CHAPTER - 3 CONCEPTUAL FRAMEWORKshodhganga.inflibnet.ac.in/bitstream/10603/93012/12/12...43 CHAPTER...
Transcript of CHAPTER - 3 CONCEPTUAL FRAMEWORKshodhganga.inflibnet.ac.in/bitstream/10603/93012/12/12...43 CHAPTER...
43
CHAPTER - 3
CONCEPTUAL FRAMEWORK
The previous chapter dealt with review of literature on various research concepts of
the study. The literature is classified in to six groups and reviewed accordingly. The
literature is grouped as (i) lead- lag relationship between the futures and spot prices
(ii) Empirical testing of futures pricing models (iii) Comparison of pricing
performance of different futures pricing models (iv) The mispricing and arbitrage of
stock index futures market (v) The relationship between futures price & market
volatility and trading volume (vi) Finally, the last group contains several
miscellaneous studies that do not fit into the above groups. The review helped to
understand the concepts of futures pricing, various futures pricing models,
applications of futures pricing models and various factors which influence futures
pricing performance. Further, review of available literature helped to understand
research methodologies, analytical tools, sources of data used by the authors in
different markets across the globe. Finally, the research gaps have been identified
based on the review of literature.
This chapter deals with conceptual framework of the study. The objective of this
chapter is to understand the various theoretical concepts of the study. The theoretical
concepts of the study is classified as follows
3.1 Indian Securities Market
3.1.1 Introduction
3.1.2 National Stock Exchange (NSE)
3.1.3 History of Derivatives in India
3.1.4 Introduction to Derivatives
3.1.4.1 Introduction to Futures Contracts, Terminologies and Mechanism
3.2 Business Growth of Global Derivatives Market
3.3 Business Growth of Indian Futures Market
3.4 Futures Pricing Models
3.5 Operational definitions
44
3.1 Indian Securities Market
3.1.1 Introduction
Securities market facilitates people to invest their savings based on their risk bearing
capabilities and return expectations, by these way financial securities market
contributes growth, development and there by strengthen the emerging market
economy. People’s savings can be converted in to investments by a number of
intermediaries through complex financial products called “securities”. As per
Securities Contracts Regulation Act (1956) “securities” include (i) shares, scrips,
stocks, debentures, bonds or any other marketable securities of similar in nature (ii)
derivative securities (iii) any instrument issued to the investor under any collective
investment schemes and mutual fund schemes (iv) Government securities (v) other
instruments declared by the central government to be security (vi) rights or interest in
securities. In general, securities are broadly classified in to three categories (1)
Equities (2) Derivatives (3) Debt securities.
Securities market is a place where purchasing and selling of securities take place.
Further, it provides an opportunity to all the corporate and entrepreneurs to raise
money for their business organizations through public issues. Transfer of people’s
savings money to corporate people in a most regulated and efficient manner through
various intermediaries and the financial securities market.
Market Segments `
Securities market can be divided in to two independent segments namely (1) Primary
Market (2) Secondary Market. Primary market is the market where issue of new
securities takes place. Primary market provides opportunity to government and
corporate to raise resources through issue of securities. In the primary market new
securities can be created either through public issue or private placement. As per the
companies act 1956 section 67(3) if an issuer, issue the securities to fifty or more
persons/ investors then is referred as public issue. However , issue of securities to a
selected group of investors not more than forty nine then is referred as private
placement ( provided that issue is neither a right issue nor a public issue). In general,
corporate and governments issue equity and debt securities.
45
Secondary market is the market where buying and selling of securities takes place in
the listed stock exchange after securities being offered to the public in the primary
market. Secondary market is operated through mediums namely exchange traded
markets and Over- the- Counter markets (OTC). Currently there are 25 stock
exchanges operating in India including two major stock exchanges the Bombay Stock
Exchange (BSE) & National Stock Exchange (NSE). Stock exchanges provide a
systematic, fair, transparent and efficient security market to investors by using
electronic trading systems and technology. Stock exchanges and all the financial
intermediaries in India are constantly regulated by SEBI to protect the interest of
investors in securities market. OTC markets are informal, less transparent, less liquid,
dealers dependent market with customised procedures and trades are negotiable
through various communication modes such as telephone, email.
Security market participants
The securities market participants are generally classified in to three categories (i) The
issuer of securities (ii) The investors in securities (iii) The intermediaries
The issuers of securities are generally corporates, entrepreneurs and governments,
who are in need of resources to develop their business. The investors in securities are
generally Foreign Institutional Investors (FII), corporate investors, venture capital
investors and individual investors, who have surplus money or savings. Intermediaries
are act as middleman between issuers and investors such as stock exchanges, brokers,
portfolio manager, custodians, primary dealers, merchant bankers, underwriters etc.
All the participants of securities market are regulated by the Security and Exchange
Board of India (SEBI), Ministry of Corporate Affairs (MCA), Reserve Bank of India
(RBI) and the department of Economic Affairs of Ministry of Finance.
3.1.2 National Stock Exchange
National Stock Exchange (NSE) India, is country’s leading stock exchange was
incorporated in the year November 1992 and recognized as a stock exchange in April
1993. Just two and half years after it got recognized as stock exchange, it became
largest stock exchange in the country in terms of market capitalization. Today NSE
operates across the nation, connects more than 1500 locations and supports 230, 000
terminals in the country. NSE offering trading in capital markets, derivatives market
and debt markets. Currently there are more than 1600 companies listed in the National
46
Stock Exchange which includes almost all the major segments of the industry. NSE
was the first to introduce an automated Screen Based Trading System (SBTS) on the
capital market segment on November 3 1994 to provide transparency, efficiency,
liquidity, speed, market integrity and safety. Before NSE introduced SBTS, stocks
exchanges in India were trading based on an open autocracy system which was time
consuming and inefficient in trading operation.
NSE is providing a platform to trade all types of securities. After recognition as stock
exchange in April 1993. It commenced trading in the WDM (Wholesale Debt Market)
in June 1994, Capital Market in November, 1994, F&O (June, 2000) and Retail Debt
of Government Securities (January, 2003).
Technology and application system of NSE
NSE, India introduced National Exchange for Automated Trading (NEAT) system
which provides a fully automated screen based trading system for easy and efficient
trading. NSE was the first stock exchange in the world to trade using satellite
communication technology to connect more than 1500 locations and supports 230,000
terminals across the country. Using NEAT, investors can be traded from their places
located any part of the country. NSE’s F &O segment trading terminals are present in
different locations across the country.
NEAT is a highly technological server based application. In this server, all the trading
related information is stored and provides very quick responses with minimum time to
all the market participants. Any trade orders enters in to NSE’s NEAT system, it takes
less than 1.5 seconds to response that trade order. NSE is a technology driven
exchange. It has been implementing various technological applications systems to
provide efficient, speedy, transparency, liquidity, well clearing and settlement system
and safety to all the market participants.
The application system of NSE can be divided into (i) Front end (ii) Back office
applications. In the front end, there are 6 different applications (NEAT- WDM,
NEAT- F&O, NEAT- IPO, NEAT- MF and surveillance systems). Similarly in back
offices there are 8 application systems (NCSS- Nationwide Clearing & Settlement
System, FOCASS, PRISM- Parallel Risk Management System, - Clearing and
settlement for F&O, OPMS- Online Position Monitoring System, Data warehousing,
Listing System, and Membership System.
47
3.1.3 History of Derivatives in India
Derivatives in India can be traced back at nineteenth century (1875) the cotton trade
association was initiated the derivative futures trading. The NSE, the largest exchange
in India commenced futures trading on CNX Nifty Index in June 2000. National Stock
Exchange (NSE) was incorporated in the year November 1992 and recognized as a
stock exchange in April 1993. NSE was the first to introduce an Automated Screen
Based Trading System (SBTS) on the capital market segment on November 3 1994 to
provide transparency, efficiency & Liquidity of the stock market. As per the
recommendations by the L.C Guptha committee and J R Verma committee formed by
SEBI on exchange traded derivatives, in 1999. The Securities Contract (Regulation)
act 1956 was amended and declared derivatives as securities.
The Tables 3.1 & 3.2 present the history and milestones of derivatives in NSE. In a
span of one year after introduction of CNX Nifty index futures, NSE, India introduced
index options, individual stock options and individual stock futures. Later, NSE also
introduced currency derivatives, interest rate derivatives, 91 day Government of India
(GOI) treasury bill- futures. First time in India NSE introduced derivatives on global
indices – S & P 500, FTSE 100 and DIJA. Table 3.1 clearly shows the chronology of
derivatives in NSE in terms of introduction and developments. Table 3.2 presents all
the products traded in futures and options segments of NSE with introduction dates.
Currently there are 9 indices including 3 global indices (CNX Nifty, Bank Nifty,
CNX Infra, CNX IT, NFTY Mid Cap 500, DJIA, S& P 500 and FTSE 100) and 145
individual stocks are available for trading in futures derivatives in NSE. Similarly,
there are 5 indices including 2 global index (CNX Nifty, Bank Nifty, CNX IT, FTSE
100 and S& P 500 index) and 145 individual stocks are available for trading in
options derivatives in NSE. (As of February 2015).
48
Table: 3.1 Historical developments of derivatives in NSE, India - A Chronology
Sl
No Progress Developments of Financial derivatives
1 November 18,
1996
SEBI set up L.C. Gupta Committee to draft a policy
framework for introducing derivatives
2 May 11, 1998
L.C. Gupta committee submits its report on the policy framework for introducing derivatives
3 May 25, 2000 SEBI allows stock exchanges to trade in index futures
4 June 12, 2000 Trading of CNX Nifty index futures commences on the NSE
5 June 4, 2001 Trading of CNX Nifty options commences at NSE
6 July 2, 2001 Trading of Stock options commences at NSE
7 November 9,
2001
Trading of Stock futures commences at NSE
8 August 29, 2008 Trading of Currency derivatives commences at NSE
9 August 31, 2009 Trading of Interest rate derivatives commences at NSE
10 February 2010
Trading of Currency futures on additional currency pairs
commences at NSE
11 October 28, 2010
Trading of European style stock options commences at NSE
12 October 29,
2010
Trading of currency options commences at NSE
13 July 2011 Trading of 91 day GOI Treasury Bill – Futures commences at
NSE
14 August 2011 Trading of derivatives on global indices commences at NSE
15 January 21, 2014 NSE Introduces ‘NSE Bond Futures II’
16 February 26,
2014
Trading of futures on India VIX index (NVIX Futures)
commences at NSE
17 March 24, 2014 Trading of CNX Nifty futures commences at Osaka Securities
Exchange , Japan
(Source: Retrieved & Adapted from www.nseindia.com)
49
Table: 3.2 Products Traded in Futures & Options Segment of NSE
Sl
No Progress Products of Financial derivatives in NSE
1 June 2000 Trading of CNX NIFTY Futures (Index Futures) commences
2 June 2001 Trading of CNX NIFTY Options ( Index Options) commences
3 July 2001 Trading of Options on individual securities commences
4 November 2001 Trading in Futures on individual securities commences
5 August 2003 Trading of Futures & Options in CNXIT Index commences
6 June 2005 Trading of Futures & Options in BANK Nifty Index commences
7 June 2007 Trading of derivatives on Nifty Junior & CNX 100 commences
8 October 2007 Trading of derivatives on Nifty Midcap 50 commences
9 January 2008 Launch of Mini Nifty derivative contracts
10 March 2008 Launch of long term option contracts on CNX Nifty Index
11 August 2008 Introduction of Currency Derivatives
12 August 2009 Introduction of Interest rate futures
13 July 2010 Trading of CNX Nifty Futures on CME commences
14 July 2011 Trading in 91 Day GOI Treasury Bill – Futures commences
15 August, 2011 Introduction of derivatives on S&P 500 and DIJA Index (Global
Indices )
16 September 2011 Trading of derivatives on CNX PSE and CNX Infrastructure Indices
17 May 2012 Introduction of Futures and Options contracts on FTSE 100
18 February 2014 Introduction of NVIX Futures – Futures on India VIX index
(Source: Retrieved & Adapted from www.nseindia.com)
3.1.4 Introduction to Derivatives
According to securities contracts (regulation) act, 1956 ‘Derivative ‘includes (a). A
security is derived from a share, loan debt instrument whether secured or unsecured,
risk instrument or contract for differences or any other form of security (b) a contract
which derives its value from the prices or index of prices of underlying securities.
Basically derivative is a contract its value derived from the value of an underlying
asset. Underlying asset could be commodities such as gold, metal, energy and
financial asset such as equity shares, debt instruments like bonds, T- bills, commercial
paper, currencies and indices of these respective assets such as CNX Nifty, Bank
Nifty, and CNXIT Index. If the underlying asset is a financial asset it is called
financial derivative and if the underlying asset is commodity, it is called commodities
derivative. If the underlying asset is currency then it is known as currency derivatives.
50
Participants
As Indian capital market developed and outstandingly successful, different types of
investors/traders attracting and participating in derivatives market. These investors
use the derivatives market to minimize the risk, to earn profit and as a part of the
investment strategy. Three broad categories of participants can be found in financial
derivatives market: a) Hedgers b) Speculators c) Arbitragers
a) Hedgers: Hedging is the process of minimizing the risk involved in the
underlying market by entering opposite position in the derivatives market due
to unfavorable change in the underlying asset price. Hedgers try to
avoid/minimize the risk of unfavorable change in the underlying asset price by
locking the price through holding a position in the derivatives market.
Hedger’s position in the derivatives market decided based on the type of
exposures, they have taken in the spot market. Indian laws emphasize
derivatives should be used for hedging purpose only ( Dr.kamalesh & Neetu (
2013) )
there are two types of hedging generally investors carried out in the futures
market: i.) Short Hedge ii.) Long Hedge
i.) Short Hedge: It involves an investor enters short position in the futures
market with anticipation of decrease in the price of underlying asset which he
is already own. For example : An investor bought SBI share in the cash
market, worries that price may come down in the future and he can hedge this
price risk by entering opposite position (short) in the futures market at NSE.
This process protect the investor from incurring losses on the underlying
market. Suppose the price of SBI falls, the investor incurs loss in the cash
market, but he can compensate this loss by earning profit in the SBI futures.
In this way an investor can manage his price risk by participating in the
derivatives market (Futures).
ii.) Long Hedge: It involves an investor enters a long position in the futures
market. It involves an investor who is planning to buy underlying asset in the
near future, enters a long position in the futures market. By this process an
investor can lock the prevailing price in the market. Because he thinks that
prevailing price is very low.
51
b. Speculators: A speculator is the one who anticipate the future price of the
index/stock. They wish to take positions in the market by betting that price of the
index/ stock will go up or go down. Generally, speculators, view on the movement of
asset price. They take calculated risk and expect quick large profits from the trade.
For example: currently SBI share trading at Rs 302 in the futures market. A speculator
expects that post union budget announcement is positive towards banking sector and
SBI share will go up. Thus, the speculator can have positions of one lot of SBI shares.
In case the post union budget announcements price of SBI increases ( more than
302), then he can make profit, suppose the post union budget announcement price of
SBI share comes down then he incurs loss.
c. Arbitragers: These are the one who have potential to earn riskless profit by
simultaneously buying in one market and selling in another market. Arbitrageurs are
basically risk averse in nature and they can earn risk less profit by taking advantage of
price discrepancy between two markets. For example: Currently (06/02/2015) Unitech
Ltd, is trading at Rs 17 per share in the cash market and Unitech futures contract
trading at Rs 17.5 in the futures market. The arbitragers can earn riskless profit by
buying the Unitech share in the cash market at Rs 17 and sell (short) the same
quantity of Unitech futures contracts at Rs 17.5. Assume that on expiry day
(26/02/2015) the price of Unitech in the spot market and the price of the futures
contract converges and closes at Rs 17.2. Then the arbitrager earn profit of Rs 0.2
(17.2- 17) from the spot market and the profit of Rs 0.3 (17.5-17.2) from the futures
market respectively. Thus, finally arbitragers earn net profit of Rs 0.5 (0.2+ 0.3) from
the arbitrage process. (Assume that there is no trading cost)
Applications of Derivatives
Risk Management
Derivatives are financial instruments that are used as risk management tools. They
help to transfer risk from the risk averse to the risk taker. Futures are used as risk
management tool through hedging technique. In this technique, hedgers try to avoid
price risk through holding a position in the futures market. Further, the investor can
use derivatives to assess the level of risk he is willing to bear and accordingly he can
take the risk.
52
Risk can be defined as “The possibility or probability of loss”. In simple terms, may
be defined as the uncertainty of returns.
Market Efficiency
Efficient Market Hypothesis (EMH) states that capital markets are “Informational
efficient” that is, at the time of investment; if new information is publically available
without any bias then the investor is not possible to earn more than average market
return consistently. Further it explains an “efficient market” is the one in which the
prices of the stock always “fully reflect” all the available information.
Further, Fama (1965, 1970) explains a market conditions which support the efficiency
of the market. The efficient market is the one in which (1) the current price of a
security “fully reflects” all the publically available information (2) There are no
transaction costs (3) Market participants easily access all the available information
with low cost . Further, he says that in efficient markets investors not possible to
predict current stock prices solely by following historical price patterns and can’t earn
abnormal profits and stock prices are random walk in nature i.e. the stock prices in the
capital market will not follow any particular pattern rather a unpredictable pattern.
The current price is not depend on the past historical share prices, it purely exhibits
randomness behaviour; the past rates of return of stock market are independent. If
stock price reflects all the available information, then the investor can’t benefit over
selling or buying of stock, using that information.
Generally, derivatives help to improve the efficiency of the capital market through
self-correcting mechanism. Arbitragers are one of the market participants who have
potential to earn riskless profit. They enter the market whenever price discrepancy
exist in the market and earn risk free profit by simultaneously buying in one market at
low price and selling in another market at high price. Arbitrager’s actions will
continue till this price deviation will be adjusted back to equilibrium simultaneously
and risk less profitable arbitrage opportunity will be eliminated.
Price Discovery
Price discovery is one of the important application of financial derivatives. Price of
the futures contract reveals the future cash market prices. Market participants can
expect future underlying market prices by analysing the price of the futures contract
(one month, two month and three month futures contract). According to CCM theory,
the futures prices will more than spot prices by the cost of carry. The cost of carry
53
equals to the interest to be paid (cost) to hold the underlying asset less the cash
dividend received (benefit). Based on CCM and prices of the futures contracts
investors predict market prices and strategically invest on cash and futures market.
Liquidity and transaction cost: Futures contracts are highly liquid. To facilitate
liquidity NSE specified some standards in derivatives contracts in terms of quantity,
price, delivery and settlement. Open interest figure of derivatives contracts is a good
indicator of the liquidity. The number of outstanding contracts is known as “open
interest” and generally maximum trading volume and open interest found in near
month contracts. T Daigler (1990) found that significantly lower transaction cost of
futures over cash and the greater liquidity in the futures market. Further, only margin
money required to trade futures contracts rather than full transaction value. This
margin money is very less, generally 20 to 30% of the total transaction value, but
investor’s entitle to get profit or incur loss based on total transaction value.
For example, Unitech stock futures price /share = Rs 17.7 and lot size = 9000 then the
contract value = 17.7×9000 = Rs159300. Say margin money = 28% of the total
contract value. If a person wants to buy one lot of Unitech stock futures then he has to
deposit margin money of Rs 44604 (Initial Margin amount = 159300 × 0.28 = Rs
44604). In case the Unitech share price increases to Rs 20.5 then investor earns profit
of = Rs 0.8 /share (20.5-17.7= Rs 0.8). Totally Rs 7200 (0.8×9000= Rs7200). Thus,
actually the investor earned a profit of Rs 7200 by investing only margin money of Rs
44604.
Types of Derivatives
1. Forward Contract.
Forward contract is relatively simple contract. It is an agreement between two
parties to buy or sell an asset at a certain future time for a price agreed on today.
In forward contract, one party assumes long position and agrees to buy the
underlying asset at a certain future time for a certain price agreed on today. The
other party of the forward contract assumes short position and agrees sell the
underlying asset on the specified date for same price.
In forward contract, both the parties have an obligation to buy or sell an asset (
underlying asset), both the parties agrees to buy or sell an underlying asset at a
54
certain future time (known as expiration date) for a specified price agreed on
today ( known as Forward price)
The basic Feature of Forward contract
1. Since Forward contracts do not trade in regulated exchanges, they generally
exposed to counter party risk. The risk arises when one of the parties of the
forward contract not fulfil the obligations.
2. Forward contract is, Unique, customized and flexible in terms of contract size,
price, expiration date and settlement.
3. A forward contract is generally traded in the over- the- counter- market between
two individual or two financial institutions & one of its clients
4. Forward contracts on foreign exchange and interest rate are highly popular
5. Forward contracts are not standardized and illiquid compare to futures contracts.
2. Options
Options derivatives provide a right to an investor who buys an options but not an
obligation to either buy or sell a specific asset on a certain price on or before certain
date. An investor who buys an options is known as option buyer or option holder.
Conversely, an investor who sells an options is known as seller or option writer. There
are two types of options: 1. Call options 2. Put options
1. Call options : In this contract, the person who buys an options has a right but
not an obligation to buy a underlying asset on a certain price on or before
certain date
2. Put options: In this contract the person who buys an options has a right but not
an obligation to sell an underlying asset on a certain price on or before certain
date.
An investor who buys an options is said to be having long position and an investor
who sells an options is said to be having short position.
In both forward & futures contracts both buyer and seller have an obligation but in
case of options derivatives only option seller (option writer) has an obligation and not
the option buyer or purchaser. Here option buyer or purchaser has only an option or
right to buy or sell the underlying asset but he need not to exercise his right. More
importantly if option buyer does exercise his right then option sellers must fulfil his
obligations both in the case of call and put options contracts. Generally options can be
55
classified in to two types based on the timing of options exercise: 1. European options
contracts 2. American options contracts.
1. European options contracts: An options exercised exactly on the expiry of the
contract
2. American options contracts: An options exercised anytime on or before the
expiry date.
3.1.4.1 Introduction to Futures Contracts , terminologies and Mechanism
Futures is an exchange traded and standardized contract between two parties to buy
(long) or sell (short) an underlying asset for a certain price at a specified future date.
Futures investors can square off the transactions in any time prior to the maturity by
closing out the futures contract. There is no counter party risk for the buyers and
sellers of futures contracts because futures derivative contracts are traded through
organised exchanges, and the clearing corporation of the exchange take care the final
settlement of the contract. Futures contract is standardized in terms of underlying
quantity, price, and delivery date & month and settlement procedure.
The basic Feature of Futures contract
1. Futures investors can square off the transactions in any time prior to the maturity
by closing out the futures contract.
2. There is no counter party risk for the buyers and sellers of futures contracts
because futures derivative contracts are traded through organized exchanges, the
clearing corporation of the exchange take care the final settlement of the
contract.
3. Futures contract is standardized in terms of underlying quantity, price, delivery
date & month, settlement procedure.
4. Investors required only a margin money (The minimum percentage of total
contract value) to trade in futures market.
5. Futures markets are regulated by Security Exchange Board of India (SEBI)
56
Essential Futures terminologies
Expiry date: The date on which the final settlement of the contract takes place. NSE
futures contracts mature on the last Thursday of every month. If the last Thursday of
every month is happened to be a trading holiday, the contracts expire on immediate
previous trading day.
Contract cycle: NSE futures contracts have a maximum of 3- month trading cycle -
one month (near), the two month (next) and the three month (far). A new futures
contract is introduced on the immediate next trading day of the expiry of the first
month (near month) contract. The new contract will be introduced for three month
duration. This way, at any point in time, there will be 3 contracts available for trading
in the market i.e., one near month, one second month and one far month duration
respectively.
Contract size (Lot size): The fixed quantity of asset that has to be bought and sold
under one contract.
Contract Value - It is a transaction value of one contract is bought or sold. This can
be determined by multiplying contract size (quantities) with price of the futures. For
example, Unitech stock futures price /share = Rs 17.7 and Lot size = 9000 then the
contract value = 17.7×9000 = Rs159300. Further, Tables 3.3 & 3.4 present illustrative
example of contract value calculation for individual stock futures and stock index
futures respectively. (As on 11/01/2013)
Table: 3.3 Illustrative example of contract value calculation for individual stock
futures
Sl
No Stocks
Underlying
Price
Lot
Size
Stock Futures
Price
Total Contract
Value
A B (A × B)
1 Axis Bank Limited 1,407 250 1,409 352125
2 BHEL 231 1000 230 230150
3 Infosys Limited 2,789 125 2,799 349875
4 Maruti Suzuki India Ltd.
1,575 250 1,573 39317
5 Asian Paints Limited 4,438 125 4,449 556125
6 Colgate Palmolive Ltd.
1,435 250 1,443 360725
(Source: Retrieved & Adapted from www.nseindia.com)
57
Table: 3.4 Illustrative example of contract value calculation for stock index
futures
Sl
No Stock Index
Underlying
Value
Lot Size Index Futures Total Contract
Value
A B (A × B)
1 Nifty Midcap 50 2,395 150 2,451 3,67,665
2 CNX
Infrastructure 2,544 1,000 2,560 25,59,800
3 CNX IT 6,640 125 6,651 8,31,363
4 CNX Bank index 12,618 250 12,683 31,70,675
5 S&P CNX Nifty 5,951 125 5,977 7,47,163
(Source: Retrieved & Adapted from www.nseindia.com)
Initial margin: The minimum percentage of total contract value, futures buyer or
seller must be deposited in the margin account at the time a futures contract is first
entered. For earlier Unitech stock example, say margin money = 28% of the total
contract value. If a person wants to buy one lot of Unitech stock futures then he has to
deposit margin money of Rs 44604 (Initial Margin amount = 159300 × 0.28 = Rs
44604)
Maintenance Margin – The clearing corporation of the exchange covers the counter
party risk through mark to market settlement process. It is the process of adjusting the
margin balance based on the daily gains or losses of the futures buyers or sellers in the
futures account. If the investor gains on a particular day then that gain to be added to
previous day’s margin balance. If he loses, then that day loss amount to be deducted
from previous day’s margin balance. This type of daily settlement is known as
marking to market settlement. The minimum level of margin money, the futures
buyers and sellers must maintain throughout the holding period of the contract is
known as maintenance margin. In case the futures investor daily losses are more than
gains and margin falls to maintenance margin or below, then future investor must
transfer the additional fund to top up the margin account to the initial margin level
before commencement of next day trading.
Basis:
The difference between futures price and spot price is known as basis. Normally basis
will be positive (Futures price > Spot Price). The variation of basis differs from month
to month but near to expiry date the futures price starts converge to spot price. On the
date of expiration the basis will be zero. Fig 3.1 clearly shows the variation of basis
over January, 2013 month. It’s clearly indicating that in the beginning of the month
58
the variation of basis is larger and time passes towards the expiry the futures price
gradually started to converge to spot price. On the date of expiration the basis was
almost zero.
Figure: 3.1 Variation of Basis over a month of January, 2013
(Source: Retrieved & Adapted from www.nseindia.com)
Futures contracts are available for trading on various financial products. The
important types of futures as follows
1. Individual stock futures
2. Stock Index futures
3. Currency futures
4. Interest Rate futures
Stock Index Futures
If futures contracts traded on stock index then it is known as index futures. Here, the
underlying asset is the index itself. For example, the underlying asset for CNX Nifty
index futures traded on NSE is spot CNX Nifty Index. Currently nine major indices
are available for trading in futures and options in NSE. They are CNX NIFTY,
CNXIT, and BANKNIFTY, CNXMIDCAP50, CNX INFRA, CNXPSE, S&P 500,
DIJA and FTSE100.
Individual Stock Futures
If futures contracts traded on individual stocks then it is known as stock futures. Here,
the underlying asset is the individual company stocks which are traded in spot market.
Currently 145 individual securities are available for trading in futures and options in
NSE.
5930
5980
6030
6080
6130
1-J
an-1
3
3-J
an-1
3
5-J
an-1
3
7-J
an-1
3
9-J
an-1
3
11
-Jan
-13
13
-Jan
-13
15
-Jan
-13
17
-Jan
-13
19
-Jan
-13
21
-Jan
-13
23
-Jan
-13
25
-Jan
-13
27
-Jan
-13
29
-Jan
-13
31
-Jan
-13
Ind
ex
valu
e
Days
Basis
Futures Price Spot Price
59
Currency Futures
Currency futures is basically a futures contract to buy (long) or sell (short) or
exchange one currency against other currency for a certain price at a specified future
date. NSE was the first stock exchange got approval from SEBI for trading currency
derivatives in its exchange. NSE launched currency futures on 29th August 2008. First
Indian Rupees against US Dollars (USD/INR) were introduced for trading at NSE,
subsequently INR against other foreign currencies were introduced – Euro (EUR),
Great Britain Pound (GBP) and Japanese Yen (JPY). In NSE’s currency futures,
currently INR was allowed to trade against four foreign currencies only.
Interest Futures
Interest rate futures is basically futures contract or an agreement to buy (long) or sell
(short) a debt asset for a certain price at a specified future date. Here, the underlying
asset for interest rate futures contract is the debt instrument of either 91 day
Government of India Treasury Bill or 10 – Year government of India security (NSE
Bond Futures II). NSE introduced interest rate futures on August 31, 2009. In today’s
market environment interest rate is the one of the important macro-economic indicator
that influence various economical activities of the country. To meet this increasing
demand of debt instruments, Government of India issuing more and more long term
debt instruments and the strong need of the same required for hedging.
Table: 3.5 Specifications of the stock index and Individual stock futures of NSE
Particulars Index Futures Individual Stock
Futures
Opening Date June 12, 2000 November 2001
Products 9 Indices 141 Securities
Contract months
The near month (one), the next month
(two) and the far month (three). at any point in time, there will be 3 contracts
available for trading in the market
Same as Index Futures
Last trading
day Last Thursday of delivery month
Last Thursday of delivery
month
Price limits +/- 10% LTP +/- 10% LTP
Price steps 0.05 0.05
Base prices Daily settlement price of the futures
contracts.
Daily settlement price of
the futures contracts.
(Source: Retrieved & Adapted from www.nseindia.com)
60
NSE is India’s leading Stock Exchange incorporated in the year 1992. Indices values
of NSE calculate based on Free Float market capitalization Method (After 2008).
Currently more than 1500 securities are listed in NSE.
Table 3.5 shows the specifications of the stock index futures and individual stocks of
NSE. NSE commenced trading of index futures on June 12 2000. CNX Nifty index
futures was the first futures contract launched on NSE. Further, NSE commenced
trading of stock futures on November 2001. As per SEBI st ipulation, currently 141
individual stock futures and 9 major stock index futures including three global indices
are available for trading in NSE. NSE futures contracts have a maximum of 3- month
trading cycle - one month (near), the two month (next) and the three month (far). A
new futures contract is introduced on the immediate next trading day of the expiry of
the first month (near month) contract. NSE futures contracts both stock index futures
and individual stocks mature on the last Thursday of every month.
Table: 3.6 Main specifications of the CNX NIFTY, BANK NIFTY & CNX IT
Futures contracts of NSE
Particulars CNX Nifty Index
Futures
Bank Nifty Index
Futures
CNX IT Index
Futures
Opening Date June 12, 2000. June 2005 August 2003
Underlying Index CNX NIFTY Bank NIFTY CNX IT
Contract Size
The value of the
futures contracts on Nifty may not be
less than Rs. 2
lakhs at the time of
introduction. Lot Size- 25
The value of the
futures contracts on BANK Nifty may
not be less than Rs.
2 lakhs at the time
of introduction. Lot Size- 25
The value of the
futures contracts on CNX IT may not be
less than Rs. 2
lakhs at the time of
introduction. Lot Size- 25
Minimum price
change 0.05 0.05 0.05
Price limits +/- 10% LTP +/- 10% LTP +/- 10% LTP
Last trading Day Last Thursday of delivery month
Last Thursday of delivery month
Last Thursday of delivery month
Settlement Cash Cash Cash
(Source: Retrieved & Adapted from www.nseindia.com)
Table 3.6 shows specifications of three stock index futures of NSE - CNX NIFTY,
BANK NIFTY & CNX IT. The CNX Nifty index futures is based on popular market
bench mark CNX Nifty underlying index which is having highest trading history of
14 years, constitutes 50 major stocks and 66.85% of free float market capitalization of
NSE as on June 30, 2014. The CNXIT index futures is based on the underlying index
61
of CNXIT Index, which is having trading history of 11 years, constitutes 20 major
stocks of IT sectors, represents 97.25% of the free float market capitalization of the IT
sectors and constitutes 11.27% of the free float market capitalization of all the stocks
of NSE as on June 30, 2014. The Bank Nifty index futures is based on the underlying
index of CNX Bank Nifty index, which is having trading history of 9 years,
constitutes 12 stocks of banking sectors, represents 89.90% of the free float market
capitalization of the banking stocks which are listed in NSE and finally constituents
15.55% of the free float market capitalization of all the stocks which are listed in NSE
Selection Criteria
Eligibility Criteria of Individual Stocks to trade in F&O
1. The individual stocks will be selected from top 500 individual stocks based on
average daily turnover and average daily market capitalization from the last six
months period on a rolling basis
2. The individual stocks median quarter sigma order size should be minimum 10
lakhs.
3. The marketwise position limit (number of shares) should be minimum Rs 300
crores. The value will be calculated based on the closing price of the underlying
asset trading on expiry date of the F&O contract. Additionally the number of
underlying stocks of the F&O contract should be 20% of the total number of
underlying stocks held by non- promoters of relevant underlying security.
4. Further an existing F&O stock in order to continue eligible in trading F&O
segment, the individual stocks average monthly turnover in F&O segment from
last 3 months should be greater than 100 crores. The market wide position limit in
the stock should be greater than 100 crores. The market wide position limit in the
stock should be greater than 200 crores and stock’s median quarter – sigma order
size from last six months should be greater than 5 lakh rupees.
Procedure to calculate the quarter sigma order size
Assume that VAR (Value at Risk) is 0.03 (VAR formula suggested by J R Verma
committee guidelines), VAR value is also known as standard deviation – the
probability of stock can vary ± 3% from the current closing price on the next trading
day.
62
Quarter sigma can be calculated by multiplying 0.25 with calculated standard
deviation (one sigma). For example assume one sigma = 0.06 then, Quarter sigma=
0.25 × 0.06 = 0.015.
Quarter Sigma price (QSP) can be calculated by multiplying quarter sigma with
average price of the stock (Best buy price+ Best sell price)/ 2. For example, security
ABC, best buy (in Rs) = 200 and Best sell (in Rs) = 210 (Best buy and sell prices
taken four times a in day from NSE’s capital market segment order book). Average
price = (200+210)/2 = 205. QSP = 0.015× 205 = 3.075.
Eligibility Criteria for Indices to trade in F & O
Indices whose 80% of the constituent stocks are individually eligible for F&O
segment trading, then such indices can be introduced for trading in F&O segment.
However, the index will be ineligible if any one of the constituent ineligible
individual stock having weightage of more than 5%. SEBI applies the above criteria
every month. If index unable to meet the above criteria for 3 months continuously
then no fresh month contracts will be issued for that index.
Clearing and Settlement
National Securities Clearing Corporation Limited (NSCCL) act as legal counterparty
and completely undertakes clearing mechanism, settlement procedure and risk
management systems for all the trade contracts of F &O segment. NSCCL achieves
the clearing and settlement activities of F&O with help of (i).Clearing Member (CM)
(ii).Clearing Banks
(i). Clearing Member: Generally three different types of clearing member are found in
NSE, F&O segment. (a). Self-clearing members : Members who clear and settle the
trades executed by themselves or their clients. (b). Trading Member –cum- clearing
member: members who clears and settle the trades executed by themselves (own) and
trades executed by other trading members. (c). Professional clearing members (PCM):
The special members who clear and settle only the trades executed by trading
members.
(ii). Clearing Banks: The banks through which F&O funds settlement takes place are
known as clearing banks. NSCCL mandate to all the clearing members to open a
separate bank account with NSCCL designated clearing banks for the purpose of all
63
F&O funds settlement process. NSE’s F& O clearing and settlement process includes
the following three important activities.
1. Clearing Mechanism
2. Settlement Procedure
3. Risk Management
1. Clearing Mechanism: The objective of clearing mechanism of F & O segment
contracts are mainly two fold. First one is to identify open positions of all the
clearing members and the second one finds out the obligations of all the clearing
members. The purpose of considering open positions is to know the participants
risk exposure and daily margin status.
Trading Member’s (TM) open positions can be determined by adding proprietary
open positions with client open positions (both long and short positions)
(ii). Final Settlement of Futures contracts.
Futures contracts on both individual stocks and indices are cash settled. The final
settlement of futures contracts take place on the expiry date of contract. NSCCL
considers expiry day’s closing price and the resulting profit or loss amount is
credited or debited to the relevant clearing member’s clearing bank account on the
next day of expiry date of the contract. In NSE the last half an hour weighted
average price of the futures contract is considered as closing price of the futures
contract.
Settlement of Futures Contracts
Settlement of futures contracts (both stocks and index) are generally two types. Daily
settlement (Mark- Market settlement) and final settlement which takes place on expiry
date of the futures contract.
Mark- to Market (MTM) Settlement
In futures contracts trading, the clearing corporation of the exchange covers the
counter party risk through mark to market settlement process. It is the process of
adjusting the margin balance based on the daily gains or losses of the futures buyers
or sellers in the futures account. If the investor gains on a particular day then that gain
to be added to previous day’s margin balance. If he loses, then that day loss amount to
be deducted from previous day’s margin balance. This type of daily settlement is
64
known as marking to market settlement. The minimum level of margin money, the
futures buyers and sellers must maintain throughout the holding period of the contract
is known as maintenance margin. In case the futures investor daily losses are more
than gains and margin falls to maintenance margin or below, then future investor must
transfer the additional fund to top up the margin account to the initial margin level
before commencement of trading on the next day. Table 3.7 shows the illustrative
example of futures Mark - to - Market (MTM) settlement process.
For example
Initial Futures Price = Rs 10000 (1000 × 10); Initial Margin Requirement = Rs 5000;
Maintenance Margin Requirement - Rs 3000; Contract Size= 10
Table: 3.7 Illustrative example of futures contracts Mark- to - Market (MTM)
settlement process
Day
Beginning
Balance
(Rs)
Funds
Deposited
(Rs)
Settlement
Price (Rs)
(1000×10)
Future
Price
Changes
Gain/Loss
for entire
contract
size
End of
the day
Balance
0 0 5000 10000 - - -
1 5000 0 9200 -80 -800 4200
2 4200 0 6000 -320 -3200 1000
3 1000 4000 11000 500 5000 10000
4 10000 0 13500 250 2500 12500
5 12500 0 13000 -50 -500 12000
6 12000 0 14000 100 1000 13000
(Source: Developed by Researcher)
Risk Management
Though derivative instruments can be used as risk management tools but exposed to
high risk if it is used for trading purposes. Thus, NSCCL has taken essential measures
to reduce counterparty risk. Risk management mechanism is one of the important
components of NCSSL. Risk management mechanism includes margin requirements,
capital based position limits, online position monitoring of clearing members, capital
adequacy requirements of members, automatic stop of trading members from further
trading when limits are breached.
The paramount activities of risk management mechanism for F&O segment is
monitoring on line positions and margining system. NCSSL carried out these two
important activities. PRISM (Parallel Risk Management System) and another
65
important system called SPAN (Standard Portfolio Analysis of Risk) are used to
assess the overall risk involved in all F&O contracts of each member. Further, PRISM
monitors whether Clearing Member (CM) is collecting adequate initial margin for
futures trading and premium margin for options trading from Trading Members (TM)
and his respective clients.
Free float methodology
Free float methodology is an index construction methodology which considers free
float market capitalization of a stock to calculate the value of indices by assigning
respective weights to each stock in the index. Free float methodology considers only
the shares of the company which are readily available for trading in the stock market
(float). It generally excludes the stocks, held by government, promoters and group,
other associate/ companies (cross holding), employee welfare trusts and other locked
in shares.
Free float market capitalization is computed by multiplying Investible Weight Factors
(IWF) with total market capitalization of respective constituent stock in the index.
Total market capitalization is the product of market price per share and the total
number of outstanding shares of the company.
Example- Determination of CNX Nifty Index value
The CNX Nifty index value to be determined relative to the base period of November
3, 1995 and Base index value of 1000. The base index value derived by the market
capitalization value of CNX Nifty during the base period is equated to index value of
1000.
Total Market Capitalization = Total number of outstanding shares of all the
constituent companies of the index * Price/ share.
Free Float Market Capitalization = Total Market Capitalization * IWF
Index Value = Current Market Value / Base Market Capital * Base Index Value
(1000)
66
Determination of IWF
Ex – ABC Company
Total number of shares – 1000
Table: 3.8 Illustrative Example of percentage of shareholding for Index
Calculation
Particulars Shares %
Promoter and group 200 20
Government holding 10 1
Group of companies ( Cross holding) 20 2
Employee welfare trust 5 0.5
Lock in category shares 100 10
Total 335 33.5%
(Source: Developed by Researcher)
Table 3.8 shows the illustrative example of percentage of shareholding for index
calculation. Table 3.8 shows 33.5% of the shares hold by the people or groups other
than public.
IWF= (1000- 335) / 1000 = 0.665
IWF = 0.665 means that only 66.5% of the total market capitalization of the
ABC company will be considered for Index calculation.
67
3.2 Business Growth of Global Derivatives Market
Table: 3.9 Historical growth of Global individual stock futures and index futures
Year
Stock Futures Stock Index Futures
No of contracts
(Million)
Notional Value
(Billion $)
No of contracts
(Million)
Notional Value
(Billion $)
Volume Growth Value Growth Volume Growth Value Growth
2000 3.36 ---- ---- ---- 185.91 ---- ---- ----
2001 12.79 280.65 ---- ---- 318.23 71.17 ---- ----
2002 54.86 328.93 52.88 ---- 528.18 65.97 95739.29 ----
2003 48.13 -12.27 211.65 300.25 623.8 18.10 40283.24 -57.92
2004 81.95 70.27 447.76 111.56 738.51 18.38 42051.06 4.39
2005 140.06 70.91 650 45.17 875.16 18.50 51402.25 22.24
2006 278.43 98.79 1538.82 136.74 1160.6 32.61 75496.65 46.87
2007 618.44 122.12 2597.47 68.8 1656.25 42.70 123978.6 64.22
2008 997.61 61.31 2174.68 -16.28 2201.58 32.92 118376.4 -4.52
2009 656.46 -34.2 2096.03 -3.62 1898.29 -13.77 79145.57 -33.14
2010 847.35 29.08 2854.44 36.18 1991.55 4.91 101303.5 28
2011 1109.22 30.9 2645.93 -7.3 2504.54 25.75 118704.2 17.18
2012 1018.12 -8.21 2167.23 -18.09 2202.82 -12.04 104099.1 -12.3
2013 883.55 -13.22 2176.99 0.45 2201.1 -0.07 125484.4 20.54
2014 1022.24 15.7 2479.49 13.9 2323.54 5.56 133055.9 6.03
CAGR (%) 74.34
55.64
22.19
8.46
(Source: Developed by Researcher)
68
Table: 3.10 Historical growth of global individual stock options and index
options
Year
Stock Options Stock Index Options
No of Contracts
(Million)
Notional Value
(Billion $ )
No of Contracts
(Million)
Notional Value
(Billion $ )
Volume Growth
(%) Value
Growth
(%) Volume
Growth
(%) Value
Growth
(%)
2000 762.87 ---- ---- ---- 353.7 ---- ---- ----
2001 1126.75 47.7 ---- ---- 1161.06 228.26 ---- ----
2002 1190.99 5.7 2370.61 ---- 2312.16 99.14 10958.45 ----
2003 931.85 -21.76 1286.42 -45.73 3207.7 38.73 27516.95 151.1
2004 1669.87 79.2 2139.73 66.33 2996.72 -6.58 43430.85 57.83
2005 2139.86 28.15 3277.81 53.19 3195.77 6.64 59374.1 36.71
2006 2668.03 24.68 5610.51 71.17 3290.75 2.97 85158.57 43.43
2007 3775.04 41.49 10105.1 80.11 3794.14 15.3 131637.9 54.58
2008 4680.23 23.98 6546.44 -35.22 4115.57 8.47 103145.6 -21.64
2009 4592.45 -1.88 5240.45 -19.95 4207.24 2.23 86967.36 -15.68
2010 3808.44 -17.07 6878.67 31.26 5067.14 20.44 124768.9 43.47
2011 3877.34 1.81 7176.48 4.33 5801.51 14.49 147297.9 18.06
2012 3803.72 -1.9 8769.53 22.2 3738.82 -35.55 101403.6 -31.16
2013 3922.2 3.11 6742.63 -23.11 2916.88 -21.98 146036 44.01
2014 3714.46 -5.3 3986.66 -40.87 3329.7 14.15 99117.89 -32.13
CAGR (%) 14.85
13.64
27.62
29.04
(Source: Developed by Researcher)
The global financial derivatives market comprises of individual stock options &
futures and stock index options and futures. It is the fastest growing segment of the
global financial sector. Table 3.9 reports the statistical figures, revealed by Word
Federation of Exchange (WFE) on growth of global derivative markets .Table 3.9
shows that, since 2000, global individual stock futures size has been increased by on
average 74.43%, per year in terms of volume of contracts traded. Volume of contracts
traded for individual stock futures has been increased from 3.36 million in 2000 to
1022.24 million in 2014. Global stock index futures size has been increased by on
average 22.19%, per year in terms of volume of contracts traded. Volume of contracts
traded for stock index futures has been increased from 185.91 million in 2000 to
2323.54 million in 2014. Further, Global individual stock futures notional value has
been increased by on average 13.64%, per year. Its notional value has been increased
from 2370.61 bn $ in 2002 to 3986.66 bn $ in 2014. Global stock index futures
notional value has been increased by on average 29%, per year. Its notional value has
been increased from 10958.45 bn $ in 2002 to 99117 bn $ in 2014.
69
Table 3.10 shows global individual options stocks size has been increased by on
average 14.85%, per year in terms of volume of contracts traded. Volume of contracts
traded for individual options stocks has been increased from 762.57 million in 2000 to
3714.24 million in 2014. Global stock index options size has been increased by on
average 27.62%, per year in terms of volume of contracts traded. Volume of contracts
traded for stock index options has been increased from 353.7 million in 2000 to
3329.7 million in 2014. Further, Global individual options stocks notional value has
been increased by on average 13.64%, per year. Its notional value has been increased
from 2370.61 bn $ in 2002 to 3986.66 bn $ in 2014. Global stock index options
notional value has been increased by on average 29.04%, per year. Its notional value
has been increased from 10958.45 bn $ in 2002 to 99117 bn $ in 2014.
Further, Tables 3.9 & 3.10 clearly show that highest global derivatives growth
recorded in the year 2007 for both options and futures category. Further, it shows that
lowest global derivatives growth recorded in the year 2009 and 2012 respectively for
both options and futures category.
In the year 2007, volume of global individual stock futures and stock index futures
increased to 122.2% and 42.70 % from the previous year respectively. Notional value
of global individual stock futures and stock index futures increased to 68.8% and
64.2% from the previous year respectively. Similarly, volume of global individual
stock options and stock index options increased to 41.49% and 15.3 % from the
previous year respectively. Notional value of global individual stock options and
stock index options increased to 80.11% and 54.58 % from the previous year
respectively
Additionally, in the year 2009, volume of global individual stock futures and stock
index futures decreased to 34.2% and 13.7 % from the previous year respectively.
Notional value of global individual stock futures and stock index futures decreased to
3.6% and 33.1% from the previous year respectively. Similarly, volume of global
individual stock options and stock index options decreased to 1.88 % and increased to
2.23 % from the previous year respectively. Notional value of global individual stock
options and stock index options decreased to 19.9% and 15.6 % from the previous
year respectively.
Further, in the year 2012, volume of global individual stock futures and stock index
futures decreased to 8.21% and 12 % from the previous year respectively. Notional
70
value of global individual stock futures and stock index futures decreased to 18.09 %
and 12.3% from the previous year respectively. Similarly, volume of global individual
stock options and stock index options decreased to 1.9% and 35.5 % from the
previous year respectively. Notional value of global individual stock options and
stock index options increased to 22.2% and decreased to 31.16% from the previous
year respectively
Though volume and turnover of global derivatives remarkably increased from 2002,
the growth of global derivatives slightly decreased from last three years (2012, 2013
and 2014). From the last three years, volume of global individual stock futures and
stock index futures decreased by on average 1.91% and 14.46% per year respectively.
Notional value of global individual stock futures and stock index futures decreased by
on average 1.2 % and increased by on average 4.7 % per year respectively. Similarly,
volume of global individual stock options and stock index options decreased by on
average 1.3% and 14.4 % per year respectively. Notional value of global individual
stock options and stock index options decreased by on average 13.9 % and 6.4% per
year respectively.
Top 10 world stock exchanges by volume of derivatives contracts traded in the
year 2013.
Figure: 3.2 The Top 10 world stock exchanges by volume of single stock futures
contracts traded in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
303
179 166
120 96
26 15 8 7 7 19
0
50
100
150
200
250
300
350
Mo
sco
w
Eure
x
NSE
Ind
ia
NYS
E Li
ffe
Ko
rea
Joh
ann
esb
urg
MEF
F
Thai
lan
d
On
e C
hic
ago
Ath
ens
Oth
ers
Co
ntr
acts
Tra
de
d
Stock Exchange
Number of Single Stock Futures Contracts Millions of Contracts Traded
71
Figure: 3.3 The Top 10 world stock exchanges by volume of index futures
contracts traded in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.4 The Top 10 world stock exchanges by volume of single stock options
contracts traded in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
574
327 268 265
193 102 100 82 74 51
297
0
100
200
300
400
500
600
CM
E G
rou
p
Eure
x
Mo
sco
w
Jap
an
Ch
ina
NSE
Ind
ia
Sin
gap
ore
NYS
E Li
ffe
BM
&FB
OV
ESP
A
Ho
ng
Ko
ng
Oth
ers
Co
ntr
acts
tra
de
d
Stock Exchange
Number of Index Futures Contracts Millions of Contracts …
909
704
584
434 334
142 124 99 82 63
248
0
200
400
600
800
BM
&FB
OV
ESP
A
NA
SDA
Q O
MX
NYS
E Eu
ron
ext
CB
OE
ISE
Eu
rex
ASE
NYS
E Li
ffe
NSE
Ind
ia
BO
E
Oth
ers
Co
ntr
acts
Tra
de
d
Stock Exchange
Number of single stock options contracts Millions of Contracts …
72
Figure: 3.5 The Top 10 world stock exchanges by volume of index options
contracts traded in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.6 The Top 10 world stock exchanges by volume of currency derivatives
contracts traded in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
930
580
317 250 230
110 92 57 48 42 121
0 100 200 300 400 500 600 700 800 900
NSE
Ind
ia
Ko
rea
Eu
rex
BSE
Lim
ited
CB
OE
TAIF
EX
CM
E G
rou
p
NYS
E Li
ffe
Tel-
Avi
v SE
Mo
sco
w
Oth
ers
Co
ntr
acts
Tra
de
d
Stock Exchange
Stcok Index Options Contracts
85
6
52
9
46
0
22
3
12
1
55
53
51
48
34
74
0
200
400
600
800
NSE
Ind
ia
MC
X-S
X
Mo
sco
w
CM
E G
rou
p
BM
&FB
OV
ESP
A
Toky
o
Ko
rea
Ro
fex
USE
Ind
ia
Joh
ann
esb
urg
Oth
ers
Co
ntr
acts
Tra
de
d
Stock Exchange
Number of Currencty Derivative Contracts Traded
73
Figure: 3.7 The Top 10 world stock exchanges by EOB number of trades in the
year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
According to survey conducted by World Federation of Exchanges on the
performance of 62 stock exchanges across the world during the year 2013, Figures
3.2 to 3.7 present the top 10 world stock exchanges by volume of derivatives contracts
traded in the year 2013.
The Figures 3.2 to 3.7 clearly indicate that, National Stock Exchange of India has
ranked for six different reasons in top 10. Fig 3.6 shows that NSE, India, has been
ranked No 1 for number of currency derivatives contracts traded (34.19%) followed
by MCX-SX, India (21.13%), Moscow, Russia (18.37%). Fig 3.5 shows that NSE,
India, has been ranked No 1 for, number of stock index options contracts traded
(34.4%) followed by Korean Stock exchange (20.8%) and Eurex, German derivative
exchange (11.4%).
Fig 3.7 shows, it has been ranked again No 1 for Electronic Order Book (EOB)
number of trades (16.74%), followed by Shenzhen, China (14.89%), NYSE and USA
(13.73%) in the year 2013. Additionally, Fig 3.2 shows, the NSE, India has been
ranked No 3 for number of single stock futures contracts traded (17.5%), after Eurex,
German derivative exchange (18.92%) and Moscow, Russia (32.03%). Further, Fig
3.3 shows the NSE India, ranked No 6 for number of stock index futures contracts
traded (4.32%), after China (8.27%), Japan (11.3%), Moscow, Russia (11.4), Eurex,
14
49
12
89
11
88
11
53
11
52
10
32
59
9
34
5
23
6
21
1
0
200
400
600
800
1000
1200
1400
1600
NSE
Ind
ia
Shen
zhen
NYS
E
Shan
ghai
NA
SDA
Q
Ko
rea
Jap
an
BSE
Ind
ia
TM
X G
rou
p
Lo
nd
on
EOB
Nu
mb
er
Stock Exchange
EOB Number of Trades Millions of EOB traded
74
Germany (14%), CME Group Chicago Mercantile Exchange, and USA (24.6%).
Finally,
Fig 3.4 shows, the NSE , India, has been ranked No 9 for number of single stock
options contracts traded (2.17%), after NYSE Liffe - Europian Markets (2.62%), ASE
(3.28%), Eurex (3.75%), ISE- International Stock Exchange (8.82%), CBOE -
Chicago Board Options Exchange (11.47%), NYSE Euronext- US Markets (15.43%),
NASDAQ OMX – US Markets (18.36%) , BM&FBOVESPA, Brazil (24.02%)
Breakdown of global derivatives volume and notional value by region.
Figure: 3.8 The Breakdown of notional value of global single stock options by
region in the year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.9 The Breakdown of volume of global single stock options by region in
the year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Americas 68%
Asia - Pacific 13%
Europe - Africa - Middle East
19%
SINGLE STOCK OPTIONS -NOTIONAL VALUE ( USD MILLION $)
Americas 82%
Asia - Pacific 7%
Europe - Africa - Middle East
11%
GLOBAL SINGLE STOCK OPTIONS - NUMBER OF CONTRACTS TRADED
75
Figure: 3.10 The Breakdown of notional value of global index options by region
in the year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.11 The Breakdown of volume of global index options by region in the
year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Americas 33%
Asia - Pacific 54%
Europe - Africa - Middle East
13%
STOCK INDEX OPTIONS - NOTIONAL VALUE
Americas 12%
Asia - Pacific 71%
Europe - Africa - Middle East
17%
GLOBAL STOCK INDEX OPTIONS - NUMBER OF CONTRACTS TRADRD
76
Figure: 3.12 The Breakdown of notional value of global index futures by region
in the year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.13 The Breakdown of volume of global index futures by region in the
year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
Americas 29%
Asia - Pacific 26%
Europe - Africa - Middle East 45%
STOCK INDEX FUTURES - NOTIONAL VALUE
Americas 29%
Asia - Pacific 37%
Europe - Africa - Middle East 34%
GLOBAL STOCK INDEX FUTURES - NUMBER OF CONTRACTS TRADED
77
Figure: 3.14 The Breakdown of notional value of global individual stock futures
by region in the year 2013
(Source: Retrieved & Adapted from www.world-exchanges.org)
Figure: 3.15 The Breakdown of volume of global individual stock futures by
region in the year 2013.
(Source: Retrieved & Adapted from www.world-exchanges.org)
According to survey conducted by World Federation of Exchanges on the
performance of world stock exchanges during the year 2013, Figures 3.8 to 3.15
present breakdown of global derivatives volume and notional value by region.
Fig 3.8 clearly indicates breakdown of global notional value of individual stock
options. After the American region stock exchanges which constitutes about 68%,
[CELLRANGE]% [CATEGORY NAME]
[CATEGORY NAME]
40.23%
[CATEGORY NAME] 59.74%
GLOBAL STOCK FUTURES- NOTIONAL VALUE
Americas 1% Asia - Pacific
29%
Europe - Africa - Middle East
70%
GLOBAL STOCK FUTURES - NUMBER OF CONTRACTS TRADED
78
Stock exchanges of Europe - Africa- Middle east region occupies second slot by
contributing 19% and Stock exchanges of Asia – Pacific region occupies third slot
with a share of 13%.
Fig.3.9 clearly shows breakdown of volume of global individual stock options. After
the American region stock exchanges which constitutes major proportions about 82%,
Stock Exchanges of Europe- Africa- Middle east region occupies second slot with a
share of 11%. Stock Exchanges of Asia – Pacific region occupies third slot by
contributing 7%.
Fig.3.10 clearly indicates breakdown of notional value of global stock index options.
After the Asia – Pacific region stock exchanges with a share of 54%, Stock exchanges
of American region occupies second slot by contributing 33% and Stock exchanges of
Europe- Africa- Middle east region occupies third slot with a share of 13%.
Fig.3.11 clearly presents breakdown of volume of global stock index options. After
the Asia – Pacific region stock exchanges with a share of 71%, Europe- Africa-
Middle east region Stock exchanges of occupies second slot by contributing 17% and
Stock exchanges of American region occupies third slot with a share of 12%.
Fig.3.12 clearly shows breakdown of notional value of global stock index futures.
After the Europe- Africa- Middle east stock exchanges with a share of 45%, American
region stock exchanges occupies second slot by contributing 29% and Stock
exchanges of Asia – Pacific region occupies third slot with a share of 26%.
Fig.3.13 clearly presents breakdown of volume of global stock index futures. After
the Asia – Pacific region stock exchanges with a share of 37%, Europe- Africa-
Middle east region Stock exchanges of occupies second slot by contributing 34% and
Stock exchanges of American region occupies third slot with a share of 29%.
Fig.3.14 clearly presents breakdown of notional value of global individual stock
futures. After the Europe- Africa- Middle east stock exchanges with a share of
59.74%, Asia – Pacific region Stock exchanges of occupies second slot with a share
79
of 40.23% and American Stock exchanges of occupies third slot with a least share of
0.02%.
Fig.3.15 clearly shows breakdown of volume of global individual stock futures. After
the Europe- Africa- Middle east stock exchanges with a major share of 70%, Asia –
Pacific region Stock exchanges of occupies second slot with a share of 29% and
American Stock exchanges occupies third slot with a least share of 1%.
Overall from the Figures 3.8 to 3.15, it can be summarize that American stock
exchanges dominates Trading of Major proportion of global individual stock options
in terms of both notional value and trading volume. Asia – Pacific region Stock
exchanges dominates trading of major proportion of global stock index options in
terms of both notional value and trading volume. Europe- Africa- Middle east stock
exchanges dominates trading of major proportion of individual stock futures in terms
of both notional value and trading volume. Though all the three regions contribute
major proportion of trading of stock index futures, Asia – Pacific region Stock
exchanges and Europe- Africa- Middle east stock exchanges dominates trading of
major proportion of global stock index futures in terms of trading volume and
notional value respectively. Finally Figures 3.14 & 3.15 show that American Stock
Exchanges occupies very minute share (0.02 % and 1%) in trading global individual
stock futures both in terms of notional value and trading volume.
80
Table: 3.11 largest global domestic equity market capitalization at year-end 2013
Sl
No Stock Exchange
Market
Capitalisation Number of
Domestic
Companies
Number of
Foreign
Companies
Total USD
Billion %
1 NYSE Euronext (US) 17950 29.85 1852 519 2371
2 NASDAQ OMX (US) 6085 10.12 2328 309 2637
3 Japan Exchange Group 4543 7.55 3408 11 3419
4 London Stock Exchange
Group 4429 7.36 - - 2490
5 NYSE Euronext (Europe) 3584 5.96 935 127 1062
6 Hong Kong Exchanges 3101 5.16 1553 90 1643
7 Shanghai SE 2497 4.15 1536 NA 1536
8 TMX Group 2114 3.52 3810 76 3886
9 Deutsche Börse 1936 3.22 639 81 720
10 SIX Swiss Exchange 1541 2.56 236 36 272
11 Shenzhen SE 1452 2.41 1536 NA 1536
12 Australian stock exchange 1365 2.27 1955 100 2055
13 NASDAQ OMX Nordic
Exchange 1269 2.11 755 27 728
14 BSE ,India 1138 1.89 5294 NA 5294
15 BME Spanish Exchanges 1116 1.86 3213 32 3245
16 NSE, India 1112 1.85 1678 1 1679
17 BM&FBOVESPA 1020 1.70 352 11 363
18 Johannesburg SE 942 1.57 322 53 375
19 Taiwan SE 822 1.37 802 64 866
20 Others 2124 3.53 - - 7311
Total 60140 100 32204
43488
(Source: Retrieved & Adapted from www.world-exchanges.org)
According to survey conducted by World Federation of Exchanges on the
performance of 62 world stock exchanges during the year 2013. Table 3.11 presents
largest global domestic equity market capitalization at the year-end 2013. It clearly
indicates that in the year 2013 global equity market capitalization reached 60140
Billion US $. Out of 62 world stock exchanges 19 world stock exchanges alone
constituents 96.47% of total global domestic equity market capitalization. Top 7
world stock exchanges (NYSE Euronext (US) , NASDAQ OMX (US) , Japan
Exchange Group, London Stock Exchange Group, NYSE Euronext (Europe) , Hong
Kong Exchanges and Shanghai SE alone constitutes 70% of the total global
domestic market capitalization in the year 2013. Further BSE, and NSE, India
occupies 14th and 16th slot with a share of 1.89% and 1.85% of world domestic equity
market capitalization respectively.
81
Further, the Table 3.11 shows that number of domestic companies and foreign
companies listed in each major stock exchanges of the world. There are totally 32204
domestic companies listed in global stock exchanges. BSE, India, is the top stock
exchange in terms of number of domestic companies listed (5295) followed by TMX
Group (3810), Japan Exchange Group (3408), BME Spanish Exchanges (3213) and
NASDAQ OMX (US) (2328), Australian stock exchange (1955), NYSE Euronext
(US) (1852) and NSE, India (1678).
3.3 Business Growth of Indian Derivatives Market
Business Growth of F & O at NSE
Figure: 3.16 Product-wise distribution of turnover of F&O segment of NSE
(2013–2014)
(Source: Retrieved & Adapted from www.nseindia.com)
Fig.3.16 presents product wise turnover of derivative (Futures and Options) segment
in NSE in the year 2013-2014. Fig.3.16 clearly indicates that index options is the
leader in the product wise turnover of futures and options segment of the NSE. The
turnover of index options contributed highest share of 73 % of the total turnover in the
Futures & Options segment of the NSE followed by stock futures and index futures
which account of 13% and 8% of the total turnover in the F & O segment of NSE
respectively. The turnover of stock options contributed lowest share of 6% of the total
turnover in the futures & options segment of the NSE. This statistics are revealed that
more investors are attracting and preferring index options segment of the NSE than
other products of F&O.
Index Futures 8%
Stock Futures 13%
Index Options 73%
Stock Options 6%
F& O TURNOVER
82
Table: 3.12 Business growth of index futures at NSE
Year
Index Futures
No of contracts Turnover
Volume
(Million) Growth (%)
Volume
(Rs. Billion) Growth (%)
2000-01 0.09 --- 23.65 ---
2001-02 1.03 1032.25 214.83 808.37
2002-03 2.13 107.37 439.52 104.59
2003-04 17.19 708.35 5544.46 1161.48
2004-05 21.64 25.85 7721.47 39.26
2005-06 58.54 170.56 15137.55 96.04
2006-07 81.49 39.20 25395.74 67.77
2007-08 156.60 92.18 38206.67 50.45
2008-09 210.43 34.37 35701.11 -6.56
2009-10 178.31 -15.26 39343.89 10.20
2010-11 165.02 -7.45 43567.55 10.74
2011-12 146.19 -11.41 35779.98 -17.87
2012-13 96.10 -34.26 25271.31 -29.37
2013-14 105.25 9.52 30831.03 22.00
CAGR (%)
66.55
66.90
(Source: Retrieved & Adapted from www.nseindia.com)
Figure: 3.17 The historical business growth of index futures in terms of number
of contracts traded at NSE, India
(Source: Table: 3.12)
0.0
9
1.0
3
2.1
3
17
.19
21
.64
58
.54
81
.49
15
6.6
0 2
10
.43
17
8.3
1
16
5.0
2
14
6.1
9
96
.10
10
5.2
5
0.00
50.00
100.00
150.00
200.00
250.00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Nu
mb
er
of
Co
ntr
acts
( M
n)
Year
83
Figure: 3.18 The historical business growth of index futures in terms of turnover
at NSE, India
(Source: Table: 3.12)
NSE, commenced trading of derivatives first time in India by introducing CNX Nifty
index futures on June 2000. Right from introduction of Nifty index futures on June
2000, over a period time NSE introduced many more indices on futures. Currently (as
of march 2015) there are 9 indices including 3 global indices are available for trading
in futures derivatives in NSE). In fact, NSE India, ranked top 6 among 62 world stock
exchanges for number of index futures contracts traded (4.32%) globally during the
year 2013. As index futures is in the third slot by contributing 8% of the total turnover
in the F &O segment in the year 2013-14 at NSE after index options (73%) and stock
futures ( 13%) respectively, there is a huge scope for significant growth of index
futures turnover.
Table 3.12 shows the business growth of index futures at NSE in terms of number of
contracts traded and turnover from 2000 -01 to 2013 -14. The size of the index futures
at NSE in terms of number of contracts traded has increased from 0.09 million in 200-
2001 to 105.25 million in 2013-14. Similarly, the index futures turnover at NSE has
increased from 23.65 Rs Billion in 2000-01 to 30831.03 Rs Billion in 2013- 14.
Additionally, the size of the index futures at NSE in terms of number of contracts
traded witnessed a CAGR (Compounded Annual Growth Rate) of 66.55% in last 14
years. Similarly, the index futures turnover at NSE witnessed a CAGR of 66.90 % in
last 14 years.
Further, Table 3.12 and Fig. 3.17 clearly show that growth of index futures in terms
of number of contracts traded has increased remarkably from 2001-02 to 2008 -09
23
.65
21
4.8
3
43
9.5
2
55
44
.46
77
21
.47
15
13
7.5
5
25
39
5.7
4
38
20
6.6
7
35
70
1.1
1
39
34
3.8
9
43
56
7.5
5
35
77
9.9
8
25
27
1.3
1
30
83
1.0
3
0.00 5000.00
10000.00 15000.00 20000.00 25000.00 30000.00 35000.00 40000.00 45000.00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (
Rs
Bn
)
Year
Turnover- Index Futures
84
but the growth is declined continuously from the year 2009-10 to 2012-13 due to
global financial crisis like recession and euro zone debt crisis. Similarly, Table 3.12
and Fig. 3.18 indicate that the growth of index futures in terms of turnover has
increased significantly year after year excluding 2008-09, 2011-12 and 2012-13 with
decline of 6.56%, 17.37% and 29.37 % respectively due to global financial crisis.
Table: 3.13 Business growth of individual stock futures at NSE
Year
Stock Futures
No of Contracts (Million) Turnover (Rs Billion)
Volume Growth (%) Value Growth (%)
2001-02 1.96 ---- 515.15 ----
2002-03 10.68 444.90 2865.33 456.21
2003-04 32.37 203.09 13059.39 355.77
2004-05 47.04 45.32 14840.56 13.64
2005-06 80.91 72.00 27916.97 88.11
2006-07 104.96 29.72 38309.67 37.23
2007-08 203.59 93.97 75485.63 97.04
2008-09 221.58 8.84 34796.42 -53.90
2009-10 145.59 -34.29 51952.47 49.30
2010-11 186.04 27.78 54957.57 5.78
2011-12 158.34 -14.89 40746.71 -25.86
2012-13 147.71 -6.71 42238.72 3.66
2013-14 170.71 15.57 49492.82 17.17
CAGR (%)
41
42
(Source: Retrieved & Adapted from www.nseindia.com)
85
Figure: 3.19 The historical business growth of stock futures in terms of number
of contracts traded at NSE, India
(Source: Table: 3.13)
Figure: 3.20 The historical business growth of stock futures in terms of turnover
at NSE, India
(Source: Table: 3.13)
NSE, commenced trading of individual stock futures on November 2001. Over a
period time NSE introduced many more individual stocks on futures. Currently (as of
march 2015) there are 145 individual stocks are available for trading in futures
1.9
6
10
.68
32
.37
47
.04
80
.91
10
4.9
6
20
3.5
9
22
1.5
8
14
5.5
9 18
6.0
4
15
8.3
4
14
7.7
1
17
0.7
1
0.00
25.00
50.00
75.00
100.00
125.00
150.00
175.00
200.00
225.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Co
ntr
acts
( m
illio
n)
Year
Number of Contarcts- Stock Futures
51
5.1
5
28
65
.33
13
05
9.3
9
14
84
0.5
6
27
91
6.9
7
38
30
9.6
7
75
48
5.6
3
34
79
6.4
2
51
95
2.4
7
54
95
7.5
7
40
74
6.7
1
42
23
8.7
2
49
49
2.8
2
0.00
10000.00
20000.00
30000.00
40000.00
50000.00
60000.00
70000.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (
Rs
Bn
)
Year
Turnover- Stock Futures
86
derivatives in NSE. In fact, NSE India, ranked top 3 among 62 world stock exchanges
for number of stock futures contracts traded (17.5%) globally during the year 2013
and stock futures is in the second slot by contributing 13% of the total turnover in the
F &O segment in the year 2013-14 at NSE after index options (73%).
Table 3.13 reveals that the business growth of stock futures at NSE in terms of
number of contracts traded and turnover from 2001 - 02 to 2013 -14. The size of the
stock futures at NSE in terms of number of contracts traded has increased from 1.96
million in 2001- 02 to 170.71 million in 2013-14. Similarly, the stock futures turnover
at NSE has increased from 515.15 Rs Billion in 2001-02 to 49492. 82 Rs Billion in
2013- 14. Additionally, the size of the stock futures at NSE in terms of number of
contracts traded witnessed a CAGR (Compounded Annual Growth Rate) of 41 % in
the last 13 years. Similarly, the stock futures turnover at NSE witnessed a CAGR of
42 % in the last 13 years.
Further, Table 3.13 and Fig.3.19 clearly show that growth of stock futures in terms of
number of contracts traded has increased significantly from 2001- 02 to 2008 -09 but
the growth declined in the year 2009-10 , 2011-12 and 2012- 13 due to global
financial crisis like recession and euro zone debt crisis. Similarly, Table 3.13 and Fig.
3.20 indicate that the growth of stock futures in terms of turnover has increased
significantly year after year especially from the year 2006-07 to 2008-09. But stock
futures declined in the year 2008- 09 (53.90%) and 2011-12 (25.86%) respectively
due to global financial crisis.
87
Table: 3.14 Business growth of index options at NSE
Year
Index Options
No of contracts (Million) Turnover (Rs Billion)
Volume
(Million)
Growth
(%)
Value
(Rs Billion)
Growth
(%)
2001-02 0.18 ---- 37.65 ----
2002-03 0.44 151.42 92.46 145.58
2003-04 1.73 291.74 528.16 471.23
2004-05 3.29 90.11 1219.43 130.88
2005-06 12.94 292.74 3384.69 177.56
2006-07 25.16 94.49 7919.06 133.97
2007-08 55.37 120.08 13621.11 72.00
2008-09 212.09 283.07 37315.02 173.95
2009-10 341.38 60.96 80279.64 115.14
2010-11 650.64 90.59 183653.66 128.77
2011-12 864.02 32.80 227200.32 23.71
2012-13 820.88 -4.99 227815.74 0.27
2013-14 928.57 13.12 277673.41 21.89
CAGR (%)
93.33
98.39
(Source: Retrieved & Adapted from www.nseindia.com)
Figure: 3.21 The historical business growth of index options in terms of number
of contracts traded at NSE, India
(Source: Table: 3.14)
0.1
8
0.4
4
1.7
3
3.2
9
12
.94
25
.16
55
.37
21
2.0
9
34
1.3
8 6
50
.64
86
4.0
2
82
0.8
8
92
8.5
7
0.00
200.00
400.00
600.00
800.00
1000.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Nu
mb
er
of
Co
ntr
acts
( M
n)
Year
Number of Contracts- Index Options
88
Figure: 3.22 The historical business growth of index options in terms of turnover
at NSE, India
(Source: Table: 3.14)
NSE, commenced trading of index options on June 2001. Over a period of time NSE
introduced many more indices on options. Currently (as of march 2015) there are 5
indices including 2 global index ( CNX Nifty, Bank Nifty, CNX IT, FTSE 100 and S
& P 500 index ) are available for trading in index options in NSE. In fact, NSE India,
has been ranked No 1 among 62 world stock exchanges for number of index options
contracts traded (34.4%) globally during the year 2013 and more importantly index
options in the first slot by contributing 73% of the total turnover in the F &O segment
in the year 2013-14 at NSE, followed by stock futures and Index futures which
account of 13% and 8% respectively.
Table 3.14 presents that the growth of stock futures at NSE in terms of number of
contracts traded and turnover from 2001 -02 to 2013 -14. The size of the index
options at NSE in terms of number of contracts traded has tremendously increased
from 0.18 million in 2001-02 to 928.57 million in 2013-14. Similarly, index options
turnover at NSE has increased from 37.65 Rs Billion in 2001-02 to 277673.41 Rs
Billion in 2013- 14. Additionally, the size of the index options at NSE in terms of
number of contracts traded witnessed a highest CAGR (Compounded Annual Growth
Rate) of 93.33 % in the last 13 years. Similarly, the index options turnover at NSE
witnessed a highest CAGR of 98.39 % in last 13 years.
Further, Table 3.14 and Fig.3.21 clearly show that growth of index options in terms of
number of contracts traded has increased continuously from 2001-02 to 2013-14
excluding in the year 2012-13 due to global financial crisis. Similarly, Table 3.14 and
37
.65
92
.46
52
8.1
6
12
19
.43
33
84
.69
79
19
.06
13
62
1.1
1
37
31
5.0
2
80
27
9.6
4
18
36
53
.66
22
72
00
.32
22
78
15
.74
27
76
73
.41
0.00
50000.00
100000.00
150000.00
200000.00
250000.00
300000.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r( R
s B
n)
Year
Turnover- Index Option
89
Fig 3.22 indicate that the growth of index options in terms of turnover has
tremendously increased continuously year after year from 2001-02 to 2013-14. This
statistics clearly indicates that index options is the leader in the product wise turnover
of F&O segment of NSE. More and more investors are attracting and preferring index
options segment of the NSE than other products of F&O.
Table: 3.15 Business growth of individual stock options at NSE
Year
Stock Options
No of Contracts Turnover
Volume
(Million) Growth (%)
Value
(Rs Billion) Growth (%)
2001-02 1.04 ---- 251.63 ----
2002-03 3.52 239.56 1001.31 297.93
2003-04 5.58 58.47 2172.07 116.92
2004-05 5.05 -9.64 1688.36 -22.27
2005-06 5.24 3.88 1802.53 6.76
2006-07 5.28 0.81 1937.95 7.51
2007-08 9.46 79.07 3591.37 85.32
2008-09 13.30 40.54 2292.27 -36.17
2009-10 14.02 5.42 5060.65 120.77
2010-11 32.51 131.93 10303.44 103.60
2011-12 36.49 12.26 9770.31 -5.17
2012-13 66.78 82.98 20004.27 104.75
2013-14 80.17 20.06 24094.89 20.45
CAGR (%)
39.71
49.03
(Source: Retrieved & Adapted from www.nseindia.com)
Figure: 3.23 The historical business growth of stock options in terms of number
of contracts traded at NSE, India
(Source: Table: 3.15)
1.0
4
3.5
2
5.5
8
5.0
5
5.2
4
5.2
8
9.4
6
13
.30
14
.02
32
.51
36
.49
66
.78
80
.17
0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Nu
mb
er
of
Co
trac
ts (
Mn
)
Year
Number of Contracts -Stock Options
90
Figure: 3.24 The historical business growth of stock options in terms of turnover
at NSE, India
(Source: Table: 3.15)
NSE, commenced trading of individual stock options on July 2001. Over a period
time NSE introduced many more individual stocks on options. Currently (as of march
2015) there are 145 individual stocks are available for trading in stock options in
NSE. In fact, NSE India, ranked top 9 among 62 world stock exchanges for number of
stock futures contracts traded (2.17%) globally during the year 2013 and Stock
options is in the last slot by contributing only 6% of the total turnover in the F &O
segment in the year 2013-14 at NSE after index options (73%), stock futures (13%)
and index futures (8%) respectively.
Table 3.15 reveals that the growth of stock options at NSE in terms of number of
contracts traded and turnover from 2001-02 to 2013 -14. The size of the stock options
at NSE in terms of number of contracts traded has increased from 1.04 million in
2001-02 to 80.17 million in 2013-14. Similarly, the stock options turnover at NSE has
increased from 251.63 Rs Billion in 2001-02 to 24094.89 Rs Billion in 2013- 14.
Additionally, the size of the stock options at NSE in terms of number of contracts
traded witnessed a CAGR (Compounded Annual Growth Rate) of 39.71% in the last
13 years. Similarly, the stock options turnover at NSE witnessed a CAGR of 49.03 %
in last 13 years.
Further, Table 3.15 and Fig. 3.23 clearly show that growth of stock options in terms
of number of contracts traded has increased slightly from 2001-02 (1.04mn) to 2009 -
10 (14.02 mn) . Moreover the growth is almost constant from the year 2003-04 to
2006-07 (5.58 mn, 5.05 mn, 5.24 mn and 5.28mn) but the growth significantly
increased from the year 2009-10 to 2013-14. Similarly, Table 3.15 and Fig.3.24
25
1.6
3
10
01
.31
21
72
.07
16
88
.36
18
02
.53
19
37
.95
35
91
.37
22
92
.27
50
60
.65
10
30
3.4
4
97
70
.31
20
00
4.2
7
24
09
4.8
9
0.00
5000.00
10000.00
15000.00
20000.00
25000.00
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (
Rs
Bn
)
Year
Stock Options - Turnover
91
indicate that the growth of stock options in terms of turnover has increased
significantly in the beginning and later it has slightly increased from the year 2004-05
to 2008-09. Moreover the growth of stock options turnover has increased significantly
from the year 2009-10 to 2013-14. This statistics clearly revealed that investors are
not preferring and attracting stock options of NSE compared to other products of F&
O. Stock options of NSE has a huge scope of improvement in terms of volume and
turnover.
Table: 3.16 Business growth of Futures & Options at NSE
Year
Futures & Options
No of contracts Turnover Average Daily
Turnover
Volume
(Million)
Growth
(%)
Value
(Rs Billion)
Growth
(%)
Value
(Rs Billion)
2000-01 0.09 ---- 23.65 ---- 0.11
2001-02 4.20 4533.33 1019.26 4209.77 4.10
2002-03 16.77 299.56 4398.62 331.55 17.52
2003-04 56.89 239.24 21306.10 384.38 83.88
2004-05 77.02 35.39 25469.82 19.54 101.07
2005-06 157.62 104.65 48241.74 89.41 192.20
2006-07 216.88 37.60 73562.42 52.49 295.43
2007-08 425.01 95.96 130904.78 77.95 521.53
2008-09 657.39 54.68 110104.82 -15.89 453.11
2009-10 679.29 3.33 176636.65 60.43 723.92
2010-11 1034.21 52.25 292482.21 65.58 1151.50
2011-12 1205.05 16.52 313497.32 7.19 1259.03
2012-13 1131.47 -6.11 315330.04 0.58 1266.39
2013-14 1284.42 13.52 382114.08 21.18 1522.37
CAGR (%)
97.40
99.80 97.6
(Source: Retrieved & Adapted from www.nseindia.com)
92
Figure: 3.25 The historical business growth of both Futures & Options in terms
of number of contracts traded at NSE, India
(Source: Table: 3.16)
Figure: 3.26 The historical business growth of both Futures & Options in terms
of turnover at NSE, India
(Source: Table: 3.16)
0.0
9
4.2
0
16
.77
56
.89
77
.02
15
7.6
2
21
6.8
8
42
5.0
1
65
7.3
9
67
9.2
9
10
34
.21
12
05
.05
11
31
.47
12
84
.42
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Nu
mb
er
of
Co
ntr
acts
( M
n)
Year
Number of Contracts- F &O
23
.65
10
19
.26
43
98
.62
21
30
6.1
0
25
46
9.8
2
48
24
1.7
4
73
56
2.4
2
13
09
04
.78
11
01
04
.82
17
66
36
.65
29
24
82
.21
31
34
97
.32
31
53
30
.04
38
21
14
.08
0.00
100000.00
200000.00
300000.00
400000.00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (
Rs
Bn
)
Year
Turnover - F &O
93
Figure: 3.27 The historical business growth of both Futures & Options in terms
of daily turnover at NSE, India
(Source: Table: 3.16)
NSE, commenced trading of derivatives on June 2000 by introducing index futures.
Over a period of time NSE introduced many more indices on options and futures.
Currently (as of march 2015) there are nine major indices including 3 global are
available for trading at NSE.
Table 3.16 presents that the growth of F& O at NSE in terms of number of contracts
traded and turnover from 2000 -01 to 2013 -14. The size of the F&O at NSE in terms
of number of contracts traded has tremendously increased from 0.09 million in 2000-
01 to1284.42 million in 2013-14. Similarly, F&O turnover at NSE has significantly
increased from 23.65 Rs Billion in 2000-01 to 382114.08 Rs Billion in 2013- 14.
Additionally, the size of the F & O at NSE in terms of number of contracts traded
witnessed a highest CAGR (Compounded Annual Growth Rate) of 97.40 % in the last
14 years. Similarly, the F&O turnover at NSE witnessed a highest CAGR of 90.80 %
in last 14 years.
Further, Table 3.16 and Fig .3.25 clearly show that growth of F & O in terms of
number of contracts traded has increased continuously from 2000-01 to 2013-14
excluding in the year 2012-13 due to global financial. Similarly, Table 3.16 and
Fig.3.26 indicate that the growth of F& O in terms of turnover has tremendously
increased continuously year after year from 2001-02 to 2013-14. Moreover, the
growth of F&O in terms of volume and turnover is declined in the years 2011-12 to
2013-14 compared to previous years.
0.1
1
4.1
0
17
.52
83
.88
10
1.0
7
19
2.2
0
29
5.4
3
52
1.5
3
45
3.1
1
72
3.9
2
11
51
.50
12
59
.03
12
66
.39
15
22
.37
0.00
200.00
400.00
600.00
800.00
1000.00
1200.00
1400.00
1600.00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Ave
rage
Dai
ly T
urn
ove
r (
Rs
Bn
)
Year
Average Daily Turnover - F &O
94
Additionally Table 3.16 and Fig.3.27 clearly show the average daily turnover of
overall F&O at NSE from 2000-01 to 2013-14. The overall average daily turnover of
F& O at NSE has significantly increased from 0.11 Rs Billion in 2000-01 to 1522.37
Rs Billion in 2013-14. The size of the F & O at NSE in terms of turnover witnessed a
highest CAGR (Compounded Annual Growth Rate) of 97.6 % in the last 14 years.
Figure: 3.28 Product-wise distribution of turnover of F&O segment of NSE
(Source: Retrieved & Adapted from www.nseindia.com)
Fig.3.28 shows product wise turnover of derivative (Futures and Options) segment in
the NSE from 2000-01 to 2013-14. Fig.3.28 clearly indicates that in the year 2000-
01, index futures alone contributed 100% turnover because it was the only product
available for trading in F &O at NSE. Further Fig.3.28 shows that the following years
(2001-02 to 2007-09) stock futures dominated F & O segment followed by index
futures, index options and stock options respectively at NSE. However, from the year
2008-09 to 2013 -14 index options gradually occupied first slot by contributing
highest turnover in product wise distribution of turnover of F &O segment. The
turnover growth of index options has tremendously increased from 10% in the year
2007- 08 to 73% in the year 2013-14 followed by stock futures, index futures and
stock options.
10
0
21
10
26
30
31
35
29
32
22
15
11
8
8
51
65
61
58
58
52
58
32
29
19
13
13
13
4 2
2 5 7
11
10
34
45
63
72
72
73
25
23
10
7 4 3
3 2
3
4
3
6
6
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
% T
urn
ove
r
index futures stock Futures Index Options stock Options
95
Figure: 3.29 CAGR Analysis of F&O Segment of NSE
(Source: Retrieved & Adapted from www.nseindia.com)
The Fig 3.29 shows CAGR (Compound Annual Growth Rate) analysis of futures and
options (F & O) segment at NSE from the year 2000-01 to 2013-14. It’s clearly
indicating that index options witnessed phenomenal and highest growth rate (93.33%
and 98.39%) in terms of both number of contracts traded and turnover followed by
index futures, stock options and stock futures.
66
.55
41
93
.33
39
.71
66
.9
42
98
.39
49
.03
0
10
20
30
40
50
60
70
80
90
100
index futures stock futures Index options stock options
CA
GR
(%)
No of contracts Turnover
96
Table: 3.17 Business growth of equity segment at NSE
Year
No. of
Compa
nies
Listed
Market
Capitalizati
on
(Rs Billion)
Growth
(%)
Turnover
(Rs
Billion)
Growth
(%)
Avg.
Daily
Turnover
(Rs
Billion)
Growth
(%)
1994-95 135 3633.5 --- 18.05 --- 0.17 ---
1995-96 422 4014.59 10.49 672.87 3627.81 2.76 1523.53
1996-97 550 4193.67 4.46 2945.03 337.68 11.76 326.09
1997-98 612 4815.03 14.82 3701.93 25.70 15.2 29.25
1998-99 648 4911.75 2.01 4144.74 11.96 16.51 8.62
1999-
2000 720 10204.26 107.75 8390.52 102.44 33.03 100.06
2000-01 785 6578.47 -35.53 13395.1 59.65 53.37 61.58
2001-02 793 6368.61 -3.19 5131.67 -61.69 20.78 -61.06
2002-03 818 5371.33 -15.66 6179.89 20.43 24.62 18.48
2003-04 909 11209.76 108.70 10995.35 77.92 43.28 75.79
2004-05 970 15855.85 41.45 11400.71 3.69 45.06 4.11
2005-06 1,069 28132.01 77.42 15695.56 37.67 62.53 38.77
2006-07 1,228 33673.5 19.70 19452.85 23.94 78.12 24.93
2007-08 1,381 48581.22 44.27 35510.38 82.55 141.48 81.11
2008-09 1,432 28961.94 -40.38 27520.23 -22.50 113.25 -19.95
2009-10 1,470 60091.73 107.49 41380.24 50.36 169.59 49.75
2010-11 1,574 67026.16 11.54 35774.12 -13.55 140.48 -17.16
2011-12 1,646 60965.18 -9.04 28108.93 -21.43 112.89 -19.64
2012-13 1,666 62390.35 2.34 27082.79 -3.65 108.33 -4.03
2013-14 1695 64205.4 2.91 23429.96 -13.48 111.18 2.63
CAGR
(%) 1.15
1.43
1.38
(Source: Retrieved & Adapted from www.nseindia.com)
97
Figure: 3.30 The historical business growth of equity segment in terms of
turnover at NSE, India
(Source: Table: 3.17)
Table 3.17 and Fig.3.30 present equity segment turnover at NSE has tremendously
increased from Rs 18.05 Billion in 1994-95 to Rs Billion 23429.96 in 2013- 14.
Additionally, the size of the equity segment at NSE in terms of turnover witnessed a
high CAGR (Compounded Annual Growth Rate) of 43 % in last 20 years. Further,
Table 3.17 and Fig.3.30 clearly show that growth of equity turnover has increased
continuously from 1994-95 to 2000-01 excluding in the year 2001- 02 and 2008-09
due to global financial crisis. Finally, the growth of equity turnover is continuously
decreasing from 2009-10.
Figure: 3.31 The historical business growth of equity segment in terms of
average daily turnover at NSE, India
(Source: Table: 3.17)
18
.05
67
3
2,9
45
3,7
02
4,1
45
8,3
91
13
,39
5
5,1
32
6,1
80
10
,99
5
11
,40
1
15
,69
6
19
,45
3
35
,51
0
27
,52
0
41
,38
0 3
57
74
.12
28
10
8.9
3
27
08
2.7
9
23
42
9.9
6
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
19
94
-95
19
95
-96
19
96
-97
19
97
-98
19
98
-99
19
99
-20
00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (R
s B
n)
Year
NSE- Equity Turnover
0.1
7
2.7
6
11
.76
15
.2
17
33
53
21
25
43
45
63
78
14
1.4
8
11
3
17
0
14
0
11
3
10
8
11
1.1
8
0 25 50 75
100 125 150 175
19
94
-95
19
95
-96
19
96
-97
19
97
-98
19
98
-99
19
99
-20
00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Ave
rage
Dai
ly T
urn
ove
r( R
s B
illio
n)
Year
Average Daily Turnover
98
The Table 3.17 and Fig.3.31 clearly show the average daily turnover of equity
segment at NSE from 1994-95 to 2013-14. The average daily turnover of equity
segment at NSE has significantly increased from Rs 0.17 Billion in 1994-95 to Rs
111.18 Billion in 2013-14. The size of the equity segment at NSE in terms of average
daily turnover witnessed a CAGR (Compounded Annual Growth Rate) of 38 % in last
20 years. Fig.3.31 show that the growth of average daily turnover of equity segment is
in decreasing trend from 2009-10.
Figure: 3.32 The historical business growth of equity segment in terms of market
capitalization at NSE, India
(Source: Table: 3.17)
The Table 3.17 and Fig.3.32 present the market capitalization of equity segment at
NSE from 1994-95 to 2013-14. The market capitalization of equity segment at NSE
has significantly increased from Rs 3633.5 Billion in 1994-95 to Rs 64205.4 Billion
in 2013-14. The size of the equity segment at NSE in terms of market capitalization
witnessed a CAGR (Compounded Annual Growth Rate) of 15 % in last 20 years. Fig.
3.32 clearly shows that the growth of market capitalization is almost constant in the
initial years and continuously increased from 2001-03 to 2007-08. Then suddenly
decreased (40%) in the year 2008-09 due to global financial crisis. Market
capitalization of equity segment is in decreasing trend from 2009-10. Finally the
growth of market capitalization increased (107%) within one year and almost constant
from 2011-12 to 2013-14.
36
33
.5
4,0
15
4,1
94
4,8
15
4,9
12
10
,20
4
6,5
78
6,3
69
5,3
71
11
,21
0
15
,85
6
28
,13
2
33
,67
4
48
,58
1
28
,96
2 6
0,0
92
67
02
6.1
6
60
96
5.1
8
62
39
0.3
5
64
20
5.4
0
10000
20000
30000
40000
50000
60000
70000
19
94
-95
19
95
-96
19
96
-97
19
97
-98
19
98
-99
19
99
-20
00
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Mar
ket C
apit
aliz
atio
n (
Rs
Bill
ion
)
Year
Market Capitlizaion
99
Table: 3.18 Relative analysis of Equity and F&O turnover at NSE
Year Turnover Rs (Billion) Number of times F&O is
Bigger than Equity Equity F&O
2000-01 13,395 24 0.00
2001-02 5,132 1,019 0.20
2002-03 6,180 4,399 0.71
2003-04 10,995 21,306 1.94
2004-05 11,401 25,470 2.23
2005-06 15,696 48,242 3.07
2006-07 19,453 73,562 3.78
2007-08 35,510 1,30,905 3.69
2008-09 27,520 1,10,105 4.00
2009-10 41,380 1,76,637 4.27
2010-11 35,774 2,92,482 8.18
2011-12 28,109 3,13,497 11.15
2012-13 27,083 3,15,330 11.64
2013-14 23,430 3,82,114 16.31
(Source: Retrieved & Adapted from www.nseindia.com)
Figure: 3.33 Relative analysis of Equity and F&O turnover of NSE
(Source: Table: 3.18)
Table 3.18 & Fig.3.33 clearly show that comparison of equity and F&O turnover from
2001- 01 to 2013-14. Right from launching of derivatives in the year 2000-01 ,
turnover of F&O continuously increasing year after year remarkably. Fig.3.33 clearly
shows, how big the derivatives market in terms of turnover compared to equity
segment. The equity turnover is continuously decreasing from the year 2009-10,
whereas the growth of F&O is tremendously increasing right from its launching at
NSE. Table 3.18 shows that the size of F&O in terms of turnover surpassed the cash
market within three years of its launching at NSE. More importantly in the year 2013-
0 50,000
100,000 150,000 200,000 250,000 300,000 350,000 400,000
20
00
-01
20
01
-02
20
02
-03
20
03
-04
20
04
-05
20
05
-06
20
06
-07
20
07
-08
20
08
-09
20
09
-10
20
10
-11
20
11
-12
20
12
-13
20
13
-14
Turn
ove
r (R
s B
n)
Turnover of F&O and Equity
Equity F&O
100
14 the size of the F&O in terms of turnover is 16.31 times bigger than the cash
market.
3.4 Futures Pricing Models
The study considered three futures pricing models to predict futures prices. They are
(1) Cost of Carry Model (CCM) (2) Hemler and Longstaff Model (HLM) (3) Hsu and
Wang Model (HWM). The CCM incorporates risk-free interest rates and constant
dividend Yield and developed an assumption that capital markets are perfect and
arbitrage mechanism completes. HLM incorporates risk free interest rates and market
volatility and developed with an assumption of capital markets are perfect. The HWM
incorporates price expectation parameter and developed an assumption that capital
markets are imperfect. The detail discussions about these models are as follows.
1. Cost of Carry Model ( CCM)
Cornell and French (1983) derived CCM in perfect market based on following
assumptions.
1. Capital Markets are perfect – There are no taxes or transaction costs, there are
no restrictions on short sales and assets are perfectly divisible.
2. The risk –free borrowing and lending rates are equal and constant.
3. The underlying stock index pays a continuous constant dividend yield, q,
during the life of the futures contract
Ft = St e (r−q) (T−t),
Where Ft is the theoretical futures price at time t for a contract that matures at a time
T, St is the current stock price at time t; r is the annualized risk free interest rate (Cost
of financing); q is constant annual dividend yield, T-t represents time to maturity.
CCM was developed under the assumption of perfect market and no arbitrage
arguments. According to CCM, the futures prices will exceed the spot prices by the
cost of carry. The cost of carry equal to the cost of holding the underlying asset
(interest forgone) less the benefit (cash dividend received). Suppose if any deviation
of actual futures price from its theoretical ‘Fair Price’ estimated by CCM then
arbitragers use an opportunity and earn riskless profit by simultaneously buying in
one market at low price and selling in another market at high price. Arbitrager’s
101
actions will continue till this price deviation will be adjusted back to equilibrium
simultaneously and risk less profitable arbitrage opportunity will be eliminated.
Cost of carry Model and arbitrage Mechanism.
CCM is based on familiar ‘Cost of Carry’ principle. It argues that, the cost of carry for
a dividend paying stock is equal to the difference between interest rate and dividend
yield. In a perfect Market, the futures price for a dividend paying stock must equal to
the deferred value of the current stock price. In case, if any violations from equality, it
leads an arbitrage opportunity for an investor to earn riskless profit.
An investor earns arbitrage profit by undertaking two kinds of trades.
A. Trade 1- Ft > St e (r-q)T
Suppose, futures price at a time t greater than the cost of purchasing the stock less the
dividend and carrying till maturity of the futures contract, Investor can earn riskless
profit by Short the futures and buy the Underlying stock. The transaction as follows
i. Borrow St rupees at risk free interest rate of r and purchase one unit of
underlying stock.
ii. Short one futures contract
The total payoff an investor gets at maturity period T equals to the difference
between a futures price and underlying stock price with interest less the dividend
for T-t period
Total Payoff = Ft - St e (r-q) T
B. Trade 2- St e (r-q)T > Ft
Suppose Futures price at a time t lesser than the cost of purchasing the stock (r-q) and
carrying till maturity of the futures contract, Investor can earn riskless profit by Short
the underlying stock and invest the same at the risk free rate of interest ( r) and buy
one futures contract. The transaction as follows
i. Short the underlying stock and invest the same at the risk free rate of interest
(r).
ii. Long one futures contract
The total payoff of an investor gets at maturity period T equals to the difference
between the underlying stock price with interest for T-t period and a futures price
102
Total Payoff = St e (r-q)T - Ft.
Finally perfect markets are fair and competitive and do not allow an investor to make
risk free profits. When trading occurs, there is a possibility of deviation of actual
futures price from theoretical futures price estimated by CCM. The arbitrageurs step
in to take advantage of this deviation by buying from the market at cheaper price and
selling in the market at higher price. Their actions quickly narrow the prices and
thereby minimizing the imperfections. By this way derivative futures reduce the
market inefficiencies by providing a self-correcting mechanism.
2. Hemler and Longstaff Model
In determining stock index futures prices. Nevertheless, stock market volatility is
excluded from the CCM and states that Market volatility should not have explanatory
power for futures prices.
Motivated by these considerations Michael L. Hemler and Francis A. Longstaff
(1991) followed the CIR (Cox et al., 1985a,b) framework and developed a closed
form general equilibrium model of stock index futures prices in a continuous
economy with risk free interest rate and market volatility. The implications of this
general equilibrium model for stock index futures prices are generally quite different
from those of the CCM and are testable using regression analysis. When the natural
logarithm of the dividend adjusted futures to spot price ratio can be represented as
linear function of two variables, the risk free interest rate and the market volatility,
they find that market volatility has significant explanatory power. These results are
consistent with the general equilibrium model, but not the cost of carry model. The
regression equation is
Lt = α+β1 rt+ β2 vt +εt
Where Lt = ln (Fteqτ /St ) is the logarithm of the dividend adjusted futures / Spot price
ratio,
Ft is the theoretical Futures price, St is the underlying spot index, τ is the time to
maturity ( T-t) , rt is the Risk free interest rate, Vt is the market volatility , α,β1& β2
are the regression coefficients. ε is the error part assumed to be normally distributed
with mean zero.
103
The empirical testing of HLM involves two stage procedures. One , it is assumed that
theoretical futures price is derived from HLM is differed from actual or observed
futures prices by a mean of zero . Hence the regression coefficients of α, β1 & β2 can
be obtained. Second stage involves substituting the estimated α, β1 & β2 to the HLM
to generate the estimate of the dividend adjusted futures / Spot price ratio Lt . Finally
the theoretical futures price (Ft) can obtain by inferring Lt.
Similarly, the natural logarithm of the CCM forward price can be represented as a
linear regression equation. In contrast to the equilibrium model, the CCM implies that
the logarithm of the dividend adjusted futures / spot price ratio depends on the risk-
free rate only and the market volatility should not have explanatory power for Lt i.e
β2= 0 . Finally the CCM implies that the interest rate coefficients (β1) should be
equivalent to the average contract maturity in years i.e β1= T-t .From the discussion it
clearly indicates that the CCM can be nested within the equilibrium regression model
(1), thus restrictions imposed by the CCM can be tested within same framework by
substituting α = 0, β1= T-t and β2= 0, then HLM equation reduces to Lt = rtτ
3. Hsu & Wang Model
Hsu & Wang (2004) incorporated price expectation parameter (uα) and developed
futures pricing model in imperfect market.
This study uses the following assumptions to develop a futures pricing model of stock
index futures in imperfect markets: (1) the underlying stock index pays a continuous
constant dividend yield, q, during the life of the futures contract. (2) The
instantaneous DOMI remains constant throughout the life of the futures contract. (3)
The underlying stock index price, S, follows a geometric Wiener process, as follows:
HWM considered a hedged portfolio that comprises one unit of spot index and x units
of index futures. The model assumes that initially cash outflow is not required for the
futures contract. Then the rate of return of the hedged portfolio is illustrated by
(wf uf + u ) dt + (wf σf +σ ) dZ (14)
Where P is the hedged portfolio, wf =
, S represents the price of the underlying
stock index , F denotes the price of the index futures, U & σ represents constant
expected growth rate and constant volatility of the underlying stock index (S)
respectively. uf & σf denotes the instantaneous expected return on futures and
104
instantaneous standard deviation of return on futures respectively and dz is a
geometric wiener process.
Further, If Wf = -
then wf σf +σ =0. uf & u remain same but second part in
equation (14) become zero. It indicates that, the hedged portfolio (P) can be expected
certainly and hedged portfolio becomes riskless. However, in order to keep this
portfolio risk free, it is necessary to rebalance wf continuously until expiration of the
futures contract. Figlewski (1989) found that, forming riskless portfolio hedge and
continuously rebalancing hedged positions is only possible in perfect markets.
Because of incomplete arbitrage mechanism and arbitrage process are exposed to
heavy risk, the hedged portfolio is not possible to riskless at any point of time.
Let up & σp represents the instantaneous expected rate of return of the hedged portfolio
(P) & the coefficient of winear process dz in the equation (14) respectively. This can
be obtained as follows.
wf uf+ u = up (15)
wf σf + σ= σp (16)
From equation (15) & (16) the result of partial differential equation can be obtained as
follows
σ2 S2Fss + uα SFs + Ft = 0 (17)
Where uα is the Hsu & Wang’s price expectation parameter uα = [ up-q) – (u-q)
] / (
1-
)
The second order partial differential equation (17) along with the following index
futures price terminal condition at expiry date (T), fully characterizes the index
futures price.
F(S, T) = St
Finally the solution of Partial Differential Equation is given by
F (S, T) = St euα(T-t)
Degree of market imperfection (DOMI)
Hsu & Wang also proposes the concept of DOMI for imperfect markets and its
valuation model. Using the argument of completion of arbitrage argument for perfect
markets & PDE technology. Hsu & Wang also derived the second order partial
105
differential equation for stock index futures prices in perfect markets, given by as
follows
σ2 S2Fss + (r-q) SFs + Ft = 0 (18)
Hsu and Wang compare PDE (17) for imperfect markets & PDE (18) for perfect
markets. As discusses earlier, in perfect markets arbitrage mechanism works
completely. Whenever the arbitrage mechanism completes, the portfolio comprises
underlying stocks & stock futures becomes perfectly hedged portfolio and portfolio
becomes riskless, thus σp =0 . If σp =0, then the price expectation parameter uα = [ up-
q) – (u-q)
] / ( 1-
) equals to (r-q).
[If σp =0, then σ
σ also equals to zero, as
σ
σ = 0, then (1-
σ
σ equals to 1]
PDE (17) for imperfect markets now is identical to PDE ( 18) for perfect markets,
thus it indicates that , whenever the capital market is perfect and arbitrage mechanism
works completely , the PDE of futures pricing model for stock index in imperfect
markets is similar to the PDE for standard CCM in perfect markets. Conversely
whenever the capital markets are imperfect and the arbitrage mechanism is not able to
complete, then the arbitrage process is exposes to large risk, thus the hedged portfolio
is not possible to continuously riskless and σp > 0, then, σ
σ also greater than zero and
PDE (17) & PDE (18) are not identical. Thus, Hsu & Wang concludes ‘ σ
σ ‘as the
degree of market imperfection.
3.5 Operational definitions
Perfect Market
Cornell and French (1983) explained perfect market is the one in which
i. There are no taxes
ii. No trading costs or transaction costs
iii. No constraints on short sales- short selling process involves selling the
security at higher price and buying back the same security at lower price.
In short selling investors can sell the security even does not own or he gas
borrowed. There is no constrains on a security even its price declines any
parentage in a day.
iv. Securities are perfectly divisible – it is possible to buy fractional shares.
v. It’s possible to borrow and lend at the same risk free interest rate
vi. traders may have homogeneous or symmetric information
106
If any new information disseminating in to the market which interpreted
and traded by both futures and cash market investors immediately and
simultaneously as a result there will be no lagged responses and arbitrage
opportunities.
Imperfect Market or Market Imperfection
Hsu and Wang (2004) explained market imperfection or imperfect market is the one
which involves
i. Transaction Costs including brokerage commission, bid &ask spread,
ii. Taxes including service tax on brokerage, stamp duty, security transaction
tax
iii. There are constraints on short sales –. Restrictions on short sales means. If
any of the security declines more than a particular percentage in a day ,
the circuit breaker would be triggered and prevented from further trading
of that security in that day.
iv. Securities are not perfectly divisible or indivisible - preventing investors
from buying or selling exact quantity of securities.
v. It’s not possible to borrow and lend at the same risk free interest rate.
vi. Traders may have heterogeneous or asymmetric information.
Under-price (Premium) - The actual futures price is lower than the theoretical price
estimated by the pricing model.
Overprice (Discount) - The actual price is higher than the theoretical price estimated
by the pricing model.
Lead- Lag relationship - Lead - lag relationship basically determines which of the
two markets (Underlying and Futures market) reacts most quickly to new information
thus leading it.