Grand Project

AMaster Level Project Report

On“Measuring the Volatility of Foreign Exchange Market in

India”

SubmittedIn the partial fulfillment of the Degree of

Master of Business AdministrationSemester-4

Prepared By:-Kaushik Gangajaliya (11SOMBA21059)

Chandni Thakker (11SOMBA21052)

Under the Guidance of:-Dr. Chetna Parmar

(Associate Professor),School of Management

Submitted To:School of Management,

RK.University,Rajkot.

DECLARATION

We hereby declare that project titled “Measuring the Volatility of Foreign Exchange Market

in India”. It is an original piece of research work carried out by us under the guidance and

supervision of Dr. Chetna Parmar. The Information has been collected from genuine and

authentic sources. The work has been submitted in the partial fulfillment of the requirement

of MBA to our college.

Signature: Name of the Students

Kaushik Gangajaliya

Chandni Thakker

Date:

Place: Rajkot

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PREFACE

As a part of our course curriculum of MBA, We are assigned some practical studies as well

as the theoretical knowledge in the related areas for completing the project. We are preparing

comprehensive report on “Measuring the Volatility of Foreign Exchange Market in India” So

far as decision of the industry is concerned; we have chosen the financial industry. In our

project we are making use of secondary data for that purpose.

This project really enhances our knowledge about the Forex Market as a whole. This project

will also give us firm understanding of market behaviour and help to know which currency is

more volatile and in which one should invest in. We have gained lot knowledge from this

project. And we believe this will help us in near future.

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ACKNOWLEDGEMENT

As a part of the MBA curriculum at R.K University, the ‘Grand Project Report Program’

enables the students to enhance their skills, expand their craniums by applying various

theories, concepts and laws to real life scenario which would further prepare them to face in

the near future.

Grand Project Report is the part of curriculum of R.K. University which helps in overall

development of the student and gives him or her platform to understand the corporate

environment as well as to implement the theoretical knowledge.

I would like to thank my faculty guide Dr. Chetna Parmar (associate Professor) for his

valuable guidance and support during my research period.

I would also like to thanks Dr. Raashid Saiyed, Director of school of management at R.K

University for giving me the opportunity to work in this research and carry the college’s

name forward.

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Table of Content

Serial No. Particulars Page No.

1 Introduction

Industry

Regulatory Authorities/Laws

7

11

14

2 Need of the Study

Review of Literature

Research Gap

17

18

21

3 Research Design and Methodology

Objectives of Study

Hypothesis

Period of Study

Sample Design

Type of Research

Data Collection Method

Tools and Techniques for Data Analysis

Limitations of Study

Future scope of study

22

23

24

24

25

26

27

27

28

28

4 Analysis and Interpretation 30

5 Conclusion 44

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CHAPTER 1

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Introduction to the Foreign Exchange Market

The foreign exchange market is the biggest financial market in the world. In forex market

everyday transactions is near about 3.98 trillion dollars. The major aim of introducing the

foreign exchange market is to facilitate international trade by enabling businesses to perform

transactions outside their local currency. The market operates round the clock from Monday

through Friday.

In the foreign exchange market a trader can purchase international currencies by paying

different currency. This type of foreign exchange market started to develop in the 1970s,

which was about thirty years after foreign exchange was introduced. Some important features

about the FX market include the following:

1. It has a very large number of daily participants. This makes its liquidity one of the

highest in the world.

2. Participants come from several countries in the world.

3. The market is open from 22:00 GMT on Sunday to 20:00 GMT on Friday.

4. Exchange rates are affected by a number of factors.

Market Size and Liquidity

Liquidity in the forex market is the highest among other financial markets in the world. The

market comprises central banks, currency speculators, organizations, governments, retail

investors and international investors. Over the years, the size of the FX market has been

constantly increasing. In 2010, The Triennial Survey by the Bank of International

Settlements reported that the average daily transaction in the US for the month of April was

$3.98 trillion. This was much greater than the $1.7 trillion recorded in 1998.

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Market Participant

There are three types of participants in the foreign exchange market. These are: central

banks, global funds, retail clients (or individual retailers) and corporations. The commercial

and investment banks belong to the group known as “interbank” market. This level

constitutes about seventy five percent of the total volume available each day.

Determinants of FX rates

For countries operating on the floating exchange rate regime, the exchange rates of their

currencies can be determined by the following theories:

1. International Parity Conditions: These include theories such as relative purchasing

power parity, interest rate parity, domestic fisher effect and international fisher effect.

Although these theories work to actually determine FX rates, they can also falter

because they are formed on assumptions that are not always true.

2. Balance of payment model: This is concerned with the exchange of goods and

services without considering the effect of the flow of money between and among

nations.

It is not possible to predict FX rates within long time frames with these theories. The best

that can be done with these is predicting future prices that can occur within a few days. FX

rates cannot be judged on a single factor but rather by combining several factors in

economics, politics and market psychology.

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Meaning of 'Derivative'

A security whose price is dependent upon or derived from one or more underlying assets.

The derivative itself is merely a contract between two or more parties. Its value is determined

by fluctuations in the underlying asset. The most common underlying assets include stocks,

bonds, commodities, currencies, interest rates and market indexes. Most derivatives are

characterized by high leverage.

Meaning of Currency Derivative

Futures Contract is a standardized exchange traded contract to buy or sell a certain

underlying instrument at a certain date in the future at a specified price. The underlying

instrument in Currency future is a foreign exchange rate. The price of a future contract is

expressed in terms of INR per unit of other currency e.g. US Dollars. Currency future

contracts allow investors to hedge against foreign exchange risk. Currently Currency Futures

are available on four currency pairs viz. US Dollars (USD-INR), Euro (EUR-INR), Great

Britain Pound (GBP-INR) and Japanese Yen (JPY-INR).

Benefits of Currency Derivative

Currency Derivatives are very efficient risk management instruments and you can derive the

below benefits:

1. Hedging: You can protect your foreign exchange exposure in business and hedge

potential losses by taking appropriate positions in the same. For e.g. If you are an

importer, and have USD payments to make at a future date, you can hedge your

foreign exchange exposure by buying USDINR and fixing your pay out rate today.

You would hedge if you were of the view that USDINR was going to depreciate.

Similarly it would give hedging opportunities to Exporters to hedge their future

receivables,

2. Speculation: You can speculate on the short term movement of the markets by using

Currency Futures. For e.g. If you expect oil prices to rise and impact India's import

bill, you would buy USDINR in expectation that the INR would depreciate.

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Alternatively if you believed that strong exports from the IT sector, combined with

strong FII flows will translate to INR appreciation you would sell USDINR.

3. Arbitrage: You can make profits by taking advantage of the exchange rates of the

currency in different markets and different exchanges.

4. Leverage: You can trade in the currency derivatives by just paying a % value called

the margin amount instead of the full traded value.

Financial Instruments

Financial instruments in the Forex market include spot, forward and swap.

Spot

A spot transaction lasts for two days except when currencies such as the US dollar, Canadian

dollar, Euro, Turkish Lira and Russian ruble are traded. In these cases, transactions are

completed on the next business day. Normally, there is no interest involved in this transaction

since it is just a direct exchange.

Forward

Forward transaction is an effective way of reducing risks in the Forex market. With this,

traders do not exchange money until when an agreed exchange rate between currencies is

actualized. This may happen in one day, several months or years.

Swap

In swap, two traders agree to make a transaction that will be reversed in the future. Since this

is not a standard operation, there is no exchange created for this.

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HISTORY OF FOREIGN EXCHANGE MARKET

Ancient

Forex first occurred in ancient times. Money-changing people, people helping others to

change money and also taking a commission or charging a fee were living in the times of the

Talmudic writings (Biblical times). These people (sometimes called "kollybistẻs") used city-

stalls, at feast times the temples Court of the Gentiles instead. The money-changer was also

in more recent ancient times silver-smiths and, or, gold-smiths.

Medieval and later

During the fifteenth century the Medici families were required to open banks at foreign

locations in order to exchange currencies to act for textile merchants. During the 17 th (or 18th)

century Amsterdam maintained an active forex market. During 1704 foreign exchange took

place between agents acting in the interests of the nations of England and Holland.

Early modern

During 1880 J.M. do Espírito Santo de Silva (Banco Espírito e Comercial de Lisboa) applied

for and was given permission to begin to engage in a foreign exchange trading business. 1880

is considered by one source to be the beginning of modern foreign exchange, significant for

the fact of the beginning of the gold standard during the year.

Modern to post-modern

Before WWII

At the time of the closing of the year 1913, nearly half of the world's forexes were being

performed using sterling. In 1902 there were altogether two London foreign exchange

brokers. In the earliest years of the twentieth century trade was most active in Paris, New

York and Berlin, while Britain remained largely uninvolved in trade until 1914.

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After WWII

After WWII the Bretton Woods Accord was signed allowing currencies to fluctuate within a

range of 1% to the currencies par. In Japan the law was changed during 1954 by the Foreign

Exchange Bank Law, so, the Bank of Tokyo was to become because of this the centre of

foreign exchange by September of that year.

After 1973

In fact 1973 marks the point to which nation-state, banking trade and controlled foreign

exchange ended and complete floating, relatively free conditions of a market characteristic of

the situation in contemporary times began (according to one source), although another states

the first time a currency pair were given as an option for U.S.A. traders to purchase was

during 1982, with additional currencies available by the next year.

On 1 January 1981 the Bank of China allowed certain domestic "enterprises" to participate in

foreign exchange trading. Sometime during the months of 1981 the South Korean

government ended forex controls and allowed free trade to occur for the first time. During

1988 the countries government accepted the IMF quota for international trade.

According to the Bank for International Settlements, as of April 2010, average daily turnover

in global foreign exchange markets is estimated at $3.98 trillion, a growth of approximately

20% over the $3.21 trillion daily volume as of April 2007. Some firms specializing on

foreign exchange market had put the average daily turnover in excess of US$4 trillion.

The $3.98 trillion break-down is as follows:

Particulars Amount In $

Spot transations 1.490 trillion

Outright forwards $475 billion

Foreign exchange swaps 1.765 trillion

Currency swaps 43 billion

Options and other products 207 billion

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HISTORY OF FOREIGN EXCHANGE MARKET WITH REFRENCE TO

INDIAN CAPITAL MARKET

The forex trading history of India dates back to 1978, when reserve bank of India took a step

towards allowing the banks to undertake intra-day trading in foreign exchange. It is during

the period of 1975-1992 when reserve bank of India, officially determined the exchange rate

of rupee according to the weighted basket of currencies with the significant business partners

of India. But it needs to be mentioned that there are too many restrictions on these banks

during this period for trading in the forex market.

The introduction of the open market policy in the year 1991 and implementation of the new

economic policy by the govt. of India brought a comprehensive change in the Forex market

of India. It is during the month of July 1991, that the rupee undergone a twofold downward

adjustment and this was in line with inflation differential to ensure competitiveness in

exports. Then as per the recommendation of a high level committee set up to review the

balance of payment position, the liberalized exchange rate management system or the lerms

was introduced in 1992. The method of dual exchange rate mechanism that was part of the

terms also came into effect 1993. It is during this time that uniform exchange rate came into

effect and that started demand and supply controlled exchange rate regime in Indian.

It was the report and recommendations of the expert group on foreign exchange, formed to

judge the forex market in India that actually helped to widen the forex trading practices in the

country. As per the recommendations of the expert committee, reserve bank of India and the

government took so many significant steps that ultimately gave freedom to the banks in many

ways. Apart from the banks corporate bodies were also given certain relaxation that also

played an instrumental role in spread of forex trading in India.

It is during the year 2008 that Indian forex market has seen a great advancement that took the

Indian forex trading at par with the global forex markets. it is the introduction of future

derivative segment in forex trading through the national stock exchange (NSE) and MCX

stock exchange (MCX-SX). this step not only increased the Indian forex market volume too

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many folds also gave the individual and retail investor a chance to trade at the forex market,

that was till this time remained a forte of the banks and large corporate.

Indian forex market got yet another boost recently when the SEBI and Reserve bank of India

permitted the trade of derivative contract at the leading stock exchanges NSE and MCX for

three new currency pairs. In its recent circulars reserve bank of India accepting the proposal

of SEBI, permitted the trade of INR-GBP (Indian rupee and Great Britain pound), INR-EUR

(Indian rupee and Euro) and INR-YEN (Indian rupee and Japanese yen). This was in addition

with the existing pair of currencies that is US$ and INR. From inclusion of these three

currency pairs in the Indian forex circuit the Indian forex scene is expected to boost even

further as these are some of the most widely traded currency pairs in the world.

REGULATORY AUTORITIES

The role of financial regulatory bodies or agencies is to control the financial markets by

making the regulations and to see that are followed by the financial companies. These

regulations are meant to have proper processes for smooth running and to avoid the scams

and unethical practices to protect the investors. These regulatory agencies are country or

economic zone dependent and could be governmental or independent. To protect the

investments it is important to check whether the regulatory status of the broker in your

country.

International organizations:

EU Commission

Ernst & Young (E&Y)

Financial Markets Association (ACI)

KPMG

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Regulatory Authorities of major countries

Country Regulatory

IndiaSecurities And Exchange Board Of India SEBI

Reserve Bank Of India RBI

AustraliaAustralian Securities and Investment Commission (ASIC)

International Financial Services Commission (IFSC)

Canada

British Columbia Securities Commission (BCSC)

Canadian Investor Protection Fund (CIPF)

Financial Transactions and Reports Analysis Center of Canada (FINTRAC)

Investment Industry Regulatory Organization of Canada (IIROC)

Ontario Securities Commission (OSC)

Dubai, UAE

Dubai Multi Commodities Centre (DMCC)

Dubai Gold & Commodities Exchange (DGCX)

Dubai Financial Services Authority (DFSA)

Emirates Securities and Commodities Authority (SCA)

United States

Commodities and Futures Trading Commission (CFTC)

Financial Industry Regulatory Authority (FINRA)

National Futures Association (NFA)

New York Stock Exchange (NYSE)

Office of the Comptroller of the Currency (OCC)

US Securities and Exchanges Commission (U.S. SEC)

Chicago Board of Trade (CBOT)

Securities Investor Protection Corporation (SIPC)

Russia FFMS in Russia (FCFR)

France Autorite des marches financiers (AMF)

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http://www.amf-france.org/

http://www.ffms.ru/

http://www.sipc.org/

http://www.cmegroup.com/

http://www.sec.gov/

http://www.occ.treas.gov/

http://www.nyse.com/

http://www.nfa.futures.org/

http://www.finra.org/

http://www.cftc.gov/

http://www.sca.ae/english

http://www.dfsa.ae/

http://www.dgcx.ae/

http://www.dmcc.ae/

http://www.osc.gov.on.ca/

http://www.iiroc.ca/

http://www.fintrac.gc.ca/

http://www.cipf.ca/

http://www.bcsc.bc.ca/

http://www.ifsc.gov.bz/

http://www.asic.gov.au/

CHAPTER 2

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NEED OF THE STUDY

Till date there has not been any perfect model to predict the volatility present in the

Forex market because of the interdependent factors increasing the complexity of the Forex

market. There is immense need to manage the risk effectively and efficiently. Going through

the vast literature on this topic, we found

1. To measure the volatility of various currencies like GBP-INR, JPY-INR, USD-INR,

EURO-INR.

2. The need to identify which Currency is more volatile.

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REVIEW OF LITERATURE

1. Bekaert (1995) analyzes the time variation in conditional means and variances of

monthly and quarterly excess dollar returns on Eurocurrency investments. All results

are based on a vector auto regression with weekly sampled data on exchange rate

changes and forward premiums of three currencies. Both past exchange rate changes

and forward premiums predict future forward market returns. Moreover, past forward

premium volatilities predict the volatility of exchange rates.

2. Bertram (2006) says that the second order properties of financial data, such as

volatility and correlation, have been the focus many recent studies investigating the

presence of long-memory, power-law tails, non-stationary and scaling behavior in

financial data. It is becoming increasingly apparent from these studies that time

dependence and non-stationary are major features of financial data.

3. Johnson (2002) introduced a model to explore the connection between realized

trends and changes in volatility. Foreign exchange returns exhibit the surprising and

consistent property that volatility increases when trends continue and decreases when

they reverse. Equivalently, the volatility spot covariance, and hence finite-horizon

skewness, behaves like a lagged momentum indicator.

4. Vergni and Vulpiani (1999) have shown the presence of long term anomalies

like the structure functions and a generalization of the usual correlation analysis in the

foreign exchange market. They say that the available information strongly depends on

the kind of investment the speculator has in mind.

5. Zumbach (2002) introduces a new family of processes that include the long

memory (power law) in the volatility correlation. This is achieved by measuring the

historical volatility on a set of increasing time horizons and by computing the

resulting effective volatility by a sum with power law weights.

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6. Hodrick (1992, 1993) deduced that the vector auto regressive approach as several

advantages over the by-now standard method of using overlapping high-frequency

data on monthly or quarterly variable estimates of the conditional variance of monthly

and quarterly forward-market returns. It is well known that the forward rate is not an

unbiased predictor of the future spot rate. One implication of the vast literature on the

subject is that returns from investing in the forward market are predictable by the

forward premium as shown in the research work of Bekaert.

7. Solano (2004) says that modeling the unconditional distribution of returns on

exchange rate and measuring its tails area are issues in the finance literature that have

been studied extensively by parametric and non-parametric estimation procedures.

However, a conflict of robustness is derived from them because the time series

involved in this process are usually fat tailed and highly peaked around the center.

8. Figlewaski (1981) argued that speculation in the derivatives market is transmitted

to the underlying spot markets. The speculation produces a net loss with some

speculators gaining (and others loosing), thereby destabilize the market. Uninformed

speculative traders increase price volatility by interjecting noise to a market with

limited liquidity. The inflow and existence of the speculators in the derivatives

market produces destabilization forces, which creates undesirable bubbles.

9. Clifton (1985) found a strong positive correlation between futures trading and

exchange rate volatility measured by the spread between the daily high and low

exchange rates for Deutsche marks, Swiss franc, Canadian dollars, and Japanese yen.

Grammatikos and Saunders (1986) investigated British pound, Canadian dollar,

Japanese yen, Swiss franc and Deutsche mark foreign currency futures traded on the

International Monetary Market over the period of 1978-1983 and found that there

exists a bidirectional causal relationship between volume and price variability in

futures market transactions.

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10. Kumar and Seppi (1992) and Jarrow (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.

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RESEARCH GAP

Most of the research paper includes the research done on volatility between the currency pair

INR and USD for the Indian foreign exchange market. There are very less number of

research done on other currencies like Euro, British Pound, Yen, etc with the Indian rupee.

This signifies that the most common currency used to measure volatility with INR is US

Dollars.

Our Research would include the measure of volatility with 4 currencies:-

1. INR- USD

2. INR- EURO

3. INR-GBP

4. INR- JPY

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CHAPTER 3

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RESEARCH METHODOLOGY

Research methodology is a way to systematically solve the research problem. It may be

understood as a science of studying how research is done scientifically. It is necessary for the

researcher to know not only the research methods/techniques but also methodology.

Researchers not only need to know how to develop certain indices or tests, how to calculate

the mean, the mode, the median or the standard deviation or chi square, how to apply

particular research techniques, but they also need to know which of these methods or

techniques are relevant or not, and what they mean and indicate and why. Researchers also

need to understand the assumptions underlying various techniques and they need to know the

criteria by which they can decide that certain techniques and procedures will be applicable to

certain problems.

Hence, when we talk of research methodology we not only talk about research methods but

also consider the logic behind the methods we use in context of our research study and

explain why we are using a particular method or technique and why we are not using others

so that research results are capable of being evaluated either by the researcher himself or by

others.

A. Objective of the study

To find out the volatility of four major currencies i.e.US Dollar, EURO, Britain

Pound and Japanese Yen that traded mostly in world and has allowed trading in

Indian Forex market

To measure the volatility distribution in these four currencies in Indian FOREX

market.

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B. Hypothesis of this study

Hypothesis is being tested for 5 percent of significance level.

1. Ho: There is not significance difference on volatility of selected currency in Forex

market.

2. Ha: There is significance difference on volatility of selected currency in Forex

market.

Sub parameter of the Hypothesis:-

1. USD-INR (Bid, Ask, Mid)

2. JPY-INR (Bid, Ask, Mid)

3. EURO-INR (Bid, Ask, Mid)

4. GBP-INR (Bid, Ask, Mid)

C. Period of the Study

This will define how much time we will take to complete this research work which is

related to volatility in Indian Forex market.

Here we have estimated that it will take 45 days to carry out research work along with

academic term.

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D. Sample Design

Sample Universe

The sampling universe is the total number of items/events from which you can select

or sample for statistical analysis and description. There are almost 182 different

currencies in the world.

Common Currencies traded in the FX Market.

Currency Name Symbol

US Dollar USD

Pound GBP

Swiss Franc CHF

Japanese Yen JPY

Canadian Dollar CAD

Euro EUR

Australian Dollar AUD

New Zealand Dollar NZD

Sample Unit

Sample Unit are the constituents of the elements i.e. the number of currencies

in our research. In our research we have taken 4 currencies to measure

volatility with Indian rupees. The 4 currencies in our research includes:-

1. USD- US Dollars

2. EUR- EURO

3. GBP- German British Pound

4. JPY- Japanese Yen

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Sample Period

Sample Period means the time taken of the sample in the research for

measuring the volatility. Here, in our research we have taken the secondary

data of past two years of the volatility. The 2 years i.e. 24 months include:-

- 1st January 2011 to 31st December 2011 (12 months)

- 1st January 2012 to 31st December 2012 (12 months)

E. Type of Research

We have used secondary data in our project so we have followed historical method of

collecting the information. There are 2 types of research:

1. Qualitative research

Qualitative research is a method of inquiry employed in many different

academic disciplines, traditionally in the social sciences, but also in market research

and further contexts. Qualitative researchers aim to gather an in-depth understanding

of human behavior and the reasons that govern such behavior. The qualitative method

investigates the why and how of decision making, not just what, where, when. Hence,

smaller but focused samples are more often needed than large samples.

2. Quantitative research

Quantitative research refers to the systematic empirical investigation of social

phenomena via statistical, mathematical or computational techniques. The objective

of quantitative research is to develop and employ mathematical models, theories

and/or hypotheses pertaining to phenomena. The process of measurement is central to

quantitative research because it provides the fundamental connection between

empirical observation and mathematical expression of quantitative relationships.

Our project includes the quantitative research because we have taken historical data

and carried out research based on the statistical data and other mathematical

information.

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F. Data Collection

There are two sources of data i.e.

1. Primary data

2. Secondary data

Primary data collection uses surveys, experiments or direct observations.

Secondary data collection may be conducted by collecting information from a

diverse source of documents or electronically stored information.

Here we have used Secondary data, like currency rates and all other

information are collected through referring websites and different research paper.

G. Tools and Techniques for Data Analysis

Here we find the Skewness and Kurtosis with the help of descriptive statistics tool, of

the given currencies to find volatility with the help of some tools like standard deviation and

the variance of the market.

Here we will use JARQUE - BERA TEST. The Jarque-Bera test is used to check

hypothesis about the fact that a given sample .x^ is a sample of normal random variable with

unknown mean and dispersion. As a rule, this test is applied before using methods of

parametric statistics which require distribution normality.

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H. Limitation of the Study

Exchange rate currencies chosen for the above study is based not on the importance

of the currency but on the volumes traded in the foreign exchange market in whole

world. And are mainly allowed in India.

Sometimes it happens that the finding of volatility may not help the investor to take

decision for choosing best investment plan

I. Future scope of the study

This research will help to know the impact of the behavior of Foreign Exchange rate

Indian forex market.

It will help to find out which currency is having more volatility in Indian forex

market.

It will also help to know whether Indian forex market is much stable or not.

This research will help the Investor to decide in which currency to invest on the basis

of the volatility of the particular currency.

The investor expecting high return will invest in highly volatile currency and investor

wanting less risk will invest with low volatile currency.

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CHAPTER 4

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Analysis and Interpretation

Descriptive Statistics

Descriptive statistics are used to describe the basic features of the data in a study. They

provide simple summaries about the sample and the measures. Together with simple graphics

analysis, they form the basis of virtually every quantitative analysis of data.

Descriptive Statistics are used to present quantitative descriptions in a manageable form. In a

research study we may have lots of measures. Or we may measure a large number of people

on any measure. Descriptive statistics help us to simply large amounts of data in a sensible

way.

Volatility is a measure of how far the current prices of an asset deviate from its average past

prices. Here we measure volatility in Forex market for USD, EURO and YEN by measuring

the mean and the variance in logarithm of change in their daily exchange rate. The greater the

deviation, the greater is the volatility. Volatility can indicate the strength or conviction

behind the price move.

Skewness quantifies how symmetrical the distribution is. A distribution that is symmetrical

has a skewness of 0. If the skewness is positive, that means the right tail is 'heavier' than the

left tail. If the skewness is negative, then the left tail of the distribution is dominant.

Kurtosis quantifies whether the shape of the data distribution matches the Gaussian

distribution. A Gaussian distribution has a kurtosis of 0. A flatter distribution has a negative

kurtosis, and a more peaked distribution has a positive kurtosis. It is sometimes referred to as

the "volatility of volatility."

JARQUE - BERA - The Jarque-Bera test is used to check hypothesis about the fact that a

given sample x^ is a sample of normal random variable with unknown mean and dispersion.

As a rule, this test is applied before using methods of parametric statistics which require

distribution normality. This test is based on the fact that skewness and kurtosis of normal

distribution equal zero. Therefore, the absolute value of these parameters could be a measure

of deviation of the distribution from normal. Using the sample Jarque-Bera statistic is

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calculated: (There n is a size of sample), then p-value is computed using a table of

distribution quantiles.

CROSS RATES OF USD/INR

End Date USD/INR BID USD/INR ASK USD/INR MID12/31/2012 54.5574 54.7223 54.6399

11/30/2012 54.6891 54.8492 54.7691

10/31/2012 52.8582 53.0416 52.9499

9/30/2012 54.2308 54.4129 54.3219

8/31/2012 55.3555 55.5268 55.4412

7/31/2012 55.1853 55.4268 55.306

6/30/2012 55.8476 56.2372 56.0424

5/31/2012 54.4692 54.8616 54.6654

4/30/2012 52.1835 52.6278 52.4056

3/31/2012 50.6989 51.1297 50.9143

2/29/2012 49.4113 49.7803 49.5958

1/31/2012 51.909 52.3554 52.1322

12/31/2011 53.0675 53.4738 53.2707

11/30/2011 50.7983 51.1129 50.9556

10/31/2011 49.5209 49.9493 49.7351

9/30/2011 47.6179 48.0485 47.8332

8/31/2011 45.2809 45.6663 45.4736

7/31/2011 44.556 44.9391 44.7475

6/30/2011 45.1789 45.5486 45.3638

5/31/2011 44.882 45.2983 45.0901

4/30/2011 44.6238 44.9972 44.8105

3/31/2011 45.3763 45.7102 45.5433

2/28/2011 45.5144 45.8936 45.704

1/31/2011 45.6407 46.0777 45.8592

Page | 31

01/01/2011

01/03/2011

01/05/2011

01/07/2011

01/09/2011

01/11/2011

01/01/2012

01/03/2012

01/05/2012

01/07/2012

01/09/2012

01/11/20120

10

20

30

40

50

60

USD/INR BID USD/INR Ask USD/INR MID

Axis Title

Rate

USD/INR ANALYSIS

Particulars Bid Rates Ask Rates Mid RatesMean 50.1438 50.4869 50.3154

Standard Error 0.8448 0.8343 0.8395

Standard Deviation 4.1389 4.0874 4.1129

Sample Variance 17.1310 16.7073 16.9167

Kurtosis -1.6462 -1.6403 -1.6436

Skewness -0.1322 -0.1478 -0.1402

Sum 1203.4534 1211.6871 1207.5703

Count 24 24 24

JB TEST (Calculated value)

Page | 32

Bid 21.65754

Ask 21.62065

Mid 21.64225

BID ASK MID

Period Average

50.143

9 50.487 50.3154

Period Low 44.556 44.9391 44.7475

Period High

55.847

6 56.2372 56.0424

Analysis and Interpretation:

Skewness and kurtosis values for monthly in USD/INR exchange return suggest that it far

from the normal distribution which ideally should be 0 in case of normal distribution. So

researcher found that there is high volatility and volatility also affected funds flow in

international market.

The above table shows difference on average, low and high of Bid, Ask and Mid rates on

USD/INR. Here table also indicated that Bid had same difference (Low and High) but more

difference realized on Ask and Mid. Currency market was continuous fluctuating as per

demand and supply of that particular currency.

The value of Jarque Bera = 21.65 is clearly greater than the critical value of 5.99 for 95% for

a =.05 for 2 degrees of freedom obtained from Chi Square Distribution Table. This means

that (.he null hypothesis that the there is no significance difference on volatility of USD/INR

is normally distributed for the time period between 2011 to 2012 is rejected for the given

confidence interval of 95% and we accept the alternate hypothesis that the returns of

USD/INR have significance difference on volatility of USD/INR.

Page | 33

CROSS RATES OF GBP/INR

End Date GBP/INR BID GBP/INR ASK GBP/INR MID12/31/2012 87.9721 88.26 88.116

11/30/2012 87.3088 87.5801 87.4445

10/31/2012 84.9799 85.2911 85.1355

9/30/2012 87.2486 87.5594 87.404

8/31/2012 86.939 87.2243 87.0816

7/31/2012 86.0822 86.4788 86.2805

6/30/2012 86.7943 87.424 87.1091

5/31/2012 86.8622 87.5108 87.1865

4/30/2012 83.4875 84.2248 83.8561

3/31/2012 80.2152 80.9182 80.5667

2/29/2012 78.0526 78.6579 78.3552

1/31/2012 80.4665 81.1859 80.8262

12/31/2011 82.7636 83.4216 83.0926

11/30/2011 80.3799 80.9005 80.6402

10/31/2011 78.0035 78.7053 78.3544

9/30/2011 75.3122 76.0147 75.6634

8/31/2011 74.116 74.7737 74.4448

7/31/2011 71.9209 72.5623 72.2416

6/30/2011 73.3178 73.9387 73.6283

5/31/2011 73.4054 74.1115 73.7585

4/30/2011 72.9435 73.5774 73.2605

3/31/2011 73.3336 73.893 73.6133

2/28/2011 73.3482 73.9809 73.6646

1/31/2011 71.9096 72.6218 72.2657

Page | 34

01/01/2011

01/03/2011

01/05/2011

01/07/2011

01/09/2011

01/11/2011

01/01/2012

01/03/2012

01/05/2012

01/07/2012

01/09/2012

01/11/20120

10

20

30

40

50

60

70

80

90

100

GBP/INR BID GBP/INR ASK GBP/INR MID

Axis Title

Axis

Title

GBP/INR ANALYSIS

Particulars Bid Rates Ask Rates Mid RatesMean 79.8817 50.4869 50.3154

Standard Error 1.2145 0.8343 0.8395


Sample Variance 35.4046 16.7073 16.9167

Kurtosis -1.6775 -1.6403 -1.6436

Skewness 0.0098 -0.1478 -0.14028

Sum 1917.1631 1211.6871 1207.5703

Count 24 24 24


Page | 35

Bid 21.87921

Ask 21.62065

Mid 21.64225

BID ASK MID

Period Average 79.8818 80.4507 80.1662

Period Low 71.9096 72.5623 72.2416

Period High 87.9721 88.26 88.116


Skewness and kurtosis values for monthly in GBP/INR exchange return suggest that it is far





GBP/INR. Here table also indicated that Bid had same difference (Low and High) but more

difference realized on Ask and Mid.


a = .05 for 2 degrees of freedom obtained from Chi Square Distribution Table. This means

that (.he null hypothesis that the there is no significance difference on volatility of GBP/INR



GBP/INR have significance difference on volatility of GBP/INR.

Page | 36

CROSS RATES OF EURO/INR

End Date EUR/INR BID EUR/INR ASK EUR/INR MID12/31/2012 71.501 71.7296 71.6153

11/30/2012 70.1525 70.37 70.2612

10/31/2012 68.5494 68.7995 68.6744

9/30/2012 69.6926 69.9394 69.816

8/31/2012 68.551 68.7752 68.6631

7/31/2012 67.9225 68.2372 68.0798

6/30/2012 69.9972 70.5086 70.2529

5/31/2012 69.9146 70.4396 70.1771

4/30/2012 68.718 69.3276 69.0228

3/31/2012 66.9831 67.57 67.2766

2/29/2012 65.3215 65.8295 65.5755

1/31/2012 66.9152 67.5137 67.2145

12/31/2011 69.9451 70.5009 70.223

11/30/2011 68.998 69.4442 69.2211

10/31/2011 67.8428 68.4517 68.1473

9/30/2011 65.6981 66.3109 66.0045

8/31/2011 64.9458 65.522 65.2339

7/31/2011 63.7411 64.3087 64.0249

6/30/2011 64.974 65.5222 65.2481

5/31/2011 64.3583 64.974 64.6662

4/30/2011 64.4152 64.9726 64.6939

3/31/2011 63.5298 64.0134 63.7716

2/28/2011 62.1063 62.6408 62.3736

1/31/2011 60.9479 61.5512 61.2496

Page | 37

01/01/2011

01/03/2011

01/05/2011

01/07/2011

01/09/2011

01/11/2011

01/01/2012

01/03/2012

01/05/2012

01/07/2012

01/09/2012

01/11/201254

56

58

60

62

64

66

68

70

72

EUR/INR BID EUR/INR ASK EUR/INR MID

Axis Title

Axis

Title

EURO/INR ANALYSIS

Particulars Bid Ask MidMean 66.9050 67.3855 67.1452

Standard Error 0.5811 0.5654 0.5731


Sample Variance 8.1059 7.6733 7.8843

Kurtosis -0.8051 -0.7696 -0.7878

Skewness -0.3712 -0.4041 -0.3885

Sum 1605.721 1617.2525 1611.4869

Count 24 24 24


Page | 38

Bid 15.03033

Ask 14.86317

Mid 14.95185


Skewness and kurtosis values for monthly in EUR/INR exchange return suggest that it is far





EUR/INR. Here table also indicated that Bid had same difference (Low and High) but more


demand and supply of that particular currency.



that (.he null hypothesis that the there is no significance difference on volatility of EUR/INR



EUR/INR have significance difference on volatility of EUR/INR.

Page | 39

BID ASK MID

Period Average 66.9051 67.3855 67.1453

Period Low 60.9479 61.5512 61.2496

Period High 71.501 71.7296 71.6153

1. CROSS RATES OF JPY/INR

End Date JPY/INR BID JPY/INR ASK JPY/INR MID12/31/2012 0.6524 0.6545 0.6534

11/30/2012 0.6763 0.6784 0.6773

10/31/2012 0.6697 0.6722 0.6709

9/30/2012 0.6934 0.6959 0.6946

8/31/2012 0.7035 0.7058 0.7046

7/31/2012 0.698 0.7012 0.6996

6/30/2012 0.7047 0.7099 0.7073

5/31/2012 0.6829 0.6882 0.6855

4/30/2012 0.6408 0.6466 0.6437

3/31/2012 0.615 0.6204 0.6177

2/29/2012 0.6305 0.6355 0.633

1/31/2012 0.6744 0.6805 0.6774

12/31/2011 0.6816 0.6871 0.6843

11/30/2011 0.6552 0.6596 0.6574

10/31/2011 0.6462 0.6521 0.6491

9/30/2011 0.6196 0.6255 0.6226

8/31/2011 0.5874 0.5928 0.5901

7/31/2011 0.5608 0.5659 0.5634

6/30/2011 0.5615 0.5663 0.5639

5/31/2011 0.5533 0.5587 0.556

4/30/2011 0.5357 0.5405 0.5381

3/31/2011 0.5558 0.5602 0.558

2/28/2011 0.5509 0.5557 0.5533

1/31/2011 0.553 0.5586 0.5558

Page | 40

01/01/2011

01/03/2011

01/05/2011

01/07/2011

01/09/2011

01/11/2011

01/01/2012

01/03/2012

01/05/2012

01/07/2012

01/09/2012

01/11/20120

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

JPY/INR BIDJPY/INR ASKJPY/INR MID

Axis Title

Axis

Title

JPY/INR

Particulars Bid Ask MidMean 0.6292 0.6338 0.6315

Standard Error 0.0117 0.0116 0.0117


Sample Variance 0.0033 0.0033 0.0033

Kurtosis -1.4525 -1.4420 -1.4469

Skewness -0.3141 -0.3267 -0.3208

Sum 15.1026 15.2121 15.157

Count 24 24 24


Page | 41

Bid 20.22027

Ask 20.15916

Mid 20.18694

BID ASK MID

Period Average 0.6293 0.6338 0.6316

Period Low 0.5357 0.5405 0.5381

Period High 0.7047 0.7099 0.7073


Skewness and kurtosis values for monthly in JPY/INR exchange return suggest that it is far





JPY/INR. Here table also indicated that Bid had same difference (Low and High) but more


demand and supply of that particular currency



that (.he null hypothesis that the there is no significance difference on volatility of JPY/INR



USD/INR have significance difference on volatility of JPY/INR.

Page | 42

CHAPTER 5

Conclusion

Page | 43

Here in our Research we can conclude that our primary hypothesis i.e. there is no

significance difference on volatility of selected currency in Forex market, is rejected and our

alternate Hypothesis i.e. There is significance difference on volatility of selected currency in

Forex market, is accepted. Means we can say that all Four Currency having significant

volatility.

We have observed more volatility in EUR/INR pair as it Kurtosis value is higher than other

three pairs. For all the four currencies under this study, we find generally an increasing trend

in volatility.

Page | 44

BIBLIOGRAPHY

Website: -

www.ibfx.com

Page | 45

http://www.ibfx.com/Trade/The-Foreign-Exchange-Market

en.wikipedia.orghttp://en.wikipedia.org/wiki/Foreign_exchange_market

www.forexabode.comhttp://www.forexabode.com/forex-regulatory-bodies

www.sharetipsinfo.comhttp://www.sharetipsinfo.com/global-forex-market-india.html

www.invesopedia.comen.wikipedia.org

www.oanda.comhttp://www.oanda.com/currency/historical-rates/

Research Paper:-

1. RBI Working paper Series WPS (DEPR): 1/2011Title:- An Empirical Analysis of the Relationship Between Currency Futures And Exchange Rates Volatility In IndiaBy-Somnath Sharma

2. Research Journal of Finance and Accounting.ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online)Vol 2, No 9/10, 2011Title: - Measuring the Volatility of Foreign Exchange Market in IndiaBy:- Neeti Khullar Upasna Joshi Sethi

Books:-Research Methodology-Methods and Techniques-Second Edition-By C. R. Kothari

Page | 46

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