Impact of the Introduction of Futures Market

8/7/2019 Impact of the Introduction of Futures Market

1/55

Impact of Introduction of Futures Index on the Spot Market: An Empirical Study

M.P. Birla Institute of Management . 1

A Research ReportOn

Impact of the Introduction of Futures MarketOn the Spot Market: An Empirical Study

Submitted in partial fulfillment of requirement for the award of thedegree of

Master of Business AdministrationOf

Bangalore UniversityBy

VINAY.R

Reg. No: 05XQCM6114

Under the Guidance and Supervision

OfProf.S.SANTHANAM

M.P.BIRLA INSTITUTE OF MANAGEMENTAssociate Bharathiya Vidya Bhavan

#43, Race Course Road, BANGALORE-560001


2/55



Declaration

I hereby declare, that this project report titled Impact of the

Introduction of Futures Market on the Spot Market , has been

successfully completed under the guidance of Prof.S.Santhanam , Project

Guide, M P Birla Institute of Management in partial fulfillment of Masters inBusiness Administration degree at Bangalore University.

I further declare that this project report is the result of my own

efforts and that it has not been submitted to any other university for the

award of a degree or does not form the basis of any degree or diploma of

other similar title of recognition in any other university.

Place: Bangalore Vinay.R

Date: (Reg. No. 05XQCM6114)


3/55


4/55



Principals Certificate

This to certify that this report entitledImpact of the Introduction ofFutures Market on the Spot Market has been prepared byMr.Vinay.R bearing Reg.No.05XQCM6114 of M P Birla Institute ofManagement in partial fulfillment of the award of the degree,Masterof Business Administration at Bangalore University , under theguidance and supervision ofProf.S.Santhanam , MPBIM , Bangalore.This report or a similar report on this topic has not been submitted forany other examination and does not form a part of any other courseundergone by Mr.Vinay.R

Place: Bangalore (Dr. N S Malavalli)Date: Principal


5/55



ACKNOWLEDGMENT

I sincerely thank Dr.Nagesh.S.Malavalli (Principal), M.P.Birla Institute of

Management, Bangalore for granting me the permission to do this Research

Project.

I extend my gratitude to Prof. T.V.N.Rao, and also Prof S.Santhanam,

professor, MPBIM who kindly spared their valuable time giving information

without which this report would have been incomplete.

I extend my deep sense of gratitude to my parents who have encouraged and

helped me to complete this project successfully.

I would like to extend my thanks to all my friends & the unseen hands that

have made this project possible.

Place: Bangalore Vinay.R

Date : ( Reg. No. 05XQCM6114)


6/55



TABLE OF CONTENTS

CHAPTERS PARTICULARS PAGE NO.

ABSTARCT 1

1. INTRODUCTION & THEORICALBACKGROUND

2 -18

2. LITERATURE REVIEW 19

2.1 Theoretical consideration 20-22

2.2 Survey of empirical literature 22-31

3 RESEARCH METHODOLOGY 32

3.1 Research problem statement 33

3.2 Methodology 33-36

3.3 Software packages used 37

4 DATA ANALYSIS ANDINTERPRETATION

38

4.1 Empirical Results 39-46

5. CONCLUSION 48

BIBLIOGRAPHY 49


7/55



ABSTRACT:

Among all the innovations that have flooded the international financial markets,

financial derivatives occupy the driver's seat. Derivatives are financial instruments whose

values depend on the values of underlying assets.

Index Futures were introduced in the Indian stock markets in the year 2000 . There has

been considerable increase in the volumes of trading in these derivative instruments since

then. Volatility is the most important input in the pricing of an option. For a sophisticated

trader, a future trading is volatility trading and the trader who can forecast volatility the

best is the most successful trader.

The objective of the study is to find out whether the introduction of Index futures has any

impact on the volatility of the Spot market. This is done by considering the before

introduction closing prices of index and after introduction closing prices of index. The

prices are tested for stationarity and volatility is calculated. Using the simple standard

deviation model the volatilities are calculated. F-test is used for find whether they are

significant or not.

Specifically, it is found that new information is assimilated into prices more rapidly than

before, and there is a decline in the persistence of volatility since the onset of futures

trading. These results for NSE Nifty are obtained even after accounting for world market

movements, asymmetric effects and sub-period analysis, and, contrasting the same with a

control index. Thus it is concluded that such a change in the volatility structure appears to

be the result of futures trading, which has expanded the routes over which information

can be conveyed to the market.

The findings of the study are the index returns are stationary series and average variation

seems to reduce statistically. It is showing a significant difference for the period June

1995 to May 2005. Market volatility has not decreased or increased but it remains

fluctuating day in and day out.


8/55



INTRODUCTION


9/55



Introduction

It has been said in the past that derivatives are a kind of a sideshow; where the main event

takes place in the money and capital markets. One could attend the sideshow without

taking part in the main event an vice versa. With respect to derivative and money/capital

markets, that is simply not true today. Derivatives are so widely used that even if one has

no intention of using them, it is important to understand how they are used by others and

what effects, positive and negative, they could have on money and capital markets.

Without financial futures, investors would have only one trading location to alterportfolio positions when they get new information that is expected to influence either

value of assets the cash market. The futures market is an alternative market that

investors can use to alter their risk exposure to an asset when new information is

acquired. Futures trading is widely used by advanced investors and fund managers to

hedge their portfolios.

With the introduction of index futures contracts on two of the existing Indian Stock

Exchanges, BSE and NSE, in June 2000, questions regarding the impact of the

introduction of Futures Market on Financial Markets have been up most in the minds of

the analysts and investors.


10/55



Derivatives

Derivative is a product whose value is derived from the value of one or more basic

variables, called bases i.e. underlying asset, index, or reference rate, in a contractual

manner. The underlying asset can be equity, forex, commodity or any other asset.

Derivatives are used by :

1. Hedgers :

For protecting against adverse movement. Hedging is a mechanism to

reduce price risk inherent in open positions. Derivatives are widely used for hedging. A

Hedge can help lock in existing profits. Its purpose is to reduce the volatility of a

portfolio, by reducing the risk.

2. Speculators :

To make quick fortune by anticipating/forecasting future market

movements. Hedgers wish to eliminate or reduce the price risk to which they are alreadyexposed. Speculators, on the other hand are those class of investors who willingly take

price risks to profit from price changes in the underlying. While the need to provide

hedging avenues by means of derivative instruments is laudable, it calls for the existence

of speculative traders to play the role of counter-party to the hedgers. It is for this reason

that the role of speculators gains prominence in a derivatives market.

3. Arbitrageurs :

To earn risk-free profits by exploiting market imperfections.

Arbitrageurs profit from price differential existing in two markets by simultaneously

operating in the two different markets.


11/55



Functions

1. Prices in an organized derivatives market reflect the perception of market

participants about the future and lead the prices of underlying to the perceivedfuture level. The prices of derivatives converge with the prices of the underlying

at the expiration of the derivative contract. Thus derivatives help in discovery of

future as well as current prices.

2. The derivatives market helps to transfer risks from those who have them but maynot like them to those who have an appetite for them.

3. Derivatives, due to their inherent nature, are linked to the underlying cashmarkets. With the introduction of derivatives, the underlying market witnesses

higher trading volumes because of participation by more players who would not

otherwise participate for lack of an arrangement to transfer risk.

4. Speculative trades shift to a more controlled environment of derivatives market.In the absence of an organized derivatives market, speculators trade in the

underlying cash markets. Margining, monitoring and surveillance of the activities

of various participants become extremely difficult in these kind of mixed markets.

5. Derivative acts as a catalyst for new entrepreneurial activity i.e. it has a history of

attracting many bright, creative, well-educated people with an entrepreneurialattitude. They often energize others to create new businesses, new products and

new employment opportunities, the benefit of which are immense.

6. Derivatives markets help increase savings and investment in the long run.Transfer of risk enables market participants to expand their volume of activity.

Types of Derivatives

Derivatives are basically classified into two based upon the

mechanism that is used to trade on them.

1. Over the Counter derivatives

2. Exchange traded derivatives


12/55



The OTC derivatives are between two private parties and are designed to suit the

requirements of the parties concerned.

The Exchange traded ones are standardized ones where the exchange sets the standards

for trading by providing the contract specifications and the clearing corporation provides

the trade guarantee and the settlement activities.

Exchange-traded vs. OTC derivatives markets

The OTC derivatives markets have witnessed rather sharp growth over the last few years,

which have accompanied the modernization of commercial and investment banking andglobalization of financial activities. The recent developments in information technology

have contributed to a great extent to these developments. While both exchange-traded

and OTC derivative contracts offer many benefits, the former have rigid structures

compared to the latter. It has been widely discussed that the highly leveraged institutions

and their OTC derivative positions were the main cause of turbulence in financial

markets in 1998. These episodes of turbulence revealed the risks posed to market stability

originating in features of OTC derivative instruments and markets. The OTC derivatives

markets have the following features compared to exchange-traded derivatives:

1. The management of counter-party (credit) risk is decentralized and located within

individual institutions,

2. There are no formal centralized limits on individual positions, leverage, or margining,

3. There are no formal rules for risk and burden-sharing,

4. There are no formal rules or mechanisms for ensuring market stability and integrity,

and for safeguarding the collective interests of market participants, and

5. The OTC contracts are generally not regulated by a regulatory authority and theexchanges self regulatory organization, although they are affected indirectly by

national legal systems, banking supervision and market surveillance.


13/55



Some of the features of OTC derivatives markets embody risks to

financial market stability. The following features of OTC derivatives markets can give

rise to instability in institutions, markets, and the international financial system:

(i) the dynamic nature of gross credit exposures;(ii) information asymmetries;(iii) the effects of OTC derivative activities on available aggregate credit;

(iv) the high concentration of OTC derivative activities in major institutions; and(v) the central role of OTC derivatives markets in the global financial system.

Instability arises when shocks, such as counter-party credit events and sharp

movements in asset prices that underlie derivative contracts occur, which significantly

alter the perceptions of current and potential future credit exposures. When asset prices

change rapidly, the size and configuration of counter-party exposures can becomeunsustainably large and provoke a rapid unwinding of positions. There has been some

progress in addressing these risks and perceptions. However, the progress has been

limited in implementing reforms in risk management, including counterparty, liquidity

and operational risks, and OTC derivatives markets continue to pose a threat to

international financial stability. The problem is more acute as heavy reliance on OTC

derivatives creates the possibility of systemic financial events, which fall outside the

more formal clearing house structures. Moreover, those who provide OTC derivative

products, hedge their risks through the use of exchange traded derivatives. In view of the

inherent risks associated with OTC derivatives, and their dependence on exchange traded

derivatives, Indian law considers them illegal.

Classification of Derivatives -

The financial Derivatives Products can be classified as 1. Forward2. Futures3. Option4. SWAP


14/55



Forward

A forward contract is an agreement to buy or sell an asset on a specified date for a

specified price. One of the parties to the contract assumes a long position and agrees to

buy the underlying asset on a certain specified future date for a certain specified price.The other party assumes a short position and agrees to sell the asset on the same date for

the same price. Other contract details like delivery date, price and quantity are negotiated

bilaterally by the parties to the contract. The forward contracts are normally traded

outside the exchanges.

The salient features of forward contracts are as follows -

1. They are bilateral contracts and hence exposed to counterparty risk.2. Each contract is custom designed, and hence is unique in terms of contract size,

expiration date and the asset type and quality.

3. The contract price is generally not available in public domain.4. On the expiration date, the contract has to be settled by delivery of the asset.5. If the party wishes to reverse the contract, it has to compulsorily go to the same

counterparty, which often results in high prices being charged.

However forward contracts in certain markets have become very standardized,

as in the case of foreign exchange, thereby reducing transaction costs and increasing

transactions volume. This process of standardization reaches its limit in the organized

futures market.

Forward contracts are very useful in hedging and speculation. The classic

hedging application would be that of an exporter who expects to receive payment in

dollars three months later. He is exposed to the risk of exchange rate fluctuations. By

using the currency forward market to sell dollars forward, he can lock on to a rate today

and reduce his uncertainty. Similarly an importer who is required to make a payment in

dollars two months hence can reduce his exposure to exchange rate fluctuations by

buying dollars forward.


15/55



If a speculator has information or analysis, which forecasts an upturn in a price, then he

can go long on the forward market instead of the cash market. The speculator would go

long on the forward, wait for the price to rise, and then take a reversing transaction to

book profits. Speculators may well be required to deposit a margin upfront. However, this

is generally a relatively small proportion of the value of the assets underlying the forward

contract. The use of forward markets here supplies leverage to the speculator.

Limitations of forward contract

Lack of centralization of trading,

Illiquidity, and

Counterparty risk

Futures

A futures contract is an agreement between two parties to buy or sell an asset at a

certain time in the future at a certain price. Futures contracts are special types of forward

contracts in the sense that the former are standardized exchange-traded contracts. These

contracts are traded on exchanges. In a nutshell futures markets are the extension of the

forward contracts. These markets being organized/standardized are very liquid by theirown nature. Therefore, liquidity problem, which persists in the forward market, does not

exist in the futures market. In these markets, clearing corporation/house becomes the

counter-party to all the trades or provides the unconditional guarantee for the settlement

of trades i.e.: assumes the financial integrity of the whole system. In other words, we

may say that the credit risk of the transactions is eliminated by the exchange through the

clearing corporation/house.

The standardized items in a futures contract are:

1. Quantity of the underlying2. Quality of the underlying3. The date and the month of delivery4. The units of price quotation and minimum price change5. Location of settlement


16/55



Distinction between futures and forwards

Futures Forwards

1. Trade on an organized exchange 1. OTC in nature

2. Standardized contract terms 2. Customized contract termshence more liquid hence less liquid

3. Requires margin payments 3. No margin payment4. Follows daily settlement 4. Settlement happens at end of period

Forward contracts are often confused with futures contracts. The confusion

is primarily because both serve essentially the same economic functions of allocating risk

in the presence of future price uncertainty. However futures are a significantimprovement over the forward contracts as they eliminate counterparty risk and offer

more liquidity. Table 3.1 lists the distinction between the two.

Futures terminology

Spot price : The price at which an asset trades in the spot market.

Futures price : The price at which the futures contract trades in the futures market.

Contract cycle : The period over which a contract trades. The index futures

contracts on the NSE have one-month, two-months and three-month expiry cycles

which expire on the last thursday of the month. Thus a January expiration contract

expires on the last Thursday of January and a February expiration contract ceases

trading on the last Thursday of February. On the Friday following the last

Thursday, a new contract having a three-month expiry is introduced for trading.

Expiry date : It is the date specified in the futures contract. This is the last day on

which the contract will be traded, at the end of which it will cease to exist.


17/55



Contract size : The amount of asset that has to be delivered under one contract.

For instance, the contract size on NSEs futures market is 200 Nifties.

Basis : In the context of financial futures, basis can be defined as the futures price

minus the spot price. There will be a different basis for each delivery month for

each contract. In a normal market, basis will be positive. This reflects that futures

prices normally exceed spot prices.

Cost of carry : The relationship between futures prices and spot prices can be

summarized in terms of what is known as the cost of carry. This measures the

storage cost plus the interest that is paid to finance the asset less the income

earned on the asset.

Initial margin : The amount that must be deposited in the margin account at the

time a futures contracts first entered into is known as initial margin.

Marking-to-market : In the futures market, at the end of each trading day, the

margin account is adjusted to reflect the investors gain or loss depending upon

the futures closing price. This is called markingtomarket.

Maintenance margin : This is somewhat lower than the initial margin. This is set

to ensure that the balance in the margin account never becomes negative. If the

balance in the margin account falls below the maintenance margin, the investor

receives a margin call and is expected to top up the margin account to the initial

margin level before trading commences on the next day.


18/55



Option

An option is a contract, which gives the buyer (holder) the right, but not the obligation,

to buy or sell specified quantity of the underlying assets, at a specific price on or before a

specified time. The underlying may be physical commodities like wheat/ rice/ cotton/ gold/ oil etc. or financial instruments like equity stocks/ stock index/ bonds etc.

Option terminology

Index options : These options have the index as the underlying. Some options are

European while others are American. Like index futures contracts, index optionscontracts are also cash settled.

Stock options : Stock options are options on individual stocks. Options currently trade on

over 500 stocks in the United States. A contract gives the holder the right to buy or sell

shares at the specified price.

Buyer of an option : The buyer of an option is the one who by paying the option

premium buys the right but not the obligation to exercise his option on the seller/writer.

Writer of an option : The writer of a call/put option is the one who receives the option

premium and is thereby obliged to sell/buy the asset if the buyer exercises on him. There

are two basic types of options, call options and put options.

Call Option - A call option gives the holder (buyer/ one who is long call), the right to

buy specified quantity of the underlying asset at a specified price on or before a specified

time. The seller (one who is short call) however, has the obligation to sell the underlying

asset if the buyer of the call option decides to exercise his option to buy.


19/55



Put Option A Put option gives the holder (buyer/ one who is long Put), the right to sell

specified quantity of the underlying asset at a specified price on or before a specified

time. The seller (one who is short put) however, has the obligation to buy the underlying

asset if the buyer of the put option decides to exercise his opti on to sell.

Option price : Option price is the price which the option buyer pays to the option seller. It

is also referred to as the option premium.

_ Expiration date : The date specified in the options contract is known as the expiration

date, the exercise date, the strike date or the maturity.

Strike price : The price specified in the options contract is known as the strike price or theexercise price.

American options : American options are options that can be exercised at any time upto

the expiration date. Most exchange-traded options are American.

_ European options : European options are options that can be exercised only on the

expiration date itself. European options are easier to analyze than American options, and

properties of an American option are frequently deduced from those of its European

counterpart.

In-the-money option : An in-the-money (ITM) option is an option that would lead to a

positive cashflow to the holder if it were exercised immediately. A call option on the

index is said to be in-the-money when the current index stands at a level higher than the

strike price (i.e. spot price _ strike price). If the index is much higher than the strike price,

the call is said to be deep ITM. In the case of a put, the put is ITM if the index is below

the strike price.


20/55



At-the-money option : An at-the-money (ATM) option is an option that would lead to

zero cashflow if it were exercised immediately. An option on the index is at-the-money

when the current index equals the strike price (i.e. spot price = strike price).

Out-of-the-money option : An out-of-the-money (OTM) option is an option that would

lead to a negative cashflow it was exercised immediately. A call option on the index is

out-of-the-money when the current index stands at a level which is less than the strike

price (i.e. spot price _strike price). If the index is much lower than the strike price, the call

is said to be deep OTM. In the case of a put, the put is OTM if the index is above the

strike price.

Distinction between futures and options

Futures Options

1. Exchange traded, with novation 1. Same as futures.2. Exchange defines the product 2. Same as futures.3. Price is zero, strike price moves 3. Strike price is fixed, price moves.4. Price is zero 4. Price is always positive.

5. Linear payoff 5. Nonlinear payoff.6. Both long and short at risk 6. Only short at risk.

SWAP Swap can be defined as "A financial transaction in which two counterparties agree to

exchange streams of payments, or cash flows, over time". Generally, two types of swaps

are generally seen i.e. interest rate swaps and currency swaps. A swap results in reducing

the borrowing cost of both parties. The two major types of swaps are as follows-


21/55



1. Interest Rate Swap

These entail swapping only the interest related cash flows between the

parties in the same currency . There are two main types:

Coupons swaps : fixed for floating rates

Basic swaps : the exchange of one bench-mark for another under floating rates

2. Currency swap

These entail swapping both principal and interest between the

parties, with the cash flows in one direction being in a different currency than those in the

opposite direction. The exchange rate used is the ruling spot rate between the two

currencies. A currency swap can also be considered as a series of forward contracts. Even

a currency swap can be combined with an interest rate swap; in that case, the dollar

outflows would carry LIBOR-based interest rate. As weaker counter parties would not be

able to get swap quotes for a longer maturity.

Introduction to derivatives market

Early forward contracts in the US addressed merchants concerns about ensuring that

there were buyers and sellers for commodities. However credit risk remained a serious

problem. To deal with this problem, a group of Chicago businessmen formed the

Chicago Board of Trade (CBOT) in 1848. The primary intention of the CBOT was to

provide a centralized location known in advance for buyers and sellers to negotiate

forward contracts. In 1865, the CBOT went one step further and listed the first exchange

traded derivatives contract in the US, these contracts were called futures contracts. In

1919, Chicago Butter and Egg Board, a spin-off of CBOT, was reorganized to allow

futures trading. Its name was changed to Chicago Mercantile Exchange (CME). TheCBOT and the CME remain the two largest organized futures exchanges, indeed the two

largest financial exchanges of any kind in the world today. The first stock index futures

contract was traded at Kansas City Board of Trade . Currently the most popular stock

index futures contract in the world is based on S&P 500 index, traded on Chicago


22/55



Mercantile Exchange. During the mid eighties, financial futures became the most active

derivative instruments generating volumes many times more than the commodity futures.

Index futures, futures on T-bills and Euro-Dollar futures are the three most popular

futures contracts traded today. Other popular international exchanges that trade

derivatives are LIFFE in England, DTB in Germany, SGX in Singapore, TIFFE in Japan,

MATIF in France, Eurex etc.

Development of exchange-traded derivatives

Derivatives have probably been around for as long as people have been trading with one

another. Forward contracting dates back at least to the 12th century, and may well have

been around before then. Merchants entered into contracts with one another for future

delivery of specified amount of commodities at specified price. A primary motivation for

pre-arranging a buyer or seller for a stock of commodities in early forward contracts was

to lessen the possibility that large swings would inhibit marketing the commodity after a

harvest. The following factors have been driving the growth of financial derivatives:

1. Increased volatility in asset prices in financial markets,

2. Increased integration of national financial markets with the international markets,

3. Marked improvement in communication facilities and sharp decline in their costs,

4. Development of more sophisticated risk management tools, providing economic agents

a wider choice of risk management strategies, and

5. Innovations in the derivatives markets, which optimally combine the risks and returns

over a large number of financial assets leading to higher returns, reduced risk as well

as transactions costs as compared to individual financial assets.


23/55



Derivatives market in India

Approval for derivatives trading

The first step towards introduction of derivatives trading in India was the promulgation of

the Securities Laws (Amendment) Ordinance, 1995, which withdrew the prohibition on

options in securities. The market for derivatives, however, did not take off, as there was

no regulatory framework to govern trading of derivatives. SEBI set up a 24member

committee under the Chairmanship of Dr.L.C.Gupta on November 18, 1996 to develop

appropriate regulatory framework for derivatives trading in India. The committee

submitted its report on March 17, 1998 prescribing necessary preconditions for

introduction of derivatives trading in India. The committee recommended that derivativesshould be declared as securities so that regulatory framework applicable to trading of

securities could also govern trading of securities. SEBI also set up a group in June 1998

under the Chairmanship of Prof..J.R.Varma, to recommend measures for risk

containment in derivatives market in India. The report, which was submitted in October

1998, worked out the operational details of margining system, methodology for charging

initial margins, broker net worth, deposit requirement and realtime monitoring

requirements. The SCRA was amended in December 1999 to include derivatives within

the ambit of securities and the regulatory framework was developed for governing

derivatives trading. The act also made it clear that derivatives shall be legal and valid

only if such contracts are traded on a recognized stock exchange, thus precluding OTC

derivatives. The government also rescinded in March 2000, the threedecade old

notification, which prohibited forward trading in securities. Derivatives trading

commenced in India in June 2000 after SEBI granted the final approval to this effect in

May 2000. SEBI permitted the derivative segments of two stock exchanges, NSE and

BSE, and their clearing house/corporation to commence trading and settlement in

approved derivatives contracts. To begin with, SEBI approved trading in index futures

contracts based on S&P CNX Nifty and BSE30 (Sensex) index. This was followed by

approval for trading in options based on these two indexes and options on individual

securities. The trading in index options commenced in June 2001 and the trading in


24/55



options on individual securities commenced in July 2001. Futures contracts on individual

stocks were launched in November 2001. Trading and settlement in derivative contracts

is done in accordance with the rules, bye laws, and regulations of the respective

exchanges and their clearing house/corporation duly approved by SEBI and notified in

the official gazette.

Derivatives market at NSE

The derivatives trading on the exchange commenced with S&P CNX Nifty Index futures

on June 12, 2000. The trading in index options commenced on June 4, 2001 and trading

in options on individual securities commenced on July 2, 2001. Single stock futures were

launched on November 9, 2001. The index futures and options contract on NSE are based

on S&P CNX Nifty Index. Currently, the futures contracts have a maximum of 3-month

expiration cycles. Three contracts are available for trading, with 1 month, 2 months and 3

months expiry. A new contract is introduced on the next trading day following the expiry

of the near month contract.

Trading mechanism

The futures and options trading system of NSE, called NEAT-F&O trading system,

provides a fully automated screenbased trading for Nifty futures & options and stock futures & options on a nationwide basis and an online monitoring and surveillance

mechanism. It supports an anonymous order driven market which provides complete

transparency of trading operations and operates on strict pricetime priority. It is similar

to that of trading of equities in the Cash Market (CM) segment. The NEAT-F&O trading

system is accessed by two types of users. The Trading Members(TM) have access to

functions such as order entry, order matching, and order & trade management. It provides

tremendous flexibility to users in terms of kinds of orders that can be placed on the

system. Various conditions like Good-till-Day, Good-till-Cancelled, Good-till- Date,

Immediate or Cancel, Limit/Market price, Stop loss, etc. can be built into an order. The

Clearing Members (CM) use the trader workstation for the purpose of monitoring the

trading member(s) for whom they clear the trades. Additionally, they can enter and set

limits to positions, which a trading member ca n take.


25/55



LITERATURE REVIEW


26/55



3.1 IMPACT OF THE INTRODUCTION OF FUTURES MARKET

ON THE SPOT MARKET: AN EMPIRICAL STUDY

Nupur Hetamsaria, Niranjan Swain

Using Standard Deviation model: Analyzing the structure of Volatility

The general approach adopted in the literature is assessed by comparing the spot markets

volatility before and after the introduction of futures trading. Here volatility is measured

using standard deviation (Hodgson et al, 1991, herbst et al, 1992) and GARCH model has

also been a preferred measure of volatility by many researchers (Kalok chan et al 1991,Antoniou and Holmes, 1995, Gregory et al, 1996, Butterworth, University of Durham) to

accommodate for heteroskedasticity in the observed returns. In this study, they have

measured volatility by computing the standard deviation of the daily returns. The

problem of heteroscedasticity does not exist as the data spans for the short period of

about five years and GARCH is not relevant for measuring volatility for a short time

span.

In the first place, the daily returns based on closing prices were computed using equation;

Rt = (Ct Ct-1)/Ct-1

Where Ct and Ct-1 are the closing prices on day t and t-1 respectively. Rt represents the

return in relation to day t. Next, they have computed the variance of this return series to

understand the inter-day volatility by using equation:


27/55



The impact of introduction of futures contract on the contracts on the underlying stock

market has been examined by comparing the daily volatility (measured by standard

deviation) before and after futures introduction in terms of (Ct-Ct-1)/Ct-1. For this

purpose they have used monthly periods including the overall period. The question of

relative volatility f the two markets (futures and spot) have been studied on a

contemporaneous basis and tested for statistical significance by using F-Test. To examine

the equality of variance before and after introduction of futures trading researcher, in

general, have used four tests, viz., a) The F-test, B) the Bartlett test, c) the Levene test

and D) the modified Levene test. However, in this study, they have only used the F-test.

As there might be other factors responsible for changes responsible in

observed volatility, other factors with potential to influence volatility are taken intoaccount. Hence, in order to determine whether the onset of futures trading has had any

impact on underlying spot market volatility it is necessary to separate the volatility

arising form market wide factors form the volatility which is specific to futures trading.

Previous studies have sought to alter out the factors that lead to market wide volatility by

regressing spot market returns against a proxy variable for which there was no related

futures contract (antonious and Holmes, 1995, Kamara et al, 1992, Gregory et al, 1996,

Darren Butterworth). For the purpose of this study, the spot market volatility is regressed

with the Nifty Junior Index returns (which essentially capture the market wide volatility)

and a dummy variable. The dummy assumes the value of one for the post futures period

and zero before the introduction of the futures trading. If the dummy variable is

significantly different from zero it is considered to have influenced the spot market

volatility with the inception of futures trading. The data has been analyzed using ordinary

least squares multiple regression technique. The following model is used for examine the

impact:


28/55



Findings and Conclusion

Volatility of spot index in the pre-futures and post-futures period

A comparison of Nifty volatility as measured by standard deviation shows that the

volatility of the post futures period is less than the volatility before the introduction of

futures volatility. Though the explanatory power due to introduction of futures is low,

there seems to be statistically significant difference between the volatility before and after

introduction of futures.

Below are the Literature review done by studying three research papers

3.1.1 BEHAVIOUR OF STOCK MARKET VOLATILITY AFTER DERIVATIVES

- Golaka C Nath

INTRODUCTION

The introduction of equity and equity index derivative contracts in Indian market has not

been very old but today the total notional trading values in derivatives contracts are much

ahead of cash market. On many occasions, the derivatives notional trading values are

double the cash market trading values. Given such dramatic changes, we would like to

study the behavior of volatility in cash market after the introduction of derivatives.

Impact of derivatives trading on the volatility of the cash market in India has been studied

by Thenmozhi(2002), Shenbagaraman(2003), Gupta and Kumar (2002) . Gupta and

Kumar(2002) did find that the overall volatility of underlying market declined after

introduction of derivatives contracts on indices. Thenmozhi(2002) reported lower level

volatility in cash market after introduction of derivative contracts. Shenbagaraman(2003)

reported that there was no significant fall in cash market volatility due to introduction of

derivatives contracts in Indian market. Raju and Karande (2003) reported a decline in

volatility of the cash market after derivatives introduction in Indian market. All these

studies have been done using the market index and not individual stocks. These studies


29/55



were conducted using data for a smaller period and when the notional trading volume in

the market was not significant and before tremendous success of futures on individual

stocks. Today derivatives market in India is more successful and we have more than 3

years of derivatives market. Hence the present study would use the longer period of data

to study the behaviour of volatility in the market after derivatives was introduced. The

study would use indices as well as individual stocks for analysis.

METHODOLOGY

This study uses the daily stock market data from January 1999 (for IGARCH data used is

from January 1998) to October 2003. Thus the daily returns are calculated using the

following equation:Rt = Log(Pt / Pt -1) *100 (1)

where Rt is the daily return, Pt is the value of the security on day t and Pt-1

is the value of the security on day t-1.

Standard deviation of returns is calculated using the following methods:

S.D = (Rt -R)2 /(n -1) (2)t =1Where R is the average return over the period. This study calculates the rolling standard

deviation for 1 year window as well as for a 6 month window to capture the conditional

dynamics. Next volatility is calculated using Risk Metrics method with l = 0.94

(IGARCH) and the initial volatility was computed using one year data from January 1998

to December 1998. Then we have used a GARCH model to estimate the daily volatility.

In the linear ARCH (q) model originally introduced by Engle (1982), the conditional

variance ht is postulated to be a linear function of the past q squared innovations:

In empirical applications of ARCH (q) models a long lag length and a large number of

parameters are often called for. An alternative and more flexible lag structure is often

provided by the generalized ARCH, or GARCH (p,q) model proposed independently by

Bollerslev (1986) and Taylor (1986). In many applications especially with daily

frequency financial data the estimate for a1 +a2 + ... +aq + b1 + b2 + ... + b p turns out to

be very close to unity. Engle and Bollerslev (1986) were the first to consider GARCH

processes with a1 + a2 + ... +a q + b1 + b2 + ... + b p = 1 as a distinct class of models,


30/55



which they termed integrated GARCH (IGARCH). In the IGARCH class of models a

shock to the conditional variance is persistent in the sense that it remains important for

future forecasts of all horizons.

DATA and DATA CHARACTERISTICS

The study uses two benchmark indices: S&P CNX NIFTY and S&P CNX NIFTY

JUNIOR along with selected few stocks for studying the volatility behaviour during the

period January 1999 to October 2003. 20 stocks have been considered a from the NIFTY

and Junior NIFTY category. Out of the 20 stocks, 13 have single stock futures and

options while 7 do not have the same. Futures and options are available on S&P CNX

NIFTY but not on S&P CNX NIFTY Junior.

CONCLUSION

The paper studies the behavior of volatility in equity market in pre and post derivatives

period in India using static and conditional variance. Conditional volatility has been

modeled using four different method: GARCH(1,1), IGARCH with l = 0.94, one year

rolling window of standard deviation and a 6 month rolling standard deviation. We have

considered 20 stocks randomly from the NIFTY and Junior NIFTY basket as well as

benchmark indices itself. Also static point volatility analysis has been used dividing the

period under study among various time buckets and justified the creation of such time

buckets. While studying conditional volatility it is observed that for most of the stocks,

the volatility has come down in the post derivative period while for only few stocks in the

sample (details are in Annexure II and III) the volatility in the post derivatives has either

remained more or less same or has increased marginally. All these methods suggested

that the volatility of the market as measured by benchmark indices like S&P CNX

NIFTY and S&P CNX NIFTY JUNIOR have fallen after in the post derivatives period.

The finding is in line with the earlier findings of Thenmozhi (2002), Shenbagaraman

(2003), Gupta and Kumar (2002) and Raju and Karande (2003). The earlier studies used

shorter period of data and pre single stock futures and options period data while we have

used data for a longer period that has taken into account various cyclical trends into

consideration.


31/55



3.1.2 EFFECT OF INTRODUCTION OF INDEX FUTURES ON

STOCK MARKET VOLATILITY: THE INDIAN EVIDENCE

- O.P. Gupta

INTRODUCTION

The Indian capital market has witnessed a major transformation and structural change

during the past one decade or so as a result of on going financial sector reforms initiated

by the Government of India since 1991 in the wake of policies of liberalization and

globalization. The major objectives of these reforms have been to improve market

efficiency, enhancing transparency, checking unfair trade practices, and bringing theIndian capital market up to international standards. As a result of the reforms several

changes have also taken place in the operations of the secondary markets such as

automated on-line trading in exchanges enabling trading terminals of the National Stock

Exchange (NSE) and Bombay Stock Exchange (BSE) to be available across the country

and making geographical location of an exchange irrelevant; reduction in the settlement

period, opening of the stock markets to foreign portfolio investors etc. In addition to these

developments, India is perhaps one of the real emerging markets in South Asian region

that has introduced derivative products on two of its principal existing exchanges viz.,

BSE and NSE in June 2000 to provide tools for risk management to investors. There had,

however, been a considerable debate on the question of whether derivatives should be

introduced in India or not. The L.C. Gupta Committee on Derivatives, which examined

the whole issue in details, had recommended in December 1997 the introduction of stock

index futures in the first place (1). The preparation of regulatory framework for the

operations of the index futures contracts took another two and a half-year more as it

required not only an amendment in the Securities Contracts (Regulation) Act, 1956 butalso the specification of the regulations for such contracts. Finally, the Indian capital

market saw the launching of index futures on June 9, 2000 on BSE and on June 12, 2000

on the NSE. A year later options on index were also introduced for trading on these

exchanges. Later, stock options on individual stocks were launched in July 2001. The


32/55



latest product to enter in to the derivative segment on these exchanges is contracts on

stock futures in November 2001. Thus, with the launch of stock futures, the basic range

of equity derivative products in India seems to be complete.

METHODOLOGY

Following Ibrahim et al. [1999] and Kar et.al. [2000], the study has used four measures of

volatility. The first measure is based upon close-to-close prices. Therefore, in the first

place, the daily returns based on closing prices were computed using equation

Rt = ln (Ct/Ct-1) (1)

Where Ct and Ct-1 are the closing prices on day t and t-1 respectively;

Rt represents the return in relation to day t. Next, we have computed the variance of this

return series to understand the inter-day volatility. The second measure of volatility isbased upon open-to-open prices. Analogously, variance of the daily has been computed

from returns series based on open-to-open prices. The third measure of volatility

estimates intra- day volatility. It has been estimated by using Parkinson .s [1980]extreme value estimator, which is considered to be more efficient.

2.1 The Data

The data employed in the study consists of daily prices of two major stock market indices

viz., the S&P CNX Nifty Index (henceforth Nifty Index) and the BSE Sensex (BSE

Index) for a four year period from June 8, 1998 to June 30, 2002. For each of these

indices four sets of prices were used. These were daily high, low, open, and close prices.

Likewise, daily high, low, open, and close prices were used from June 9, 2000 to March

31, 2002 for the BSE Index Futures (7) and from June 12, 2000 to June 30, 2001 for the

Nifty Index Futures. The necessary data have from collected from the Derivative

Segments of both of these exchanges.

CONCLUSIONS

This paper has been aimed at examining the impact of index futures introduction on stock

market volatility. Further, it has also examined the relative volatility of spot market and

futures market. The study utilized daily price data (high, low, open and close) for BSE


33/55



Sensex and S&P CNX Nifty Index from June 1998 to June 2002. Similar data from June

9, 2000 to March 31, 2002 have also been used for BSE Index Futures and from June 12,

2000 to June 30, 2002 for the Nifty Index Futures. The study has used four measures of

volatility: (a) the first is based upon close-to-close prices, (b) the second is based upon

open-to-open prices, (c) the third is Parkinson .s Extreme Value Estimator, and (d) thefourth is Garman-Klass measure volatility (GKV). The empirical results reported here

indicate that the over-all volatility of the underlying stock market has declined after the

introduction of index futures on both the indices in terms of all the three measures i.e. ln

(Ct/Ct-1) ln(Ot/Ot-1) and ln(Ht/Lt). It must, however, be noted that since the introduction

of index futures the Indian stock market has witnessed several changes in its market

micro-structure such as the abolition of the traditional `badla system , reduction in the

trading cycle etc. Therefore, these results should be interpreted in the light of thesechanges. However, there is no conclusive evidence, which suggests that, the futures

volatility is higher (lower) in comparison to the underlying stock market for both the

indices in terms of all the four measures of volatility. In fact, there is some evidence that

the futures volatility is lower in some months in comparison to the underlying stock

market for both of these indices. These results are in contrast to those reported for the

other emerging markets. The study, being first in the Indian context, has several policy

implications for regulators, policy makers, and investors.

3.1.3 DO FUTURES AND OPTIONS TRADING INCREASE STOCK

MARKET VOLATILITY?

-Dr. Premalata Shenbagaraman

INTRODUCTION

In the last decade, many emerging and transition economies have started introducing

derivative contracts. As was the case when commodity futures were first introduced on

the Chicago Board of Trade in 1865, policymakers and regulators in these markets are

concerned about the impact of futures on the underlying cash market. One of the reasons


34/55



for this concern is the belief that futures trading attract speculators who then destabilize

spot prices. This concern is evident in the following excerpt from an article by John

Stuart Mill (1871):

The safety and cheapness of communications, which enable a deficiency in one place tobe, supplied from the surplus of another render the fluctuations of prices much lessextreme than formerly. This effect is much promoted by the existence of speculativemerchant. Speculators, therefore, have a highly useful office in the economy of society ..Since futures encourage speculation, the debate on the impact of speculators intensifiedwhen futures contracts were first introduced for trading; beginning with commodity

futures and moving on to financial futures and recently futures on weather and electricity.

However, this traditional favorable view towards the economic benefits of speculative

activity has not always been acceptable to regulators. For example, futures trading wasblamed by some for the stock market crash of 1987 in the USA, thereby warranting more

regulation. However before further regulation in introduced, it is essential to determine

whether in fact there is a causal link between the introduction of futures and spot market

volatility. It therefore becomes imperative that we seek answers to questions like: What is

the impact of derivatives upon market efficiency and liquidity of the underlying cash

market? To what extent do derivatives destabilize the financial system, and how should

these risks be addressed? Can the results from studies of developed markets be extended

to emerging markets? This paper seeks to contribute to the existing literature in many

ways. This is the first study to examine the impact of financial derivatives introduction on

cash market volatility in an emerging market, India. Further, this study improves upon the

methodology used in prior studies by using a framework that allows for generalized auto-

regressive conditional heteroskedasticity (GARCH) i.e., it explicitly models the volatility

process over time, rather than using estimated standard deviations to measure volatility.

This estimation technique enables us to explore the link between information/news

arrival in the market and its effect on cash market volatility. The study also looks at the

linkages in ongoing trading activity in the futures market with the underlying spot market

volatility by decomposing trading volume and open interest into an expected component

and an unexpected (surprise) component. Finally this is the first study to our knowledge

that looks at the effects of both stock index futures introduction as well as stock index


35/55



options introduction on the underlying cash market volatility. The results of this study are

crucial to investors, stock exchange officials and regulators. Derivatives play a very

important role in the price discovery process and in completing the market. Their role in

risk management for institutional investors and mutual fund managers need hardly be

overemphasized. This role as a tool for risk management clearly assumes that derivatives

trading do not increase market volatility and risk. The results of this study will throw

some light on the effects of derivative introduction on the efficiency and volatility of the

underlying cash markets.

METHODOLOGY

One of the key assumptions of the ordinary regression model is that the errors have the

same variance throughout the sample. This is also called the homoskedasticity model. If the error variance is not constant, the data are said to be heteroskedastic. Since ordinary

least-squares regression assumes constant error variance, heteroskedasticity causes the

OLS estimates to be inefficient. Models that take into account the changing variance can

make more efficient use of the data. There are several approaches to dealing with

heteroskedasticity. If the error variance at different times is known, weighted regression

is a good method. If, as is usually the case, the error variance is unknown and must be

estimated from the data, one can model the changing error variance. In the past, studies of

volatility have used constructed volatility measures like estimated standard deviations,

rolling standard deviations, etc, to discern the effect of futures introduction. These studies

implicitly assume that price changes in spot markets are serially uncorrelated and

homoskedastic. However, findings of heteroskedasticity in stock returns are well

documented (Mandelbrot 1963), Fama (1965), Bollerslev (1986). Thus the observed

differences in variances from models assuming homoscedasticity may simply be due to

the effect of return dependence and not necessarily due to futures introduction. The

GARCH model assumes conditional heteroscedasticity, with homoskedastic

unconditional error variance. That is, the model assumes that the changes in variance are

a function of the realizations of preceding errors and that these changes represent

temporary and random departures from a constant unconditional variance, as might be the

case when using daily data. The advantage of a GARCH model is that it captures the


36/55



tendency in financial data for volatility clustering. It therefore enables us to make the

connection between information and volatility explicit, since any change in the rate of

information arrival to the market will change the volatility in the market. Thus, unless

information remains constant, which is hardly the case, volatility must be time varying,

even on a daily basis. The impact of stock index futures and option contract introduction

in the Indian market is examined using a unvaried GARCH (1, 1) model. The time series

of daily returns on the S&P CNX Nifty Index is modeled as a univariate GARCH

process. Following Pagan and Schwert (1990) and Engle and Ng (1993), we need to

remove from the time series any predictability associated with lagged world returns

and/or day of the week effects. Further, it is required to control for the effect of market

wide factors, since one is interested in isolating the unique impact of the introduction of

the futures/options contracts. Fortunately for the Indian stock market there is an index,the Nifty Junior, which comprises stocks for which no futures contracts are traded. As

such, it serves as a perfect control variable for us to isolate market wide factors and

thereby concentrate on the residual volatility in the Nifty as a direct result of the

introduction of the index derivative contracts. Therefore the study introduces the return

on the Nifty Junior index as an additional independent variable.

CONCLUSION

In this study one has examined the effects of the introduction of the Nifty futures and

options contracts on the underlying spot market volatility using a model that captures the

heteroskedasticity in returns that characterize stock market returns. The results indicate

that derivatives introduction has had no significant impact on spot market volatility. This

result is robust to different model specifications. However, futures introduction seems to

have changed the sensitivity of nifty returns to the S&P500 returns. Also, the day-of-the

week effects seem to have dissipated after futures introduction. Later the model is

estimated separately for the pre and post futures period and finds that the nature of the

GARCH process has changed after the introduction of the futures trading. Pre-futures, the

effect of information was persistent over time, i.e. a shock to todays volatility due to

some information that arrived in the market today, has an effect on tomorrow s volatilityand the volatility for days to come. After futures contracts started trading the persistence


37/55



has disappeared. Thus any shock to volatility today has no effect on tomorrows volatility

or on volatility in the future. This might suggest increased market efficiency, since all

information is incorporated into prices immediately. Next, using a procedure inspired by

Bessembinder and Sequin (1992), it is found that after the introduction of futures trading,

one is unable to pick up any link between the volume of futures contracts traded and the

volatility in the spot market.


38/55



RESEARCH METHODOLOGY


39/55



RESEARCH PROBLEM STATEMENT

In the last decade, many emerging and transition economies have started introducing thederivatives contracts. As was the case when commodity trading were first introduced on

Chicago Board of Trading in 1865, policymakers and regulators were worried about

impact of future on the underlying cash market. One of the reason for this concern was

futures trading attracts speculators who then destabilize the spot market. In India too,

Index Futures were introduced during June 2000 with the purpose of offering the

investors a hedging tool to minimize their risk aroused mixed feeling amongst the

inventors. The general belief was, after the introduction of Index Futures the market has

become more volatile. Implying there is more return at the cost of more risk. The purpose

of this study is to test whether the market volatility has increased significantly after the

introduction of Index Futures.

SCOPE OF THE STUDY

The limited scope of the study is to find out: Whether the introduction of stock index

futures reduces stock market volatility. The Study does not intend to find out whether

changes of any other international markets affected the market during the same period.

3.1 METHODOLOGY

3.1.1 OBJECTIVEThe objective of this study is to test, whether the introduction of Index Futures has had

any impact on the volatility of Indian stock market.

3.1.2 DATA3.1.2.1 Nature of data

The nature of the data for the above study will be a time series secondary data showing

heteroskedastic nature.


40/55



3.2.2.2 Sources of data The data employed in the study consists of daily prices of the S@P CNX Nifty Index,

NSE 500 for the period June 1, 1995 to May 2005. The prices used are daily open and

close prices. These data will be collected from National Stock Exchange website.

3.2.2.3 Data Period The period of data is from June 1, 1995 to May 31, 2005.

HYPOTHESIS OF STUDY

H0 : Introduction of Index Futures has no impact on the volatility of Spot Market.H1 : Introduction of Index Futures has an impact on the volatility of Spot Market.

STATISTICAL PROCEDURE

3.3.1 The first objective is to find out whether the data is stationary or non stationary?

This is tested by using Unit Root test.

3.3.2 The second objective is to test the hypothesis by F-test..

CALCULATION OF VOLATILITY:

As this volatility is calculated using historical prices this is called Historical volatility

We have used the daily stock market data from June 1995 to May 2005. We have

calculated daily returns using the following equation:

Rt = LN(Pt/Pt-1)*100 Where Rt is the daily return, Pt is the value of the security on day t and Pt-1 is the value

of the security on day t-1 .


41/55



We have calculated the standard deviation of returns using the following methods:

N _ 2 = (Rt-R)^2 /(N-1)

t =1

where R is the average return over the period.

TEST FOR STATIONARITY:

STATIONARY STOCHASTIC PROCESS:A random or stochastic process is a collection of random variables ordered in time. A

stochastic process is said to be stationary if its mean and variance are constant over timeand the value of the covariance between the two time periods depends only on the

distance or gap or lag between the two time periods and the actual time at which the

covariance is computed.

NON STATIONARY STOCHASTIC PROCESS:A stochastic process is said to be non stationary if its mean and variance change over

time. An example for non stationary is random walk model.

There are two types of random walk:Random walk without drift

Random with drift

UNIT ROOT TEST:A test of stationarity (or nonstationarity) that is well known is the UNIT ROOT TEST.

The starting point of unit root test is

Y t=Y (t-1) +Ut

Where,

Ut =white noise term.

Yt = random variable at discrete time interval t.


42/55



If =1, then the unit root exist. That is: the time series under consideration is

Non-stationary or follows a random walk.

If ! = 1, then unit root does not exist. That is: the time series under consideration is

stationary.

Theoretically, value can be calculated by regressing Yt with one period lag values.

AUGMENTED DICKEY FULLER (ADF) TEST:

ADF Test is used for calculating , where = -1.Hypothesis:

H0= Time series is non stationary.

If = 0.(unit root)H1= Time series is stationary.

If ! =0.

Decision Rule:

1) If T*>ADF critical value, not reject the null hypothesis i.e., unit root exists.

2) If T*


43/55



3.3 STATISTICAL SOFTTWARE PACKAGES USED

E views

This software has been used to conduct the Augmented Dickey Fuller Unit root.

Limitations of the study

1. The results may not give accurate picture as there could be many other factors which

influence the volatility of Market Index.


44/55



DATA ANALYSIS &

INTERPRETATION


45/55



EMPIRICAL RESULTS

Daily closing prices for S & P CNX Nifty were obtained from www.nseindia.com over

the period 1 st May 1995 to 30 th June 2005. The data comprises 1240 observations relatedto the period prior to the introduction of futures trading and the remaining 1281

observations to the period after the introduction of futures trading. Continuously

compounded percentage returns are estimated as the log price relative. That is for an

index with daily closing price P t, its return R t is defined as log (P t/P t-1). All the return

series (before and after introduction period) are subjected to Augmented Dickey Fuller

test.

Fig 1and Fig 2 plots the returns of Nifty daily closing price, Fig 3 and Fig 4 plot

the log data of the returns showing the phenomenon of volatility clustering and Fig 5

plots the log price difference indicating price change volatility. The study of these graphs

provides an initial view of volatility for NSE Nifty indices. It can be observed from the

graph that the pre-futures NSE Nifty volatility is greater than that of post-futures. This

broadly suggests that the introduction of index futures has not destabilized the spot

market. However, inferences cannot be drawn from these figures alone, as they are not

supported by any statistical data.


46/55



GRAPHICAL EVIDENCE

GRAPH OF CLOSING PRICES

GRAPH SHOWING MOVEMENT OF NIFTY DAILY CLOSING

PRICES

0

500

1000

1500

2000

1 101 201 301 401 501 601 701 801 901 1001 1101 1201

NO. OF OBSERVATIONS

CLOSING PRICES

(BEFORE INTRODUCTION PERIOD)

GRAPH SHOWING MOVEMENT OF NIFTY DAILY CLOSING

PRICES

0

500

1000

1500

2000

2500

1 105 209 313 417 521 625 729 833 937 1041 1145 1249

NO. OF OBSERVATIONS

CLOSING PRICE

(AFTER INTROCDUTION PERIOD)


47/55



GRAPH OF LOG PRICE DATA


-10

-5

0

5

10

15

1 99 197 295 393 491 589 687 785 883 981 1079 1177

NO. OF OBSERVATIONS

LOG PRICE

(BEFORE INTRODUCTION PERIOD)


-15

-10

-5

0

5

10

1 102 203 304 405 506 607 708 809 910 1011 1112 1213

NO. OF OBSERVATIONS

LOG PRICE

(AFTER INTROCDUTION PERIOD)


48/55



GRAPH OF LOG PRICE DIFFERENCE

GRAPH OF LOG PRICE DIFFERENCE

-15

-10

-5

0

5

10

1 102 203 304 405 506 607 708 809 910 1011 1112 1213

NO. OF OBSERVATIONS

LO

G PRICE DIFFEREN

CE


49/55



STATISTICAL PROCEDURE

UNIT ROOT TEST

Before Introduction of Futures

ADF Test Statistic -15.259 1% Level of significance -3.4395% Level of significance -2.864310% Level of significance -2.5683

The computed AUGMENTED DICKEY FULLER test-statistic( -15.259) at 4 lag, issmaller than the critical values -3.439at 1% level, -2.8643at 2% level, and -2.5683at 10% level. It doesn t have unit root problem, the data is stationary. It is clear that it haspassed the Durbin-Watson test and we can trust the regression result. Hence data is

stationary.

After Introduction of Futures

ADF Test Statistic -14.2496 1% Level of significance -3.43845% Level of significance -2.864310% Level of significance -2.5683

The computed AUGMENTED DICKEY FULLER test-statistic( -14.2496)at 4 lag, is smaller than the critical values -3.4384at 1% level, -2.8643at 2% level, and-2.5683at 10% level. It doesn t have unit root problem, the data is stationary. It is clearthat it has passed the Durbin-Watson test and we can trust the regression result. Hence

data is stationary.


50/55



TEST FOR HETEROSKEDASTICITY

One of the key assumptions of the ordinary regression model is that the errors have the

same variance throughout the sample. This is also called the homoskedasticity model. If

the error variance is not constant, the data are said to be heteroskedastic. Since ordinary

least-squares regression assumes constant error variance, heteroskedasticity causes the

OLS estimates to be inefficient. In the past, studies of volatility have used constructed

volatility measures like estimated standard deviations, rolling standard deviations, etc, to

discern the effect of futures introduction. These studies implicitly assume that price

changes in spot markets are serially uncorrelated and homoskedastic. However, findings

of heteroskedasticity in stock returns are well documented. Performing aDESCRIPTIVE ANALYSIS on the daily stock returns of both S&P CNX Nifty proves

the heteroskedastic nature of the above data. As seen below from the analysis we can

conclude that the variance of before introduction period and after introduction period is

different thus proving that the data considered is heteroskedastic .

STATISTICAL EVIDENCES

Further to prove the heteroskedastic nature of the stock returns statistically, F-TEST is

carried out. The F is named in the honour of the great statistician R.A. Fisher. The object

of the F- test is to find out whether the two independent estimates of population variance

differ significantly , or whether the two samples may be regarded as drawn from normal

populations having the same variances.


51/55



before intro std. dev after intro std. dev F-Test

Jun-95Jul-95

Aug-95Sep-95Oct-95Nov-95Dec-95Jan-96Feb-96Mar-96Apr-96

May-96Jun-96Jul-96


May-97Jun-97Jul-97


May-98Jun-98Jul-98

Aug-98Sep-98Oct-98Nov-98Dec-98Jan-99

0.75391.14580.79790.66530.75361.35581.04580.99422.59841.28741.6562

1.51591.06191.54071.06991.08431.76521.30291.79482.06011.20352.48591.6354

0.84840.86051.40241.55520.95513.10101.70731.40001.53291.00511.46431.5708

1.38683.12201.88151.57391.31011.85331.20661.49172.0643

Jun-00Jul-00Aug-00Sep-00Oct-00Nov-00Dec-00Jan-01Feb-01Mar-01Apr-01

May-01Jun-01Jul-01Aug-01Sep-01Oct-01Nov-01Dec-01Jan-02Feb-02Mar-02Apr-02

May-02Jun-02Jul-02Aug-02Sep-02Oct-02Nov-02Dec-02Jan-03Feb-03Mar-03Apr-03

May-03Jun-03Jul-03Aug-03Sep-03Oct-03Nov-03Dec-03Jan-04

1.39261.76491.08202.00751.61311.40041.45491.20991.59942.97102.2899

0.89451.25691.03360.54922.62721.22201.20211.24971.00621.52670.91981.1128

1.35431.13550.98630.86440.73410.84580.69210.92470.79730.86791.12641.3978

0.76310.95801.06361.55071.83701.56061.16130.88712.1929

3.41172.37261.83909.10554.58181.06691.93541.48080.37895.32611.9116

0.34821.40100.45010.26355.87080.47920.85130.48490.23861.60910.13690.4630

2.54781.74120.49460.30890.59080.07440.16430.43620.27050.74560.59180.7919

0.30270.09420.31950.97071.96600.70900.92630.35361.1285


52/55



Feb-99Mar-99Apr-99

May-99Jun-99Jul-99


May-00

1.73331.39293.35152.19021.35931.60191.34561.33322.09061.36631.45001.94831.89441.82773.60742.4301

Feb-04Mar-04Apr-04May-04Jun-04Jul-04Aug-04Sep-04Oct-04Nov-04Dec-04Jan-05Feb-05Mar-05Apr-05May-05

1.64801.36271.30144.42851.45081.26351.01190.84770.91940.69830.75701.66720.79721.09681.18200.6854

0.90410.95720.15084.08841.13930.62210.56550.40430.19340.26120.27250.73230.17710.36010.10740.0796

Interpretation :

If F-Test value is below 1.53 tabulated value = Significant

If F-Test value is above 1.53 tabulated value = Non-significant

Even though Average variation seems to reduce statistically, it is not showing a

significant difference. Out of 60 pairs of tested observations 46 are not significant and 14

are highly significant from June 1995 to May 2005.


53/55



CONCLUSION


54/55



Volatility of Spot Index in the pre-futures & post-futures period.

A comparison of Nifty volatility as measured by standard deviation shows that the

volatility in the post-futures period has not changed much but there is a declining trend in

volatility after the introduction of futures volatility, although statistically there is no

significant difference between the volatility before and after introduction of futures.


55/55


BIBLIOGRAPHY

REFERNCE BOOKS

Investment Analysis & Portfolio Management Prasanna Chandra.l

WEBSITES

www.nseindia.com

www.finance.yahoo.com

www.google.com

www.investorpedia.com

REFERNCE ARTICLES

Behaviour of stock market volatility after derivatives - golaka c nath

Do futures and options trading increase stock market volatility?

Dr. premalata shenbagaraman

Effect of introduction of index futures on stock market volatility: the indian

evidence - o.p. gupta

Impact of the Introduction of Futures Market

Documents

Transcript of Impact of the Introduction of Futures Market