mayur ph.d thesis.pdf

“AN IN-DEPTH STUDY OF ORGANISATION ANDWORKING OF DERIVATIVES WITH REFERENCE TO

INDIAN CAPITAL MARKET”

A thesisSubmitted for the Partial Fulfillment of the

Requirement for the Degree of

Doctor of PhilosophyIN

Management

Submitted toGANPAT UNIVERSITY

Submitted by

SHAH MAYUR DASHARATHLALREGISTRATION NO. MM/02/03/07.

Under the Guidance of

PROF. D. M. PESTONJEEEx-Professor

IIMAhmedabad

February 2011

i

PREFACE

Derivatives, today, have become an integral part of the financial system of a country as

well as at international level. They have influenced almost every aspect of capital and

money markets all over the world ranging from investing, raising of funds and managing

the risk.

Due to the globalization and liberalization process initiated by the states all over the

world, the international trade and financial activities have grown in multifold resulting

rising levels of all types of risks for market participants such as market risk, interest rate

risk, foreign exchange risk, inflation risk and price risk. Managing all these risks is

essential and significant to be successful in financial and trading activities. Financial

derivatives like options, futures, forwards and swaps have emerged in the financial

markets to handle and manage such risks. New products and strategies are being

developed at the fast rate in order to cope with changing environment.

Financial markets in India continue to evolve towards growth and efficiency resulting

into a manifold rise in financial activities in depth and width. Market participants,

financial institutions and investors are looking in a different way to play efficiently in the

market. During the mid 1990s, Indian government initiated the process of liberalizing of

the financial market in all sectors specifically opening the market for foreign investment.

As a result, the infrastructure of the financial markets geared to international norms in all

respects. The stock market’s structure and trading in India have gone under a sea change.

Institutionalization of broking activities, modernization, automation of stock exchanges

and entry of foreign institutional investors have opened a multiple options to various

participants in the financial markets.

Options and futures in India commenced from 2000 on National Stock Exchange (NSE)

and Bombay stock exchange (BSE) in stock index futures, stock futures, stock index

options and stock options. It was a welcome step on the part of the government since it

was important in the present environment. This was significant development in the

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history of Indian stock markets. A lot of trading in futures and options segment in Indian

stock market was seen and number of market participants increased phenomenal in a

short period. As a result, awareness about the financial derivative instruments and their

application has increased among the investing people at large. On the other side of this

development was that element of risk and volatility in the stock market has risen.

So the broad objective at the outset was to study derivatives traded in Indian capital

market and acquire understanding about what the investors in India perceive regarding

derivatives. The research present in forthcoming pages aims to capture an understanding

regarding growth and development of capital market in India, major reforms in capital

market, derivatives and their types, features, need for and evolution of derivatives in

India.

The thesis is an endeavor to understand the empirical profile of high net worth individual

investors (HNIs) in Gujarat state and systematically investigate the usage, satisfaction

level, factors considered by investors while investing into derivatives. The research is

intended to assist corporate professional, brokers, policy makers, educationalists,

researchers and all others who would like to understand further about Indian capital

market and derivatives.

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ACKNOWLEDGEMENT

Derivatives is a newer area and the challenging task of conducting research in this area

would have been difficult for me without the support of all those who helped me directly

or indirectly in successfully completing it.

I am indebted to Prof. (Dr.) D. M. Pestonjee for being a supportive guide. He motivated

me to undertake this research work, guided through this process and helped me focus the

study. His skills, as a researcher and guide helped me overcome all the hurdles. Without

his constant support and encouragement I would not have been able to complete the

research work successfully.

I owe a debt of gratitude to Prof. Mahendra Sharma, Dean, FMS, Ganpat University for

his moral support and motivation.

I wish to thank the industry people, who supported me a lot for my primary research. A

special thanks to Mr. Tejas Shah, India Infoline, Ahmedabad; Mr. Jagrut patel, Anagram

Equity, Ahmedabad; Mr. B. V. Shah, Angel Broking., Rajkot; Mr. Satish Shah, Angel

Broking., Surat; Mr. Suresh Patel, Rathi Broking ltd., Baroda.

I am thankful to Dr. Akash Patel, Dr. Narayan Baser, Dr. Parag Sanghani for their

continuous help during my research work. I am thankful to Dr. S. O .Junare, National

Institute of Cooperative Management, Gandhingar for their continuous help during my

research work.

I would also like to thank my friend Mr. Amit A. Patel at V. M. Patel Institute of

Management for providing valuable support to me during the course of research.

I would like to thank all my family members, my father Dashrathlal B. Shah, my mother

Smt. Pushpaben, and my wife Ankita for their love, blessings and moral support through

out my research work. I give my special thanks to my wife without whose sacrifice and

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constant support this thesis would not have seen the light of the day.

Thank you all for being there when I needed someone to talk to and for your keen interest

in my development.

At last, I thank the one and all, for the divine blessings.

Mayur Shah

v

DECLARATION BY CANDIDATE

This thesis titled “AN IN-DEPTH STUDY OF ORGANIZATION & WORKING OF

DERIVATIVES WITH REFERENCE TO INDIAN CAPITAL MARKET” is

submitted in fulfillment of the requirements for the award of the degree of Doctor of

Philosophy (Ph.D.) in Management to Ganpat University, Mehsana. I declare that this

thesis is based on my original work except for quotations and citations which have been

duly acknowledged. I also declare that this thesis has not been previously or concurrently

submitted either in whole or in part, for any other qualification to Ganpat University or

other institutions.

Date:

Place: Ganpat University (Shah Mayur D.)

vi

CERTIFICATE OF GUIDE

This is to certify that this thesis titled “AN IN-DEPTH STUDY OF ORGANIZATION

& WORKING OF DERIVATIVES WITH REFERENCE TO INDIAN CAPITAL

MARKET” submitted by Shah Mayur Dasharathlal, at Faculty of Management Studies,

Ganpat University, Mehsana is the bonafide work completed under my supervision and

guidance for the fulfillment of the requirement for the award of the degree of Doctor of

Philosophy (Ph.D.) in Management.

Date:

Place: Ganpat University (Prof. D. M. Pestonjee)

vii

CONTENTS

Preface I

Acknowledgement III

Declaration by Candidate V

Certificate of Guide VI

List of Tables XI

List of Figures XII

CHAPTER 1 INTRODUCTION TO THESIS 1

1.1 Background and Justification to the Research 2

1.2 Capital Market of India: Introduction and Overview 4

1.2.1 Financial System in India 4

1.2.2 Financial Intermediaries 5

1.2.3 Financial Instruments 6

1.2.4 Financial Services 7

1.2.5 Financial Market 7

1.2.6 Money Market 8

1.2.7 Capital Market 8

1.2.8 Functions of Capital Market 9

1.2.9 Primary Market 13

1.2.10 Secondary Market 15

1.3 Developments and Major Reforms in Indian Capital Market 22

1.4 Outline of the Thesis 25

CHAPTER 2 DERIVATIVES – INTRODUCTION AND OVERVIEW 27

2.1 An Introduction 28

2.2 History of Derivatives 28

2.3 Need for Derivatives in India 32

2.4 Evolution of Derivatives in India 33

2.5 Major Recommendations of Dr. L. C. Gupta Committee 36

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2.6 Factors Contributing To the Growth of Derivatives 40

2.7 Benefits of Derivatives 43

2.8 Definition of Financial Derivative 44

2.9 Features of Financial Derivative 47

2.10 Types and Classifications of Derivatives 50

2.11 Uses of Derivatives 52

2.12 Critique of Derivatives 53

2.13 Myths about Derivatives 57

2.14 Emerging Structure of Derivatives Markets in India 66

2.15 Categories of Derivatives Traded in India. 67

2.16 Equity Derivatives 68

2.17 Derivative Trading at NSE and BSE 73

2.18 Futures and Options as Derivative Instruments & Its Application. 77

CHAPTER 3 DERIVATIVES –LITERATURE REVIEW 119


3.2 Stabilization Arguments 129

3.3 Destabilization Arguments 130

3.4 Investors’ Perceptions about Derivatives 135

CHAPTER 4 RESEARCH METHODOLOGY 140


4.2 Objective of the Study 141

4.3 Hypothesis of the Study 141

4.4 Scope of the Study 141

4.5 Research Methodology 142

CHAPTER 5 DATA ANALYSIS AND RESEARCH FINDINGS. 146

5.1 Details of the Investors Surveyed 147

5.2 Hypothesis Testing and Analysis of Variance 153

5.2.1 Findings 163

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5.3 Factor Analysis 173

5.3.1 An introduction 173

5.3.2 Factor Analysis Process 174

5.3.3 Conducting Factor analysis for Perceptions of Investors

- A Detailed Explanation 176

5.3.3.1 Findings 185

5.3.4 Conducting Factor analysis on Factors to be considered

while Investing into Derivatives 186


5.3.4.2 Linking Factor Analysis Findings with Demographic factor 196

5.4 Cluster Analysis 197

5.4.1 An introduction 197

5.4.2 Cluster Analysis Process 197

5.4.3 Conducting Cluster Analysis for Various Perception on Growth of

Derivatives in India: A Detailed Explanation 199


5.4.4 Conducting Cluster Analysis on

Various Perceptions about Derivatives: A Detailed Explanation 213


CHAPTER 6 SUMMARY AND CONCLUSIONS 227


6.2 Scope of the Study 228

6.3 Data Collection and Research Methodology 229

6.4 Emergence of Derivatives as an Important Segment in Indian Capital Market 229

6.5 Conclusions related to Test of Differences 230

6.6 Conclusions related to Factor Analysis 233

6.7 Conclusions related to Cluster Analysis 238

6.8 Limitations of the Study 240

6.9 Directions for Further Research 240

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BIBLIOGRAPHY 242

ANNEXURE No. 1 248

ANNEXURE No. 2 258

ANNEXURE No. 3 260

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LIST OF TABLES

Table 1.1: Market Participants in Securities Market 12

Table 1.2: Mobilization of Resource from Primary Market 15

Table 1.3: Turnover on all Exchanges 18

Table 1.4: Stock Market Indicators 21

Table 2.1: Evolution of Derivatives 34

Table 2.2: Business Growth in Derivatives segment 68

Table 2.3: Buy Calls and Sell Puts 108

Table 2.4: Sell calls and Buy Puts 111

Table 2.5: Bull Spread 114

Table 2.6: Bear Spread 117

Table 5.1: City wise details 148

Table 5.2: Age wise details 148

Table 5.3: Gender wise details 149

Table 5.4: Marital Status 149

Table 5.5: Occupation wise details 149

Table 5.6: Income profile 149

Table 5.7: Occupation 150

Table 5.8: Proportion of Investment into Derivatives 150

Table 5.9: Percentage of Income available for derivative 151

Table 5.10: Purpose of investment 151

Table 5.11: Types of contracts 151

Table 5.12: Education profile of investors 152

Table 5.13: Contract period of trading 152

Table 5.14 Descriptives related to On-way ANOVA 154

Table 5.15 F test and Significance values in One-Way ANOVA 159

Table 5.16: Case Processing Summary and Reliability Statistics 177

Table 5.17: KMO and Bartlett's Test 177

Table 5.18: Communalities 180

Table 5.19: Total Variance Explained 182

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Table 5.20: Rotated Component Matrix(a) 183

Table 5.21: Final Rotated Component Matrix with variable name 184

Table 5.22 Reliability Statistics 186

Table 5.23: KMO and Bartlett's Test 187

Table 5.24: Communalities – Principal Component Method 189

Table 5.25: Total Variance Explained and Eigenvalues 191

Table 5.26: Rotated Component Matrix 192

Table 5.27: Final rotated matrix with variable name 194

Table 5.28: Agglomeration Schedule 200

Table 5.29: Initial Cluster Centers 205

Table 5.30: Final Cluster Centers 206

Table 5.31 Number of Cases in each Cluster 206

Table 5.32: Cluster Membership 206

Table 5.33: Agglomeration Schedule – Ward’s Procedure 213

Table 5.34: Initial Cluster Centers – Non Hierarchical Method 218

Table 5.35: Final Cluster Centers - Non Hierarchical Method 219

Table 5.36: Number of Cases in each Cluster 220

Table 5.37: Cluster Membership- Non Hierarchical Method 220

Table 6.1: List of Hypothesis 228

LIST OF FIGURES

Figure 2.1: Types of Derivatives 51

Figure 2.2: Types of Derivatives 51

Figure 2.3: Payoff for buyer of futures 86

Figure 2.4: Payoff for seller of futures 87

Figure 2.5: Variation of basis over time 91

Figure 2.6: Payoff for investor who went Long Nifty at 2220 99

Figure 2.7: Payoff for buyer of call option 100

Figure 2.8: Payoff profile for writer of call options: Short call 101

Figure 2.9: Payoff for buyer of put option 102

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Figure 2.10: Payoff for writer of put option 103

Figure 2.11: Payoff for writer of put options at various strikes 109

Figure 2.12: Payoff for seller of call option at various strikes 112

Figure 2.13: Payoff for buyer of put options at various strikes 113

Figure 2.14: Payoff for a bull spread created using call options 114

Figure 2.15: Payoff for a bear spread created using call options 117

Figure 5.1: ANOVA Process 153

1

CHAPTER – 1

INTRODUCTION TO THE THESIS

1.1 Background and Justification to the Research

1.2 Capital Market of India: Introduction and Overview

1.2.1 Financial System in India

1.2.2 Financial Intermediaries

1.2.3 Financial Instruments

1.2.4 Financial Services

1.2.5 Financial Market

1.2.6 Money Market

1.2.7 Capital Market

1.2.8 Functions of Capital Market

1.2.9 Primary Market

1.2.10 Secondary Market

1.3 Developments and Major Reforms in Indian Capital Market

1.4 Outline of the Thesis

2

1.1 BACKGROUND AND JUSTIFICATION TO THE RESEARCH

Starting from a controlled economy, India has moved towards a world where prices

fluctuate every day. The introduction of risk management instruments in India gained

momentum in the last few years due to liberalisation process and Reserve Bank of India’s

(RBI) efforts in creating currency forward market. Derivatives are an integral part of

liberalisation process to manage risk. NSE gauging the market requirements initiated the

process of setting up derivative markets in India. In July 1999, derivatives trading

commenced in India1

In practice, some foreign investors also invest in Indian markets by issuing Participatory

Notes to an off-shore investor. Among exchange-traded derivative markets in Asia, India

was ranked second behind S. Korea for the first quarter of 2005. How about China, with

who India is frequently compared in other respects? China is preparing to develop its

derivatives markets rapidly. It has recently entered into joint ventures with the leading

U.S. futures exchanges. It has taken steps to loosen currency controls, and the Central

Bank has allowed domestic and foreign banks to trade yuan forward and swaps contracts

on behalf of clients. However, unlike India, China has not fully implemented necessary

reforms of its stock markets, which is likely to hamper growth of its derivatives markets.

Indian market has equalled or exceeded many other regional markets. While the growth is

being spearheaded mainly by retail investors, private sector institutions and large

corporations, smaller companies and state-owned institutions are gradually getting into

the act. Foreign brokers such as JP Morgan Chase are boosting their presence in India in

reaction to the growth in derivatives. The variety of derivatives instruments available for

trading is also expanding.

There remain major areas of concern for Indian derivatives users. Large gaps exist in the

range of derivatives products that are traded actively. In equity derivatives, NSE figures

show that almost 90% of activity is due to stock futures or index futures, whereas trading

in options is limited to a few stocks, partly because they are settled in cash and not the

1 Susan, Thomas (ed), Derivative Markets in India, (New Delhi, Tata McGraw-Hill 2003), p. 15

3

underlying stocks. Exchange-traded derivatives based on interest rates and currencies are

virtually absent.

The past decade has witnessed the multifold growth in the volume of international trade

and business due to the wave of globalization and liberalization all over the world. As a

result, the demand for the international money and financial instruments increased

significantly at the global level. In this respect, changes in the interest rates, exchange

rates, and stock market prices at the different financial markets have increased the

financial risks to the corporate world. Adverse changes have even threatened very

survival of the business world. It is, therefore, to manage such risks, the new financial

instruments have been developed in the financial markets, which are also popularly

known as financial derivatives.

As Indian derivatives markets grow more sophisticated, greater investor awareness will

become essential. NSE has programmes to inform and educate brokers, dealers, traders,

and market personnel. In addition, institutions will need to devote more resources to

develop the business processes and technology necessary for derivatives trading.

A numbers of theoretical and empirical studies have been done on the impact of the

introduction of derivatives in the stock markets on the stock return volatility. The studies

are concerned with both the developed as well as developing countries. There are two

sets of views according to the theoretical as well as empirical findings. One is of the view

that introduction of derivatives has increased the volatility and market performance,

through forwarding its speculative roles and the other view is that the introduction of

derivatives has reduced the volatility in the stock market thus increasing the stability of

the stock market.

There is lot of things remain unexplored in India so far as derivatives are concerned, this

research thesis focuses more on investor’s perceptions about derivatives in India. This

research can be justified due to its theoretical and practical contributions to the body of

knowledge. The present research makes a significant contribution in terms of

4

understanding derivatives and perceptions of investors regarding derivatives across major

cities of Gujarat.

The value of this study will be justified by the empirical research that will attempt to

make an important contribution to the body of knowledge and the literature in the area of

derivatives and perceptions of investors with regard to satisfaction level, its features,

uses, benefits, limitations, factors affecting to derivatives etc.

Most of the previous studies have limited their investigations to impact of derivatives on

cash market. This study is conducted in India capturing the experience of investors and

their perceptions since the introduction of derivatives in India till date. This research

employs the study of hypothesis using ANOVA testing, Factor Analysis, Cluster analysis

to understand the investors’ perceptions in better way. Few studies have tried to to

employ the same.

The results and insights obtained concerning the investors views regarding derivatives

will be used to infer conclusions which will make significant contributions to the existing

body of literature.

1.2 CAPITAL MARKET OF INDIA: INTRODUCTION AND OVERVIEW

1.2.1 Financial System in India:

Capital is one of the important factors of production in any economy. In economy, a well

organized financial system provides adequate capital formation through savings, finance

and investments2. An investment depends upon Savings and in turn Savings depends

upon earnings of an individual or profits of the organization. This system may be viewed

as a set of sub-systems with so many elements which are interdependent and interlinking

with each other to produce the purposeful result with in the boundary. Hence, the term

2 L. M. Bhole, Financial Institutions and Markets: Structure, Growth and Innovation. (New Delhi, Tata McGraw-Hill, 2007) pp. 6-14.

5

system in the context of finance means a set of complex and closely connected financial

institutions, instruments, agents, markets and so on which are interdependent and

interlinking with each other to produce the economic growth with in the country. Transfer

process is effectively fulfilled by the financial system to facilitate economic growth

through the channel of finance.

In the recent past the Indian Financial System has undergone sea changes and

invented many new channels of financial sub-systems through the process of

financial reforms. This thesis is based on this ‘recent past’ which will be dealt

thoroughly later in coming chapters on “derivatives”. Let’s have a brief look at the

Indian financial system and its components to have background knowledge first.

Indian financial system can be broadly grouped into main pillars like (1) financial market

(2) financial intermediaries (3) financial instruments (4) financial services.

1.2.2 Financial Intermediaries:

Financial Intermediaries also termed as Financial Institutions. We can classify the

financial intermediaries into two groups one is organized financial intermediaries and

other one is unorganized financial intermediaries. Organized financial intermediaries

comes under the purview of regulating authorities namely Reserve Bank of India,

Securities Exchange Board of India, Companies Act, Securities Contract (Regulation)

Act and so on. Whereas unorganized financial institutions are not cover under the

purview of these regulating authorities, such type of institutions are called local money

lenders, pawn brokers etc. Our study is mainly focusing on formal or organized financial

intermediaries only3.

Organised financial intermediaries can be classified as Banking Institutions, Non

Banking Financial Institutions, Insurance Companies and Housing Finance Companies.

3 Ajit Singh, ‘Financial Liberalization, Stock Markets and Economic Development.’ The Economic

Journal, vol. 107 (May 1997), pp. 607-12.

6

These financial intermediaries plays vital role in the capital formation by means of

mobilizing savings and facilitating the allocation of funds in an effective manner. These

intermediaries provide the convenience to the small investors by mobilizing their savings

in the form of divisibility and distribute the claims at the time of maturity or redemption.

1.2.3 Financial instruments:

Financial instruments can be categorized into various parts namely equity shares,

preference shares, debt instruments and various combinations of these, time deposits,

Mutual Funds and insurance polices, futures, options etc.

A financial asset/Instrument/security is a claim against another economic unit and is held

as a store of value and for the return that is expected4. While the value of a

tangible/physical asset depends on its physical properties such as buildings, machines,

furniture's, vehicles and so on, a financial asset represents a claim to future cash flows in

the form of interest, dividends and so on. They are a claim on a stream of income and/or

particular assets.. The entity/economic unit that offer the future cash flows are the issuer

of the financial instrument’ and the owner of the security is the investor’.

Depending upon the nature of claim/return, an instrument may be (i) debt (security) such

as bonds, debentures, term loans, (ii) equity (security) shares and (iii) hybrid security

such as preference shares and convertibles.

Based on the type of issuer, the security may be (1) direct (2) indirect and (3) derivative.

The securities issued by manufacturing companies are direct assets (e.g.

shares/debentures). Indirect assets are claims against financial intermediaries (e.g. units

of mutual funds). The derivative instruments include options and futures. The prevalence

of a variety of securities to suit the investment requirements of heterogeneous investors

offers differentiated investment choice to them and is an important element in the

maturity and sophistication of the financial system. 4 Bimal, Jalan,, ‘Finance and Development’, RBI bulletin, (June 2000), pp. 29-45

7

1.2.4 Financial Services:

Financial services have been growing rapidly with the emergence of new investment

flows in financial reconstitute a large and growing sector in almost all economies. Trade

and investment flows in financial services have been growing rapidly with the emergence

of new and growing markets in developing and transition economies, with modernization,

rapid technological change, use of new financial instruments, and financial and trade

liberalization5. The financial services sector is also quite large and complex and covers a

wide range of activities and instruments, including for instance, corporate banking,

derivatives, factoring, foreign exchange trading, pensions and investment fund

management, advisory and consultancy services, insurance broking and underwriting,

project finance, securities trading, venture capital, and wholesale and retail banking

services. Given the range of instruments and activities that fall under the purview of the

financial services sector, there are also a large number of players.

1.2.5 Financial Market:

The Indian Financial Market promotes the enormous savings of the economy, by

providing an effective channel of returns to the investors from whom the savings are

mobilized. Hence, the term Financial Markets can be defined as a market for the

exchange of capital and credit including the money markets and the capital markets.

Financial Markets are facilitating tools for procurement of funds and invest in to various

assets.

The main activities of Financial Markets can be viewed as sale or purchase of shares or

stocks, bonds, bills of exchange, commodities, future and options, foreign currency etc.

Financial market can be broadly classified into (i) Money market (ii) Capital market.

5 Bharati, Pathak, Indian Financial Systems, (Delhi, Pearson Education, 2006), pp. 4-5.

8

1.2.6 Money Market

The Money Market refers to the market for short term debt instrument which has maturity

less than one year. The Money Market provides the borrower to borrow the funds for

shorter period with lowest cost of funds. At the same time it also facilitates to the investor

a platform to invest his savings which can generate interest thereon. Money Markets does

not have an organised trading market place such as the stock exchange for its primary

issue and secondary market trades. The participants in the money market are banks,

primary dealers, and financial institutions, mutual funds, non-bank financial companies,

manufacturing companies, State Governments, provident funds, non-resident Indians,

overseas corporate bodies, foreign institutional investors and trusts. The RBI and

Securities and Exchange Board of India (SEBI) regulate the participants and use of

instruments in the money market depending upon their respective roles in the financial

system6. For instance, financial institutions and mutual funds are allowed only as lenders

in the call money market but are permitted to buy and sell Commercial Paper.

1.2.7 Capital Market:

Capital Market is the market for long term finance with the maturity period more than

one year. The Capital Market deals with the stock markets which provide financing

through the issuance of shares or common stock in the primary market, and enable the

subsequent trading in the secondary market. Capital Markets also deals with Bond

Market which provide financing through issuance of Bonds in the primary market and

subsequent trading thereof in the secondary market7.

6Bharati, Pathak, Indian Financial Systems, (Delhi, Pearson Education, 2008), pp. 42-45. 7 Bharti, Pathak,, Indian Financial Systems, (Delhi, Pearson Education, 2008), pp. 102-105.

9

1.2.8 Functions of Capital Markets8:

1) The organised and regulated capital market motivates individual to save and

invest funds. The availability of safe and profitable source of investment is an

essential criterion to create propensity to save and invest on the part of the earning

public.

2) It provides for the investors a safe and productive channels for investment of

savings and secure the recurring benefit of return thereon, as long as the savings

are retained.

3) It provides liquidity to the savings of the investors, by developing a secondary

capital market, and thus makes even short term savings, consistently available for

long-term users

4) It thus mobilizes savings of large number of individuals, families and associations

and make the same available for meeting the large capital needs of organised

industry, trade and business and for progress and development of the country as a

whole and its economy.

Financial markets are also classified as primary and secondary markets. The primary

market deals in fresh capital / new securities therefore they are known as new issue

Markets. Secondary markets deal in securities already issued or existing or outstanding.

The primary markets mobilize savings and they supply fresh capital to business units.

While secondary market helps in raising additional capital by providing liquidity to

existing capital.

The term capital market is coexistence not only with the stock market but also with the

money market. However, in its popular usage, it refers to the stock market. It is not

always possible to include a given participant (say a bank) only in either of the two

(money and capital) markets.

8 B. M. Misra, ‘Fifty Years of The Indian Capital Market’ RBI occasional papers, (June and September 1999), p.8.

10

In the ensuing pages, research is mainly concerned with capital market in its popular

sense focusing upon organisation and working of its emerging derivative segment.

Let’s have a look at it.

Organization of securities market

The term ‘securities market’ refers to the market provided by the different stock

exchanges to securities which includes corporate securities such as shares, stocks,

debentures, bonds, government securities such as dated securities and Treasury bill and

right, titles or interest in such securities which includes derivatives in securities such as

options and futures contract9.

Size and design of securities market

Transfer of resources from those with idle resources to others who have a productive

need for them is perhaps most efficiently achieved through the securities markets. Stated

formally, securities markets provide channels for reallocation of savings to investments

and entrepreneurship and thereby decouple these two activities. As a result, the savers

and investors are not constrained by their individual abilities, but by the economy’s

abilities to invest and save respectively, which inevitably enhances savings and

investment in the economy. Savings are linked to investments by a variety of

intermediaries through a range of complex financial products called “securities” which is

defined in the Securities Contracts (Regulation) Act, 1956 to include:

(1) Shares, scrips, stocks, bonds, debentures, debenture stock or other marketable

securities of a like nature in or of any incorporated company or body corporate;

(a) Derivatives;

(b) Units of any other instrument issued by any collective investment scheme to

the investors in such schemes;

(c) Security receipt as defined in clause (zg) of section 2 of the Securitisation and

Reconstruction of Financial Assets and Enforcement of Security Interest Act,

2002;

9 National Stock Exchange, Indian Securities Market: A Review, volume IV, 2005

11

(d) Units or any other such instrument issued to the investors under any mutual

fund scheme;

(e) any certificate or instrument (by whatever name called), issued to an investor

by any issuer being a special purpose distinct entity which possesses any debt or

receivable, including mortgage debt, assigned to such entity, and acknowledging

beneficial interest of such investor in such debt or receivable, including mortgage

debt, as the case may be;

(2) Government securities,

(a) Such other instruments as may be declared by the Central Government to be

securities; and

(3) Rights or interest in securities.

There are a set of economic units who demand securities in lieu of funds and others who

supply securities for funds. These demand for and supply of securities and funds

determine, under competitive market conditions in both goods and securities market, the

prices of securities which reflect the present value of future prospects of the issuer,

adjusted for risks and also prices of funds10. It is not that the users and suppliers of funds

meet each other and exchange funds for securities. It is difficult to accomplish such

double coincidence of wants. The amount of funds supplied by the supplier may not be

the amount needed by the user. Similarly, the risk, liquidity and maturity characteristics

of the securities issued by the issuer may not match preference of the supplier. In such

cases, they incur substantial search costs to find each other. Search costs are minimized

by the intermediaries who match and bring the suppliers and users of funds together.

These intermediaries may act as agents to match the needs of users and suppliers of funds

for a commission, help suppliers and users in creation and sale of securities for a fee or

buy the securities issued by users and in turn, sell their own securities to suppliers to

book profit. It is, thus, a misnomer that securities market disintermediates by establishing

a direct relationship between the savers and the users of funds. The market does not work

in a vacuum; it requires services of a large variety of intermediaries. The

10 Ajay , Shah, ‘Securities Markets Towards Greater Efficiency,’ in K. S. Parikh (ed.) India Development Report, (Delhi, Oxford University Press, 1997 )

12

disintermediation in the securities market is in fact an intermediation with a difference; it

is a risk-less intermediation, where the ultimate risks are borne by the savers and not the

intermediaries. A large variety and number of intermediaries provide intermediation

services in the Indian securities market as may be seen from Table

The securities market, thus, has essentially three categories of participants, namely the

issuers of securities, investors in securities and the intermediaries. The issuers and

investors are the consumers of services rendered by the intermediaries while the investors

are consumers (they subscribe for and trade in securities) of securities issued by issuers.

In pursuit of providing a product to meet the needs of each investor and issuer, the

intermediaries churn out more and more complicated products. They educate and guide

them in their dealings and bring them together. Those who receive funds in exchange for

securities and those who receive securities in exchange for funds often need the

reassurance that it is safe to do so. This reassurance is provided by the law and by

custom, often enforced by the regulator. The regulator develops fair market practices and

regulates the conduct of issuers of securities and the intermediaries so as to protect the

interests of suppliers of funds. The regulator ensures a high standard of service from

intermediaries and supply of quality securities and non- manipulated demand for them in

the market11.

Table 1.1 : Market Participants in Securities Market

Market Participants

Number as on March

31

2007 2008

Securities Appellate Tribunal 1 1

Regulators* 4 4

Depositories 2 2

Stock Exchanges

With Equities Trading 21 19

With Debt Market Segment 2 2

With Derivative Trading 2 2

11 Ajay, Shah, and Susan Thomas, ‘Policy Issues In India’s Capital Markets In 2000AD,’ in Surjit S. Bhalla (ed.), New Economic Policies – For a new India, Indian Council of Social Science Research, (Haranand Publication Pvt. Ltd., 2000), pp. 185-210.

13

Brokers 9,443 9,487

Corporate Brokers 4,110 4,183

Sub-brokers 27,541 44,073

FIIs 996 1,319

Portfolio Managers 158 205

Custodians 15 15

Primary Dealers 17 16

Merchant Bankers 152 155

Bankers to an Issue 47 50

Debenture Trustees 30 28

Underwriters 45 35

Venture Capital Funds 90 106

Foreign Venture Capital Investors 78 97

Mutual Funds 40 40

Collective Investment Schemes 0 0

(Source: SEBI Handbook)

The securities / capital market has two interdependent and inseparable segments: the

primary and the secondary market.

1.2.9 Primary Market

The primary market provides the channel for sale of new securities. Primary market

provides opportunity to issuers of securities; Government as well as corporates, to raise

resources to meet their requirements of investment and/or discharge some obligation.

They may issue the securities at face value, or at a discount/premium and these securities

may take a variety of forms such as equity, debt etc. They may issue the securities in

domestic market and/or international market. The primary market issuance is done either

through public issues or private placement. A public issue does not limit any entity in

investing while in private placement, the issuance is done to select people. In terms of the

Companies Act, 1956, an issue becomes public if it results in allotment to more than 50

persons. This means an issue resulting in allotment to less than 50 persons is private

placement. There are two major types of issuers who issue securities. The corporate

14

entities issue mainly debt and equity instruments (shares, debentures, etc.), while the

governments (central and state governments) issue debt securities (dated securities,

treasury bills). The price signals, which subsume all information about the issuer and his

business including associated risk, generated in the secondary market, help the primary

market in allocation of funds12.

13Resources rose through public issues declined by 91.5 per cent to Rs. 2,031 crore

during April-June 2008 over those in the corresponding period of last year. The number

of issues declined from 24 in April-June 2007 to 15 in April-June 2008. The average size

of public issues also declined to Rs.135 crore during April-June 2008 from Rs.994 crore

during April-June 2007. All public issues during April-June 2008 were in the form of

equity. Out of 15 issues during April-June 2008, 13 issues were initial public offerings

(IPOs), accounting for 78.4 per cent of total resource mobilisation. Mobilisation of

resources through private placement increased by 45.7 per cent to Rs.2,12,568 crore

during 2007-08 over the previous year. Resources mobilised by private sector entities

increased by 58.3 per cent during 2007-08, while those by public sector entities increased

by 29.7 per cent. Financial intermediaries (both from public sector and private sector)

accounted for the bulk (67.9 per cent) of the total resource mobilization from the private

placement market during 2007-08 (68.9 per cent during 2006-07). Resources raised

through Euro issues – American Depository Receipts (ADRs) and Global Depository

Receipts (GDRs) – by Indian corporate during April-June 2008 at Rs.4,056 crore were

substantially higher than those during the corresponding period of previous year. During

April-June 2008, net mobilisation of resources by mutual funds declined by 25.3 per cent

to Rs.38,437 crore over the corresponding period of 2007 (Table 49). Scheme-wise,

during April-June 2008, 90.0 per cent of net mobilisation of funds was under income/debt

oriented schemes. Growth-oriented schemes accounted for 7.9 per cent of net resource

mobilisation during April-June 2008.

12 L. M. Bhole, Financial Institutions and Markets: Structure, Growth, and Innovation, (New Delhi, Tata McGraw-Hill, 2006) 13 SEBI, Hand Book of Statistics on Indian Securities Market 2008, pp. 67-68.

15


1.2.10 Secondary Market

Secondary market refers to a market where securities are traded after being initially

offered to the public in the primary market and/or listed on the Stock Exchange. Majority

of the trading is done in the secondary market. Secondary market comprises of equity

markets and the debt markets. The secondary market enables participants who hold

securities to adjust their holdings in response to changes in their assessment of risk and

return. They also sell securities for cash to meet their liquidity needs. Once the new

securities are issued in the primary market they are traded in the stock (secondary)

Table 1.2: Mobilization of Resource from Primary Market

16

market. The backbone of the capital market is formed by the various securities exchanges

that provide a forum for equity (equity market) and debt (debt market) transactions14.

The secondary market is operated through two mediums, namely, the Over-the Counter

(OTC) market and the Exchange- Traded market. OTC markets are informal markets

where trades are negotiated. Most of the trades in the government securities are in the

OTC market. All the spot trades where securities are traded for immediate delivery and

payment take place in the OTC market. The exchanges do not provide facility for spot

trades in a strict sense. Closest to spot market is the cash market in exchanges where

settlement takes place after some time. There are 19 exchanges (at the end of March

2008) in India and all of them follow a systematic settlement period. All the trades taking

place over a trading cycle (day=T) are settled together after a certain time (T+2 day).

Trades executed on NSE and BSE only are cleared and settled by a clearing corporation

which provides novation and settlement guarantee. Nearly 100% of the trades in market

are settled through demat delivery. For example, NSE also provides a formal trading

platform for trading of a wide range of debt securities including government securities in

both retail and wholesale mode. NSE also provides trading in derivatives of equities,

interest rate as well indices.

A variant of secondary market is the forward market, where securities are traded for

future delivery and payment. Pure forward is out side the formal market. The versions of

forward in formal market are futures and options. In futures market, standardized

securities are traded for future delivery and settlement. These futures can be on a basket

of securities like an index or an individual security. In case of options, securities are

traded for conditional future delivery. There are two types of options–a put option

permits the owner to sell a security to the writer of options at a predetermined price while

a call option permits the owner to purchase a security from the writer of the option at a

predetermined price. These options can also be on individual stocks or basket of stocks

14 Bharti, Pathak,, Indian Financial Systems, (Delhi, Pearson Education, 2008 ), pp. 164-170..

17

like index. Two exchanges, namely NSE and the Bombay Stock Exchange, (BSE)

provide trading of derivatives of securities.

Today the market participants have the flexibility of choosing from a basket of products

like: Equities, Bonds issued by both Government and Companies, Futures on benchmark

indices as well as stocks, Options on benchmark indices as well as stocks, Futures on

interest rate products like Notional 91-day T-Bills, 10 year notional zero coupon bond

and 6% notional 10 year bond.

The stock exchanges are the exclusive centers for trading of securities. Listing of

companies on a Stock Exchange is mandatory to provide an opportunity to investors to

invest in the securities of local companies. The trading volumes on exchanges have been

witnessing phenomenal growth for last few years. Since the advent of screen based

trading system in 1994-95, it has been growing by leaps and bounds and reported a total

turnover of Rs.51, 30,816 crore during 2007-0815. The growth of turnover has, however,

not been uniform across exchanges. The increase in turnover took place mostly at big

exchanges (NSE and BSE) and it was partly at the cost of small exchanges that failed to

keep pace with the changes. The business moved away from small exchanges to big

exchanges, which adopted technologically superior trading and settlement systems. The

huge liquidity and order depth of big exchanges further diverted liquidity of other stock

exchanges. The 19 small exchanges put together reported less than 0.02% of total

turnover during 2007-08, while 2 big exchanges accounted for over 99.98 % of turnover.

For most of the exchanges, the raison d’être for their existence, i.e. turnover, has

disappeared. NSE and BSE are the major exchanges having nationwide operations. NSE

operated through 2,956 VSATs in 245 cities at the end of March 2008. .

15 SEBI Annual Report 2007-08, Various issues.

18

Table 1.3: Turnover on all Exchanges

(In Rs. crore)

Exchange 2006-07 2007-08

NSE 19,45,287 35,51,038

BSE 9,56,185 15,78,857

Uttar Pradesh 799 475

Ahmedabad 0 0

Calcutta 694 446

Madras 1 0

OTCEI 0 0

Delhi 0 0

Hyderabad 92 0

Bangalore 0 0

Magadh 0 0

Bhubaneshwar 1 0

Cochin 0 0

Coimbatore 0 0

Gauhati 0 0

Jaipur 0 0

Ludhiana 0 0

Madhya Pradesh 0 0

Mangalore 0 0

Pune 0 0

SKSE 0 0

Vadodara 0 0

Total 29,03,058 5,130,816

NSE+BSE 29,01,472 5,129,895

Total (Except

NSE + BSE) 1,586 921


19

The past decade in many ways has been remarkable for securities market in India. It has

grown exponentially as measured in terms of amount raised from the market, number of

stock exchanges and other intermediaries, the number of listed stocks, market

capitalisation, trading volumes and turnover on stock exchanges, and investor population.

Along with this growth, the profiles of the investors, issuers and intermediaries have

changed significantly. The market has witnessed several institutional changes resulting in

drastic reduction in transaction costs and significant improvements in efficiency,

transparency, liquidity and safety. In a short span of time, Indian derivatives market has

got a place in list of top global exchanges. The market capitalization has grown over the

period indicating more companies using the trading platform of the stock exchange. As of

March 2008, the market capitalization of NSE was Rs. 48,581,217 million16. The market

capitalization ratio is defined as market capitalization of stocks divided by GDP. It is

used as a measure of stock market size. It is of economic significance since market is

positively correlated with the ability to mobilize capital and diversify risk. The trading

volumes on exchanges have been witnessing phenomenal growth over the past few years.

During 2007-08, the capital market segment of NSE itself only reported a trading volume

of Rs. 35,510,382 million.

The turnover ratio, which reflects the volume of trading in relation to the size of the

market, stood at 73.09% in the year 2007-08. The turnover ratio is defined as the total

value of shares traded on a country’s stock exchange divided by market capitalization. It

is used as a measure of trading activity or liquidity in the stock markets. The top 2 stock

exchanges accounted for nearly 99% of turnover, while the rest of the exchanges had

negligible volumes during 2007-08. The movement of the NIFTY50, the most widely

used indicator of the market, has been responding to changes in the government’s

economic policies, the increase in FIIs inflows, etc.

Domestic stock markets, which remained generally firm up to first week of January 2008,

witnessed severe bouts of volatility thereafter due to heightened concerns over the

severity of sub-prime lending crisis in the US and its spillover to other market segments

16 Capital Market, 3-16 May 2008

20

and in other countries. The domestic stock markets recovered somewhat during April-

May 2008. On May 21, 2008, the BSE Sensex registered gains of 10.2 per cent over end-

March 2008. The upward trend was attributed to better than expected fourth quarter

results of 2007-08 declared by IT majors, net purchases by FIIs in the Indian equity

market, and some easing of international crude oil prices. The market sentiment,

however, turned cautious thereafter mainly on account of hike in domestic retail fuel

prices, rise in domestic inflation rate, net sales by FIIs in the Indian equity market,

concerns over rising trade deficit and depreciation of the rupee, downward trend in major

international equity markets, increase in international crude oil prices and other sector

and stock specific news. As a result, both the BSE Sensex and the S&P CNX Nifty closed

lower at 14942.28 and 4476.80, respectively, on July 23, 2008, registering losses of 4.5

per cent and 5.4 per cent, respectively, over their end-March 2008 level. Between end-

March 2008 to July 23, 2008, the BSE Sensex moved in a range of 12576-17600.

According to the data released by the Securities and Exchange Board of India (SEBI),

FIIs made net sales of Rs.16,279 crore (US $ 4.0 billion) in the Indian equity market

during 2008-09 so far (up to July 17, 2008) as against net purchases of Rs.30,777 crore

(US $ 7.4 billion) during the corresponding period of the previous year17. Mutual funds,

on the other hand, made net purchases of Rs.3,654 crore during 2008-09 so far (up to July

17, 2008) as compared with net purchases of Rs.2,604 crore during the corresponding

period of last year. The sectoral indices witnessed a mixed trend during the current

financial year so far (up to July 18, 2008). The losers among the sectoral indices were

capital goods, auto, banking, public sector undertakings, metal, fast moving consumer

goods, consumer durables and oil and gas, while the gainers were information technology

and healthcare sector stocks. NSE in the cash segment during April-June 2008 was higher

by 38.2 per cent than the corresponding period of 2007.

17 SEBI, Hand Book of Statistics on Indian Securities Market 2008.

21

Reforms in the securities market, particularly the establishment and empowerment of

SEBI, market determined allocation of resources, screen based nation-wide trading,

dematerialization and electronic transfer of securities, rolling settlement and ban on

deferral products, sophisticated risk management and derivatives trading, have greatly

improved the regulatory framework and efficiency of trading and settlement. Indian

market is now comparable to many developed markets in terms of a number of qualitative

parameters.

Let’s have a look at each major developments and reforms taken place for the last 20

years briefly.

Table 1.4: STOCK MARKET INDICATORS

Source: BSE and NSE Fact book published. (Based on Sensex 30 scrips and nifty 50 scrips)

22

1.3 DEVELOPMENTS & MAJOR REFORMS IN INDIAN CAPITAL MARKET.

Indian Capital Markets have grown exponentially in the last few years. The growth has

been in every sphere, in the amount of capital raised through primary issuances, in

exchange trading turnovers, in the market indices and market capitalization, in mutual

fund assets and foreign institutional investment. Corporate earnings are growing at

healthy pace and the markets are a reflection of the health of the Indian economy.

However none of this would have been possible if the Indian markets had not developed

a world class market and regulatory infrastructure. The efforts of the last decade in

developing an efficient market infrastructure have created a market that has made

transactions transparent and settlements safer. The new derivative market has provided a

transparent avenue for managing risk to a wide variety of investors. SEBI’s objective has

been to encourage the development of the market while protecting the interests of

investors. The task is however only partly done. Rapidly expanding markets require the

industry and regulators to continually shore up their skills and resources. On the other

side, the retail Indian investor is still not aware or confident of investing opportunities in

the markets. There is a need to improve the quality of investment advice being provided

to investors and to regulate those who interface with the retail investor. Further new

products and markets need to be developed.

The opening up of Indian economy in the 1990's led to a series of financial sector

reforms, prominent being the capital market reforms. These reforms have led to the

development of the Indian equity markets to the standards of the major global equity

markets. All this started with the abolition of Controller of Capital Issues and subsequent

free pricing of shares. The introduction of dematerialization of shares, leading to faster

and cheaper transactions and introduction of derivative products and compulsory rolling

settlement has followed subsequently18. Despite a series of stock market scams and crises

beginning from 1992 Harshad Mehta's scam to the Ketan Parekh's 2001 scam, the Indian

equity markets have transformed themselves from a broker dominated market to a mass

market.

18 U. R. Bhat, ‘The Market Needs A Make Over’, The Economic Times, (December 13 2004), 8

23

The introduction of online trading has given a much-needed impetus to the Indian equity

markets. However, over the years, reforms in the equity markets have brought the country

on par with many developed markets on several counts. Today, India boasts of a variety

of products, including stock futures, an instrument launched only by select markets.

The introduction of rolling settlement is the latest step in the direction of overhauling the

stock market. The equity market of the country will most likely be comparable with the

world's most advanced secondary markets with regard to international best practices. The

market moved to compulsory rolling settlement and now all settlements are executed on

T+2 basis and market is gearing up for moving to T+1 settlement in 2004 while the

Straight Through Processing (STP) is in place from December 2002.

The importance of equity market is increasing. Rightly, realizing the advantages of

resource allocation through market, Government of India and Reserve Bank of India have

been pushing reforms in equity markets. Series of steps are being taken to remove

hurdles, increase market efficiency and to make it attractive for the retail investors to take

part in the equity market. It may not be an exaggeration to say that the Indian markets are

resourceful to put themselves on par with the markets of the developed countries. The

Indian markets have assimilated in a relatively lesser time, many a developments that

took long time in the developed markets.

The Government of India has been trying to improve market efficiency, enhance

transparency and bring the Indian Equity Market up to international standards. Many

reform measures have been initiated in the 90s19. The principal ones are the formation of

Securities Exchange Board of India (SEBI), repeal of the Capital Issues (Control) Act,

1947, introduction of screen-based trading, shortening of trading cycle, demutualization

of stock exchanges, establishment of depositories disappearance of physical share

certificates and better risk management systems in stock exchanges.

19 Ashok, Rambhia, ‘Fifty years of Indian Capital Market’, Capital Market, (August 2003), 14-17.

24

The formation of SEBI was the first attempt towards integrated regulation of the

securities market. SEBI regulates all market intermediaries and has the powers to impose

monetary penalties for misconduct of any intermediary. One of the major stumbling

blocks in fair pricing of capital issues has been the Capital Issues (Control) Act, 1947.

The issuers were denied the opportunity to economically raise money from the capital

market. This is now a matter of the past thanks to the repeal of the Act itself. SEBI has

also issued Disclosure and Investor Protection (DIP) guidelines to ensure fair prices for

the investors, though however, many issuers in the 90s could unfairly price their capital

issues at the cost of the poor common investors.

The introduction of Screen Based Trading Systems (SBTS) by NSE is a major

development in the capital market. This made the markets more efficient. The

geographical barriers to trade were dismantled resulting in increased trading volumes.

This was possible due to the great advancements in the area of information technology.

SBTS electronically matches orders cutting down time, cost and errors, and minimizing

the chances of fraud. Very long settlement cycle was another major hindrance in effecting

deliveries in the equity market. Often the securities were delivered after 30 days or more

due to weekly/fortnightly settlements and carry forward transactions. SEBI has enforced

the discipline to compulsorily settle trades in T+3 days since April 2002. This is slated to

reduce to T+2 days from April 2003. All scrips are now under rolling settlement since

December 2001.

The Equity Market is incomplete without products to manage risks in portfolio values. At

long last, derivatives trading appeared on Indian exchanges in June 2000. While the

product range in derivatives is still limited (futures and options on stocks and stock

indices), it is certainly a major step forward in broadening the financial markets. NSE

was established as a demutualized structure separating the roles of ownership,

management and trading to eliminate any conflict of interest among the stakeholders to

improve market efficiency and to focus on investor interest. Another notable

development in the Indian equity market has been the introduction of depositories to

dematerialize the share certificates. This avoids physical movement of certificates, bad

25

deliveries and quicker transfer of ownership of shares. Presently all actively traded shares

are held, traded and settled in Demat form. The setting up of National Securities Clearing

Corporation Ltd., (NSCCL) in April 1996 has been a major development in managing

counterparty risks in the equity market. This has helped in increasing trading volumes

since traders are now more confident about default-free settlements. While most of the

above measures have helped in reinforcing confidence in the Indian equity market by

providing more transparent and efficient buying, selling and transfer of shares.

1.4 Outline of the thesis:

Thesis is structured into six chapters. Chapter 1 titled introduction to the thesis discusses

the background and justifications of the research, capital market of India, functions of

capital market and major reforms taken place in capital market.

Chapter 2 provides the basic introduction and overview of derivatives in India. This

chapter covers literature pertaining to history of derivatives, need for and evolution of

derivatives, factors contributing to the growth of derivatives, merits & demerits, critique

of derivatives. Application of derivative instrument like futures and options has been

discussed in detail in this chapter.

Chapter 3 provides review of literature relevant to this research area. It presents the

various studies done by researchers concerning derivatives across the world as well as in

India. It establishes theoretical and conceptual foundation for the research work carried

out and presented in this thesis.

Chapter 4 contains research methodology used to carry out research work. It also includes

research design, objectives, sampling methods, methods and tools of data collection etc.

Chapter 5 presents the analysis of the collected data and addresses the findings of this

research.

26

Finally, Chapter 6 draws conclusions from the results of the analysis and implications for

further research work.

27

CHAPTER 2

DERIVATIVES: INTRODUCTION AND OVERVIEW

2.1 An Introduction

2.2 History of Derivatives

2.3 Need for Derivatives in India

2.4 Evolution of Derivatives in India

2.5 Major Recommendations of Dr. LC. Gupta Committee

2.6 Factors Contributing to the Growth of Derivatives

2.7 Benefits of Derivatives

2.8 Definition of Financial Derivative

2.9 Features of Financial Derivative

2.10 Types and Classifications of Derivatives

2.11 Uses of Derivatives

2.12 Critique of Derivatives

2.13 Myths about Derivatives

2.14 Emerging Structure of Derivatives Markets in India

2.15 Categories of Derivatives Traded in India.

2.16 Equity Derivatives

2.17 Derivative Trading at NSE and BSE

2.18 Futures and Options as Derivative Instruments and their Application.

28

2.1 AN INTRODUCTION

The past decade has witnessed the multiple growths in the volume of international trade




rates and stock market prices at the different financial markets have increased the

financial risks to the corporate world. Adverse changes have even threatened the very

survival of the business world. It is, therefore, to manage such risks; the new financial


known as financial derivatives. The basic purpose of these instruments is to provide

commitments to prices for future dates for giving protection against adverse movements

in future prices, in order to reduce the extent of financial risks. Not only this, they also

provide opportunities to earn profit for those persons who are ready to go for higher risks.

In other words, these instruments, indeed, facilitate to transfer the risk from those who

wish to avoid it to those who are willing to accept the same.

Today, the financial derivatives have become increasingly popular and most commonly

used in the world of finance. This has grown with so phenomenal speed all over the

world that now it is called as the derivatives revolution. In an estimate, the present annual

trading volume of derivative markets has crossed US $ 30,000 billion, representing more

than 100 times gross domestic product of India20.

2.2 HISTORY OF DERIVATIVES MARKETS

It is difficult to trace the main origin of futures trading since it is not clearly established

as to where and when the first forward market came into existence. Historically, it is

evident that the development of futures markets followed the development of forward

markets. It is believed that the forward trading has been in existence since 12th century in

20 Gulen H and Mayhew S, “Stock Index Futures Trading and Volatility in International Equity Markets”, Journal of Futures Markets, Vol. 20, (2004), 661-685.

29

England and France. Forward trading in rice was started in 17th century in Japan, known

as Cho-at-Mai a kind (rice trade-on-book) concentrated around Dojima in Osaka, later on

the trade in rice grew with a high degree of standardization. In 1730, this market got

official recognition from the Tokugawa Shogurate. As such, the Dojima rice market

became the first futures market in the sense that it was registered on organized exchange

with the standardized trading norms21.

The butter and eggs dealers of Chicago Produce Exchange joined hands in 1898 to form

the Chicago Mercantile Exchange for futures trading. The exchange provided a futures

market for many commodities including pork bellies (1961), live cattle (1964), live hogs

(1966),and feeder cattle (1971).The International Monetary Market was formed as a

division of the Chicago Mercantile Exchange in 1972 for futures trading in foreign

currencies. In 1982,it introduced a futures contract on the S&P 500 Stock Index. Many

other exchanges throughout the world now trade futures contracts. Among them are the

Chicago Rice and Cotton Exchange, the New York Futures Exchange, the London

International Financial Futures Exchange, the Toronto Futures Exchange and the

Singapore International Monetary Exchange. They grew so rapidly that the number of

shares underlying the option contracts sold each day exceeded the daily volume of shares

traded on the New York Stock Exchange22.

In the 1980s. markets developed for options in foreign exchange, options on stock

indices, and options on futures contracts. The Philadelphia Stock Exchange is the premier

exchange for trading foreign exchange options. The Chicago Board Options Exchange

trades options on the S&P 100and the S&P 500 stock indices while the American Stock

Exchange trades options on the Major Market Stock Index, and the New York Stock

Exchange trades options on the NYSE Index. Most exchanges offering futures contracts

now also offer options on these futures contracts. Thus, the Chicago Board of Trades

offers options on com futures, the Chicago Mercantile Exchange offers options on live

21 Robert W, Kolb, Financial Derivatives, (Miami, Kolb Publishing, 2000), pp 78-80. 22 Williams, Michael S. and Hoffman, Amy. Fundamentals Of Futures And Options Market, (Mcgraw-hill Companies, 2001), p. 203

30

cattle futures, and the International Monetary Market offers options on foreign currency

futures, and so on.

The basic cause of forward trading was to cover the price risk. In earlier years,

transporting goods from one market to other markets took many months. For example, in

the 1800s, food grains produced in England sent through ships to the United States which

normally took few months. Sometimes, during this time, the price crashed due to

unfavourable events before the goods reached to the destination23. In such cases, the

producers had to sell their goods at the loss. Therefore, the producers sought to avoid

such price risk by selling their goods forward, or on a "to arrive" basis. The basic idea

behind this move at that time was simply to cover future price risk. On the opposite side,

the speculator or other commercial firms seeking to offset their price risk came forward

to go for such trading. In this way, the forward trading in commodities came into

existence.

In the beginning, these forward trading agreements were formed to buy and sell food

grains in the future for actual delivery at the pre-determined price. Later on these

agreements became transferable, and during the American Civil War period, i.e., 1860to

1865,it became common place to sell and resell such agreements where actual delivery of

produce was not necessary. Gradually, the traders realized that the agreements were

easier to buy and sell if the same were standardized in terms of quantity, quality and

place of delivery relating to food grains. In the nineteenth century this activity was

centred in Chicago which was the main food grains marketing centre in the United States.

In this way, the modem futures contracts first came into existence with the establishment

of the Chicago Board of Trade (CBOT) in the year 1848, and today, it is the largest

futures market of the world. In 1865, the CBOT framed the general rules for such trading

which later on became a trendsetter for so many other markets.

23 Keith, Redhead, Financial Derivatives: An Introduction to Futures and Options, (New Delhi, Prentice Hall of India, 2002), pp 24-27.

31

In 1874, the Chicago Produce Exchange was established which provided the market for

butter, eggs, poultry, and other perishable agricultural products. In the year 1877, the

London Metal Exchange came into existence, and today, it is leading market in metal

trading both in spot as well as forward. In the year 1898, the butter and egg dealers

withdrew from the Chicago Produce Exchange to form separately the Chicago Butter and

Egg Board, and thus, in 1919 this exchange were renamed as the Chicago Mercantile

Exchange (CME) and were reorganized for futures trading. Since then, so many other

exchanges came into existence throughout the world which trade in futures contracts24.

Although financial derivatives have been in operation since long, but they have become a

major force in financial markets in the early 1970s.The basic reason behind this

development was the failure of Bretton wood System and the fixed exchange rate regime

was broken down. As a result, new exchange rate regime, i.e., floating rate (flexible)

system based upon market forces came into existence. But due to pressure of demand and

supply on different currencies, the exchange rates were constantly changing, and often,

substantially. As a result, the business firms faced a new risk, known as currency or

foreign exchange risk. Accordingly, a new financial instrument was developed to

overcome this risk in the new financial environment.

Another important reason for the instability in the financial market was fluctuation in the

short-term interests. This was mainly due to that most of the government at that time tried

to manage foreign exchange fluctuations through short-term interest rates and by

maintaining money supply targets, but which were contrary to each other. Further, the

increased instability of short-term interest rates created adverse impact on long-term

interest rates, and hence, instability in bond prices because they are largely determined by

long-term interest rates. The result is that it created another risk, named interest rate risk,

for both the issuers and the investors of debt instruments.

24 H S Houthkker and P J Williamson, Economics of Financial Markets, (, London, Oxford university Press, 2002,) pp 55- 56.

32

Interest rate fluctuations had not only created instability in bond prices, but also in other

long-term assets such as, company stocks and shares. Share prices are determined on the

basis of expected present values of future dividends payments discounted at the

appropriate discount rate. Discount rates are usually based on long-term interest rates in

the market. So, increased instability in the long-term interest rates caused to enhanced

fluctuations in the share prices in the stock markets. Further volatility in stock prices is

reflected in the volatility in stock market indices which causes to systematic risk or

market risk.

In the early 1970s, it is witnessed that the financial markets were highly unstable; as a

result, so many financial derivatives have been emerged as the means to manage the

different types of risks stated above, and also of taking advantage of it. Hence, the first

financial futures market was the International Monetary Market, established in 1972by

the Chicago Mercantile Exchange which was followed by the London International

Financial Futures Exchange in 198225.

2.3 NEED FOR DERIVATIVES IN INDIA

Since 1991, due to liberalization of economic policy, the Indian economy has entered an

era in which Indian companies cannot ignore global markets. Before the nineties, prices

of many commodities, metals and other assets were controlled. Others, which were not

controlled, were largely based on regulated prices of inputs. As such there was limited

uncertainty, and hence, limited volatility of prices. But after 1991, starting the process of

deregulation, prices of most commodities are decontrolled. It has also resulted in partly

deregulating the exchange rates, removing the trade controls, reducing the interest rates,

making major changes for the capital market entry of foreign institutional investors,

introducing market based pricing of government securities, etc. All these measures have

increased the volatility of prices of various goods and services in India to producers and

consumers alike. Further, market determined exchange rates and interest rates also

25 M J Powers and D Vogel, Inside the Financial Futures Markets (New York, John Wiley and Sons, 1999), pp 7-11.

33

created volatility and instability in portfolio values and securities prices. Hence, hedging

activities through various derivatives emerged to different risks.

Futures trading offer a risk-reduction mechanism to the farmers, producers, exporters,

importers, investors, bankers, trader, etc. which are essential for any country. In the

words of Alan Greenspan, Chairman of the US Federal Reserve Board, "The array of

derivative products that has been developed in recent years has enhanced economic

efficiency. The economic function of these contracts ,is to allow risks that formerly had

been combined to be unbundled and transferred to those most willing to assume and

manage each risk components26." Development of futures markets in many countries has

contributed significantly in terms of invisible earnings in the balance of payments,

through the fees and other charges paid by the foreigners for using the markets. Further,

economic progress of any country, today, much depends upon the service sector as on

agriculture or industry. Services are now backbone of the economy of the future. India

has already crossed the roads of revolution in industry and agriculture sector and has

allowed the same now m services like financial futures. India has all the infrastructure

facilities and potential exists for the whole spectrum of financial futures trading in like

stock market indices, treasury bills, gilt-edged securities, foreign currencies, cost of

living index, stock market index, etc. For all these reasons, there is a major potential for

the growth of financial derivatives markets in India.

2.4 EVOLUTION OF DERIVATIVES IN INDIA






26 J L Stein, The Economics of Futures Markets, (London, Oxford University Press, 2004), pp 12-14.

34


commenced in India27

Table 2.1 – Evolution of Derivatives

1991 Liberalization process initiated

14 December 1995 NSE asked SEBI for permission to trade index futures.

18 November 1996 SEBI setup L.C.Gupta Committee to draft a policy framework

for index futures.

11 May 1998 L.C.Gupta Committee submitted report.

7 July 1999 RBI gave permission for OTC forward rate agreements (FRAs)

and interest rate swaps.

24 May 2000 SIMEX chose Nifty for trading futures and options on an Indian

index.

25 May 2000 SEBI gave permission to NSE and BSE to do index futures

trading.

9 June 2000 Trading of BSE Sensex futures commenced at BSE.

12 June 2000 Trading of Nifty futures commenced at NSE.

25 September 2000 Nifty futures trading commenced at SGX.

2 June 2001 Individual Stock Options & Derivatives

(Source: NSE Fact Book 2004)

Commodities futures trading in India was initiated long back in 1950s, however, the

1960s marked a period of great decline in futures trading. Market after market was closed

usually because different commodities' prices increases were attributed to speculation on

these markets. Accordingly, the Central Government imposed the ban on trading in

derivatives in 1969 under a notification issue. The late 1990s shows this signs of opposite

trends-a large scale revival of futures markets in India28, and hence, the Central

Government revoked the ban on futures trading in October, 1999. The Civil Supplies

Ministry agreed, in principle for starting of futures trading in Basmati rice, further, in

27 Susan, Thomas (ed), Derivative Markets in India ,( New Delhi, Tata McGraw-Hill, 2003), pp. 45-67. 28Ajay, Shah (ed), Commodity Derivatives (New Delhi, Tata McGraw-Hill, 2003), p. 10

35

1996 the Government granted permission to the Indian Pepper and Spice Trade

Association to convert its Pepper Futures Exchange into an International Pepper

Exchange. As such, on November 17, 1997, India's first international futures. Exchange

at Kochi, known as the India Pepper and Spice Trade Association-International

Commodity Exchange (IPSTA-ICE) was established.

Similarly, the Cochin Oil Millers Association, in June 1996, demanded the introduction

of futures trading in coconut oils. The Central Minister for Agriculture announced in June

1996 that he was in favour of introduction of futures trading both domestic and

international. Further, a new coffee futures exchange (The Coffee Futures Exchange of

India) is being started at Bangalore. In August, 1997, the Central Government proposed

that Indian companies with commodity price exposures should be allowed to use foreign

futures and option markets. The trend is not confined to the commodity markets alone, it

has initiated in financial futures too.

The Reserve Bank of India set up the Sodhani Expert Group which recommended major

liberalization of the forward exchange market and had urged the setting up of rupee based

derivatives in financial instruments. The RBI accepted several of its recommendations in

August, 199629. A landmark step taken in this regard when the Securities and Exchange

Board of India (SEBI) appointed a Committee named the Dr. LC. Gupta Committee

(LCGC) by its resolution, dated November 18, 1996in order to develop appropriate

regulatory framework for derivatives trading in India. While the Committee's focus was

on equity derivatives but it had maintained a broad perspective of derivatives in general.

The Board of SEBI, on May 11, 1998, accepted the recommendations of the Dr. L C.

Gupta Committee and approved introduction of derivatives trading in India in the phased

manner30. The recommendation sequence is stock, index futures, index options and

options on stocks. The Board also approved the 'Suggestive Bye-Laws' recommended by

29O.P Sodhani, (Chairman) et al, Report of Expert Group on Foreign Exchange Markets In India, RBI, (June 1995) 30 Reforms in Secondary Markets in India, Working paper from National stock exchange (NSE), India, (2000)

36

the Committee for regulation and control of trading and settlement of derivatives’

contracts in India. Subsequently, the SEBI appointed J.R. Verma Committee to look into

the operational aspects of derivatives markets. To remove the road-block of non-

recognition of derivatives as securities under Securities Contract Regulation Act, the

Securities Law (Amendment) Bill, 1999 was introduced to bring about the much needed

changes. Accordingly, in December, 1999, the new framework has been approved and

'Derivatives' have been accorded the status of 'Securities', however, due to certain

completion of formalities, the launch of the Index Futures was delayed by more than two

years. In June, 2000, the National Stock Exchange and the Bombay Stock Exchange

started stock index based futures trading in India. Further, the growth of this market did

not take off as” anticipated. This is mainly attributed to the low awareness about the

product and mechanism among the market players and investors. The volumes, however,

are gradually picking up due to active interest of the institutional investors.

2.5 MAJOR RECOMMENDATIONS OF Dr. L.C. GUPTA COMMITTEE31

Before discussing the emerging structure of derivatives markets in India, let us have a

brief view of the important recommendations made by the Dr. LC. Gupta Committee on

the introduction of derivatives markets in India. These are as under:

1. The Committee is strongly of the view that there is urgent need of introducing of

financial derivatives to facilitate market development and hedging in a most cost-

efficient way against market risk by the participants such as mutual funds and

other investment institutions.

2. There is need for equity derivatives, interest rate derivatives and currency

derivatives.

3. Futures trading through derivatives should be introduced in phased manner

starting with stock index futures, which will be followed by options on index and

31 L. C, Gupta, (Chairman) et al, Report of the Committee on Regulatory Framework for Derivatives Trading, SEBI, (September 1997 and March 1998.)

37

later options on stocks. It will .enhance the efficiency and liquidity of cash

markets in equities through arbitrage process.

4. There should be two-level regulation (regulatory framework for derivatives

trading), i.e., exchange level and SEBI level. Further, there must be considerable

emphasis on self regulatory competence of derivative exchanges under the overall

supervision and guidance of SEBI.

5. The derivative trading should be initiated on a separate segment of existing stock

exchanges having an independent governing council. The number of the trading

members will be limited to 40 percent of the total number. The Chairman of the

governing council will not be permitted to trade on any of the stock exchanges.

6. The settlement of derivatives will be through an independent clearing

Corporation/Clearing house, which will become counter-party for all trades or

alternatively guarantees the settlement of all trades. The clearing corporation will

have adequate risk containment measures and will collect margins through EFT.

7. The derivatives exchange will have on-line-trading and adequate surveillance

systems. It will disseminate trade and price information on real time basis through

two information vending networks. It should inspect 100 percent of members

every year.

8. There will be complete segregation of client money at the level of trading/clearing

member and even at the level of clearing corporation.

9. The trading and clearing member will have stringent eligibility conditions. At

least two persons should have passed the certification programme approved by the

SEBI.

10. The clearing members should deposit minimum Rs 50 lakh with clearing

corporation and should have a net worth of Rs 3 crore.

11. Removal of the regulatory prohibition on the use of derivatives by mutual funds

while making the trustees responsible to restrict the use of derivatives by mutual

funds only to hedging and portfolio balancing and not for specification.

12. The operations of the cash market on which the derivatives market will be based,

needed improvement in many respects.

38

13. Creation of a Derivation Cell, a Derivative Advisory Committee, and Economic

Research Wing by SEBI.

14. Declaration of derivatives as 'securities' under Section 2 (h) of the SCRA and

suitable amendments in the notification issued by the Central Government in

June, 1969under Section 16of the S()RJl g'

The SEBI Board approved the suggested Bye-Laws recommended by the LC. Gupta

Committee for regulation and control of trading and settlement of derivatives contracts.

2.5.1 Explanation of some important terms used in the committee's

recommendations

Derivatives concept: A derivative product, or simply 'derivative', is to be sharply

distinguished from the underlying cash asset. Cash asset is the asset which is bought or

sold in the cash market on normal delivery terms. Thus, the term 'derivative' indicates

that it has no independent value. It means that its value is entirely 'derived' from the value

of the cash asset. The main point is that derivatives are forward or futures contracts, i.e.,

contracts for delivery and payment on a-specified future date. They are essentially to

facilitate hedging of price risk of the cash asset. In the market term, they are called as

'Risk Management Tools'32.

Financial derivatives- Types: Though the Committee was mainly concerned with equity

based derivatives but it has tried to examine the need for derivatives in a broad

perspective for creating a better understanding and showing inter-relationship. Broadly,

there are three kinds of price risk exposed to a financial transaction33, viz.

1. Exchange rate risk, a position arisen in a foreign currency transaction like import,

export, foreign loans, foreign investment, rendering foreign services, etc.

32 T.V.,Somanathan, Derivatives, (New Delhi, Tata McGraw-Hill, 2000), pp. 238-239. 33 Kalmakar, D.S., ‘Regulation and Policy Issues for Derivatives In India’, Derivative Markets India, (New Delhi, Tata McGraw-Hill, 2003)

39

2. Interest rate risk, as in the case of fixed-income securities, like treasury bond

holdings whose market price could fall heavily if interest rates shot up

3. Equities', 'market risk', also called 'systematic risk'-a risk which cannot be

diversified away because stock market as a whole may go up or down from time

to time

The above said classification indicates towards the emergence of three types of financial

derivatives namely currency futures, interest rate futures and equity futures. As both

forward contracts and futures contracts can be used for hedging, but the Committee

favors the introduction of futures wherever possible.

Forward contracts are presently being used in India to provide forward cover against

exchange rate risk. Currency and interest rate futures lie in the sphere of Reserve Bank of

India (RBI)34.

The Dr. L C. Gupta Committee recognizes that the basic principles underlying the

organization, control and regulation of markets of all kinds of financial futures are the

more or less same and that the trading infrastructure may be common or separate,

partially or wholly. The Committee is of further opinion that there must be a formal

mechanism for coordination between SEBI and RBI in respect of financial derivatives

markets so that all kinds of overlapping of jurisdiction in respect of trading mechanism

are removed.

Financial derivatives markets in India have been developed so far in three important

instruments like equity, interest and currency. First one is regulated by the SEBI, whereas

other two are controlled by the RBI. The markets of these instruments are in their

preliminary stage.

34 R. V. Gupta,. (Chairman) et al, Report of the committee on ‘Hedging through International Commodity Exchanges’, RBI, (November 1997)

40

2.6 FACTORS CONTRIBUTING TO THE GROWTH OF DERIVATIVES:

Factors contributing to the explosive growth of derivatives are price volatility,

globalization of the markets, technological developments and advances in the financial

theories.

2.6.1 Price Volatility

A price is what one pays to acquire or use something of value. The objects having value

maybe commodities, local currency or foreign currencies. The concept of price is clear to

almost everybody when we discuss commodities. There is a price to be paid for the

purchase of food grain, oil, petrol, metal, etc. the price one pays for use of a unit of

another persons money is called interest rate. And the price one pays in one’s own

currency for a unit of another currency is called as an exchange rate.

Prices are generally determined by market forces. In a market, consumers have ‘demand’

and producers or suppliers have ‘supply’, and the collective interaction of demand and

supply in the market determines the price. These factors are constantly interacting in the

market causing changes in the price over a short period of time. Such changes in the price

are known as ‘price volatility’. This has three factors: the speed of price changes, the

frequency of price changes and the magnitude of price changes35.

The changes in demand and supply influencing factors culminate in market adjustments

through price changes. These price changes expose individuals, producing firms and

governments to significant risks. The break down of the BRETTON WOODS agreement

brought and end to the stabilizing role of fixed exchange rates and the gold convertibility

of the dollars. The globalization of the markets and rapid industrialization of many

underdeveloped countries brought a new scale and dimension to the markets. Nations that

were poor suddenly became a major source of supply of goods. The Mexican crisis in the

35 Pati, Pratap Chandra and Padhan, Purna Chandra, “Information, Price Discovery and Causality in the Indian Stock Index Futures Market”, Journal Of Financial Risk Management, VI, 3 & 4, (2009), 7-10.

41

south east-Asian currency crisis of 1990’s has also brought the price volatility factor on

the surface. The advent of telecommunication and data processing bought information

very quickly to the markets. Information which would have taken months to impact the

market earlier can now be obtained in matter of moments. Even equity holders are

exposed to price risk of corporate share fluctuates rapidly.

This price volatility risk pushed the use of derivatives like futures and options

increasingly as these instruments can be used as hedge to protect against adverse price

changes in commodity, foreign exchange, equity shares and bonds.

2.6.2 Globalisation of Markets

Earlier, managers had to deal with domestic economic concerns; what happened in other

part of the world was mostly irrelevant. Now globalization has increased the size of

markets and as greatly enhanced competition .it has benefited consumers who cannot

obtain better quality goods at a lower cost. It has also exposed the modern business to

significant risks and, in many cases, led to cut profit margins

In Indian context, south East Asian currencies crisis of 1997 had affected the

competitiveness of our products vis-à-vis depreciated currencies. Export of certain goods

from India declined because of this crisis. Steel industry in 1998 suffered its worst set

back due to cheap import of steel from south East Asian countries. Suddenly blue chip

companies had turned in to red. The fear of china devaluing its currency created

instability in Indian exports. Thus, it is evident that globalization of industrial and

financial activities necessitates use of derivatives to guard against future losses36. This

factor alone has contributed to the growth of derivatives to a significant extent.

2.6.3 Technological Advances

A significant growth of derivative instruments has been driven by technological break

through. Advances in this area include the development of high speed processors,

36 Hansda, Sanjiv K. and Partha Ray , ‘BSE and Nasdaq: Globalisation, Information Technology and Stock Prices,’ Economic and Political Weekly, VII, 5, (February 2, 2002), 459-67.

42

network systems and enhanced method of data entry. Closely related to advances in

computer technology are advances in telecommunications. Improvement in

communications allow for instantaneous world wide conferencing, Data transmission by

satellite. At the same time there were significant advances in software programmed

without which computer and telecommunication advances would be meaningless. These

facilitated the more rapid movement of information and consequently its instantaneous

impact on market price.

Although price sensitivity to market forces is beneficial to the economy as a whole

resources are rapidly relocated to more productive use and better rationed overtime the

greater price volatility exposes producers and consumers to greater price risk. The effect

of this risk can easily destroy a business which is otherwise well managed. Derivatives

can help a firm manage the price risk inherent in a market economy. To the extent the

technological developments increase volatility, derivatives and risk management products

become that much more important.

2.6.4 Advances in Financial Theories

Advances in financial theories gave birth to derivatives. Initially forward contracts in its

traditional form, was the only hedging tool available. Option pricing models developed

by Black and Scholes in 1973 were used to determine prices of call and put options. In

late 1970’s, work of Lewis Edeington extended the early work of Johnson and started the

hedging of financial price risks with financial futures. The work of economic theorists

gave rise to new products for risk management which led to the growth of derivatives in

financial markets37.

The above factors in combination of lot many factors led to growth of derivatives

instruments.

37 John C. Hull, Introduction to Futures and Options Market, (New Delhi, Prentice Hall of India,2004 ) pp. 295-97.

43

2.7 BENEFITS OF DERIVATIVES IN INDIA

During December, 1995, the NSE applied to the SEBI for permission to undertake

trading in stock index futures. Later SEBI appointed the Dr. L C. Gupta Committee,

which conducted a survey amongst market participants and observed an overwhelming

interest in stock index futures, followed by other derivatives products. The LCGC

recommended derivatives trading in the stock exchanges in a phased manner. It is in this

context, SEBI permitted both NSE and BSE in the year 2000 to commence trading in

stock index futures. The question, therefore, becomes relevant-what are the benefits of

trading in Derivatives for the country and in particular for choosing stock index futures as

the first preferred product? Following are some benefits of derivatives:

1. India's financial market system will strongly benefit from smoothly functioning

index derivatives markets.

2. Internationally, the launch of derivatives has been associated with substantial

improvements in market quality on the underlying equity market. Liquidity and

market efficiency on India's equity market will improve once the derivatives

commence trading.

3. Many risks in the financial markets can be eliminated by diversification. Index

derivatives are special in so far as they can be used by the investors to protect

themselves from the one risk in the equity market that cannot be diversified away,

i.e., a fall in the market index. Once the investors use index derivatives, they will

suffer less when fluctuations in the market index take place.

4. Foreign investors coming into India would be more comfortable if the hedging

vehicles routinely used by them worldwide are available to them.

5. The launch of derivatives is a logical next step in the development of human

capital in India. Skills in the financial sector have grown tremendously in the last

few years. Thanks to the structural changes in the market, the economy is now

ripe for derivatives as the next area for addition of skills.

44

2.8 DEFINITION OF FINANCIAL DERIVATIVE

Before explaining the term financial derivative, let us see the dictionary meaning of

'derivative’. Webster’s Ninth New Collegiate Dictionary (1987) states derivatives as:

1. A word formed by derivation. It means, this word has been arisen by derivation.

2. Something derived; it means that some things have to be derived or arisen out of

the underlying variables. For example, financial derivative is an instrument indeed

derived from the financial market.

3. The limit of the ratio of the change is a function to the corresponding change in its

independent variable. This explains that the value of JIl1ancial derivative will

change as per the change in the value of the underlying financial instrument.

4. A chemical substance related structurally to another substance, and theoretically

derivable from it. In other words, derivatives are structurally related to other

substances.

5. A substance that can be made from another substance in one or more steps. In

case of .financial derivatives, they are derived from a combination of cash market

instruments or other derivative instruments.

For example, you have purchased gold futures on May 2003 for delivery in August 2003.

The price of gold on May 2003 in the spot market is Rs 4500 per 10 grams and for

futures delivery in August 2003 is Rs 4800 per 10 grams. Suppose in July 2003 the spot

price of the gold changes and increased to Rs 4800 per 10 grams. In the same line value

of financial derivatives or gold futures will also change.

From the above, the term derivatives may be termed as follows: The term "Derivative"

indicates that it has no independent value, i.e., its value is entirely derived from the value

of the underlying asset38. The underlying asset can be securities, commodities, bullion,

currency, livestock or anything else. In other words, derivative means forward, futures,

38 John C Hull, Introduction to Futures and Options Market,(New Delhi, Prentice Hall of India, 2004), pp. 3-4.

45

option or any other hybrid contract of predetermined fixed duration, linked for the

purpose of contract fulfillment to the value of a specified real or financial asset or to an

index of securities.

The Securities Contracts (Regulation) Act 1956 defines "derivative" as under:

"Derivative" includes

1. Security derived from a debt instrument, share, loan whether secured or

unsecured, risk instrument or contract for differences or any other form of

security.

2. A contract which derives its value from the prices, or index of prices of

underlying securities.

The above definition conveys that

1. The derivatives are financial products.

2. Derivative is derived from another financial instrument/contract called the

underlying. In the case of Nifty futures, Nifty index is the underlying. A

derivative derives its value from the underlying assets. Accounting Standard

SFAS133 defines a derivative as, 'a derivative instrument is a financial derivative

or other contract with all three of the following characteristics:

(i) It has (1) one or more underlying, and (2) one or more notional amount or

payments provisions or both. Those terms determine the amount of the settlement

or settlements.

(ii) It requires no initial net investment or an initial net investment that is smaller

than would be required for other types of contract that would be expected to have

a similar response to changes in market factors.

(iii) Its terms require or permit net settlement. It can be readily settled net by a

means outside the contract or it provides for delivery of an asset that puts the

recipients in a position not substantially different from) net settlement.

46

In general, from the aforementioned, derivatives refer to securities or to contracts that

derive from another-whose value depends on another contract or assets. As such the

financial derivatives are financial instruments whose prices or values are derived from the

prices of other underlying financial instruments or financial assets. The underlying

instruments may be a equity share, stock, bond, debenture, treasury bill, foreign currency

or even another derivative asset. For example, a stock option's value depends upon the

value of a stock on which the option is written. Similarly, the value of a treasury bill of

futures contracts or foreign currency forward contract will depend upon the price or value

of the underlying assets, such as Treasury bill or foreign currency. In other words, the

price of the derivative is not arbitrary rather it is linked or affected to the price of the

underlying asset that will automatically affect the price of the financial derivative39. Due

to this reason, transactions in derivative markets are used to offset the risk of price

changes in the underlying assets. In fact, the derivatives can be formed on almost any

variable, for example, from the price of hogs to the snow falling at a certain ski resort.

The term financial derivative relates with a variety of financial instruments which include

stocks, bonds, treasury bills, interest rate, foreign currencies and other hybrid securities.

Financial derivatives include futures, forwards, options, swaps, etc. Futures contracts are

the most important form of derivatives, which are in existence long before the term

'derivative' was coined. Financial derivatives can also be derived from a combination of

cash market instruments or other financial derivative instruments. In fact, most of the

financial derivatives are not revolutionary new instruments rather they are merely

combinations of older generation derivatives and/or standard cash market instruments.

In the 1980s,the financial derivatives were also known as off-balance sheet instruments

because no asset or liability underlying the contract was put on the balance sheet as such.

Since the value of such derivatives depend upon the movement of market prices of the

underlying assets, hence, they were treated as contingent asset or liabilities and such

transactions and positions in derivatives were not recorded on the balance sheet.

39 M T, Raju and Kiran, Karande, ‘Price Discovery and Volatility on NSE futures Market’, www.sebi.com, Working Paper Series No.7, (2003)

47

However, it is a matter of considerable debate whether off-balance sheet instruments

should be included in the definition of derivatives. Which item or product given in the

balance sheet should be considered for derivative is a debatable issue. .

In brief, the term financial market derivative can be defined as a treasury capital market

instrument which is derived from, or bears a close relation to a cash instrument or another

derivative instrument. Hence, financial derivatives are financial instruments whose prices

are derived from the prices of other financial instruments.

2.9 FEATURES OF A FINANCIAL DERIVATIVE

As observed earlier, a financial derivative is a financial instrument whose value is derived

from the value of an underlying asset; hence, the name 'derivative' came into existence.

There are a variety of such instruments which are extensively traded in the financial

markets all over the world, such as forward contracts, futures contracts, call and put

options, swaps, etc. A more detailed discussion of the properties of these contracts will be

given later part of this lesson. Since each financial derivative has its own unique features,

in this section, we will discuss some of the general features of a simple financial

derivative instrument.

The basic features of the derivative instrument can be drawn from the general definition

of a derivative irrespective of its type. Derivatives or derivative securities are future

contracts which are written between two parties (counter parties) and whose value are

derived from the value of underlying widely held and easily marketable assets such as

agricultural and other physical (tangible) commodities, or short term and long term

financial instruments, or intangible things like weather, commodities price index

(inflation rate), equity price index, bond price index, stock market index, etc. Usually, the

counter parties to such contracts are those other than the original issuer (holder) of the

48

underlying asset40. From this definition, the basic features of a derivative may be stated as

follows:

1. A derivative instrument relates to the future contract between two parties. It

means there must be a contract-binding on the underlying parties and the same to

be fulfilled in future. The future period may be short or long depending upon the

nature of contract, for example, short term interest rate futures and long term

interest rate futures contract.

2. Normally, the derivative instruments have the value which derived from the

values of other underlying assets, such as agricultural commodities, metals,

financial assets, intangible assets, etc. Value of derivatives depends upon the

value of underlying instrument and which changes as per the changes in the

underlying assets, and sometimes, it may be nil or zero. Hence, they are closely

related.

3. In general, the counter parties have specified obligation under the derivative

contract. Obviously, the nature of the obligation would be different as per the type

of the instrument of a derivative. For example, the obligation of the counter

parties, under the different derivatives, such as forward contract, future contract,

option contract and swap contract would be different.

4. The derivatives contracts can be undertaken directly between the two parties or

through the particular exchange like financial futures contracts. The exchange-

traded derivatives are quite liquid and have low transaction costs in comparison to

tailor-made contracts. Example of exchange traded derivatives are Dow Jones,

S&P 500, Nikki 225, NIFTY option, S&P Junior that are traded on New York

Stock Exchange, Tokyo Stock Exchange, National Stock Exchange, Bombay

Stock Exchange and so on.

5. In general, the financial derivatives are carried off-balance sheet. The size of the

derivative contract depends upon its notional amount. The notional amount is the

amount used to calculate the payoff. For instance, in the option contract, the

40 Dheeraj, Misra, and Misra Sangeeta D , ‘Growth of Derivatives in the Indian Stock Market’, The Indian Journal of Economics, LXXXV, 340, (2005), 45-47.

49

potential loss and potential payoff, both may be different from the value of

underlying shares, because the payoff of derivative products differs from the

payoff that their notional amount might suggest.

6. Usually, in derivatives trading, the taking or making of delivery of underlying

assets is not involved; rather underlying transactions are mostly settled by taking

offsetting positions in the derivatives themselves. There is, therefore, no effective

limit on the quantity of claims, which can be traded in respect of underlying

assets.

7. Derivatives are also known as deferred delivery or deferred payment instrument.

It means that it is easier to take short or long position in derivatives in comparison

to other assets or securities. Further, it is possible to combine them to match

specific, i.e., they are more easily amenable to financial engineering41.

8. Derivatives are mostly secondary market instruments and have little usefulness in

mobilizing fresh capital by the corporate world, however, warrants and

convertibles are exception in this respect.

9. Although in the market, the standardized, general and exchange-traded derivatives

are being increasingly evolved, however, still there are so many privately

negotiated customized, over-the-counter (OTC) traded derivatives are in

existence. They expose the trading parties to operational risk, counter-party risk

and legal risk. Further, there may also be uncertainty about the regulatory status

of such derivatives.

10. Finally, the derivative instruments, sometimes, because of their off-balance sheet

nature, can be used to clear up the balance sheet. For example, a fund manager

who is restricted from taking particular currency can buy a structured note whose

coupon is tied to the performance of a particular currency pair42.

41 Jegadeesh Narsimham and Avanidhar Subrahmanyam , ‘Effects of the Introduction of the S&P 500 Index Futures Contract on Underlying Stocks’, Journal Of Business, 66, (2003),171-187. 42 A N, Sah and A A, Kumar, ‘Price Discovery in Cash and Futures Market: The case of S&P Nifty and Nifty Futures’, The Icfai Journal of Applied Finance, 12, 4, (2006), 55-63.

50

2.10 TYPES AND CLASSIFICATIONS OF DERIVATIVES

In the past section, it is observed that financial derivatives are those assets whose value is

determined by the value of some other assets, called as the underlying. Presently, there

are bewilderingly complex varieties of derivatives already in existence, and the markets

are innovating newer and newer ones continuously.

For example, various types of financial derivatives based on their different properties

like, plain, simple or straightforward, composite, joint or hybrid, synthetic, leveraged,

mildly leveraged, customized or OTC traded, standardized or organized exchange traded,

etc. are available in the market. Due to complexity in nature, it is very difficult to classify

the financial derivatives, so in the present context, the basic financial derivatives which

are popular in the market have been described in brief. The details of their operations,

mechanism and trading, will be discussed in the forthcoming respective chapters. In

simple form, the derivatives can be classified into different categories which are shown in

the Figure.

One form of classification of derivative instruments is between commodity derivatives

and financial derivatives. The basic difference between these is the nature of the

underlying instrument or asset. In a commodity derivatives, the underlying instrument is

a commodity which may be wheat, cotton, pepper, sugar, jute, turmeric, corn, soyabeans,

crude oil, natural gas, gold, silver, copper and so on. In a financial derivative, the

underlying instrument may be treasury bills, stocks, bonds, foreign exchange, stock

index, gilt-edged securities, cost of living index, etc43. It is to be noted that financial

derivative is fairly standard and there are no quality issues whereas in commodity

derivative, the quality may be the underlying matters. However, the distinction between

these two from structure and functioning point of view, both are almost similar in nature.

43T V, Somanathan, ‘Derivatives’, (New Delhi, Tata McGraw-Hill, 1999), pp. 7-8.

51

Derivatives

Future Option Forward Swaps

Figure 2.1 - TYPES OF DERIVATIVES MARKET

Exchange Traded Derivatives Over The Counter Derivatives

National Stock Bombay Stock Commodity Exchanges

Exchange Exchange

Index Future Index option Stock option Stock future

Figure 2.2 - TYPES OF DERIVATIVES

52

Another way of classifying the financial derivatives is into basic and complex

derivatives. In this, forward contracts, futures contracts and option contracts have been

included in the basic derivatives whereas swaps and other complex derivatives are taken

into complex category because they are built up from either forwards/futures or options

contracts, or both. In fact, such derivatives are effectively derivatives of derivatives.

2.11 USES OF DERIVATIVES

Derivatives are supposed to provide the following services:

1. One of the most important services provided by the derivatives is to control,

avoid, shift and manage efficiently different types of risks through various

strategies like hedging, arbitraging, spreading, etc. Derivatives assist the holders

to shift or modify suitably the risk characteristics of their portfolios44. These are

specifically useful in highly volatile financial market conditions like erratic

trading, highly flexible interest rates, volatile exchange rates and monetary chaos.

2. Derivatives serve as barometers of the future trends in prices which result in the

discovery of new prices both on the spot and futures markets. Further, they help in

disseminating different information regarding the futures markets trading of

various commodities and securities to the society which enable to discover or

form suitable or correct or true equilibrium prices in the markets. As a result, they

assist in appropriate and superior allocation of resources in the society45.

3. As we see that in derivatives trading no immediate full amount of the transaction

is required since most of them are based on margin trading. As a result, large

number of traders, speculators arbitrageurs operates in such markets. So,

derivatives trading enhance liquidity and reduce transaction costs in the markets

for underlying assets. 44 Robert, Whaley, Derivatives: Markets, Valuation and Risk Management, (New York, John Wiley & Sons, 2006), pp. 26-28. 45 K N, Mukherjee and R K, Mishra, ‘Lead-Lag Relationship between Equities and Stock Index Futures Market and Its Variation around Information Release: Empirical Evidence from India’, www.nseindia.com. (2006)

53

4. The derivatives assist the investors, traders and managers of large pools of funds

to devise such strategies so that they may make proper asset allocation increase

their yields and achieve other investment goals.

5. It has been observed from the derivatives trading in the market that the derivatives

have smoothen out price fluctuations, squeeze the price spread, integrate price

structure at different points of time and remove gluts and shortages in the markets.

6. The derivatives trading encourage the competitive trading in the markets,

different risk taking preference of the market operators like speculators, hedgers,

traders, arbitrageurs, etc. resulting in increase in trading volume in the country.

They also attract young investors, professionals and other experts who will act as

catalysts to the growth of financial markets46.

7. Lastly, it is observed that derivatives trading develop the market towards

'complete markets'. Complete market concept refers to that situation where no

particular investors be better of than others, or patterns of returns of all additional

securities are spanned by the already existing securities in it, or there is no further

scope of additional security.

2.12 CRITIQUES OF DERIVATIVES

Besides from the important services provided by the derivatives, some experts have

raised doubts and have become critique on the growth of derivatives. They have warned

against them and believe that the derivatives will cause to de-stabilization, volatility,

financial excesses and oscillations in financial markets. It is alleged that they assist the

speculators in the market to earn lots of money, and hence, these are exotic instruments.

In this section, a few important arguments of the critiques against derivatives have been

discussed.

46 N D Vohara, and B R Bagri, Futures and Options, (New Delhi, Tata McGraw-Hill, 2003), pp. 35-36.

54

2.12.1 Speculative and gambling motives

One of most important arguments against the derivatives is that they promote speculative

activities in the market. It is witnessed from the financial markets throughout the world

that the trading volume in derivatives have increased in multiples of the value of the

underlying assets and hardly one to two percent derivatives are settled by the actual

delivery of the underlying assets. As such speculation has become the primary purpose of

the birth, existence and growth of derivatives. Sometimes, these speculative buying and

selling by professionals and amateurs adversely affect the genuine producers and

distributors.

Some financial experts and economists believe that speculation brings about a better

allocation of supplies overtime, reduces the fluctuations in prices, make adjustment

between demand and supply, removes periodic gluts and shortages, and thus, brings

efficiency to the market47. However, in actual practice, above such agreements are \ not

visible. Most of the speculative activities are 'professional speculation' or 'movement

trading' which lead to destabilization in the market. Sudden and sharp variations in prices

have been caused due to common, frequent and widespread consequence of speculation.

2.12.2 Increase in risk

The derivatives are supposed to be efficient tool of risk management in the market. In

fact this is also one sided argument. It has been observed that the derivatives market-

specially OTC markets, as particularly customized, privately managed and negotiated,

and thus, they are highly risky. Empirical studies in this respect have shown that

derivatives used by the banks have not resulted in the reduction in risk, and rather these

have raised of new types of risk. They are powerful leveraged mechanism used to create

47 T V, Somanathan, Derivatives, (New Delhi, Tata McGraw-Hill,1999), pp 24-27.

55

risk48. It is further argued that if derivatives are risk management tool, then why

'government securities, a riskless security, are used for trading interest rate futures which

is one of the most popular financial derivatives in the world.

2.12.3 Instability of the financial system

It is argued that derivatives have increased risk not only for their users but also for the

whole financial system. The fears of micro and macro financial crisis have caused to the

unchecked growth of derivatives which have turned many market players into big losers.

The malpractices, desperate behaviour and fraud by the users of derivatives have

threatened the stability of the financial markets and the financial system.

2.12.4 Price instability49

Some experts argue in favour of the derivatives that their major contribution is toward

price stability and price discovery in the market whereas some others have doubt about

this. Rather they argue that financial derivatives are not new; they have been around for

years. A description of the first know option contract can be found in Aristotle's writing

tells philosopher from Mitetus who developed a financial device, which involves a

principal of universal application. People reproved Thales, syning that his lack of wealth

was proof that philosophy was a useless occupation and of no practical value.

But Thales knew what he was doing and made plans to prove to others his wisdom and

intellect. Thales had great skill in forecasting and predicted that the olive harvest would

be exceptionally good the next autumn. Confident in his prediction, he made agreements

with area olive-press owners to deposit what little money he had with them to guarantee

him exclusive use of their olive presses when the harvest was ready. Thales successfully

negotiated low prices because the harvest was in the futures and no one knew whether the 48 S. L, Gupta, Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), pp. 16-17. 49 S. L, Gupta, Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), pp. 17-18. .

56

harvest would be plentiful or pathetic and because the olive-press owners were willing to

hedge against the possibility of a poor yield. Aristotle's story about Thales ends as one

might guess: "when the harvest-time came, and many [presses] were wanted all at once

and of a sudden, he let them out at any rate which he pleased, and made a quantity of

money. Thus he showed the world that philosophers can easily be rich if they like, but

that their ambition is of another sort." So Thales exercised the first known option

contracts some 2,500 years ago. He was not obliged to exercise the option. If the olive

harvest had not been good, Thales could have let the option contracts expire unused and

limited his loss to the original price paid for the option.

Most financial derivatives traded today are the "plain vanilla" variety the simplest form of

a financial derivatives that are much difficult to measure, manage, and understand. For

those instruments, the measurement and control of risk can be far more complicated,

creating the increased possibili'ty of unforeseen losses.

Wall Street's "rocket scientist" are continually creating new, complex, sophisticated

financial derivative products. However, those products are all built on foundation of the

four basis types of derivatives. Most of the newest innovations are designed to hedge

complex risks in an effort to reduce future uncertainties and mange risks more

effectively. But the newest innovations require a firm understanding of the tradeoff of

risks and rewards. To that end, derivative users should establish a guiding set of

principles to provide a framework for effectively managing and controlling financial

derivative activities. Those principles should focus on the role of senior management,

valuation and market risk argument, credit measurement and management, enforceability

operating systems and controls and accounting and disclosure of risk-management

positions.

57

2.13 MYTHS ABOUT DERIVATIVES

3.13.1 Myth number 1

"Derivatives are purely speculative, highly leveraged instrument"

Put another way. This myth is that "derivatives" is a fancy name for gambling. Has

speculative trading of derivative products fuelled the rapid growth in their use? Are

derivatives used only to speculate on the direction of interest rates or currency exchange

rates? Of course, not, indeed, the explosive use of financial derivative products in recent

years was brought about by three primary forces: more volatile markets, deregulation and

new technologies50.

The turning point seems to have occurred in the early 1970s with the breakdown of the

fixed-rate international currency exchange regime, which was established at the

1944conference at Bretton Woods and maintained by the International Monetary Fund.

Since then currencies have floated freely. Accompanying that development was the

gradual removal of government-established interest-rate ceilings when Regulation Q

interest-rate restrictions were phased out. Not long afterward came inflationary oilprice

shocks and wild interest-rate fluctuations. In sum, financial markets were more volatile

than at any time since the Great Depression. Banks and other financial intermediaries

responded to the new environment by developing financial risk management products

designed to better control risk. The first were simple foreign exchange forwards that

obligated one counterpart to buy, and the other to sell, a fixed amount of currency at an

agreed date in the future51. By entering into a foreign exchangeforward contract,

customers could offset the risk that large movements in foreign exchange rates would

destroy the economic viability of their overseas projects. Thus, derivatives were

originally intended to be used to effectively hedge certain risks; and, in fact, that was the

key that unlocked their explosive development. 50 S. L, Gupta, Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), p. 21 51 Neilsen, Lars Tyge, ‘Pricing and Hedging Derivatives Securities, (London, Oxford University Press, 1999), pp. 23-25.

58

Beginning in the early 1980s, a host of new competitors accompanied the deregulation of

financial markets, and the arrival of powerful but inexpensive personal computers

ushered in new ways to analyze information and break down risk into component parts.

To serve customers better, financial intermediaries offered an ever-increasing number of

novel products designed to more effectively manage and control financial risks. New

technologies quickened the pace of innovation and provided banks with

superiormethodsfortrackingandsimulatingtheirownderivativesportfolios. .


"The enormous size of the financial derivatives market dwarfs bank capital, thereby

making derivatives trading an unsafe and unsound banking practice"

The financial derivatives market's worth is regularly reported as more than $20 trillion.

That estimate dwarfs not only bank capital but also the nation's $7 trillion annual gross

domestic product. Those often quoted figures are notional amounts. For derivatives,

notional principal is the amount on which interest and other payments are based. Notional

principal typically does not change hands; it is simply a quantity used to calculate

payments52.

While notional principal is the most commonly used volume measure in derivatives

markets, it is not an accurate measure of credit exposure. A useful proxy for the actual

exposure of derivative instruments is replacement-cost credit exposure. That exposure is

the cost of replacing the contract at current market values should the counterpart default

before the settlement date.

For the 10 largest derivatives players among US bank holding companies, derivative

credit exposure averages 15 percent of total assets. The average exposure is 49 percent of

assets for those banks' loan portfolios. In other words, if those 10 banks lost 100 percent

52 S. L, Gupta,. Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), pp. 17-20.

59

on their loans, the loss would be more than three times greater than it would be if they

had to replace all of their derivative contracts.

Derivatives also help to improve market efficiencies because risks can be isolated and

sold to those who are willing to accept them at the least cost. Using derivatives breaks

risk into pieces that can be managed independently. Corporations can keep the risks they

are most comfortable managing and transfer those they do not want to other companies

that are more willing to accept them. From a market oriented perspective, derivatives

offer the free trading of financial risks.

The viability of financial derivatives rests on the principle of comparative advantage-that

is, the relative cost of holding specific risks. Whenever comparative advantages exist,

trade can benefit all parties involved. And financial derivatives allow for the free trading

of individual risk components.


"Only large multinational corporations and large banks have a purpose for using

derivatives"

Very large organizations are the biggest users of derivative instruments. However, firms

of all sizes can benefit from using them. For example, consider a small regional bank

(SRB) with total assets of $5 million. The SRB has a loan portfolio composed primarily

of fixed-rate mortgages, a portfolio of government securities, and interest-bearing

deposits that are often repriced. Two illustrations of how SRBs can use derivatives to

hedge risks are:

First, rising interest rates will negatively affect prices in the SRB's $1 million securities

portfolio. But by selling short a $1 million treasury-bond futures contract, the SRB can

effectively hedge against that interest-rate risk and smooth its earnings stream in a

volatile market. If interest rates went higher, the SRB would be hurt by a drop in value of

its securities portfolio, but that loss would be offset by a gain from its derivative contract.

60

Similarly, if interest nites fell, the bank would gain from the increase in value of its

securities portfolio but would record a loss from its derivative contract. By entering into

derivatives contracts, the SRB can lock in a guaranteed rate of return on its securities

portfolio and not be as concerned about interest-rate volatility53.

The second illustration involves a swap contract. As in the first illustration, rising interest

rates will harm the SRB because it receives fixed cash flows on its loan portfolio and

must pay variable cash flows for its deposits. Once again, the SRB can hedge against

interest-rate risk by entering into a swap contract with a dealer to pay fixed and receive

floating payments.


"Financial derivatives are simply the latest risk-management fad"

Financial derivatives are important tools that can help organizations to meet their specific

risk management objectives. As is the case with all tools, it is important that the user

understand the tool's intended function and that are necessary to undertake various

purposes. What kinds of derivative instruments and trading strategies are most

appropriate? How will those instruments perform if there is a large increase or decrease

in interest rates? How will those instruments perform if there are wild fluctuations in

exchange rates? Without a clearly defined risk-management strategy, use of financial

derivatives can be dangerous. It can threaten the accomplishment of a firm's long-range

objectives and result in unsafe and unsound practices that could lead to the organization's

insolvency. But when used wisely, financial deIivatives can increase shareholder value

by providing a means to better control a firm's risk exposures and cash flows. Clearly,

derivatives are here to stay.We are well on our way to truly global fina!1cialmarkets that

will continue to develop new financial innovations to improve risk-management


61

practices. Financial derivatives are not the latest risk-management fad54. They are

important to'Olsfor helping organizations to better manage their risk exposures.


"Derivatives take money out of productive processes and never put anything back"

Financial derivatives, by reducing uncertainties, make it possible for corporations to

initiate productive activities that might not otherwise be pursued. For example, a

company may want to build a manufacturing facility in the United Slates but is concerned

about the project's overall cost because of exchange rate volatility between the dollar. To

ensure that the company will have the cash available when it is needed for investment,

the manufacturer should devise a prudent risk-management strategy that is in harmony

with its broader corporate objective of building a manufacturing facility in the United

States. As part of that strategy, the firm should use financial derivatives to hedge against

foreign exchange risk. Derivatives used as a hedge can improve the management of cash

flows at the individual firm level.

To ensure that productive activities are pursued, corporate finance and treasury groups

should transform their operations from mundane bean counting to activist financial risk

management. They should integrate a clear set of risk management goals and objectives

into the organization's overall corporate strategy. The ultimate goal is to ensure that the

organization has the necessary funds at its disposal to pursue investments that maximize

shareholder value55. Used properly; financial derivatives can help corporations to reduce

uncertainties and promote more productive activities.


"Only risk-seeking organizations should use derivatives"

54 S. L, Gupta,. Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), pp. 17-20. . 55 Robert W, Kolb, Financial Derivatives, (New York, John Wiley, 2003), pp. 56-65

62

Financial derivatives can be used in two ways: to hedge against unwanted risks or to

speculate by taking a position in anticipation of a market movement The olive-press

owners, by locking in a guaranteed return no matter how good or bad the harvest, hedged

against the risk that the next season's olive harvest might not be plentiful. Thales

speculated that the next season's olive harvest would be exceptionally good, and

therefore, paid an up-front premium in anticipation of that event Similarly, organizations

today can use financial derivatives to actively seek out specific risks and speculate on the

direction of interest-rate or exchange-rate movements, or they can use derivatives to

hedge against unwanted risks56. Hence, it is not true that only risk-seeking institutions use

derivatives. Indeed, organizations should use derivatives as part of their overall risk

management strategy for keeping those risks that they are comfortable managing and

selling those that they do not want to others who are more willing to accept them. Even

conservatively managed institutions can use derivatives to improve their cash flow

management to ensure that the necessary funds are available to meet broader corporate

objectives. One could argue that organizations that refuse to use financial derivatives are

at greater risk than are those that use them. .

When using financial derivatives, however, organizations should be careful to use only

those instruments that they un?erstand and that fit best with their corporate risk-

management philosophy. It may be prudent to. Stay away from the more exotic

instruments, unless the risk/reward tradeoffs are clearly understood by the firm's senior

management and its independent risk-management review team. Exotic contracts should

not be used unless there is some obvious reason for doing so. .


"The risks associated with financial derivatives are new and unknown"

The kinds of risks associated with derivatives are no different from those associated with

traditional financial instruments, although they can be far more complex. There are credit


63

risks, operating risks, markets and so on. Risks from derivatives originate with the

customer. With few exceptions, the risks are man-made, that is, they do not readily

appear in nature. For example, when a new homeowner negotiates with a lender to

borrow a sum of money, the customer creates risks by the type of mortgage he chooses.-

risks to himself and the lending company. Financial derivatives allow the lending

institution to break up those risks and distribute them around the financial system via

secondary markets57. Thus, many risks associated with derivatives are actually created by

the dealers' customers or by their customers' customers. Those risks have been inherent in

our nation's financial system since its inception.

Banks and other financial intermediaries should view themselves as risk managers

blending their knowledge of global financial markets with their clients' needs to help their

clients anticipate change and have the flexibility to pursue opportunities that maximize

their success. Banking is inherently a risky business. Risk permeates much of what banks

do. And, for banks to survive, they must be able to understand measure and manage

financial risks effectively. The types of risks faced by corporations today have not

changed; rather, they are more {complex and interrelated. The increased complexity and

volatility of the financial markets have paved the way for the growth of numerous

financial innovations that can enhance returns relative to risk. But a thorough

understanding of the new financial-engineering tools and their proper integration into a

firm's overall risk-management strategy and corporate philosophy can help to turn

volatility into profitability.

Risk management is not about the elimination of risk; it is about the management of risk:

selectively choosing those risks an organization is comfortable with and minimizing

those that it does not want. Financial derivatives serve a useful purpose in fulfilling risk-

management objectives. Through derivatives, risks from traditional instruments can be

57 Susan Thomas, and Ajay Shah, ‘Equity Derivatives in India: The state of the art’, (New Delhi, Tata McGraw Hill series, 2003), pp. 2-4.

64

efficiently unbundled and managed independently. Used correctly, derivatives can save

costs and increase returns58.

Today dealers manage portfolios of derivatives and oversee the net, or residual, risk of

their overall position. That development has changed the focus of risk management from

individual transactions to portfolio exposures and has substantially improved dealers'

ability to accommodate a broad spectrum of customer transactions. Because most active

derivatives players today trade on portfolio exposures, it appears that financial derivatives

do not wind markets together any more tightly than do loa11:s. Derivatives players do not

match every trade with an offsetting trade; instead, they continually manage the residual

risk of the portfolio. If a counterpart defaults on a swap, the defaulted party does not turn

around and default on some other counterpart that offset the original transaction. Instead,

a derivatives default is very similar to a loan default. That is why it is important that

derivatives players perform with due diligence in determining th(' financial strength and

default risks of potential counter parties.


"Because of the risks associated with derivatiVes, banking regulators should ban their

use by any institution covered by federal deposit insurance"

The problem is not derivatives but the perverse incentive banks have under the current

system of federal deposit guarantees. Deposit insurance and other deposit reforms were

first introduced to address some of the instabilities associated with systemic risk.

Through federally guaranteed deposit insurance, the US government attempted to avoid,

by increasing depositors' confidence, the experience of deposit runs that characterized

banking crises before the 1930s.

The current deposit guarantee structure has, indeed, reduced the probability of large-scale

bank panics, but it has also created some new problems. Deposit insurance effectively

58 Ajay, Shah,’ Market Efficiency on the Indian Equity Derivatives Market’, Tata McGraw-Hill series, (2003), pp. 99-104.

65

dominates the discipline provided by the market mechanism that encourages banks to

maintain appropriate capital levels and restrict unnecessary risk taking. Therefore, banks

may wish to pursue higher risk strategies because depositors have a diminished incentive

to monitor banks. Further, federal deposit insurance may actually encOl,lragebanks to use

derivatives as speculative instruments to pursue higher risk strategies, instead of to hedge,

or as dealers59.

Since federal deposit insurance discourages market discipline, regulators have been put in

the position of monitoring banks to ensure that they are managed in a safe and sound

manner. Given the present system of federal deposit guarantees, regulatory proposals

involving financial derivatives should focus on market-oriented reforms as opposed to

laws that might eliminate risk management benefits of derivatives. To that end, banking

regulators should emphasize more disclosure of derivatives positions in financial

statements and be certain that institutions trading huge derivatives portfolios have

adequate capital. In addition, because derivatives could have implications for the stability

of the financial system, it is important that users maintain sound management practices.

Regulators have issued guidelines that banks with substantial trading or derivatives

activity should follow. Those guidelines include . Active board and senior management

oversight of trading activities; Establishment of an internal risk-management audit

function that is independent of the trading function thorough and timely audits to identify

internal control weaknesses; and, risk-measurement and risk-management information

systems that include stress tests, simulations, and contingency plans for adverse market

movements. It is the responsibility of a bank's senior management to ensure that risks are

effectively controlled and limited to levels that do not pose a serious threat to its capital

position. Regulation is an ineffective substitute for sound risk management at the

individual form level60.

59 S. L, Gupta,. Financial Derivatives: theory, concepts and Problems, (New Delhi, Prentice-Hall of India, 2006), pp. 17-20. 60 J R, Verma, (Chairman), et al, The SEBI committee Report on the Development and Regulation of Derivatives markets in India, (2002)

66

2.14 EMERGING STRUCTURE OF DERIVATIVES MARKETS IN INDIA

Derivatives markets in India can be broadly categorized into two markets namely;

financial derivatives markets and commodities futures markets. Financial derivatives

markets deal with the financial futures instruments like stock futures, index futures, stock

options, index options, interest rate futures, currency forwards and futures, financial

swaps, etc. whereas commodity future markets deal with commodity instruments like

agricultural products; food grains, cotton and oil; metals like gold, silver, copper, and

steel and other assets like live stocks, vegetables and so on61.

Financial derivatives markets in India are regulated and controlled by the Securities and

Exchange Board of India (SEBI). The SEBI is authorized under SEBI Act to frame rules

and regulations for financial futures trading on the stock exchanges with the objective to

protect the interest of the investors in the market. Futher carry forward trading (Badla

trading) was also regulated by the SEBI which is traded on the stock exchanges.

Some of the other financial derivatives like currency options and futures and interest rate

futures are controlled by the Reserve bank of India (RBI). These are dealt on Over-the-

Counter (OTC) markets. Financial futures on interest rate include both short term interest

rate and long term interest rate forwards. Currencies include options and forwards. Since

the RBI is the apex body to regulate currencies and interest rates in India, hence, financial

derivatives relating to foreign currencies and interest rates are generally come under RBI

regulation.

Major stock exchanges in India, under the regulation of SEBI, trade in two kinds of

futures products namely equity and carry forwards. Equity futures include stock futures,

index futures, stock options, index options. Currently these are traded on National Stock

Exchange and Bombay Stock Exchange.

61 D. C, Patwari, Options an Futures in an Indian perspective, (Mumbai, JAICO publishing House, 2001), pp. 3-9

67

Commodity futures markets are regulated in India by Forward Market Commission

(FMC). The commission is entrusted with to regulate commodities futures trading in

India. Central government has allowed 54 commodities of different categories to be

eligible for trading on exchanges.

The future derivative trading in India is bright and growing day by day. More new

products and instruments are coming up to be traded on stock and commodity exchanges.

2.15 CATEGORIES OF DERIVATIVES TRADED IN INDIA

1. Commodities futures for coffee, oil seeds, oil, gold, silver, pepper, cotton, jute

andjute goods are traded in the commodities futures. Forward Markets

Commission regulates the trading of commodities futures.

2. Index futures based on Sensex and NIFTY index are also traded under the

supervision of Securities and Exchange Board of India (SEBI).

3. The RBI has permitted banks, Financial Institutions (FI's) and Primary Dealers

(PD's) to enter into forward rate agreement (FRAs)/interest rate swaps in order to

facilitate hedging of interest rate risk and ensuring orderly development of the

derivatives market.

4. The National Stock Exchange (NSE) became the first exchange to launch trading

in options on individual securities. Trading in options on individual securities

commenced from July, 2001. Options contracts are American style and cash

settled and are available in about 40 securities stipulated by the Securities and

Exchange Board of India62.

5. The NSE commenced trading in futures on individual securities on November 9,

2001. The futures contracts are available in about 31 securities stipulated by

SEBI. The BSE also started trading in stock options and futures (both Index and

Stocks) around at the same time as the NSE.

62 www.nseindia.com

68

6. The National Stock Exchange commenced trading in interest rate future on June

2003. Interest rate futures contracts are available on 91-day T-bills, lO-year bonds

and lO-year zero coupon bonds as specified by the SEBI.

Table 2.2: Business Growth in Derivatives segment Year Index Futures Stock Futures Index Options Stock Options

No. of

contracts

Turnover

(Rs. cr.)

No. of

contracts

Turnover

(Rs. cr.)

No. of

contracts

Notional

Turnover

(Rs. cr.)

No. of

contracts

Notional

Turnover

(Rs. cr.)

2009-10 86651879 1715349.01 59128122 2257189.61 132889753

2789950.24

4731748 187261.34

2008-09 210428103 3570111.40 221577980 3479642.12 212088444

3731501.84

13295970 229226.81

2007-08 156598579 3820667.27 203587952 7548563.23 55366038

1362110.88

9460631 359136.55

2006-07 81487424 2539574 104955401 3830967 25157438 791906

5283310 193795

2005-06 58537886 1513755 80905493 2791697 12935116 338469

5240776 180253

2004-05 21635449 772147 47043066 1484056 3293558 121943

5045112 168836

2003-04 17191668 554446 32368842 1305939 1732414 52816

5583071 217207

2002-03 2126763 43952 10676843 286533 442241 9246

3523062 100131

2001-02 1025588 21483 1957856 51515 175900 3765 1037529 25163

2000-01 90580 2365 - - - - - -


2.16 EQUITY DERIVATIVES

Dr. L.C. Gupta Committee considered in its study both types of equity like stock index

derivatives and individual stocks derivatives. At the international level, stock index

derivative is more popular than the individual stock. The Committee found in its survey

69

that index futures are more preferable than individual stock from the respondents63. The

order of over-all preference in India as per the survey of the Committee was as follows:

(i) Stock index futures, (ii) Stock index options, (iii) Individual stock options and (iv)

Individual stock futures.

Basic reasons for the preference of stock index futures: Not only in India, in other

countries too, stock index futures is most popular financial derivatives due to the

following reasons:

1. Institutional investors and other large equity holders prefer the most this

instrument in terms of portfolio hedging purpose.

2. Stock index futures are the most cost-efficient hedging device whereas hedging

through individual stock futures is costlier as observed in other countries.

3. Stock index futures cannot be easily manipulated whereas individual stock price

can be exploited more easily. In India it is rather easier to play this game as

witnessed in the past scams.

4. This is in fact that due to a limited supply of an individual stock, supply can easily

be cornered even in large companies in India like Reliance Industries, State Bank

of India, etc. The Management of these companies has complained many times

about their share prices being manipulated by some interested parties. On the

other hand, the supply of stock index futures is unlimited, and hence, the

possibility of cornering is ruled out. In fact, the manipulation of stock index

futures can be possible only of the cash prices of each component securities in the

index be influenced, which is rare and not so high.

5. It is observed from the experiences of other countries that stock index futures are

more liquid, more popular and favorable than individual stock futures. The same

is also witnessed by the LC Gupta Committee in its survey from the responses of

the respondents.

63 Gautam, Bhardwaj, ‘The Outlook for Derivatives in India: Some Survey Evidence’, Derivative markets in India (New Delhi, Tata McGraw-Hill, 2003), pp. 309-319.

70

6. Since, stock index futures consists of many securities, so being an average stock,

is much less volatile than individual stock price. Further, it implies much lower

capital adequacy and margin requirements in comparison of individual stock

futures.

7. In case of stock index futures trading, there is always clearing house guarantee, so

the chances of the clearing house going to be bankrupt is very rare, and hence, it

is less risky.

8. Another important reason is that in case of individual stocks, the outstanding

positions are settled normally against physical delivery of the shares. Hence, it is

necessary that futures and cash prices remained firmly tied to each other.

However, in case of stock index futures, the physical delivery is almost

impractical, and they are settled in cash all over the world on the premise that

index value, as independently derived from the cash market, is safely accepted as

the settlement price.

9. Lastly, it is also seen that regulatory complexity is much less in the case of stock

index futures in comparison to other kinds of equity derivatives.

In brief, it is observed that the stock index futures are more safer, popular and

attractive derivative instrument than the individuals stock. Even in the US market, the

regulatory framework does not allow use of futures on the individual stocks. Further

only very few countries of world, say one or two, have futures trading on individual

stock.

Strengthening of Cash Market

The Dr. L.C Gupta Committee observed that for successful introduction of futures market

in any country, there must be a strong cash market because derivatives extract their value

from the cash asset. The constant feedback between these two markets through arbitrage

will keep these markets in alignment with each other. The Committee noted certain

weaknesses of the Indian equities markets which should be taken care for success of the

futures trading in India. A few important weaknesses observed are as under:

71

Mixing of cash and forward transactions

1. There is queer mixture of cash and future transactions in the Indian stock markets.

For example, cash transactions (involving delivery), in most active scripts,

deliveries are just around 5percent of the trading volume whereas in many others,

it is just, 20-30 percent. In fact, the dominant cash transactions are the non-

delivery which are the equivalent of futures/forward transactions.

2. It is further noted that the above said mixed system (cash-cum-carry forward) is

not very sound for futures trading because (i) no transparency in the carry forward

system, (ii) the influence of fundamental factors is not so strong due to dominance

of short term speculation and (iii) creating a future market on such basis may have

the effect of compounding the existing weaknesses.

3. The Committee is of the view that there must be separation between cash market

and futures market. It will promote the markets economic efficiency. This has led

to the adoption of the rolling settlement system because in this way, cash market

will function as genuine cash markets but no carry forward. Even futures market

does not permit carry forward from one settlement to another in the way practised

in India64.

4. The trading in Indian stock market was shifted to rolling settlement recently

where always emphasized for settlement by delivery. But in India, 'squaring up or

closing' business (i.e. offsetting of buying and selling transactions within the

settlement) is accounted for in bulk which is not appropriate for futures trading.

Differences in trading cycles among stock exchanges

1. Indian stock exchanges, now, most of them, have a weekly trading cycle but the

cycles are not uniform. For example, NSE has from Wednesday to Tuesday and

BSE has from Monday to Friday. Due to difference in trading cycles, the brokers

who have membership in both the exchanges can easily go on circulating their

trades from one exchange to the other without ever having to delivery. Such

64 J R, Verma, (Chairman), et al, The SEBI committee Report on the Development and Regulation of Derivatives markets in India, (2002).

72

situation is a complete travesty of the cash market and an abuse to the stock

market system.

2. It seems that in Indian stock markets, the different trading cycles have been kept

with a vested interest in order to deliberately generate arbitrage opportunities. It is

seen that due to this, the prices for the same securities on two (NSE and BSE)

stock exchanges differ from 0.5 to 1.5 percent even it is larger on expiration days.

The Committee feels that the different cycles serving the interest of only

speculators and not of genuine investors. Even it is not good for market

development and futures trading65.

3. It is also noted, that the prices of various securities on both exchanges (NSE and

BSE), sometimes are not the same. As a result, the value of the stock indices on

both the exchanges will not be same, if computed separately from the NSE and

BSE prices. This will create a problem in valuation of future market stock. ,.

4. The Committee also noted that for a successful future trading, a coordinated but

pro-competitive nation wide market system be achieved. So it is suggested that

before implementing a uniform trading cycle system among all exchanges, till

such time the rolling settlement system can be adopted. This system will provide a

sound and reliable basis for futures trading in India.

Weakness of stock exchange administrative machinery

The Dr. LC. Gupta Committee members were of the strong opinion that for successful

derivatives trading on the stock exchanges, there must be stringent monitoring norms and

much higher standard of discipline, than in the present, be maintained. Though the SEBI

has already made a good efforts but much more still is to be done specifically in the

controlling of trading members.

Inadequate depository system

The Committee is of the view that all such securities which are composing in stock index

and used for stock index futures, should necessarily be in depository mode. As observed

65 T V, Somnathan,, ‘The Regulatory Framework of Futures and Derivatives Trading’, Derivatives, (New Delhi, Tata McGraw-Hill publication, 2000 ), pp. 221-245.

73

earlier, settlement problems of the cash market may weaken the arbitrage process by

making it risky and costly. Since, index based derivatives trading does not itself involve

deliveries, it will increase the arbitrage trading between cash and index derivatives

markets. The arbitrage process keeps the two markets in alignment. Thus, due to this

reason, it is essential for successful futures trading that all the scripts of the particular

stock index futures must be in the depository mode. Hence, depository scripts in India

should be enhanced. The Committee has no doubt that the creation of futures markets by

introducing the financial derivatives, including equity futures, currency futures and

interest rate futures would be a major step towards the further growth and development of

the Indian financial markets provided that the trading must be cost-efficient and risk

hedging facilities66.

2.17 DERIVATIVES TRADING AT NSE/BSE

The most notable of development in the history of secondary segment of the Indian stock

market is the commencement of derivatives trading in June, 2000. The SEBI approved

derivatives trading based on futures contracts at National Stock Exchange (NSE) and

Bombay Stock Exchange (BSE) in accordance with the ruleslbye-Iaws and regulations of

the stock exchanges. To begin with, the SEBI permitted equity derivatives named stock

index futures. The BSE introduced on 9 June, 2000 stock index futures based on the

sensitive Index (also called SENSEX comprising 30 scripts)named BSX, and NSE started

on June 12, 2000 stock index future based on its index S&P CNX NIFTY (comprised 50

scripts) in the name of N FUTIDX NIFTY.

In India, stock index futures are available for one-month, two-month and three-month

maturities. All the open positions in these contracts are settled daily. Further, the buyers

and sellers are required to deposit margin with the respective stock exchanges determined

as per the SEBI guidelines. To facilitate the effective risk management in the derivatives

segment, all the important measures like minimum net worth requirement for the broker,

66 T V, Somnathan,, ‘The Regulatory Framework of Futures and Derivatives Trading’, Derivatives, (New Delhi, Tata McGraw-Hill publication, 2000, pp. 221-245.

74

determination of margin based on value at risk model, position limit for various

participants, mechanism for collection and enforcement of margin, etc. have been put in

place. Subsequently, the derivative products range had been increased by including

options and futures on the indices and on several highly traded stocks. In an estimate, the

product wise turnover of derivatives on the Indian stock markets as on July 6,2002 is

stock futures (50%), index futures (21%), stock options (25%) and index option (4%). It

means stock futures are most popular derivative traded at the stock market of India67.

During the last decade, to make stock market functioning effective for futures trading, the

SEBI has adopted several internationally tested and accepted mechanism for

implementation at the Indian stock exchanges. For this, proper surveillance and risk

containment like the circuit breaker, price bands, value at risk (VaR)based margin

collections, etc. have been introduced.

The SEBI set up a 'Technical Group' headed by Prof. l.R. Verma to prescribe risk

containment measures for new derivative products. The group recommended the

introduction of exchange traded options on Indices which is also conformity with the

sequence of introduction of derivatives products recommended by Dr. Lc. Gupta

Committee.

The Technical Group has recommended the risk containment measure for exchange

traded options on indices. The following are the important features of the risk

containment framework for the trading and settlement of both index futures and index

option contracts68:

1. European style index options will be permitted initially. These will be settled in

cash.

2. Index option contracts will have a minimum contract size of Rs 21akh, at the time

of its introduction.

67 RBI, Annual Report, Various issues, 2003, pp 56-57. 68Ravi, Narain, , ‘Experiences with Derivatives Trading at NSE’, Derivative Markets In India, (New Delhi, Tata McGraw-Hill Series, 2003 ), pp. 27-35.

75

3. The risk containment measures described hereunder are only for premium style

European option.

4. Index option contract will have a maximum maturity of 12months and a minimum

of three strikes, i.e., in the money, near the money and out of the money.

5. A portfolio based margining approach, which would take an integrated view of

the risk involved in the portfolio of individual client, will be adopted. It is for the

first time that such an approach is introduced in the Indian stock market. It is

inconsistent with the practices followed in the countries. This approach will not

only cover the risk but also help in reducing the transaction costs in derivatives.

6. The initial margin requirements will be based on worst case loss of a portfolio of

an individual client to cover a 99% value at risk (Var) over a one day horizon.

The initial margin requirement will be netted at level of individual client and it

will be on gross basis at the level of Trading/Clearing member. Further, the initial

margin requirement for the proprietary position of Trading/Clearing member will

also be on net basis.

7. The short option minimum margin equal to 30%of the Notional value of all short

index option will be charged if sum of the worst scenario loss and the calendar

spread margin is lower than the short option minimums margin.

8. Net option value will be calculated on the current market value of the option times

the number of options (positive for long options and negative for short options) in

the portfolio. The net option value will be added to the Liquid Net Worth of the

clearing member.

9. For option positions, the premium will be paid in by the buyer in cash and paid

out to the seller in cash on T + 1day until the buyer pays in the premium due shall

be deducted from the available Liquid Net Worth on a real time basis. In case of

index futures contracts, the mark-to-market gains losses for index futures position

will continue to be settled.

Contrary to international experience, the growth of derivatives market did not take off as

anticipated. The value of trading have been low. This is mainly attributed to the low

awareness about the products and mechanism of trading among the market players and

76

investors. SEBI's technical group on new derivative products has recently examined this

issue and recommended the following measures for the development of derivatives

market69:

1. The system of sub-brokers be used for increasing the volume of trading in this

market.

2. Financial institutions and mutual funds be permitted to sell short in the cash

market for facilitating the free arbitrage between cash and derivatives market.

However, such short sale may be restricted to the extent of corresponding

exposure in the derivative market.

3. Arbitrage between cash and derivatives markets will assist in better price

discovery in both the markets.

Countries like USA, UK and Singapore have reaped considerably economic benefit from

foreign participation in their futures markets. Foreign participation in futures markets

hedge the potential to act as a substantial 'invisible earner' of foreign exchange. Earlier

the SEBI and the RBI both were hesitant to allow the foreign institutional investors (FIIs)

for trading in the futures markets. However, recently the RBI has allowed FIIs to trade in

derivatives market subject to the condition that the overall open position of the FII shall

not exceed 100percent of the market value of the concerned FII's total investment. As per

the recent notification of the Central Government, SEBI and RBI will jointly examine the

issues concerning trading in financial derivatives by FIs and FII(s).

The SEBI board has initially approved the introduction of single stock futures contract on

31 stocks on which option contracts have been introduced on BSE and NSE. A list of

these has been given in Table 5.2. The Advisory Committee on Derivatives of the SEBI

shall review the eligibility criteria for introduction of futures and options on any other

stock from time to time. A brief structure in general relating to financial derivatives

operating in India has been shown in Fig. 5.1.

69 Technical Group Report, SEBI.

77

2.18 FUTURES AND OPTIONS AS DERIVATIVE INSTRUMENTS & ITS

APPLICATION.

In recent years, derivatives have become increasingly important in the field of finance.

While futures and options are now actively traded on many exchanges, forward contracts

are popular on the OTC market. In this chapter we shall study in detail these three

derivative contracts.

2.18.1 Forward Contracts

A forward contract is an agreement to buy or sell an asset on a specified date for a

specified price. One of the parties to the contract assumes a long position and agrees to

buy the underlying asset on a certain specified future date for a certain specified pric e.

The other party assumes a short position and agrees to sell the asset on the same date for

the same price. Other contract details like delivery date, price and quantity are negotiated

bilaterally by the parties to the contract. The forward contracts are normally traded

outside the exchanges70.

The salient features of forward contracts are:

• They are bilateral contracts and hence exposed to counter-party risk.

• Each contract is custom designed, and hence is unique in terms of contract size,

expiration date and the asset type and quality.

• The contract price is generally not available in public domain.

• On the expiration date, the contract has to be settled by delivery of the asset.

• If the party wishes to reverse the contract, it has to compulsorily go to the same

counter-party, which often results in high prices being charged.

However forward contracts in certain markets have become very standardized, as in the

case of foreign exchange, thereby reducing transaction costs and increasing transactions

volume. This process of standardization reaches its limit in the organized futures market.

70 John Marshall and Vipul Bansal,, Financial Engineering : A complete guide to Financial Innovation, (New Delhi, Prentice Hall of India, 1999), p.33

78

Forward contracts are very useful in hedging and speculation. The classic hedging

application would be that of an exporter who expects to receive payment in dollars three

months later. He is exposed to the risk of exchange rate fluctuations. By using the

currency forward market to sell dollars forward, he can lock on to a rate today and reduce

his uncertainty. Similarly an importer who is required to make a payment in dollars two

months hence can reduce his exposure to exchange rate fluctuations by buying dollars

forward.

If a speculator has information or analysis, which forecasts an upturn in a price, then he

can go long on the forward market instead of the cash market. The spec ulator would go

long on the forward, wait for the price to rise, and then take a reversing transaction to

book profits. Speculators may well be required to deposit a margin upfront. However, this

is generally a relatively small proportion of the value of the assets underlying the forward

contract. The use of forward markets here supplies leverage to the speculator.

Limitations of Forward Markets

Forward markets world-wide are afflicted by several problems:

. • Lack of centralization of trading,

. • Illiquidity, and

. • Counterparty risk

In the first two of these, the basic problem is that of too much flexibility and generality.

The forward market is like a real estate market in that any two consenting adults can form

contracts against each other. This often makes them design terms of the deal which are

very convenient in that specific situation, but makes the contracts non-tradable.

Counterparty risk arises from the possibility of default by any one party to the

transaction. When one of the two sides to the transaction declares bankruptcy, the other

suffers. Even when forward markets trade standardized contracts, and hence avoid the

79

problem of illiquidity, still the counterparty risk remains a very serious issue71.

2.18.2 Introduction to Futures

Futures markets were designed to solve the problems that exist in forward markets. A

futures contract is an agreement between two parties to buy or sell an asset at a certain

time in the future at a certain price. But unlike forward contracts, the futures contracts are

standardized and exchange traded. To facilitate liquidity in the futures contracts, the

exchange specifies certain standard features of the contract. It is a standardized contract

with standard underlying instrument, a standard quantity and quality of the underlying

instrument that can be delivered, (or which can be used for reference purposes in

settlement) and a standard timing of such settlement. A futures contract may be offset

prior to maturity by entering into an equal and opposite transaction. More than 99% of

futures transactions are offset this way72.

The standardized items in a futures contract are:

. • Quantity of the underlying

. • Quality of the underlying

. • The date and the month of delivery

. • The units of price quotation and minimum price change

. • Location of settlement

Distinction between futures and forwards

FUTURES FORWARDS

Trade on an organized exchange OTC in nature

Standardized contract terms Customised contract terms

hence more liquid hence less liquid

Requires margin payments No margin payment

Follows daily settlement Settlement happens at end of

period

71 Baz, Jamil and Chacko, George, Financial Derivatives: Pricing, Application and Mathematics, (London, Cambridge University Press, 2003) 72 S L, Gupta, ‘Financial Derivatives: Theory, Concepts and Problems’, (New Delhi, Prentice Hall of India, 2006), pp. 86-95.

80

Distinction between Futures and Forwards Contracts

Forward contracts are often confused with futures contracts. The confusion is primarily

because both serve essentially the same economic functions of allocating risk in the

presence of future price uncertainty. However futures are a significant improvement over

the forward contracts as they eliminate counterparty risk and offer more liquidity. Table

3.1 lists the distinction between the two.

Futures Terminology

• Spot price: The price at which an asset trades in the spot market.

• Futures price: The price at which the futures contract trades in the futures

market.

• Contract cycle: The period over which a contract trades. The index futures

contracts on the NSE have one-month, two-months and three-months expiry cycles which

expire on the last Thursday of the month. Thus a January expiration contract expires on

the last Thursday of January and a February expiration contract ceases trading on the last

Thursday of February. On the Friday following the last Thursday, a new contract having

a three-month expiry is introduced for trading.

• Expiry date: It is the date specified in the futures contract. This is the last day on

which the contract will be traded, at the end of which it will cease to exist.

• Contract size: The amount of asset that has to be delivered in one contract, also

called as lot size.

• Basis: In the context of financial futures, basis can be defined as the futures price

minus the spot price. There will be a different basis for each delivery month for

each contract. In a normal market, basis will be positive. This reflects that futures

prices normally exceed spot prices.

• Cost of carry: The relationship between futures prices and spot prices can be

summarized in terms of what is known as the cost of carry. This measures the

storage cost plus the interest that is paid to finance the asset less the income

earned on the asset.

• Initial margin: The amount that must be deposited in the margin account at the

time a futures contract is first entered into is known as initial margin.

81

• Marking-to-market: In the futures market, at the end of each trading day, the

margin account is adjusted to reflect the investor's gain or loss depending upon

the futures closing price. This is called marking-to-market.

• Maintenance margin: This is somewhat lower than the initial margin. This is set

to ensure that the balance in the margin account never becomes negative. If the

balance in the margin account falls below the maintenance margin, the investor

receives a margin call and is expected to top up the margin account to the initial

margin level before trading commences on the next day.

2.18.3 Introduction to Options

In this section, we look at the next derivative product to be traded on the NSE, namely

options. Options are fundamentally different from forward and futures contracts. An

option gives the holder of the option the right to do something. The holder does not have

to exercise this right. In contrast, in a forward or futures contract, the two parties have

committed themselves to doing something. Whereas it costs nothing (except margin

requirements) to enter into a futures contract, the purchase of an option requires an up-

front payment73.

Option Terminology

. • Index options: These options have the index as the underlying. Some

options are European while others are American. Like index futures contracts, index

options contracts are also cash settled.

. • Stock options: Stock options are options on individual stoc ks. Options

currently trade on over 500 stocks in the United States. A contract gives the holder the

right to buy or sell shares at the specified price.

• Buyer of an option: The buyer of an option is the one who by paying the option

premium buys the right but not the obligation to exercise his option on the seller/writer.

• Writer of an option: The writer of a call/put option is the one who receives the

73John C. Hull, Introduction to Futures and Options Market, (New Delhi, Prentice Hall of India, 2006), pp. 110-119.

82

option premium and is thereby obliged to sell/buy the asset if the buyer exercises

on him.

There are two basic types of options, call options and put options.

• Call option: A call option gives the holder the right but not the obligation to buy

an asset by a certain date for a certain price.

• Put option: A put option gives the holder the right but not the obligation to sell an

asset by a certain date for a certain price.

• Option price/premium: Option price is the price which the option buyer pays to

the option seller. It is also referred to as the option premium.

• Expiration date: The date specified in the options contract is known as the

expiration date, the exercise date, the strike date or the maturity.

• Strike price: The price specified in the options contract is known as the strike

price or the exercise price.

• American options: American options are options that can be exercised at any time

upto the expiration date. Most exchange-traded options are American.

• European options: European options are options that can be exercised only on the

expiration date itself. European options are easier to analyze than American

options, and properties of an American option are frequently deduced from those

of its European counterpart.

• In-the-money option: An in-the-money (ITM) option is an option that would lead

to a positive cash flow to the holder if it were exercised immediately. A call

option on the index is said to be in-the-money when the current index stands at a

level higher than the strike price (i.e. spot price > strike price). If the index is

much higher than the strike price, the call is said to be deep ITM. In the case of a

put, the put is ITM if the index is below the strike price.

• At-the-money option: An at-the-money (ATM) option is an option that would

lead to zero cash flow if it were exercised immediately. An option on the index is

at-the-money when the current index equals the strike price

(i.e. spot price = strike price).

• Out-of-the-money option: An out-of-the-money (OTM) option is an option that

83

would lead to a negative cashflow if it were exercised immediately. A call option

on the index is out-of-the-money when the current index stands at a level which is

less than the strike price (i.e. spot price < strike price). If the index is much lower

than the strike price, the call is said to be deep OTM. In the case of a put, the put

is OTM if the index is above the strike price.

• Intrinsic value of an option: The option premium can be broken down into two

components - intrinsic value and time value. The intrinsic value of a call is the

amount the option is ITM, if it is ITM. If the call is OTM, its intrinsic value is

zero. Putting it another way, the intrinsic value of a call is Max[0, (St — K)]

which means the intrinsic value of a call is the greater of 0 or (St — K). Similarly,

the intrinsic value of a put is Max[0, K — St],i.e. the greater of 0 or (K — St). K is

the strike price and St is the spot price.

• Time value of an option: The time value of an option is the difference between its

premium and its intrinsic value. Both calls and puts have time value. An option

that is OTM or ATM has only time value. Usually, the maximum time value

exists when the option is ATM. The longer the time to expiration, the greater is an

option's time value, all else equal. At expiration, an option should have no time

value.

2.18.4 Index Derivatives74

Index derivatives are derivative contracts which derive their value from an underlying

index. The two most popular index derivatives are index futures and index options. Index

derivatives have become very popular worldwide. Index derivatives offer various

advantages and hence have become very popular.

• Institutional and large equity-holders need portfolio-hedging facility. Index-

derivatives are more suited to them and more cost-effective than derivatives based

on individual stocks. Pension funds in the US are known to use stock index

futures for risk hedging purposes.

74 S L, Gupta, Financial Derivatives: Theory, Concepts and Problems, (New Delhi, Prentice Hall of India, 2006), pp. 203-226.

84

• Index derivatives offer ease of use for hedging any portfolio irrespective of its

composition.

• Stock index is difficult to manipulate as compared to individual stock prices,

more so in India, and the possibility of cornering is reduced. This is partly

because an individual stock has a limited supply, which can be cornered.

• Stock index, being an average, is much less volatile than individual stock prices.

This implies much lower capital adequacy and margin requirements.

• Index derivatives are cash settled, and hence do not suffer from settlement delays

and problems related to bad delivery, forged/fake certificates.

2.18.5 Applications Of Futures And Options

The phenomenal growth of financial derivatives across the world is attributed the

fulfillment of needs of hedgers, speculators and arbitrageurs by these products. In this

chapter we first look at how trading futures differs from trading the underlying spot. We

then look at the payoff of these contracts, and finally at how these contracts can be used

by various entities in the economy.

A payoff is the likely profit/loss that would accrue to a market participant with change in

the price of the underlying asset. This is generally depicted in the form of payoff

diagrams which show the price of the underlying asset on the X-axis and the

profits/losses on the Y-axis.

Trading Underlying Versus Trading Single Stock Futures

The single stock futures market in India has been a great success story across the world.

NSE ranks first in the world in terms of number of contracts traded in single stock

futures. One of the reasons for the success could be the ease of trading and settling these

contracts.

To trade securities, a customer must open a security trading account with a securities

broker and a demat account with a securities depository. Buying security involves putting

up all the money upfront. With the purchase of shares of a company, the holder becomes

85

a part owner of the company. The shareholder typically receives the rights and privileges

associated with the security, which may include the receipt of dividends, invitation to the

annual shareholders meeting and the power to vote.

Selling securities involves buying the security before selling it. Even in cases where short

selling is permitted, it is assumed that the securities broker owns the security and then

"lends" it to the trader so that he can sell it. Besides, even if permitted, short sales on

security can only be executed on an up-tick.

To trade futures, a customer must open a futures trading account with a derivatives

broker. Buying futures simply involves putting in the margin money. They enable the

futures traders to take a position in the underlying security without having to open an

account with a securities broker. With the purchase of futures on a security, the holder

essentially makes a legally binding promise or obligation to buy the underlying security

at some point in the future (the expiration date of the contract). Security futures do not

represent ownership in a corporation and the holder is therefore not regarded as a

shareholder75.

A futures contract represents a promise to transact at some point in the future. In this

light, a promise to sell security is just as easy to make as a promise to buy security.

Selling security futures without previously owning them simply obligates the trader to

selling a certain amount of the underlying security at some point in the future. It can be

done just as easily as buying futures, which obligates the trader to buying a certain

amount of the underlying security at some point in the future. In the following sections

we shall look at some uses of security future.

2.18.5.1 FUTURES PAYOFFS

Futures contracts have linear payoffs. In simple words, it means that the losses as

well as profits for the buyer and the seller of a futures contract are unlimited. These

75 N.D Vohra, and B. R. Bagri, , Futures and Options, (New Delhi, Tata Mcgraw-Hill, 2003) , pp. 123-128.

86

linear payoffs are fascinating as they can be combined with options and the

underlying to generate various complex payoffs76.

Payoff for buyer of futures: Long futures

The payoff for a person who buys a futures contract is similar to the payoff for a person

who holds an asset. He has a potentially unlimited upside as well as a potentially

unlimited downside. Take the case of a speculator who buys a two-month Nifty index

futures contract when the Nifty stands at 2220.

The underlying asset in this case is the Nifty portfolio. When the index moves up, the

long futures position starts making profits, and when the index moves down it starts

making losses. Figure 2.3 shows the payoff diagram for the buyer of a futures contract.

The figure shows the profits/losses for a long futures position. The investor bought

futures when the index was at 2220. If the index goes up, his futures position starts

making profit. If the index falls, his futures position starts showing losses.

Figure 2.3 Payoff for buyer of futures

76 John C. Hull, Fundamentals of Futures and Options Market, (New Delhi, Prentice Hall of India, 2006), pp. 73-76.

87

Payoff for seller of futures: Short futures

The payoff for a person who sells a futures contract is similar to the payoff for a person

who shorts an asset. He has a potentially unlimited upside as well as a potentially

unlimited downside. Take the case of a speculator who sells a two-month Nifty index

futures contract when the Nifty stands at 2220. The underlying asset in this case is the

Nifty portfolio. When the index moves down, the short futures position starts making

profits, and when the index moves up, it starts making losses. Figure 2.4 shows the

payoff diagram for the seller of a futures contract.

The figure shows the profits/losses for a short futures position. The investor sold futures

when the index was at 2220. If the index goes down, his futures position starts making

profit. If the index rises, his futures position starts showing losses.

Figure 2.4: Payoff for seller of futures

2.18.5.2 Pricing Futures

Pricing of futures contract is very simple. Using the cost-of-carry logic, we calculate the

fair value of a futures contract. Every time the observed price deviates from the fair

value, arbitragers would enter into trades to capture the arbitrage profit. This in turn

would push the futures price back to its fair value. The cost of carry model used for

pricing futures is given below77:

77 O P Gupta, and Kumar Muneesh, ‘Impact of Introduction of Index Furtures on Stock Volatility: Indian Experience’, NSE Research Initiative, National Stock Exchange, (Mumbai, 2002), p.25.

88

where: r Cost of financing (using continuously

compounded interest rate) T Time till expiration in

years e 2.71828

Example: Security XYZ Ltd trades in the spot market at Rs. 1150. Money can be invested

at 11% p.a. The fair value of a one-month futures contract on XYZ is calculated as

follows:

Pricing equity index futures

A futures contract on the stock market index gives its owner the right and obligation to

buy or sell the portfolio of stocks characterized by the index. Stock index futures are cash

settled; there is no delivery of the underlying stocks.

In their short history of trading, index futures have had a great impact on the world's

securities markets. Its existence has revolutionized the art and science of institutional

equity portfolio management.

The main differences between commodity and equity index futures are that:

. • There are no costs of storage involved in holding equity.

. • Equity comes with a dividend stream, which is a negative cost if you are

long the stock and a positive cost if you are short the stock.

Therefore, Cost of carry = Financing cost -Dividends. Thus, a crucial aspect of dealing

with equity futures as opposed to commodity futures is an accurate forecasting of

dividends. The better the forecast of dividend offered by a security, the better is the

estimate of the futures price78.

78 K S Nagraj and Kotha Kiran Kumar, ‘Index Fuutures Trading and Spot Market Volatility : Evidence from an Emerging Market’, The ICFAI Journal of Applied finance,10, 8, (2003) 5-15.

89

Pricing index futures given expected dividend amount

The pricing of index futures is also based on the cost-of-carry model, where the carrying

cost is the cost of financing the purchase of the portfolio underlying the index, minus the

present value of dividends obtained from the stocks in the index portfolio.

Example

Nifty futures trade on NSE as one, two and three-month contracts. Money can be

borrowed at a rate of 10% per annum. What will be the price of a new two-month futures

contract on Nifty?

1. Let us assume that ABC Ltd. will be declaring a dividend of Rs.20 per share after

15 days of purchasing the contract.

2. Current value of Nifty is 4000 and Nifty trades with a multiplier of 100.

3. Since Nifty is traded in multiples of 100, value of the contract is 100*4000 =

Rs.400,000.

4. If ABC Ltd. Has a weight of 7% in Nifty, its value in Nifty is Rs.28,000

i.e.(400,000 * 0.07).

5. If the market price of ABC Ltd. Is Rs.140, then a traded unit of Nifty involves

200 shares of ABC Ltd. i.e. (28,000/140).

6. To calculate the futures price, we need to reduce the cost-of-carry to the extent of

dividend received. The amount of dividend received is Rs.4000

i.e. (200*20). The dividend is received 15 days later and hence compounded only

for the remainder of 45 days. To calculate the futures price we need to compute the

amount of dividend received per unit of Nifty. Hence we divide the compounded

dividend figure by 100.

7. Thus, futures price

Pricing index futures given expected dividend yield

If the dividend flow throughout the year is generally uniform, i.e. if there are few

historical cases of clustering of dividends in any particular month, it is useful to calculate

the annual dividend yield.

90

F = Se (r-q)T

where:

F = futures price

S = spot index value

r = cost of financing

q = expected dividend yield

T = holding period

Example: A two-month futures contract trades on the NSE. The cost of financing is 10%

and the dividend yield on Nifty is 2% annualized. The spot value of Nifty 4000. The fair

value of the futures contract is :

(0.1-0.02) × (60 / 365)

Fair value = 4000e

= Rs.4052.95

The cost-of-carry model explicitly defines the relationship between the futures price and

the related spot price. As we know, the difference between the spot price and the futures

price is called the basis.

Nuances

• As the date of expiration comes near, the basis reduces -there is a convergence of

the futures price towards the spot price. On the date of expiration, the basis is

zero. If it is not, then there is an arbitrage opportunity. Arbitrage opportunities can

also arise when the basis (difference between spot and futures price) or the

spreads (difference between prices of two futures contracts) during the life of a

contract are incorrect. At a later stage we shall look at how these arbitrage

opportunities can be exploited.

• There is nothing but cost-of-carry related arbitrage that drives the behavior of the

futures price.

• Transactions costs are very important in the business of arbitrage.

The figure shows how basis changes over time. As the time to expiration of a contract

reduces, the basis reduces. Towards the close of trading on the day of settlement, the

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futures price and the spot price converge. The closing price for the June 28 futures

contract is the closing value of Nifty on that day.

Figure 2.5 Variation of basis over time (Source: www.nseindia.com)

2.18.5.3 Pricing Stock Futures

A futures contract on a stock gives its owner the right and obligation to buy or sell the

stocks. Like index futures, stock futures are also cash settled; there is no delivery of the

underlying stocks. Just as in the case of index futures, the main differences between

commodity and stock futures are that:

. • There are no costs of storage involved in holding stock.

. • Stocks come with a dividend stream, which is a negative cost if you are

long the stock and a positive cost if you are short the stock.

Therefore, Cost of carry = Financing cost -Dividends. Thus, a crucial aspect of dealing

with stock futures as opposed to commodity futures is an accurate forecasting of

dividends. The better the forecast of dividend offered by a security, the better is the

estimate of the futures price.

Pricing stock futures when no dividend expected

The pricing of stock futures is also based on the cost-of-carry model, where the carrying

cost is the cost of financing the purchase of the stock, minus the present value of

dividends obtained from the stock. If no dividends are expected during the life of the

contract, pricing futures on that stock is very simple. It simply involves multiplying the

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spot price by the cost of carry.

Example

XYZ futures trade on NSE as one, two and three-month contracts. Money can be

borrowed at 10% per annum. What will be the price of a unit of new two-month futures

contract on SBI if no dividends are expected during the two-month period?

1. 1. Assume that the spot price of XYZ is Rs.228.

2. 2. Thus, futures price F = 228e

0.10× (60/365) = Rs.231.90

Pricing stock futures when dividends are expected

When dividends are expected during the life of the futures contract, pricing involves

reducing the cost of carry to the extent of the dividends. The net carrying cost is the cost

of financing the purchase of the stock, minus the present value of dividends obtained

from the stock.

Example: XYZ futures trade on NSE as one, two and three-month contracts. What will be

the price of a unit of new two-month futures contract on XYZ if dividends are expected

during the two-month period?

1. Let us assume that XY Z will be declaring a dividend of Rs. 10 per share after 15

days of purchasing the contract.

2. Assume that the market price of XYZ is Rs. 140.

3. To calculate the futures price, we need to reduce the cost-of-carry to the extent of

dividend received. The amount of dividend received is Rs.10. The dividend is

received 15 days later and hence compounded only for the remainder of 45 days.

4. Thus, futures price =

0.1× (60/365) 0.1× (45/365)

F = 140e -10e = Rs.132.20

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2.18.5.4 Application of Futures

Understanding beta79

The index model suggested by William Sharpe offers insights into portfolio

diversification. It express the excess return on a security or a portfolio as a function of

market factors and non market factors. Market factors are those factors that affect all

stocks and portfolios. These would include factors such as inflation, interest rates,

business cycles etc. Non-market factors would be those factors which are specific to a

company, and do not affect the entire market. For example, a fire breakout in a factory, a

new invention, the death of a key employee, a strike in the factory, etc. The market

factors affect all firms. The unexpected change in these factors cause unexpected changes

in the rates of returns on the entire stock market. Each stock however responds to these

factors to different extents. Beta of a stock measures the sensitivity of the stocks

responsiveness to these market factors. Similarly, Beta of a portfolio, measures the

portfolios responsiveness to these market movements. Given stock betas, calculating

portfolio beta is simple. It is nothing but the weighted average of the stock betas. The

index has a beta of 1.

Hence the movements of returns on a portfolio with a beta of one will be like the index. If

the index moves up by ten percent, my portfolio value will increase by ten percent.

Similarly if the index drops by five percent, my portfolio value will drop by five percent.

A portfolio with a beta of two, responds more sharply to index movements. If the index

moves up by ten percent, the value of a portfolio with a beta of two will move up by

twenty percent. If the index drops by ten percent, the value of a portfolio with a beta of

two, will fall by twenty percent. Similarly, if a portfolio has a beta of 0.75, a ten percent

movement in the index will cause a 7.5 percent movement in the value of the portfolio. In

short, beta is a measure of the systematic risk or market risk of a portfolio. Using index

futures contracts, it is possible to hedge the systematic risk. With this basic

understanding, we look at some applications of index futures. We look here at some

applications of futures contracts. We refer to single stock futures. However since the

79 William F, Sharpe, ‘A Simplified Model of Portfolio Analysis’, Management Science, (1963)

94

index is nothing but a security whose price or level is a weighted average of securities

constituting an index, all strategies that can be implemented using stock futures can also

be implemented using index futures.

Hedging: Long security, sell futures

Futures can be used as an effective risk-management tool. Take the case of an investor

who holds the shares of a company and gets uncomfortable with market movements in

the short run. He sees the value of his security falling from Rs.450 to Rs.390. In the

absence of stock futures, he would either suffer the discomfort of a price fall or sell the

security in anticipation of a market upheaval.

With security futures he can minimize his price risk. All he need do is enter into an

offsetting stock futures position, in this case, take on a short futures position. Assume that

the spot price of the security he holds is Rs.390. Two-month futures cost him Rs.402. For

this he pays an initial margin. Now if the price of the security falls any further, he will

suffer losses on the security he holds. However, the losses he suffers on the security, will

be offset by the profits he makes on his short futures position. Take for instance that the

price of his security falls to Rs.350. The fall in the price of the security will result in a fall

in the price of futures. Futures will now trade at a price lower than the price at which he

entered into a short futures position. Hence his short futures position will start making

profits. The loss of Rs.40 incurred on the security he holds, will be made up by the profits

made on his short futures position.

Index futures in particular can be very effectively used to get rid of the market risk of a

portfolio. Every portfolio contains a hidden index exposure or a market exposure. This

statement is true for all portfolios, whether a portfolio is composed of index securities or

not80. In the case of portfolios, most of the portfolio risk is accounted for by index

fluctuations (unlike individual securities, where only 3060% of the securities risk is

accounted for by index fluctuations). Hence a position LONG PORTFOLIO + SHORT

NIFTY can often become one-tenth as risky as the LONG PORTFOLIO position!

80 Markowitz, Harry, ‘Portfolio Selection’, Journal of Finance, (March 1952)

95

Suppose we have a portfolio of Rs. 1 million which has a beta of 1.25. Then a complete

hedge is obtained by selling Rs.1.25 million of Nifty futures.

Hedging does not always make money. The best that can be achieved using hedging is

the removal of unwanted exposure, i.e. unnecessary risk. The hedged position will make

less profits than the unhedged position, half the time. One should not enter into a hedging

strategy hoping to make excess profits for sure; all that can come out of hedging is

reduced risk81.

Speculation: Bullish security, buy futures

Take the case of a speculator who has a view on the direction of the market. He would

like to trade based on this view. He believes that a particular security that trades at

Rs.1000 is undervalued and expects its price to go up in the next two-three months. How

can he trade based on this belief? In the absence of a deferral product, he would have to

buy the security and hold on to it. Assume he buys a 100 shares which cost him one lakh

rupees. His hunch proves correct and two months later the security closes at Rs.1010. He

makes a profit of Rs.1000 on an investment of Rs. 1,00,000 for a period of two months.

This works out to an annual return of 6 percent.

Today a speculator can take exactly the same position on the security by using futures

contracts. Let us see how this works. The security trades at Rs.1000 and the two-month

futures trades at 1006. Just for the sake of comparison, assume that the minimum contract

value is 1,00,000. He buys 100 security futures for which he pays a margin of Rs.20,000.

Two months later the security closes at 1010. On the day of expiration, the futures price

converges to the spot price and he makes a profit of Rs.400 on an investment of

Rs.20,000. This works out to an annual return of 12 percent. Because of the leverage they

provide, security futures form an attractive option for speculators.

81 Bodie, Kane, Marcus and Mohanty, Investments, (New Delhi, Tata McGraw-Hill, 2006), pp. 813-820.

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Speculation: Bearish security, sell futures

Stock futures can be used by a speculator who believes that a particular security is over-

valued and is likely to see a fall in price. How can he trade based on his opinion? In the

absence of a deferral product, there wasn't much he could do to profit from his opinion.

Today all he needs to do is sell stock futures.

Let us understand how this works. Simple arbitrage ensures that futures on an individual

securities move correspondingly with the underlying security, as long as there is

sufficient liquidity in the market for the security. If the security price rises, so will the

futures price. If the security price falls, so will the futures price. Now take the case of the

trader who expects to see a fall in the price of ABC Ltd. He sells one two-month contract

of futures on ABC at Rs.240 (each contact for 100 underlying shares). He pays a small

margin on the same. Two months later, when the futures contract expires, ABC closes at

220. On the day of expiration, the spot and the futures price converges. He has made a

clean profit of Rs.20 per share. For the one contract that he bought, this works out to be

Rs.2000.

Arbitrage: Overpriced futures: buy spot, sell futures

As we discussed earlier, the cost-of-carry ensures that the futures price stay in tune with

the spot price. Whenever the futures price deviates substantially from its fair value,

arbitrage opportunities arise.

If you notice that futures on a security that you have been observing seem overpriced,

how can you cash in on this opportunity to earn riskless profits? Say for instance, ABC

Ltd. trades at Rs.1000. One-month ABC futures trade at Rs.1025 and seem overpriced.

As an arbitrageur, you can make riskless profit by entering into the following set of

transactions.

1. On day one, borrow funds, buy the security on the cash/spot market at 1000.

2. Simultaneously, sell the futures on the security at 1025.

3. Take delivery of the security purchased and hold the security for a month.

4. On the futures expiration date, the spot and the futures price converge. Now

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unwind the position.

5. Say the security closes at Rs.1015. Sell the security.

6. Futures position expires with profit of Rs.10.

7. The result is a riskless profit of Rs.15 on the spot position and Rs.10 on the

futures position.

8. Return the borrowed funds.

When does it make sense to enter into this arbitrage? If your cost of borrowing funds to

buy the security is less than the arbitrage profit possible, it makes sense for you to

arbitrage. This is termed as cash-and-carry arbitrage. Remember however, that exploiting

an arbitrage opportunity involves trading on the spot and futures market. In the real

world, one has to build in the transactions costs into the arbitrage strategy82.

Arbitrage: Underpriced futures: buy futures, sell spot

Whenever the futures price deviates substantially from its fair value, arbitrage

opportunities arise. It could be the case that you notice the futures on a security you hold

seem underpriced. How can you cash in on this opportunity to earn riskless profits? Say

for instance, ABC Ltd. trades at Rs.1000. One-month ABC futures trade at Rs. 965 and

seem underpriced. As an arbitrageur, you can make riskless profit by entering into the

following set of transactions.

1. On day one, sell the security in the cash/spot market at 1000.

2. Make delivery of the security.

3. Simultaneously, buy the futures on the security at 965.

4. On the futures expiration date, the spot and the futures price converge.

Now unwind the position.

5. Say the security closes at Rs.975. Buy back the security.

6. The futures position expires with a profit of Rs.10.

7. The result is a riskless profit of Rs.25 on the spot position and Rs.10 on

the futures position.

82 Bodie et al, Investments, (New Delhi, Tata McGraw-Hill, 2006), pp. 856-58.

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If the returns you get by investing in riskless instruments is more than the return from the

arbitrage trades, it makes sense for you to arbitrage. This is termed as reverse-cash-and-

carry arbitrage. It is this arbitrage activity that ensures that the spot and futures prices stay

in line with the cost-of-carry. As we can see, exploiting arbitrage involves trading on the

spot market. As more and more players in the market develop the knowledge and skills to

do cash-and-carry and reverse cash-and-carry, we will see increased volumes and lower

spreads in both the cash as well as the derivatives market.

2.18.5.5 OPTIONS PAYOFFS

The optionality characteristic of options results in a non-linear payoff for options. In

simple words, it means that the losses for the buyer of an option are limited; however the

profits are potentially unlimited. For a writer, the payoff is exactly the opposite. His

profits are limited to the option premium; however his losses are potentially unlimited.

These non-linear payoffs are fascinating as they lend themselves to be used to generate

various payoffs by using combinations of options and the underlying. We look here at the

six basic payoffs83.

Payoff profile of buyer of asset: Long asset

In this basic position, an investor buys the underlying asset, Nifty for instance, for 2220,

and sells it at a future date at an unknown price, St. Once it is purchased, the investor is

said to be "long" the asset. Figure 4.4 shows the payoff for a long position on the Nifty.

Payoff profile for seller of asset: Short asset

In this basic position, an investor shorts the underlying asset, Nifty for instance, for 2220,

and buys it back at a future date at an unknown price, St. Once it is sold, the investor is

said to be "short" the asset. Figure 4.5 shows the payoff for a short position on the Nifty.

83 Hull, John C. (2006), Fundamentals of Futures and Options Market, Prentice Hall of India, New Delhi, pp. 182-186.

99

Payoff profile for buyer of call options: Long call84

A call option gives the buyer the right to buy the underlying asset at the strike price

specified in the option. The profit/loss that the buyer makes on the option depends on the

spot price of the underlying. If upon expiration, the spot price exceeds the strike price, he

makes a profit. Higher the spot price, more is the profit he makes. If the spot price of the

underlying is less than the strike price, he lets his option expire un-exercised. His loss in

this case is the premium he paid for buying the option. Figure 2.6 gives the payoff for the

buyer of a three month call option (often referred to as long call) with a strike of 2250

bought at a premium of 86.60.

The figure shows the profits/losses from a long position on the index. The investor

bought the index at 2220. If the index goes up, he profits. If the index falls he looses.

Figure 2.6 Payoff for investor who went Long Nifty at 2220

The figure shows the profits/losses from a short position on the index. The investor sold

the index at 2220. If the index falls, he profits. If the index rises, he looses.

84 John C, Hull, Fundamentals of Futures and Options Market, (New Delhi, Prentice Hall of India, 2006), pp. 202-204.

100

Figure 2.7 Payoff for buyer of call option

The figure shows the profits/losses for the buyer of a three-month Nifty 2250 call option.

As can be seen, as the spot Nifty rises, the call option is in-the-money. If upon expiration,

Nifty closes above the strike of 2250, the buyer would exercise his option and profit to

the extent of the difference between the Nifty-close and the strike price. The profits

possible on this option are potentially unlimited. However if Nifty falls below the strike

of 2250, he lets the option expire. His losses are limited to the extent of the premium he

paid for buying the option.

Payoff profile for writer of call options: Short call

A call option gives the buyer the right to buy the underlying asset at the strike price

specified in the option. For selling the option, the writer of the option charges a premium.

The profit/loss that the buyer makes on the option depends on the spot price of the

underlying. Whatever is the buyer's profit is the seller's loss. If upon expiration, the spot

price exceeds the strike price, the buyer will exercise the option on the writer. Hence as

the spot price increases the writer of the option starts making losses. Higher the spot

price, more is the loss he makes. If upon expiration the spot price of the underlying is less

than the strike price, the buyer lets his option expire un-exercised and the writer gets to

keep the premium. Figure 2. 7 gives the payoff for the writer of a three month call option

(often referred to as short call) with a strike of 2250 sold at a premium of 86.60.

The figure shows the profits/losses for the seller of a three-month Nifty 2250 call option.

As the spot Nifty rises, the call option is in-the-money and the writer starts making

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losses. If upon expiration, Nifty closes above the strike of 2250, the buyer would exercise

his option on the writer who would suffer a loss to the extent of the difference between

the Nifty-close and the strike price. The loss that can be incurred by the writer of the

option is potentially unlimited, whereas the maximum profit is limited to the extent of the

up-front option premium of Rs.86.60 charged by him.

Figure 2.8: Payoff profile for writer of call options: Short call

Payoff profile for buyer of put options: Long put85

A put option gives the buyer the right to sell the underlying asset at the strike price

specified in the option. The profit/loss that the buyer makes on the option depends on the

spot price of the underlying. If upon expiration, the spot price is below the strike price, he

makes a profit. Lower the spot price, more is the profit he makes. If the spot price of the

underlying is higher than the strike price, he lets his option expire un-exercised. His loss

in this case is the premium he paid for buying the option. Figure 2. 8 gives the payoff for

the buyer of a three month put option (often referred to as long put) with a strike of 2250

bought at a premium of 61.70.

The figure shows the profits/losses for the buyer of a three-month Nifty 2250 put option.

As can be seen, as the spot Nifty falls, the put option is in-the-money. If upon expiration,

Nifty closes below the strike of 2250, the buyer would exercise his option and profit to


102

the extent of the difference between the strike price and Nifty-close. The profits possible

on this option can be as high as the strike price. However if Nifty rises above the strike of

2250, he lets the option expire. His losses are limited to the extent of the premium he paid

for buying the option.

Figure 2.9 Payoff for buyer of put option

Payoff profile for writer of put options: Short put

A put option gives the buyer the right to sell the underlying asset at the strike price

specified in the option. For selling the option, the writer of the option charges a premium.

The profit/loss that the buyer makes on the option depends on the spot price of the

underlying. Whatever is the buyer's profit is the seller's loss. If upon expiration, the spot

price happens to be below the strike price, the buyer will exercise the option on the

writer. If upon expiration the spot price of the underlying is more than the strike price, the

buyer lets his option unexercised and the writer gets to keep the premium. Figure 4.9

gives the payoff for the writer of a three month put option (often referred to as short put)

with a strike of 2250 sold at a premium of 61.70.

The figure shows the profits/losses for the seller of a three-month Nifty 2250 put option.

As the spot Nifty falls, the put option is in-the-money and the writer starts making losses.

If upon expiration, Nifty closes below the strike of 2250, the buyer would exercise his

option on the writer who would suffer a loss to the extent of the difference between the

strike price and Nifty-close. The loss that can be incurred by the writer of the option is a

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maximum extent of the strike price (Since the worst that can happen is that the asset price

can fall to zero) whereas the maximum profit is limited to the extent of the up-front

option premium of Rs.61.70 charged by him.

Figure 2.10: Payoff for writer of put option

2.18.5.6 PRICING OPTIONS

An option buyer has the right but not the obligation to exercise on the seller. The worst

that can happen to a buyer is the loss of the premium paid by him. His downside is

limited to this premium, but his upside is potentially unlimited. This optionality is

precious and has a value, which is expressed in terms of the option price. Just like in

other free markets, it is the supply and demand in the secondary market that drives the

price of an option86.

There are various models which help us get close to the true price of an option. Most of

these are variants of the celebrated Black-Scholes model for pricing European options.

Today most calculators and spread-sheets come with a built-in Black-Scholes options

pricing formula so to price options we don't really need to memorize the formula. All we

need to know is the variables that go into the model. The Black-Scholes formulas for the

86 R C, Merton, ‘The Relationship between Put and Call Prices: Comment’, Journal of Finance, (1973) 183-84.

104

prices of European calls and puts on a non-dividend paying stock are87:

• The Black/Scholes equation is done in continuous time. This requires continuous

compounding. The “r” that figures in this is ln(l + r). Example: if the interest rate per

annum is 12%, you need to use ln

1.12 or 0.1133, which is the continuously compounded equivalent of 12% per annum.

. • N() is the cumulative normal distribution. N(d1) is called the delta of the

option which is a measure of change in option price with respect to change in the price of

the underlying asset.

. • s a measure of volatility, is the annualized standard deviation of

continuously compounded returns on the underlying. When daily sigma are given, they

need to be converted into annualized sigma.


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2.18.5.7 APPLICATION OF OPTIONS

We look here at some applications of options contracts. We refer to single stock options

here. However since the index is nothing but a security whose price or level is a weighted

average of securities constituting the index, all strategies that can be implemented using

stock futures can also be implemented using index options.

Hedging: Have underlying buy puts

Owners of stocks or equity portfolios often experience discomfort about the overall stock

market movement. As an owner of stocks or an equity portfolio, sometimes you ma y

have a view that stock prices will fall in the near future. At other times you may see that

the market is in for a few days or weeks of massive volatility, and you do not have an

appetite for this kind of volatility. The union budget is a common and reliable source of

such volatility: market volatility is always enhanced for one week before and two weeks

after a budget. Many investors simply do not want the fluctuations of these three weeks.

One way to protect your portfolio from potential downside due to a market drop is to buy

insurance using put options88.

Index and stock options are a cheap and easily implementable way of seeking this

insurance. The idea is simple. To protect the value of your portfolio from falling below

a particular level, buy the right number of put options with the right strike price. If you

are only concerned about the value of a particular stock that you hold, buy put options

on that stock. If you are concerned about the overall portfolio, buy put options on the

index. When the stoc k price falls your stock will lose value and the put options bought

by you will gain, effectively ensuring that the total value of your stock plus put does

not fall below a particular level. This level depends on the strike price of the stock

options chosen by you. Similarly when the index falls, your portfolio will lose value

and the put options bought by you will gain, effectively ensuring that the value of your

portfolio does not fall below a particular level. This level depends on the strike price of

88 J R, Verma, ‘Equity Options in India: An Empirical Examination’, Derivative Markets In India, (New Delhi, Tata McGraw-Hill, 2003), pp. 47-51.

106

the index options chosen by you.

Portfolio insurance using put options is of particular interest to mutual funds who

already own well-diversified portfolios. By buying puts, the fund can limit its

downside in case of a market fall.

Speculation: Bullish security, buy calls or sell puts

There are times when investors believe that security prices are going to rise. For

instance, after a good budget, or good corporate results, or the onset of a stable

government. How does one implement a trading strategy to benefit from an upward

movement in the underlying security? Using options there are two ways one can do

this:

1. 1. Buy call options; or

2. 2. Sell put options

We have already seen the payoff of a call option. The downside to the buyer of the call

option is limited to the option premium he pays for buying the option. His upside

however is potentially unlimited. Suppose you have a hunch that the price of a particular

security is going to rise in a months time. Your hunch proves correct and the price does

indeed rise, it is this upside that you cash in on. However, if your hunch proves to be

wrong and the security price plunges down, what you lose is only the option premium.

Having decided to buy a call, which one should you buy? Table 4.1 gives the premia for

one month calls and puts with different strikes. Given that there are a number of one-

month calls trading, each with a different strike price, the obvious question is: which

strike should you choose? Let us take a look at call options with different strike prices.

Assume that the current price level is 1250, risk-free rate is 12% per year and volatility of

the underlying security is 30%. The following options are available:

1. 1. A one month call with a strike of 1200.





107

Which of these options you choose largely depends on how strongly you feel about the

likelihood of the upward movement in the price, and how much you are willing to lose

should this upward movement not come about. There are five one-month calls and five

one-month puts trading in the market. The call with a strike of 1200 is deep in-the-money

and hence trades at a higher premium. The call with a strike of 1275 is out-of-the-money

and trades at a low premium. The call with a strike of 1300 is deep-out-of-money. Its

execution depends on the unlikely event that the underlying will rise by more than 50

points on the expiration date. Hence buying this call is basically like buying a lottery.

There is a small probability that it may be in-the-money by expiration, in which case the

buyer will make profits. In the more likely event of the call expiring out-of-the-money,

the buyer simply loses the small premium amount of Rs.27.50.

As a person who wants to speculate on the hunch that prices may rise, you can also do so

by selling or writing puts. As the writer of puts, you face a limited upside and an

unlimited downside. If prices do rise, the buyer of the put will let the option expire and

you will earn the premium. If however your hunch about an upward movement proves to

be wrong and prices actually fall, then your losses directly increase with the falling price

level. If for instance the price of the underlying falls to 1230 and you've sold a put with

an exercise of 1300, the buyer of the put will exercise the option and you'll end up losing

Rs.70. Taking into account the premium earned by you when you sold the put, the net

loss on the trade is Rs.5.20.

Having decided to write a put, which one should you write? Given that there are a

number of one-month puts trading, each with a different strike price, the obvious question

is: which strike should you choose? This largely depends on how strongly you feel about

the likelihood of the upward movement in the prices of the underlying. If you write an at-

the-money put, the option premium earned by you will be higher than if you write an out-

of-the-money put. However the chances of an at-the-money put being exercised on you

are higher as well.

The spot price is 1250. There are five one-month calls and five one-month puts trading in

the market. The call with a strike of 1200 is deep in-the-money and hence trades at a

higher premium. The call with a strike of 1275 is out-of-the-money and trades at a low

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premium. The call with a strike of 1300 is deep-out-of-money. Its execution depends on

the unlikely event that the price of underlying will rise by more than 50 points on the

expiration date. Hence buying this call is basically like buying a lottery. There is a small

probability that it may be in-the-money by expiration in which case the buyer will profit.

In the more likely event of the call expiring out-of-the-money, the buyer simply loses the

small premium amount of Rs. 27.50. Figure 4.10 shows the payoffs from buying calls at

different strikes. Similarly, the put with a strike of 1300 is deep in-the-money and trades

at a higher premium than the at-the-money put at a strike of 1250. The put with a strike of

1200 is deep out-of-the-money and will only be exercised in the unlikely event that

underlying falls by 50 points on the expiration date.

Table 2.3: Buy Calls and Sell Puts

Underlying Strike price of

option

Call Premium(Rs.) Put Premium(Rs.)

1250 1200 80.10 18.15

1250 1225 63.65 26.50

1250 1250 49.45 37.00

1250 1275 37.50 49.80

1250 1300 27.50 64.80

At a price level of 1250, one opt ion is in-the-money and one is out-of-the-money. As

expected, the in-the-money option fetches the highest premium of Rs.64.80 whereas the

out-of-the-money option has the lowest premium of Rs. 18.15.

Speculation: Bearish security, sell calls or buy puts

Do you sometimes think that the market is going to drop? That you could make a profit

by adopting a position on the market? Due to poor corporate results, or the instability of

the government, many people feel that the stocks prices would go down. How does one

implement a trading strategy to benefit from a downward movement in the market?

Today, using options, you have two choices:

1. 1. Sell call options; or

2. 2. Buy put options

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We have already seen the payoff of a call option. The upside to the writer of the call

option is limited to the option premium he receives upright for writing the option. His

downside however is potentially unlimited. Suppose you have a hunch that the price of a

particular security is going to fall in a months time. Your hunch proves correct and it

does indeed fall, it is this downside that you cash in on. When the price falls, the buyer of

the call lets the call expire and you get to keep the premium. However, if your hunch

proves to be wrong and the market soars up instead, what you lose is directly proportional

to the rise in the price of the security.

The figure shows the profits/losses for a buyer of calls at various strikes. The in-the-

money option with a strike of 1200 has the highest premium of Rs.80.10 whereas the out-

of-the-money option with a strike of 1300 has the lowest premium of Rs.27.50.

Figure 2.11 Payoff for writer of put options at various strikes

The figure shows the profits/losses for a writer of puts at various strikes. The in-the-

money option with a strike of 1300 fetches the highest premium of Rs.64.80 whereas the

out-of-the-money option with a strike of 1200 has the lowest premium of Rs. 18.15.

Having decided to write a call, which one should you write? Table 4.2 gives the

premiums for one month calls and puts with different strikes. Given that there are a

number of one-month calls trading, each with a different strike price, the obvious

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question is: which strike should you choose? Let us take a look at call options with

different strike prices. Assume that the current stock price is 1250, risk-free rate is 12%

per year and stock volatility is 30%. You could write the following options:






Which of this options you write largely depends on how strongly you feel about the

likelihood of the downward movement of prices and how much you are willing to lose

should this downward movement not come about. There are five one-month calls and five

one-month puts trading in the market. The call with a strike of 1200 is deep in-the-money

and hence trades at a higher pre mium. The call with a strike of 1275 is out-of-the-money

and trades at a low premium. The call with a strike of 1300 is deep-out-of-money. Its

execution depends on the unlikely event that the stock will rise by more than 50 points on

the expiration date. Hence writing this call is a fairly safe bet. There is a small probability

that it may be in-the-money by expiration in which case the buyer exercises and the

writer suffers losses to the extent that the price is above 1300. In the more likely event of

the call expiring out-of-the-money, the writer earns the premium amount ofRs.27.50.

As a person who wants to speculate on the hunch that the market may fall, you can also

buy puts. As the buyer of puts you face an unlimited upside but a limited downside. If the

price does fall, you profit to the extent the price falls below the strike of the put

purchased by you. If however your hunch about a downward movement in the market

proves to be wrong and the price actually rises, all you lose is the option premium. If for

instance the security price rises to 1300 and you've bought a put with an exercise of 1250,

you simply let the put expire. If however the price does fall to say 1225 on expiration

date, you make a neat profit of Rs.25.

Having decided to buy a put, whic h one should you buy? Given that there are a number

of one-month puts trading, each with a different strike price, the obvious question is:

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which strike should you choose? This largely depends on how strongly you feel about the

likelihood of the downward movement in the market. If you buy an at-the-money put, the

option premium paid by you will by higher than if you buy an out-of-the-money put.

However the chances of an at-the-money put expiring in-the-money are higher as well.

The spot price is 1250. There are five one-month calls and five one-month puts trading in

the market. The call with a strike of 1200 is deep in-the-money and hence trades at a

higher premium. The call with a strike of 1275 is out-of-the-money and trades at a low

premium. The call with a strike of 1300 is deep-out-of-money. Its execution depends on

the unlikely event that the price will rise by more than 50 points on the expiration date.

Hence writing this call is a fairly safe bet. There is a small probability that it may be in-

the-money by expiration in which case the buyer exercises and the writer suffers losses to

the extent that the price is above 1300. In the more likely event of the call expiring out-

of-the-money, the writer earns the premium amount of Rs.27.50. Figure 4.12 shows the

payoffs from writing calls at different strikes. Similarly, the put with a strike of 1300 is

deep in-the-money and trades at a higher premium than the at-the-money put at a strike of

1250. The put with a strike of 1200 is deep out-of-the-money and will only be exercised

in the unlikely event that the price falls by 50 points on the expiration date. The choice of

which put to buy depends upon how much the speculator expects the market to fall.

Table 2.4: Sell calls and Buy Puts

Price Strike price of Call Put Premium(Rs.)

option Premium(Rs.)

1250 1200 80.10 18.15

1250 1225 63.65 26.50

1250 1250 49.45 37.00

1250 1275 37.50 49.80

1250 1300 27.50 64.80

The figure shows the profits/losses for a seller of calls at various strike prices. The in-the-

money option has the highest premium of Rs.80.10 whereas the out-of-the-money option

has the lowest premium of Rs. 27.50.

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Figure 2.12 Payoff for seller of call option at various strikes

The figure shows the profits/losses for a buyer of puts at various strike prices. The in-the-

money option has the highest premium of Rs.64.80 whereas the out-of-the-money option

has the lowest premium of Rs. 18.50.

Figure 2.13 Payoff for buyer of put options at various strikes

Bull spreads - Buy a call and sell another

There are times when you think the market is going to rise over the next two months,

however in the event that the market does not rise, you would like to limit your downside.

One way you could do this is by entering into a spread. A spread trading strategy

involves taking a position in two or more options of the same type, that is, two or more

calls or two or more puts. A spread that is designed to profit if the price goes up is called

a bull spread.

How does one go about doing this? This is basically done utilizing two call options

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having the same expiration date, but different exercise prices. The buyer of a bull spread

buys a call with an exerc ise price below the current index level and sells a call option

with an exercise price above the current index level. The spread is a bull spread because

the trader hopes to profit from a rise in the index. The trade is a spread because it

involves buying one option and selling a related option. What is the advantage of entering

into a bull spread? Compared to buying the underlying asset itself, the bull spread with

call options limits the trader's risk, but the bull spread also limits the profit potential.

The figure shows the profits/losses for a bull spread. As can be seen, the payoff obtained

is the sum of the payoffs of the two calls, one sold at Rs.40 and the other bought at Rs.80.

The cost of setting up the spread is Rs.40 which is the difference between the call

premium paid and the call premium received. The downside on the position is limited to

this amount. As the index moves above 3800, the position starts making profits (cutting

losses) until the index reaches 4200. Beyond 4200, the profits made on the long call

position get offset by the losses made on the short call position and hence the maximum

profit on this spread is made if the index on the expiration day closes at 4200. Hence the

payoff on this spread lies between -40 to 360. Who would buy this spread? Somebody

who thinks the index is going to rise, but not above 4200. Hence he does not want to buy

a call at 3800 and pay a premium of 80 for an upside he believes will not happen.

Figure 2.14 Payoff for a bull spread created using call options

In short, it limits both the upside potential as well as the downside risk. The cost of the

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bull spread is the cost of the option that is purchased, less the cost of the option that is

sold. Table 4.3 gives the profit/loss incurred on a spread position as the index changes.

Figure 4.14 shows the payoff from the

bull spread.

Broadly, we can have three types of bull spreads:

1. 1. Both calls initially out-of-the-money.

2. 2. One call initially in-the-money and one call initially out-of-the-money,

and

3. 3. Both calls initially in-the-money.

The decision about which of the three spreads to undertake depends upon how much risk

the investor is willing to take. The most aggressive bull spreads are of type 1. They cost

very little to set up, but have a very small probability of giving a high payoff.

Expiration day cash flows for a Bull spread using two-month calls

The table shows possible expiration day profit for a bull spread created by buying calls at

a strike of 3800 and selling calls at a strike of 4200. The cost of setting up the spread is

the call premium paid (Rs.80) minus the call premium received (Rs.40), which is Rs.40.

This is the maximum loss that the position will make. On the other hand, the maximum

profit on the spread is limited to Rs.360. Beyond an index level of 4200, any profits made

on the long call position will be cancelled by losses made on the short call position,

effectively limiting the profit on the combination.

Table 2.5: Bull Spread

Nifty Buy Jan 3800

Call

Sell Jan 4200 Call Cash

Flow

Profit&Loss

(Rs.)

3700 0 0 0 -40

3750 0 0 0 -40

3800 0 0 0 -40

3850 +50 0 50 +10

3900 +100 0 100 +60

3950 +150 0 150 +110

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4000 +200 0 200 +160

4050 +250 0 250 +210

4100 +300 0 300 +260

4150 +350 0 350 +310

4200 +400 0 400 +360

4250 +450 -50 400 +360

4300 +500 -100 400 +360

Bear spreads - sell a call and buy another

There are times when you think the market is going to fall over the next two months.

However in the event that the market does not fall, you would like to limit your

downside. One way you could do this is by entering into a spread. A spread trading

strategy involves taking a position in two or more options of the same type, that is, two or

more calls or two or more puts. A spread that is designed to profit if the price goes down

is called a bear spread.

How does one go about doing this? This is basically done utilizing two call options

having the same expiration date, but different exercise prices. How is a bull spread

different from a bear spread? In a bear spread, the strike price of the option purchased is

greater than the strike price of the option sold. The buyer of a bear spread buys a call with

an exercise price above the current index level and sells a call option with an exercise

price below the current index level. The spread is a bear spread because the trader hopes

to profit from a fall in the index. The trade is a spread because it involves buying one

option and selling a related option. What is the advantage of entering into a bear spread?

Compared to buying the index itself, the bear spread with call options limits the trader's

risk, but it also limits the profit potential. In short, it limits both the upside potential as

well as the downside risk.

A bear spread created using calls involves initial cash inflow since the price of the call

sold is greater than the price of the call purchased. Table 4.4 gives the profit/loss incurred

on a spread position as the index changes. Figure 4.15 shows the payoff from the bear

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spread.

Broadly we can have three types of bear spreads:

1. 1. Both calls initially out-of-the-money.

2. 2. One call initially in-the-money and one call initially out-of-the-money, and

3. 3. Both calls initially in-the-money.

The decision about which of the three spreads to undertake depends upon how much risk

the investor is willing to take. The most aggressive bear spreads are of type 1. They cost

very little to set up, but have a very small probability of giving a high payoff. As we

move from type 1 to type 2 and from type 2 to type 3, the spreads become more

conservative and cost higher to set up. Bear spreads can also be created by buying a put

with a high strike price and selling a put with a low strike price.

The figure shows the profits/losses for a bear spread. As can be seen, the payoff obtained

is the sum of the payoffs of the two calls, one sold at Rs. 150 and the other bought at

Rs.50. The maximum gain from setting up the spread is Rs. 100 which is the difference

between the call premium received and the call premium paid. The upside on the position

is limited to this amount. As the index moves above 3800, the position starts making

losses (cutting profits) until the spot reaches 4200. Beyond 4200, the profits made on the

long call position get offset by the losses made on the short call position.

The maximum loss on this spread is made if the index on the expiration day closes at

2350. At this point the loss made on the two call position together is Rs.400 i.e. (4200-

3800).

However the initial inflow on the spread being Rs.100, the net loss on the spread turns

out to be 300. The downside on this spread position is limited to this amount. Hence the

payoff on this spread lies between +100 to -300.

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Figure 2.15 Payoff for a bear spread created using call options

Expiration day cash flows for a Bear spread using two-month calls

The table shows possible expiration day profit for a bear spread created by selling one

market lot of calls at a strike of 3800 and buying a market lot of calls at a strike of 4200.

The maximum profit obtained from setting up the spread is the difference between the

premium received for the call sold (Rs. 150) and the premium paid for the call bought

(Rs.50) which is Rs. 100.

In this case the maximum loss obtained is limited to Rs.300. Beyond an index level of

4200, any profits made on the long call position will be canceled by losses made on the

short call position, effectively limiting the profit on the combination.

Table 2.6: Bear Spread

Nifty Buy Jan 4200 Call Sell Jan 3800

Call

Cash Flow Profit&Loss

(Rs.)

3700 0 0 0 +100

3750 0 0 0 +100

3800 0 0 0 +100

3850 0 -50 -50 +50

3900 0 -100 -100 0

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3950 0 -150 -150 -50

4000 0 -200 -200 -100

4050 0 -250 -250 -150

4100 0 -300 -300 -200

4150 0 -350 -350 -250

4200 0 -400 -400 -300

4250 +50 -450 -400 -300

4300 +100 -500 -400 -300

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CHAPTER 3

DERIVATIVES – REVIEW OF LITERATURE.

3.1 An Introduction

3.2 Stabilization Arguments

3.3 Destabilization Arguments

3.4 Investors’ Perceptions about Derivatives

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3.1 AN INTRODUCTION

Derivatives are traded for a variety of reasons. Derivatives enable a trader to hedge some

pre-existing risk by taking positions in derivatives markets that offset potential losses in

the underlying or spot market. In India, most derivatives users describe themselves as

hedgers and Indian laws generally require that derivatives be used for hedging purposes

only. Another motive for derivatives trading is speculation (i.e. taking positions to profit

from anticipated price movements). In practice, it may be difficult to distinguish whether

a particular trade was for hedging or speculation, and active markets require the

participation of both hedgers and speculators.

It is argued that derivatives encourage speculation, which destabilizes the spot market.

The alleged destabilization takes the form of higher stock market volatility. The reason

behind it is informational effect of the futures trading. Futures trading can alter the

available information for two reasons: first, futures trading attract additional traders in the

market; second, as transaction costs in the futures market are lower than those in the spot

market, new information may be transmitted to the futures market more quickly. Thus,

future markets provide an additional route by which information can be transmitted to the

spot markets and therefore, increased spot market volatility may simply be a consequence

of the more frequent arrival and more rapid processing of information.

Raju and Ghosh (2004)89 have expressed view for the consideration of volatility in the

Indian stock market as tools of analysis of risk factors. Stock prices and their volatility

add to the concern of attention. The growing linkages of national markets in currency,

commodity and stock with world markets and existence of common players, have given

volatility a new property – that of its speedy transmissibility across markets.

Among the general public, the term volatility is simply synonymous with risk. In their

view, high volatility is to be deplored, because it means that security values are not

89M.T, Raju, and A. Ghosh, ‘Stock MarketVolatility – International Comparison’, Working Paper Series No.8, SEBI. (2004)

121

dependable and the capital markets are not functioning as well as they should. Merton

Miller (1991) the winner of the 1990 Nobel Prize in economics - writes in his book

"Financial Innovation and Market Volatility" …. “By volatility public seems to mean

days when large market movements, particularly down moves, occur. These precipitous

market wide price drops cannot always be traced to a specific news event.... The public

takes a more deterministic view of stock prices; if the market crashes, there must be a

specific reason.” (Cited in Raju and Ghosh 2004).

The volatility on the Indian stock exchanges may be thought of as having two

components: The volatility arising due to information based price changes and Volatility

arising due to noise trading/ speculative trading, i.e., destabilizing volatility. As a

concept, volatility is simple and intuitive.

In a large scale, the success of derivatives trading will depend on the choice of products

to be traded in the markets. The popularly traded and usual types of derivatives are

futures and options. The products to be traded in the stock markets need to have the

following characteristics which are mentioned by Tsetsekos Varangis (2000)90:

......a sufficiently higher as well as lower level of price volatility to attract hedgers

or speculators, a significant amount of money for speculative motive at a certain level of

risk; a significant number of domestic market participants—and possibly buyers and

sellers from abroad; a large number of producers, processors, and banks interested in

using derivatives contracts (that is, enough speculators to provide additional liquidity);

and a weak correlation between the price of the underlying asset and the price of the

already-traded derivatives contract(s) in other exchanges (basis risk).

Introduction of derivatives in the Indian capital market was initiated by the Government

following L C Gupta Committee Report on Derivatives in December 1997. The report

suggested the introduction of stock index futures in the first place to be followed by other

90 Tsetsekos, George and Panos Varangis,, ‘Structuring Derivatives ’ Working paper, (Honolulu., Finance Management Asociation,2000)

122

products once the market matures. Following the recommendations and pursuing the

integration policy, futures on benchmark indices (Sensex and Nifty 50) were introduced

in June 2000. The policy was followed by introduction of index options on indices in

June 2001, followed by options on individual stocks in July 2001. Stock futures were

introduced on individual stocks in November, 2001 (Nath 2003)91

By definition, derivatives are the future contracts whose value depends upon the

underlying assets. When derivatives are introduced in the stock market, the underlying

asset may be anything as component of stock market like, stock prices or market indices,

interest rates, etc. Derivatives products are specialised contracts92 which signify an

agreement or an option to buy or sell the underlying asset to extend up to the maturity

time in the future at a prearranged price.

Only futures and options are used in this analysis, so these are introduced in brief.

Futures: A futures contract is an agreement between two parties to buy or sell an asset at

a certain time in the future at a certain price. Presently Index futures on S&P CNX

NIFTY and CNX IT, Stock futures on certain specified Securities and Interest Rate

Futures are available for trading at NSE. All the futures contracts are settled in cash. A

futures contract is a forward contract which trades on an exchange. Futures markets

feature a series of innovations in how trading is organised. (Shah Thomas 2000)93

Options: An Option is a contract which gives the right, but not an obligation, to buy or

sell the underlying at a stated date and at a stated price. While a buyer of an option pays

the premium and buys the right to exercise his option, the writer of an option is the one

91 G C Nath, and Tulsi, ‘Derivatives and its impact on spot market’, Derivative Markets, IUP, IV, 3, (2003), 24-25. 92 The contract has a fixed expiry period mostly in the range of 3 to 12 months from the date of commencement of the contract. The value of the contract depends on the expiry period and also on the price of the underlying asset 93 Thomas, Susan, ‘Derivative Markets in in India 2003’, (New Delhi , Tata McGraw-Hill Series, 2003) , pp. 2-12

123

who receives the option premium and therefore obliged to sell/buy the asset if the buyer

exercises it on him.

The above description about the derivatives creates a research problem that need be

reported. What is the impact of derivatives trading on the stock market risk and return in

practice? The theoretical literature on derivatives trading is of the view that derivatives

trading increase the efficiency of the stock market through minimising the risk, but the

opposite effect may also be caused by derivatives trading.

Derivatives trading in the stock market have been a subject of enthusiasm of research in

the field of finance. Derivatives trading have two attributes on the basis of its

effectiveness. So there have often been contrary views among the researchers of what

may be the impact of derivatives trading. According to the nature of this instrument it is

argued that this could enhance the market efficiency by establishing the market. There are

many empirical findings for both there roles of derivatives trading. Many theories have

been developed about the pros and cons of the impact of derivatives trading in the stock

market. A common agreement has been found among the studies that the introduction of

derivatives products, specially the equity index futures enables traders to transact large

volumes at much lower transaction costs relative to the cash market.

A major theoretical argument for the benefit of derivatives trading is that it reduces the

volatility of the stock market. The logic is that it reduces the asymmetric information

among the investors and information reduces the speculation in the trading system. A

variety of theoretical arguments have been advanced over the years to explain why

speculative trading in general, or the existence of derivatives markets in particular, might

affect the volatility of the underlying asset market. In recent past, the volatility of stock

returns has been a major topic in finance literature. Empirical researchers have tried to

find a pattern in stock return movements or factors determining these movements.

Generally, volatility is considered as a measurement of risk in the stock market return and

a lot of discussions have taken place about the nature of stock return volatility. Therefore,

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understanding factors that affect stock return volatility is an imperative task in many

ways.

A numbers of theoretical and empirical studies have been done on the impact of the

introduction of derivatives in the stock markets on the stock return volatility. The studies

are concerned with both the developed as well as developing countries. There are two

sets of views according to the theoretical as well as empirical findings. One is of the view

that introduction of derivatives has increased the volatility and market performance,

through forwarding its speculative roles and the other view is that the introduction of

derivatives has reduced the volatility in the stock market thus increasing the stability of

the stock market.

The behaviour of volatility in the equity market in India, for the pre and post derivatives

period, has been examined using conditional variance for the period of 1999-2003 in

(Agrawal, 1998)94. He modeled conditional volatility using different method such as

GARCH (1,1). He has considered 20 stocks randomly from the Nifty and Junior Nifty

basket as well as benchmark indices itself. As result, he observed that for most of the

stocks, the volatility came down in the post-derivative trading period. All these methods

suggest that the volatility of the market as measured by benchmark indices like S&P

CNX Nifty and Nifty Junior have fallen in the post-derivatives period.

The impacts of the introduction of the derivatives contracts such as Nifty futures and

options contracts on the underlying spot market volatility have been examined using a

model that captures the heteroskedasticity in returns that is recognised as the Generalised

Auto Regressive Conditional Heteroskedasticity (GARCH) Model in Shenbagaraman

(2003)95. She used the daily closing prices for the period 5th Oct. 1995 to 31st Dec. 2002

for the CNX Nifty the Nifty Junior and S&P500 returns. Results indicate that derivatives

94 Agrwal R, ‘Stock Index Futures and Cash market Volitilty’, Review of Futures Marekt, 7, (1988), 290-299. 95 Shenbagaraman Premalata, "Do Futures and Options trading increase stock market volatility" NSE

NEWS Letter (Mumbai, National Stock Exchange of India, January 2003.)

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introduction has had no significant impact on spot market volatility but the nature of the

GARCH process has changed after the introduction of the futures trading.

Both theoretical and empirical aspect of the question of how the speculation, in general,

and derivative securities in particular, effects the underlying asset markets has been

explained in Mayhew (2000)96. The theoretical research has revealed that there are many

different aspects of the relationship between cash and derivative markets. Although many

models predict that derivatives should have a stabilizing effect, this result normally

requires restrictive assumptions. At the end of the day, the theoretical literature gives

ambiguous predictions about the effects of derivatives markets.

Price discovery and volatility have been examined in the context of introduction of Nifty

futures at the National Stock Exchange (NSE) in June 2000 applying Cointegration and

Generalised Auto Regressive Conditional Heteroscedasticity (GARCH) techniques

respectively from January1998 to October 2002 in Raju and Karande (2003)97. Their

finding suggests that the introduction of futures has reduced volatility in the cash market.

The impact of trading in the Dow Jones Industrial Average index futures and futures

options on the conditional volatility of component stocks has been examined in Rahman

(2001)98. The conditional volatility of intraday returns for each stock before and after the

introduction of derivatives is estimated with the GARCH model. Estimated parameters of

conditional volatility in pre-futures and post-futures periods are then compared to

determine if the estimated parameters have changed significantly after the introduction of

various derivatives. The data for this study consist of transaction prices from the 30

stocks comprising the DJIA. Transaction prices for April through June 1997 (pre-futures 96 Stewart Mayhew, “The Impact of Derivatives on Cash Markets: What Have We Learned?” , Journal of

Finance, Terry College of Business, University of Georgia, (February,2000,14-17. 97 M. T Raju. and Kiran Karande, "Price Discovery and Volatility on NSE Futures Market" Securities and Exchange Board of India, Working Paper Series, 7, (March. 2003) 98 Rahman Shafiqur, "The introduction of derivatives on the Dow Jones Industrial Average and their

impact on the volatility of component stocks" The Journal of Futures Markets, 21, 7, (July 2001), p. 63.

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period) and April through June 1998 (post-futures period) are used. The results suggest

that the introduction of index futures and options on the DJIA has produced no structural

changes in the conditional volatility of component stocks. The null hypothesis of no

change in conditional volatility from pre futures to post futures periods cannot be

rejected.

Gupta (2002)99 has examined the impact of index futures introduction on stock market

volatility. Further, he has also examined the relative volatility of spot market and futures

market. He has used daily price data (high, low, open and close) for BSE Sensex and

S&P CNX Nifty Index from June 1998 to June 2002. Similar data from June 9, 2000 to

March 31, 2002 have also been used for BSE Index Futures and from June 12, 2000 to

June 30, 2002 for the Nifty Index Futures. He has used four measures of volatility the

first is based upon close-to-close prices, the second is based upon open-to-open prices,

the third is Parkinson’s Extreme Value Estimator, and the fourth is Garman-Klass

measure volatility (GKV). The empirical results indicate that the over-all volatility of the

underlying stock market has declined after the introduction of index futures on both the

indices.

The impact of the introduction of index futures on the volatility of stock market in India

was examined employing daily data of Sensex and Nifty CNX for period of Jan 1997-

March 2003 in Bandivadekar and Ghosh (2005)100. The return volatility has been

modeled using GARCH framework. They found strong relationship between information

of introduction of derivatives and return volatility. They have concluded that the

introduction of derivatives has reduced the volatility of the stock market. The same study

was done by Hetamsaria and Swain (2003)101. they have examined the impact of the

introduction of index futures on the volatility of stock market in India applying regression

99 O.P. Gupta, "Effect of Introduction of Index Futures on Stock Market Volatility: The Indian Evidence" UTI Capital Market Conference Paper, (Mumbai, 2002) 100 Bandivadekar Snehal and Ghosh Saurabh, "Derivatives and Volatility on Indian Stock Markets",

Reserve Bank of India, Occasional Papers. (2005) 101 Hetamsaria Nupur and Niranjan Swain, "Impact of Introduction of Futures Market on the Spot Market: An Empirical Study" the ICFAI Journal of Applied Finance, 9, 8, (November, 2003), 34-37.

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analysis. They have used Nifty 50 index price data for the period of Jan 1998 - March

2003. They found that the volatility of the Nifty return has declined after the introduction

of index futures.

Darrat, Rahman, and Zhong (2002)102 have examined the impact of the introduction of

index futures on the volatility of stock market in India and causal relationship between

volume in the futures market and spot market. They have used EGARCH approach and

Granger Causality (G C) test. Their finding suggests that index futures trading may not be

blamed for the increasing volatility in the spot market. They found that volatility in the

spot market has produced volatility in the futures market.

Board, Sandamann and Sutcliffe (2001)103, have tested the hypothesis that increases in

the futures market trading activity increases spot market price volatility. They used the

GARCH model and Schewert Model and found that the result does not support the

hypothesis. The data samples are taken from the U K market. Jeanneau and Micu

(2003)104 have explained that information based or speculative transaction also creates a

link between volatility and activity in asset and derivatives market. This link depends in

part on whether the new information is private or public and on the type of asset traded.

In theory, the arrival of new private information should be reflected in a rise in the

volatility of return and trading volumes in single equity and equity related futures and

options.

The majority of studies have employed the standard ARCH or GARCH model to

examine volatility shifting. Mostly the findings are supporting the hypothesis that

introduction of derivatives has reduced the market volatility. These studies use daily

102 Darat Ali, Shafiqur Rahman, and Maosen Zhong, "On The Role of Futures Trading in Spot Market Fluctuations: Perpetrator of Volatility or Victim of Regret?" The Journal of Financial Research, XXV, 3, (2002),431-444. 103 Board Jhon, Sandamann Gleb and Sutcliffe Charles, “The Effect of Futures Market Volume on Spot Market Volatility", Journal of business Finance and Accounting, 28, 7&8, (October 2001), pp. 306-686. 104 Jeanneau Serge Marian Micu, "Volatility and derivatives turnover: a tenuous relationship" BIS Quarterly Review, (March 2003), 139-141.

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observations to estimate volatility, whereas interday data are used here. Given that

financial markets display high speeds of adjustment, studies based on longer intervals

such as daily observations may fail to capture information contained in intraday market

movements. Moreover, because of modern communications systems and improved

technology, volatility measures based on daily observations ignore critical information

concerning intraday price patterns. Andersen (1996)105 pointed out that the focus of the

market microstructure literature is on intraday patterns rather than interday dynamics.

This study is also based on the hypothesis that the introduction of the derivatives products

has reduced the risk inefficiency in the BSE stock market. Three derivatives products

(index futures, stock futures and index options) have been used that have been introduced

in the different time periods. The time period is also for about 8 years including the most

recent earning period as 2005-2006. Derivatives turnover also have been used for the

same return series.

Some of the studies have undertaken to investigate the impact of the introduction of

futures trading on volatility of developed and under developed economies including

Indian stock market. The majority group of researchers supported the argument that the

introduction of the futures trading stabilizes the spot market by decreasing its volatility.

Few of them are, Baldauf and Samtoni (1991) using the S&P 500 index in US, Antoinmu

and Holems (1995, Galloway and Miller (1997) using mid 400 index, Darram (2000)

using the FITSE Mid 250 contract in UK), Bologna (2002) using MIB 30 in Italy, (2003),

Gupta (2002) and Raju and Kardnde (2003)106 using NSE 50 in India. Most of the studies

show that there is decrease in the spot market volatility upon the introduction of the index

futures trading.

Another group of researchers supported that introduction of the futures trading increased

the spot market volatility there by destabilizing the market, due to futures market

105 Anderson, ‘Does the Futures Trading Increases Stock Market Volatility’, Financial Analysts Journal, Vol. 44, (1996), 63-69. 106 Raju M. T. and Kiran Karande, "Price Discovery and Volatility on NSE Futures Market" Securities and Exchange Board of India, Working Paper Series, 7, (March 2003)

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promoting speculation and high degree of leverage Figlewaski (1981), Harris (1989)

suggested uninformed speculator trader in the futures market add noise to spot market

and decrease the information content of the spot price. , Chang at el (1989) Nikki index in

the Japan, Brosan at el (1991), Lee and Ohk (1992) for Japan and UK, Kmara at el (1992)

S&P 500 in US are some of studies which supported that destabilizing hypothesis. Since

the introduction index futures trading whether decrease or increase stock market

volatility, we need to investigate empirically.

3.2 STABILIZATION ARGUMENTS AND HYPOTHESIS

There is debate how introduction of index futures trading influence cash market

volatility. One group of author's views argued that, the introduction of index futures

trading decreases spot market volatility, due to speculative traders migrated from spot to

futures market.

Grossman and Miller (1988)107 suggested that spot market volatility decreases by higher

liquidity provided by speculators. This additional liquidity allows hedging the position

and curb volatility attributes to order imbalance. There are several ways by which futures

market increases the efficiency and smoothens price variations in the underlying spot

market. Futures markets provide a mechanism for those who buy and sell the actual

commodity to hedge themselves against unfavorable price movement. Though the futures

market spreads across a large number of investors and transferred away from those

hedging spot position to professional speculators who are willing and able to bear it. The

availability of risk transference afforded by the futures market reduces the spot price

volatility because it eliminates the need to incorporate risk premium in the spot market

transaction to compensate the risk of price fluctuations. Futures’ trading attracts more

traders to spot market making it more liquid and therefore less volatile. The debate about

speculators and impacts of futures trading on spot price volatility suggesting decreases

volatility in stock market.

107 Grossman and Miller, ‘Liquidity and Volatility Aspects of Derivatives’, Journal of Business, Vol. 46, (1988), 434-453.

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Bologna (2002)108 argued that the speculation in the futures market also leads to

stabilization of the spot prices. Since futures are characterized by high degree

informational efficiency, the effect of the stabilization permits to the spot market. The

profitable speculation stabilizes the spot price because informed speculators tend to buy

when the price is low pushing it up and sell when the price is high causing it to fall.

These opposing forces constantly check the price swings and guide the price towards to

the mean level. Uninformed speculators are not successful and are eliminated from the

market. This profitable speculation in the futures market leads to a decrease spot price

volatility. Company related factors including bonus announcement, dividends, and others

also play an important role.

There are several empirical studies shows that introduction on index futures trading

improve market efficiency and reduced informational asymmetries. Darram (2000)109

also argued that introduction of the futures market leads to more complete market

enhancing the information flow. Futures market allows for new positions and expanded

investment sets and enables to position to take at lower cost. Futures’ trading brings more

information to the market and allows for quicker disseminations of the information. The

transfer of the speculative activity from spot to futures market decreases the spot market

volatility.

3.3 DESTABILIZING ARGUMENT AND HYPOTHESIS

Another group of authors views argument that, introduction of index futures trading

increases cash market volatility, due to low transaction costs in futures market induce

more uninformed speculative traders, adding noise to the market and decreases in

108 Bolgna and laura cavallo, ‘Does the introduction of stock index futures reduce stock market volatility ? Evidence from the Italian stock exchange using GARCH’, Applied Financial Economics, 12, (2002), 183-192. 109 Darren Butter worth, ‘the impact of introduction of the index futures trading on underlying stock index volatility in the case of the FISE Mid 250 contract’, Journal of Financial Economics, 7, ( 2000), 223-226.

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formatives of prices. Figlewaski (1981)110 argued that speculation in the futures market is

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

speculators gaining (and others loosing), thereby destabilizing 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 futures market produce

destabilization forces, which creates un desirable bubbles.

Kenneth and William (1992)111 suggested the futures market activity increases the spot

price variability when futures price is changed by technical factors or manipulations.

Some times futures market induces a significant amount of hedge trading without

attracting enough speculation to permit the effective risk transfer. The hedging pressure

in the futures market than spills over to the spot market when traders end up bearing risk

transfer through both futures and spot market. Futures trading increases spot price

volatility if traders in the futures market do not have good information as participant in

the spot market even if futures prices accurately reflect the information available to the

trader in the market, their collective actions pushes the spot market prices away from its

most appropriate value. This situation presents profitable opportunities to better informed

spot market participants whose trading acts to stabilize futures prices while allowing

greater volatility in the spot market.

Further, futures market are distributed information asymmetrically the information

content of the spot price is altered, spot prices variability and welfare is reduced. Since

the proposed logical arguments both support and reject the proposition of futures markets

having a destabilizing effect on spot market, it is self-evident that the theoretical debate

on how futures trading affects underlying stock market still remains rather inconclusive.

Thus the uncertainty of the existent theoretical literature implies that the issue of whether

and how futures trading affect underlying spot market remains mainly an empirical one.

110 Figlewaski S, ‘Futures Trading and Volatility in GNMA futures’, The Journal of Finance, 36, (1981), 445-456. 111 D G Kenneth and L S William, ‘Price Movements and Price Discovery in Futures and Cash Markets’, The Review of Economics and Statistics, 65, 2, (1992), 289-297.

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The effect of the introduction of stock index futures on volatility of the Italian stock

exchange was examined by Bologna and Cavallo (2002).They employed GARCH family

of techniques to capture time varying nature of volatility using daily closing price of MIB

stock index periods from 2nd January 1990 to December 1997. The result shows that,

there was no destabilization of spot market as result of the introduction of equity index

futures contracts in Italy. They concluded that the introduction of the stock index futures

trading has lead to diminish the stock market volatility, due to the increase impact on

recent news and reduced effect of the uncertainty originating from the old news.

Another study examined the impact of introduction of KOSPI 200 futures on Korean

stock market using data for the period from 1 September 1993 to December 1998. Ryoo

and Graham smith (2003)112 argued that introduction of index futures trading have

destabilizations spot market. They used ARCH/ GARCH models to capture time varying

nature of volatility phenomena in present data. The results shows futures trading

increases the speed at which information impounded into the spot market prices, reduces

the persistent of the information and increase the spot market volatility.. This study

investigated the influences of the inception of Taiwan Index future trading on spot price

volatility on the Taiwan Stock exchange using the data period from 5th January 1995 to

May 2000. The macro economic effects are controlled and asymmetric response behavior

is studied.

Chiang and Wang (2002)113 suggested that the trading of TAIEX futures has major

impact on spot price volatility mechanism, while the trading of MSCI Taiwan does not.

They used GJR GARCH model to capture the asymmetric features in the data. The result

shows that the increase asymmetric response behavior the following the beginning the

trading of two index futures reflect that a fact the major proportion of the investors in

TSE is of non institutional investors are generally un-informed and are inclined to the

112 Graham Smith, ‘ Stock Index Futures Trading and Volatility in International Equity Markets’, Journal of Futures Markets, 20, (2003), 661-685. 113 Chiang and Wang, The impact of futures trading on spot index volatility evidence from Taiwan Index futures; Applied Economic Letters, 9, (2002), 381-385.

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over react to the bad news. Meanwhile, the instruction of the TAIEX the futures trading

improves the efficiency of the information transmission from futures to spot markets.

In a study that compared the volatility of NSE 50 index before and after introduction of

Nifty futures trading, vipul (2006)114 found a decline volatility of Nifty index of each

year between 1998 and 2004. He used GARCH model to capture time varying nature of

volatility and volatility clustering phenomena present in data. The results shows that

introduction of derivatives trading has not destabilization stock market. This is largely

attributed to reduce the persistence in the previous day’s volatility. However, intraday

unconditional volatility of equity increases. This contradiction is explained by a increased

correlation between price of its constituent shares caused by arbitrage transaction in the

cash market.

The effect of the introduction of the futures and options to FTSE/ASE 20 index on

volatility of underlying was investigated. According to Nagraj and Kiran (200)115, there is

reduction in spot market volatility after introduction on stock index futures trading. They

used EGARCH technique to capture the asymmetric features in data. They points out that

asymmetric an effect of the futures trading has induced a reduction in the conditional

volatility index and consequently it has increased the efficiency.

The impact of the introduction stock index futures on underlying index volatility

evidence from India was investigated by Debashish (2008)116. They employed ARIMA

ARCH models to capture volatility of clustering and time varying nature of volatility or

heteroskedasticity using daily closing price of nifty index periods from June 2000 to May

2007. They concluded that while the introduction of the stock index trading has no effect

on underlying mean level and marginal volatility, it has significantly altered the structure

114 Vipul Bansal, ‘the Impact of the introduction of the derivatives on underline volatility :evidence from India’, Applied financial Economics, 16, (2006), 687-694. 115 Nagaraj K S and Kotha Kiran Kumar, ‘Index Futures Trading and Spot Market Volatility’, The Icfai Journal of Applied Finance, 10,.8, (2004),5-15. 116Sathya Swaroop, Debashish, , ‘ Impact of Futures Trading Activity on Stock Price volatility of NSE Nifty Stock Index’, Derivative Markets, IUP, V, 4, (2008), 75-78.

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of the stock market volatility. This can explained by new information is assimilated into

prices more rapidly then before and there is decline in the persistence of volatility since

onset of futures trading.

In a similar study done to explored the impact of introduction of index futures and

options contracts on volatility of Indian stock market, Shenbagaran (2003)117 found there

was no significant impact on spot market volatility after futures introduction. He

employed ARCH/GARCH models to capture the keteroskedasticity in returns that

characterize stock market returns. The analysis shows that introduction of futures trading

has not destabilization spot market. This can explain by introduction of derivatives

contracts improve liquidity and reduced informational asymmetries in market.

This study investigated the effect of introduction of futures trading on stock market in

USA, UK, Japan, Australia, France and Hong Kong. Shang ( 2001)118 argued that impact

of introduction of index futures on volatility of stock returns in USA, France and

Australia, rose significantly, while no significant changes in the volatility were found in

UK and Hong Kong. The different results might be attributed to macroeconomic factors

and the structure of various markets.

The effect of the index futures trading on the underlying market volatility in Australia,

Hong Kong, Japan, and UK have been examined by Lee and Ohk (1992).Using

multivariate GARCH model and they found that the stock market volatility had increased

significantly after the introduction of the stock index futures rendering it more efficiency,

volatility of the shocks reflect the information which is transmitted and absorbed rapidly

by the market. However, Australia and Hong Kong were observed to be exceptional

cases, where stock market volatility did not increase.

117 Shenbargarman Do futures and Options trading increases stock market volatility?, NSE working paper, (2003), 1-17 118 Shang, K, ‘Information flows Across Major Futures markets’, Multinational Finance Journal, 1, (2001), 255-271.

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3.4 INVESTORS’ PERCEPTIONS ABOUT DERIVATIVES:

Various organizations and researchers in India and across the world have tried to explore

the perceptions of investors in market with regard to derivatives. Following are list of

major research done to explore and understand the perceptions, attitudes, behavior of

various investors towards derivatives, bifurcated into two parts.

3.4.1 Research across the world:

Bodnar and Gebhardt (2004) 119 explored, in their comparative survey of German and US

investors’ perceptions towards derivative, that German investors are more likely to use

derivatives than US investors, with 78% of German investors using derivatives compared

to 57% of US investors. Aside from this higher overall usage, the general pattern of usage

across industry and size groupings is comparable across the two countries. In countries,

Stock and foreign currency derivative usage is most common, followed closely by

interest rate derivatives, with commodity derivatives a distant third. Usage rates across all

three classes of derivatives are higher for German investors than US investors. In contrast

to the similarities, investors in the two countries differ notably on issues such as the

primary goal of hedging, their choice of instruments, and the influence of their market

view when taking derivative positions. These differences appear to be driven by the

greater importance of financial accounting statements in Germany than the US and

stricter German corporate policies of control over derivative activities. German investors

also indicate significantly less concern about derivative related issues than US firms,

which appears to arise from a more basic and simple strategy for using derivatives.

Finally, among the derivative non-users, German investors tend to cite reasons

suggesting derivatives were needed or not whereas US investors tend to cite reasons

suggesting a possible role for derivatives, but a hesitation to use them for some reason.

While investors in both countries overwhelmingly indicate that they use derivatives 119 Bodnar, Gordon M., Gebhardt, Gunther C, ‘Wharton Survey of Derivatives Usage and Perceptions by U.S. Non-Financial Investors’, Financial Management, 24, 2, (2001), 104-114.

136

mostly for risk management, differences appear in the primary goal of using derivatives,

with German investors focusing more on managing accounting results whereas US

investors focused more on managing cash flows. German investors are more likely to

incorporate their own market view on price movement when taking positions with

derivatives than US investors. Despite this, German investors are also more relaxed about

derivatives, indicating a significantly lower level of concern about issues related to

derivatives than US firms. This attitude is consistent with the German investors’

consistently stricter attitudes and policies towards controlling derivatives activities.

However, there have been several studies on the use of derivatives by US non-financial

companies. Among these are the surveys of the Treasury Management Association

(1996), Greenwich Associates (1996), and especially two large-scale surveys conducted

by the Wharton School: one in 1994 (Bodnar, Hayt, Marston, and Smithson (1995)) and

another in late 1995 (Bodnar, Hayt, and Marston (1996)). These studies also have

provided some insight into the use of derivatives for risk management and other purposes

as well as reporting and control issues for US non-financial firms.

Very interesting and useful are the results of the survey undertaken by Berkman et al

(1997)120, where the hedging practices of the non-financial firms and investors in New

Zealand and U.S.A. are compared. The extent of derivatives usage is higher among firms

and investors in New Zealand, mainly due to the greater corporate exposure to financial

risks and despite the higher transaction costs the local firms face, whereas the local firms

also report their derivative positions to higher management more frequent than U.S. firms

do. Comparing their conclusions drawn from the investigation of derivatives use by non-

financial firms and large investors in Sweden to the previous survey in New Zealand and

U.S., Alkeback and Hagelin [Alkabd eback/Hagelin, 1999] find that derivatives usage is

more common among large firms, that the main objective of Swedish firms is also the

hedging of risks and that the lack of sufficient knowledge is the main source of concern

120 Berkman, H., Bradbury, M., 1996. Empirical Evidence on the Corporate Use of Derivatives. Financial Management, 25 (2), 5-13.

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for firms in Sweden, contrary to U.S. firms where the lack of knowledge is a matter of

least concern.

The first evidence of derivatives use by non-financial firms is presented during 1995, in a

survey conducted by Philips (1995)121 in a sample of 415 U.S. Investors including

institutional investors. 63.2% of the responding investors mention that they use

derivatives to hedge their financial risk, 90.4% of which face interest rate risk, 75.4%

face currency risk, while commodity risk faces just 36.6% of users. In addition, the

evidence verifies that derivatives are not used for speculation against market movements,

but mainly for hedging anticipated transactions and firms’ commitments. According to

the second of the series survey the fraction of derivatives users reaches 41% -despite the

extensive losses that many firms suffered during fiscal year 1995 because of derivatives

and which received great attention by the Press- and approaches 50% in the 1998 survey.

3.4.2 Research in India:

Derivative Market Review Committee (2008) was set up by SEBI to review the

developments in the Indian derivative market and to suggest the future course of action.

The committee was headed by Prof. M. Rammohan Rao. The members were Prof. P G

Apte, Dr. Nachiket Mor, Ms Chitra Ramkrishna, Ms. Deena Mehta, Dr, Sanjeevan

Kaphse. Committee investigated various issues pertaining to institutional as well as

investors and gave recommendations. Committee had suggested the introduction of mini

contracts equity indexes, option contracts with longer life, options on futures, Bond

indexes and FO contracts, exchange traded currency and credit derivatives, revision of

position limits, investor education and profiling.

121 Phillips, A., Derivatives practices and instruments surveys. Financial Management, 24 ,2, (1995), 115-125.

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Bose (2006)122 studied the attitudes and perceptions of investors about equity derivatives.

She found that Derivatives markets provide at least two very important benefits to the

investors. One is that they facilitate risk shifting, which is also known as risk

management or hedging or redistributing risk away from risk averse investors towards

those more willing and able to bear risk. People and businesses who have exposure to risk

can either hedge against that risk with a derivatives contract or transfer. She also found

that many investors have given importance to the certain company related factors being

taken into account by them for derivative trading. Factors like Corporate actions

including dividend, bonus, and results do affect derivative market and investors in

general.

Bhaumik (2007)123 studied the perceptions of investors regarding merits and demerits of

derivatives traded in Indian stock market. The study explored the preferences of various

investors towards equity futures and options. Major findings reveal that investors prefer

stock futures more than any other varieties of derivatives. All investors agree on the

benefits of risk management offered by derivatives. At the same time they commonly

agree on the impact of futures market on spot market. It was found that equity derivatives

trading is more concentrated in the top 10 urban centres, when compared with the equity

spot market.

Harish (2004124) investigated the potential of derivatives in India by surveying more than

100 brokers and investors. He found that various factors are being considered by them

while making investment into derivatives. Company related factors are perceived as most

important factors affecting to derivative market. Many investors and brokers have clearly

122 Suchismita R Bose, “Financial Derivatives I: What Indian investors think?”, Money & Finance, 6, 4 (2006) 123 Sumon K, Bhaumik,. “Financial Derivatives II: The Risks and their Management”, Money & Finance, 13,. 5, (June 2007), 22-32 124 A. S. Harish "Potential of Derivatives Market in India", The ICFAI Journal of Applied Finance, 7,5,

(Nov. 2004), pp 1-24

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expressed their views on uses of derivatives. Mostly all considered derivative market as

highly risky and volatile segment of capital market.

The question that arises is how investors judge perceive such derivative in light of its

features, merits and demerits, factors considered while investing into derivative

investment is not well captured in earlier existing works. So, based on the above literature

available, researcher has found major gap in the research with regard to investor’s

perceptions related to derivatives in the context of merits, demerits, features, factors

affecting while investing into derivatives, and satisfaction level. So researcher has

focused more on to fill this gap which is observed from existing literature.

Hence, research presented in this thesis would make an addition to existing works on

Derivatives.

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CHAPTER 4

RESEARCH METHODOLOGY

4.1 An Introduction

4.2 Objective of the Study

4.3 Hypothesis of the Study

4.4 Scope of the Study

4.5 Research Methodology

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4.1 INTRODUCTION

Research is a scientific and systematic search for pertinent information on a specific

topic. In fact, it is an art of scientific investigation. This chapter provides the detailed

view of the how the research has been carried out.

4.2 OBJECTIVE OF THE STUDY

The broad objective of this research study is “An in-depth study of Organization and

Working of Derivatives in Indian capital market.’’

4.2.1 Specific objectives of the research are:

1. To study the structure of Indian capital market and its role in Indian economy.

2. To study the derivatives traded and used in Indian capital market.

3. To study the role and impact of derivatives on Indian capital market.

4. To know the investor’s perceptions regarding Equity derivatives.

5. To know various factors affecting Investment into Equity derivatives.

4.3 HYPOTHESIS OF THE STUDY – (TEST OF DIFFERENCES)

Various hypothesis have been considered to examine significance of differences between

cities and Investor’s perceptions about derivatives. (Refer chapter no.5)

4.4 SCOPE OF THE STUDY

The scope of this research study “An in-depth study of Organization and Working of

Derivatives in Indian capital market.’’ is limited to 1) know the perception of HNI

investors regarding equity derivatives traded on the floors of NSE only, and 2) to know

the various factors considered by HNI investors while investing into Derivatives.

1. The geographical scope of the study is limited to major cities of Gujarat region

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only.

2. The researcher has restricted the study to the HNI investors only.

4.5 RESEARCH METHODOLOGY

A system of models, procedures and techniques used to find the result of a research

problem is called Research Methodology. It gives a framework and direction to the

study. The technique of data collection and the methodology of their analysis has a great

bearing on the reliability of the result arrived at. Well-planned research methodology

explains the logic behind the methods the researcher has used in the context of his

research study. It also explains why researcher has used a particular method or technique

and why he has not used others so that research results are capable of being evaluated

either by the researcher himself or by others.

4.5.1 Research Design

A research design is a specification of methods and procedures for acquiring the needed

information. It is the overall operational pattern or framework, of the project that

stipulates what type of information is to be collected from which sources and by what

procedures. Means, it is the conceptual structure within which research is conducted; it

constitutes the blue print for the collection, measurement and analysis of data.

To develop hypothesis, to isolate key variables and relationship, to provide insights into,

and understanding of the problem, exploratory research design has been used. To identify

the problem, develop an approach to the problem and to formulate an appropriate

research design secondary data have been used. To understand the perception of HNI

investors regarding their investment into Futures and options, primary information is

collected from the HNI investors of various stock broking companies.

4.5.2. Population

A population is the set of all elements of interest in a study. It is the total collection of

elements about which researcher wish to make some inferences. The population elements

143

for the study are the investors dealing in stock market.

4.5.3 Sampling Technique

Sampling techniques may be broadly classified as non-probability and probability.

Non-probability sampling relies on the personal judgment of the researcher rather than

chance to select sample elements. The researcher can arbitrarily or consciously decide

what elements to include in the sample. It may yield good estimates of the population

characteristics. Commonly used non-probability sampling techniques includes

convenience sampling, judgmental sampling, quota sampling and snowball sampling. In

probability sampling, sampling units are selected by chance. As sampling frame doesn’t

exist for the population, Probability Sampling Method can’t be applied. Therefore Non-

probability Sampling Method is appropriate sampling method for the study.

Judgmental sampling has been attempted to obtain a sample of convenient elements.

Researcher has selected HNI investors as respondents. .Responses has been collected

from the Various HNI investors across major cities of Gujarat.

4.5.4 Sampling Unit

There are more than 80 major brokerage houses present in major cities of Gujarat. HNI

investors of any brokerage houses from each major city have been selected where survey

has been conducted. Major cities include Ahmedabad, Rajkot, Baroda, and Surat only.

4.5.5 Sample

Sample is the group of respondents consisting of a portion of the target population,

carefully selected to represent the population. Means it is a subset of the population

drawn to collect data. Researcher has selected HNI investors whose daily turnover is

more than 10, 00,000 and also dealing in equity derivatives traded at NSE across major

cities of Gujarat for the study.

144

4.5.6 Sample size

There are total 200 respondents surveyed. After removing questionnaire with error and

half filled, the effective sample size taken for the study is 150.

4.5.7 Method of Data Collection

There are various methods available for the collection of the data. It includes personal

contact, telephonic survey, mail survey and electronic survey. Researcher has preferred

the personal contact method to collect the primary data as it is more effective compared

to other.

4.5.8 Tool of Data Collection

Various tools viz; interview of respondent or group of respondents, questionnaire and

observation methods; are available for data collection. Researcher has developed the

structured questionnaire comprise close-ended as well as open-ended questions for the

purpose of data collection.

The questionnaire was pre-tested among thirty selected sample respondents to check its

workability for the purpose of the study and time required to fill up the questionnaire.

4.5.9 Sources of Data

Two types of data are collected. Major source of information is primary data. The

primary data is collected from HNI investors of various stock broking companies in

major cities of Gujarat

To understand and explore the research problem, to build the theoretical frame work,

various secondary data sources are used. This includes research journals, magazines,

books, websites, research report, news papers etc.

145

4.5.10 Data Analysis

Data analysis begins with preliminary check of all questionnaires for its completeness.

Examination of the filled up questionnaire is required to detect the error, omission of

half-filled and unqualified questionnaires and to correct the errors wherever possible.

This ensures accuracy, consistency and uniformity of data. Then numerical codes have

been assigned to represent a specific response to a specific question. After this, the data

were tabulated, i.e. arranged in a logical manner in columns and rows for further analysis.

Various statistical tools have been used for the analysis of the data. Appropriate statistical

tools were applied according to the objectives and hypothesis of the study. This includes

Frequency Distribution, Cross-tabulation, Mean, Standard Deviation, Factor Analysis,

Analysis of Variance etc. The data was analyzed using Statistical Package for Social

Sciences version 12.0.

146

CHAPTER 5

DATA ANALYSIS AND INTERPRETATION

5.1 Details of the Investors Surveyed

5.2 Hypothesis Testing and Analysis of Variance

5.2.1 Findings

5.3 Factor Analysis

5.3.1 An introduction

5.3.2 Factor Analysis Process

5.3.3 Conducting Factor Analysis for Perceptions of Investors - A Detailed

Explanation

5.3.3.1 Findings

5.3.4 Conducting Factor Analysis on Factors to be considered while Investing

into Derivatives

5.3.4.1 Findings

5.3.4.2 Linking Factor Analysis Findings with Demographic Factor

5.4 Cluster Analysis

5.4.1 An introduction

5.4.2 Cluster Analysis Process

5.4.3 Conducting Cluster Analysis for Various Perception on Growth of

Derivatives in India: A Detailed Explanation

5.4.3.1 Findings

5.4.4 Conducting Cluster Analysis on Various Perceptions about Derivatives:

A Detailed Explanation

5.4.4.1 Findings

147

5.1 DETAILS OF INVESTORS SURVEYED:

50% of the investors surveyed belong to Ahmedabad, while 16.7% of the

investors belong to Surat, Baroda, and Rajkot respectively.

51.3% of the investors surveyed were from age bracket 21-30, while 31.3% of

them were from 31-40.

91.3% of investors surveyed were males.

2/3rd of investors were married.

41.3% of investors surveyed were engaged in Business, while 38% were doing

service and 20% of them were having their own profession.

45.3% of the investors surveyed had an annual income of 5 lacks.

49.3% of the investors surveyed were investing up to 5 lacks into derivatives

44.7% of the investors surveyed were investing into derivatives for the purpose of

hedging only.

40% of the investors surveyed were investing into derivatives for the purpose of

speculation only.

32% of the investors surveyed were trading into all types of derivative contracts

available at NSE ltd.

86% of the investors surveyed were trading into one month contracts.

Major findings of the survey related to investor’s perception are amplified below:

65% of the investors surveyed consider derivatives like Futures and Options are

effective risk management tools.

60% of the investors surveyed consider futures and options help in discovery of

prices in better way

82% of the investors surveyed believe that futures and options enable to expand

volume of activity.

72% of the investors believe that derivative helps to hedge risk effectively.

50% of the investors believe that derivatives induce more speculation.

32% of investors do not believe in benefit less margin benefit.

87% of the investors believe that India lacks proper accounting system.

67% of investors believe that derivatives destabilize spot market.

148

54% of investors believe that Lot size of contracts should be reduced.

80% of investors believe that derivative market regulations need to be

strengthened.

96% investors consider FII activity as important factor affecting to derivative

market.

86% investors consider Dividend as important factor.

79% investors consider Interest rate changes by RBI as an important factor

affecting to derivative investment.

91% investors consider Budget Announcement as an important factor.

96% of the investors do look at financial result of the company while investing

into derivatives.

34% of the investors were neutral about Business policy changes by company.

Table 5.1: City wise details

Frequency Percent Cumulative Percent

Valid Ahmedabad 76 50.7 50.7

Surat 25 16.7 67.3

Rajkot 25 16.7 84.0

Baroda 24 16.0 100.0

Total 150 100.0

Table 5.2: Age wise details

Frequency Percent Valid Percent Cumulative Percent

Valid <20 2 1.3 1.3 1.3

21-30 77 51.3 51.3 52.7

31-40 47 31.3 31.3 84.0

41-50 17 11.3 11.3 95.3

>50 7 4.7 4.7 100.0

Total 150 100.0 100.0

149

Table 5.3: Gender wise details

Frequency Percent Valid

Percent

Cumulative

Percent

Valid Male 137 91.3 91.3 91.3

Female 13 8.7 8.7 100.0

Total 150 100.0 100.0

Table 5.4: Marital Status


Percent

Cumulative

Percent

Married 100 66.7 66.7 66.7

Single 50 33.3 33.3 100.0

Valid

Total 150 100.0 100.0

Table 5.5: Occupation wise details


Percent

Cumulative

Percent

Service 57 38.0 38.0 38.0

Busines

s

62 41.3 41.3 79.3

Profess

ion

31 20.7 20.7 100.0

Valid

Total 150 100.0 100.0

Table 5.6: Income profile:


Percent

Cumulative

Percent

Valid Upto 5

Lacs

68 45.3 45.3 45.3

5 Lacs - 34 22.7 22.7 68.0

150

10 Lacs

10 Lacs -

20 Lacs

28 18.7 18.7 86.7

Above 20

Lacs

20 13.3 13.3 100.0

Total 150 100.0 100.0

Table 5.7: Occupation


Percent

Cumulative

Percent

Valid Service 57 38.0 38.0 38.0

Business 62 41.3 41.3 79.3

Profession 31 20.7 20.7 100.0

Total 150 100.0 100.0

Table 5.8: Proportion of Investment into Derivatives


Percent

Cumulative

Percent

Valid Upto 5

Lacs

74 49.3 49.3 49.3

5 Lacs -

10 Lacs

28 18.7 18.7 68.0

10 Lacs -

25 Lacs

27 18.0 18.0 86.0

Above 25

Lacs

21 14.0 14.0 100.0

Total 150 100.0 100.0

151

Table 5.9: Percentage of Income available for derivatives:


Percent

Cumulative

Percent

Valid Less than 10% 54 36.0 36.0 36.0

11-20% 34 22.7 22.7 58.7

21-30 36 24.0 24.0 82.7

Above 30% 26 17.3 17.3 100.0

Total 150 100.0 100.0

Table 5.10: Purpose of investment


Percent

Cumulative

Percent

Valid Hedge only 67 44.7 44.7 44.7

Speculate only 60 40.0 40.0 84.7

Investment only 20 13.3 13.3 98.0

All 3 2.0 2.0 100.0

Total 150 100.0 100.0

Table 5.11: Types of contracts:


Percent

Cumulative

Percent

Stock Futures only 21 14.0 14.0 14.0

Stock Option only 1 .7 .7 14.7

Index Futures only 8 5.3 5.3 20.0

Both Stock & Index

Futures

35 23.3 23.3 43.3

All 48 32.0 32.0 75.3

Both Stock Futures &

Options

31 20.7 20.7 96.0

Valid

Both Index futures & 6 4.0 4.0 100.0

152

Options

Total 150 100.0 100.0

Table 5.12: Education profile of investors


Percent

Cumulative

Percent

Valid Secondary 4 2.7 2.7 2.7

Graduation 80 53.3 53.3 56.0

Post Graduation 66 44.0 44.0 100.0

Total 150 100.0 100.0

Table 5.13: Contract period of trading


Percent

Cumulative

Percent

Valid One month 130 86.7 86.7 86.7

Two months 4 2.7 2.7 89.3

Three months 16 10.7 10.7 100.0

Total 150 100.0 100.0

153

5.2 HYPOTHESIS TESTING & ANALYSIS OF VARIANCE

Analysis of variance125 is used for examining differences in the mean values of the

dependent variables associated with the effect of the controlled independent variables,

after taking into account the influence of the uncontrolled independent variables.

Essentially, analysis of variance (ANOVA) is used as a test of means for two or more

populations. The null hypothesis, typically, is that all means are equal or groups were not

different in preference for or perception about something.

In its simplest form, analysis of variance must have a dependent variable that is metric.

There must also be one or more independent variable/s which must be all non-metric

(categorical). Here, Researcher has used One-way analysis of variance which involves

only one categorical variable.

Figure 5.1: ANOVA Process126 (Conducting One-way ANOVA)

125 Naresh K. Malhotra and Satyabhushan Dash, Marketing Research: An Applied Orientation, (New Delhi, Pearson Education, 2009), pp. 502-510. 126 Naresh K. Malhotra and Satyabhushan Dash, Marketing Research: An Applied Orientation, (New Delhi, Pearson Education, 2009), p. 525

Step-1

Identify the dependent and independent variable

Step-2

Decompose the total variation

Step-3

Measure the effects

Step-4

Test the Significance

154

(Source: Malhotra and Dash, Marketing Research )

(1) Identify the Dependent and Independent Variable: the dependent variable is

denoted by Y and the independent variable is denoted by X. X is a categorical variable

having c categories. There are n observations on Y for each category of X. the sample

size in each category of X is n, and the total size N = n X c.

(2) Decompose the total variation: In examining differences among means, one-way

analysis of variance involves decomposition of total variation observed in the dependent

variable. This variation is measured by the sums of squares corrected for the mean (SS)

variation within and between is measured.

(3) Measure the effects: the effects of X on Y are measured by sum of squares between

the categories of X.

(4) Test the Significance: Null hypothesis that category means are equal in population

are measured. If the associated probability is less than the significance level of 0.05, the

null hypothesis of equal population means is rejected.

(5) Interpret results: if null hypothesis is rejected, then the effect of the independent

variable is significant. In other words, the mean value of the dependent variable will be

different for different categories of independent variable.

Conducting One-way analysis of variances for various Perceptions of investors

towards Derivatives (Q.No. 8) from different Cities:

Step-5

Interpret the results

155

Table 5.14 Descriptives related to One-way ANOVA of all Perception of Investors.

N Mean Std.

Deviation

Std.

Error

Q.8S1 Ahmedabad 76 3.89 .974 .112

Surat 25 3.56 .870 .174

Rajkot 25 3.28 1.400 .280

Baroda 24 3.58 1.381 .282

Total 150 3.69 1.124 .092

Q.8S2 Ahmedabad 76 3.70 .910 .104

Surat 25 3.52 .714 .143

Rajkot 25 3.12 1.092 .218

Baroda 24 3.42 1.176 .240

Total 150 3.53 .974 .080

Q.8S3 Ahmedabad 76 3.78 .932 .107

Surat 25 4.04 .611 .122

Rajkot 25 3.96 .841 .168

Baroda 24 4.04 .751 .153

Total 150 3.89 .845 .069

Q.8S4 Ahmedabad 76 4.04 .791 .091

Surat 25 3.96 .676 .135

Rajkot 25 3.88 .927 .185

Baroda 24 4.00 .978 .200

Total 150 3.99 .823 .067

Q.8S5 Ahmedabad 76 3.39 1.297 .149

Surat 25 3.04 1.485 .297

Rajkot 25 1.88 1.394 .279

Baroda 24 2.13 1.454 .297

Total 150 2.88 1.497 .122

Q.8S6 Ahmedabad 76 3.70 .864 .099

Surat 25 3.68 .748 .150

Rajkot 25 3.92 .812 .162

Baroda 24 3.92 .830 .169

Total 150 3.77 .831 .068

Q.8S7 Ahmedabad 76 3.20 .938 .108

Surat 25 3.60 .764 .153

Rajkot 25 3.76 .926 .185

Baroda 24 3.83 .868 .177

156

Total 150 3.46 .931 .076

Q.8S8 Ahmedabad 76 3.50 1.039 .119

Surat 25 3.08 .954 .191

Rajkot 25 3.32 1.249 .250

Baroda 24 3.63 1.209 .247

Total 150 3.42 1.095 .089

Q.8S9 Ahmedabad 76 3.21 1.037 .119

Surat 25 3.52 .770 .154

Rajkot 25 3.52 1.388 .278

Baroda 24 3.38 1.345 .275

Total 150 3.34 1.116 .091

Q.8S10 Ahmedabad 76 3.80 .910 .104

Surat 25 3.08 .812 .162

Rajkot 25 3.64 1.114 .223

Baroda 24 3.79 1.103 .225

Total 150 3.65 .990 .081

Q.8S11 Ahmedabad 76 2.95 1.118 .128

Surat 25 2.68 1.215 .243

Rajkot 25 3.00 1.472 .294

Baroda 24 3.17 1.435 .293

Total 150 2.95 1.247 .102

Q.8S12 Ahmedabad 76 2.91 .982 .113

Surat 25 2.80 1.225 .245

Rajkot 25 2.68 1.314 .263

Baroda 24 3.04 1.301 .266

Total 150 2.87 1.131 .092

Q.8S13 Ahmedabad 76 3.37 1.106 .127

Surat 25 3.56 1.325 .265

Rajkot 25 3.84 1.068 .214

Baroda 24 3.58 1.100 .225

Total 150 3.51 1.140 .093

Q.8S14 Ahmedabad 76 3.84 1.046 .120

Surat 25 4.16 .898 .180

Rajkot 25 4.08 .277 .055

Baroda 24 4.13 .338 .069

Total 150 3.98 .855 .070

Q.8S15 Ahmedabad 76 3.39 1.212 .139

Surat 25 3.84 1.179 .236

Rajkot 25 3.84 .987 .197

157

Baroda 24 3.63 1.096 .224

Total 150 3.58 1.160 .095

Q.8S16 Ahmedabad 76 3.54 1.248 .143

Surat 25 2.60 1.443 .289

Rajkot 25 2.28 1.242 .248

Baroda 24 2.46 1.351 .276

Total 150 3.00 1.400 .114

Q.8S17 Ahmedabad 76 3.97 .879 .101

Surat 25 4.04 .935 .187

Rajkot 25 4.16 .374 .075

Baroda 24 4.21 .415 .085

Total 150 4.05 .767 .063

Q.8S18 Ahmedabad 76 3.78 1.078 .124

Surat 25 3.88 .971 .194

Rajkot 25 3.36 1.036 .207

Baroda 24 3.29 1.197 .244

Total 150 3.65 1.088 .089

Q.8S19 Ahmedabad 76 3.18 .828 .095

Surat 25 3.60 .913 .183

Rajkot 25 2.52 1.005 .201

Baroda 24 2.63 1.056 .215

Total 150 3.05 .975 .080

Q.8S20 Ahmedabad 76 2.75 .981 .113

Surat 25 2.60 .866 .173

Rajkot 25 2.52 1.194 .239

Baroda 24 2.58 1.213 .248

Total 150 2.66 1.035 .085

Q.8S21 Ahmedabad 76 3.34 .932 .107

Surat 25 3.68 .627 .125

Rajkot 25 3.44 1.121 .224

Baroda 24 3.38 1.173 .239

Total 150 3.42 .964 .079

Q.8S22 Ahmedabad 76 3.93 .899 .103

Surat 25 4.04 .611 .122

Rajkot 25 4.36 .860 .172

Baroda 24 4.25 .989 .202

Total 150 4.07 .875 .071

Q.8S23 Ahmedabad 76 3.91 .751 .086

Surat 25 4.12 .666 .133

158

Rajkot 25 4.00 .913 .183

Baroda 24 3.83 1.007 .206

Total 150 3.95 .809 .066

Q.8S24 Ahmedabad 76 3.91 .819 .094

Surat 25 3.92 .640 .128

Rajkot 25 3.72 .891 .178

Baroda 24 3.71 .908 .185

Total 150 3.85 .817 .067

Q.8S25 Ahmedabad 76 3.24 1.153 .132

Surat 25 3.56 1.158 .232

Rajkot 25 3.56 .917 .183

Baroda 24 3.38 .970 .198

Total 150 3.37 1.089 .089

Q.8S26 Ahmedabad 76 3.83 .900 .103

Surat 25 4.20 .645 .129

Rajkot 25 4.04 .889 .178

Baroda 24 3.96 .955 .195

Total 150 3.95 .873 .071

Q.8S27 Ahmedabad 76 3.79 1.024 .117

Surat 25 3.12 1.130 .226

Rajkot 25 2.36 1.319 .264

Baroda 24 2.42 1.381 .282

Total 150 3.22 1.305 .107

Q.8S28 Ahmedabad 76 4.12 .832 .095

Surat 25 4.16 .473 .095

Rajkot 25 3.56 .768 .154

Baroda 24 3.54 .833 .170

Total 150 3.94 .813 .066

Q.8S29 Ahmedabad 76 3.84 .910 .104

Surat 25 4.04 .351 .070

Rajkot 25 3.88 .526 .105

Baroda 24 3.92 .504 .103

Total 150 3.89 .725 .059

Q.8S30 Ahmedabad 76 4.09 .836 .096

Surat 25 4.32 .690 .138

Rajkot 25 3.60 1.080 .216

Baroda 24 3.46 1.179 .241

Total 150 3.95 .961 .078

Q.8S31 Ahmedabad 76 3.43 1.300 .149

159

Surat 25 2.92 1.441 .288

Rajkot 25 1.72 1.308 .262

Baroda 24 1.92 1.381 .282

Total 150 2.82 1.511 .123

Q.8S32 Ahmedabad 76 3.80 1.033 .118

Surat 25 3.92 1.152 .230

Rajkot 25 4.92 .277 .055

Baroda 24 4.88 .338 .069

Total 150 4.18 1.017 .083

Q.8S33 Ahmedabad 76 3.34 1.102 .126

Surat 25 3.40 1.041 .208

Rajkot 25 3.92 .954 .191

Baroda 24 3.75 .989 .202

Total 150 3.51 1.066 .087

Q.8S34 Ahmedabad 76 2.78 .826 .095

Surat 25 2.60 .707 .141

Rajkot 25 2.72 .980 .196

Baroda 24 2.79 .977 .199

Total 150 2.74 .855 .070

Q.8S35 Ahmedabad 76 3.47 1.113 .128

Surat 25 3.16 1.028 .206

Rajkot 25 2.64 .995 .199

Baroda 24 2.83 1.049 .214

Total 150 3.18 1.112 .091

Q.8S36 Ahmedabad 76 3.79 1.024 .117

Surat 25 4.12 .927 .185

Rajkot 25 3.72 1.339 .268

Baroda 24 3.75 1.225 .250

Total 150 3.83 1.098 .090

Q.8S37 Ahmedabad 76 3.75 1.034 .119

Surat 25 4.36 .490 .098

Rajkot 25 3.68 .988 .198

Baroda 24 3.67 1.007 .206

Total 150 3.83 .974 .080

Q.8S38 Ahmedabad 76 3.20 1.096 .126

Surat 25 2.56 .917 .183

Rajkot 25 2.80 1.041 .208

Baroda 24 2.96 1.160 .237

Total 150 2.99 1.087 .089

160

Table 5.15 F test and Significance values in One-Way ANOVA for Q.No.8.

Sum of

Squares

df Mean

Square

F Sig.

Q.8S1 Between Groups 8.082 3 2.694 2.183 .093

Within Groups 180.191 146 1.234

Total 188.273 149


Within Groups 134.753 146 .923

Total 141.393 149

Q.8S3 Between Groups 2.218 3 .739 1.037 .378


Total 106.293 149

Q.8S4 Between Groups .512 3 .171 .248 .863


Total 100.993 149


Within Groups 274.383 146 1.879

Total 333.840 149

Q.8S6 Between Groups 1.681 3 .560 .809 .491


Total 102.833 149



Total 129.260 149


Within Groups 173.905 146 1.191

Total 178.540 149


Within Groups 182.737 146 1.252

Total 185.660 149



Total 145.973 149

Q.8S11 Between Groups 3.011 3 1.004 .641 .590

Within Groups 228.563 146 1.565

Total 231.573 149


161

Within Groups 188.754 146 1.293

Total 190.593 149


Within Groups 189.038 146 1.295

Total 193.473 149



Total 108.940 149


Within Groups 194.503 146 1.332

Total 200.540 149


Within Groups 245.880 146 1.684

Total 292.000 149



Total 87.573 149


Within Groups 168.556 146 1.154

Total 176.273 149



Total 141.573 149


Within Groups 158.323 146 1.084

Total 159.660 149



Total 138.540 149



Total 114.193 149



Total 97.573 149



Total 99.473 149

Q.8S25 Between Groups 3.151 3 1.050 .883 .451

162

Within Groups 173.682 146 1.190

Total 176.833 149

Q.8S26 Between Groups 2.879 3 .960 1.266 .288


Total 113.573 149


Within Groups 194.865 146 1.335

Total 253.740 149



Total 98.460 149



Total 78.293 149



Total 137.573 149


Within Groups 261.384 146 1.790

Total 340.140 149



Total 154.140 149


Within Groups 161.445 146 1.106

Total 169.473 149



Total 108.860 149


Within Groups 167.401 146 1.147

Total 184.140 149


Within Groups 176.812 146 1.211

Total 179.493 149



Total 141.493 149


163

Within Groups 167.158 146 1.145

Total 175.973 149

5.2.1 Hypothesis of Study & Findings:

(1) H0: There is no significant difference between mean values for cities with regard to

Derivatives as an effective risk management tools:

The above result clearly indicates that the value of F = 2.183 with 3 and 146 degrees of

freedom, resulting in a probability of 0.093. As the associated probability value of F-test

is more than the significance level of 0.050, the null hypothesis of equal population

means is accepted. So, there is no significance difference between mean values of

dependent variable “Derivative is risk management tool” for various categories of cities.

As can be seen from above table, the sample means, with values of 3.89, 3.56, 3.28, 3.58

are also quite same.


Futures and options helps in discovery of prices in better way:

The above tables clearly indicates that the value of F = 2.98 with 3 and 146 degrees of




dependent variable “Futures and options helps in discovery of prices in better way” for

various categories of cities. As can be seen from above table, the sample means with

values are also quite same.


F&O enables to expand volume of activity:



164



dependent variable “F&O enables to expand volume of activity” for various categories of

cities. As can be seen from above table, the sample means with values are also quite

same.


Derivatives help to hedge/transfer risk completely:





dependent variable “Derivatives help to hedge/transfer risk completely” for various

categories of cities. As can be seen from above table, the sample means with values are

also quite same.


Futures and options helps to eliminate risk completely:


freedom, resulting in a probability of 0.000 As the associated probability value of F-test

is less than the significance level of 0.050, the null hypothesis of equal population means

is rejected. So, there is a significance difference between mean values of dependent

variable “Futures and options helps to eliminate risk completely” for various categories

of cities. As can be seen from above table, the sample means with values are also quite

different.


Futures and options helps to minimize risk by locking in prices:

165





dependent variable “Futures and options helps to minimize risk by locking in prices” for

various categories of cities. As can be seen from above table, the sample means with

values are also quite same.


Hedging via derivatives reaps more profits in bullish/bearish Market:





dependent variable “Hedging via derivatives reaps more profits in bullish/bearish

Market” for various categories of cities. As can be seen from above table, the sample

means with values are also quite same.


Derivatives induces more speculation:

The above tables clearly indicates that the value of F = .779 with 3 and 146 degrees of




dependent variable “Derivatives induces more speculation” for various categories of


same.


F&O helps to benefit of price discrepancy:

166





variable “F&O helps to benefit of price discrepancy” for various categories of cities. As

can be seen from above table, the sample means with values are also quite different.


Derivatives reduces transaction costs.:

The above tables clearly indicates that the value of F =0 .641 with 3 and 146 degrees of




dependent variable “Derivatives reduces transaction costs” for various categories of


same.


benefit of large position with fewer margins:

The above tables clearly indicates that the value of F =1.383 with 3 and 146 degrees of



means is accepted

(12) H0: There is no significant difference between mean values for cities with regard to a

hedge against inflation, interest rate:

167





variable “hedge against inflation, interest rate” for various categories of cities. As can be

seen from above table, the sample means with values are also quite different.


Derivatives removes problem of bad delivery:




means is accepted


Derivatives enable access to estimates of the riskiness of corporate performance and

stock prices:





variable for various categories of cities. As can be seen from above table, the sample

means with values are also quite different.


Derivatives enable the shifting of risk from those unwilling to bear risk to those willing to

bear risk



168


means is accepted


Derivative in India lacks proper accounting system, efficient internal control and strict

supervision




means is accepted


Derivatives destabilize associated spot market by increasing spot price volatility.




means is accepted


Transmission of volatility from future to spot market raises expected rate of return further

leading to misallocation of resources and the potential loss of welfare of the economy




means is accepted


Derivative trading brings more information to the market and allows for quicker

disseminations of information.

169




means is accepted


Trading in derivative does affect underlying cash market




means is accepted


Derivatives help the investors to adjust the risk and return to create and manage portfolio

carefully.




is rejected.


Derivatives provide signals of market movement efficiently




is rejected

170


Lot size of derivative contracts should be reduced to increase participation in the market.




is rejected.


Derivative market is properly regulated.




is rejected.

(25) H0: Derivatives contracts are flexible enough allowing us to deal into variety of

different trades




is rejected.


More no. of scrips should be allowed.




means is accepted

171


Trading lowers cost of capital.




is rejected


No mechanism for stock selection:




means is accepted


Cash settlement




is rejected


derivatives provides very good return in terms of capital appreciation of wealth.




means is accepted.

172

(31) H0: there is no significant difference between mean values for cities with regard to

need to strengthen regulations in India:

The above table clearly indicates that the value of F = 15.810 with 3 and 146 degrrees of

freedom, resulting into a probability of 0.0000. As the associated probability value of F

test is less than the significance level of 0.050, the null hypothesis of equal means is

rejected.

173

5.3 FACTOR ANALYSIS

5.3.1 An Introduction:

Use of multivariate statistical technique of factor analysis increased during the past

decade in all fields of business related research. As the number of variable to be

considered in multivariate techniques increases so does the need for increased knowledge

of the structure and interrelationships of the variables.

Factor analysis is an interdependence technique whose primary purpose is to define

underlying structure among the variables in the analysis127. Obviously variables play a

key in multivariate analysis. Broadly speaking, factor analysis provides the tools for

analyzing structure of the interrelationships (correlations) among a large number of

variables by defining sets of variables that are highly interrelated, known as factors.

These groups of variables (factors) that are by definition highly inter correlated, are

assumed to represent dimension within the data if we are only concerned with reducing

the number of variables, than the dimensions can guide in creating new composite

measures. On the other hand, if we have a conceptual basis for understanding the

relationship between variables, than the dimensions may actually have meaning for what

they collectively represent. In latter case, these dimensions may correspond to the

concepts that can not be adequately described by a single measure. We will see that

factor analysis presents several ways of representing these groups of variables for using

other multivariate technique.

We should note at this point that factor analytic techniques can achieve their purpose

from either an exploratory of confirmatory perspective.

127 Hair, et al., Multivariate Data Analysis, (New Delhi, Pearson Education, 2008), pp. 125-155.

174

5.3.2 Factor Analysis Process

Stage 1: Objective of factor analysis.

Factor analysis can identify the structure of variables as well as provide a process for data

reduction. In my study, the perceptions of HNI investors on 30 attributes are examined.

Stage 2: Designing a factor analysis

Understanding the stricture of the perceptions of variables require R-type factor analysis

and correlation matrix between variables, not respondents. All the variables are metric

and constitute s homogenous set of perceptions appropriate for factor analysis.

Stage 3: Assumptions in Factor analysis

The underlying statistical assumptions influence factor analysis to the extent that they

affect the derived correlations. Departure from normality, homoscedasticity, and linearity

can diminish correlations between variables. The researcher can asses the overall

significance of the correlation matrix with the Bartlett test and factorability of the overall

set of variables and individual variables using the measure of the sampling adequacy

(MSA). Because factor analysis will always derive factors, the objective is to ensure a

base level of statistical correlations within the set of variables, such that the resulting

factor structure has objective basis.

In our example, the Bartlett’s test finds that correlations, when taken collectively, are

significant at the 0.0000 level. This test only indicates the presence of nonzero

correlations, not the pattern of correlations. The measure of sampling adequacy (MSA)

looks not only at the correlations but their patterns between variables. In this situation the

overall MSA value should fall in the acceptable rage above 0.50. Variables that have

MSA values under 0.50 will be omitted and deleted from analysis. Again MSA values

will be recalculated and verified.

175

Stage 4: Deriving factors and assessing overall fit.

Given that the Principal component method of extraction will be used first, next decision

is to select the number of components to be retained for further analysis. As discussed

earlier the researcher should employ a number of different criteria in determining number

of factors to be retained for interpretation, ranging from more subjective to more

objective. In addition to assessing the importance of each component, we can also use the

eigenvalues to assist in selecting the number of factors. Factor with eigenvalues greater

then 1.0 can be retained.

Stage 5: interpreting the factors

Once the factor matrix of loading has been calculated, interpretation process proceeds by

examining the unrotated and than rotated factor matrices for significant factor loadings

and adequate communalities. If deficiencies are found, respecification of the factor is

considered. Once the factors are finalized, they can be described based on significant

factor loadings characterizing each factor.

Step 1: Examine the factor matrix of loadings for the Unrotated factor matrix: Factor

loadings, in either the unrotated or rotated factor matrices, represent the degree of

association (correlations) of each variable with each factor. The loadings take on a key

role in interpretation of the factors. We will first examine the unrotated factor solution

and determine whether the use of the rotated solution is necessary. The total amount of

variance explained by either a single factor or the overall factor solution can be compared

to the total variations in the set of variables as represented by the Trace.

Step 2: Identify the significant loadings in the unrotated factor matrix: having defined

various elements of unrotated factor matrix.

Step 3: Asses the communalities of the variables in the unrotated factor matrix: the row

sum of squared factor loadings, known as communalities, show the amount of variance in

a variable that is accounted for by the two factors taken together. The size of the

communality is a useful index for assessing how much variance in a particular variable is

176

accounted for by the factor solution. Either communality value indicates that a large

amount of the variance in variable has been extracted by the factor solution. Small

communalities show that a substantial portion of the variable’s variance is not accounted

for by the factors. Practical considerations dictate a lower than 0.50 for communalities

will be eliminated.

Give that the unrotated factor matrix did not have a completely clean set of factor

loadings; rotation technique can be applied to hopefully improve the interpretation. In

this case, the VARIMAX rotation is used. If any problems like non significant loadings,

cross loadings remain, respecification of the factor analysis has been considered.

Step 4: Respecify the factor model if needed: another rotation will be performed after

deleting any Variable having cross loadings. Many times, the number of factors will be

decreased also.

Step 5: Naming the factors: when a satisfactory solution has been derived, the next

attempt is to assign some meaning to the factors.

5.3.3 Conducting Factor analysis for Perceptions of Investors: A Detailed

Explanation

The steps involved in conducting factor analysis for the 30 statements of Question no. 8

underlying the perception of HNI investors regarding various features, benefits and

demerits of Derivatives are amplified below. A sample of 150 respondents from four

cities of Gujarat was taken. The respondents were asked to indicate their degree of

agreement with the statements using a 5-point scale (5 = Strongly Agree,,,, 1=Strongly

Disagree).

(1) Reliability Analysis: Reliability is an assessment of the degree of consistency

between multiple measurements of a variable. The objective is to ensure that responses

are not too varied across time periods so that a measurement taken at any point of time is

reliable. Researcher has used Cronbach’s alpha which is a diagnostic measure and

177

reliability coefficient assessing the consistency of entire scale. The generally agreed upon

lower limit for Cronbach’s alpha is 0.70. In our example of Question no. 8, Cronbach’s

Alpha of all 30 statements is 0.703 which is higher than acceptable level indicating a very

good overall consistency.

Table 5.16: Case Processing Summary and Reliability Statistics

(2) Testing Appropriateness by KMO Statistic and Bartlett’s test of sphericity:

As we know that researcher has to ensure that the data matrix has sufficient correlations

to justify the application of factor analysis. Formal statistics are available for testing the

appropriateness of factor model. Bartlett’s test of sphericity determines the overall

significance of all correlations within a correlation matrix. Bartlett’s test of sphericity is

used to test the null hypothesis that the variables are uncorrelated. A large value of chi-

square statistic will reject the null hypothesis indicating significance of all correlations.

Another useful statistic is Kaiser-Meyer-Olkin (KMO) measure of Sampling

Adequacy which quantify the degree of intercorrelations among the variables and

appropriateness of factor analysis. MSA value grater than 0.50 is desirable.

Table 5.17: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. 0.708

Bartlett's Test of

Sphericity

Approx. Chi-

Square 2798.884

df 435

Sig. 0.000

In our example, above result clearly indicates that the null hypothesis of all variables are

uncorrelated, is rejected because of higher value of chi-square statistic is 2798.884 with

435 degree of freedom. Significance level of 0.000 (which is ideal one) indicates that

correlations exist among the variables to proceed.

Cronbach's Alpha N of Items

.703 30

178

Even KMO measure of sampling adequacy is 0.708, a very large value, which exceeds

minimum acceptable level of 0.50, suggesting that factor analysis can be considered an

appropriate technique for analyzing the correlation matrix of Question no.8.

(3) Measure of Sampling Adequacy (Anti-Image Correlation matrix):

Apart from calculating KMO measure of sampling adequacy for appropriateness of

Factor analysis, a Variable-Specific Measure of Intercorrelations needs to be established

from Anti-Image correlation matrix. Anti-image correlation matrix shows a variable’s

correlations with the other variables in the analysis. The researcher should examine the

MSA values for each variable and exclude those falling in the unacceptable range. In

deleting variables, the researcher should first delete the variable with lowest MSA and

then recalculate the factor analysis. Continuing the process of deleting the variable with

the lowest MSA value under 0.50 until all variables have an acceptable MSA value.

For Table of Anti-image correlation matrix of question 8, refer Annexure 2

In our example, above table of anti-image correlation matrix indicates the partial

correlations among variables representing the degree to which the factors explain each

other in the results. The diagonal values contain Measures of Sampling Adequacy for

each variable and the off-diagonal values are partial correlations among variables.

In the diagonal MSA values, we can see that Variable named Q.8S29, Q.8S30, Q.8S36

are having value less than 0.50. As Variable Q.8S29 is having the lowest MSA values of

0.469 in all variables, this variable will be deleted from the list of variables and Revised

Anti-Image correlation matrix will be calculated. Every time, variable with values less

than 0.50 will be omitted from the factor analysis one at a time, with smallest one being

omitted each time. In our case, we revised Anti-image correlation matrix for another two

times deleting Variable Q8S30 and Q8S36 one by one.

(4) Factor Extraction:

179

Once it has been determined that factor analysis is appropriate technique for analyzing

the data, an appropriate method must be selected. The two basic approaches are

Principal components analysis and common factor analysis.

• Principal Component analysis is used when the objective is to determine the

minimum number of factors that will account for maximum variance in the data

for use in subsequent multivariate analysis. The factors are called Principal

Components. Specifically, with the component analysis, unities (values of 1.0) are

inserted in the diagonal of the correlation matrix, so that the full variance is

brought into the factor matrix.

• Common factor analysis, in contrast considers only the common or shared

variance.

Researcher has used Principal Component Analysis as a method of extracting factors.

Understanding communality: in order to select between the two methods of factor

extraction, we need to understand the variance for variable and how it is divided or

partitioned. Variance is value that represents the total amount of dispersion of values for

a single variable about its mean. When variance is shared with all other variables in the

analysis is known as Common variance or Communality.

Once individual variables achieve an acceptable level of MSA values from Anti-image

correlation matrix, next move is look for communalities.

SPSS table given below shows the communalities before and after extraction. Principal

component analysis works on the initial premise that all variance is common; therefore

before extraction all communalities are 1.0. The communalities in the column labeled

‘extraction’ reflect the common variance in the data structure. So for example, we can say

that 79.6% of variance associated with Question 8S1 is common or shared variance.

In our example, we can see from the table given below that, by applying Principal

Component analysis for factor extraction, Variable named Q8S38 has lowest value of

O.333 (Table 5.18) which is less than minimum acceptable value of 0.5, so this variable

will be deleted and process of extraction will be revised.

180

Table 5.18: Communalities Initial Extraction

Q.8S1 1.000 .796

Q.8S2 1.000 .747

Q.8S3 1.000 .380

Q.8S4 1.000 .672

Q.8S5 1.000 .797

Q.8S6 1.000 .573

Q.8S8 1.000 .591

Q.8S9 1.000 .777

Q.8S10 1.000 .638

Q.8S11 1.000 .676

Q.8S14 1.000 .421

Q.8S16 1.000 .840

Q.8S18 1.000 .581

Q.8S19 1.000 .762

Q.8S21 1.000 .651

Q.8S22 1.000 .577

Q.8S23 1.000 .776

Q.8S24 1.000 .672

Q.8S25 1.000 .621

Q.8S26 1.000 .763

Q.8S27 1.000 .818

Q.8S28 1.000 .571

Q.8S31 1.000 .719

Q.8S33 1.000 .721

Q.8S35 1.000 .706

Q.8S37 1.000 .623

Q.8S38 1.000 .333

Extraction Method: Principal Component Analysis.

Revised Anti-image and Revised Communality: process of revising Anti-Image

correlation matrix and Communality will be done by deleting smallest value of MSA and

Communality value respectively until all variables achieve acceptable values.

Every time MSA values and communality will be checked whenever Factor model

Respecified.

181

In our example, we deleted variables named Q8S30, Q8S36, Q8S38, Q.8S19, Q8S14,

Q.8S3, Q8S21, Q8S37 one by one by revising Anti-image correlation matrix and

Communality table.

Eigenvalues and Total Variance explained:

Eigenvalues represents the amount of variance accounted for by a factor. The table

labeled “Initial eigenvalues” gives the eigenvalues. The eigenvalues for the factors are as

expected; in decreasing order of magnitude as we go from factor one to last factor.

Component 1 explains 30.003 % of total variance. (Eigenvalues over 1 option is selected

so that our SPSS output will result in that format).

In the column labeled “extraction of sum of squared loadings”, the values are the same as

the values before extraction, except that the values for discarded factors are ignored. In

the final part of table (last column) labeled ‘Rotation of sum of squared loadings’, the

eigenvalues after rotation are displayed. Interpretation of the solution is often enhanced

by a rotation of the factors.

It is recommended that the factors extracted should account for at least 60 percent of the

total variance. In our example this comes to 70.192 % fairly higher than minimum

acceptable level.

182

Table 5.19: Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 6.301 30.003 30.003 6.301 30.003 30.003 4.314 20.544 20.544

2 3.625 17.263 47.266 3.625 17.263 47.266 3.077 14.652 35.196

3 2.158 10.278 57.544 2.158 10.278 57.544 2.942 14.010 49.206

4 1.637 7.797 65.341 1.637 7.797 65.341 2.248 10.707 59.913

5 1.019 4.851 70.192 1.019 4.851 70.192 2.159 10.280 70.192

6 .880 4.192 74.385

7 .719 3.426 77.811

8 .702 3.341 81.152

9 .642 3.056 84.208

10 .606 2.887 87.095

11 .470 2.237 89.332

12 .402 1.915 91.247

13 .362 1.724 92.971

14 .305 1.453 94.424

15 .252 1.201 95.625

16 .212 1.011 96.636

17 .180 .857 97.493

18 .175 .834 98.327

19 .140 .667 98.994

20 .115 .547 99.541

21 .096 .459 100.000


(5) Factor Rotation (Interpretation):

First, the initial unrotated Factor matrix is computed containing the factor loadings for

each variable on each factor. Factor loadings are the correlation of each variable and the

factor. Loadings indicate the degree of correspondence between the variable and the

factor. As this unrotated factor matrix does not provide any adequate interpretation of the

variables under examination, next is to employ a rotational method to achieve simpler

and more meaningful solutions. The ultimate effect of rotating the factor matrix is to

redistribute the variance from earlier factors.

The simplest case of rotation is an orthogonal factor rotation, in which the axes are

maintained at 90 degrees. one of the approach of orthogonal rotation is VARIMAX

criterion which has been applied in our example.

183

The VARIMAX method maximises the sum of variances of required loadings of the

factor matrix.

Assessing factor loadings and identifying significant / cross loading: there are

guidelines for identifying significant loadings based on sample size, which says that

Loadings + or – 0.50 or greater are considered practically significant.

Interpretation should start with first variable on the first factor and move horizontally

from left to right. When a variable is found to have more than one significant loading, it

is termed as Cross loading. Any variable having cross loading will be eliminated and

loadings will be recalculated. This process will continue till the we reach to that level

when rotated component matrix does not have any cross loading.

Table 5.20: Rotated Component Matrix (a) Component

1 2 3 4 5

Q.8S27 .862

Q.8S5 .826

Q.8S31 .790

Q.8S16 .712 .515

Q.8S33 -.678

Q.8S28 .531

Q.8S23 .892

Q.8S26 .779

Q.8S22 .760

Q.8S11 -.664

Q.8S2 .778

Q.8S4 .774

Q.8S6 .701

Q.8S1 .579 .630

Q.8S8 .506

Q.8S25 .790

Q.8S9 .737

Q.8S10 .511 -.608

184

Q.8S24 .857

Q.8S35 .605

Q.8S18 .534

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with

Kaiser Normalization. a Rotation converged in 8 iterations.

By looking at the above table, we come to know three Cross loadings with respect to

Variable named Q8S16, Q8S1, and Q.8S10 has been found. These variables will be

eliminated and next rotation process will be performed.

(6) Naming the Factors:

When a satisfactory solution has been derived, next attempt is assign some meaning to

the factors. The process involves substantive interpretation of the pattern of factor

loadings for the variables, including their signs, in an effort to name each of the factors.

In our example, naming of factors will be done based on Final Rotated Component

matrix given below.

Table 5.21: Final Rotated Component Matrix with variable name.

Variables Component

1 2 3 4

Derivative helps to manage portfolio. .870

Hedging via Derivative reaps more profits in bullish /

bearish market. .835

Derivative market is properly regulated. .798

Exchange should add / allow more no. of scrips on which

derivatives can be traded. .693

Derivative in India lacks proper accounting system, efficient

internal control and strict supervision. .596

Derivative trading brings more information to the market

and allows for quicker disseminations of information. .844

Trading in derivative does affect underlying cash market. .790

185

Derivatives provide signals of market movement efficiently. .773

Derivative reduces transaction cost in the market. .720

Futures and options induces more speculation in market

leading to destabilization of prices .829

Derivatives destabilize associated spot market by increasing

spot price volatility. .722

Trading of derivatives lower the cost of capital expected in

the market. -.655

Futures and options help to minimize risk considerably by

locking in prices. .783

Futures and options help to hedge/transfer risk efficiently. .759

Futures and options helps in discovery of prices in better

way. .709

Futures and options helps to eliminate risk completely. .520


Kaiser Normalization.

a Rotation converged in 7 iterations.

5.3.3.1 Factor Analysis Findings:

(1) Factor 1: Derivative segment:

All variable relating to this factor focuses upon Exchange related system with regard to

Adding new scrips or Requirement of proper accounting system. There is a highest

loading for derivatives help to manage portfolio followed by derivatives help to reap

profits.

(2) Factor 2: Information flow in market.

All variables focus more on information flow between derivative and spot market and its

benefits and demerits. Derivatives bring information to the market, derivative does affect

cash market are having highest loadings.

186

(3) Factor 3: Spot market volatility

All variables are related to Volume and price volatility of Derivatives affecting to spot

market. Derivatives does create volatility in the market, derivatives do destabilse

associated spot market.

(4) Factor 4: Risk Management: all variables in this factor are related to containment

of risk by derivative contracts.

5.3.4 Conducting Factor analysis on Factors to be considered while investing into

Derivatives:

The steps involved in conducting factor analysis for the 30 statements of Question no. 11

underlying the perception of HNI investors regarding various factors affecting to

Derivative investment are amplified below. A sample of 150 respondents from four cities

of Gujarat was taken. The respondents were asked to indicate their degree of importance

with the statements using a 5-point scale (5 = Most important,,,, 1=Unimportant).

(1) Reliability analysis: Researcher has used Cronbach’s alpha which is a diagnostic

measure and reliability coefficient assessing the consistency of entire scale. The generally

agreed upon lower limit for Cronbach’s alpha is 0.70. In our example of Question no. 8,

Cronbach’s Alpha of all 23 factors is 0.909 which is higher than acceptable level

indicating a very good overall consistency.

Table 5.22 Reliability Statistics

Cronbach's

Alpha

N of

Items

0.909 23

(2) Testing Appropriateness by KMO Statistic and Bartlett’s test of sphericity:

As we know that researcher has to ensure that the data matrix has sufficient correlations

to justify the application of factor analysis. Formal statistics are available for testing the

appropriateness of factor model. Bartlett’s test of sphericity determines the overall

187

significance of all correlations within a correlation matrix. Bartlett’s test of sphericity is

used to test the null hypothesis that the variables are uncorrelated. A large value of chi-

square statistic will reject the null hypothesis indicating significance of all correlations.

Another useful statistic is Kaiser-Meyer-Olkin (KMO) measure of Sampling

Adequacy which quantify the degree of intercorrelations among the variables and

appropriateness of factor analysis. MSA value grater than 0.50 is desirable.

Table 5.23: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of

Sampling Adequacy. 0.799

Bartlett's Test of

Sphericity

Approx. Chi-Square 2494.151

Df 253

Sig. .000

In our example, above result clearly indicates that the null hypothesis of all variables are

uncorrelated, is rejected because of higher value of chi-square statistic is 2494.151 with

253 degree of freedom. Significance level of 0.000 (which is ideal one) indicates that

correlations exist among the variables to proceed.

Even KMO measure of sampling adequacy is 0.799, a very large value, which exceeds

minimum acceptable level of 0.50, suggesting that factor analysis can be considered an

appropriate technique for analyzing the correlation matrix of Question no.11.

(3) Measure of Sampling Adequacy (Anti-Image Correlation matrix):

Apart from calculating KMO measure of sampling adequacy for appropriateness of

Factor analysis, a Variable-Specific Measure of Intercorrelations needs to be established

from Anti-Image correlation matrix. Anti-image correlation matrix shows a variable’s

correlations with the other variables in the analysis. The researcher should examine the

MSA values for each variable and exclude those falling in the unacceptable range. In

188

deleting variables, the researcher should first delete the variable with lowest MSA and

then recalculate the factor analysis. Continuing the process of deleting the variable with

the lowest MSA value under 0.50 until all variables have an acceptable MSA value.

Table of Anti-image correlation matrix of question 11, refer annexure No.3

In the diagonal MSA values, we can see that Variable named Q.11F15 is having value of

0.452 which is less than 0.50. This variable will be deleted from the list of variables and

Revised Anti-Image correlation matrix will be calculated. Every time, variable with

values less than 0.50 will be omitted from the factor analysis one at a time, with smallest

one being omitted each time. In our case, we revised Anti-image correlation matrix for

another two times deleting Variable Q11F150 and Q11F4 one by one.

(4) Factor Extraction:

Once it has been determined that factor analysis is appropriate technique for analyzing

the data, an appropriate method must be selected. The two basic approaches are

Principal components analysis and common factor analysis.

• Principal Component analysis is used when the objective is to determine the

minimum number of factors that will account for maximum variance in the data

for use in subsequent multivariate analysis. The factors are called Principal

Components. Specifically, with the component analysis, unities (values of 1.0) are

inserted in the diagonal of the correlation matrix, so that the full variance is

brought into the factor matrix.

• Common factor analysis, in contrast considers only the common or shared

variance.

Researcher has used Principal Component Analysis as a method of extracting factors.

Understanding communality: in order to select between the two methods of factor

extraction, we need to understand the variance for variable and how it is divided or

partitioned. Variance is value that represents the total amount of dispersion of values for

a single variable about its mean. When variance is shared with all other variables in the

analysis is known as Common variance or Communality.

189

Once individual variables achieve an acceptable level of MSA values from Anti-image

correlation matrix, next move is look for communalities.

SPSS table given below shows the communalities before and after extraction. Principal

component analysis works on the initial premise that all variance is common; therefore

before extraction all communalities are 1.0. The communalities in the column labeled

‘extraction’ reflect the common variance in the data structure. So for example, we can say

that 75.7% of variance associated with Question 11F1 is common or shared variance.

In our example, we can see from the table given below that, by applying Principal

Component analysis for factor extraction, Variable named Q11F16 has lowest value of

O.467 which is less than minimum acceptable value of 0.5, so this variable will be

deleted and process of extraction will be revised.

Table 5.24: Communalities Initial Extraction

Q.11F1 1.000 .757

Q.11F2 1.000 .686

Q.11F3 1.000 .612

Q.11F4 1.000 .656

Q.11F5 1.000 .700

Q.11F6 1.000 .782

Q.11F7 1.000 .703

Q.11F8 1.000 .865

Q.11F9 1.000 .794

Q.11F10 1.000 .685

Q.11F11 1.000 .711

Q.11F12 1.000 .753

Q.11F13 1.000 .691

Q.11F14 1.000 .726

Q.11F16 1.000 .467

Q.11F17 1.000 .832

Q.11F18 1.000 .797

Q.11F19 1.000 .648

Q.11F20 1.000 .753

Q.11F21 1.000 .806

190

Q.11F22 1.000 .569

Q.11F23 1.000 .664


Revised Anti-image and Revised Communality: process of revising Anti-Image

correlation matrix and Communality will be done by deleting smallest value of MSA and

Communality value respectively until all variables achieve acceptable values.

Every time MSA values and communality will be checked whenever Factor model

Respecified.

In our example, we deleted variables named Q11F6, Q11F4 one by one by revising Anti-

image correlation matrix and Communality table.

Eigenvalues and Total Variance explained:

Eigenvalues represents the amount of variance accounted for by a factor. The table

labeled “Initial eigenvalues” gives the eigenvalues. The eigenvalues for the factors are as

expected; in decreasing order of magnitude as we go from factor one to last factor.

Component 1 explains 40.781 % of total variance. (Eigenvalues over 1 option is selected

so that our SPSS output will result in that format).

In the column labeled “extraction of sum of squared loadings”, the values are the same as

the values before extraction, except that the values for discarded factors are ignored. In

the final part of table (last column) labeled ‘Rotation of sum of squared loadings’, the

eigenvalues after rotation are displayed. Interpretation of the solution is often enhanced

by a rotation of the factors.

It is recommended that the factors extracted should account for at least 60 percent of the

total variance. In our example this comes to 70.994 % fairly higher than minimum

acceptable level.

191

Table 5.25: Total Variance Explained and Eigenvalues Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %

1 7.748 40.781 40.781 7.748 40.781 40.781 6.532 34.377 34.377

2 2.814 14.809 55.590 2.814 14.809 55.590 2.702 14.220 48.597

3 1.689 8.890 64.480 1.689 8.890 64.480 2.426 12.769 61.366

4 1.228 6.464 70.944 1.228 6.464 70.944 1.820 9.578 70.944

5 .862 4.539 75.483

6 .721 3.797 79.280

7 .621 3.271 82.551

8 .575 3.028 85.579

9 .475 2.501 88.080

10 .408 2.146 90.226

11 .370 1.946 92.171

12 .351 1.845 94.016

13 .280 1.474 95.490

14 .214 1.125 96.615

15 .201 1.055 97.671

16 .181 .953 98.624

17 .095 .502 99.126

18 .089 .471 99.597

19 .077 .403 100.000


(5) Factor Rotation (Interpretation):

First, the initial unrotated Factor matrix is computed containing the factor loadings for

each variable on each factor. Factor loadings are the correlation of each variable and the

factor. Loadings indicate the degree of correspondence between the variable and the

factor. As this unrotated factor matrix does not provide any adequate interpretation of the

variables under examination, next is to employ a rotational method to achieve simpler

and more meaningful solutions. The ultimate effect of rotating the factor matrix is to

redistribute the variance from earlier factors.

The simplest case of rotation is an orthogonal factor rotation, in which the axes are

maintained at 90 degrees. one of the approach of orthogonal rotation is VARIMAX

criterion which has been applied in our example.

192

The VARIMAX method maximises the sum of variances of required loadings of the

factor matrix.

Assessing factor loadings and identifying significant / cross loading: there are

guidelines for identifying significant loadings based on sample size, which says that

Loadings + or – 0.50 or greater are considered practically significant.

Interpretation should start with first variable on the first factor and move horizontally

from left to right. When a variable is found to have more than one significant loading, it

is termed as Cross loading. Any variable having cross loading will be eliminated and

loadings will be recalculated. This process will continue till the we reach to that level

when rotated component matrix does not have any cross loading.

Table 5.26: Rotated Component Matrix(a) Component

1 2 3 4 5

Q.11F8 .883

Q.11F17 .876

Q.11F9 .855

Q.11F18 .825

Q.11F12 .801

Q.11F14 .799

Q.11F13 .773

Q.11F5 .755

Q.11F7 .746

Q.11F3 .607

Q.11F21 .786

Q.11F22 .699

Q.11F20 .691

Q.11F19 .683

Q.11F23 .666

Q.11F11 .863

Q.11F10 .768

Q.11F1 .735

193

Q.11F2 .701

Q.11F4 .802

Q.11F6 .570 .584


Kaiser Normalization. a Rotation converged in 7 iterations.

By looking at the above table, we come to know one Cross loadings with respect to

Variable named Q11F6 has been found. These variables will be eliminated and next

rotation process will be performed.

(6) Naming the Factors:

When a satisfactory solution has been derived, next attempt is assign some meaning to

the factors. The process involves substantive interpretation of the pattern of factor

loadings for the variables, including their signs, in an effort to name each of the factors.

In our example, naming of factors will be done based on Final Rotated Component

matrix given below.

Final Rotated Component Matrix(a)

Component

1 2 3 4

Q.11F17 .874

Q.11F8 .870

Q.11F9 .851

Q.11F18 .840

Q.11F12 .805

Q.11F14 .804

Q.11F13 .773

Q.11F5 .748

Q.11F7 .730

Q.11F3 .566

Q.11F23 .751

194

Q.11F22 .744

Q.11F21 .713

Q.11F20 .685

Q.11F19 .607

Q.11F11 .876

Q.11F10 .760

Q.11F2 .723

Q.11F1 .706


Kaiser Normalization.

a Rotation converged in 5 iterations.

Table 5.27: Final rotated matrix with variable name.

Component

1 2 3 4

GDP .874

Index of Industrial Production .870

Money market movements .851

RBI monetary policy changes .840

Tax policy changes .805

Monsoon .804

Bullion & other commodity market movements .773

Exchange rate volatility .748

Inflation .730

Volatility in Global financial markets. .566

Business policy .751

Announcement regarding IPO .744

Announcement regarding M&A .713

Bonus announcement .685

195

Cash Market Volatility .607

Budget announcement .876

Political scenario / developments .760

MF activity .723

FII activity .706

5.3.4.1 Factor Analysis Findings:

Factor 1: Economy related factors

Looking at the variables grouped in factor 1, we can interpret and name factor 1 as

Economy related factors, as mostly all the variables represent economic indicators

affecting to the market and companies in general in stock market. We see that GDP has

high loading of 0.874, IIP has loadings of 0.870, Money market movements has a loading

of 0.851 and so on. There is high degree of interrelationship among these variables.

Variables like GDP, Money market movements, Index of industrial production,

Monsoon, tax policy changes, exchange rate volatility, and inflation are included in this

factor suggesting high degree of relationship among them.

Factor 2: Company related factors

Looking at the above table of final rotated factor matrix, we see that Business policy

changes, announcement regarding IPO, M&A, Bonus, we can interpret and name factor 2

as Company related factors. Business policy changes has got highest loading suggesting

its direct impact on future prices to be considered by all investors. IPO announcement is

also considered to be an important factor affecting to the investment into derivatives.

Factor 3: Government related factors

We can interpret factor 3 components as Government related factors as any major

announcement in budget by finance minister will affect the future market as well.

Political situation has also been considered as important factor to be reckoned with.

196

Factor 4: Institutional Factors

It is evident from the fact that FII buying and selling does affect the derivative market,

which is also vouched by the investors. We can interpret this factor as Institutional factor

as Both Domestic as well as FII activity determines volatility in derivative market now.

5.3.4.2 Linking factor analysis findings with demographic factor like city:

GDP – 96% of the investors surveyed in four cities believe GDP as an important factor to

be considered while investing into derivatives. Even within four cities surveyed, 97% of

investors based in Ahmedabad perceive GDP as an important factor. 92% of the investors

based in Surat believe GDP as an important factor. While 100% of investors based in

Rajkot and Baroda have considered GDP as an important factor while investing into

derivatives.

Business policy changes – 73% of the investors surveyed in four cities believe corporate

actions like Business policy changes are an important factor. Even within four cities

surveyed, 70% of the investors based in Ahmedabad consider it as an important factor.

84% of the investors based in Surat consider Business policy changes as an important

factor. While 68% and 70% of investors based in Rajkot and Baroda respectively

consider it as an important factor.

Budget Announcement – 91% of the investors surveyed in four cities perceive budget as

an important factor. Within four cities surveyed, 91%, 88% of the investors based in

Ahmedabad and Surat respectively consider it as an important factor. While 92% and

91% of the investors based in Rajkot and Baroda attach importance to it.

FII activity – 97% of the investors surveyed in four cities consider FII as an important

variable affecting to market. Even within four cities, 97% and 92% of the investors based

in Ahmedabad and Surat respectively consider it as important factor. While 100% of the

investors of both Rajkot and Baroda consider it as an important factor.

197

5.4 CLUSTER ANALYSIS.

5.4.1 Introduction

Cluster Analysis is a class of techniques used to classify objects or cases into relatively

homogeneous groups called clusters. Cluster analysis classifies objects (respondents) so

that each object is similar to others in the cluster based on a set of selected characteristics.

The resulting clusters of objects should exhibit high internal (within-cluster) homogeneity

and high external (between-cluster) heterogeneity. In this research, cluster analysis has

been used to group similar kind of objects (respondents) based on their perceptions.

5.4.2 Cluster Analysis Process

Stage 1: Objectives of cluster analysis.

The Primary goal of cluster analysis is to partition a set of objects into two or more

groups based on similarity of the objects for a set of specified characteristics. In this

research, respondents have been grouped based on their similarity into clusters. So,

instead of viewing all of the observations as unique, they can be viewed as members of

unique clusters and profiled by their general characteristics in this research.

Stage 2: Measuring Similarity

The concept of similarity is fundamental to cluster analysis. Interobject similarity is an

empirical measure of correspondence, or resemblance, between objects to be clustered.

Interobject similarity can be measured in variety of ways, but most commonly used

measure of similarity are Distance Measures. These distance measures represent

similarity as the proximity of observations to one another across the variables in the

cluster variate. Squared Euclidean distance is the most commonly recognized measure

of distance, which is the sum of squared differences without taking the square root.

Researcher has used this measure of similarity or distance in this research.

Stage 3: Assumptions in cluster analysis.

198

The researcher has assumed that sample is representative and the results are generalisable

to the population of interest.

Stage 4: Selecting clustering procedure & deciding on the no. of clusters to be

formed.

Having selected a distance or similarity measure, the partitioning process begins.

So, the first major question to answer in developing a cluster solution involves selecting

the partitioning procedure (i.e. placing similar objects into groups or clusters). The most

widely used procedure can be classified as either (1) Hierarchical or (2) Non-

Hierarchical.

(1) Hierarchical cluster procedure: Hierarchical procedure involves n – 1 clustering

decisions that combine observations into a hierarchy or a tree like structure. Hierarchical

methods can be Agglomerative or divisive methods. In the Agglomerative methods, each

object or observations starts out as its own cluster, while in divisive methods all

observations start in a single cluster and are successively divided.

Researcher has used Agglomerative hierarchical clustering method in this research.

Among numerous Agglomerative approaches like Linkage method, variance method, and

centroid method, A commonly used Ward’s procedure of Variance method has been

applied in this Research by the researcher. In this method, for each cluster, the distance

the cluster means is calculated and then these distances are summed for all the objects.

(2) Non Hierarchical Cluster procedure: A procedure that first assigns or determines a

cluster center and then groups all objects within a pre-specified threshold values from the

center. This method is frequently referred as K-means clustering. In this method, number

of cluster required must be pre-specified.

Here, in this research, Researcher has followed two-step approach of employing

both Hierarchical and Non Hierarchical methods. First, a Hierarchical technique is

used to generate a complete set of cluster solutions and second, Non hierarchical

technique is used to form final clusters.

Stage 5: Interpretation of clusters & assigning a label.

199

The interpretation stage involves examining each cluster in terms of cluster variate to

name or assign a label accurately describing the nature of clusters.

5.4.3 Conducting Cluster Analysis for Various Perception on Growth of Derivatives

in India: A Detailed Explanation

The steps involved in conducting cluster analysis for the 8 statements of Question no. 10

underlying the perception of HNI investors regarding their agreement over the important

reason for growth of Derivatives in India are amplified below. A sample of 150

respondents from four cities of Gujarat was taken. The respondents were asked to

indicate their degree of agreement with the statements using a 5-point scale (5 = Strongly

Agree,,,, 1=Strongly Disagree).

(1) Selecting a Distance or Similarity measure

The most commonly used measure of similarity is the Squared Euclidean distance, which

is the square root of the sum of the squared differences in values for each variable, has

been used in this research.

(2) Selecting a clustering procedure

Researcher has used Agglomerative method of Hierarchical clustering which starts with

each object in a separate cluster. Clusters are formed by grouping objects into bigger

clusters. One of the procedures of Agglomerative approach is Ward’s procedure which is

used by the researcher. At each stage, the two clusters with the smallest increases in the

overall sum of squares within cluster distance are combined in this method.

(3) Identifying and deciding on the number of clusters.

This can be done by looking at Agglomeration schedule, Dendogram and Icicle plot

obtained after running a hierarchical clustering procedure to find number of clusters in

the data.

Agglomeration schedule: Useful information is contained in the agglomeration

schedule, which shows from top to bottom the number of cases or clusters being

200

combined at each stage until at the last stage. The last row indicates one cluster, the row

before that indicates a 2-cluster solution and so on. Wherever maximum difference

between coefficients occurs, the lower row indicates the number of clusters.

In our example of Question no. 10, the first line represents stage 1, with 149 clusters.

Respondents 145 and 150 are combined at this stage, as shown in the columns labeled

“Cluster Combined”. The squared Euclidean Distance between these two respondents is

given under the column labeled “Coefficients”. The column entitled “stage cluster first

appears” indicates the stage at which a cluster is first formed. To illustrate, an entry of 1

at stage 6 indicates that respondent 145 was first grouped at stage 1. The last column

“Next stage” indicates the stage at which another case or cluster is combined with this

one. Because the number in the first line of the last column is 6, we see that at stage 6,

respondent 105 is combined with 145 and 150 to form a single cluster. Similarly, the

second line represents stage 2 with 148 clusters. In stage 2, respondents 139 and 149 are

grouped together.

Table 5.28: Agglomeration Schedule

Cluster Combined

Stage Cluster First

Appears

Stage Cluster 1 Cluster 2 Coefficients Cluster 1 Cluster 2 Next Stage

1 145 150 .000 0 0 6

2 139 149 .000 0 0 12

3 138 148 .000 0 0 13

4 137 147 .000 0 0 14

5 136 146 .000 0 0 15

6 105 145 .000 0 1 26

7 134 144 .000 0 0 17

8 133 143 .000 0 0 18

9 132 142 .000 0 0 19

10 131 141 .000 0 0 20

11 130 140 .000 0 0 21

12 14 139 .000 0 2 32

13 108 138 .000 0 3 33

14 58 137 .000 0 4 34

15 1 136 .000 0 5 35

16 125 135 .000 0 0 26

201

17 104 134 .000 0 7 37

18 103 133 .000 0 8 38

19 102 132 .000 0 9 39

20 101 131 .000 0 10 40

21 31 130 .000 0 11 41

22 119 129 .000 0 0 32

23 118 128 .000 0 0 33

24 117 127 .000 0 0 34

25 116 126 .000 0 0 35

26 105 125 .000 6 16 36

27 114 124 .000 0 0 37

28 113 123 .000 0 0 38

29 112 122 .000 0 0 39

30 111 121 .000 0 0 40

31 110 120 .000 0 0 41

32 14 119 .000 12 22 42

33 108 118 .000 13 23 131

34 58 117 .000 14 24 76

35 1 116 .000 15 25 45

36 105 115 .000 26 0 125

37 104 114 .000 17 27 136

38 103 113 .000 18 28 138

39 102 112 .000 19 29 129

40 101 111 .000 20 30 109

41 31 110 .000 21 31 50

42 14 109 .000 32 0 119

43 61 107 .000 0 0 76

44 100 106 .000 0 0 45

45 1 100 .000 35 44 66

46 88 99 .000 0 0 57

47 60 98 .000 0 0 77

48 52 97 .000 0 0 103

49 38 96 .000 0 0 92

50 31 95 .000 41 0 143

51 35 94 .000 0 0 125

52 21 93 .000 0 0 96

53 84 92 .000 0 0 119

54 79 91 .000 0 0 62

55 75 90 .000 0 0 65

56 65 89 .000 0 0 72

202

57 71 88 .000 0 46 97

58 57 87 .000 0 0 103

59 85 86 .000 0 0 109

60 81 83 .000 0 0 102

61 76 80 .000 0 0 111

62 5 79 .000 0 54 85

63 59 78 .000 0 0 78

64 74 77 .000 0 0 66

65 37 75 .000 0 55 126

66 1 74 .000 45 64 70

67 68 73 .000 0 0 70

68 3 72 .000 0 0 105

69 11 69 .000 0 0 115

70 1 68 .000 66 67 88

71 7 67 .000 0 0 110

72 4 65 .000 0 56 86

73 9 64 .000 0 0 105

74 10 63 .000 0 0 86

75 12 62 .000 0 0 85

76 58 61 .000 34 43 111

77 13 60 .000 0 47 106

78 2 59 .000 0 63 117

79 55 56 .000 0 0 80

80 54 55 .000 0 79 122

81 46 49 .000 0 0 114

82 44 45 .000 0 0 104

83 18 36 .000 0 0 128

84 6 24 .000 0 0 88

85 5 12 .000 62 75 107

86 4 10 .000 72 74 87

87 4 8 .000 86 0 110

88 1 6 .000 70 84 94

89 32 41 .500 0 0 93

90 17 33 1.000 0 0 98

91 16 19 1.500 0 0 100

92 20 38 2.167 0 49 101

93 30 32 3.000 0 89 107

94 1 29 3.929 88 0 113

95 66 70 4.929 0 0 121

96 21 43 6.262 52 0 118

203

97 26 71 7.762 0 57 120

98 17 47 9.262 90 0 113

99 27 28 10.762 0 0 112

100 16 23 12.262 91 0 116

101 20 39 13.845 92 0 117

102 81 82 15.845 60 0 114

103 52 57 17.845 48 58 120

104 44 53 19.845 82 0 135

105 3 9 21.845 68 73 115

106 13 40 24.095 77 0 127

107 5 30 26.387 85 93 132

108 15 42 28.887 0 0 130

109 85 101 31.744 59 40 129

110 4 7 34.744 87 71 126

111 58 76 37.855 76 61 121

112 25 27 41.022 0 99 124

113 1 17 44.211 94 98 116

114 46 81 47.411 81 102 136

115 3 11 50.744 105 69 123

116 1 16 54.277 113 100 118

117 2 20 58.027 78 101 123

118 1 21 62.435 116 96 137

119 14 84 66.935 42 53 138

120 26 52 71.685 97 103 128

121 58 66 76.846 111 95 141

122 22 54 82.096 0 80 130

123 2 3 87.840 117 115 127

124 25 34 93.673 112 0 133

125 35 105 99.673 51 36 139

126 4 37 106.491 110 65 140

127 2 13 114.106 123 106 132

128 18 26 122.856 83 120 140

129 85 102 132.082 109 39 135

130 15 22 141.332 108 122 133

131 50 108 152.165 0 33 139

132 2 5 163.119 127 107 137

133 15 25 176.419 130 124 143

134 48 51 190.919 0 0 142

135 44 85 206.169 104 129 141

136 46 104 222.569 114 37 142

204

137 1 2 239.512 118 132 144

138 14 103 257.012 119 38 145

139 35 50 276.250 125 131 146

140 4 18 297.717 126 128 144

141 44 58 321.534 135 121 145

142 46 48 346.184 136 134 147

143 15 31 374.384 133 50 146

144 1 4 412.853 137 140 148

145 14 44 460.328 138 141 147

146 15 35 537.756 143 139 148

147 14 46 625.775 145 142 149

148 1 15 768.182 144 146 149

149 1 14 1120.980 148 147 0

If we look at agglomeration schedule, going up from the last row to first row, stage 149

represents 1 cluster solution and so on. We have to identify how many clusters are there

in data. We use the difference between rows in a measure called “Coefficient” in column

4 to identify the number of clusters in data. We see that there is difference of 362.7

(1120.98 – 768.182) between 1 cluster solution at stage 149. Further there is a difference

of 142 (768.182 – 625.77) between 2 cluster solution at stage 148. The next difference is

of 88 (625.775 – 537.75). The next one after that is 77 (537.756 – 460.32). Thereafter

differences are significantly smaller not enough to decide. So, researcher can decide

either 4 cluster or 3 cluster solution depending upon membership of case in cluster

solution. If we look at number of membership in 4 cluster solution given in table below

by making simple frequency count, we see that 4 cluster solution results in clusters with

69, 30, 39, 12 elements. However if we go for 3 cluster solution, the sizes of clusters are

69, 30 and 51 which is more meaningful and very well distributed. So 3 cluster solution

should be selected for further Non-Hierarchical method analysis.

Icicle plot: Another important part of the output is contained in the icicle plot given in

the table below. The columns correspond to the objects being clustered. The rows

correspond to the number of clusters. This figure is read from bottom to top. At first, all

cases are considered as individual clusters. Because there are 150 respondents, there are

150 clusters. At the first step, the two closest objects are combined, resulting in 149

205

clusters. The last line of figure shows these 149 clusters. These two respondents 145 and

150 that have been combined at this stage 149 have between them all Xs in rows 1

through 149. hence, each subsequent step leads to the formation of a new cluster.

Dendogram: Another graphic device that is useful in displaying clustering results is

dendogram, which is read from left to right. Vertical line represents clusters that are

joined together. This gives the same conclusion as given by Agglomeration schedule.

Ultimately we decide cluster solution form cluster membership table, in which researcher

has confirmed 3 cluster solution to be specified for further procedure.

(4) Conducting Non-Hierarchical method of analysis

Once the number of clusters is identified, Researcher has conducted non hierarchical K-

cluster analysis to derive final stable clusters. The number of cluster decided (3 in our

example) will be specified and the output will be obtained.

Non hierarchical method gives the tabular output like Initial cluster centers, Final cluster

centers, Case listing of cluster memberships, distance between final cluster centers and

no. of cases in each cluster. Final cluster centers have been used to interpret the mean

values of each variable for a cluster, and there by describe the clusters.

Table 5.29: Initial Cluster Centers

Cluster

1 2 3

Q.10S1 5 1 4

Q.10S2 5 4 4

Q.10S3 5 2 2

Q.10S4 5 2 2

Q.10S5 5 2 1

Q.10S6 4 2 5

Q.10S7 4 1 5

Q.10S8 4 1 5

206

Table 5.30: Final Cluster Centers

Cluster

1 2 3

Q.10S1 4 1 3

Q.10S2 4 5 4

Q.10S3 4 4 3

Q.10S4 4 4 3

Q.10S5 4 2 3

Q.10S6 4 4 3

Q.10S7 4 3 4

Q.10S8 4 4 4

Table 5.31 Number of Cases in each Cluster

1 68.000

2 34.000

Cluster

3 48.000

Valid 150.000

Missing .000

Table 5.32: Cluster Membership

Case Number Cluster Distance

1 1 .833

2 1 1.451

3 1 1.481

4 1 1.686

5 1 1.410

6 1 .833

7 1 1.451

8 1 1.686

9 1 1.106

10 1 1.686

11 1 1.614

12 1 1.410

13 1 1.451

14 3 2.016

15 3 2.947

207

16 1 1.501

17 1 1.420

18 1 2.435

19 1 1.967

20 1 1.346

21 1 1.208

22 3 3.320

23 1 1.668

24 1 .833

25 3 2.554

26 1 1.812

27 1 3.099

28 3 2.350

29 1 1.471

30 1 .994

31 3 2.817

32 1 1.145

33 3 1.422

34 3 2.847

35 3 2.097

36 1 2.435

37 1 2.034

38 1 1.171

39 1 1.754

40 1 2.194

41 1 1.302

42 3 3.132

43 1 1.623

44 2 2.479

45 2 2.479

46 2 1.855

47 3 1.233

48 2 4.528

49 2 1.855

50 3 3.865

51 2 4.848

52 1 2.392

53 2 2.307

54 3 1.392

55 3 1.392

208

56 3 1.392

57 1 2.026

58 2 1.444

59 1 1.451

60 1 1.451

61 2 1.444

62 1 1.410

63 1 1.686

64 1 1.106

65 1 1.686

66 3 2.222

67 1 1.451

68 1 .833

69 1 1.614

70 3 2.278

71 1 1.530

72 1 1.481

73 1 .833

74 1 .833

75 1 2.034

76 2 1.806

77 1 .833

78 1 1.451

79 1 1.410

80 2 1.806

81 2 1.790

82 2 1.706

83 2 1.790

84 3 2.780

85 3 2.016

86 3 2.016

87 1 2.026

88 1 1.530

89 1 1.686

90 1 2.034

91 1 1.410

92 3 2.780

93 1 1.208

94 3 2.097

95 3 2.817

209

96 1 1.171

97 1 2.392

98 1 1.451

99 1 1.530

100 1 .833

101 2 1.581

102 2 1.902

103 3 1.887

104 2 2.812

105 3 1.984

106 1 .833

107 2 1.444

108 3 3.003

109 3 2.016

110 3 2.817

111 2 1.581

112 2 1.902

113 3 1.887

114 2 2.812

115 3 1.984

116 1 .833

117 2 1.444

118 3 3.003

119 3 2.016

120 3 2.817

121 2 1.581

122 2 1.902

123 3 1.887

124 2 2.812

125 3 1.984

126 1 .833

127 2 1.444

128 3 3.003

129 3 2.016

130 3 2.817

131 2 1.581

132 2 1.902

133 3 1.887

134 2 2.812

135 3 1.984

210

136 1 .833

137 2 1.444

138 3 3.003

139 3 2.016

140 3 2.817

141 2 1.581

142 2 1.902

143 3 1.887

144 2 2.812

145 3 1.984

146 1 .833

147 2 1.444

148 3 3.003

149 3 2.016

150 3 1.984

The table of Final cluster centers describe the mean value of each variable for each of the

3 clusters. For example, cluster 1 is described by the mean values of variable Q10S1 = 4,

variable Q10S2 = 4 and all variables have value equal to 4 in our example. Similiarly

cluster 3 is described by variable Q10S1 = 3, variable Q10S2 = 4 and so on.

If we go back to the original variables (in this case 8 statements), and if we take into

account cluster 1 in which all variables are having values 4 which is equivalent and near

agree on the scale of 1 to 5. so we can easily describe cluster 1 consists of people who

strongly believes that all variables are having importance in explosive growth of

derivatives in India.

Similarly, cluster 2 shows people who don’t consider global factors as important factor

(mean values are equal or less than 2) but give more importance to technological

advances and risk management strategies. While cluster 3 shows respondents who are

neutral in giving their opinions regarding factors contributing behind explosive growth of


211

5.4.3.1 Cluster Analysis Findings: (Interpreting the clusters.)

After having classified respondents into 3 clusters, emphasis will be given on describing

each cluster as follows.

Cluster 1: Investors belonging to this cluster are strong believers in all the factors who

have contributed towards the growth of derivatives in India. They are sure about all

global as well domestic factors have paved the way for emergence and growth of


Cluster 2: Investors belonging to this cluster do not consider global factors as important

one in explosive growth of derivatives. Even these people reject all other global factors

like integration and FIIs as important factor. They strongly consider internal factors like

govt. policy and modernization of banking as important factor behind explosive growth

of derivatives.

Cluster 3: Investors belonging to this cluster are neutral in their opinions regarding all

the factors mentioned indicating they did not give ample weighting to any of the factors

further suggesting any other reasons for growth of derivatives in India.

Segregation of Clusters members into cities in which they live:

After having described above clusters with their characteristics, Researcher has tried to

segregate and investigate that how many investors of Ahmedabad, Surat, Rajkot, and

Baroda form a part of which clusters mentioned above.

For the purpose of segregation and identification of cluster members / investors into cities

they belong, researcher has used Table 5.32 of cluster membership. If we look at this

table, case number denotes the number of respondents / investors. Second column

indicates the cluster to which they belong. As researcher has substituted the data in one

specific order only, It is relatively easy to identify and locate the city of one investor.

Column of Case number 1 to 75 are investors of Ahmedabad, while case number 76 to

212

100 are investors of Surat. Case number 101 to 125 belong to Rajkot and remaining are

from Baroda.

Segregation Cluster 1 Members: There are total 68 members of this cluster.

49 investors of cluster 1 belong to Ahmedabad.

14 investors of cluster 1 belong to Surat.

2 investors of cluster 1 belong to Rajkot.

3 investors of cluster 1 belong to Baroda.





9 investors of cluster 2 belong to Baroda.





12 investors of cluster 3 belong to Baroda

Analysis of above Findings:

From the above data, it can be inferred that 64% of investors of Ahmedabad believe in all

the factors who have contributed towards the growth of derivatives in India. They are

sure about all global as well domestic factors have paved the way for emergence and

growth of derivatives in India. Even within the cluster 1 solution, 72% belong to

Ahmedabad. While in the case of cluster 2 solution, 44% of investors of Rajkot do not

consider global factors as important one in explosive growth of derivatives, which is also

supported by 38% of investors of Baroda. In case of cluster 3 solution, 50% of the

investors of both Rajkot and Baroda are neutral in their responses.

213

Cluster Analysis for Q.8

5.4.4 Conducting Cluster Analysis on Various Perceptions about Derivatives: A

Detailed Explanation

The steps involved in conducting cluster analysis for the 8 statements of Question no. 8

underlying the perception of HNI investors regarding their perceptions about Derivatives

in India are amplified below. A sample of 150 respondents from four cities of Gujarat

was taken. The respondents were asked to indicate their degree of agreement with the

statements using a 5-point scale (5 = Strongly Agree,,,, 1=Strongly Disagree).

(1) Selecting a Distance or Similarity measure

The most commonly used measure of similarity is the Squared Euclidean distance, which

is the square root of the sum of the squared differences in values for each variable, has

been used in this research.

(2) Selecting a clustering procedure

Researcher has used Agglomerative method Hierarchical clustering which starts with

each object in a separate cluster. Clusters are formed by grouping objects into bigger

clusters. One of the procedures of Agglomerative approach is Ward’s procedure which is

used by the researcher. At each stage, the two clusters with the smallest increases in the

overall sum of squares within cluster distance are combined in this method.

(3) Identifying and deciding on the number of clusters.

This can be done by looking at Agglomeration schedule, Dendogram and Icicle plot

obtained after running a hierarchical clustering procedure to find number of clusters in

the data.

Agglomeration schedule: Useful information is contained in the agglomeration

schedule, which shows from top to bottom the number of cases or clusters being

combined at each stage until at the last stage. The last row indicates one cluster, the row

214

before that indicates a 2-cluster solution and so on. Wherever maximum difference

between coefficients occurs, the lower row indicates the number of clusters.

In our example of Question no. 8, the first line represents stage 1, with 149 clusters.

Respondents 145 and 150 are combined at this stage, as shown in the columns labeled

“Cluster Combined”. The squared Euclidean Distance between these two respondents is

given under the column labeled “Coefficients”. The column entitled “stage cluster first

appears” indicates the stage at which a cluster is first formed. To illustrate, an entry of 1

at stage 6 indicates that respondent 145 was first grouped at stage 1. The last column

“Next stage” indicates the stage at which another case or cluster is combined with this

one. Because the number in the first line of the last column is 6, we see that at stage 6,

respondent 105 is combined with 145 and 150 to form a single cluster. Similarly, the

second line represents stage 2 with 148 clusters. In stage 2, respondents 139 and 149 are

grouped together.

Table 5.33: Agglomeration Schedule

Cluster Combined Stage Cluster First

Appears

Stage

Cluster 1 Cluster 2

Coefficients

Cluster 1 Cluster 2

Next Stage

1 145 150 .000 0 0 6

2 139 149 .000 0 0 12

3 138 148 .000 0 0 13

4 137 147 .000 0 0 14

5 136 146 .000 0 0 15

6 105 145 .000 0 1 26

7 134 144 .000 0 0 17

8 133 143 .000 0 0 18

9 132 142 .000 0 0 19

10 131 141 .000 0 0 20

11 130 140 .000 0 0 21

12 14 139 .000 0 2 32

13 108 138 .000 0 3 33

14 58 137 .000 0 4 34

215

15 1 136 .000 0 5 35

16 125 135 .000 0 0 26

17 104 134 .000 0 7 37

18 103 133 .000 0 8 38

19 102 132 .000 0 9 39

20 101 131 .000 0 10 40

21 31 130 .000 0 11 41

22 119 129 .000 0 0 32

23 118 128 .000 0 0 33

24 117 127 .000 0 0 34

25 116 126 .000 0 0 35

26 105 125 .000 6 16 36

27 114 124 .000 0 0 37

28 113 123 .000 0 0 38

29 112 122 .000 0 0 39

30 111 121 .000 0 0 40

31 110 120 .000 0 0 41

32 14 119 .000 12 22 42

33 108 118 .000 13 23 140

34 58 117 .000 14 24 60

35 1 116 .000 15 25 44

36 105 115 .000 26 0 133

37 104 114 .000 17 27 141

38 103 113 .000 18 28 129

39 102 112 .000 19 29 140

40 101 111 .000 20 30 139

41 31 110 .000 21 31 50

42 14 109 .000 32 0 145

43 61 107 .000 0 0 60

44 1 106 .000 35 0 65

45 6 100 .000 0 0 72

46 88 99 .000 0 0 53

47 60 98 .000 0 0 68

48 52 97 .000 0 0 95

49 38 96 .000 0 0 89

50 31 95 .000 41 0 144

51 35 94 .000 0 0 84

52 21 93 .000 0 0 132

53 71 88 .000 0 46 86

216

54 57 87 .000 0 0 128

55 82 83 .000 0 0 56

56 81 82 .000 0 55 103

57 76 80 .000 0 0 119

58 74 77 .000 0 0 101

59 8 65 .000 0 0 109

60 58 61 .000 34 43 146

61 18 36 .000 0 0 107

62 10 63 .500 0 0 85

63 3 72 1.500 0 0 113

64 7 67 2.500 0 0 116

65 1 73 4.214 44 0 81

66 5 91 6.214 0 0 88

67 66 70 8.214 0 0 83

68 13 60 10.214 0 47 116

69 11 69 12.714 0 0 117

70 2 59 15.214 0 0 77

71 55 56 17.714 0 0 111

72 6 68 20.381 45 0 92

73 46 49 24.881 0 0 98

74 44 45 29.881 0 0 108

75 4 89 35.381 0 0 85

76 9 64 41.881 0 0 90

77 2 78 48.714 70 0 90

78 85 86 55.714 0 0 107

79 84 90 64.214 0 0 86

80 16 30 73.214 0 0 87

81 1 62 82.375 65 0 97

82 27 33 91.875 0 0 93

83 54 66 101.875 0 67 103

84 35 43 111.875 51 0 102

85 4 10 121.875 75 62 92

86 71 84 134.175 53 79 101

87 16 19 146.508 80 0 93

88 5 79 159.175 66 0 113

89 29 38 171.842 0 49 94

90 2 9 184.808 77 76 115

91 51 53 198.308 0 0 108

92 4 6 212.785 85 72 115

217

93 16 27 228.351 87 82 112

94 20 29 243.935 0 89 102

95 32 52 259.935 0 48 110

96 17 42 276.435 0 0 112

97 1 12 293.337 81 0 109

98 46 92 310.837 73 0 119

99 25 39 328.337 0 0 123

100 15 22 345.837 0 0 126

101 71 74 363.894 86 58 118

102 20 35 383.073 94 84 121

103 54 81 402.573 83 56 124

104 26 47 422.073 0 0 120

105 28 34 442.073 0 0 106

106 23 28 463.406 0 105 114

107 18 85 485.906 61 78 126

108 44 51 508.656 74 91 111

109 1 8 532.515 97 59 117

110 24 32 556.515 0 95 121

111 44 55 581.098 108 71 127

112 16 17 605.913 93 96 114

113 3 5 631.846 63 88 122

114 16 23 658.198 112 106 125

115 2 4 684.755 90 92 122

116 7 13 711.355 64 68 135

117 1 11 738.296 109 69 137

118 71 75 767.189 101 0 124

119 46 76 796.389 98 57 127

120 26 37 826.222 104 0 131

121 20 24 856.066 102 110 123

122 2 3 889.496 115 113 135

123 20 25 923.338 121 99 130

124 54 71 957.446 103 118 132

125 16 40 995.682 114 0 134

126 15 18 1035.182 100 107 136

127 44 46 1077.285 111 119 138

128 50 57 1123.285 0 54 133

129 48 103 1169.952 0 38 143

130 20 41 1217.122 123 0 131

131 20 26 1267.297 130 120 134

218

132 21 54 1322.252 52 124 138

133 50 105 1381.586 128 36 139

134 16 20 1441.691 125 131 136

135 2 7 1502.243 122 116 137

136 15 16 1578.472 126 134 144

137 1 2 1655.371 117 135 148

138 21 44 1734.459 132 127 142

139 50 101 1822.554 133 40 142

140 102 108 1930.054 39 33 141

141 102 104 2052.554 140 37 146

142 21 50 2176.137 138 139 143

143 21 48 2317.677 142 129 147

144 15 31 2461.112 136 50 145

145 14 15 2692.347 42 144 148

146 58 102 2929.393 60 141 147

147 21 58 3367.019 143 146 149

148 1 14 3857.718 137 145 149

149 1 21 4933.127 148 147 0

If we look at agglomeration schedule, going up from the last row to first row, stage 149

represents 1 cluster solution and so on. We have to identify how many clusters are there

in data. We use the difference between rows in a measure called “Coefficient” in column

4 to identify the number of clusters in data. We see that there is difference of 1075.409

(4933.127 – 3857.718) between 1 cluster solution at stage 149. Further there is a

difference of 490 (3857.718 – 3367.019) between 2 cluster solution at stage 148. The

next difference is of 437 (3367.019 – 2929.393). The next one after that is 238 (2929.393

– 2692.347). Thereafter differences are significantly smaller not enough to decide. So,

researcher can decide either 5 cluster or 4cluster solution depending upon membership of

case in cluster solution. If we look at number of membership in 4 cluster solution given in

table below by making simple frequency count, we see that 5 cluster solution results in

clusters with 69, 30, 39, 12 , 47 elements. However if we go for 4 cluster solution, the

sizes of clusters are 34, 48, 46, 22 which is more meaningful and very well distributed.

So 4 cluster solution should be selected for further Non-Hierarchical method analysis.

219

Icicle plot: Another important part of the output is contained in the icicle plot given in

the table below. The columns correspond to the objects being clustered. The rows

correspond to the number of clusters. This figure is read from bottom to top. At first, all

cases are considered as individual clusters. Because there are 150 respondents, there are

150 clusters. At the first step, the two closest objects are combined, resulting in 149

clusters. The last line of figure shows these 149 clusters. These two respondents 145 and

150 that have been combined at this stage 149 have between them all Xs in rows 1

through 149. hence, each subsequent step leads to the formation of a new cluster.

Dendogram: Another graphic device that is useful in displaying clustering results is

dendogram, which is read from left to right. Vertical line represents clusters that are

joined together. This gives the same conclusion as given by Agglomeration schedule.

Ultimately we decide cluster solution form cluster membership table, in which researcher

has confirmed 4 cluster solution to be specified for further procedure.

(4) Conducting Non-Hierarchical method analysis

Once the number of clusters is identified, Researcher has conducted non hierarchical K-

cluster analysis to derive final stable clusters. The number of cluster decided (4 in our

example) will be specified and the output will be obtained.

Non hierarchical method gives the tabular output like Initial cluster centers, Final cluster

centers, Case listing of cluster memberships, distance between final cluster centers and

no. of cases in each cluster. Final cluster centers have been used to interpret the mean

values of each variable for a cluster, and there by describe the clusters.

Table 5.34: Initial Cluster Centers – Non Hierarchical Method

Cluster

1 2 3 4

Q.8S1 4 5 1 5

Q.8S2 4 4 1 1

220

Q.8S3 4 4 1 5

Q.8S4 4 4 2 5

Q.8S5 3 5 1 2

Q.8S6 4 2 2 4

Q.8S8 4 4 2 2

Q.8S9 2 2 4 4

Q.8S10 5 5 1 2

Q.8S11 5 2 3 2

Q.8S14 4 5 2 5

Q.8S16 3 4 1 5

Q.8S18 1 4 2 4

Q.8S19 1 2 2 4

Q.8S21 1 4 2 4

Q.8S22 2 5 4 4

Q.8S23 2 5 5 2

Q.8S24 4 4 5 2

Q.8S25 2 2 2 5

Q.8S26 2 4 4 2

Q.8S27 1 4 3 4

Q.8S28 2 4 2 2

Q.8S29 4 5 2 5

Q.8S30 4 2 3 4

Q.8S31 2 5 1 4

Q.8S33 4 2 3 4

Q.8S35 3 5 2 2

Q.8S36 3 5 4 2

Q.8S37 3 4 2 2

Q.8S38 3 5 2 4

Table 5.35: Final Cluster Centers - Non Hierarchical Method

Cluster

1 2 3 4

Q.8S1 2 5 3 4

Q.8S2 2 4 3 2

Q.8S3 3 4 3 2

Q.8S4 2 4 3 4

Q.8S5 2 5 2 4

Q.8S6 2 4 3 4

221

Q.8S8 3 4 2 3

Q.8S9 2 3 4 4

Q.8S10 3 4 3 3

Q.8S11 3 2 3 2

Q.8S14 2 4 4 4

Q.8S16 2 5 2 2

Q.8S18 2 5 4 3

Q.8S19 1 3 3 3

Q.8S21 3 4 3 3

Q.8S22 5 4 2 4

Q.8S23 4 4 4 5

Q.8S24 4 2 4 4

Q.8S25 2 3 4 4

Q.8S26 2 4 5 4

Q.8S27 2 4 3 4

Q.8S28 3 4 3 4

Q.8S29 2 4 3 3

Q.8S30 5 4 3 2

Q.8S31 1 3 3 1

Q.8S33 5 4 3 5

Q.8S35 3 3 3 4

Q.8S36 4 3 2 3

Q.8S37 4 4 2 3

Q.8S38 2 4 2 4

Table 5.36: Number of Cases in each Cluster 1 25.000

2 38.000

3 43.000

Cluster

4 44.000

Valid 150.000

Missing .000

Table 5.37: Cluster Membership Case Number Cluster Distance

1 2 2.621

2 2 2.631

3 2 3.970

4 2 3.013

222

5 2 3.506

6 2 2.194

7 2 4.907

8 2 3.822

9 2 3.903

10 2 2.897

11 2 3.573

12 2 4.469

13 2 3.856

14 4 5.732

15 4 4.636

16 4 3.267

17 4 4.967

18 4 5.147

19 4 3.889

20 2 5.239

21 2 5.949

22 4 5.911

23 4 4.828

24 4 5.291

25 4 4.680

26 4 4.781

27 4 3.617

28 4 5.350

29 4 4.066

30 4 3.528

31 4 4.814

32 4 4.795

33 4 4.177

34 4 5.640

35 4 3.267

36 4 5.147

37 4 6.891

38 4 3.146

39 4 6.003

40 4 6.667

41 4 6.738

42 4 5.380

43 4 3.642

223

44 3 4.510

45 3 4.838

46 3 4.697

47 4 5.044

48 3 7.509

49 3 4.051

50 1 7.670

51 3 4.398

52 4 3.436

53 3 5.191

54 4 3.824

55 3 4.334

56 3 4.178

57 3 4.971

58 1 4.769

59 2 2.942

60 2 3.863

61 1 4.769

62 2 2.996

63 2 2.833

64 2 3.257

65 2 3.822

66 3 3.127

67 2 4.771

68 2 2.466

69 2 4.422

70 3 3.687

71 3 3.018

72 2 4.120

73 2 2.476

74 3 3.835

75 3 5.864

76 3 5.034

77 3 3.835

78 2 3.602

79 2 5.081

80 3 5.034

81 3 2.835

82 3 2.835

224

83 3 2.835

84 3 3.436

85 1 4.212

86 1 4.479

87 3 4.971

88 3 3.018

89 2 2.852

90 3 3.336

91 2 3.580

92 3 5.130

93 2 5.949

94 4 3.267

95 4 4.814

96 4 3.146

97 4 3.436

98 2 3.863

99 3 3.018

100 2 2.194

101 3 4.461

102 1 3.917

103 3 4.576

104 1 4.893

105 3 3.371

106 2 2.621

107 1 4.769

108 1 4.860

109 4 5.732

110 4 4.814

111 3 4.461

112 1 3.917

113 3 4.576

114 1 4.893

115 3 3.371

116 2 2.621

117 1 4.769

118 1 4.860

119 4 5.732

120 4 4.814

121 3 4.461

225

122 1 3.917

123 3 4.576

124 1 4.893

125 3 3.371

126 2 2.621

127 1 4.769

128 1 4.860

129 4 5.732

130 4 4.814

131 3 4.461

132 1 3.917

133 3 4.576

134 1 4.893

135 3 3.371

136 2 2.621

137 1 4.769

138 1 4.860

139 4 5.732

140 4 4.814

141 3 4.461

142 1 3.917

143 3 4.576

144 1 4.893

145 3 3.371

146 2 2.621

147 1 4.769

148 1 4.860

149 4 5.732

150 3 3.371

The table of Final cluster centers describe the mean value of each variable for each of the

4 clusters. For example, cluster 1 is described by the mean values of variable Q8S1 = 4,

Similarly cluster 4 is described by variable Q8S1 = 2, variable Q8S2 = 3 and so on.

5.4.4.1 Cluster Analysis Findings: (Interpreting the clusters.)

If we go back to the original variables (in this case statements of perceptions), and if we

take into account cluster 1 in which many variables are having values 2 which is

226

equivalent and near disagree on the scale of 1 to 5. so we can easily describe cluster 1

consists of people who are strongly negative about the benefit of derivatives available in

market. While cluster 2 people completely opposite of cluster 1. cluster 2 members

strongly positive about benefits of derivatives in terms of hedging risk as well as

providing good return. Cluster 3 members are by and large neutral so far as benefits and

limitations of derivatives are concerned. Cluster 4 members are unique in nature as they

do agree with the benefits of derivatives but simultaneously they also agree with negative

effects of Derivatives in market especially destabilizing effects.

227

CHAPTER 6

SUMMARY AND CONCLUSIONS

6.1 An Introduction

6.2 Scope of the Study

6.3 Data Collection and Research Methodology

6.4 Emergence of Derivatives as an Important Segment in Indian Capital Market

6.5 Conclusions related to Test of Differences

6.6 Conclusions related to Factor Analysis

6.7 Conclusions related to Cluster Analysis

6.8 Limitations of the Study

6.9 Directions for Further Research

228

6.1 INTRODUCTION:

In the recent past the Indian Financial System has undergone sea changes and invented

many new channels of financial sub-systems through the process of financial reforms.

The past decade has witnessed the multiple growths in the volume of international trade




rates and stock market prices at the different financial markets have increased the

financial risks to the corporate world. Adverse changes have even threatened the very

survival of the business world. It is, therefore, to manage such risks; the new financial


known as financial derivatives. The basic purpose of these instruments is to provide

commitments to prices for future dates for giving protection against adverse movements

in future prices, in order to reduce the extent of financial risks. Not only this, they also

provide opportunities to earn profit for those persons who are ready to go for higher risks.

In other words, these instruments, indeed, facilitate to transfer the risk from those who

wish to avoid it to those who are willing to accept the same.

Today, the financial derivatives have become increasingly popular and most commonly

used in the world of finance. This has grown with so phenomenal speed all over the

world that now it is called as the derivatives revolution.

6.2 SCOPE OF STUDY

The scope of this research study “An in-depth study of Organization and Working of

Derivatives in Indian capital market.’’ is limited to 1) know the perception of HNI

investors regarding equity derivatives traded on the floors of NSE only, and 2) to know

the various factors considered by HNI investors while investing into Derivatives. The

geographical scope of the study is limited to major cities of Gujarat region only. The

researcher has restricted the study to the HNI investors only.

229

6.3 DATA COLLECTION AND RESEARCH METHODOLOGY

The data for the study is collected from secondary and primary sources. To develop

hypothesis, to isolate key variables and relationship, to provide insights into, and

understanding of, the problem, exploratory research design has been used. To identify the

problem, develop an approach to the problem and formulate an appropriate research

design, secondary data has been used. Secondary data was collected from libraries of

IIMA, NIM.

To collect information for the study, primary research has been used. Primary data was

collected through a structured questionnaire. Judgmental sampling method has been used

for data collection. The population elements have been selected based on the judgment.

HNI investors concerned with derivative trading formed the sampling unit. Data

preparation began with preliminary check of questionnaires for their correctness. Then

numerical codes were assigned to represent a specific response to a specific question. The

data was analyzed using SPSS. Hypothesis Testing using ANOVA, Factor Analysis,

Cluster Analysis methods of data analysis have been used.

6.4 EMERGENCE OF DERIVATIVES AS AN IMPORTANT SEGMENT IN

INDIAN CAPITAL MARKET.







commenced in India. These derivatives can be classified into exchange traded versus

OTC.

230

Factors contributing to the explosive growth of derivatives are price volatility,

globalization of the markets, technological developments and advances in the financial

theories. Derivative market is growing very fast in the Indian Economy. The turnover of

Derivative Market is increasing year by year in the India’s largest stock exchange NSE.

Stock futures are still most popular among all varieties of contracts available in Indian

stock market.

Equity Derivatives have prominent place in Indian capital market looking at the huge

volume and number of contracts taking place in market. After having introduced

derivatives in India in 2000, there was a need to understand the perceptions of investors

who have done some trading in this segment. The research carried out here captured the

same with regard to its benefits, uses, demerits.

6.5 CONCLUSIONS RELATED TO HYPOTHESIS TESTING (TEST OF

DIFFERENCES)

Table 6.1: List of Hypothesis

Sr. No Hypothesis Result

1 H0: There is no significant difference between mean values

for cities with regard to Derivatives as an effective risk

management tools

Accepted


for cities with regard to Futures and options helps in

discovery of prices in better way

Accepted


for cities with regard to F&O enables to expand volume of

activity

Accepted


for cities with regard to Derivatives help to hedge/transfer

risk completely.

Accepted


for cities with regard to Futures and options helps to

Rejected

231

eliminate risk completely


for cities with regard to Futures and options helps to

minimize risk by locking in prices

Accepted


for cities with regard to Hedging via derivatives reaps more

profits in bullish/bearish Market

Accepted


for cities with regard to Derivatives induces more speculation

Accepted


for cities with regard to F&O helps to benefit of price

discrepancy.

Rejected


for cities with regard to Derivatives reduces transaction costs

Accepted


for cities with regard to benefit of large position with fewer

margins.

Accepted


for cities with regard to a hedge against inflation, interest

rate.

Rejected


for cities with regard to Derivatives removes problem of bad

delivery.

Accepted


for cities with regard to Derivatives enable access to

estimates of the riskiness of corporate performance and stock

prices.

Rejected


for cities with regard to Derivatives enable the shifting of risk

from those unwilling to bear risk to those willing to bear risk.

Accepted

232


for cities with regard to Derivative in India lacks proper

accounting system, efficient internal control and strict

supervision.

Accepted


for cities with regard to Derivatives destabilize associated

spot market by increasing spot price volatility.

Accepted


for cities with regard to Transmission of volatility from

future to spot market raises expected rate of return further

leading to misallocation of resources and the potential loss of

welfare of the economy

Accepted


for cities with regard to Derivative trading brings more

information to the market and allows for quicker


Accepted


for cities with regard to Trading in derivative does affect

underlying cash market

Accepted

21 There is no significant difference between mean values for

cities with regard to Derivatives help the investors to adjust

the risk and return to create and manage portfolio carefully.

Rejected


for cities with regard to Derivatives provide signals of market

movement efficiently

Rejected


for cities with regard to Lot size of derivative contracts

should be reduced to increase participation in the market.

Rejected


for cities with regard to Cash settlement

Rejected

233

It can be concluded from the test of differences that researcher has not found any

significant variation among the investors of four cities with regard to:

- Derivatives as an effective risk management tools

- Futures and options helps in discovery of prices in better way

- F&O enable to expand volume of activity

- Derivatives help to hedge/transfer risk completely.

- Futures and options help to minimize risk by locking in prices

- Hedging via derivatives reaps more profits in bullish/bearish Market

- Derivatives induces more speculation

- Derivatives reduces transaction costs

- Benefit of large position with fewer margins.

- Derivatives removes problem of bad delivery

- Derivative in India lacks proper accounting system, efficient internal control.

- Derivatives destabilize associated spot market by increasing spot price volatility

- Trading in derivative does affect underlying cash market

It can be inferred that investors do consider derivatives as an effective risk management

tools with hedging benefits embedded in it, but at the same time they also consider

trading in derivatives affect cash market by destabilizing it. It can also be inferred from

the above that investors do believe that derivative removes the problem of bad delivery

and helps to reduce the transaction cost as large positions can be created with fewer

margins.

6.6 CONCLUSIONS RELATED TO FACTOR ANALYSIS

Factor analysis provides the tools for analyzing structure of the interrelationships

(correlations) among a large number of variables by defining sets of variables that are

highly interrelated, known as factors. These groups of variables (factors) that are by

definition highly inter correlated, are assumed to represent dimension within the data if

we are only concerned with reducing the number of variables, than the dimensions can

guide in creating new composite measures. On the other hand, if we have a conceptual

basis for understanding the relationship between variables, than the dimensions may

234

actually have meaning for what they collectively represent. In latter case, these

dimensions may correspond to the concepts that can not be adequately described by a

single measure. We will see that factor analysis presents several ways of representing

these groups of variables for using other multivariate technique.

In this study, following factors have been found to be important from the point of view of

HNI Investors. Factor analysis is bifurcated into two major segments. First part of factor

analysis was attributed to the major variables related to perceptions of investors regarding

derivatives. Researcher has applied factor analysis to reduce the data and group them into

meaningful factors. While second part of factor analysis is focusing upon various factors

considered by investors while investing into derivative.

Part I - Factor analysis on Perceptions of investors:

Following variables have been extracted after applying factor analysis technique for data

reduction:

Derivative helps to manage portfolio.

Hedging via Derivative reaps more profits in bullish / bearish market.

Derivative market is properly regulated.

Exchange should add / allow more no. of scrips on which derivatives can be

traded.

Derivative in India lacks proper accounting system, efficient internal control and

strict supervision.

Derivative trading brings more information to the market and allows for quicker


Trading in derivative does affect underlying cash market.

Derivatives provide signals of market movement efficiently.

Derivative reduces transaction cost in the market.

Futures and options induces more speculation in market leading to destabilization

of prices

Derivatives destabilize associated spot market by increasing spot price volatility.

Trading of derivatives lower the cost of capital expected in the market.

235

Futures and options help to minimize risk considerably by locking in prices.

Futures and options help to hedge/transfer risk efficiently.

Futures and options helps in discovery of prices in better way.

Futures and options help to eliminate risk completely.

Above results are in consistent with various previous studies carried out by various

researchers. The impact of the introduction of index futures on the volatility of stock

market in India was examined employing daily data of Sensex and Nifty CNX for period

of Jan 1997-March 2003 in Bandivadekar and Ghosh (2005). The return volatility has

been modeled using GARCH framework. They found strong relationship between

information of introduction of derivatives and return volatility. They have concluded that

the introduction of derivatives has reduced the volatility of the stock market. The same

study was done by Hetamsaria and Swain (2003). they have examined the impact of

the introduction of index futures on the volatility of stock market in India applying

regression analysis. They have used Nifty 50 index price data for the period of Jan 1998 -

March 2003. They found that the volatility of the Nifty return has declined after the

introduction of index futures.

Darrat, Rahman, and Zhong (2002) have examined the impact of the introduction of

index futures on the volatility of stock market in India and causal relationship between

volume in the futures market and spot market. They have used EGARCH approach and

Granger Causality (G C) test. Their finding suggests that index futures trading may not be

blamed for the increasing volatility in the spot market. They found that volatility in the

spot market has produced volatility in the futures market. Kenneth and William (1992)

suggested the futures market activity increases the spot price variability when futures

price is changed by technical factors or manipulations. Some times futures market

induces a significant amount of hedge trading without attracting enough speculation to

permit the effective risk transfer. The hedging pressure in the futures market than spills

over to the spot market when traders end up bearing risk transfer through both futures and

spot market.

236

Even above findings are also in consistent with research done across the world. Bodnar

and Gebhardt (2004) explored, in their comparative survey of German and US investors’

perceptions towards derivative, that German investors are more likely to use derivatives

than US investors, with 78% of German investors using derivatives compared to 57% of

US investors. Aside from this higher overall usage, the general pattern of usage across

industry and size groupings is comparable across the two countries. In countries, Stock

and foreign currency derivative usage is most common, followed closely by interest rate

derivatives, with commodity derivatives a distant third. Usage rates across all three

classes of derivatives are higher for German investors than US investors. In contrast to

the similarities, investors in the two countries differ notably on issues such as the primary

goal of hedging, their choice of instruments, and the influence of their market view when

taking derivative positions. These differences appear to be driven by the greater

importance of financial accounting statements in Germany than the US and stricter

German corporate policies of control over derivative activities. German investors also

indicate significantly less concern about derivative related issues than US firms, which

appears to arise from a more basic and simple strategy for using derivatives. Finally,

among the derivative non-users,

German investors tend to cite reasons suggesting derivatives were needed or not whereas

US investors tend to cite reasons suggesting a possible role for derivatives, but a

hesitation to use them for some reason. While investors in both countries overwhelmingly

indicate that they use derivatives mostly for risk management, differences appear in the

primary goal of using derivatives, with German investors focusing more on managing

accounting results whereas US investors focused more on managing cash flows. German

investors are more likely to incorporate their own market view on price movement when

taking positions with derivatives than US investors. Despite this, German investors are

also more relaxed about derivatives, indicating a significantly lower level of concern

about issues related to derivatives than US firms. This attitude is consistent with the

German investors’ consistently stricter attitudes and policies towards controlling

derivatives activities.

237

All these perceptions elaborated in above study done on German and US investors are

also getting amplified in this research also.

Part II - Factor analysis on various factors (considered as important ones by

investors):

(1) Economy related factors

Variables like GDP, Index of Industrial Production, Money market changes, RBI policy

changes, tax policy changes, Monsoon, Bullion market changes, exchange rate volatility,

volatility in global financial market, inflation grouped in factor 1, we can interpret and

name factor 1 as Economy related factors, as mostly all the variables represent economic

indicators affecting to the market and companies in general in stock market. We see that

GDP has high loading of 0.874, IIP has loadings of 0.870, and Money market movements

has a loading of 0.851 and so on. There is high level of interrelationship observed among

these variables. Economy related factors plays major role in determining stock market

movements especially in case of derivatives, which is supported by factor analysis

presented here by the researcher.

Even findings obtained from factor analysis seem to be in consistent with the study

carried out by Raju and Ghosh (2004). Raju and Ghosh has expressed their views on the

growing linkages of national markets in currency, commodity and stock with world

markets and existence of common players, have given volatility a new property – that of

its speedy transmissibility across markets. Variables like Exchange rate volatility,

inflation have been found to have lead lag relations with stock market.

Company related factors

Looking at the table of final rotated factor matrix given in factor analysis, we see that

business policy changes, announcement regarding IPO, M&A, bonus, we can interpret

and name factor 2 as Company related factors. Business policy changes have got highest

loading suggesting its direct impact on future prices to be considered by all investors.

IPO announcement is also considered to be an important factor affecting to the

238

investment into derivatives. There is a high level of interrelationship observed among

these variables. It seems that corporate actions taken by company does affect derivative

market scenario which is supported by factor analysis findings presented by the

researcher.

Government related factors

We can interpret factor 3 components as Government related factors as any major

announcement in budget by finance minister will affect the future market as well.

Political situation has also been considered as important factor to be reckoned with.

There is no doubt that budget has got special place in the minds of investors which is

very well recognized and got reflected in the factor analysis findings.

Factor 4: Institutional Factors

It is evident from the fact that FII buying and selling does affect the derivative market,

which is also vouched by the investors. We can interpret this factor as Institutional factor

as Both Domestic as well as FII activity determines volatility in derivative market now.

FII in Indian market has emerged as most important player affecting to derivative

segment also.

Many previous studies have also revealed above factors as an important in terms of their

impact on derivative market. Notable ones are studies carried out by Raju and Ghosh

(2004), Bologna (2002).

Researcher has applied factor analysis technique to reduce the number of variables into

meaningful and important ones to be considered for further research also.

6.7 CONCLUSIONS RELATED TO CLUSTER ANALYSIS.

The Primary goal of cluster analysis was to partition a set of objects into two or more

groups based on similarity of the objects for a set of specified characteristics. In this

research, respondents have been grouped based on their similarity into clusters. So,

239

instead of viewing all of the observations as unique, they can be viewed as members of

unique clusters and profiled by their general characteristics in this research.

Cluster Analysis is a class of techniques used to classify objects or cases into relatively

homogeneous groups called clusters. Cluster analysis classifies objects (respondents) so

that each object is similar to others in the cluster based on a set of selected characteristics.

The resulting clusters of objects should exhibit high internal (within-cluster) homogeneity

and high external (between-cluster) heterogeneity. In this research, cluster analysis has

been used to group similar kind of objects (respondents) based on their perceptions. After

having classified respondents into 3 clusters, emphasis will be given on describing each

cluster as follows.

Respondents belonging to first cluster are strong believers in all the factors who have

contributed towards the growth of derivatives in India. They are sure about all global as

well domestic factors have paved the way for emergence and growth of derivatives in

India.

Respondents belonging to second cluster do not at all consider global factors as important

one in explosive growth of derivatives. Even these people reject all other global factors

like integration and FIIs as important factor. They strongly consider internal factors like

govt. policy and modernization of banking as important factor behind explosive growth

of derivatives.

Respondents belonging to third cluster are neutral in their opinions regarding all the

factors mentioned indicating they did not give ample weighting to any of the factors

further suggesting any other reasons for growth of derivatives in India.

From findings of cluster analysis, it can be inferred that 64% of investors of Ahmedabad

believe in all the factors who have contributed towards the growth of derivatives in India.

They are sure about all global as well domestic factors have paved the way for emergence

and growth of derivatives in India. Even within the cluster 1 solution, 72% belong to

240

Ahmedabad. While in the case of cluster 2 solution, 44% of investors of Rajkot do not

consider global factors as important one in explosive growth of derivatives, which is also

supported by 38% of investors of Baroda. In case of cluster 3 solution, 50% of the

investors of both Rajkot and Baroda are neutral in their responses.

6.8 LIMITATIONS OF STUDY

This research is exploratory in nature given the methodology employed in exploring the

subject under scrutiny. This study is focused on one single state viz., Gujarat and also is

limited to HNI investors only. Theoretical extensions and comparing the findings of this

study with existing theories is another possible avenue for future research. Segregation of

cluster members into city wise data was difficult one and considered as major limitation.

Therefore, generalization of the findings of this study can not be applied to any other

states of India and even all types of investors.

6.9 DIRECTIONS FOR FURTHER RESEARCH

One obvious direction for further research would be to sample a wide variety of investors

with more diverse demographic backgrounds as this will provide better insights to

understand the perceptions of investors regarding derivatives. It would be useful to

extend the geographical scope and type and number of investors to gain better

understanding of working of derivatives.

In this study, most of the variables included in this research and measurements of these

variables were selected and developed respectively from the previous studies

investigating investors’ perceptions about derivatives. A great deal of care has been taken

to explore the variables explaining major perceptions and factors considered while

investing into derivatives. Still, the researcher is left with a feeling that more number of

variables would have been added. A forward step in future would be to include other

possible variables explaining the perceptions of investors regarding derivatives.

241

The future research may be conducted to investigate the application part of derivatives

and perceptions about it. Further research may be needed to generalize the findings by

including various categories of investors rather than HNI investors only. Further studies

can refine the measurement scales used in this research by using multi items and ranking

scales to know importance of each variables used.

242

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Annexure - 1

Questionnaire Dear Sir/Madam,

This survey is carried out to understand the HNI investors’ perception regarding derivatives in Indian capital market. We request you to kindly fill up the questionnaire for the same. The data provided by you will be kept confidential and is purely for academic purpose.

Personal Details: Name of the respondent: City: Gender: Male Female Age (yrs): >20 21-30 31-40 41-50 50> Marital Status: Married Single No. of Family members: < 5 6-10 11-15 15> Education: Primary Secondary Graduation Post-Graduation

Illiterate Occupation: Service (Govt/Private) Business Profession Any other (specify) ________ Income (Annual): Up to Rs.5, 00,000 Rs.5, 00,000-10, 00,000

Rs. 10, 00,000-20, 00,000 Above 20, 00,000 Q.1 Do you invest in equity derivatives?

Yes No Q.2 How much do you invest in derivatives? < Rs. 5, 00,000 Rs. 5, 00,000-10, 00,000

Rs. 10, 00,000-25, 00,000 > Rs. 25, 00,000

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Q.3 Normally, What percentage of your income is available for investment into derivatives?

Less than 10 % Between 11 to 20 % Between 21 to 30 %

More than 30 % Q.4 Kindly tick mark your purpose of investment into derivatives. To Hedge to Speculate to Invest To Arbitrage Q.5 Kindly tick mark the type of derivative in which you are trading

Futures contract only Option contract only Both futures and options

Q.6 Kindly tick mark derivative contract in which you are trading. Stock futures index futures

Stock options Index options Q.7 Tick mark the contract maturity period in which you are trading. 1 month 2 months 3 months Q.8 Rate the following statements on a five point scale below.

5 Strongly Agree 4 Agree 3 Neither Agree nor Disagree 2 Disagree 1 Strongly Disagree

(1) Derivatives like Futures and Options are effective risk management tools.

Strongly agree Agree Neither agree nor disagree Disagree Strongly Disagree

(2) Futures and options helps in discovery of prices in more better way.

Strongly agree Agree Neither agree nor disagree Disagree Strongly

Disagree

(3) Futures and options enables to expand volume of activity Strongly agree Agree Neither agree nor disagree Disagree Strongly

Disagree

250

(4) Futures and options helps to hedge/transfer risk efficiently.


Disagree

(5) Futures and options helps to eliminate risk completely.


(6) Futures and options help to minimize risk considerably by locking in prices.


(7) Derivatives enhance liquidity in market.


Disagree (8) Hedging via Derivative reaps more profits in bullish / bearish market.


Disagree (9) Futures and options induces more speculation in market leading to destabilization

of prices Strongly agree Agree Neither agree nor disagree Disagree Strongly

Disagree (10) Futures and options help to take benefit of price discrepancy in the two markets

simultaneously.


(11) Derivatives reduce transaction costs in the markets.


Disagree (12) Derivatives assist in appropriate and superior allocation of resources to manage

portfolio.

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(13) Derivatives induces more volatility by creating more risk


Disagree (14) One can take large positions in derivative markets by depositing fewer margins.


(15) Derivatives are very risky and highly leveraged instruments.


Disagree (16) Derivatives can be used to hedge against interest rates fluctuations, inflation and

market risk.


(17) Derivatives gives more variety or combinations to create positions in the market.


(18) Derivative contracts are settled in cash which removes problems of bad delivery

and counterparty risk.


(19) Derivatives enable access to estimates of the riskiness of corporate performance

and stock prices.


(20) Derivatives enable estimation of the price of risk and the price to be paid to

avoid risk.


252

(21) Derivatives enable the shifting of risk from those unwilling to bear risk to those

willing to bear risk.


(22) Derivative in India lacks proper accounting system, efficient internal control and

strict supervision.


(23) Derivatives destabilize associated spot market by increasing spot price volatility.


(24) Transmission of volatility from future to spot market raises expected rate of

return further leading to misallocation of resources and the potential loss of welfare of the economy.


Disagree (25) Derivative trading brings more information to the market and allows for quicker



(26) Trading in derivative does affect underlying cash market.


(27) Derivatives help the investors to adjust the risk and return to create and manage

portfolio carefully.


(28) Derivatives provide signals of market movement efficiently.


253

(29) Derivatives contracts are flexible enough allowing us to deal into variety of

different trades.


(30) Lot size of derivative contracts should be reduced to increase participation in the

market.


(31) Derivative market is properly regulated.


(32) There is a need to strengthen regulation on derivatives in India.


(33) Exchange should add / allow more no. of scrips on which derivatives can be

traded.


(34) Trading of derivative on company’s equity leads to significant reduction of

equity’s beta. Strongly agree Agree Neither agree nor disagree Disagree Strongly

Disagree (35) Trading of derivatives lower the cost of capital expected in the market.


(36) There is no proper timing and mechanism for stock selection for derivative

segment.


(37) Derivatives contracts should be allowed to settle via cash market holdings.

254


(38) Derivatives provide very good return in terms of capital appreciation of wealth.


Disagree Q.9 Tick mark the following important characteristic features of derivatives that one

can leverage. (any one) Low risk – low reward Low risk – high reward High risk – low reward High risk – high reward.

Q.10 Following factor can best be considered as important factor for explosive growth

and faster adoption of derivatives in India. Rate as follows. 5 = Strongly Agree 4 = Agree 3 = Neither Agree nor Disagree 2 = Disagree 1 = Strongly Disagree

(1) The increased volatility in global financial markets and its impact on India.

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree (2) The technological advances enabling cheaper communications and computing power

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree (3) Wider choices of risk management strategies and instrument that optimally combine

the risk and return over a large number of financial assets.

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree (4) Deregulation in financial market and market oriented policies by government

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree (5) Increased integration of domestic financial market with global ones.

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree

255

(6) Innovations in the derivatives markets have led to the diversification of risk over a large number of financial assets, leading to higher returns

Strongly agree agree Neither agree nor disagree Disagree Strongly

Disagree (7) Huge flow and participation of FIIs in Indian market.

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree (8) Modernization of commercial and investment banking in India.

Strongly agree agree Neither agree nor disagree Disagree Strongly Disagree Q.11 kindly rate the importance of following variables to be considered important

factor affecting derivatives / investment into derivatives. (On five point scale below.)

5 Most important 4 Important 3 Neutral 2 Less important 1 Not al all important / Unimportant

(1) FII buying and selling activity

Most Important Important Neutral Less Important Unimportant

(2) Mutual Fund activity

Most Important Important Neutral Less Important Unimportant (3) Volatility in Global financial markets.

Most Important Important Neutral Less Important Unimportant (4) Corporate actions like dividend announcement.

Most Important Important Neutral Less Important Unimportant (5) Exchange rate volatility

Most Important Important Neutral Less Important Unimportant (6) Interest rate changes by RBI

256


(7) Inflation

Most Important Important Neutral Less Important Unimportant (8) Index of industrial production (IIP)

Most Important Important Neutral Less Important Unimportant (9) Money market Movements

Most Important Important Neutral Less Important Unimportant (10) Political scenario / developments

Most Important Important Neutral Less Important Unimportant (11) Budget announcement

Most Important Important Neutral Less Important Unimportant (12) Tax policy changes

Most Important Important Neutral Less Important Unimportant (13) Bullion and other commodity market movements

Most Important Important Neutral Less Important Unimportant (14) Monsoon

Most Important Important Neutral Less Important Unimportant (15) Financial result of company

Most Important Important Neutral Less Important Unimportant (16) Spot market volatility.

Most Important Important Neutral Less Important Unimportant (17) GDP


257

(18) Changes in Monetary policy by RBI,

Most Important Important Neutral Less Important Unimportant (19) Bonus announcement

Most Important Important Neutral Less Important Unimportant (20) Announcement regarding Merger and acquisition

Most Important Important Neutral Less Important Unimportant (21) Announcement regarding IPO.

Most Important Important Neutral Less Important Unimportant (22) Changes in Company’s business policy.

Most Important Important Neutral Less Important Unimportant (23) News regarding company entering into new business.

Most Important Important Neutral Less Important Unimportant.

258

Annexure - 2Anti-Image correlation for Question no. 8

Anti-imageCorrelation

Q.8S1 .792(a) -0.29 0.10 -0.39 -0.28 0.02 -0.09 0.08 -0.24 -0.21 0.12 -0.09 -0.13

Q.8S2 -0.29 .792(a) -0.26 -0.13 -0.03 0.11 -0.18 0.08 -0.16 -0.15 -0.12 0.24 -0.03

Q.8S3 0.10 -0.26 .574(a) -0.15 -0.11 -0.16 0.15 -0.09 0.05 0.04 0.09 0.07 -0.06

Q.8S4 -0.39 -0.13 -0.15 .759(a) 0.09 -0.27 -0.12 -0.04 0.12 0.28 -0.24 0.13 0.05

Q.8S5 -0.28 -0.03 -0.11 0.09 .829(a) 0.06 0.02 -0.08 -0.21 0.08 0.05 -0.14 0.11

Q.8S6 0.02 0.11 -0.16 -0.27 0.06 .575(a) -0.29 0.11 -0.19 0.08 0.08 0.13 -0.09

Q.8S8 -0.09 -0.18 0.15 -0.12 0.02 -0.29 .816(a) 0.05 -0.03 -0.16 -0.10 -0.30 0.14

Q.8S9 0.08 0.08 -0.09 -0.04 -0.08 0.11 0.05 .763(a) 0.04 -0.19 0.03 -0.17 0.09

Q.8S10 -0.24 -0.16 0.05 0.12 -0.21 -0.19 -0.03 0.04 .775(a) -0.03 -0.03 0.10 -0.15

Q.8S11 -0.21 -0.15 0.04 0.28 0.08 0.08 -0.16 -0.19 -0.03 .695(a) -0.06 0.05 0.16

Q.8S14 0.12 -0.12 0.09 -0.24 0.05 0.08 -0.10 0.03 -0.03 -0.06 .553(a) 0.02 -0.01

Q.8S16 -0.09 0.24 0.07 0.13 -0.14 0.13 -0.30 -0.17 0.10 0.05 0.02 .735(a) -0.35

Q.8S18 -0.13 -0.03 -0.06 0.05 0.11 -0.09 0.14 0.09 -0.15 0.16 -0.01 -0.35 .669(a)

Q.8S19 0.08 -0.12 0.28 -0.21 -0.10 0.20 -0.17 -0.10 0.24 0.04 0.15 0.33 -0.30

Q.8S21 -0.17 0.20 -0.23 0.16 0.01 0.01 0.01 0.11 0.16 0.16 -0.21 -0.06 -0.22

Q.8S22 -0.10 0.02 -0.06 -0.04 0.36 0.18 0.00 -0.17 -0.21 0.11 0.11 -0.06 0.06

Q.8S23 0.26 0.07 0.18 0.03 -0.32 -0.07 -0.09 0.03 -0.05 0.06 -0.01 0.33 -0.16

Q.8S24 0.40 -0.36 0.22 -0.24 -0.06 -0.07 0.23 0.01 -0.03 -0.19 -0.03 -0.22 -0.16

Q.8S25 0.10 -0.19 0.09 -0.17 -0.04 -0.15 0.28 -0.33 0.19 -0.04 -0.04 -0.02 0.01

Q.8S26 -0.20 -0.08 -0.07 0.17 0.05 -0.11 0.00 -0.19 0.24 0.16 -0.14 0.04 -0.18

Q.8S27 0.02 -0.10 0.14 -0.11 -0.26 -0.13 0.10 -0.08 0.30 -0.15 -0.01 -0.23 -0.28

Q.8S28 -0.08 -0.13 0.04 0.15 0.03 -0.04 -0.10 -0.24 -0.07 0.10 0.04 0.20 0.17

Q.8S29 -0.09 0.02 -0.12 0.03 -0.14 -0.13 0.12 0.07 -0.06 -0.03 -0.26 -0.03 0.21

Q.8S30 0.16 -0.03 0.10 0.06 -0.14 -0.25 0.21 0.03 -0.03 0.11 -0.14 -0.25 0.06

Q.8S31 -0.03 -0.02 -0.18 -0.13 0.03 0.22 0.10 0.13 -0.20 0.01 0.06 -0.26 0.16

Q.8S33 0.01 -0.05 0.07 0.05 0.38 0.02 0.02 0.06 -0.10 -0.06 0.12 0.27 -0.17

Q.8S35 0.10 -0.33 0.10 0.02 -0.12 -0.12 0.05 0.32 0.02 0.23 0.12 -0.35 0.25

Q.8S36 -0.26 0.25 -0.38 0.15 0.15 0.26 -0.06 0.24 0.04 0.06 -0.12 0.29 -0.17

Q.8S37 0.20 -0.04 -0.07 -0.06 0.04 -0.02 0.03 -0.03 -0.04 -0.36 -0.03 -0.13 -0.32

Q.8S38 -0.04 -0.07 0.00 0.00 0.18 -0.06 -0.05 0.13 -0.17 -0.03 -0.01 -0.19 0.07

259

Anti-Image correlation for Question no. 8

0.08 -0.17 -0.10 0.26 0.40 0.10 -0.20 0.02 -0.08 -0.09 0.16 -0.03 0.01 0.10 -0.26 0.20 -0.04

-0.12 0.20 0.02 0.07 -0.36 -0.19 -0.08 -0.10 -0.13 0.02 -0.03 -0.02 -0.05 -0.33 0.25 -0.04 -0.07

0.28 -0.23 -0.06 0.18 0.22 0.09 -0.07 0.14 0.04 -0.12 0.10 -0.18 0.07 0.10 -0.38 -0.07 0.00

-0.21 0.16 -0.04 0.03 -0.24 -0.17 0.17 -0.11 0.15 0.03 0.06 -0.13 0.05 0.02 0.15 -0.06 0.00

-0.10 0.01 0.36 -0.32 -0.06 -0.04 0.05 -0.26 0.03 -0.14 -0.14 0.03 0.38 -0.12 0.15 0.04 0.18

0.20 0.01 0.18 -0.07 -0.07 -0.15 -0.11 -0.13 -0.04 -0.13 -0.25 0.22 0.02 -0.12 0.26 -0.02 -0.06

-0.17 0.01 0.00 -0.09 0.23 0.28 0.00 0.10 -0.10 0.12 0.21 0.10 0.02 0.05 -0.06 0.03 -0.05

-0.10 0.11 -0.17 0.03 0.01 -0.33 -0.19 -0.08 -0.24 0.07 0.03 0.13 0.06 0.32 0.24 -0.03 0.13

0.24 0.16 -0.21 -0.05 -0.03 0.19 0.24 0.30 -0.07 -0.06 -0.03 -0.20 -0.10 0.02 0.04 -0.04 -0.17

0.04 0.16 0.11 0.06 -0.19 -0.04 0.16 -0.15 0.10 -0.03 0.11 0.01 -0.06 0.23 0.06 -0.36 -0.03

0.15 -0.21 0.11 -0.01 -0.03 -0.04 -0.14 -0.01 0.04 -0.26 -0.14 0.06 0.12 0.12 -0.12 -0.03 -0.01

0.33 -0.06 -0.06 0.33 -0.22 -0.02 0.04 -0.23 0.20 -0.03 -0.25 -0.26 0.27 -0.35 0.29 -0.13 -0.19

-0.30 -0.22 0.06 -0.16 -0.16 0.01 -0.18 -0.28 0.17 0.21 0.06 0.16 -0.17 0.25 -0.17 -0.32 0.07

.500(a) -0.26 -0.10 0.19 0.28 0.01 -0.01 0.09 -0.07 -0.01 -0.20 -0.21 0.07 -0.07 0.04 -0.09 -0.04

-0.26 .553(a) -0.08 -0.24 -0.23 -0.19 0.38 0.02 -0.28 -0.16 0.37 0.13 0.04 -0.15 0.23 -0.07 0.06

-0.10 -0.08 .625(a) -0.51 -0.08 -0.11 -0.04 -0.11 -0.03 -0.42 -0.05 0.33 0.34 -0.11 0.12 0.01 0.01

0.19 -0.24 -0.51 .595(a) 0.05 0.16 -0.48 -0.01 0.14 0.21 -0.14 -0.40 -0.16 0.14 -0.16 0.01 -0.20

0.28 -0.23 -0.08 0.05 .610(a) 0.11 -0.04 0.23 -0.05 0.12 -0.10 -0.01 0.15 -0.07 -0.28 0.16 -0.02

0.01 -0.19 -0.11 0.16 0.11 .746(a) -0.22 0.09 0.11 0.07 0.00 -0.11 -0.27 0.10 -0.17 0.04 -0.20

-0.01 0.38 -0.04 -0.48 -0.04 -0.22 .676(a) 0.05 -0.27 -0.04 0.20 0.03 0.06 -0.20 0.12 -0.15 0.25

0.09 0.02 -0.11 -0.01 0.23 0.09 0.05 .746(a) -0.37 0.11 0.00 -0.37 -0.02 0.06 -0.31 0.42 -0.11

-0.07 -0.28 -0.03 0.14 -0.05 0.11 -0.27 -0.37 .713(a) 0.02 -0.25 -0.06 -0.02 0.02 -0.10 -0.12 -0.15

-0.01 -0.16 -0.42 0.21 0.12 0.07 -0.04 0.11 0.02 .469(a) -0.11 -0.28 -0.28 0.06 -0.09 -0.04 0.18

-0.20 0.37 -0.05 -0.14 -0.10 0.00 0.20 0.00 -0.25 -0.11 .496(a) -0.01 -0.22 0.04 -0.13 -0.06 0.31

-0.21 0.13 0.33 -0.40 -0.01 -0.11 0.03 -0.37 -0.06 -0.28 -0.01 .772(a) 0.09 -0.12 0.30 -0.02 -0.01

0.07 0.04 0.34 -0.16 0.15 -0.27 0.06 -0.02 -0.02 -0.28 -0.22 0.09 .803(a) -0.08 0.22 0.11 -0.03

-0.07 -0.15 -0.11 0.14 -0.07 0.10 -0.20 0.06 0.02 0.06 0.04 -0.12 -0.08 .808(a) -0.20 -0.23 -0.01

0.04 0.23 0.12 -0.16 -0.28 -0.17 0.12 -0.31 -0.10 -0.09 -0.13 0.30 0.22 -0.20 .486(a) -0.25 -0.08

-0.09 -0.07 0.01 0.01 0.16 0.04 -0.15 0.42 -0.12 -0.04 -0.06 -0.02 0.11 -0.23 -0.25 .612(a) -0.01

-0.04 0.06 0.01 -0.20 -0.02 -0.20 0.25 -0.11 -0.15 0.18 0.31 -0.01 -0.03 -0.01 -0.08 -0.01 .783(a)

260

Annexure - 3Anti-Image correlation for Question no. 11

Anti-image Correlation Q.11F1 0.64 -0.45 -0.03 0.09 0.02 -0.33 0.02 0.01 0.03 0.13 -0.25

Q.11F2 -0.45 0.81 -0.14 -0.14 0.02 0.09 -0.14 0.06 -0.06 -0.07 0.04

Q.11F3 -0.03 -0.14 0.80 -0.01 -0.13 -0.05 0.15 -0.45 0.17 -0.22 0.08

Q.11F4 0.09 -0.14 -0.01 0.52 -0.02 0.01 -0.19 0.09 0.09 -0.01 -0.08

Q.11F5 0.02 0.02 -0.13 -0.02 0.85 -0.07 -0.41 0.04 -0.02 -0.08 0.13

Q.11F6 -0.33 0.09 -0.05 0.01 -0.07 0.75 -0.37 0.05 -0.09 -0.44 0.13

Q.11F7 0.02 -0.14 0.15 -0.19 -0.41 -0.37 0.83 -0.35 0.02 0.12 0.04

Q.11F8 0.01 0.06 -0.45 0.09 0.04 0.05 -0.35 0.87 -0.35 0.25 0.03

Q.11F9 0.03 -0.06 0.17 0.09 -0.02 -0.09 0.02 -0.35 0.90 -0.12 0.15

Q.11F10 0.13 -0.07 -0.22 -0.01 -0.08 -0.44 0.12 0.25 -0.12 0.67 -0.38

Q.11F11 -0.25 0.04 0.08 -0.08 0.13 0.13 0.04 0.03 0.15 -0.38 0.66

Q.11F12 -0.15 0.10 0.01 0.13 -0.55 0.09 0.09 -0.02 -0.25 0.04 -0.28

Q.11F13 0.14 -0.29 -0.14 0.26 -0.13 0.21 -0.15 0.05 -0.19 0.09 -0.29

Q.11F14 0.10 -0.08 -0.14 -0.22 0.32 -0.14 -0.01 0.02 -0.11 -0.07 0.24

Q.11F15 0.04 0.24 0.15 -0.43 0.03 -0.35 0.27 0.00 -0.15 0.11 0.08

Q.11F16 -0.07 0.17 -0.01 0.10 -0.02 0.05 -0.30 0.18 0.12 -0.21 -0.20

Q.11F17 0.14 0.14 -0.15 -0.07 0.18 -0.01 -0.08 -0.29 -0.10 0.01 0.05

Q.11F18 0.08 -0.14 0.36 -0.12 -0.22 -0.35 0.30 -0.15 0.07 0.10 -0.17

Q.11F19 -0.30 0.01 -0.24 0.10 -0.04 0.39 -0.18 0.08 -0.06 -0.09 -0.01

Q.11F20 -0.19 0.22 0.11 -0.19 0.11 -0.09 0.11 -0.06 0.17 -0.11 -0.04

Q.11F21 0.09 -0.11 0.17 0.12 -0.12 0.13 -0.01 0.00 0.14 -0.21 0.01

Q.11F22 -0.04 0.00 -0.14 -0.01 0.26 0.12 -0.24 0.18 -0.35 -0.09 0.22

Q.11F23 0.25 -0.16 0.03 -0.07 -0.05 -0.25 0.06 -0.11 0.09 0.31 -0.11

261

Anti-Image correlation for Question no. 11

-0.15 0.14 0.10 0.04 -0.07 0.14 0.08 -0.30 -0.19 0.09 -0.04 0.25

0.10 -0.29 -0.08 0.24 0.17 0.14 -0.14 0.01 0.22 -0.11 0.00 -0.16

0.01 -0.14 -0.14 0.15 -0.01 -0.15 0.36 -0.24 0.11 0.17 -0.14 0.03

0.13 0.26 -0.22 -0.43 0.10 -0.07 -0.12 0.10 -0.19 0.12 -0.01 -0.07

-0.55 -0.13 0.32 0.03 -0.02 0.18 -0.22 -0.04 0.11 -0.12 0.26 -0.05

0.09 0.21 -0.14 -0.35 0.05 -0.01 -0.35 0.39 -0.09 0.13 0.12 -0.25

0.09 -0.15 -0.01 0.27 -0.30 -0.08 0.30 -0.18 0.11 -0.01 -0.24 0.06

-0.02 0.05 0.02 0.00 0.18 -0.29 -0.15 0.08 -0.06 0.00 0.18 -0.11

-0.25 -0.19 -0.11 -0.15 0.12 -0.10 0.07 -0.06 0.17 0.14 -0.35 0.09

0.04 0.09 -0.07 0.11 -0.21 0.01 0.10 -0.09 -0.11 -0.21 -0.09 0.31

-0.28 -0.29 0.24 0.08 -0.20 0.05 -0.17 -0.01 -0.04 0.01 0.22 -0.11

0.85 0.15 -0.51 -0.02 0.21 0.01 -0.10 0.05 -0.12 0.03 -0.16 0.02

0.15 0.84 -0.39 -0.24 -0.05 -0.01 -0.20 0.23 -0.23 -0.11 0.11 0.10

-0.51 -0.39 0.85 0.06 -0.22 -0.03 -0.01 -0.09 0.08 -0.02 0.23 -0.24

-0.02 -0.24 0.06 0.45 -0.05 0.11 0.13 -0.30 0.10 -0.07 0.04 -0.03

0.21 -0.05 -0.22 -0.05 0.65 -0.17 0.01 -0.02 0.08 0.04 -0.04 -0.04

0.01 -0.01 -0.03 0.11 -0.17 0.87 -0.56 -0.14 -0.08 -0.15 0.05 0.27

-0.10 -0.20 -0.01 0.13 0.01 -0.56 0.84 -0.13 -0.05 0.13 -0.16 0.03

0.05 0.23 -0.09 -0.30 -0.02 -0.14 -0.13 0.73 0.00 -0.39 0.09 -0.25

-0.12 -0.23 0.08 0.10 0.08 -0.08 -0.05 0.00 0.80 -0.38 -0.21 -0.23

0.03 -0.11 -0.02 -0.07 0.04 -0.15 0.13 -0.39 -0.38 0.77 -0.20 -0.05

-0.16 0.11 0.23 0.04 -0.04 0.05 -0.16 0.09 -0.21 -0.20 0.69 -0.30

0.02 0.10 -0.24 -0.03 -0.04 0.27 0.03 -0.25 -0.23 -0.05 -0.30 0.65

mayur ph.d thesis.pdf

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