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A SUMMER INTERNSHIP PROJECT PRESENTATION ON “A STUDY ON Currency Futures, its features and modus operandi at Arihant capital market Ltd. SUBMITTED TO (Oakbrook Business School) GUJARAT TECHNOLOGICAL UNIVERSITY (MBA PROGRAMME) SUBMITTED BY Saloni Parghi Bhavin Surani [ ENROLLMENT NO.: 148320592087] [ENROLLMENT NO.: 148320592052]

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ASUMMER INTERNSHIP PROJECT PRESENTATION

ON“A STUDY ON Currency Futures, its features and modus

operandi at Arihant capital market Ltd.

SUBMITTED TO (Oakbrook Business School)

GUJARAT TECHNOLOGICAL UNIVERSITY(MBA PROGRAMME)

SUBMITTED BY

Saloni Parghi Bhavin Surani [ ENROLLMENT NO.: 148320592087] [ENROLLMENT NO.:

148320592052]

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INTRODUCTION OF THE INDUSTRY

A financial market is a market in which people trade financial securities, commodities, and other fungible items of value at low transaction costs and at prices that reflect supply and demand. Securities include stocks and bonds, and commodities include precious metals or agricultural goods.

• Capital markets : Commodity, Derivatives, Futures, Insurance, Foreign exchange markets.

• Money markets

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INTRODUCTION OF THE COMPANY

• Services• Online trading• Depository• Portfolio

management system• Advisory Services

• Products• Equity & Derivatives• Mutual funds• IPO• Currency• Commodities

ARIHANT capital markets ltd.

• Established in 1994

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INTRODUCTION OF THE TOPIC

01.08.14

4 Currency: USD, GBP, EURO, JPY• Futures • OptionsFeatures of currency futures:• Contract Size• Quoted and Settle in Indian Rupees• Maturity • Settlement price

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LITERATURE REVIEWRef. Objective Findings Anand and Kaushik (2008)

what motivates the management to use foreign currency derivatives in corporate India

Use of derivatives is hedging the risk (96.1 percent ranked it as the number one objective), arbitrage (55.3 ranked it as number two objective) and price discovery (36.4 percent assigned it rank two and 33.3 percent assigned it rank three). Speculative objective is the least preferred option (62.1 percent assigned rank four).

Sivakumar and Sarkar (2008)

to evaluate the various alternatives available to the Indian corporates for hedging currency exposure

that most Indian firms use forwards and options to hedge their foreign currency exposure.

Nair (2004)   observed that in most of the countries, where currency futures have really flourished, the trading takes place on multiple commodity exchanges, rather than stock exchanges. Besides, since foreign operators – NRIs, FIIs etc. – are barred from participating, the new exchange means the contract can be traded only within India and that too, without involving any outflow of funds.

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OBJECTIVES

• To know about the currency market in India.

• To assess the customer’s perception

• To motivate currency trading among the masses.

• Attributes that drives the retail investors for each asset market.

• Reasons for non-inclination of investors towards. 01.08.14

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Research methodology

Descriptive Research: Data Collection: data collected by questionnaire which is included demographic information and related currency market dataSources of data: Primary data

Sampling size: 200 Questionnaire

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Research methodology

Hypothesis:• Ho : There is a significant relation between

asset market and driving attributes of each asset market

• H1 : There is no significant relation between asset market and driving attributes of each asset market

Statistical tool : • Mean S.D and chi-square

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Limitation:

• As only Ahmedabad was dealt in the survey so it does not represent the view of the total Indian market.

• The sample size was restricted with two hundred respondents.• There was lack of time on the part of respondents.• The survey was carried through questionnaire and the

questions were based on perception.• There may be biasness in information by market participant.• Complete data was not available due to company privacy and

secrecy.• Some people were not willing to disclose the investment

profile.

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Data Analysis and Interpretation

Demographic information

Age :

Below 25 5825-30 4130-35 6935 Above 32Total 200

Age

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Gender

 Gender

Female 61Male 139Total 200

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Profession

ProfessionGovt. Employee 32Grad/Post graduate student 26Others 13Self employed 63Service 66Total 200

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Income

IncomeNo Income 25Rs. 11 lac & above 4Rs. 2.5 lac-Rs. 5 lac 60Rs. 5 lac-Rs. 8 lac 79Rs. 8 lac-Rs. 11 lac 32Total 200

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Q-1 did you ever think of currency derivatives trading as an investment option

or profession?

No , but planning to invest after performing research

113

Never, What's Currency Derivatives 23Yes 64

Total20

0

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Q-2 In which asset markets do you trade?

Commodity 52Mix 15Currency 42Equity 63No Trade 28

Total20

0

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Q-3 Rate you expertise in the asset markets:

Beginner

Expert

Intermediate

Zero

Commodity 40 38 93 29Currency Derivatives 40 24 102 34Equity 26 63 96 15

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Q-4 For which purpose you invest?

Hedging 56  

import export 32

 

No Trade 5  

Speculation

107

 

Total20

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Q-5 what kind of trader best describes you?

Arbitrager

Hedger

no trade

Speculator

Commodity 18 63 34 85Currency Derivatives 13 89 43 55Equity 19 37 28 116

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Q-6 choose the following driving attributes for each asset markets

Arbitrage

Hedging

Market volatility

no trade

Portfolio diversification

Returns

Commodity 15 37 29 28 24 67Currency Derivatives 5 85 13 42 23 32

Equity 39 42 13 39 12 55

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Q-7 why do think Indian retail investors are less inclined towards currency derivatives

trading?

Insignificant

Neutral

Significant

Very Insignificant

very significant

Not enough self-knowledge 49 58 47 40 6Less popular among peers 23 88 35 25 9Lack of govt. Initiatives 26 84 61 9 20

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Q-8 how effective would be the following factors to boost currency derivatives trading

in India?1 2 3 4 5

Through media broadcast 10 13 53 80 44Opportunity to trade in non US currency futures 38 43 63 46 10Relaxation of regulatory framework by SEBI 11 18 61 52 58

Through media

broadcast

Opportunity to

trade

Relaxation in regulation

Mean 3.675 2.735 3.64

S.D 1.04635 1.1582241.1519

7

Rank 1 3 2

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Testing of hypothesis

Hypothesis:• Ho : There is a significant relation between asset

market and driving attributes of each asset market • H1 : There is no significant relation between asset

market and driving attributes of each asset marketCross Tabulation : Driving attributes and asset market

Driving Attributes : Portfolio diversification, returns, arbitrage, market volatility, hedging.

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Cross Tabulation : Driving attributes and Equity

Crosstab Equity      Driving attributes / equity

Total

      Portfolio diversificati

onHedgin

gReturn

sArbitrag

eMarket

VolatilityNo

TradeAsset market

Equity Count 2 17 27 14 4 11 75Expected Count 4.5 15.8 20.6 14.6 4.9 14.6 75.0

% within Asset market 2.7% 22.7% 36.0% 18.7% 5.3% 14.7% 100.0%

Commodity

Count 5 12 11 14 6 4 52Expected Count 3.1 10.9 14.3 10.1 3.4 10.1 52.0

% within Asset market 9.6% 23.1% 21.2% 26.9% 11.5% 7.7% 100.0%

Currency Count 5 13 13 11 3 0 45Expected Count 2.7 9.4 12.4 8.8 2.9 8.8 45.0

% within Asset market 11.1% 28.9% 28.9% 24.4% 6.7% .0% 100.0%

No Trade Count 0 0 4 0 0 24 28Expected Count 1.7 5.9 7.7 5.5 1.8 5.5 28.0

% within Asset market .0% .0% 14.3% .0% .0% 85.7% 100.0%

Total Count 12 42 55 39 13 39 200Expected Count 12.0 42.0 55.0 39.0 13.0 39.0 200.0

% within Asset market 6.0% 21.0% 27.5% 19.5% 6.5% 19.5% 100.0%

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Chi square Tests

Value df Asymp. Sig. (2-sided)Pearson Chi-Square 1.0602 15 .000Likelihood Ratio 101.198 15 .000Linear-by-Linear Association 14.810 1 .000N of Valid Cases 200

Driving attributes * Equity

• Chi square Tab(30.578) > Chi square Cal(1.0602)• So null hypothesis(Hnot) is Accepted so we can say

that there is a significance relation between Equity and driving attributes

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Cross Tabulation : Driving attributes and CurrencyCrosstab

      Driving attributes / Currency

Total      Portfolio

diversification Hedging Returns ArbitrageMarket

VolatilityNo

TradeAsset market

Equity Count 12 30 8 4 6 15 75

Expected Count 8.6 31.9 12.0 1.9 4.9 15.8 75.0

% within Asset market

16.0% 40.0% 10.7% 5.3% 8.0% 20.0% 100.0%

Commodity Count 7 25 12 1 5 2 52

Expected Count 6.0 22.1 8.3 1.3 3.4 10.9 52.0

% within Asset market

13.5% 48.1% 23.1% 1.9% 9.6% 3.8% 100.0%

Currency Count 3 29 12 0 1 0 45

Expected Count 5.2 19.1 7.2 1.1 2.9 9.4 45.0

% within Asset market

6.7% 64.4% 26.7% .0% 2.2% .0% 100.0%

No Trade Count 1 1 0 0 1 25 28

Expected Count 3.2 11.9 4.5 .7 1.8 5.9 28.0

% within Asset market

3.6% 3.6% .0% .0% 3.6% 89.3% 100.0%

Total Count 23 85 32 5 13 42 200

Expected Count 23.0 85.0 32.0 5.0 13.0 42.0 200.0

% within Asset market

11.5% 42.5% 16.0% 2.5% 6.5% 21.0% 100.0%

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Chi square Tests

Driving attributes * Currency

Value Df Asymp. Sig. (2-sided)Pearson Chi-Square 1.1612 15 .000Likelihood Ratio 113.515 15 .000Linear-by-Linear Association 15.654 1 .000N of Valid Cases

200

• Chi square Tab(30.578) > Chi square Cal(1.1612)

• So null hypothesis(Hnot) is accepted so we can say that there is a significance relation between currency and driving attributes

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Cross Tabulation : Driving attributes and Commodity

Crosstab      Driving attributes / Commodity

Total

      Portfolio diversifica

tionHedgi

ngRetur

nsArbitra

ge

Market Volatilit

y

No Trad

eAsset market

Equity Count 13 16 25 8 11 2 75Expected Count 9.0 13.9 25.1 5.6 10.9 10.5 75.0% within Asset market 17.3% 21.3%33.3% 10.7% 14.7% 2.7

%100.0

%Commodity Count 2 11 24 3 10 2 52

Expected Count 6.2 9.6 17.4 3.9 7.5 7.3 52.0% within Asset market 3.8% 21.2%46.2% 5.8% 19.2% 3.8

%100.0

%Currency Count 7 10 17 4 7 0 45

Expected Count 5.4 8.3 15.1 3.4 6.5 6.3 45.0% within Asset market 15.6% 22.2%37.8% 8.9% 15.6% .0% 100.0

%No Trade Count 2 0 1 0 1 24 28

Expected Count 3.4 5.2 9.4 2.1 4.1 3.9 28.0% within Asset market 7.1% .0% 3.6% .0% 3.6% 85.7

%100.0

%Total Count 24 37 67 15 29 28 200

Expected Count 24.0 37.0 67.0 15.0 29.0 28.0 200.0% within Asset market 12.0% 18.5%33.5% 7.5% 14.5% 14.0

%100.0

%

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Chi square Tests

• Chi square Tab(30.578) > Chi square Cal(1.4842)• So null hypothesis(Hnot) is accepted so we can say

that there is a significance relation between commodity and driving attributes

01.08.14

Value df Asymp. Sig. (2-sided)Pearson Chi-Square 1.4842 15 .000

Likelihood Ratio 117.157 15 .000Linear-by-Linear Association 30.313 1 .000

N of Valid Cases 200

Driving attributes * Commodity

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FINDINGS

• The major responders find are male and there are major no. Of age group between 30 to 35 years.

• There is a majority of service class and self-employed class in this research.

• The major no. Of responders are having income of Rs. 5 to 8 lacs.

• From the data we found that major no. Of people are planning to invest in currency futures after performing research.

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FINDINGS

• We have observed from collected data that the major no. Of expertise are intermediate in all asset markets.

• Customers are having negative perception about currency futures.

• The higher no of purposes are speculations in equity market as per collected data.

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Suggestions

• Give more reasons of less inclination of investors

• Boost currency trading by media broadcast

• Remove negative perception about currency

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CONCLUSION

As per our Research and Findings we would like to conclude that There is negative perception about currency in the mind of investors and if we want to boost the currency trading in India we should take a help of media broadcasts but we can’t conclude the reason of the less inclination towards currency trading because people have neutral responses of said reasons. It seems that they are not clear about the reasons or might be they have other reasons of less inclination. We also put hypothesis on the research in which we had proved that there is a significance relation between all asset market and the driving attributes of asset. We are also concluding on the basis of our research that most people prefer equity first.

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BIBLIOGRAPHYBook referred: - Research Methodology by C R KothariReference:• Nair, C.K.G. (2004) ‘Commodity Futures Markets in India: Ready

for Take-off’ Nsenews letter, July 2004.• Kaushik (2008), Use of foreign currency derivates in India IIMB

Management Review, 20(3), July - September, 2008, pp. 324-339• Sivakumar and Sarkar (2008), Corporate Hedging for Foreign

Exchange Risk in India• Dash and Madhava (2008), A study on the impact of currency

fluctuation on the Indian IT Sector(April 15, 2008) Available at SSRN: http://ssrn.com/abstract=1326506 

• Jesswein, Kwok and Floks (1995), Jesswein, Kurt, Chuck C. Y. Kwok, and William Folks, Jr. “Corporate Use of Innovative Foreign Exchange Risk Management Products.” Columbia Journal of World Business (Fall 1995), pp. 70–82.

 Websites:- • www.arihantcapital.com, www.sebi.gov.in, www.nseindia.com,

www.bse.com

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Thank you