Abhishek Saraff-05-Stock Futures on Spot Market Volatility

8/8/2019 Abhishek Saraff-05-Stock Futures on Spot Market Volatility

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ImpactofStockFuturesonSpotMarketVolatility:AStudyonNifty.

M.P.Birla Institute of Management, Bangalore

1

ADissertationReportOn

ImpactofStockFuturesonSpotMarket

Volatility:AstudyonNifty

Submittedinpartialfulfillmentofrequirementfortheawardof

thedegreeofMasterofBusinessAdministrationofBangalore

University

ByABHISHEK.CSARAFF

Reg.No:05XQCM6004

UndertheGuidanceandSupervisionOf

Dr.NAGESH.S MALAVALLI

M.P.BIRLAINSTITUTEOFMANAGEMENTAssociateBharathiyaVidyaBhavan

#43,RaceCourseRoad,BANGALORE560001

2005-2007


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DECLARATION

I hereby declare that this dissertation entitled IMPACT OF

STOCK FUTURE VOLATILITY ON SPOT MARKET: A STUDY

ON NIFTY is the result of my own research work carried out under

the guidance and supervision of Dr. Nagesh S. Malavalli, M P Birla

Institute of Management Bangalore.

I also declare that this dissertation has not been submitted

earlier to any Institute/organization for the award of any degree or

diploma.

Place: Bangalore

Date: Abhishek Saraff


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CERTIFICATE

I hereby certify that this dissertation entitled IMPACT OF


ON NIFTY is the result of research work carried out by Mr.

ABHISHEK SARAFF bearing Reg No: 05XQCM6004 under the

guidance of DR. NAGESH S. MALAVALLI, M P Birla Institute of

Management, Bangalore.

Place: Bangalore Dr N.S.

Malavalli

Date: PRINCIPAL


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GUIDE CERTIFICATE

I hereby certify that this dissertation entitled IMPACT OF


ON NIFTY is an offshoot of the research carried out by Mr.

ABHISHEK SARAFF Reg No: 05XQCM6004 UNDER my guidance

and supervision.

Place: Bangalore

Date: Dr N.S. Malavalli


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ACKNOWLEDGEMENT

I would like to express my sincere gratitude to my research guide

DR. NAGESH S. MALAVALLI, Principal, M.P.Birla Institute of

Management, Bangalore for his constant encouragement and guidance

in the course of the research investigation.

I would like to thank DR. T.V. NARSHIMA RAO, Adjunct

Faculty, M.P.Birla Institute of Management, Bangalore for his

constant guidance and timely support in the course of the research.

I would also like to thank PROF. S. SANTHANAM, Adjunct

Faculty, M.P.Birla Institute of Management, Bangalore who helped

me to analysis data with his expertise knowledge in statistics.

And further I would like to thank all the faculty members of

MPBIM who have helped me in completing my project. I have gained

a lot of knowledge throughout the course of carrying out this project.

I would like to sincerely thank my Parents and all my Friends

who have helped me in completing this project by providing me with

the psychological and academic support.


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ABHISHEK SARAFF

CHAPTERS PARTICULARS PAGE NO

Abstract 1

1 Introduction

1.1 Background of the study 2

1.2 Dervivatives at NSE 2

1.3 Trading Mechanism 3

1.4 Importance of the study 3

2 Literature Review

2.1 survey of empirical literature 5-18

3 Research Methodology

3.1 Research problem statement 19

3.2 Scope of the study 19

3.3 Objective of the study 19

3.4 Data 20

3.5 Hypothesis of study 20

3.6 Statistical Procedure 21-23

3.7 Actual collection of data 23

3.8 Tools used for testing hypothesis 23

3.9 Sources of secondary data 24

3.10 Softwares used for data analysis 24

4 Data Analysis & Interpretation4.1 Empirical Results 25

4.2 Presentations of data 26-62

4.3 Interpretation 63

5 Conclusion 64

6 Bibliography 65


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ABSTRACT:

The paper examines the impact of stock futures on spot market volatility, i.e.,

Nifty. There are two contradicting schools of thoughts with regards to this: one,

which advocates that the derivatives product has impact on spot market volatility,

while the other, which apposes this. Ever since the introduction of stock futures in

various market all over the world, numerous studies have been carried out upon

the effects of futures listing on underlying cash market volatility.

In India, stock futures trading were started by the National Stock Exchange

with a view to bring stability in the market for commodities and to keep a check

on the spiraling prices of shares. The underlying research work aims at finding out

impact of stock futures on the spot market volatility or whether after introduction

of stock futures have fluctuated drastically compared to before the introduction of

stock futures.

For the purpose of determining the above, the spot prices two years prior

the introduction of futures and two year prices after introduction of futures were

obtained from the National Stock Exchange website. The log natural was

calculated on the collected data and subsequently Augmented Dickey Fuller Test

of Stationarity was used to conduct the test of stationarity on the calculated log

natural. Subsequently standard deviations prior and after the introduction of

futures was calculated and the values were subjected to an F-test. Based on the

results of the above we were able to conclude that there is no impact of stock

futures on the volatility of spot market (CNX Nifty).

Also during the course of the literature review various information about

the stock futures were identified i.e. advantages of futures trading, trading, history

of futures trading, technical terminologies and about National Stock exchanges

was learnt during the course of review of the literature.


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Chapter-1

1.1 Background of the Study:

The Indian capital market has witnessed radical changes, especially during the last

decade. Having discarded the age old practices like open outcry trading system,

physical form of shares and new settlement procedure, and others, the markets are

now operating with world class practices and products. The reforms in the capital

markets have helped to improve efficiency in many aspects namely, the

dissemination of information, transparency in operations, prohibiting unfair trade

practices.

The most certain thing about the markets is uncertainty, which leads to

risk. One such risk is financial risk, due to the changes in stock market prices. Tomanage such risks, financial instruments, known as financial derivatives, have

been developed and introduced into the Indian capital markets as well as across

the globe, over a period of time. Based on the recommendations of L.C. Gupta

Committee, SEBI permitted the stock exchanges viz., BSE and NSE in India to

introduce financial derivatives in June 2000. The first product was futures on

indices followed by options on indices, individual stock options and futures.

The term derivative implies that it has no independent value. Its value is

derived from the value of the other asset. According to the L.C. Gupta

Committees Report, derivatives means a forward future or option contract for a

predetermined fixed duration, linked for the purpose of contract fulfillment to

value of specified real or financial asset or to an index security.

1.2 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


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contract is introduced on the next trading day following the expiry of the near

month contract.

1.3 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, order and 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, Goodtill- 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 can take.

1.4 Importance of the study:

The impact of derivatives on the cash market volatility is a much debated and

widely studied research topic. Ever since the Chicago Board of Trade introduced

the commodity futures in 1865, various markets have been studied at different

time periods. The concern over how trading in index futures and options affect the

spot market has been an interesting subject for investors, academicians, regulators

and exchanges. Financial derivatives were introduced in India, mainly as a risk

management tool for both institutional and retail investors. The two main

functions of derivative market are: Price discovery and hedging. The available

literature offers two different kinds of arguments. Some authors like Gupta and

Kumar, Golaka C Nath found that the overall volatility of the underlying stock

market was reduced after introduction of derivative contracts on indices in India.

The other side of the argument is that the volatility of the spot market could


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increase with the derivatives products because of speculation and arbitrage

strategies.

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.

The present paper attempts to study the impact of introduction of stock

futures on the underlying spot market volatility i.e., Nifty.


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Chapter-2

SURVEY OF THE EMPIRICAL LITERATURE:

The introduction of equity index futures markets enables traders to transact large

volumes at much lower transaction costs relative to the cash market. The

consequence of this increase in order flow to futures markets is unresolved on

both a theoretical and an empirical front. Stein (1987) develops a model in which

prices are determined by the interaction between hedgers and informed

speculators. In this model, opening a futures market has two effects; (1). The

futures market improves risk sharing and therefore reduces price volatility, and

(2). If the speculators observe a noisy but informative signal, the hedgers react to

the noise in the speculative trades, producing an increase in volatility.

In contrast, models developed by Danthine (1978) argue that the futures

markets improve market depth and reduce volatility because the cost to informed

traders of responding to mis-pricing is reduced. Froot and Perold (1991) extend

Kyles(1985) model to show that market depth is increased by more rapid

dissemination of market-wide information and the presence of market makers in

the futures market in addition to the cash market. Ross (1989) assumes that there

exists an economy that is devoid of arbitrage and proceeds to provide a condition

under which the no-arbitrage situation will be sustained. It implies that the

variance of the price change will be equal to the rate of information flow. The

implication of this is that the volatility of the asset price will increase as the rate of

information flow increases. Thus, if futures increase the flow of information, than

in the absence of arbitrage opportunity, the volatility of the spot price must

change. Overall, the theoretical work on futures listing effects offer no consensus

on the size and the direction of the change in volatility. We therefore need to turn

to the empirical literature on evidence relating to the volatility effects of listing

index futures, index options, stock futures and stock option.


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BEHAVIOUR OF STOCK MARKET VOLATILITY AFTER

DERIVATIVES

Golaka C Nath

INTRODUCTIONThe 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 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 behavior

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:


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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:

Where 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, 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.


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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 behavior 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.


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EFFECT OF INTRODUCTION OF INDEX FUTURES ON

STOCKMARKET VOLATILITY: THE INDIAN EVIDENCEO.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 the Indian 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 ofwhether 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 but also 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 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


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seems to be complete day volatility. It has been estimated by using Parkinsons

[1980] extreme value estimator, which is considered to be more efficient.

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 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 Parkinsons Extreme Value Estimator, and (d) the fourth 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

these changes. However, there is no conclusive evidence, which suggests that, the


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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.


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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 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 to be, supplied from the surplus of another render the fluctuations of

prices much less extreme than formerly. This effect is much promoted by the

existence of speculative merchant. Speculators, therefore, have a highly useful

office in the economy of society.

Since futures encourage speculation, the debate on the impact of speculators

intensified when 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 were blamed 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?


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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 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


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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

homoskedasticity 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

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 whichno 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


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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 tomorrows volatility and the volatility for days to come.

After futures contracts started trading the persistence 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.


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Impact of Financial Derivative Products on Spot Market

Volatility: A Study on Nifty

S V Ramana Rao

Introduction

The Indian capital market has witnessed radical changes, especially during the last

decade. Having discarded the age old practices like open outcry trading system,

physical form of shares and new settlement procedure, and others, the markets are

now operating with world class practices and products. The reforms in the capital

markets have helped to improve efficiency in many aspects namely, the

dissemination of information, transparency in operations, prohibiting unfair trade

practices.

The most certain thing about the markets is uncertainty, which leads to

risk. One such risk is financial risk, due to the changes in stock market prices. To

manage such risks, financial instruments, known as financial derivatives, have

been developed and introduced into the Indian capital markets as well as across

the globe, over a period of time. Based on the recommendations of L.C. Gupta

Committee, SEBI permitted the stock exchanges viz., BSF and NSE in India to

introduce financial derivatives in June 2000. The first product was futures on

indices followed by options on indices, individual stock options and futures.

The term derivative implies that it has no independent value. Its value is

derived from the value of the other asset. According to the L.C. Gupta

Committees Report, derivatives means a forward future or option contract for a

predetermined fixed duration, linked for the purpose of contract fulfillment to

value of specified real or financial asset or to an index security.

The impact of derivatives on the cash market volatility is a much debated

and widely studied research topic. Ever since the Chicago Board of Trade

introduced the commodity futures in 1865, various markets have been studied at

different time periods. The concern over how trading in index futures and options

affect the spot market has been an interesting subject for investors, academicians,

regulators and exchanges. Financial derivatives were introduced in India, mainly

as a risk management tool for both institutional and retail investors. The two main

functions of derivative market are: Price discovery and hedging. The available

literature offers two different kinds of arguments. Some authors like Gupta and


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Kumar, Golaka C Nath found that the overall volatility of the underlying stock

market was reduced after introduction of derivative contracts on indices in India.

The other side of the argument is that the volatility of the spot market could

increase with the derivatives products because of speculation and arbitrage

strategies.

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 theunderlying cash markets.

The present paper attempts to study the impact of introduction of index

futures, index options, stock options and stock futures on the underlying spot

market volatility i.e., Nifty.

Methodology

The study is carried out using ordinary linear regression. The impact of the

introduction of derivative products on the volatility of Nifty-the spot market

under studyis determined by comparing its volatility before and after the

introduction of derivative products. This can be done by calculating the

descriptive statistics, after eliminating the effect of various factors. For instance,

to nullify the effect of various market-wide factors, Nifty 500 taken into account,

which is a broad-based index for the Indian capital market; similarly to eliminate

the yesterdays impact on the todays market, Lag Nifty has also been included in

the regression equation. In this study, the Nifty volatility is regressed with Nifty500, Lag Nifty and a dummy variable. The dummy variable assumes the value of

1 for the post-derivative products period and 0 for the pre-derivative products

period. The sign of the dummy coefficient signifies a fall or rise in the volatility

with the inception of derivative products. The data has been analyzed using


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ordinary least square technique. To examine the impact of derivative products on

the volatility of the spot market, the following regression model has been used.

Nt =0 + 1 Nifty 500 + 2 Dt

Ntis the standard deviation of Nifty return series

Nifty 500 represents the standard deviation of Nifty 500 return series is the

dummy variable.

Hypothesis

Using the above methodology, the following hypothesis was tested.

H0: Derivative products like index futures, index options, stock options and stock

futures

influence the underlying spot market volatility, i.e., Nifty.

H1: Derivative products like index futures, index options, stock options and stock

futures do not influence the underlying spot market volatility, i.e., Nifty.

Conclusion

This study has examined the impact of index futures, index options, stock option

and stock futures on the volatility of Nifty. A regression analysis has been done to

examine the changes in volatility with the help of dummy variables. Thecoefficients of the dummy variables are positive, indicating that Nifty volatility

has increased with the introduction of the above- mentioned derivative products

such as index futures, index options, stock options and stock futures. This may be

due to the speculative operations and the FIIs active participation in the market.

The market players might have been attracted to the futures and options segment,

because of low transaction costs and the leverage advantage available in the

market. Index trading may not be blamed for the volatility in the spot market

because, in an excessively volatile cash market, the fear among investors

motivates them to engage in more hedging activities in the future market, which in

turn leads to volatility.


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CHATER-III

3.1 RESEARCH PROBLEM STATEMENT

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

introducing the derivatives contracts. As was the case when commodity trading

were first introduced on Chicago Board of Trading in 1865, policy makers 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, Stock Future were introduced

during November 2001 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 Stock Future 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 the impact of index futures on spot market volatility.

3.2 SCOPE OF THE STUDY

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

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

changes any other international markets affected the market during the same

period.

3.3 Objective of the study:

The introduction of derivatives products in Indian capital market has

not been very old, but today the notional trading values in the future

trading valves in the futures is ahead of cash market. Sometimes, the

notional trading value of the derivatives is higher than the cash market

trading values. The purpose of the study is to examine the impact of

introduction of stock futures on the underlying spot market volatility,

i.e., Nifty.


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3.4 DATA

3.4.1 Nature of data:

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

showing heteroskedastic nature.

3.4.2 Sources of data:

The data employed in the study consists of daily closing prices of 40 stocks traded

on the CNX Nifty. These data will be collected from National Stock Exchange

website.

3.4.3Data Period:

Data is collected for 4 years.

Before introduction: 9th Nov 1999 to 9th Nov 2001

After introduction: 10th Nov 2001 to 7th Nov 2003

3.5 HYPOTHESIS OF STUDY:

H0: Introduction of Stock Futures has no impact on the volatility of

Spot

Market.

H1: Introduction of Stock Futures has an impact on the volatility of

Spot

Market.


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3.6 STATISTICAL PROCEDURE

3.6.1 CALCULATION OF LOG NATURALS:

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

WhereRtis the daily return, Ptis the value of the security on day tand Pt-1 is the

value of the security on day t-1.

3.6.2 UNIT ROOT TEST:

A unit root test tests whether a unit root is present in an autoregressive model. The

most famous test is the Dickey-Fuller test. Another test is the Phillips-Perron test.

Theory of Stationarity:

Following are different ways of thinking about whether a time series variable Xt is

stationary or has a unit root:

In the AR (1) model, if F=1, then X has a unit root. If |F|


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Augmented Dickey-Fuller Test (Unit root testing)

In Statistics and econometrics, an Augmented Dickey-Fuller test (ADF) is a

test for a unit root in a time series sample. It is an augmented version of the

Dickey-Fuller testto accommodate some forms of serial correlation.

Testing Procedure

The testing procedure for the ADF test is the same as for the Dickey-Fuller test

but it is applied to the model.

Where is a constant, the coefficient on a time trend andp the lag order of the

autoregressive process. Imposing the constraints = 0 and = 0 corresponds tomodeling a random walk and using the constraint = 0 corresponds to modeling a

random walk with a drift. By including lags of the orderp the ADF formulation

allows for higher-order autoregressive processes. This means that the lag length p

has to be determined when applying the test. One possible approach is to test

down from high orders and examine the t-values on coefficients.

The unit root test is then carried out under the null hypothesis = 0 against the

alternative hypothesis of < 0. Once a value for the test statistic computed it can

be compared to the relevant critical value for the Dickey-Fuller Test. If the test

statistic is less than the critical value then the null hypothesis of = 0 is rejected

and no unit root is present.


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3.6.3 STANDARD DEVIATION:

The standard deviation of Log Natural returns is calculated using the following

methods:

WhereR is the average return over the period.

3.6.4 F- TEST:

F- Test = (Standard Deviation 1)2

(Standard Deviation 2)2

3.7 Actual collection of data: The data includes the following:

1) Two years prior to introduction of Stock Futures

2) Two years after the introduction of Stock Futures

3.8 Tools used for testing of hypothesis:

The following statistical tools were used to analyze the data:

1) Log Natural

2) Augmented Dickey Fuller Test (for stationarity)

3) Standard Deviation

4) F- Test


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3.9 Source of Secondary data:

Books and Journals

Capital Line

Internet

J Stor

3.10 Other software used for data analysis:

The following softwares were used for data analysis:

1) SPSS

2) E-VIEWS3) EXCEL SPREADSHEET


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EMPIRICAL RESULTS

Daily closing prices for 40 stocks of CNX Nifty were obtained from

www.nseindia.com over the period 9th

Nov 1999 to 9th

Nov 2003. The data

comprises 502 observations for each stock related to the period prior to the

introduction of Stock Future and the remaining 499 observations for each stock to

the period after the introduction of Stock Futures. Continuously compounded

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

daily closing price Pt, its return Rt is defined as log (Pt/Pt-1). All the return series

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

test. The data under consideration is stationary and unit root test doesnt exist.

The tables below show the calculations of monthly standard deviation of all 40

companies for prior and after introduction of stock futures. Then the average of

standard deviation is calculated for prior and after introduction is calculated. The

F -test is computed on the average standard deviation. If the F-test value is less

than tabulated value, the null hypothesis is accepted which implies that the

introduction of stock futures has no impact on spot market volatility. It can be

observed from the graph that the Post- futures volatility is more compared to Pre-

future period. This broadly suggests that the introduction of stock futures has notstabilized the spot market. The inference cannot be drawn from these figures

alone, as they are not supported by all statistical data.


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ABB (Monthly Standard Deviation):

ABB

DATE Before DATE After

Nov-99 0.06152 Nov-01 0.02451

Dec-99 0.03006 Dec-01 0.01283Jan-00 0.02967 Jan-02 0.012

Feb-00 0.04568 Feb-02 0.02673

Mar-00 0.03624 Mar-02 0.01979

Apr-00 0.03326 Apr-02 0.0189

May-00 0.02341 May-02 0.01889

Jun-00 0.02819 Jun-02 0.01764

Jul-00 0.02953 Jul-02 0.01368

Aug-00 0.02139 Aug-02 0.00737

Sep-00 0.01344 Sep-02 0.0117

Oct-00 0.02005 Oct-02 0.03845

Nov-00 0.02304 Nov-02 0.02201Dec-00 0.01734 Dec-02 0.01052

Jan-01 0.01996 Jan-03 0.01562

Feb-01 0.02185 Feb-03 0.01974

Mar-01 0.03823 Mar-03 0.01492

Apr-01 0.03084 Apr-03 0.01759

May-01 0.0297 May-03 0.01469

Jun-01 0.01562 Jun-03 0.0263

Jul-01 0.01322 Jul-03 0.02055

Aug-01 0.00895 Aug-03 0.23539

Sep-01 0.03528 Sep-03 0.02143

Oct-01 0.01057 Oct-03 0.02061

Avg 0.0265 Avg 0.0276

F test 1.0795

Interpretation:

If F-Test value is above 2.08 tabulated value = Significant

If F-Test value is below 2.08 tabulated value = Non-significant

Since F-Test value is less than tabulated value, null hypothesis is acceptedand there is no impact of stock futures on volatility of spot market.

ABB Share Price (Before)

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

1 27 53 79 105 131 157 183 209 235 261287 313 339 365 391 417 443 469 495

No. of Obsevat ions

ABB Share Price (After )

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400

No. o f Observat ions


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ACC (Monthly Standard Deviation):

ACC

DATE Before DATE After

Nov-99 0.0326 Nov-01 0.0252

Dec-99 0.0447 Dec-01 0.0189Jan-00 0.034 Jan-02 0.0295

Feb-00 0.0431 Feb-02 0.0286

Mar-00 0.0522 Mar-02 0.0198

Apr-00 0.0478 Apr-02 0.0111

May-00 0.0422 May-02 0.0202

Jun-00 0.0182 Jun-02 0.0107

Jul-00 0.0378 Jul-02 0.0161

Aug-00 0.0308 Aug-02 0.0145

Sep-00 0.0256 Sep-02 0.0162

Oct-00 0.0243 Oct-02 0.0159

Nov-00 0.0398 Nov-02 0.0162

Dec-00 0.0241 Dec-02 0.0158

Jan-01 0.023 Jan-03 0.0162

Feb-01 0.0218 Feb-03 0.0249

Mar-01 0.0622 Mar-03 0.019

Apr-01 0.0527 Apr-03 0.0142

May-01 0.035 May-03 0.0141

Jun-01 0.0201 Jun-03 0.0226

Jul-01 0.0232 Jul-03 0.0268

Aug-01 0.013 Aug-03 0.2292

Sep-01 0.0507 Sep-03 0.0274Oct-01 0.0279 Oct-03 0.0237

Avg 0.034 Avg 0.028

F test 0.67

Interpretation:


If F-Test value is below 2.08 tabulated value = Non-significantSince F-Test value is less than tabulated value, null hypothesis is accepted

and there is no impact of stock futures on volatility of spot market.

Acc Share Price (Before)

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381

No. o f Observat ion

ACC Share Price (After)

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400

No. o f Observat ion


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Arvind Mills (Monthly Standard Deviation):

Arvind MillsDATE Before DATE After

Nov-99 0.0174 Nov-01 0.0234

Dec-99 0.0376 Dec-01 0.0459

Jan-00 0.0383 Jan-02 0.0249

Feb-00 0.0438 Feb-02 0.0563

Mar-00 0.0373 Mar-02 0.031

Apr-00 0.048 Apr-02 0.0479

May-00 0.0541 May-02 0.0301

Jun-00 0.0447 Jun-02 0.0527

Jul-00 0.0181 Jul-02 0.0371

Aug-00 0.0251 Aug-02 0.0266

Sep-00 0.072 Sep-02 0.0299

Oct-00 0.0245 Oct-02 0.0156 Nov-00 0.0607 Nov-02 0.0289

Dec-00 0.0463 Dec-02 0.0211

Jan-01 0.035 Jan-03 0.0257

Feb-01 0.0481 Feb-03 0.0221

Mar-01 0.0524 Mar-03 0.0134

Apr-01 0.0307 Apr-03 0.0324

May-01 0.0451 May-03 0.0372

Jun-01 0.0364 Jun-03 0.0203

Jul-01 0.0208 Jul-03 0.0364

Aug-01 0.0321 Aug-03 0.2273Sep-01 0.0472 Sep-03 0.0297

Oct-01 0.0236 Oct-03 0.037

Avg 0.04 Avg 0.04

F test 1.03

Interpretation:



Since F-Test value is less than tabulated value, null hypothesis is accepted


Arvind Mills Share Price (Before)

-0 .1500

-0.1000

-0.0500

0.0000

0.0500

0.100 0

0.1500

0.2000

0.2500

1 2 9 57 8 5 113 14 1 16 9 19 7 2 25 2 53 2 81 3 09 33 7 3 65 3 9

No. of Observations

Arvind Mills Share Price (After)

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

1 23 45 67 89 111 133 155 177 199 221 243 265 287 309 331353 375 397



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BAJAJ AUTO (Monthly Standard Deviation) :

BAJAJ AUTODATE Before DATE After

Nov-99 0.0114 Nov-01 0.0158

Dec-99 0.0277 Dec-01 0.0159

Jan-00 0.0371 Jan-02 0.0258

Feb-00 0.0323 Feb-02 0.0213

Mar-00 0.039 Mar-02 0.0173

Apr-00 0.0182 Apr-02 0.0212

May-00 0.0144 May-02 0.0224

Jun-00 0.0124 Jun-02 0.0186

Jul-00 0.0136 Jul-02 0.0215

Aug-00 0.0106 Aug-02 0.0177

Sep-00 0.0095 Sep-02 0.0185

Oct-00 0.0398 Oct-02 0.0237 Nov-00 0.0189 Nov-02 0.0185

Dec-00 0.0264 Dec-02 0.0129

Jan-01 0.0376 Jan-03 0.0156

Feb-01 0.0254 Feb-03 0.0155

Mar-01 0.0283 Mar-03 0.0158

Apr-01 0.0219 Apr-03 0.0158

May-01 0.0283 May-03 0.0115

Jun-01 0.0307 Jun-03 0.0204

Jul-01 0.0234 Jul-03 0.02

Aug-01 0.02 Aug-03 0.2246

Sep-01 0.0144 Sep-03 0.0188

Oct-01 0.0253 Oct-03 0.0177

Avg 0.02 Avg 0.03

F test 1.303

Interpretation:





Bajaj Auto Share Price (Before)

-0.15

-0.1

-0.05

0

0.05

0.1

1 23 45 67 89 111 133 155 177 199 221 243 265 287 309 331 353 375

No. of Observ ations

Log

Naturals

Bajaj Auto Share Price (After)

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

1 24 47 70 93 116 139 162 185 208 231 254 277 300 323 346 369 392


Log

Natural


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BHEL (Monthly Standard Deviation):

BHELDATE Before DATE After

Nov-99 0.026 Nov-01 0.0221

Dec-99 0.0364 Dec-01 0.0218

Jan-00 0.0384 Jan-02 0.0219

Feb-00 0.0456 Feb-02 0.0431

Mar-00 0.05 Mar-02 0.0247

Apr-00 0.0467 Apr-02 0.0192

May-00 0.0382 May-02 0.0223

Jun-00 0.0263 Jun-02 0.0211

Jul-00 0.0441 Jul-02 0.0147

Aug-00 0.0209 Aug-02 0.0098

Sep-00 0.0444 Sep-02 0.0108

Oct-00 0.0186 Oct-02 0.0081 Nov-00 0.0357 Nov-02 0.0168

Dec-00 0.0511 Dec-02 0.0146

Jan-01 0.0302 Jan-03 0.0178

Feb-01 0.039 Feb-03 0.0236

Mar-01 0.052 Mar-03 0.0174

Apr-01 0.0478 Apr-03 0.0176

May-01 0.0251 May-03 0.0195

Jun-01 0.0269 Jun-03 0.0169

Jul-01 0.0436 Jul-03 0.0187

Aug-01 0.019 Aug-03 0.2286

Sep-01 0.0437 Sep-03 0.0224

Oct-01 0.0253 Oct-03 0.026

Avg 0.04 Avg 0.03

F test 0.603

Interpretation:





BHEL Share Price (Before)

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

0.2000

1 24 47 70 93 116 139 162 185 208 231 254 277 300 323 346 369 392


Log

Natural

BHEL Share Price

-0.1500

-0.1000

-0.0500

0.0000

0.0500

0.1000

0.1500

1 24 47 70 93 116 139 162 185 208 231 254 277 300 323 346 369 392

No. of Observations

Log

Natural


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BPCL(Monthly Standard Deviation) :

BPCLDATE Before DATE After

Nov-99 0.0444 Nov-01 0.0186

Dec-99 0.0385 Dec-01 0.0364

Jan-00 0.0283 Jan-02 0.0244

Feb-00 0.05 Feb-02 0.0444

Mar-00 0.0617 Mar-02 0.0229

Apr-00 0.0455 Apr-02 0.0225

May-00 0.0621 May-02 0.0322

Jun-00 0.0272 Jun-02 0.0276

Jul-00 0.0401 Jul-02 0.0241

Aug-00 0.0234 Aug-02 0.021

Sep-00 0.0352 Sep-02 0.0543

Oct-00 0.0353 Oct-02 0.0368 Nov-00 0.0333 Nov-02 0.0116

Dec-00 0.1586 Dec-02 0.0341

Jan-01 0.0366 Jan-03 0.0208

Feb-01 0.0523 Feb-03 0.0162

Mar-01 0.0556 Mar-03 0.0204

Apr-01 0.0483 Apr-03 0.0135

May-01 0.0225 May-03 0.022

Jun-01 0.0254 Jun-03 0.0129

Jul-01 0.0206 Jul-03 0.0217

Aug-01 0.0178 Aug-03 0.231Sep-01 0.0468 Sep-03 0.0275

Oct-01 0.0261 Oct-03 0.0289

Avg 0.04 Avg 0.03

F test 0.636

Interpretation:





BPCL Share Price (Before)

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 38

No. of Observat ions

BPCL Share Price (After)

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

1 23 45 67 89 111 133 155 177 199 221243 265 287 309 331 353 375 397

No. of Observations


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43

CIPLA (Monthly Standard Deviation):

CIPLADATE Before DATE After

Nov-99 0.03 Nov-01 0.0148

Dec-99 0.0319 Dec-01 0.0102

Jan-00 0.0396 Jan-02 0.0106

Feb-00 0.0322 Feb-02 0.0115

Mar-00 0.0563 Mar-02 0.0067

Apr-00 0.0457 Apr-02 0.0152

May-00 0.0416 May-02 0.0133

Jun-00 0.0331 Jun-02 0.0123

Jul-00 0.0459 Jul-02 0.0061

Aug-00 0.0207 Aug-02 0.0109

Sep-00 0.0205 Sep-02 0.0121

Oct-00 0.0297 Oct-02 0.0254 Nov-00 0.0265 Nov-02 0.0112

Dec-00 0.0322 Dec-02 0.0102

Jan-01 0.0148 Jan-03 0.0162

Feb-01 0.0185 Feb-03 0.0096

Mar-01 0.0259 Mar-03 0.0151

Apr-01 0.0392 Apr-03 0.0282

May-01 0.0232 May-03 0.0092

Jun-01 0.015 Jun-03 0.0142

Jul-01 0.0215 Jul-03 0.0212

Aug-01 0.0235 Aug-03 0.2317

Sep-01 0.0373 Sep-03 0.0182

Oct-01 0.029 Oct-03 0.0219

Avg 0.03 Avg 0.02

F test 0.574

Interpretation:





Cipla Share Price (Before)

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Log

Naturals

Cipla Share Price (Afte r)

-0.12

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

1 23 45 67 89 111 133 155 177 199 221243 265 287 309 331 353 375 397

No. of Observations


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44

COLGATE (Monthly Standard Deviation):

COLGATEDATE Before DATE After

Nov-99 0.01543 Nov-01 0.013

Dec-99 0.01583 Dec-01 0.0093

Jan-00 0.02886 Jan-02 0.0085

Feb-00 0.02864 Feb-02 0.0103

Mar-00 0.02692 Mar-02 0.0041

Apr-00 0.03766 Apr-02 0.0335

May-00 0.02546 May-02 0.0058

Jun-00 0.0191 Jun-02 0.0128

Jul-00 0.02136 Jul-02 0.0119

Aug-00 0.01823 Aug-02 0.0064

Sep-00 0.01333 Sep-02 0.0031

Oct-00 0.01684 Oct-02 0.0087 Nov-00 0.01352 Nov-02 0.006

Dec-00 0.01312 Dec-02 0.0123

Jan-01 0.01504 Jan-03 0.0056

Feb-01 0.0246 Feb-03 0.0093

Mar-01 0.01366 Mar-03 0.0071

Apr-01 0.02013 Apr-03 0.0096

May-01 0.01331 May-03 0.0106

Jun-01 0.00792 Jun-03 0.0289

Jul-01 0.01367 Jul-03 0.0215

Aug-01 0.0071 Aug-03 0.2258Sep-01 0.01744 Sep-03 0.0108

Oct-01 0.00723 Oct-03 0.0111

Avg 0.018 Avg 0.02

F test 1.2527

Interpretation:





Colgate Share Price (Before)

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

0.12

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Log

Natural

Colgate Share Prices (After)

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 23 45 67 89 111 133 155 177 199 221 243 265 287 309 331 353 375 39


Lo

g

Natural


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45

DABUR(Monthly Standard Deviation) :

DABURDATE Before DATE After

Nov-99 0.01877 Nov-01 0.0207

Dec-99 0.0388 Dec-01 0.0404

Jan-00 0.04699 Jan-02 0.0111

Feb-00 0.04671 Feb-02 0.0141

Mar-00 0.04935 Mar-02 0.0225

Apr-00 0.04564 Apr-02 0.0227

May-00 0.02831 May-02 0.0131

Jun-00 0.01787 Jun-02 0.015

Jul-00 0.02645 Jul-02 0.0191

Aug-00 0.01615 Aug-02 0.0154

Sep-00 0.02643 Sep-02 0.0076

Oct-00 0.02026 Oct-02 0.0057 Nov-00 0.47973 Nov-02 0.0083

Dec-00 0.02669 Dec-02 0.0087

Jan-01 0.01205 Jan-03 0.0206

Feb-01 0.02799 Feb-03 0.0119

Mar-01 0.03312 Mar-03 0.0148

Apr-01 0.02307 Apr-03 0.0203

May-01 0.02018 May-03 0.0224

Jun-01 0.01702 Jun-03 0.018

Jul-01 0.00888 Jul-03 0.0317

Aug-01 0.01516 Aug-03 0.2205

Sep-01 0.03167 Sep-03 0.0348

Oct-01 0.01475 Oct-03 0.0173

Avg 0.046 Avg 0.03

F test 0.3399

Interpretation:





Dabur Share Price (Before)

-2.5

-2

-1.5

-1

-0.5

0

0.5

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Log

Natural

Dabur Share Price (After)

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

0.12

1 23 45 67 89 111 133 155 177 199 221 243 265 287 309 331 353 375 39

No. of Observations

Log

Natural


46/78



46

DR REDDY (Monthly Standard Deviation):

DR REDDYDATE Before DATE After

Nov-99 0.03796 Nov-01 0.0362

Dec-99 0.04225 Dec-01 0.0159

Jan-00 0.04625 Jan-02 0.0154

Feb-00 0.05019 Feb-02 0.0233

Mar-00 0.07129 Mar-02 0.0158

Apr-00 0.05175 Apr-02 0.0163

May-00 0.04012 May-02 0.0224

Jun-00 0.03353 Jun-02 0.012

Jul-00 0.03778 Jul-02 0.0342

Aug-00 0.02206 Aug-02 0.0088

Sep-00 0.02582 Sep-02 0.0161

Oct-00 0.02239 Oct-02 0.023 Nov-00 0.024 Nov-02 0.0126

Dec-00 0.02061 Dec-02 0.0219

Jan-01 0.01581 Jan-03 0.0174

Feb-01 0.01281 Feb-03 0.0102

Mar-01 0.02883 Mar-03 0.0083

Apr-01 0.04356 Apr-03 0.0237

May-01 0.02206 May-03 0.0149

Jun-01 0.03061 Jun-03 0.0212

Jul-01 0.02729 Jul-03 0.0279

Aug-01 0.02647 Aug-03 0.2443Sep-01 0.02902 Sep-03 0.0185

Oct-01 0.1587 Oct-03 0.0287

Avg 0.038 Avg 0.03

F test 0.5592

Interpretation:





Dr Reddy Share Price (Before )

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379

No. of Observat ons

Dr Reddy Share Price (Afte r)

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400

No. o f Obse r v a t ions


47/78



47

ESSAR OIL (Monthly Standard Deviation):

Essar OilDATE Before DATE After

Nov-99 0.03519 Nov-01 0.0479

Dec-99 0.02939 Dec-01 0.0278

Jan-00 0.03295 Jan-02 0.0196

Feb-00 0.04345 Feb-02 0.0382

Mar-00 0.04905 Mar-02 0.035

Apr-00 0.06417 Apr-02 0.0242

May-00 0.03634 May-02 0.0681

Jun-00 0.03248 Jun-02 0.031

Jul-00 0.04101 Jul-02 0.0413

Aug-00 0.02676 Aug-02 0.0327

Sep-00 0.05524 Sep-02 0.0253

Oct-00 0.03467 Oct-02 0.0252 Nov-00 0.02054 Nov-02 0.0264

Dec-00 0.02377 Dec-02 0.0249

Jan-01 0.02957 Jan-03 0.0125

Feb-01 0.0512 Feb-03 0.0322

Mar-01 0.08201 Mar-03 0.0243

Apr-01 0.03853 Apr-03 1.0993

May-01 0.02799 May-03 0.0609

Jun-01 0.0308 Jun-03 0.056

Jul-01 0.01711 Jul-03 0.0662

Aug-01 0.03172 Aug-03 0.2512

Sep-01 0.04249 Sep-03 0.0523

Oct-01 0.0644 Oct-03 0.0394

Avg 0.039 Avg 0.09

F test 5.2808

Interpretation:



Since F-Test value is more than tabulated value, null hypothesis is rejected

and there is impact of stock futures on volatility of spot market.

Essaar Oil Share Price (Before)

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381


Essar Oil Share Price (After )

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400



48/78



48

GLAXO (Monthly Standard Deviation):

GLAXODATE Before DATE After

Nov-99 0.0144 Nov-01 0.0232

Dec-99 0.02149 Dec-01 0.0168

Jan-00 0.03226 Jan-02 0.0164

Feb-00 0.03927 Feb-02 0.0216

Mar-00 0.03493 Mar-02 0.0159

Apr-00 0.03499 Apr-02 0.0281

May-00 0.03334 May-02 0.0256

Jun-00 0.04018 Jun-02 0.0168

Jul-00 0.02847 Jul-02 0.0185

Aug-00 0.01795 Aug-02 0.0088

Sep-00 0.01477 Sep-02 0.0101

Oct-00 0.02619 Oct-02 0.0153 Nov-00 0.01264 Nov-02 0.018

Dec-00 0.01566 Dec-02 0.0137

Jan-01 0.01013 Jan-03 0.0098

Feb-01 0.03159 Feb-03 0.0155

Mar-01 0.02578 Mar-03 0.0113

Apr-01 0.02532 Apr-03 0.0147

May-01 0.02583 May-03 0.0134

Jun-01 0.02912 Jun-03 0.0127

Jul-01 0.02432 Jul-03 0.0228

Aug-01 0.00804 Aug-03 0.2369Sep-01 0.03318 Sep-03 0.0194

Oct-01 0.01737 Oct-03 0.0132

Avg 0.025 Avg 0.03

F test 1.0726

Interpretation:





Glaxo Share Price (Before )

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Glaxo Share Price (After )

-0.1

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

1 23 45 67 89 111 133 155 177 199 221 243 265 287 309 331 353 375 397

No. of Observat ons


49/78



49

GRASIM (Monthly Standard Deviation):

GRASIMDATE Before DATE After

Nov-99 0.0134 Nov-01 0.0193

Dec-99 0.0392 Dec-01 0.0263

Jan-00 0.03906 Jan-02 0.0117

Feb-00 0.04384 Feb-02 0.0164

Mar-00 0.05117 Mar-02 0.012

Apr-00 0.04196 Apr-02 0.009

May-00 0.05954 May-02 0.0201

Jun-00 0.03255 Jun-02 0.0123

Jul-00 0.03707 Jul-02 0.0162

Aug-00 0.0368 Aug-02 0.0075

Sep-00 0.02552 Sep-02 0.0105

Oct-00 0.03884 Oct-02 0.0136 Nov-00 0.0306 Nov-02 0.0127

Dec-00 0.04659 Dec-02 0.0176

Jan-01 0.02619 Jan-03 0.0123

Feb-01 0.03343 Feb-03 0.0111

Mar-01 0.04075 Mar-03 0.01

Apr-01 0.04646 Apr-03 0.0153

May-01 0.02373 May-03 0.0148

Jun-01 0.01949 Jun-03 0.0343

Jul-01 0.02512 Jul-03 0.0166

Aug-01 0.01762 Aug-03 0.2268

Sep-01 0.03283 Sep-03 0.0234

Oct-01 0.0198 Oct-03 0.0275

Avg 0.034 Avg 0.02

F test 0.529

Interpretation:





Grasim Share Price (Before)

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Grasim Share Price (After)

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400



50/78



50

GUJARATH AMBUJA CEMENT (Monthly Standard Deviation):

GUJAMBCEM

DATE Before DATE After Nov-99 0.0104 Nov-01 0.0129

Dec-99 0.15848 Dec-01 0.0253

Jan-00 0.0466 Jan-02 0.0241

Feb-00 0.03051 Feb-02 0.0361

Mar-00 0.04145 Mar-02 0.016

Apr-00 0.04111 Apr-02 0.0237

May-00 0.04283 May-02 0.0156

Jun-00 0.02218 Jun-02 0.004

Jul-00 0.03706 Jul-02 0.0093

Aug-00 0.03711 Aug-02 0.0128Sep-00 0.02112 Sep-02 0.0168

Oct-00 0.02679 Oct-02 0.0123

Nov-00 0.02566 Nov-02 0.01

Dec-00 0.0281 Dec-02 0.0119

Jan-01 0.022 Jan-03 0.0151

Feb-01 0.03241 Feb-03 0.0138

Mar-01 0.04024 Mar-03 0.0125

Apr-01 0.03731 Apr-03 0.0079

May-01 0.02991 May-03 0.0136

Jun-01 0.01097 Jun-03 0.0159

Jul-01 0.01481 Jul-03 0.0177Aug-01 0.01087 Aug-03 0.228

Sep-01 0.02966 Sep-03 0.026

Oct-01 0.01995 Oct-03 0.0214

Avg 0.034 Avg 0.03

F test 0.5438

Interpretation:





Gujrath Ambuja Cement Share Price (Before)

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379


Log

Natural

Gujrath Ambuja Cement Share Price (After)

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400



51/78



51

HDFC BANK (Monthly Standard Deviation):

HDFCBANKDATE Before DATE After Nov-99 0.03515 Nov-01 0.01

Dec-99 0.04716 Dec-01 0.017

Jan-00 0.04136 Jan-02 0.0167

Feb-00 0.04329 Feb-02 0.0245

Mar-00 0.04324 Mar-02 0.0126

Apr-00 0.05714 Apr-02 0.0115

May-00 0.02348 May-02 0.0136

Jun-00 0.0236 Jun-02 0.0119

Jul-00 0.02561 Jul-02 0.0119

Aug-00 0.03683 Aug-02 0.0058

Sep-00 0.03453 Sep-02 0.0184

Oct-00 0.01411 Oct-02 0.0102 Nov-00 0.01727 Nov-02 0.0086

Dec-00 0.01787 Dec-02 0.0183

Jan-01 0.01884 Jan-03 0.0171

Feb-01 0.02453 Feb-03 0.0092

Mar-01 0.03885 Mar-03 0.0172

Apr-01 0.01628 Apr-03 0.0155

May-01 0.01381 May-03 0.0137

Jun-01 0.02751 Jun-03 0.0168

Jul-01 0.01668 Jul-03 0.031

Aug-01 0.01208 Aug-03 0.2285

Sep-01 0.03612 Sep-03 0.0155

Oct-01 0.01609 Oct-03 0.0233

Avg 0.028 Avg 0.02

F test 0.722

Interpretation:





HDFC Bank Share Prices (Befor e)

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381

No. o f Observat ons

HDFC Bank Share Price (After)

-0.08

-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

1 22 43 64 85 106 127 148 169 190 211 232 253 274 295 316 337 358 379 400



52/78



52

HDFC (Monthly Standard Deviation):

HDFCDATE Before DATE After

Nov-99 0.02763 Nov-01 0.0117

Dec-99 0.03653 Dec-01 0.0079

Jan-00 0.02811 Jan-02 0.013

Feb-00 0.04782 Feb-02 0.0194

Mar-00 0.04631 Mar-02 0.0126

Apr-00 0.03979 Apr-02 0.0134

May-00 0.04467 May-02 0.0118

Jun-00 0.02495 Jun-02 0.0211

Jul-00 0.04611 Jul-02 0.0152

Aug-00 0.01788 Aug-02 0.0146

Sep-00 0.02454 Sep-02 0.0115

Oct-00 0.01387 Oct-02 0.0112 Nov-00 0.01775 Nov-02 0.0107

Dec-00 0.01081 Dec-02 0.1582

Jan-01 0.03159 Jan-03 0.0092

Feb-01 0.02065 Feb-03 0.0119

Mar-01 0.03617 Mar-03 0.0151

Apr-01 0.02008 Apr-03 0.0227

May-01 0.02441 May-03 0.0191

Jun-01 0.01407 Jun-03 0.0196

Jul-01 0.01315 Jul-03 0.0281

Aug-01 0.01538 Aug-03 0.2243

Sep-01 0.04149 Sep-03 0.0245

Oct-01 0.02679 Oct-03 0.0236

Avg 0.028 Avg 0.03

F test 1.1862

Interpretation:





HDFC Share Price (Before)

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381


HDFC Share Price (After )

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

1 2 9 57 8 5 113 14 1 16 9 19 7 2 25 2 53 2 81 30 9 3 37 3 6 5 3 93

No. of Observations


53/78



53

HERO HONDA (Monthly Standard Deviation):

HEROHONDADATE Before DATE After

Nov-99 0.02135 Nov-01 0.12888

Dec-99 0.037566 Dec-01 0.01928

Jan-00 0.029683 Jan-02 0.0294

Feb-00 0.022306 Feb-02 0.03164

Mar-00 0.025893 Mar-02 0.03099

Apr-00 0.027902 Apr-02 0.0177

May-00 0.037436 May-02 0.02412

Jun-00 0.032869 Jun-02 0.01949

Jul-00 0.028086 Jul-02 0.02065

Aug-00 0.044448 Aug-02 0.02257

Sep-00 0.041322 Sep-02 0.02016

Oct-00 0.016282 Oct-02 0.03898 Nov-00 0.014536 Nov-02 0.02551

Dec-00 0.042296 Dec-02 0.02182

Jan-01 0.00846 Jan-03 0.0139

Feb-01 0.02841 Feb-03 0.02616

Mar-01 0.024006 Mar-03 0.03105

Apr-01 0.013224 Apr-03 0.03141

May-01 0.015002 May-03 0.02102

Jun-01 0.020783 Jun-03 0.02009

Jul-01 0.040002 Jul-03 0.02409

Aug-01 0.353278 Aug-03 0.23338 Sep-01 0.059998 Sep-03 0.02275

Oct-01 0.026856 Oct-03 0.02665

Avg 0.0422 Avg 0.038

F test 0.79392

Interpre

Abhishek Saraff-05-Stock Futures on Spot Market Volatility

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