

two are however different as in case of a foreign exchange future market, none of the parties

involved is actually buying or selling any commodity but currencies. This is because all quotes in

case of a foreign exchange future market are made against the U.S. dollar. Traditional futures are

traded on centralized stock exchanges whereas the deal flow of foreign exchange future markets

is available through many different exchanges in the home and foreign country. But this doesn't

imply that foreign exchange future markets are quoted in OTC (Over the Counter). They have a

designated 'size per contract' and are available in whole numbers.

Other features of a Foreign Exchange Future Market:

A foreign exchange future market is 'marked to market' thus making it a portfolio of

forward contracts that are adjusted daily for cash settlements. This in fact mitigates the credit risk

to a very large extent.

These are carried out through the clearing house of the exchange. The margin payments

accrue to the exchange and the exchange ensures the proper functioning of the contract. A

foreign exchange future market contract rarely results in a delivery. It is used by parties as it is a

highly liquid way of hedging and speculating and efficient transactions can be fixed up without

delay.

FORWARDS

One way to deal with the foreign exchange risk is to engage in a forward transaction. In

this transaction, money does not actually change hands until some agreed upon future date. A

buyer and seller agree on an exchange rate for any date in the future, and the transaction occurs

on that date, regardless of what the market rates are then. The duration of the trade can be one

day, a few days, months or years. Usually the date is decided by both parties. Then the forward

contract is negotiated and agreed upon by both parties.

SWAPS

The most common type of forward transaction is the FX swap. In an FX swap, two

parties exchange currencies for a certain length of time and agree to reverse the transaction at a

later date. These are not standardized contracts and are not traded through an exchange.

OPTIONS

A foreign exchange option (commonly shortened to just fx option) is a derivative where

the owner has the right but not the obligation to exchange money denominated in one currency

into another currency at a pre-agreed exchange rate on a specified date. The FX options market is

the deepest, largest and most liquid market for options of any kind in the world.

1.2.6 CURRENCY FUTURES IN INDIA

A currency future, also known as FX future, is a futures contract to exchange one

currency for another at a specified date in the future at a price (exchange rate) that is fixed on the

purchase date. On NSE the price of a future contract is in terms of INR per unit of other currency

e.g. US Dollars. Currency future contracts allow investors to hedge against foreign exchange

risk. Currency Derivatives are available on four currency pairs viz. US Dollars (USD), Euro

(EUR), Great Britain Pound (GBP) and Japanese Yen (JPY). Currency options are currently

available on US Dollars.

NSE was the first exchange to have received an in-principle approval from SEBI for

setting up currency derivative segment. The exchange launched its currency futures trading

platform on 29th August, 2008. Currency futures on USD-INR were introduced for trading and

subsequently the Indian rupee was allowed to trade against other currencies such as euro, pound

sterling and the Japanese yen. Currency Options was introduced on October 29, 2010.

Major Currency Pairs

The most traded currency pairs in the world are called the majors. The list includes

following currencies: Euro (EUR), US Dollar (USD), Japanese Yen (JPY), Pound Sterling

(GBP), Australian Dollar (AUD), Canadian Dollar (CAD), and Swiss Franc (CHF). These

currencies follow free floating method of evaluation. Amongst these currencies the most active

currency pairs are: EURUSD, USDJPY, GBPUSD, AUDUSD, CADUSD and USDCHF.

According to Bank of International Settlement (BIS) survey of April 2010, the share of different

currency pairs in daily trading volume is given below:

Currency Share (%)

EUR/USD 28

USD/JPY 14

GBP/USD 9

AUD/USD 6

USD/CHF 4

USD/CAD 5

USD/Others 18

Others/Others 16

Total 100

Basics of currency markets and peculiarities in India

Currency pair

Unlike any other traded asset class, the most significant part of currency market is the

concept of currency pairs. In currency market, while initiating a trade you buy one currency and

sell another currency. Therefore same currency will have very different value against every other

currency. For example, same USD is valued at say 45 against INR and says 82 against JPY. This

peculiarity makes currency market interesting and relatively complex. For major currency pairs,

economic development in each of the underlying country would impact value of each of the

currency, although in varying degree. The currency dealers have to keep abreast with latest

happening in each of the country.

Base Currency / Quotation Currency

Every trade in FX market is a currency pair: one currency is bought with or sold for

another currency. We need to identify the two currencies in a trade by giving them a name. The

names cannot be “foreign currency” and “domestic currency” because what is foreign currency

in one country is the domestic currency in the other. The two currencies are called “base

currency” (BC) and “quoting currency” (QC). The BC is the currency that is priced and its

amount is fixed at one unit. The other currency is the QC, which prices the BC, and its amount

varies as the price of BC varies in the market. What is quoted throughout the FX market

anywhere in the world is the price of BC expressed in QC. There is no exception to this rule.

For the currency pair, the standard practice is to write the BC code first followed by the

QC code. For example, in USDINR (or USDINR), USD is the BC and INR is the quoted

currency; and what is quoted in the market is the price of USD expressed in INR. If you want the

price of INR expressed in USD, then you must specify the currency pair as INRUSD. Therefore

if a dealer quotes a price of USDINR as 45, it means that one unit of USD has a value of 45 INR.

Similarly, GBPUSD = 1.60 means that one unit of GBP is valued at 1.60 USD. Please note that

in case of USDINR, USD is bas e currency and INR is quotation currency while in case of

GBPUSD, USD is quotation currency and GBP is base currency. In the interbank market, USD is

the universal base currency other than quoted against Euro (EUR), Sterling Pound (GBP),

Australian Dollar (AUD), Canadian Dollar (CAD) and New Zealand Dollar (NZD).

COMPANY PROFILE

1.3.1 INTRODUCTION

INDITRADE Capital Ltd formerly known as JRG Securities Ltd. is one of India’s

leading financial services providers with strong presence in South India. It was incorporated in

1994 and over the years it acquired a name of trust through equity and commodity broking

businesses. In 2007, baring India private equity fund 11 ltd., a leading private equity firm of

international repute acquired a majority stake in the company. With the investment of BIPEF

came fresh inflow of talent and a focused team committed to taking this company to greater

heights. Since then Inditrade has undergone several transformations – expanding into new

geographies, adopting state-of-the-art technology, strengthening credit and risk management

systems, creating new products and strengthening client relationships through service focus. The

company is committed to fully compliant with all regulatory compliances with the exchanges,

SEBI, IRDA, FMC and RBI. Inditrade is listed on the Bombay stock exchange and has a diverse

set of public share holders.

As the company transforms itself to being a professionally run, high quality brokerage

house in India, the focus is on providing best-in-class services to the customers. The new

management team consists of high quality professional talent from within the company and from

the market place. The company strives to attract and retain the best talent, which is amongst the

key building blocks for the company. The new growth strategy has four key building blocks-

Trust, Transparency, Technology and Talent.

The company is a member of the National Stock Exchange of India (NSE), the Bombay

Stock Exchange (BSE), the National Multi Commodity Exchange of India Ltd (NMCEIL), the

National Commodities Derivatives Exchange Ltd (NCDEX), the Multi Commodity Exchange of

India Ltd (MCX) and the Indian Pepper and Spices Trades Association (IPSTA). Inditrade is a

full-fledged depository participant of the National Securities Depository Ltd and Central

Depository Services (India) Limited. Besides these, it is also a leading Insurance Broker.

In order to expand its reach, Inditrade has launched its internet trading services through

www.inditrade.com. The online services will provide customers an opportunity to trade from the

comfort of their home or offices and also trade while travelling. Inditrade.com will empower

customers to trade and invest in equities, commodities, currencies, mutual funds and insurance.

1.3.2 VISION

“Empowering the Investor in You”

JRG provides a full array of financial products to you as per your needs through a

customer-centric approach and technology-oriented solutions.

1.3.3 STRATEGY

“We aspire to become a pan India, full-services, brokerage house by enabling every

Indian to invest and by facilitating financial decision making. We endeavor to ensure that our

customers have a delightful experience by partnering with us. We do this by equipping our

customers with a full array of financial options, understanding their needs and priorities, and

proving smart solutions to execute their plans. We commit to providing a superior execution

platform to the customer by constantly investing and upgrading our services delivery channels,

investing in cutting-edge technology, and having the most dynamic and motivated team on the

ground, that is focused on enhancing the customers’ experience.”

1.3.4 Inditrade Group Companies

The Inditrade Group, a leading financial and investment service company in India. From a

modest beginning a decade back, Inditrade is today a power to reckon with in the financial

services industry through the following Inditrade Group of Companies

Inditrade capital ltd

JRG Fincorp ltd

Inditrade business consultants’ ltd

Inditrade derivatives and commodities ltd

Inditrade insurance broking private ltd

1.3.5 Inditrade offerings

Product

IndiSave: Earn higher interest than on your fixed deposits. Invest in corporate debt,

government bonds, debt funds and gold.

IndiInvest: Create wealth. Invest in equities, gold, mutual funds and property.

IndiLever: Leverage your margins, avail margin funding, take loan against shares. Trade

in equities, commodities and currency using our advisory support.

IndiLoans: Personal loans, home loans, business loans, loans against property, loans

against securities, loans against commodities/securities/MF, Gold Loan, margin funding.

IndiSure: Insure yourself and your assets. Protect your family’s future with children’s

education and health insurance.

IndiPlan: Use our financial planning services to set your financial goals.

Services

Online trading platform

Advisory desk-research and advisory calls, reports and services

Centralized risk management desk

Centralized dealing support

Client management system

Real time market information and updates

Products and Services

Depository Services

Equity

Commodity

Currency Derivative

Initial Public Offer

Mutual Fund

Depository Services

JRG is a depository participant with the National Securities Depository Limited (NSDL)

and Central Depository Services (India) Limited (CDSL) for trading and settlement of

dematerialized (DEMAT) shares. JRG performs clearing services for all securities transactions

through its accounts. At JRG, investors can open DEMAT account for holding securities, mutual

funds and commodities.

Equity

Trading in Equities with JRG brings us the very best of the Technology, Research,

Access and Ease. It empowers us to invest in equities by providing an anchor to guide us as to

when, where and how to invest.

They have some key focus areas which they work on incessantly in order to bring us a

superior trading experience. These focuses areas-based on their objective of customer centricity

include the following:

Best-in-class technology

Powerful Research & Analytics

Transparency and Compliance

Call & Trade

Customer Service

Reach & Delivery Model Commodity

Commodity

Commodity derivative market has emerged as a new avenue for investors to create

wealth. Today commodities have evolved as the next best option after stocks and bonds for

diversifying the portfolio. Based on the fundamentals of demand and supply, commodities form

a separate asset class offering investors, arbitrageurs and speculators immense potential to earn

returns.

JRG aims to harness the immense potential of the commodities market by providing you

a simple yet effective interface, research and knowledge. JRG provide user friendly online

trading platform to trade various commodity sectors like bullion, base metals, energy and

agriculture.

Currency Derivatives

The global increase in trade and foreign investments has led to inter-connection of many

national economies leading to greater need for a stronger foreign exchange risk management

mechanism. The growth of the FX futures market has manifold with the participation of

speculators, investors and arbitragers and emerged as an alternative investment vehicle for Indian

investors. JRG are a member of two major currency exchanges- MCX-SX and NSE.

Trade in currency futures because:-

Low commissions

No middlemen

Standardized lot size

Low transaction cost

High liquidity

Instant transactions

Online access

Self-regulatory

No insider trading

Limited regulation

Initial Public Offer

An investor can garner estimable returns by investing early in a company through an

initial public offering. JRG helps to invest in the primary market through the IPO route in an

effortless way.

Mutual Fund

Investing in a mutual fund is an excellent way of diversifying risk as well as portfolio.

JRG presents its mutual fund services that strive to meet all your mutual fund investment needs.

They have wide spectrum of investment schemes from all top mutual fund houses.

BOARD OF DIRECTOR

Mr.P. Viswanathan Chairman

Mr. Munish Dayal Director

Mr. B R Menon Director

KEY MANAGEMENT

Samson K J  M D- Inditrade Derivatives and Commodities Ltd

Dr. Shankar Anappindi Asst. Vice President - HR

Harish Galipelli Head Commodity & Currency

Mr. Dnyanesh Sovani  Vice President – Online Business

Praveen P A Vice President-NBFC

1.4 PROBLEM DEFINITION

The market for foreign exchange involves the purchase and sale of national currencies. A

Foreign Exchange market exists because economies employ national currencies. If the world

economy used a single currency there would be no need for foreign exchange markets. In Europe

II economies have chosen to trade their individual currencies for a common currency. But the

euro will still trade against other world currencies. For now, the foreign exchange market is a

fact of life.

Foreign exchange risk is a financial risk posed by an exposure to unanticipated changes

in the exchange rate between two currencies. Investors and multinational businesses exporting or

importing goods and services or making foreign investments throughout the global economy are

faced with an exchange rate risk which can have severe financial consequences if not managed

appropriately. In every foreign exchange transaction, there are simultaneously buying one

currency and selling another. In effect, using the proceeds from the currency that sold to

purchase the currency you are buying. Furthermore, every currency in the world comes attached

with an interest rate set by the central bank of that currency's country. From this background it

has been decided to make a study on the risk and return of forex market.

1.5 SIGNIFICANCE OF THE STUDY

This study focus on the importance of risk in the foreign exchange market from the

perspective of a carry trade investor, thereby considering ‘known unknowns’ (volatility) and

‘unknown unknowns’ (uncertainty) and their relative importance. The theoretical framework

show how volatility and uncertainty affect risk and risk premia in the foreign exchange market.

Empirically examine the relation between risk, expected volatility and uncertainty of foreign

exchange returns based on this framework. The study reveals that uncertainty is the most

important factor driving risk, and therefore only

focusing on volatility gives an incomplete representation of risk. Moreover, volatility and

uncertainty are also important for the expected risk premium. In times of high volatility and/or

uncertainty, investors expect to receive a higher risk premium in the near future. The study

contributes to the foreign exchange asset market debate by showing that interest rate risk and

uncertainty about fundamentals have a significant impact on exchange rate risk. The main

objective of this study is to focus on the determinants of the risk and return in forex market.

Volatility in the foreign exchange (forex) and stock markets usually rises with macro financial

uncertainty. Price dynamics in these markets reveal information on the empirical distribution of

financial returns

1.6 SCOPE OF THE STUDY

The study on risk and return associated with forex market will give an exposure to

different currencies across the world and also a detailed description regarding individual

currencies. The study will provide information’s regarding historical volatility occurred in the

forex market and trends associated with each currencies. The study also provides information on

the coefficient of variation of all currencies under study and also the return on all the currencies.

Through this study an investor also gets a detailed idea about the risk and return associated with

the currencies in the forex market.

1.7 PERIOD OF STUDY

The study was undertaken during a period of forty five days from 2011 to 2013 quarterly.

1.8 LIMITATIONS OF THE STUDY

As the time allotted for the study was short, it became difficult to gather all technical

information.

The study was mainly based on secondary data. Secondary data is not accurate in many

situations.

Lack of awareness in respect to management of currencies.

REVIEW OF LITERATURE

2.1 THEORETICAL ASPECTS OF RISK AND RETURN

Foreign Exchange is a very large financial market. At times foreign exchange market becomes

very volatile. This is responsible for the various risks in foreign exchange market. Everyone

involved in the foreign exchange trading should we aware of foreign exchange risk. Foreign

exchange risk (also known as exchange rate risk or currency risk) is a financial risk that exists

when a financial transaction is denominated in a currency other than that of the base currency of

the company. The risk is that there may be an adverse movement in the exchange rate of the

denomination currency in relation to the base currency before the date when the transaction is

completed. Investors and businesses exporting or importing goods and services or making

foreign investments have an exchange rate risk which can have severe financial consequences;

but steps can be taken to manage (i.e., reduce) the risk. Foreign exchange risk is the variability of

domestic currency values of assets, liabilities or operating incomes due to unanticipated change

in exchange rate. This is measured by the variance of the values, i.e. Var (V), where ‘V’ is the

value of assets or liabilities and Var=variance= (standard deviation) 2.

Value at risk (VaR)

Risk is about odds of losing money and VaR is based on that common sense fact. Here risk is the

odds of really big loss. Big loss is different for every investor depending on the investor's

appetite. But every investor whether big or small does wants to know his/her losses in the worst

case. VAR answers the question, "What is my worst-case scenario?"

To calculate VaR we need three components. These three components are: a time period, a

confidence level and a loss amount or loss percentage. Using VaR investor will get to know

things like:

What is the most I can expect to lose with 95% confidence over a period of 10 days?

What is the maximum percentage I can expect to lose with 95% confidence over a period of

10 days?

Time period taken can be anything like a day, 10 day, a month or a year depending upon what

investor is looking for.

A one day VAR of $10mm using a probability of 5% means that there is a 5% chance that the

portfolio could lose more than $10mm in the next trading day.

There are three methods of calculating VaR: the Historical method, the parametric method also

known as variance-covariance method and the Monte Carlo simulation.

The Historical Method: The historical method simply re-organizes actual historical returns,

putting them in order from worst to best. It then assumes that history will repeat itself, from a

risk perspective. We then put these data in the histogram that compare the frequency of return.

Tiny bars in histogram represent the less frequent daily return while the highest point in

histogram represents the most frequent daily return.

Parametric Method

This method assumes that the stock returns are normally distributed. In this method we estimate

only two factors - an expected return and a standard deviation. These two factors allow us to plot

a normal distribution curve.

Monte Carlo Simulation: The third method involves developing a model for future stock price

returns and running multiple hypothetical trials through the model. A Monte Carlo simulation

refers to any method that randomly generates trials, but by itself does not tell us anything about

the underlying methodology. Every run of Monte Carlo Simulation gives different result. But

differences between these results are likely to be very narrow

Standard Deviation

Standard deviation is a measure of how far apart the data are from the average of the data. If all

the observations are close to their average then the standard deviation will be small.

In finance, standard deviation is applied to the annual rate of return of an investment to measure

the investment's volatility. Standard deviation is also known as historical volatility and is used by

investors as a gauge for the amount of expected volatility.

Mean Return

The average expected return of a given investment, when all possible outcomes are considered.

To calculate mean return, estimate the probability of each possible return, and then take a

weighted average of those returns.

To calculate mean return, at first we need to calculate all the possible rate of return of the

investment with their respective probability.

Foreign Exchange Rates

Foreign exchange rate is the rate at which one currency can be exchanged for another. In other

words, it is the value of another country's currency compared to that of our own. If we are

travelling to another country, you need to "buy" the local currency. Just like the price of any

asset, the exchange rate is the price at which you can buy that currency. Suppose we are

travelling to Egypt, and the exchange rate for INR to Egyptian pounds is 7.5:1, this means that to

buy every Egyptian pounds we need to spend INR 7.5.

Types of Foreign Exchange Rates

The various types of foreign exchange rates are:

a. Floating Rates

b. Fixed Rates

c. Pegged Rates

Floating Rates: When the value of the currencies fluctuates freely due to market forces, these

frequent changes in the values of currencies are termed as floating rates. Floating rates are

preferred by a country if there are reasons to believe that the country can cope up with the

constant change in the value of its currency. There are a number of reasons for the fluctuation in

the value of a currency. The most common reason is that of demand and supply. If there is a

trade deficit than it will cause less demand for the currency, as a result the value of currency will

go down. In case of trade surplus than it will cause more demand for the currency, as a result the

value of currency will rise.

Fixed Rates: Fixed rates are generally used by smaller economies. Smaller economies uses fixed

exchange rate because it is difficult for them to keep pace with the frequently changing exchange

rate. Fixed exchange rate secures the foreign investor from any loss due to exchange rate

fluctuation. Fixed exchange rates do have their disadvantages on the economic front. Due to

fixed exchange rate the monetary policies of the country becomes ineffective.

Pegged Rates: It is a compromise between fixed rates and floating rates. In pegged rate the

currency fluctuate within a fixed band around central value. It is better for developing economy

in comparison with the other two exchange rates as it allows certain degree of market adjustment

as well as stability.

Exchange rate depending upon type of transaction

Exchange rate also depends upon the type of transaction. Here the type of transactions are sale

transaction and purchase transaction. Authorized Dealer does quote different rates for sales and

purchase of foreign currency. Purchase of foreign currency is called inward remittance of foreign

currency. Similarly, sale of foreign currency is called outward remittance of foreign currency.

Factors influencing Foreign Exchange Rates

An exchange rate is determined by supply and demand factors. These are the various factors

which determine the demand and supply of a currency.

Inflation

If inflation in the India is lower than elsewhere, then Indian exports will become more

competitive and there will be an increase in demand for INR. Also foreign goods will be less

competitive and so Indian citizens will supply less INR to buy foreign goods. Therefore the rate

of INR will tend to increase.

Interest Rates

If interest rates in India rise relative to elsewhere, it will become more attractive to deposit

money in the India. Therefore demand for INR will rise. This is known as “hot money flows”

and is an important short run determinant of the value of a currency.

Speculation

If speculators believe the INR will rise in the future, they will demand more now to be able to

make a profit. This increase in demand will cause the value of INR to rise. Therefore movements

in the exchange rate do not always reflect economic fundamentals, but are often driven by the

sentiments of the financial markets.

For example, if markets see news which makes an interest rate increase more likely, the value of

the INR will probably rise in anticipation.

Change in competitiveness

If Indian goods become more attractive and competitive, this will cause the value of the

Exchange Rate to rise. This is important for determining the long run value of the INR.

Relative strength of other currencies

INR will rise if there is depreciation in the values of other currencies. For example, if USD

depreciates then this will result in the relative appreciation in the value of INR.

Balance of Payments

A large deficit on the current account means that the value of imports is greater than the value of

exports. If this is financed by a surplus on the financial / capital account then this is okay. But a

country who struggles to attract enough capital inflows will see depreciation in the currency.

Foreign Exchange Risk and Hedging

There is a spectrum of opinions regarding various foreign exchange risks and methods to hedge

them. Some firms feel hedging techniques are speculative or do not fall in their area of expertise

and hence do not venture into hedging practices. Other firms are unaware of being exposed to

foreign exchange risks. There are a set of firms who only hedge some of their risks, while others

are aware of the various risks they face, but are unaware of the methods to guard the firm against

the risk. There is yet another set of companies who believe shareholder value cannot be increased

by hedging the firm's foreign exchange risks as shareholders can themselves individually hedge

themselves against the same using instruments like forward contracts available in the market or

diversify such risks out by manipulating their portfolio.

Different categories of risk

The various risks associated with foreign exchange are:

Interest Rate Risk

Exchange Rate Fluctuation Risk

Counter-party Risk

Political Risk

Translation Risk

Interest Rate Risk: Interest rate risk refers to the profit and loss generated by fluctuations in the

forward spreads. Along with fluctuations in forward spread, forward amount mismatches and

maturity gaps among transactions in the foreign exchange book also plays a significant role

towards the interest rate risk. The forward amount mismatch is the difference between the spot

and the forward amounts.

Exchange Rate Fluctuation Risk: Exchange rate fluctuation risk refers to the risks to which

investors are exposed because of the change in exchange rate of that foreign currency against

INR. If the value of the foreign currency goes down with respect to INR then investors are bound

to lose. In case foreign currency appreciates against INR then the investor will gain more.

Counter-party risk: Counter-party risk refers to the risk of each party of the contract that the

counterparty will not leave up to his contractual obligations. Counterparty risk is also referred to

as “Default Risk”.

Political Risk: Political Risk refers to the reaction of the foreign exchange market due to the

change in the business environment of a country. However, the reaction of the foreign exchange

market is more dramatic for unfavorable events than for favorable events.

Translation Risk: Translation risk is encountered when there is a need to translate foreign

currency assets or liabilities into the home currency for accounting purpose in a given period.

2.2 EMPERICAL PERSPECTIVE

Soenen1 A key assumption in the concept of foreign exchange risk is that exchange rate changes

are not predictable and that this is determined by how efficient the markets for foreign exchange

are. research in the area of efficiency of foreign exchange markets has thus far been able to

establish only a weak form of the efficient market hypothesis conclusively which implies that

successive changes in exchange rates cannot be predicted by analyzing the historical sequence of

exchange rates (Soenen, 1979). However, when the efficient markets theory is applied to the

foreign exchange market under floating exchange rates there is some evidence to suggest that the

present prices properly reflect all available information. This implies that exchange rates react to

new information in an immediate and unbiased fashion, so that no one party can make a profit by

this information and in any case, information on direction of the rates arrives randomly so

exchange rates also fluctuate randomly. It implies that foreign exchange risk management cannot

be done away with by employing resources to predict exchange rate changes.

Giddy and Dufey2 There is a spectrum of opinions regarding foreign exchange hedging. Some

firms feel hedging techniques are speculative or do not fall in their area of expertise and hence

do not venture into hedging practices. Other firms are unaware of being exposed to foreign

exchange risks. There are a set of firms who only hedge some of their risks, while others are

aware of the various risks they face, but are unaware of the methods to guard the firm against the

risk. There is yet another set of companies who believe shareholder value cannot be increased by

hedging the firm’s foreign exchange risks as shareholders can themselves individually hedge

themselves against the same using instruments like forward contracts available in the market or

diversify such risks out by manipulating their portfolio (Giddy and Dufey, 1992). There are some

explanations backed by theory about the irrelevance of managing the risk of change in exchange

rates. For example, the international fisher effect states that exchange rates changes are balanced

out by interest rate changes, the purchasing power parity theory suggests that exchange rate

changes will be offset by changes in relative price indices/inflation since the law of one price

should hold. Both these theories suggest that exchange rate changes are evened out in some form

or the other. Also, the unbiased forward rate theory suggests that locking in the forward

exchange rate offers the same expected return and is an unbiased indicator of the future spot rate.

But these theories are perfectly played out in perfect markets under homogeneous tax regimes.

Also, exchange rate-linked changes in factors like inflation and interest rates take time to adjust

and in the meanwhile firms stand to lose out on adverse movements in the exchange rates. The

existence of different kinds of market imperfections, such as incomplete financial markets,

positive transaction and information costs, probability of financial distress, and agency costs and

restrictions on free trade make foreign exchange management an appropriate concern for

corporate management. (Giddy and Dufey, 1992) it has also been argued that a hedged firm,

being less risky can secure debt more easily and this enjoy a tax advantage (interest is excluded

from tax while dividends are taxed). This would negate the Modigliani-miller proposition as

shareholders cannot duplicate such tax advantages. The mm argument that shareholders can

hedge on their own is also not valid on account of high transaction costs and lack of knowledge

about financial manipulations on the part of shareholders. There is also a vast pool of research

that proves the efficacy of managing foreign exchange risks and a significant amount of evidence

showing the reduction of exposure with the use of tools for managing these exposures. in one of

the more recent studies, Allayanis and OFEK (2001) use a multivariate analysis on a sample of

S&P 500 non-financial firms and calculate a firms exchange-rate exposure using the ratio of

foreign sales to total sales as a proxy and isolate the impact of use of foreign currency derivatives

(part of foreign exchange risk management) on a firm’s foreign exchange exposures. they find a

statistically significant association between the absolute value of the exposures and the (absolute

value) of the percentage use of foreign currency derivatives and prove that the use of derivatives

in fact reduce exposure.2 based on giddy, Ian h and Dufey, gunter,1992, the management of

foreign exchange risk corporate hedging for foreign exchange risk.

John Russell3 In forex trading, the market tends to be "moody", meaning it follows the moods of

its participants. These moods come in mainly two flavors, risk taking, and risk aversion. Risk

taking is when investors are not worried about any upcoming issues in the market. They

generally feel that there are no surprises coming. Risk aversion is when the future is looking a

little murky, or just plain unpredictable. During the financial crisis of 2008, the forex market

overreacted with massive risk aversion. Investors pulled their money out of anything that paid

interest and focused on "safe haven" type currencies. This caused a crash on the Australian

Dollar and a surge in the US Dollar. Ironically, the center of the triggers for the financial crisis

were based on the United States, but because the US Dollar is viewed as a safe haven during

unpredictable time’s money flowed into it day after day as investors were increasingly unsure of

what was to come. This is true of any time of uncertainty in the markets, even mild uncertainty.

Whenever the market terrain is unpredictable, you will see risk aversion. It comes out as the

selling of higher yielding assets and moves into lower yielding (safe) assets. Sometimes the

moves last for days and sometimes months or years.

Profiting from risk aversion is possible, but ironically risky. To profit from risk aversion, you

have to keep an eye on the bigger picture and keep your trading light. In the instance of the 2008

financial crisis, some days had moves up and down of 500 pips. If you traded that looking to

make big money with highly leveraged trades, a poor entry could have left you without an

account. The two ways to profit from risk aversion are, stand aside and wait for things to return

to normal, or trade small with large targets. It seems like leaving money on the table to trade this

way, but the alternative, losing a lot of money on trades, is much worse. If you plan on using risk

aversion to your advantage, just make sure that you have an adequate grip on the reason for the

risk aversion. Failure to know the reason behind the attitude shift in the market could leave you

trading the wrong direction after the turn around.

Jack Clark francis24 (1986) revealed the importance of the rate of return in investments and

reviewed the possibility of default and bankruptcy risk. He opined that in an uncertain world,

investors cannot predict exactly what rate of return an investment will yield. However he

suggested that the investors can formulate a probability distribution of the possible rate of return.

He also opined that an investor who purchases corporate securities must face the possibility of

default and bankruptcy by the issuer. Financial analysts can foresee bankruptcy. He disclosed

some easily observable warnings of a firm's failure, which could be noticed by the investors to

avoid such a risk.

Lewis Mandells5 (1992) reviewed the nature of market risk, which according to him is very

much 'global'. He revealed that certain risks that are so global that they affect the entire

investment market. Even the stocks and bonds of the well-managed companies face market risk.

He concluded that market risk is influenced by factors that cannot be predicted accurately like

economic conditions, political events, mass psychological factors, etc. Market risk is the

systemic risk that affects all securities simultaneously and it cannot be reduced through

diversification.

Sunil Damodar’o6 (1993) evaluated the 'Derivatives' especially the 'futures' as a tool for short-

term risk control. He opined that derivatives have become an indispensable tool for finance

managers whose prime objective is to manage or reduce the risk inherent in their portfolios. He

disclosed that the over-riding feature of 'financial futures' in risk management is that these

instruments tend to be most valuable when risk control is needed for a short- term, ie, for a year

or less. They tend to be cheapest and easily available for protecting against or benefiting from

short term price. Their low execution costs also make them very suitable for frequent and short

term trading to manage risk, more effectively.

Philippe Jhorion and Sarkis Joseph Khoury7 (1996) reviewed international factors of risks and

their effect on financial markets. He opined that domestic investment is a subset of the global

asset allocation decision and that it is impossible to evaluate the risk of domestic securities

without reference to international factors. Investors must be aware of factors driving stock prices

and the interaction between movements in stock prices and exchange rates. According to them

the financial markets have become very much volatile over the last decade due to the

unpredictable speedy changes like oil price shocks, drive towards economic and monetary

unification in Europe, the wide scale conversion of communist countries to free market policies

etc. They emphasized the need for tightly controlled risk management measures to guard against

the unpredictable behavior of financial markets.

S.Rajagopal8 (1996) commented on risk management in relation to banks. He opined that good

risk management is good banking. A professional approach to Risk Management will safeguard

the interests of the banking institution in the long run. He described risk identification as an art of

combining intuition with formal information. And risk measurement is the estimation of the size,

probability and timing of a potential loss under various scenarios.

V.T.Godse9 (1996) revealed the two separate but simultaneous processes involved in risk

management. The first process is determining risk profile and the second relates to the risk

management process itself. Deciding risk profile is synonymous with drawing a risk picture and

involves the following steps.

1. Identifying and prioritizing the inherent risks

2. Measuring and scoring inherent risks.

3. Establishing standards for each risk component

4. Evaluating and controlling the quality of managerial controls.

5. Developing risk tolerance levels.

He opined that such an elaborate risk management process is relevant in the Indian context. The

process would facilitate better understanding of risks and their management.

Aswath Damodaran10 (1996) reviewed the ingredients for a good risk and return model.

According to him a good risk and return model should-

1. Come up with a measure for risk that is universal

2. Specify what types of risks are rewarded and what types are not.

3. Standardize risk measures, to enable analysis and comparison.

4. Translate the risk measure into an expected return.

He opined that a risk measure, to be useful, has to apply to all investments whether stocks or

bonds or real estate. He also stated that one of the objectives of measuring risk is to come up

with an estimate of an expected return for an investment. This expected return would help to

decide whether the investment is a 'good' or 'bad' one.

Basudev Sen11 (1997) disclosed the implications of risk management in the changed

environment and the factors constraining the speed of risk management technology up-gradation.

He opined that the perception and management of risk is crucial for players and regulators in a

market oriented economy. Investment managers have started upgrading their risk management

practices and systems. They have strengthened the internal control systems including internal

audit and they are increasingly using equity research of better quality. He observed that risk

measurement and estimation problems constrain the speed of up-gradation. Also, inadequate

availability of skills in using quantitative risk management models and lack of risk hedging

investments for the domestic investors are major constraints. He concluded that with the

beginning of a derivative market, new instruments of risk hedging would become available.

Terry.J.Watsham12 (1998) discusses the nature of the risks associated with derivative

instruments, how to measure those risks and how to manage them. He stated that risk is the

quantified uncertainty regarding the undesirable change in the value of a financial commitment.

He opined that an organization using derivatives would be exposed to risks from a number of

sources, which are identified as market risk, credit or deficit risk, operational risk and legal risk.

He revealed that there is 'systemic risk' that the default by one market participant will precipitate

a failure among many participants because of the inter-relationship between the participants.

Ghosh T.P13 reviewed the various types of risks in relation to the different institutions. He

opined that 'Managing risk' has different meanings for banks, financial institutions, and non-

banking financial companies and manufacturing companies. In the case of manufacturing

companies, the risk is traditionally classified as business risk and financial risk. Banks, financial

institutions and non- banking financial companies are prone to various types of risks important of

which are interest rate risk, market risk, foreign exchange risk, liquidity risk, country and

sovereign risk and insolvency risk.

Mukul Gupta14 (1999) described the risk management framework as the building blocks for

Enterprise Risk Management ERM is the systems and procedures designed to deal with multiple

types of risks. The objectives of ERM are to obtain information and analyze data so that

uncertainty is turned into quantifiable risk and appropriate management action can be taken to

mitigate the risk. He opined that it is necessary to understand the three main building blocks to

the risk measurement and management process that are analytics, business process and

technology. By analytics is meant the capability of developing the mathematical tools to measure

various forms of risks. By processes is meant the knowledge of business opportunities and the

way business is conducted. Technology is the experience in implementing the hardware and

software required to facilitate the risk management information system. He concluded that a

successfully implemented ERM could be used both for a defensive or an offensive approach.

Akash Joshi15 (2000) reviewed the utility of derivatives in reducing risks. He opined that

derivatives allow an investor to hedge or reduce risks. But they tend to confound investors due to

their esoteric nature. The leverage that the derivatives offer to any trader, investor or speculator

is tremendous. By the use of derivatives the volatility of the market also gets neutralized. He

concluded the article by stating that while the discerning one stands to gain from it, a person who

fails to read it right could land up burning his fingers.

Raghavan R.S16 (2000) reviewed the need for a risk management system, which should be a

daily practice in banks. He opined that bank management should take upon in serious terms, risk

management systems, which should be a daily practice in their operations. He is very much sure

that the task is of very high magnitude, the commitment to the exercise should be visible and

failure may be suicidal as we are exposed to market risks at international level, which is not

under our control as it was in the insulated economy till sometime back.

Vijay Soodd17 (2000) revealed the risks faced by banks and financial institutions and the degree

of risk faced by them. According to him, risk management is gathering momentum at a time

when there is increasing pressure on banks to better manage their assets and improve their

balance sheet. He opined that the greater the volatility of expected returns, the higher is the risk.

The essence of risk management is to reduce the volatility.

Jayanth M Thakur J18 (2000) disclosed the implications of derivatives. The use of derivatives

can be for safeguarding oneself against risks. It is widely recognized by all including the SEBI

committee on derivatives that a substantial degree of speculative activity in a market for

derivatives is necessary and without this, a good market in derivatives cannot function. He

revealed that the basic purpose of providing a system for trading in derivatives is to enable a

person to protect himself against the risk of fluctuations in the market prices. This is known as

hedging. But he argued that it might lead to the bankruptcy of the grantor of an option to buy as

he takes a huge risk since the price could go upward to an unlimited extent and still he would

have to deliver the shares. This is one of the important reasons that the derivatives are criticized.

He concluded the article by suggesting that the objective of the Regulator would be to provide

protection to all concerned.

Lucas19 The model analyzed in this paper is a generalization of the two country model proposed

by Lucas (1982). The Lucas model is a complete, dynamic, two countries, general equilibrium

model which provides some useful insights into the possible nature of risk premiums in the

forward foreign exchange market. Given the highly stylized nature of the model and the

generality of its stochastic structure, direct empirical tests of the model are impossible without

additional restrictions. We do not pursue that strategy here; rather, we use the implications of the

Lucas model to motivate a re-examination of the empirical analysis of Hansen and Hodrick and

the trading strategy of Bilson.

Baumol and Tobin20 In the widely respected money-demand models of Baumol (1952) and

Tobin (1956), individuals choose a range of acceptable levels for their money balances, rather

than a single point value. Only when an individual’s balance reaches the boundaries of his/her

range does he adjust his money holdings. As a result, money demand at any point in time is not

uniquely determined, and the equilibrium money supply can fall anywhere within a range

(determined by the aggregate of individual money demands) without generating any change in

individual behavior, interest rates, or exchange rates. With regard to money supply, reserve

accounting procedures imply that money supply is also not uniquely determined at short

horizons, even if the central bank directly controls reserves.

Carlson21 Currency traders also face incentives to avoid risk. Most significantly, they face the

gambler’s ruin problem: if they run into a long series of losses, they will shortly be out of a job

even if their profitability would ultimately have been outstanding had they been permitted to

continue trading. Such traders will behave as if they are risk adverse (Carlson 1998). For some

short-term traders, risk also directly affects their annual bonus.

Lewis22 (1995), comments that “the sign of the risk premium would [also] depend on the

difference between domestic holdings of foreign bonds and foreign holdings of domestic bonds.

When domestic residents are net creditors, then the overall effect on the risk premium is to

compensate domestic investors for net holdings of foreign deposits” (pp. 1926-1927). Lewis is

critical of that model, stressing that countries’ net asset positions change sign infrequently.

Implicitly Lewis assumes that the international asset holdings relevant to currency risk premiums

encompass the entire range of capital-account items, including assets intended to be held for

many years, such as foreign direct investment, official holdings, and loans.

A.Se1varaj.x23 (1999) reviewed the strategies for combating risk. A risk management

programme should encompass all parts of the organization and all types of potential risks. Risk

management is, essential and one should be aware of how to strategically organize an effective

programme. He revealed that to safeguard a business against risk, it is necessary to know the

various kinds of risks that the business faces. There are risks in everything and the degree of risk

may vary. He recommended certain strategies for combating risks. When risks must be born,

prudence lies in the reduction of the area of uncertainty within which a business is operating. He

opined that since most of these risks proceed largely from ignorance, they could be avoided by

understanding them properly.

Bollerslev and Domowitz24 (1994) found for foreign exchange markets is that the size of bid-ask

spreads in the foreign exchange market (DM/$ rates) is positively related to the underlying

exchange rate (conditional) volatility, by using ordered profit regression to cope with

discreteness in the spreads data. Bollerslev and Domowitz (1993) suggest that quotation activity

of foreign exchange does not influence bid-ask spread changes - seemingly contradicting the fact

derived from stock markets – while spreads have a positive effect on return volatility.

Aliber and Stickney25 According to Aliber and Stickney, 1975 Criticisms of foreign currency

risk management all rest on efficient market operating conditions. Proponents of foreign

currency risk management argue their case pointing at limitations in assumptions and caveats

inherent in conditions necessary for foreign exchange markets to operate efficiently. Studies

have indicated that, in the long term PPP theorem holds, in that, long term exchange rates are

approximated by relative price differentials. However, short term adjustment between price

changes and exchange rates are not immediate. Studies have shown poor correlation between

exchange rate changes and relative price changes and interest rates in the short run As long as

adjustment between exchange rates and relative price changes and interest rates is not

immediate; firms are exposed to exchange risk.

Pavlova and Rigobon26 A very interesting paper has been published in 2003 by Pavlova and

Rigobon. The authors use a two-country, two-good model to describe the behavior of the real

exchange rate, the stock and the bond markets. They make predictions that are inspired by the

concept that exchange rates behave by the same principles as the stock market, and should

therefore be treated in a similar manner. Their predictions seem to be confirmed by the data and

are therefore a welcome contribution to the literature.

Pettengill, Sundaram and Mathur27 (1995) find that when the realized return is used instead of

the expected return to estimate the CAPM, the relationship between the risk parameters beta and

the return must be conditional on the relationship between the realized market returns and the

risk-free rate. They therefore introduce a conditional relationship between beta and the realized

return as an alternative approach to that used by Fama and Macbeth (1973). They determine

whether the direction of the market is “up” or “down” based on the relationship between the

realized market returns and the risk-free rate, and separate the “up” market from the “down”

market to create a conditional relationship between risk factors and the realized return. Whether

the market is up or down depends on whether the excess market return, which they define as the

difference between the market return and risk-free rate, is positive or negative. If the excess

market return is positive, the stock market is “up”; if excess market returns is negative, the stock

market is “down”. When the excess market return (or premium) is positive, the relationship

between beta and the return will be positive. On the other hand, if excess market return is

negative, the investor will hold the risk-free asset, which has a low beta, and the relationship

between beta and return will be negative. Thus, while the relationship between expected returns

and risk is always positive, the relationship between realized returns and risk can be either

positive or negative depending on the market excess returns.

Kumar and Seppi28 (1992) and Jarrow29 (1992) studied the impact of currency derivatives on

spot market volatility and found that speculative trading executed by big players in the

derivatives market increases the volatility in the spot exchange rate. Hence, currency futures

trading increases the spot market volatility. Glen and Jorion30 (1993) examined the usefulness

of currency futures/forwards and concluded that currency risk can be minimized through

futures/forward hedging. Chatrath, Ramchander and Song31 (1996) analyzed the impact of

currency futures trading on spot exchange rate volatility by establishing relationship between

level of currency futures trading and the volatility in the spot rates of the British pound,

Canadian dollar, Japanese yen, Swiss franc and Deutsche mark. They concluded that there exists

a causal relationship between currency futures trading volume and exchange rate volatility and

also found that the trading activity in currency futures has a positive impact on conditional

volatility in the exchange rate changes. Further, futures trading activity has declined on the day

following increased volatility in spot exchange rates.

Bhargava and Malhotra32 (2007) analyzed futures trading on four currencies over the time

period of 1982-2000 and found the evidence that day traders and speculators destabilize the

market for futures but it is not clear whether hedgers stabilize or destabilize the market.

Exchange rate movements affect expected future cash flow by changing the home currency value

of foreign cash inflows and outflows and the terms of trade and competition. Consequently, the

use of currency derivatives for hedging the unexpected movement of currency becomes more

sensitive and essential. Sharma33 (2011) investigated the impact of currency futures trading in

India by establishing relation between volatility in the exchange rate in the spot market and

trading activity in the currency futures. The results show that there is a two-way causality

between the volatility in the spot exchange rate and the trading activity in the currency futures

market.

Lessard and Lightstone34 show that real exchange rate changes have both margin effects and

volume effects, and they argue that managers need to understand that exchange rates can have a

significant impact on profits. Bodnar and Gentry35 contend that exchange rate fluctuations can

significantly affect domestic profits by the changing terms of competition with foreign

competitors. Hung36 estimates the impact of exchange rate changes on firms’ profits and finds

that changes in exchange rate are transmitted to profits through a price-volume effect and a

currency translation effect.

Kwok37 examines whether managers should hedge cash flows originating in different currencies

independently or use an integrative approach, and he indicates that while the independent

approach does not lead to the lowest risk, this approach could save time and resources as its

effectiveness is close to that of the integrative approach. Eaker and Grant38 provide empirical

evidence on the effectiveness of cross-hedging with currency futures in reducing foreign

exchange risk. They find that cross-hedging is substantially less effective and more variable than

traditional hedging, but they suggest that if cross-hedging is the only alternative, multiple cross-

hedges are more effective.

Soenen39 Soenen studies the effectiveness of diversification with regard to reducing the

variability of a portfolio of currencies, and the results indicate that the marginal reduction in the

variation of a firm's currency portfolio diminishes rapidly and becomes almost insignificant with

the inclusion of more than eight currencies. DeMaskey40 compares the effectiveness of currency

futures and currency options as hedging instruments of covered and uncovered currency

positions. Results of this study indicate that currency futures provide a more effective covered

hedge while currency options are more effective for an uncovered hedge. Collier and Davis41

survey a sample of large U.K. firms about management of currency transaction risk. The results

of their survey indicate that for most firms surveyed, management of currency transaction risk is

centralized and supported by formal policies for dealing with risk exposure. In a subsequent and

similar study of U.K. and U.S. firms, Collier, Davis, Coates, and Longden42 find that U.S. firms

exhibit policies that are slightly more inclined toward asymmetric risk aversion, even when

overall risk profiles are similar.

2.3 REFERENCE

1. Soenen, L.A., Henningan, E.S.(1988), “An analysis of exchange rates and stock prices-

the US experience between 1980 and 1986”, Akron Business and Economic Review,

Vol.19, pp.7-16

2. Duffie, D. and giddy 1996, “A yield-factor model of interest rates”, Mathematical

Finance, 6, 379–406.

3. Article from John Russell, former About.com Guide

4. Jack Clark Francis, lnzlestrrrents - Analysis and Management, MC Graw Hill,

International Editions, 1986.

5. Lewis Mandell, Inzlestnlerlts, Macmillan Publishing Company, New York, 1992.

6. Sunil damodar, An Introduction to Derivatives and Risk Management in Financial

Markets", State Bank of India, Monthly Review Vol. XXXII No. 8, August 1993.

7. Philippe Jhorion & Sarkis Joseph Khoury, Financial Risk Mnnngeiizeizt Domestic and

international dimensions, Black Well Publishers, Basil Blackwell, Cambridge,

Massachusetts 1996.

8. S.Rajagopal, "Bank Risk Management - A risk pricing model", State Bank of India,

Monthly Review, VoI. XXXV, No.11, November 1996, p.555.

9. V.T.Godse., "Conceptual Framework for Risk Management", I.B.A. Bulletin, July 1996,

p.22.

10. Aswath Damodaran, investment valuation Tools and Techniques, John Wiley & Sons Inc.

New York 1996

11. Basudev Sen, Development of regulation of the Indian Capital Market, Risk Management

implications, University Books House (Pvt. Ltd., Jaipur 1997)

12. Terry. J. Watsham, futures and options in risk management, Terry. J. Watsham, A

division of International Thomson Publishing, 1998

13. Ghosh.T.P. "Value at Risk", Express investment Week, Weekly Vo1.8, No. 49,

November 30 to December 6, 1998

14. Mukul Gupta, "Looking Back, Looking Forward, The Economic times, Vol. 39, No. 27,

March 319' 1999, p.15

15. Akash Joshi, "Spreading the basket - Derivative Instruments Mitigate Investment Risk,

The Financial Express Daily, Vol. V, No. 223, December 219' 1999, p.11.

16. Raghavan.R.S., "Risk Management in Banks", the Hindu Daily, Vol. 123, No. 272,

November 16, 2000, Business p.4

17. Vijay Sood, "Risk in Industry and company specific" The Economic times Daily, Vol.

40, No. 261, November 22nd, 2000.

18. Jayanth. M. Thakur, "World of Derivatives and Related Law", The Financial Express,

Daily, Vol. VI, No. 8, February 14tJ1,2000, p.2.

19. Lucas, R., 1982, “Interest Rates and Currency Prices in a Two–Country World,” Journal

of Monetary Economics 10, 335-360

20. Baumol, William J. "The Transactions Demand for Cash: An Inventory Theoretic

Approach." Quarterly Journal of Economics, 1952.

21. Carlson, John A. “Risk Aversion, Foreign Exchange Speculation and Gambler’s Ruin.”

Economica, August 1998, 65, pp. 441-453

22. Lewis, Karen K. “Puzzles in International Financial Markets,” in G. Grossman and K.

Roof, eds., Handbook of International Economics, Vol. III, Elsevier Science, 1995, pp.

1913-1971

23. A.Selvaraj., "Risk Management - Profitability" The management accountant, Monthly,

Vo1.2, No. 2, February 1999

24. Bollerslev, T., and I. Domowitz, 1993, Trading patterns and prices in the interbank

foreign exchange market, Journal of Finance 48, 1421–1443

25. Aliber, R and C. Stickney (1975)"Accounting Measures of Foreign Exchange Exposure"

The Accounting Review, January pp 44-47

26. Anna Pavlova and Roberto Rigobon. Asset prices and exchange rates. June 2003

27. Pettengill, G., Sundaram, S., & Mathur, I. (1995). The conditional relation between beta

and return. Journal of Financial and Quantitative Analysis 30, 101−116

28. Kumar, P. and D.J. Seppi (1992), Futures Manipulation with Cash Settlement, The

Journal of Finance, Vol. XLVII (4): pp.1485-1501

29. Jarrow, R.A., (1992), Market Manipulation, Bubbles, Corners, and Short Squeezes,

Journal of Financial and Quantitative Analysis, Vol. 27(3): pp.311- 336

30. Glen, J. and Jorion, P., (1993), Currency Hedging for International Portfolios, Journal of

Finance, Vol. 48: pp.1865-86

31. Chatrath, A., Ramchander, S. and Song, F.,(1996), The Role of Futures Trading Activity

in Exchange Rate Volatility, The Journal of Futures Markets, Vol.16(5): pp.561- 584

32. Bhargava V., Malhotra D.K., (2007), the relationship between futures trading activity and

exchange rate volatility, revisited, Journal of Multinational Financial Management, Vol.

17: pp.95-111.

33. Sharma, S., (2011), An Empirical analysis of the relationship between Currency futures

and Exchange Rates Volatility in India, Working Paper Series, Reserve Bank of India,

1/2011.

34. Lessard, D.R. and J.B. Lightstone. (1986). "Volatile Exchange Rates Can Put Operations

at Risk," Harvard Business Review, 64, 107-114

35. Bodnar, G.M. and W.M. Gentry. (1993). "Exchange Rate Exposure and Industry

Characteristics: Evidence from Canada, Japan, and the USA,” Journal of International

Money and Finance, 12, 29-45

36. Hung, J. (1993). "Assessing the Exchange Rate's Impact on U.S. Manufacturing Profits,"

Federal Reserve Bank of New York Quarterly Review, 17, 44-63

37. Kwok, C.Y. (1987). "Hedging Foreign Exposures: Independent vs. Integrative

Approaches," Journal of International Business Studies, 18, 33-51.

38. Eaker, M.R. and D.M. Grant. (1987). "Cross-Hedging Foreign Currency Risk," Journal of

International Money and Finance, 6, 85-105

39. Soenen, L.A. (1988). "Risk Diversification Characteristics of Currency Cocktails,"

Journal of Economics and Business, 40, 177-189

40. DeMaskey, A.L. (1995). "A Comparison of the Effectiveness of Currency Futures and

Currency Options in the Context of Foreign Exchange Risk Management," Managerial

Finance, 21, 40-51.

41. Collier, P. and E.W. Davis. (1985). "The Management of Currency Transaction Risk by

UK Multinational Companies," Accounting and Business Research, 15, 327-334

42. Collier, P., E.W. Davis, J.B. Coates, and S.G. Longden. (1990). "The Management of

Currency Risk: Case Studies of US and UK Multinationals," Accounting and Business

Research, 20, 206-210.

3.1 TOPIC OF THE STUDY

A study on risk and return in forex market

3.2 RESEARCH DESIGN

Financial research can be a systematic and organized effort to investigate into a problem

encountered in the investment scenario. It comprises a series of theoretical concepts design and

executed, with the goal of finding answers to the issues that are of concern to the manager and

the work environment. The first step in the process is to identify the problem areas that exist in

the selection of securities. Once the problem is clearly identified the next step is to gather

information analyze the data, and determine the factors that are associated with the problem and

solve it by taking necessary corrective actions. The entire process by which we attempt to solve

the problem is called research. Thus research involves a series of well thought out and carefully

executed actions that will enable the manager to know how organizational problems can be

solved. Research thus encompasses the process of enquiry, investigation, examination and

experimentation. These processes are to be carried out critically, objectively, and logically.

A research design encompasses the methodology and procedures employed to conduct

scientific research. Research design stands for the framework of research. The research design

utilized in this study is analytical. For that various statistical tools as well as Microsoft excel

tools are being used here.

3.3 DATA COLLECTION METHOD

Secondary data were used to carry out the study.

Secondary Data includes

Details from company files, records and documents.

Various published books, journals and news papers.

Web pages of forex market etc.

3.4 RESEARCH METHODOLOGY

This project is designed as analytical in nature which help an investor to know and familiarize

with the risk and return associated with forex market. For conducting this research appropriate

method and techniques are selected. It helped in arriving at best solution by critically analyzing

and relating available data’s with unknown aspect of the problem.

3.5 OBJECTIVES OF THE STUDY

Primary Objective

To study on the risk and return in forex market.

Secondary Objectives

To evaluate market return in the forex market.

To find out volatility in forex market

To study on risk associated with forex market

3.6 DATA ANALYSIS TOOLS AND TECHNIQUES

The major tools used in data analysis and data interpretation are;

a. Coefficient of variation

Co-efficient of variation is a relative measure of dispersion. So it is free from the unit in

which values in the series are measured.

co−efficient of variation= SDMean

∗100

b. Standard deviation

Standard deviation (represented by the symbol σ) shows how much variation or

"dispersion" exists from the average (mean, or expected value). It can be calculate with

the formula:

σ=√[∑ x2

n¿−(∑ x

n)

2

]¿

c. Moving average

Moving average is used for analyzing the historical volatility of share. For that first

change in the price is found out and the standard deviation of the change. Finally

volatility is found out by using formula

Moving Average=SD∗Number of days

d. Price Volatility

A statistical measure of the dispersion of returns for a given security or market index.

Volatility can either be measured by using the standard deviation or variance between

returns from that same security or market index.

Price Volatility= Price DifferencePrice at the Beginning

∗100

4.1 RISK AND RETURN ANALYSIS

US DOLLAR (USD)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 45.3884 45.2854 -0.226930229

30-Jun-11 FUTCUR 45.4916 45.3348 -0.344679018

30-Sep-11 FUTCUR 49.4995 49.6167 0.236770068

31-Dec-11 FUTCUR 54.5234 54.2859 -0.435592791

31-Mar-12 FUTCUR 52.0992 51.8521 -0.474287513

30-Jun-12 FUTCUR 56.8925 56.0542 -1.473480687

30-Sep-12 FUTCUR 52.4862 52.5 0.026292625

31-Dec-12 FUTCUR 54.689 54.689 0

31-Mar-13 FUTCUR 54.4017 54.355 -0.085842906

30-Jun-13 FUTCUR 59.6964 59.597 -0.166509203

30-Sep-13 FUTCUR 62.702 62.702 0

31-Dec-13 FUTCUR 61.753 61.7744 0.034654187

TOTAL 649.6229 648.0465 -2.909605466AVERAGE RETURN -0.242467122 SD 0.4414541

VARIANCE 0.194881723

Table 4.1.1

Interpretation

It can be seen from the above that the standard deviation of US DOLLAR (i.e. total risk

associated with stock) is 0.4414541, where as the average value is -0.242467122. Here it means

that all risk associated with this stock can be eliminated with proper diversification of the

portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-12

1-Mar-12

1-May-121-Jul-12

1-Sep-121-Nov-12

1-Jan-13

1-Mar-13

1-May-131-Jul-13

1-Sep-131-Nov-13

-1.6

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

Return

Return

Chart 4.1.1

Inference

From the graph, the beta is less than one and it shows that the less volatility of the price of the

stock in comparison with the market returns. Here it can be ascertained that there exist a

comparatively high difference between systematic risk and unsystematic risk.

EURO (EUR)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 63.954 63.8429 -0.17371861

30-Jun-11 FUTCUR 65.103 65.235 0.202755633

30-Sep-11 FUTCUR 67.2921 67.4628 0.253670193

31-Dec-11 FUTCUR 70.4507 70.2921 -0.225121965

31-Mar-12 FUTCUR 69.2967 69.1593 -0.19827784

30-Jun-12 FUTCUR 70.8806 70.4966 -0.541756136

30-Sep-12 FUTCUR 67.7412 67.4908 -0.369642108

31-Dec-12 FUTCUR 72.2726 72.2704 -0.003044031

31-Mar-13 FUTCUR 69.7315 69.663 -0.09823394

30-Jun-13 FUTCUR 77.8525 77.5184 -0.429144857

30-Sep-13 FUTCUR 84.7725 84.7725 0

31-Dec-13 FUTCUR 84.8653 85.0387 0.204323793

TOTAL 864.2127 863.2425 -1.378189868AVERAGE RETURN -0.114849156 SD 0.258149766

VARIANCE 0.066641302

Table 4.1.2

Interpretation

It can be seen from the above that the total risk associated with stock (standard deviation) of

EURO is 0.258149766, where as the average value is -0.114849156. Here it means that all risk

associated with this stock can be eliminated with proper diversification of the portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-12

1-Mar-12

1-May-121-Jul-12

1-Sep-121-Nov-12

1-Jan-13

1-Mar-13

1-May-131-Jul-13

1-Sep-131-Nov-13

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

Return

Return

Chart 4.1.2

Inference

From the graph, the beta is less than one and it shows that the less volatility of the price of the

stock in comparison with the market returns. Here it can be ascertained that there exist a

comparatively high difference between systematic risk and unsystematic risk.

JAPANESE YEN (JPY)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 0.5536 0.5465 -1.282514451

30-Jun-11 FUTCUR 0.5624 0.5598 -0.46230441

30-Sep-11 FUTCUR 0.6467 0.6475 0.123704964

31-Dec-11 FUTCUR 0.7009 0.7012 0.042802112

31-Mar-12 FUTCUR 0.6315 0.6302 -0.205859066

30-Jun-12 FUTCUR 0.7161 0.7047 -1.591956431

30-Sep-12 FUTCUR 0.6755 0.6736 -0.281273131

31-Dec-12 FUTCUR 0.6366 0.6366 0

31-Mar-13 FUTCUR 0.5779 0.5767 -0.207648382

30-Jun-13 FUTCUR 0.6034 0.601 -0.397746105

30-Sep-13 FUTCUR 0.6379 0.6379 0

31-Dec-13 FUTCUR 0.587 0.587 0

Total 7.5295 7.5027 -4.2627949AVERAGE RETURN -0.355232908 SD 0.540921454

VARIANCE 0.292596019

Table 4.1.3

Interpretation

The total risk associated with stock (standard deviation) of JAPANESE YEN is 0.540921454,

where as the average value is -0.355232908. Here it means that all risk associated with this stock

can be eliminated with proper diversification of the portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-12

1-Mar-12

1-May-121-Jul-12

1-Sep-121-Nov-12

1-Jan-13

1-Mar-13

1-May-131-Jul-13

1-Sep-131-Nov-13

-2

-1.5

-1

-0.5

0

0.5

Return

Return

Chart 4.1.3

Inference

From the graph JAPANESE YEN has a less volatility of the price of the stock in comparison

with the market returns as the average return is less than one.

GREAT BRITAIN POUND (GBP)

Trade Date

Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 72.5928 72.5993 0.008954056

30-Jun-11 FUTCUR 72.6878 72.6155 -0.099466485

30-Sep-11 FUTCUR 77.3678 77.5276 0.206545876

31-Dec-11 FUTCUR 84.1083 83.8886 -0.261210844

31-Mar-12 FUTCUR 82.8555 82.8975 0.05069066

30-Jun-12 FUTCUR 88.4638 87.5275 -1.058399029

30-Sep-12 FUTCUR 85.0528 84.8631 -0.223037925

31-Dec-12 FUTCUR 88.3413 88.3408 -0.000565987

31-Mar-13 FUTCUR 82.666 82.5614 -0.126533278

30-Jun-13 FUTCUR 90.9606 90.6375 -0.355208739

30-Sep-13 FUTCUR 101.173 101.173 0

31-Dec-13 FUTCUR 101.729 101.854 0.122875483

TOTAL 1027.9987 1026.4858 -1.735356212AVERAGE RETURN -0.144613018 SD 0.330250256

VARIANCE 0.109065232

Table 4.1.4

Interpretation

The total risk associated with stock (standard deviation) of GBP is 0.330250256, where as the

average value is -0.144613018. Here it means that all risk associated with this stock can be

eliminated with proper diversification of the portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-121-Mar-1

21-May-1

21-Jul-12

1-Sep-121-Nov-12

1-Jan-131-Mar-1

31-May-1

31-Jul-13

1-Sep-131-Nov-13

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

Return

Return

Chart 4.1.4

Inference

From the graph that the GBP has a less volatility of the price of the stock in comparison with the

market returns as the average return is less than one.

AUSTRALIAN DOLLAR (AUD)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 46.5158 46.6852 0.364177333

30-Jun-11 FUTCUR 47.6679 48.0327 0.765294884

30-Sep-11 FUTCUR 48.9031 48.5822 -0.65619562

31-Dec-11 FUTCUR 55.0146 55.2327 0.396440218

31-Mar-12 FUTCUR 53.9774 53.8495 -0.23695102

30-Jun-12 FUTCUR 57.285 56.9455 -0.592650781

30-Sep-12 FUTCUR 54.731 54.4772 -0.46372257

31-Dec-12 FUTCUR 56.7185 56.7174 -0.001939402

31-Mar-13 FUTCUR 56.6463 56.6178 -0.0503122

30-Jun-13 FUTCUR 55.0287 54.4287 -1.090340132

30-Sep-13 FUTCUR 58.3894 58.3894 0

31-Dec-13 FUTCUR 54.7564 54.8106 0.098983863

TOTAL 645.6341 644.7689 -1.467215428AVERAGE RETURN -0.122267952 SD 0.517885504

VARIANCE 0.268205395

Table 4.1.5

Interpretation

It can be seen from the above that the total risk associated with stock (standard deviation) of

AUSTRALIAN DOLLAR is 0.517885504, where as the average value is -0.122267952. Here it

means that all risk associated with this stock can be eliminated with proper diversification of the

portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-121-Mar-1

21-May-1

21-Jul-12

1-Sep-121-Nov-12

1-Jan-131-Mar-1

31-May-1

31-Jul-13

1-Sep-131-Nov-13

-1.5

-1

-0.5

0

0.5

1

Return

Return

Chart 4.1.5

Inference

From the graph beta is less than one and it shows that the less volatility of the price of the stock

in comparison with the market returns. Here it can be ascertained that there exist a comparatively

high difference between systematic risk and unsystematic risk.

BAHRAINI DINAR (BHD)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 120.107 119.774 -0.277252783

30-Jun-11 FUTCUR 120.648 120.232 -0.344804721

30-Sep-11 FUTCUR 131.003 131.202 0.151904918

31-Dec-11 FUTCUR 144.23 143.534 -0.482562574

31-Mar-12 FUTCUR 137.476 136.896 -0.421891821

30-Jun-12 FUTCUR 150.013 147.814 -1.465872958

30-Sep-12 FUTCUR 138.384 137.011 -0.992166724

31-Dec-12 FUTCUR 144.964 144.987 0.015866008

31-Mar-13 FUTCUR 143.419 142.402 -0.709111066

30-Jun-13 FUTCUR 157.415 155.585 -1.16253216

30-Sep-13 FUTCUR 165.34 162.36 -1.80234668

31-Dec-13 FUTCUR 162.881 162.36 -0.319865423

Total 1715.88 1704.157 -7.810635984AVERAGE RETURN -0.650886332 SD 0.594243192

VARIANCE 0.353124971

Table 4.1.6

Interpretation

As from the above it can be seen that the standard deviation (total risk associated with stock) of

BAHRAINI DINAR is 0.594243192, where as the average value is -0.650886332. Here it means

that all risk associated with this stock can be eliminated with proper diversification of the

portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-11

1-Nov-111-Jan

-12

1-Mar-12

1-May-121-Jul-12

1-Sep-12

1-Nov-121-Jan

-13

1-Mar-13

1-May-131-Jul-13

1-Sep-13

1-Nov-13

-2

-1.5

-1

-0.5

0

0.5

Return

Return

Chart 4.1.6

Inference

From the graph, the beta is less than one and it shows that the less volatility of the price of the

stock in comparison with the market returns. Here it can be ascertained that there exist a

comparatively high difference between systematic risk and unsystematic risk.

KUWAITI DINAR (KWD)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 163.391 162.921 -0.287653543

30-Jun-11 FUTCUR 165.244 164.513 -0.442376123

30-Sep-11 FUTCUR 178.628 179.16 0.297825649

31-Dec-11 FUTCUR 195.621 194.671 -0.485632933

31-Mar-12 FUTCUR 187.185 186.404 -0.417234287

30-Jun-12 FUTCUR 202.378 199.24 -1.550563796

30-Sep-12 FUTCUR 186.544 186.501 -0.023050862

31-Dec-12 FUTCUR 194.098 194.001 -0.049974755

31-Mar-13 FUTCUR 189.87 189.688 -0.095855059

30-Jun-13 FUTCUR 208.984 208.578 -0.194273246

30-Sep-13 FUTCUR 221.148 220.937 -0.095411218

31-Dec-13 FUTCUR 218.17 218.655 0.222303708

TOTAL 2311.261 2305.269 -3.121896464AVERAGE RETURN -0.260158039 SD 0.474591506

VARIANCE 0.225237098

Table 4.1.7

Interpretation

The total risk associated with stock (standard deviation) of GBP is 0.474591506, where as the

average value is -0.260158039. Here it means that all risk associated with this stock can be

eliminated with proper diversification of the portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-12

1-Mar-12

1-May-121-Jul-12

1-Sep-121-Nov-12

1-Jan-13

1-Mar-13

1-May-131-Jul-13

1-Sep-131-Nov-13

-2

-1.5

-1

-0.5

0

0.5

-0.287653543 -0.44237612300000

4

0.297825649000005

-0.485632933-0.417234287

-1.55056379599998

-0.023050862-0.049974755-

0.0958550590000002-0.194273246

-0.095411218

0.222303708

Return

Return

Chart 4.1.7

Inference

It can be seen from the above graph that the KUWAITI DINAR (KWD) has a less volatility of

the price of the stock in comparison with the market returns as the average return is less than

one.

OMANI RIAL (OMR)

TRADE DATE

INSTRUMENT OPEN PRICECLOSE PRICE

RETURN

31-MAR-11 FUTCUR 117.562 117.298 -0.224562359

30-JUN-11 FUTCUR 118.129 117.722 -0.344538598

30-SEP-11 FUTCUR 128.211 128.507 0.230869426

31-DEC-11 FUTCUR 140.538 141.186 0.461085258

31-MAR-12 FUTCUR 134.923 134.29 -0.469156482

30-JUN-12 FUTCUR 147.314 145.128 -1.483905128

30-SEP-12 FUTCUR 135.922 135.943 0.015450038

31-DEC-12 FUTCUR 141.663 142.049 0.272477641

31-MAR-13 FUTCUR 140.933 140.823 -0.078051273

30-JUN-13 FUTCUR 154.598 154.26 -0.218631548

30-SEP-13 FUTCUR 162.436 162.419 -0.01046566

31-DEC-13 FUTCUR 159.978 160.054 0.047506532

TOTAL 1682.207 1679.679 -1.801922152AVERAGE RETURN -0.150160179 SD 0.497016701

VARIANCE 0.247025601

Table 4.1.8

Interpretation

The total risk associated with stock (standard deviation) of GBP is 0.497016701, where as the

average value is -0.150160179. Here it means that all risk associated with this stock can be

eliminated with proper diversification of the portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-121-Mar-1

21-May-1

21-Jul-12

1-Sep-121-Nov-12

1-Jan-131-Mar-1

31-May-1

31-Jul-13

1-Sep-131-Nov-13

-2

-1.5

-1

-0.5

0

0.5

1

-0.224562359-0.344538598

0.230869426

0.461085258

-0.469156482

-1.483905128

0.015450038

0.272477641

-0.078051273-0.218631548

-0.010465660.04750653200000

01

RETURN

RETURNLinear (RETURN)

Chart 4.1.8

Inference

It can be seen from the above graph that the OMANI RIAL (OMR) has a less volatility of the

price of the stock in comparison with the market returns as the average return is less than one.

GERMAN MARK* (DEM)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 32.6992 32.6424 -0.173704555

30-Jun-11 FUTCUR 33.2867 33.3541 0.202483274

30-Sep-11 FUTCUR 34.4059 34.4932 0.253735551

31-Dec-11 FUTCUR 36.0209 35.9398 -0.225147067

31-Mar-12 FUTCUR 35.4308 35.3606 -0.198132698

30-Jun-12 FUTCUR 36.2407 36.0443 -0.541932137

30-Sep-12 FUTCUR 34.6356 34.5075 -0.369850674

31-Dec-12 FUTCUR 36.9524 36.9513 -0.002976803

31-Mar-13 FUTCUR 35.6532 35.6181 -0.098448386

30-Jun-13 FUTCUR 39.8053 39.6345 -0.429088589

30-Sep-13 FUTCUR 43.3435 43.3435 0

31-Dec-13 FUTCUR 43.3909 43.4796 0.204420743

TOTAL 441.8651 441.3689 -1.378641341AVERAGE RETURN -0.114886778 SD 0.258175478

VARIANCE 0.066654577

Table 4.1.9

Interpretation

As from the above it can be seen that the standard deviation (total risk associated with stock) of

BAHRAINI DINAR is 0.594243192, where as the average value is -0.650886332. Here it means

that all risk associated with this stock can be eliminated with proper diversification of the

portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-121-Mar-1

21-May-1

21-Jul-12

1-Sep-121-Nov-12

1-Jan-131-Mar-1

31-May-1

31-Jul-13

1-Sep-131-Nov-13

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

Return

Return

Chart 4.1.9

Inference

From the graph the beta is less than one and it shows that the less volatility of the price of the

stock in comparison with the market returns. Here it can be ascertained that there exist a

comparatively high difference between systematic risk and unsystematic risk.

SWISS FRANC (CHF)

Trade Date Instrument Open Price Close Price Return

31-Mar-11 FUTCUR 49.4206 49.132 -0.58396701

30-Jun-11 FUTCUR 54.577 54.417 -0.293163787

30-Sep-11 FUTCUR 55.157 55.2931 0.246750186

31-Dec-11 FUTCUR 57.8007 57.7577 -0.074393563

31-Mar-12 FUTCUR 57.4894 57.403 -0.150288575

30-Jun-12 FUTCUR 59.011 58.6685 -0.580400264

30-Sep-12 FUTCUR 55.9984 55.8475 -0.269471985

31-Dec-12 FUTCUR 59.842 59.8394 -0.004344775

31-Mar-13 FUTCUR 57.2939 57.208 -0.149928701

30-Jun-13 FUTCUR 63.1741 63.0289 -0.229841027

30-Sep-13 FUTCUR 69.1686 69.1686 0

31-Dec-13 FUTCUR 69.2275 69.3697 0.2054097

TOTAL 708.1602 707.1334 -1.8836398AVERAGE RETURN -0.156969983 SD 0.260644556

VARIANCE 0.067935585

Table 4.1.10

Interpretation

As from the above it can be seen that the standard deviation (total risk associated with stock) of

SWISS FRANC (CHF) is 0.260644556, where as the average value is -0.156969983. Here it

means that all risk associated with this stock can be eliminated with proper diversification of the

portfolio.

1-Mar-11

1-May-111-Jul-11

1-Sep-111-Nov-11

1-Jan-12

1-Mar-12

1-May-121-Jul-12

1-Sep-121-Nov-12

1-Jan-13

1-Mar-13

1-May-131-Jul-13

1-Sep-131-Nov-13

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

Return

Return

Chart 4.1.10

Inference

From the graph the beta is less than one and it shows that the less volatility of the price of the

stock in comparison with the market returns. Here it can be ascertained that there exist a

comparatively high difference between systematic risk and unsystematic risk.

CURRENCIESSTANDARD DEVIATION

AVERAGE RETURN VARIANCE

US DOLLAR (USD)

0.44145 -0.2425 0.19488

EURO (EUR)0.25815 -0.1148 0.06664

JAPANESE YEN (JPY)0.54092 -0.3552 0.2926

GREAT BRITAIN POUND (GBP)0.33025 -0.1446 0.10907

AUSTRALIAN DOLLAR (AUD)

0.51789 -0.1223 0.26821

BAHRAINI DINAR (BHD)

0.59424 -0.6509 0.35312

KUWAITI DINAR (KWD)0.47459 -0.2602 0.22524

OMANI RIAL (OMR)0.49702 -0.1502 0.24703

GERMAN MARK* (DEM)0.25818 -0.1149 0.066655

SWISS FRANC (CHF)0.26064 -0.157 0.06794

Table 4.1.11

Interpretation

The above table shows that the standard deviation of BAHRAINI DINAR (BHD) is the highest

among other currencies and the value of which is -0.1148. The standard deviation of JAPANESE

YEN is -0.1149 and that of AUSTRALIAN DOLLAR is 0.51789. The EURO has the lowest

standard deviation with the value of 0.25815.

The average return of EURO is the highest among other currencies and the value of which is

0.59424. The average return of GERMAN MARK* (DEM) is 0.54092 and that of SWISS

FRANC (CHF) is -0.157. The BAHRAINI DINAR (BHD) has the lowest average return with the

value of -0.6509.

The the variance of BAHRAINI DINAR (BHD) is the highest among other currencies and the

value of which is 0.35312. The variance of JAPANESE YEN is 0.2926 and that of

AUSTRALIAN DOLLAR is 0.26821. The EURO has the lowest variance with the value of

0.06664.

US DOLLA

R (USD)

EURO (EUR)

JAPANESE YEN

(JPY)

GREAT BRITAIN POUND (GBP)

AUSTRALIAN DOLLA

R (AUD)

BAHRAINI DINAR (BHD)

KUWAITI DINAR (KWD)

OMANI RIAL (OMR)

GERMAN MARK* (DEM

)

SWISS

FRANC (CHF)

0

0.1

0.2

0.3

0.4

0.5

0.6

standard deviation

Chart 4.1.11

Inference

The chart shows that the standard deviation of BAHRAINI DINAR (BHD) is the highest among

other currencies. The EURO has the lowest standard deviation.

US DOLLA

R (USD)

EURO (EUR)

JAPANESE YEN

(JPY)

GREAT BRITAIN POUND (GBP)

AUSTRALIAN DOLLA

R (AUD)

BAHRAINI DINAR (BHD)

KUWAITI DINAR (KWD)

OMANI RIAL (OMR)

GERMAN MARK* (DEM

)

SWISS

FRANC (CHF)

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

average return

average return

Chart 4.1.12

Inference

The chart shows that the average return of EURO is the highest among other currencies. The

BAHRAINI DINAR (BHD) has the lowest average return.

US DOLLAR (USD)

EURO (EUR)

JAPANESE YEN

(JPY)

GREAT BRITAIN POUND (GBP)

AUSTRALIAN DOLLA

R (AUD)

BAHRAINI DINAR (BHD)

KUWAITI DINAR (KWD)

OMANI RIAL (OMR)

GERMAN MARK* (DEM)

SWISS

FRANC (CHF)

00.05

0.10.15

0.20.25

0.30.35

0.4

variance

Chart 4.1.13

Inference

The chart shows that the variance of BAHRAINI DINAR (BHD) is the highest among other

currencies. The EURO has the lowest variance.

4.2 MOVING AVERAGE

A moving Average is a moving mean of data. In other word, moving average perform a

mathematical function where data. In other words, Moving Average perform a mathematical

function where data within selected period is averaged and the average “moves” as a new data is

included in the calculation while older data is removed or lessened. Moving averages essentially

smooth data by removing “noise”. This smoothing of data makes moving averages popular tools

in identifying price trends and trend reversals. The difference between the four main types of

moving averages (simple, Exponential, Volume adjusted and weighted) lies in the way that they

are calculated and whether they look at all the data available or only the data within selected

period. This means that each type of moving average has its own characteristics, for example

how quickly each will respond to change in the underlying price.

US DOLLAR (USD)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 45.2854

30-Jun-11 45.3348

30-Sep-11 49.6167 140.2369 46.7456

31-Dec-11 54.2859 149.2374 49.7958

31-Mar-12 51.8521 155.7547 51.9182

30-Jun-12 56.0542 162.1922 54.0690

30-Sep-12 52.5 160.4063 53.4687

31-Dec-12 54.689 163.2432 59.4144

31-Mar-13 54.355 161.544 53.848

30-Jun-13 59.597 168.641 56.2136

30-Sep-13 62.702 176.659 58.8846

31-Dec-13 61.7744 189.0734 61.3578

Table 4.2.1

Interpretation

The above table as well as the chart shows that the volatility of US DOLLAR show an upward

volatility as the moving average increases. It can be seen from the above that the moving average

as on 30-Sep-11was 46.7456 and the same had been increased to 49.7958 on 31-Dec-11. There

after it had been increased to 61.3578 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan

-121-Mar-1

21-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan

-131-Mar-1

31-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

10

20

30

40

50

60

70

3 Period Moving Average

3 Period Moving Average

Chart 4.2.1

Inference

The moving average shows an increase it can be concluded from the above that the US

DOLLAR is more volatile.

EURO (EUR)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 63.8429

30-Jun-11 65.235

30-Sep-11 67.4628 196.5407 65.5136

31-Dec-11 70.2921 202.9899 67.6633

31-Mar-12 69.1593 206.9142 68.9714

30-Jun-12 70.4966 209.998 69.9826

30-Sep-12 67.4908 207.1467 69.0489

31-Dec-12 72.2704 210.2578 70.0859

31-Mar-13 69.663 209.4242 69.8080

30-Jun-13 77.5184 219.4518 73.1506

30-Sep-13 84.7725 231.9539 77.3179

31-Dec-13 85.0387 247.3296 82.4432

Table 4.2.2

Interpretation

The above table shows that the volatility of EURO show an upward volatility as the moving

average increases. It can be seen from the above that the moving average as on 30-Sep-11was

65.5136and the same had been increased to 67.6633on 31-Dec-11. There after it had been

increased to 82.4432 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan

-121-Mar-1

21-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan

-131-Mar-1

31-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

10

20

30

40

50

60

70

80

90

3 Period Moving Average

3 Period Moving Average

Chart 4.2.2

Inference

The moving average shows an increase it can be concluded from the above that the EURO is

more volatile.

JAPANESE YEN (JPY)

Trade Date Close Price 3 period total

3 period moving average

31-Mar-11 0.5465

30-Jun-11 0.5598

30-Sep-11 0.6475 1.7538 0.5846

31-Dec-11 0.7012 1.9085 0.6362

31-Mar-12 0.6302 1.9789 0.6596

30-Jun-12 0.7047 2.0361 0.6787

30-Sep-12 0.6736 2.0085 0.6695

31-Dec-12 0.6366 2.0149 0.6716

31-Mar-13 0.5767 1.8869 0.6289

30-Jun-13 0.601 1.8143 0.6048

30-Sep-13 0.6379 1.8156 0.6052

31-Dec-13 0.587 1.8259 0.6086

Table 4.2.3

Interpretation

The above table shows that the volatility of JAPANESE YEN is highly volatile. It can be seen

from the above that the moving average as on 30-Sep-11was 0.5846 and the same had been

increased to 0.6362on 31-Dec-11. There after it had been increased to 0.6086 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan-12

1-Mar-121-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan-13

1-Mar-131-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0.52

0.54

0.56

0.58

0.6

0.62

0.64

0.66

0.68

0.7

3 Period Moving Average

3 Period Moving Average

Chart 4.2.3

Inference

The moving average shows an increase it can be concluded from the above that the JAPANESE

YEN is volatile.

GREAT BRITAIN POUND (GBP)

Trade Date Close Price 3 period total 3 period moving

average

31-Mar-11 72.5993

30-Jun-11 72.6155

30-Sep-11 77.5276 222.7424 74.2475

31-Dec-11 83.8886 234.0417 78.0139

31-Mar-12 82.8975 244.3137 81.4379

30-Jun-12 87.5275 254.3136 84.7712

30-Sep-12 84.8631 255.2881 85.0960

31-Dec-12 88.3408 260.7314 86.9104

31-Mar-13 82.5614 255.7653 85.2551

30-Jun-13 90.6375 261.5397 87.1799

30-Sep-13 101.173 274.3719 91.4573

31-Dec-13 101.854 293.6645 97.8882

Table 4.2.4

Interpretation

The above table shows that the volatility of GREAT BRITAIN POUND show an upward

volatility as the moving average increases from 74.2475 to 97.8882. It can be seen from the

above that the moving average as on 30-Sep-11was 74.2475and the same had been increased to

78.0139 on 31-Dec-11. There after it had been increased to 97.8882on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan-12

1-Mar-121-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan-13

1-Mar-131-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

20

40

60

80

100

120

3 Period Moving Average

3 Period Moving Average

Chart 4.2.4

Inference

The moving average shows an increase it can be concluded from the above that the GREAT

BRITAIN POUND is more volatile.

AUSTRALIAN DOLLAR (AUD)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 46.6852

30-Jun-11 48.0327

30-Sep-11 48.5822 143.3001 47.7667

31-Dec-11 55.2327 151.8476 50.6159

31-Mar-12 53.8495 157.6644 52.5548

30-Jun-12 56.9455 166.0277 55.3425

30-Sep-12 54.4772 165.2722 55.0908

31-Dec-12 56.7174 168.1401 56.0467

31-Mar-13 56.6178 167.8124 55.9374

30-Jun-13 54.4287 167.7639 55.9213

30-Sep-13 58.3894 169.4359 56.4786

31-Dec-13 54.8106 167.6287 55.8762

Table 4.2.5

Interpretation

The above table shows that the volatility of AUSTRALIAN DOLLAR as the moving average

increases from 47.7667 to 55.8762. It can be seen from the above that the moving average as on

30-Sep-11 was 47.7667 and the same had been increased to 50.6159on 31-Dec-11. There after

also the moving average was continuously increasing.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan-12

1-Mar-121-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan-13

1-Mar-131-May-1

31-Jul-13

1-Sep-13

1-Nov-13

42

44

46

48

50

52

54

56

58

3 Period Moving Average

3 Period Moving Average

Chart 4.2.5

Inference

The chart shows that the volatility of AUSTRALIAN DOLLAR shows an upward volatility as

the moving average.

BAHRAINI DINAR (BHD)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 119.774

30-Jun-11 120.232

30-Sep-11 131.202 371.208 123.736

31-Dec-11 143.534 394.968 131.656

31-Mar-12 136.896 411.632 137.2106

30-Jun-12 147.814 428.2114 142.748

30-Sep-12 137.011 421.721 140.5736

31-Dec-12 144.987 429.812 143.2707

31-Mar-13 142.402 424.4 141.4667

30-Jun-13 155.585 442.974 147.658

30-Sep-13 162.36 460.347 153.449

31-Dec-13 162.36 480.305 160.1017

Table 4.2.6

Interpretation

The above table as well as the chart shows that the volatility of BAHRAINI DINAR show an

upward volatility as the moving average increases. It can be seen from the above that the moving

average as on 30-Sep-11was 123.736 and the same had been increased to 131.656 on 31-Dec-11.

There after it had been increased to 160.1017 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan

-121-Mar-1

21-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan

-131-Mar-1

31-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

20

40

60

80

100

120

140

160

180

3 Period Moving Average

3 Period Moving Average

Chart 4.2.6

Inference

The moving average shows an increase it can be concluded from the above that the BAHRAINI

DINAR is more volatile.

KUWAITI DINAR (KWD)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 162.921

30-Jun-11 164.513

30-Sep-11 179.16 506.594 168.8647

31-Dec-11 194.671 538.344 179.448

31-Mar-12 186.404 560.235 186.745

30-Jun-12 199.24 580.315 193.4383

30-Sep-12 186.501 572.145 190.715

31-Dec-12 194.001 579.742 193.2473

31-Mar-13 189.688 570.19 190.0633

30-Jun-13 208.578 592.267 197.4223

30-Sep-13 220.937 619.195 206.3983

31-Dec-13 218.655 648.17 216.0566

Table 4.2.7

Interpretation

The above table as well as the chart shows that the volatility of KUWAITI DINAR show an

upward volatility as the moving average increases. It can be seen from the above that the moving

average as on 30-Sep-11was 168.8647and the same had been increased to 179.448 on 31-Dec-

11. There after it had been increased to 216.0566on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan

-121-Mar-1

21-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan

-131-Mar-1

31-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

50

100

150

200

250

3 Period Moving Average

3 Period Moving Average

Chart 4.2.7

Inference

The moving average shows an increase it can be concluded from the above that the KUWAITI

DINAR is more volatile.

OMANI RIAL (OMR)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 32.6424

30-Jun-11 33.3541

30-Sep-11 34.4932 100.4897 33.4966

31-Dec-11 35.9398 103.7871 34.5957

31-Mar-12 35.3606 105.7936 35.2645

30-Jun-12 36.0443 107.3447 35.7815

30-Sep-12 34.5075 105.9124 35.3041

31-Dec-12 36.9513 107.5031 35.8344

31-Mar-13 35.6181 107.0769 35.6923

30-Jun-13 39.6345 112.2039 37.4013

30-Sep-13 43.3435 118.5961 39.5320

31-Dec-13 43.4796 126.4576 42.1525

Table 4.2.8

Interpretation

It can be seen from the above that the volatility of OMNI RIAL show an upward volatility as the

moving average increases. It can be seen from the above that the moving average as on 30-Sep-

11 was 33.4966 and the same had been increased to 34.5957on 31-Dec-11. There after the

increase was up to 42.1525 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan-12

1-Mar-121-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan-13

1-Mar-131-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

5

10

15

20

25

30

35

40

45

3 Period Moving Average

3 Period Moving Average

Chart 4.2.8

Inference

The moving average shows an increase it can be concluded from the above that the OMNI RIAL is more volatile.

GERMAN MARK* (DEM)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 117.298

30-Jun-11 117.722

30-Sep-11 128.507 363.527 121.1757

31-Dec-11 141.186 387.415 129.1383

31-Mar-12 134.29 403.983 134.661

30-Jun-12 145.128 420.604 140.2013

30-Sep-12 135.943 415.361 138.4537

31-Dec-12 142.049 423.12 141.04

31-Mar-13 140.823 418.815 139.605

30-Jun-13 154.26 437.132 145.7107

30-Sep-13 162.419 457.502 152.5007

31-Dec-13 160.054 476.733 158.911

Table 4.2.9

Interpretation

It can be seen from the above that the volatility of GERMAN MARK show an upward volatility

as the moving average increases. It can be seen from the above that the moving average as on 30-

Sep-11 was 121.1757 and the same had been increased to 129.1383 on 31-Dec-11. There after

the increase was up to 158.911 on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan

-121-Mar-1

21-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan

-131-Mar-1

31-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

20

40

60

80

100

120

140

160

180

3 Period Moving Average

3 Period Moving Average

Chart 4.2.9

Inference

The moving average shows an increase it can be concluded from the above that the GERMAN

MARK is more volatile.

SWISS FRANC (CHF)

Trade Date Close Price3 period total

3 period moving average

31-Mar-11 49.132

30-Jun-11 54.417

30-Sep-11 55.2931 158.8421 52.9474

31-Dec-11 57.7577 167.4678 55.8226

31-Mar-12 57.403 170.4538 56.8179

30-Jun-12 58.6685 173.8292 57.9430

30-Sep-12 55.8475 171.919 57.3063

31-Dec-12 59.8394 174.3554 58.1184

31-Mar-13 57.208 172.8949 57.6316

30-Jun-13 63.0289 180.0763 60.0254

30-Sep-13 69.1686 189.4055 63.1352

31-Dec-13 69.3697 201.5672 67.1891

Table 4.2.10

Interpretation

It can be seen from the above that the volatility of SWISS FRANC show an upward volatility as

the moving average increases. It can be seen from the above that the moving average as on 30-

Sep-11 was 52.9474 and the same had been increased to 55.8226 on 31-Dec-11. There after the

increase was up to 67.1891on 31-Dec-13.

1-Mar-111-May-1

11-Jul-11

1-Sep-11

1-Nov-111-Jan-12

1-Mar-121-May-1

21-Jul-12

1-Sep-12

1-Nov-121-Jan-13

1-Mar-131-May-1

31-Jul-13

1-Sep-13

1-Nov-13

0

10

20

30

40

50

60

70

80

3 Period Moving Average

3 Period Moving Average

Chart 4.2.10

Inference

The moving average shows an increase it can be concluded from the above that the SWISS

FRANC is more volatile.

4.3 CO-EFFICIENT OF VARIATION

US DOLLAR (USD)

Trade Date Close Price(X)X2

31-Mar-11 45.2854 2050.767

30-Jun-11 45.3348 2055.244

30-Sep-11 49.6167 2461.817

31-Dec-11 54.2859 2946.959

31-Mar-12 51.8521 2688.64

30-Jun-12 56.0542 3142.073

30-Sep-12 52.5 2756.25

31-Dec-12 54.689 2990.887

31-Mar-13 54.355 2954.466

30-Jun-13 59.597 3551.802

30-Sep-13 62.702 3931.541

31-Dec-13 61.7744 3816.076

Table 4.3.1

SD=√¿¿ = 5.39656895: Mean=∑ x

n = 54.00375

Co−efficient of variation= SDMean

∗100

= 10.4377

Interpretation

The co efficient of variation of US DOLLAR is 10.4377. A high value of co efficient of

variation means that the currency is more volatile.

EURO (EUR)

Trade Date Close Price(X)X^2

31-Mar-11 63.8429 4075.916

30-Jun-11 65.235 4255.605

30-Sep-11 67.4628 4551.229

31-Dec-11 70.2921 4940.979

31-Mar-12 69.1593 4783.009

30-Jun-12 70.4966 4969.771

30-Sep-12 67.4908 4555.008

31-Dec-12 72.2704 5223.011

31-Mar-13 69.663 4852.934

30-Jun-13 77.5184 6009.102

30-Sep-13 84.7725 7186.377

31-Dec-13 85.0387 7231.58

Table 4.3.2

SD=√¿¿ = 6.977583229: Mean=∑ x

n = 71.936875

Co−efficient of variation= SDMean

∗100

= 9.6996

Interpretation

It can be seen that the co efficient of variation of EURO is 9.6996

JAPANESE YEN (JPY)

Trade Date Close Price(X)X2

31-Mar-11 0.5465 0.298662

30-Jun-11 0.5598 0.313376

30-Sep-11 0.6475 0.419256

31-Dec-11 0.7012 0.491681

31-Mar-12 0.6302 0.397152

30-Jun-12 0.7047 0.496602

30-Sep-12 0.6736 0.453737

31-Dec-12 0.6366 0.40526

31-Mar-13 0.5767 0.332583

30-Jun-13 0.601 0.361201

30-Sep-13 0.6379 0.406916

31-Dec-13 0.587 0.344569

Table 4.3.3

SD=√¿¿ = 0.052327919: Mean=∑ x

n = 0.625225

Co−efficient of variation= SDMean

∗100

= 8.3695

Interpretation

The co efficient of variation of JAPANESE YEN is 8.3695.

GREAT BRITAIN POUND (GBP)

Trade Date Close Price(X)X2

31-Mar-11 72.5993 5270.658

30-Jun-11 72.6155 5273.011

30-Sep-11 77.5276 6010.529

31-Dec-11 83.8886 7037.297

31-Mar-12 82.8975 6871.996

30-Jun-12 87.5275 7661.063

30-Sep-12 84.8631 7201.746

31-Dec-12 88.3408 7804.097

31-Mar-13 82.5614 6816.385

30-Jun-13 90.6375 8215.156

30-Sep-13 101.173 10235.98

31-Dec-13 101.854 10374.24

Table 4.3.4

SD=√¿¿ = 9.371424533: Mean=∑ x

n = 85.54048333

Co−efficient of variation= SDMean

∗100

= 10.9555

Interpretation

The co efficient of variation of GREAT BRITAIN POUND is 10.9555. A high value of co

efficient of variation means that the currency is more volatile.

AUSTRALIAN DOLLAR (AUD)

Trade Date Close Price(X)X2

31-Mar-11 46.6852 2179.508

30-Jun-11 48.0327 2307.14

30-Sep-11 48.5822 2360.23

31-Dec-11 55.2327 3050.651

31-Mar-12 53.8495 2899.769

30-Jun-12 56.9455 3242.79

30-Sep-12 54.4772 2967.765

31-Dec-12 56.7174 3216.863

31-Mar-13 56.6178 3205.575

30-Jun-13 54.4287 2962.483

30-Sep-13 58.3894 3409.322

31-Dec-13 54.8106 3004.202

Table 4.3.5

SD=√¿¿ = 3.842208671: Mean=∑ x

n = 53.73074167

Co−efficient of variation= SDMean

∗100

= 7.1509

Interpretation

The co efficient of variation of AUSTRALIAN DOLLAR is 7.1509. A high value of co efficient

of variation means that the currency is more volatile.

BAHRAINI DINAR (BHD)

Trade Date Close Price(X)X2

31-Mar-11 119.774 14345.81

30-Jun-11 120.232 14455.73

30-Sep-11 131.202 17213.96

31-Dec-11 143.534 20602.01

31-Mar-12 136.896 18740.51

30-Jun-12 147.814 21848.98

30-Sep-12 137.011 18772.01

31-Dec-12 144.987 21021.23

31-Mar-13 142.402 20278.33

30-Jun-13 155.585 24206.69

30-Sep-13 162.36 26360.77

31-Dec-13 162.36 26360.77

Table 4.3.6

SD=√¿¿ = 14.12357004: Mean=∑ x

n = 142.0130833

Co−efficient of variation= SDMean

∗100

= 9.9453

Interpretation

The co efficient of variation of BAHRAINI DINAR is 9.9453.

KUWAITI DINAR (KWD)

Trade Date Close Price(X)X^2

31-Mar-11 162.921 26543.25

30-Jun-11 164.513 27064.53

30-Sep-11 179.16 32098.31

31-Dec-11 194.671 37896.8

31-Mar-12 186.404 34746.45

30-Jun-12 199.24 39696.58

30-Sep-12 186.501 34782.62

31-Dec-12 194.001 37636.39

31-Mar-13 189.688 35981.54

30-Jun-13 208.578 43504.78

30-Sep-13 220.937 48813.16

31-Dec-13 218.655 47810.01

Table 4.3.7

SD=√¿¿ = 18.38719736: Mean=∑ x

n = 192.10575

Co−efficient of variation= SDMean

∗100

= 9.5714

Interpretation

As from the above it can be seen that the co efficient of variation of BAHRAINI DINAR is

9.5714.

OMNI RIAL (OMR)

Trade Date Close Price(X)X2

31-Mar-11 117.298 13758.82

30-Jun-11 117.722 13858.47

30-Sep-11 128.507 16514.05

31-Dec-11 141.186 19933.49

31-Mar-12 134.29 18033.8

30-Jun-12 145.128 21062.14

30-Sep-12 135.943 18480.5

31-Dec-12 142.049 20177.92

31-Mar-13 140.823 19831.12

30-Jun-13 154.26 23796.15

30-Sep-13 162.419 26379.93

31-Dec-13 160.054 25617.28

Table 4.3.8

SD=√¿¿ = 14.56501002: Mean=∑ x

n = 139.97325

Co−efficient of variation= SDMean

∗100

= 10.4056

Interpretation

As from the above it can be seen that the co efficient of variation of OMANI RIAL is 10.4056.

GERMAN MARK* (DEM)

Trade Date Close Price(X)X2

31-Mar-11 32.6424 1065.526

30-Jun-11 33.3541 1112.496

30-Sep-11 34.4932 1189.781

31-Dec-11 35.9398 1291.669

31-Mar-12 35.3606 1250.372

30-Jun-12 36.0443 1299.192

30-Sep-12 34.5075 1190.768

31-Dec-12 36.9513 1365.399

31-Mar-13 35.6181 1268.649

30-Jun-13 39.6345 1570.894

30-Sep-13 43.3435 1878.659

31-Dec-13 43.4796 1890.476

Table 4.3.9

SD=√¿¿ = 3.567578926: Mean=∑ x

n = 36.78074167

Co−efficient of variation= SDMean

∗100

= 9.6996

Interpretation

As from the above it can be seen that the co efficient of variation of GERMAN MARK is

9.6996.

SWISS FRANC (CHF)

Trade Date Close Price(X)X2

31-Mar-11 49.132 2413.953

30-Jun-11 54.417 2961.21

30-Sep-11 55.2931 3057.327

31-Dec-11 57.7577 3335.952

31-Mar-12 57.403 3295.104

30-Jun-12 58.6685 3441.993

30-Sep-12 55.8475 3118.943

31-Dec-12 59.8394 3580.754

31-Mar-13 57.208 3272.755

30-Jun-13 63.0289 3972.642

30-Sep-13 69.1686 4784.295

31-Dec-13 69.3697 4812.155

Table 4.3.10

SD=√¿¿ = 5.856470393: Mean=∑ x

n = 58.92778333

Co−efficient of variation= SDMean

∗100

= 9.9384

Interpretation

As from the above it can be seen that the co efficient of variation of SWISS FRANC is 9.9384.

CURRENCIES COEFFICIENT OF VARIATION

US DOLLAR (USD)10.4377

EURO (EUR)9.6996

JAPANESE YEN (JPY)8.3695

GREAT BRITAIN POUND (GBP)10.9555

AUSTRALIAN DOLLAR (AUD)7.1509

BAHRAINI DINAR (BHD)9.9453

KUWAITI DINAR (KWD)9.5714

OMANI RIAL (OMR)10.4056

GERMAN MARK* (DEM)9.6996

SWISS FRANC (CHF)9.9384

Table 4.3.11

Interpretation

The analysis shows that the co- efficient of variation of GREAT BRITAIN POUND is 10.9555,

the greatest and the co- efficient of variation of AUSTRALIAN DOLLAR is 7.1509, the lowest.

US DOLLA

R (USD)

EURO (EUR)

JAPANESE YEN

(JPY)

GREAT BRITA

IN POUND (GBP)

AUSTRALIA

N DOLLAR (AUD)

BAHRAINI DINAR (BHD)

KUWAITI DINAR (KWD)

OMANI RIAL (OMR)

GERMAN MARK* (DEM

)

SWISS

FRANC (CHF)

0

2

4

6

8

10

12

Series1

Chart 4.3.1

Inference

The analysis shows that the co- efficient of variation of GREAT BRITAIN POUND is the

greatest and thus it can be interpreted that the GREAT BRITAIN POUND is more volatile and

the co- efficient of variation of AUSTRALIAN DOLLAR is the lowest and thus the same is less

volatile than other currency.

FINDINGS

The major findings of the study are the following.

It was found that the co- efficient of variation of GREAT BRITAIN POUND is the

greatest and thus it can be interpreted that the GREAT BRITAIN POUND is more

volatile and the co- efficient of variation of AUSTRALIAN DOLLAR is the lowest and

thus the same is less volatile than other currency.

The moving average analysis shows that the moving average of all the currencies under

study are shows an upward trend.

It was found that the standard deviation of BAHRAINI DINAR (BHD) is the highest

among other currencies and the value of which is -0.1148.. The EURO has the lowest

standard deviation with the value of 0.25815.

The average return of EURO is the highest among other currencies and the value of

which is 0.59424. The BAHRAINI DINAR (BHD) has the lowest average return with the

value of -0.6509.

The variance of BAHRAINI DINAR (BHD) is the highest among other currencies and

the value of which is 0.35312. The EURO has the lowest variance with the value of

0.06664.

SUGGESTIONS

An investor who is looking to make decision should depend on the analysis of each

currencies rather than going with pure market information. He should consider the trend

shown by the currencies for last few years. Study of risk and return will help the investor

to take appropriate decision regarding his investment.

The moving average of the currency is technical indicators that follow the movement of

the currency. It shows a sustained movement upwards or downwards of the currency. The

moving average of the currencies shows the trend followed by each currency against

Indian rupee during the period.

The return from the currencies is the performance measure used to evaluate the efficiency

of an investment. The return from the currencies is different and EURO (EUR) has the

highest return value compared to all other currencies.

The co-efficient of variation of the currencies is used to know about the degree of

variation. The coefficient of variation is used to determine how much volatility (risk) can

be assumed in comparison to the amount of return that can be expected from your

investment. The lower the ratio of standard deviation to mean return, the better your risk-

return trade-off. GREAT BRITAIN POUND (GBP) has the highest co-efficient of

variation of all the currencies.

Higher volatility means that a security's value can potentially be spread out over a larger

range of values. A lower volatility means that a security's value does not fluctuate

dramatically. Higher the volatility, the riskier the trading of the currency. BAHRAINI

DINAR (BHD) has the highest volatility and it is riskier in trading. EURO (EUR) has the

least volatility and it has the less risk in trading.

CONCLUSION

The study carried out on risk and return associated with the Foreign Exchange market. The

awareness of the forex market in India is very low in compare to other financial instruments.

Only fewer people know about the currency trading. In India US Dollar, Euro, British Pound,

and Japanese Yen are the currencies which have been traded mostly. US dollar and euro are the

most preferred currency in response from the investor. The main or primary object of investing

in currency market by investor is hedging. More number of respondents is connected in the

business of import-export. They use to hedge the currency market for future payment and earn

the deference. In the case of developing countries these results address a gap in the existing

literature on forecasting exchange rate volatility using daily data. To the best of our knowledge,

there are no existing studies of developing countries’ data that focus on the forecasting

performance of models that capture daily exchange rate volatility. Further work along these lines

may be called for, to check that results are not specific to the particular data set and/or the

specification in the volatility process. For instance, it would be of great interest to check whether

our results for four developing countries can be generalized for a wider range of other

developing countries, although at present our analysis focused on countries that have not been

subject to a discrete change in their exchange rate regime during the sample. This study

concluded that the investors in forex market try to study volatility in currencies and take logical

decision under the risk and return analysis.

BIBLIOGRAPHY

Avandi.V.A, (fifth edition), “Investment Management”, Himalaya Publication House (2003)

Elton, Edwin.J and Gruber, Martin J, (fifth edition), “Modern Portfolio Theory and Investment

Analysis”

Prasanna Chandra, (second edition), “Investment Analysis and Portfolio Management” TATA

McGraw Hill Publishing Company (2005)

Raja Rajan in the article “Chennai Investors is Conservative”, 1997

S Kevin “Security Analysis and Portfolio Management”, PHI Learning Private Limited 2010

Singh, Preethi (tenth edition), “Investment Management”, Himalaya Publication 2002

Stephen. J, The institute of international auditors UK and Ireland University Edition. “Managing

currency risk: Using Financial derivatives”, 2003.

Syama Sunder in the article “Growth Prospects of Mutual Funds and Investor Perception with

the special reference to Kothari Pioneer Mutual Funds”, 1998

Valdez. S. 5th edition. “An introduction to global financial markets”, Palgrave Macmillan, 2007

ABBREVIATIONS

AUD: Australian Dollar

AUM: Assets under Management

BHD: Bahraini Dinar

CDSL: Central Depository Services (India) Ltd

CHF: Swiss Franc

CME: Chicago Mercantile Exchange

DEM: German Mark

EUR: Euro

GBP: Great Britain Pound

JPY: Japanese Yen

KWD: Kuwaiti Dinar

NCDEX: National Commodities Derivative Exchange Ltd

NMCEIL: National Multi Commodity Exchange of India Ltd

NSDL: National Securities Depository Ltd

OMR: Omani Rial

USD: US Dollar

APPENDIX

US DOLLAR (USD)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 45.3884 45.3884 45.2854 45.3369 45.285430-Jun-11 FUTCUR 45.4916 45.4916 43.3348 45.4132 45.334830-Sep-11 FUTCUR 49.4995 49.6167 49.4995 49.5581 49.616731-Dec-11 FUTCUR 54.5234 54.5234 54.2859 54.4047 54.285931-Mar-12 FUTCUR 52.0992 52.0992 51.8521 51.9757 51.852130-Jun-12 FUTCUR 56.8925 56.8925 56.0542 56.4733 56.054230-Sep-12 FUTCUR 52.4862 52.5000 52.4862 52.4931 52.500031-Dec-12 FUTCUR 54.6890 54.6890 54.6890 54.6890 54.689031-Mar-13 FUTCUR 54.4017 54.4017 54.3550 54.3783 54.355030-Jun-13 FUTCUR 59.6964 59.6964 595970 59.6467 59.597030-Sep-13 FUTCUR 62.7020 62.7020 62.7020 62.7020 62.702031-Dec-13 FUTCUR 61.7530 61.7744 61.7530 61.7637 61.7744

EURO (EUR)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 63.9540 63.9540 63.8429 63.8984 63.842930-Jun-11 FUTCUR 65.1030 65.2350 65.1030 65.1690 65.235030-Sep-11 FUTCUR 67.2921 67.4628 67.2921 67.3775 67.462831-Dec-11 FUTCUR 70.4507 70.4507 70.2921 70.3714 70.292131-Mar-12 FUTCUR 69.2967 69.2967 69.1593 69.2280 69.159330-Jun-12 FUTCUR 70.8806 70.8806 70.4966 70.6886 70.496630-Sep-12 FUTCUR 67.7412 67.7412 67.4908 67.6160 67.490831-Dec-12 FUTCUR 72.2726 72.2726 72.2704 72.2715 72.270431-Mar-13 FUTCUR 69.7315 69.7315 69.6630 69.6972 69.663030-Jun-13 FUTCUR 77.8525 77.8525 77.5184 77.6855 77.518430-Sep-13 FUTCUR 84.7725 84.7725 84.7725 84.7725 84.772531-Dec-13 FUTCUR 84.8653 85.0387 84.8653 84.9520 85.0387

JAPANESE YEN (JPY)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 0.5536 0.5536 0.5465 0.5501 0.546530-Jun-11 FUTCUR 0.5624 0.5624 0.5598 0.5611 0.559830-Sep-11 FUTCUR 0.6467 0.6475 0.6467 0.6471 0.647531-Dec-11 FUTCUR 0.7009 0.7012 0.7009 0.7010 0.701231-Mar-12 FUTCUR 0.6315 0.6315 0.6302 0.6309 0.630230-Jun-12 FUTCUR 0.7161 0.7161 0.7047 0.7104 0.704730-Sep-12 FUTCUR 0.6755 0.6755 0.6736 0.6746 0.673631-Dec-12 FUTCUR 0.6366 0.6366 0.6366 0.6366 0.636631-Mar-13 FUTCUR 0.5779 0.5779 0.5767 0.5773 0.576730-Jun-13 FUTCUR 0.6034 0.6034 0.6010 0.6022 0.601030-Sep-13 FUTCUR 0.6379 0.6379 0.6379 0.6379 0.637931-Dec-13 FUTCUR 0.5870 0.5870 0.5870 0.5870 0.5870

GREAT BRITAIN POUND (GBP)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 72.5928 72.5993 72.5928 72.5960 72.599330-Jun-11 FUTCUR 72.6878 72.6878 72.6155 72.6516 72.615530-Sep-11 FUTCUR 77.3678 77.5276 77.3678 77.4477 77.527631-Dec-11 FUTCUR 84.1083 84.1083 83.8886 83.9984 83.888631-Mar-12 FUTCUR 82.8555 82.8975 82.8555 82.8765 82.897530-Jun-12 FUTCUR 88.4638 88.4638 87.5275 87.9957 87.527530-Sep-12 FUTCUR 85.0528 85.0528 84.8631 84.9580 84.863131-Dec-12 FUTCUR 88.3413 88.3413 88.3408 88.3410 88.340831-Mar-13 FUTCUR 82.6660 82.6660 82.5614 82.6137 82.561430-Jun-13 FUTCUR 90.9606 90.9606 90.6375 90.7990 90.637530-Sep-13 FUTCUR 101.173 101.173 101.173 101.173 101.17331-Dec-13 FUTCUR 101.729 101.854 101.729 101.791 101.854

AUSTRALIAN DOLLAR (AUD)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 46.5158 46.6852 46.5158 46.6005 46.685230-Jun-11 FUTCUR 47.6679 48.0327 47.6679 47.8503 48.032730-Sep-11 FUTCUR 48.9031 48.9031 48.5822 48.7426 48.582231-Dec-11 FUTCUR 55.0146 55.2327 55.0146 55.1236 55.232731-Mar-12 FUTCUR 53.9774 53.9774 53.8495 53.9134 53.849530-Jun-12 FUTCUR 57.2850 57.2850 56.9455 57.1153 56.945530-Sep-12 FUTCUR 54.7310 54.7310 54.4772 54.6041 54.477231-Dec-12 FUTCUR 56.7185 56.7185 56.7174 56.7180 56.717431-Mar-13 FUTCUR 56.6463 56.6463 56.6178 56.6320 56.617830-Jun-13 FUTCUR 55.0287 55.0287 54.4287 54.7287 54.428730-Sep-13 FUTCUR 58.3894 58.3894 58.3894 58.3894 58.389431-Dec-13 FUTCUR 54.7564 54.8106 54.7564 54.7835 54.8106

BAHRAINI DINAR (BHD)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 120.107 120.107 119.774 119.941 119.77430-Jun-11 FUTCUR 120.648 120.648 120.232 120.440 120.23230-Sep-11 FUTCUR 131.003 131.202 131.202 131.102 131.20231-Dec-11 FUTCUR 144.230 144.230 143.534 143.882 143.53431-Mar-12 FUTCUR 137.476 137.476 136.896 137.186 136.89630-Jun-12 FUTCUR 150.013 150.013 147.814 148.913 147.81430-Sep-12 FUTCUR 138.384 138.384 137.011 137.697 137.01131-Dec-12 FUTCUR 144.964 144.987 144.964 144.976 144.98731-Mar-13 FUTCUR 143.419 143.419 142.402 142.911 142.40230-Jun-13 FUTCUR 157.415 157.415 155.585 156.500 155.58530-Sep-13 FUTCUR 165.340 165.340 162.360 163.850 162.36031-Dec-13 FUTCUR 162.881 162.881 162.360 162.341 162.360

KUWAITI DINAR (KWD)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 163.391 163.391 162.921 163.156 162.92130-Jun-11 FUTCUR 165.244 165.244 164.513 164.879 164.51330-Sep-11 FUTCUR 178.628 179.160 178.628 178.894 179.16031-Dec-11 FUTCUR 195.621 195.621 194.671 195.146 194.67131-Mar-12 FUTCUR 187.185 187.185 186.404 186.794 186.40430-Jun-12 FUTCUR 202.378 202.378 199.240 200.809 199.24030-Sep-12 FUTCUR 186.544 186.544 186.501 186.523 186.50131-Dec-12 FUTCUR 194.098 194.098 194.001 194.050 194.00131-Mar-13 FUTCUR 189.870 189.870 189.688 189.774 189.68830-Jun-13 FUTCUR 208.984 208.984 208.578 208.781 208.57830-Sep-13 FUTCUR 221.148 221.148 220.937 221.043 220.93731-Dec-13 FUTCUR 218.170 218.655 218.170 218.412 218.655

OMANI RIAL (OMR)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 117.562 117.562 117.298 117.430 117.29830-Jun-11 FUTCUR 118.129 118.129 117.722 117.925 117.72230-Sep-11 FUTCUR 128.211 128.507 128.211 128.359 128.50731-Dec-11 FUTCUR 140.538 141.186 140.538 140.862 141.18631-Mar-12 FUTCUR 134.923 134.923 134.290 134.506 134.29030-Jun-12 FUTCUR 147.314 147.314 145.128 146.221 145.12830-Sep-12 FUTCUR 135.922 135.943 135.922 135.933 135.94331-Dec-12 FUTCUR 141.663 142.049 141.663 141.856 142.04931-Mar-13 FUTCUR 140.933 140.933 140.823 140.878 140.82330-Jun-13 FUTCUR 154.598 154.598 154.260 154.429 154.26030-Sep-13 FUTCUR 162.436 162.436 162.419 162.149 162.41931-Dec-13 FUTCUR 159.978 160.054 159.978 160.054 160.054

GERMAN MARK* (DEM)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 32.6992 32.6992 32.6424 32.6708 32.642430-Jun-11 FUTCUR 33.2867 33.3541 33.2867 33.3204 33.354130-Sep-11 FUTCUR 34.4059 34.4932 34.4059 34.4496 34.493231-Dec-11 FUTCUR 36.0209 36.0209 35.9398 35.9804 35.939831-Mar-12 FUTCUR 35.4308 35.4308 35.3606 35.3957 35.360630-Jun-12 FUTCUR 36.2407 36.2407 36.0443 36.1425 36.044330-Sep-12 FUTCUR 34.6356 34.6356 34.5075 34.5716 34.507531-Dec-12 FUTCUR 36.9524 36.9524 36.9513 36.9519 36.951331-Mar-13 FUTCUR 35.6532 35.6532 35.6181 35.6356 35.618130-Jun-13 FUTCUR 39.8053 39.8053 39.6345 39.7199 39.634530-Sep-13 FUTCUR 43.3435 43.3435 43.3435 43.3435 43.343531-Dec-13 FUTCUR 43.3909 43.4796 43.3909 43.4352 43.4796

SWISS FRANC (CHF)

Trade Date

Instrument Open Price

High Price Low Price Average Price

Close Price

31-Mar-11 FUTCUR 49.4206 49.4206 49.1320 49.2763 49.132030-Jun-11 FUTCUR 54.5770 54.5770 54.4170 54.4970 54.417030-Sep-11 FUTCUR 55.1570 55.2931 55.1570 55.2250 55.293131-Dec-11 FUTCUR 57.8007 57.8007 57.7577 57.7792 57.757731-Mar-12 FUTCUR 57.4894 57.4894 57.4030 57.4462 57.403030-Jun-12 FUTCUR 59.0110 59.0110 58.6685 58.8398 58.668530-Sep-12 FUTCUR 55.9984 55.9984 55.8475 55.9230 55.847531-Dec-12 FUTCUR 59.8420 59.8420 59.8394 59.8407 59.839431-Mar-13 FUTCUR 57.2939 57.2939 57.2080 57.2510 57.208030-Jun-13 FUTCUR 63.1741 63.1741 63.0289 63.1015 63.028930-Sep-13 FUTCUR 69.1686 69.1686 69.1686 69.1686 69.168631-Dec-13 FUTCUR 69.2275 69.3697 63.1741 69.2986 69.3697