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A STUDY ON THE ROLE OF FUTURE AND OPTIONS INSTRUMENTS WITH REFERENCE TO BOMBAY STOCK EXCHANGE

A Project Submitted to University of Mumbai for partial completion of the degree of Bachelor in Commerce (Accounting and Finance) Under the Faculty of Commerce By VIMAL KISHOR VEKARIYA

Under the Guidance of

PROF. ARPITA VARTAK DR. BABASAHEB AMBEDKAR COLLEGE

MARCH 18-19

A STUDY ON THE ROLE OF FUTURE AND OPTIONS INSTRUMENTS WITH REFERENCE TO BOMBAY STOCK EXCHANGE

A Project Submitted to University of Mumbai for partial completion of the degree of Bachelor in Commerce (Accounting and Finance) Under the Faculty of Commerce By VIMAL KISHOR VEKARIYA

Under the Guidance of

PROF. ARPITA VARTAK DR. BABASAHEB AMBEDKAR COLLEGE

MARCH 18-19

INDEX CH. NO

PARTICULARS

PAGE.NO.

CHAPTER NO : 1 INTRODUCTION TO BSE……………………………………………..……...2 CHAPTER NO 2: RESEARCH METHODOLOGY…………………………………….............10 CHAPTER NO 3: LITERATURE REVIEW……………………………………………..............15 CHAPTER NO 4: DATA ANALYSIS & FINDINGS…………………………………………...29 CHAPTER NO 5 : CONCLUSION……………………………………………..............................61 CHAPTER NO 6 : BIBLOGRAPHY ............................................................................... …62

DR. BABASAHEB AMBEDKAR AND ADV.GURUNATH KULKARNI COLLEGE OF SCIENCE AND COMMERCE. NR. DIWANMAN TALAO, VASAI WEST

Certificate

This is to certify that Ms/Mr VIMAL KISHOR VEKARIYA has worked and duly completed her/his Project Work for the degree of Bachelor in Commerce (Accounting & Finance) under the Faculty of Commerce in the subject of FINANCIAL ANALYSIS and her/his project

is

entitled, “ A STUDY ON THE ROLE OF

FUTURES AND OPTION INSTRUMENT WITH REFERENCE TO BOMBAY STOCK EXCHANGE” under my supervision. I further certify that the entire work has been done by the learner under my guidance and that no part of it has been submitted previously for any Degree or Diploma of any University. It is her/ his own work and facts reported by her/his personal findings and investigations.

Name and Signature of Seal of the College

Date of submission:

Guiding Teacher

Declaration by learner I the undersigned Miss / Mr.

VIMAL KISHOR VEKARIYA

here by,

declare that the work embodied in this project work titled “ A STUDY ON THE ROLE OF FUTURES AND OPTION INSTRUMENT WITH REFERENCE TO BOMBAY STOCK EXCHANGE ”, forms my own contribution to the research work carried out under the guidance of PROF. ARPITA VARTAK is a result of my own research work and has not been previously submitted to any other University for any other Degree/ Diploma to this or any other University. Wherever reference has been made to previous works of others, it has been clearly indicated as such and included in the bibliography. I, here by further declare that all information of this document has been obtained and presented in accordance with academic rules and ethical conduct.

Name and Signature of the learner

Certified by Name and signature of the Guiding Teacher

Acknowledgment To list who all have helped me is difficult because they are so numerous and the depth is so enormous. I would like to acknowledge the following as being idealistic channels and fresh dimensions in the completion of this project. I take this opportunity to thank the University of Mumbai for giving me chance to do this project. I would like to thank my Principal, Y.K. THOMBARE for providing the necessary facilities required for completion of this project. I take this opportunity to thank our Coordinator PROF. DEVANG ASHAR, for her moral support and guidance. I would also like to express my sincere gratitude towards my project guide PROF. ARPITA VARTAK. whose guidance and care made the project successful.

I would like to thank my College Library, for having provided various reference books and magazines related to my project. Lastly, I would like to thank each and every person who directly or indirectly helped me in the completion of the project especially my Parents and Peers who supported me throughout my project.

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CHAPTER 1 : INTRODUCTION TO BOMBAY STOCK EXCHANGE

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INTRODUCTION- BOMBAY STOCK EXCHANGE When it comes to Indian Stock Market , the first thing which comes to one’s mind is the two prominent exchange board of India which is NSE and BSE. How about we begin with the meaning of a stock trade? The most broadly comprehended and acknowledged meaning of a stock exchange is that it is a regulated and organized place where investors can buy and sell stocks, bonds, and other securities. In India, the two major stock exchanges are the NSE and BSE.However, trade is not tied in to any physical location and happens electronically. These two are the greatest stock trades that rule securities exchange interest in India. All things considered, there are clear contrasts between the two, which can affect your choice to contribute by means of the BSE or the NSE. Let’s start with the definition of a stock exchange. The most widely understood and accepted definition of a stock exchange is that it is a regulated and organized place where investors can buy and/or sell stocks, bonds, and other securities. In India, the two big stock exchanges are the NSE and BSE. Usually, there’s a central location for record keeping. However, trade is not tied in to any physical location and happens electronically. These two are the biggest stock exchanges that dominate stock market investment in India. That said, there are clear differences between the two, which can impact your decision to invest via the BSE or the NSE.

BSE is the oldest stock exchange not only in India, but also in Asia. NSE, on the other hand, is larger than BSE in terms of daily turnover and number of trades that happen on the index. BSE’s index is known by the name SENSEX (Sensitive Index) which shows 30 top trading companies. Nifty (National Fifty) is the index of NSE, displays 50 most traded companies. 3|Page

BSE started as an Association of persons in 1875, which was accredited as a stock exchange in 1957. NSE was founded in 1992, as a tax paying company, but later on, in 1993 it was recognized as a Stock Exchange.

In terms of market capitalization, BSE ranks the 10th in the world whereas NSE ranks 11th. BSE has more than 6000 companies listed on it, while NSE has more than 1600 companies listed on it.

BSE has raised capital by issuing its shares, which are traded on the NSE. However, NSE is still a private limited company, which is getting ready to come up soon with its IPO.

A look at the indices gives us a good picture of the status of the markets. Both NSE and BSE have different types of indices such as broader, sectorial, thematic, and strategic indices.

Broader indices capture the broader picture of the markets. Sectoral indices tell you the status of a specific sector. In case of NSE, examples of broader indices include Nifty 100, Nifty 200, Nifty 500, Nifty Midcap 50, and Nifty SML 100. Sectoral indices of the NSE include bank, auto, FMCG, media, IT, metal, and pharma.

In case of BSE, broader indices include S&P BSE Largecap, Allcap, Midcap select index, and smallcap. Sectoral indices at the BSE include S&P BSE Bankex, IT, PSU, and metal. There are also special indices such as the S&P BSE IPO, which tracks all the IPOs. There is the S&P BSE SME IPO, which tracks SME IPOs. There are also volatility indices in the BSE.

In case of liquidity, NSE is a clear winner, since volumes traded in NSE are much higher compared with BSE. Thus, intraday traders generally prefer NSE. On the other hand, BSE could be a good option for long-term investors. However, for intraday traders who trade on leverage, low volumes on BSE could be a problem. For instance, volume of HDFC shares traded on the NSE on May 05, 2017 was 23 lakhs whereas it was only 1.32 lakhs on the BSE for HDFC. In case of NSE, the benchmark index is Nifty, which is made of major 50 stocks listed on it. In case of the BSE, the benchmark index is the Sensex, which is made of major 30 stocks listed on it. These indices are reviewed periodically and the stocks that do not satisfy the laid down criteria are replaced. 4|Page

ABOUNT BOMBAY STOCK EXCHANGE (BSE) On the basis of registered members, it stood first in the list of top stock exchanges across the world. It offers a diversified range of services in various areas like depository services through CDSL (Central Depository Services Limited), risk management, market data services, etc.

Bombay Stock Exchange Limited is the oldest stock exchange in Asia with a rich heritage. Popularly known as "BSE", it was established as "The Native Share & Stock Brokers Association" in 1875. It was the first stock exchange in the country to obtain permanent recognition in 1956 from the Government of India under the Securities Contracts (Regulation) Act, 1956. Earlier an Association of Persons (AOP), the Exchange is now a demutualized and corporatized entity incorporated under the provisions of the Companies Act, 1956, pursuant to the BSE (Corporatisation and Demutualization) Scheme, 2005 notified by the Securities and Exchange Board of India (SEBI). SENSEX is introduced, as a first equity index in 1986 to provide a base for identifying the top 30 trading companies of the exchange, in more than 10 sectors. Bombay Stock Exchange Limited received its Certificate of Incorporation on 8th August, 2005 and Certificate of Commencement of Business on 12th August, 2005. The Exchange has succeeded the business and operations of BSE on going concern basis and its recognition as an Exchange has been continued by SEBI. BSE Institute Limited is one of the renowned capital market educational institute of Bombay stock Exchange.

Members

The BSE has over 874 members-brokers across the country, The initial joining fee for a member at BSE is Rs. 90 Lakhs

Listing

Listing means formal admission of a security to the trading platform of the Exchange. In BSE, the 5|Page

securities may be of any public limited company, Central or State Government, quasi governmental and other financial institutions/corporations, municipalities, etc. The objectives of listing are mainly to :provide liquidity to securities; mobilize savings for economic development; protect interest of investors by ensuring full disclosures. The Exchange has a separate Listing Department to grant approval for listing of securities of companies in accordance with the provisions of the Securities Contracts (Regulation) Act, 1956, Securities Contracts (Regulation) Rules, 1957, Companies Act, 1956, Guidelines issued by SEBI and Rules, Bye-laws and Regulations of the Exchange. A company intending to have its securities listed on the Exchange has to comply with the listing requirements prescribed by the Exchange. Some of the requirements are: ➢ Minimum Listing Requirements for new companies ➢ Minimum Listing Requirements for companies listed on other stock exchanges ➢ Minimum Requirements for companies delisted by this Exchange seeking relisting of this Exchange ➢ Permission to use the name of the Exchange in an Issuer Company's prospectus ➢ Submission of Letter of Application ➢ Allotment of Securities ➢ Trading Permission ➢ Requirement of 1% Security ➢ Payment of Listing Fees ➢ Compliance with Listing Agreement ➢ Cash Management Services (CMS) - Collection of Listing Fees

Indices

The main Index of BSE is SENSEX. The other indices at BSE are: BSE 500, BSE 100, BSE 200, BSE PSU, BSE MIDCAP, BSE SMLCAP, BSE BANKEX, BSE Teck, BSE Auto, BSE Pharma, BSE Fast Moving Consumer Goods (FMCG), BSE Consumer Durables (SYMBOL: Cons Dura), BSE Metal.

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FUNCTIONS OF BSE Bombay Stock Exchange – BSE is the oldest stock exchange in India. It was established in 1875 under the name “The Native Share and Stock Broker Association.”

- It functions as the first level regulator in the security market.

- It monitors mechanisms which may detect manipulations in the stock market.

Prior to that brokers and traders would gather under banyan trees to conduct transactions. BSE functions as the first-level regulator in the securities market, providing monitoring and surveillance mechanisms that are able to detect irregularities and manipulations in stock prices. 7|Page

The Bombay Stock Exchange (BSE) is Asia's oldest stock exchange. Based in Mumbai, India, BSE was established in 1875 as the Native Share & Stock Brokers' Association. Prior to that brokers and traders would gather under banyan trees to conduct transactions.

BSE functions as the first-level regulator in the securities market, providing monitoring and surveillance mechanisms that are able to detect irregularities and manipulations in stock prices. The Exchange also provides counter-party risk management in all transactions that take place on its trading platform through its clearing and settlement services. Shares of more than 5,000 companies are traded on BSE. In addition to equity and debt, the Exchange allows for trading of mutual fund units and derivatives

Bombay Stock Exchange was recognized as an exchange under the Securities Contracts (Regulation) Act in 1957. Its benchmark index, the Sensitive Index (Sensex) was launched in 1986. In 1995, the BSE launched its fully automated trading platform called BSE On-Line Trading system (BOLT) which fully replaced the open outcry system.

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MCX–NCDEX

In 2005, the Exchange changed from being simply an association of brokers to became a corporate entity. The administrative structure of the Exchange is headed by a board of directors, below which is a governing council and management that presides over its day-to-day functioning.

India you have two options where you can invest your money for trading with stocks. One is Indian Share Market and the other one is Indian commodity market. Indian commodity market is not much experienced but in between some couple of years it has attracted the investors a large. To trade with the Indian commodity market there are some tips or rules that you need to follow. These are as follows:

Account: If you want to trade with the commodity exchange the first and foremost thing you need to do is to open an account in either MCX or in NCDEX. After opening the account you can choose the sectors or commodities e.g. Metal, Energy, Commodities, Fuel, Oil.

Concept about the Market: The things that is most vital for you before start trading is to gather information about the market where you are in. These two commodity markets are having different tips and formats that you have to learn before trade with.

Contracts: The next responsibility of yours is to make some contracts (normally three to six) for trading which will have certain time limit. After that time these contracts will be invalid or become void. Through these contracts you can buy or sale or do both simultaneously in the exchange. Basically the commodity stocks are fixed with the margin prices that are fixed by the market itself. It has a range of 5-20 percent in which you can play with. This margin price will be changed or vary while these commodities are become most speculative. These are some simple tips that you need to maintain while you trade with the MCX or with NCDEX. But always remember that to trade with the commodity market you can earn safe and some extra profit than the stock market.

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CHAPTER 2 : RESEARCH METHODOLOGY

METHODOLOGY Study Period: The present study covers a period of Nineteen years i.e. from 1995 to 2013. For the purpose of detailed analysis, the study period is divided into three sub periods 1. Pre introduction of derivatives period(1995 to 2000) 2. Post introduction period-I (2000 to 2006) 3. Post introduction period-II (2006-2013). Each sub period covers five years and the analysis is 10 | P a g e

made by taking both short-term intervals as well as long-term intervals within these periods. Short intervals range from one month to one year. Long intervals range from two years to five years. For instance, to assess the impact of derivatives on volatility during short intervals, comparison is made between one month, two months, three months, six months, nine months and one year of pre periods with the corresponding post periods in the short intervals. Similarly, in the long intervals the comparison is made between two years, three years, and four years of pre periods with the corresponding interval periods in the post introduction. Further, during the long intervals, the comparison is also made between the volatility during the five years before introduction with the two post sub periods of five years. To study the impact of non-price variables in index options contracts three sub periods have been considered. First sub period from July 2001 to December 2001, 2. Second sub period from January 2006 to June 2006 and 3. Third sub period from July 2011 to Dec December 2011, comprising a total of Eighteen months (excluding the expiration day). To assess the impact of Stock Futures and Stock Options on stock market volatility, 10 industrial groups out of 13 industrial groups in which derivatives trading is permitted have been chosen. These industrial sectors are Banking, FMCG, Infrastructure,

Pharmaceuticals,

Telecommunication,

Finance,

Information

Technology,

Petrochemicals, Manufacturing and Engineering. For the purpose of detailed analysis, two companies from each of these industrial groups have been selected. The companies selected for detailed analysis for futures and options are different. The purpose behind in selecting two separate set of companies to study the impact of futures and options is the basic difference between the nature of these instruments. While the Future contracts are binding contracts the execution of which is obligatory, the execution of option contracts is not obligatory. But, care has been taken to see that the two sets of companies are representative of the respective industrial sectors. The market capitalisation weightage of the selected companies for impact study of futures is about 40% and the market capitalisation weightage of the selected companies for studying the impact of options is about 21per cent in total market capitalisation of NIFTY INDEX as on 29th June 2012. Hence, the weightage of selected companies for the study on futures and options put together is about 61%. While selecting these companies care has been taken to see that permission for derivatives trading in these companies is almost from the date of 11 | P a g e

launching/nearer to the date of launching of derivatives in India. Care also has been taken to see that the selected companies are among the top five in terms of turnover in the Derivative trading in the respective industrial sectors.

The selected companies are shown below sector wise: Sector Name

BANKS

Company Name

Company Name

(Futures)

(Options)

State Bank of India

ICICI Bank Ltd Hindustan Unilever ltd.

MCG

ITC Ltd.

INFRASTRUCTURE

Reliance Infrastructure

Jaiprakash Associates

PHARMACEUTICALS

Ranbaxy Laboratories LTD.

Cipla Ltd.

TELECOMMUNICATION

Mahanagar Telephone Nigam Ltd

Bharti Airtel Ltd

FINANCE

Housing Development & Finance Reliance Capital Ltd. Corporation LTD.

INFORMATION

Infosys Technologies

TECHNOLOGY

Ltd.

PETROCHEMICALS

Reliance Petroleum Ltd

Wipro Ltd

Oil & Natural Gas Corporation Ltd

MANUFACTURING

Tata Steel Limited

Tata Motors Ltd

ENGINEERING

Larsen & Toubro Ltd.

Praj Industries Ltd

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Sample: To assess the impact of Index Futures and Index Options on Stock Market volatility, S&P CNX Nifty of NSE is selected as it constitute more than three-fourth of the total turnover of Derivatives trading in India. To assess the impact of Stock Futures and Stock Options, the daily opening, high, low and closing prices of respective stocks have been taken for the study.

Data collection: The study is based mainly on secondary data, which have been collected from various websites of NSE, BSE, SEBI and selected companies. The opening, high, low and closing prices of S&P CNX Nifty index and opening, high, low and closing prices of selected individual Stock were collected from the official website of NSE. Data on turnover in derivative instruments at NSE were collected from various monthly and yearly bulletins of SEBI. The data regarding the non-price variables has been taken from the daily bhavcopy posted on the NSE website which provides all the market information on call and put options traded on different stocks during the day that include option premium (open, high, low and close), trading volume and open interest at each strike price.

Statistical tools of analysis: The collected data have been scrutinized to measure the volatility in CNX NIFTY and selected stock prices. Four types of volatility in stock prices – open-to-open, close-to-close, high-low and open to close have been calculated for both short and long intervals before and after the introduction of derivatives. For measuring the inter-day volatility, variations between open-to-open prices and Close to close prices have been calculated by using the statistical measure of standard deviation. For measuring intra-day volatility, variations between high-low prices and the open to close prices have been calculated by applying the Parkinson’s Model and Garman and Klass Model respectively. The data have been tested by using the statistical tool F-test to observe the significant levels of impact. The inter relationship between the net open interest and trading volume in Option market and the prices in underlying cash market have been measured using the technique of Granger’s Causality test by many researchers in the past. But, in the present study, a simple and widely accepted methodology used by Bhuyan and Choudhury (2001), Bhuyan and Yan (2002) and recently by Srivastava (2003) have been 13 | P a g e

taken into consideration. The terms and notations applied in the methodology of the present study are quite same as used in these studies. The notations which have been applied for two predictors-volume based predictor and open interest based predictor respectively are VCit for call option trading volume and VPjtfor put option trading volume. Simultaneously the notations OCit and OPjt respectively have been applied for call net open interest and put net open interest at time ‘t’ with the strike price X Ci and XPj respectively. The natural logarithms of all the variable have been used to account for the hetroscedasticity, i.e. unequal variance among the variables. Now, in order to find out the relative significance of volume-based predictors and open interest based predictors separately in the matter of price prediction in underlying cash market, the following regression equations have been used: ln IT = α0 + α1 ln It + α2 ln OCt + α3 ln OPt + εt

ln IT = α0 + α1 ln It + α2 ln VCt + α3 ln VPt + εt

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CHAPTER 3 : LITERATURE REVIEW

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Abhay and Abhyankar23 (1998) made an investigation on linear and nonlinear Granger Causality. The main purpose of this study was to tie together of Dwyer, Locke and Yu (1996) and explore further the nature of the nonlinear of causal relationship between the index futures and the cash market in U.K. Back and Brock test, Granger Causality test and ARMA model were used in its empirical analysis as tools to reveal the objectives. The data set consisted of intraday price histories for four FTSE 100 index futures contracts maturing in March 92, June 92, Sept 92 and the FTSE 100 index recorded minutes by minutes during 1992. The FTSE cash index series exhibited high positive auto correlation at the first lag in each period with statistically significant positive autocorrelation up to lag 6 during some futures contracts periods. The results of the linear Granger Causality test based on the multivariate regression index using both raw and AR filtered cash index return indicated that a high degree of contemporaneous correlation between the cash and futures contracts. Jacobs and Onochie24 (1998) revealed that there is a positive relationship between trading volume and price volatility, by measuring the price changes in conditional heteroskedasticity in international financial futures markets by applying bivariate GARCH(1,1). The underlying products are interest rate assets representing investments in various international money and bond markets of Sterling, Eurodollar, U.S. Treasury bond, German Government bond (Bund), 3-month European Currency Unit (ECU), and the Euro mark. The result suggest that there is a strong evidence of second-order dependence in the joint return and trading volume process for various international financial futures markets and the level of trading volume positively influences the conditional variance of futures price change. It also inferred that the issue of time varying volatility is of importance to option pricing. The implication of these findings that futures price changes and volume are not only jointly distributed, but also influences price volatility, can guide theorists and practitioners alike in re-thinking the pricing relationships for financial futures. Joshua Turkinton and David Walsh25 (1999) made an investigation on price discovery and causality in the Australian share price index futures markets. This study aimed to address the extend and timing of lead lag relationship between share price index futures and the underlying spot index. The sample period of the study ran from 3rd January 1995 to 21st December 1995 where the sample was drawn every 5 minutes. Simple Cost and Carry method, Co-integration test, ARMA model and simple Granger Causality test were employed for the analysis of the 16 | P a g e

study. The causality tests results indicated that bi-directional causality among the variables and authors found that an index shop appears to induce a very large response in the futures. Cao26 (1999) studies the effect of derivative assets on information acquisition and price behavior in a rational expectation equilibrium. Firstly, his results show that introduction of options performs market completion function, however, additional new option trading will have less effect on the price of underlying asset. Secondly, he concludes that introduction of derivatives reduces price volatility as price becomes a less biased estimate of the asset payoff due to more information collection. Thirdly, the informational content of future earnings announcements decreases after the introduction of option trading as information collection is more intensive before public announcement. This can be proved from the fact that there is an increase in the number of analysts covering the stock and rise in institutional holding after the listing of options. Finally, as regards the volume effect of options, he cautioned that the effect on trading volume in underlying asset market would depend upon the kind of derivative asset introduced in the market. He expects the liquidity of underlying asset to increase after the commencement of option trading. Gulen and Mayhew27 (2000) examine stock market volatility before and after the introduction of index futures trading in twenty-five countries, using various GARCH models augmented with either additive or multiplicative dummy. Their statistical model takes care of asynchronous data, conditional heteroskedasticity, asymmetric volatility responses, and the joint dynamics of each country’s index with the world market portfolio. They found that futures trading is related to an increase in conditional volatility in the U.S. and Japan, but in nearly every other country, no significant effect could be found. Joel Hasbrouck28 (2001) studied on intraday price formation in US equity index markets. This study empirically investigated in the price discovery of US equity index market in the new environment where the mirror of index with exchange traded funds, electronically traded markets, small denomination futures contracts and a family of sector ETF that break the index into nine components. This paper assessed the importance of the step by step development of US equity markets by considering the NASDAQ 100 index, EFT futures contracts and S&P 500 index as the sample for the analysis. Co-integration, Vector Error Correction Model and VAR 17 | P a g e

Models result suggested that for the S&P 500 and NASDAQ 100 index, price discovery was dominated by futures trading. The S&P 500 sector funds were EFTs that were constructed on industry lines and could be used to replicate the overall index. Isakov and Morard29(2001) in their paper have investigated the performance of option strategies especially covered call strategy on Swiss exchange during 1989-1996. The authors have used stochastic dominance and modified beta approaches rather than mean-variance model to compare the performance of portfolio because in their opinion mean-variance framework is not appropriate to assess the relative performance of portfolios, as return distribution of portfolios including options are not normal. They concluded that the use of option strategies consistently increase the performance of stock portfolios even in the presence of transaction cost. Toshiaki Watanabe31 (2001) examined the relation between price volatility, trading volume and open interest for Nikkei 225 stock index futures traded on the Osaka Securities Exchange (OSE) by employing the method developed by Bessembinder and Seguin (1993) for the sample period extended from 24th August 1990 to 30th December 1997. The reason for investigating the Nikkei 225 futures traded on the OSE was that the OSE changed regulation such as margin requirements, price range and time interval in updating quotation several times. The authors felt interesting to examine whether changes in regulation may influence the effects of volume on volatility. Bhanupant32 (2001) investigated the dynamic relationship between stock index returns and trading volume using the Augmented Dickey-Fuller (ADF), Linear and Non-Linear Granger Causality hypothesis test on the National Stock Exchange (NSE) data 1 January 1996 to 6 August 2002 with a total of 1649 data points. Linear Granger Causality test was used to investigate the linear relationship while the Non-Linear Granger causality was investigated using modified Baek and Brock test proposed by Hiemstra and Jones (1994) for the daily returns on S&P CNX Nifty and the total trading volume at NSE. Bidirectional linear Granger causality between index returns and volume change was observed for the period when rolling settlement was either not introduced or partially introduced. The period, when rolling settlement was introduced, there found no evidence of linear causality in either direction McKenzie, Brailsford and Faff 33 (2001) have studied impact of single stock futures for existing stock futures of Sydney Futures Exchange for a period of Jan 1990 to June 1998. In order to 18 | P a g e

verify conditional and unconditional volatility of deriving stocks they employed T-GARCH method of estimation for a mean market model. Their study found evidence of a reduction in the underlying stocks’ unconditional volatility and some evidence, which is no consistent across all stocks for asymmetric response. Pilar and Rafael34 (2002), examined the effect of introduction of derivatives on the volatility and trading volume of underlying Ibex-35 index by using GJR model and result that trading volume increased significantly but conditional volatility decreased after introduction of derivatives. Najand Mohammad35 (2002) examined the relative ability of various models to forecast daily stock index futures volatility for S&P 500 futures index between January 1983 and December 1996 with a continuous sequence of 3561 observations are gathered over fourteen year period. He estimated the models using 3500 and 3380 observations and saving the last 60 and 180 observations for out-of-sample forecasting comparisons between models. Their findings suggest autoregressive (AR) model is a more appropriate model under RMSE and MAPE criteria. In nonlinear model, GARCH and ESTAR model fitting were more appropriate than linear models by using RMSE and MAPE error statistics. Finally, EGARCH appeared to be the best model for forecasting stock index futures price volatility. Pandey Ajay36 (2002) reported the empirical performance of various unconditional volatility estimators and conditional volatility models by using S&P CNX Nifty, India. The data set on S&P CNX Nifty for the period 1st January 1996 to 31st December 2001 were considered by using different class of models. In order to test the ability of models estimated to forecast volatility, he compared the unconditional estimators with the realized volatility measure. For conditional volatility models, the forecasts for the same periods are obtained by estimating models from the time-series prior to the forecast period. The results indicate, that the conditional volatility models provide less biased estimates, extreme-value estimators are more efficient estimators of realized volatility. As far as forecasting ability of models is concerned, conditional volatility models fare extremely poorly in forecasting five-day (weekly) or monthly realized volatility. In contrast, extreme value estimators, other than the Parkinson estimator, perform relatively well in forecasting volatility over these horizons. 19 | P a g e

Nath Golaka C38 (2003), his paper on “Behaviour of Stock Market Volatility after Derivatives”, examined the behaviour of volatility in equity market in pre and post derivatives period in India using static and conditional variance. he reproduced conditional volatility using 4 different method: GARCH(1,1), IGARCH with l = 0.94, one year rolling window of standard deviation and a 6 month rolling standard deviation. He has considered 20 stocks randomly from the NIFTY and Junior NIFTY basket as well as benchmark indices itself. He also used static point volatility analysis dividing the period under study among various time buckets and justified the creation of such time buckets. It observed that for most of the stocks, the volatility had come down in the post derivative period while for only few stocks in the sample, the volatility in the post derivatives has either stayed more or less same or has increased marginally. All these methods advised 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. Syed Abuzar Moonis and Ajay Shah39 (2003) tested time-variation in Beta in India. There are two approaches on time variation beta such as kalman filter model and bivariate GARCH model in this study. The data sets of the study contained daily return on the BSE for 50 highly liquid stocks and the NSE50 index for the period from 1st May 1996 to 30th March 2000. To measure the improvement on fit over the conventional OLS beta market model, they used two measures, the coefficients of determination and the variances of the errors. The empirical results showed a tendency for beta to be mean reverting and showed little evidence of beta as a random walk process. Snehal and Saurabh40(2003) examined the volatility effects on Indian spot market in line with Bologna and Cavallo (2002) GARCH Methodology using daily data of both BSE Sensex and S&P CNX Nifty having BSE-200 and Nifty Junior as proxy to capture market wide changes. The study predicts that there is change in the underlying market since year 2000 reflected by the reduction in volatility in all the examined indices. However, they concluded that as BSE have rare volumes in the derivative segment, the reduction of volatility can be attributed only to S&P CNX Nifty futures and same as vague for BSE. Rahman41(2004), explored the impact of trading in DJIA Index future & future option on the conditional volatility of component stock by using GARCH model to make comparison of 20 | P a g e

conditional volatility of intra-day return before and after introduction of derivatives. The result showed that introduction of index future & future option on DJIA has no impact on conditional volatility of component stock. Premalatha Shenbagaraman42 (2004) made research on the topic do futures and option trading increase stock market volatility with the objective to assess the impact of introducing index futures and option contracts on the volatility of the underlying stock index in India. Daily closing prices for the period October 1995 to December 2002 for the CNX Nifty, Nifty Junior, Nifty futures contract volume and open interest were taken from NSE website. The authors used GARCH model, EGARCH model of Nelson (1991), the GARCH mode with t. distribution and GJR-GARCH Model of Glosten. The empirical results of the study revealed that derivatives introduction had no significant impact on spot market volatility. Robbani and Bhuyan43 (2005), used the GARCH model to examine the effect of introduction of future & option on the DJIA on the volatility & trading volume of its underlying stocks and found that level of volatility and trading volume increased after introduction of future & option on the index. Ash Narayan Sah and G. Omkarnath45 (2005) made a study on derivatives trading and volatility of Indian stock market. This study tried to understand whether the Indian stock markets show some significant changes in the volatility after the introduction of derivatives trading and also examined whether decline or rise in volatility can be attributed to introduction of derivatives alone or due to some macro economic reasons. The study used daily data like S&P Nifty, Junior Nifty, NSE 200 and S&PCNX 500, BSE Sensex-BSE 100, BSE 200 from the period April 1998 to March 2005. Auto-Regressive Conditional Heteroskedastic (ARCH) model was applied to achieve the stated objective. The study concluded that the impact of the introduction of the futures and options of the volatility of the underlying markets was negligible as evident from the magnitude of the coefficient of the futures and options dummies. Oliver Fratzscher46(2006) in his observation, derivatives constitute an important in the efficient operations of capital markets across Asia. According to Oliver Fratzscher, developmental benefits of real economic growth can be significant only when uncertainty is reduced and risk is managed more efficiently. In this regard, he said that the derivatives have emerged as most significant 21 | P a g e

hedging instruments. In his opinion, the success of derivative markets depends on clearing and settlement through central counter party, good governance, best practice of accounting standards, full disclosure etc., According to him derivative products made Asian capital markets more competitive and have given significant developmental benefits as hedging tools for commodity producers and cheaper financial tools for corporations. In his opinion, derivatives are inherently risky products and have to be cautiously employed balance by between danger and opportunity. Mukherjee and Mishra’s47 (2006) study empirically investigated the usefulness and impact of two non-price variables-open interest and trading volume from option market preceding the Nifty index in underlying cash market in India. The study applied open interest and volume based predictors for both call and put option. Daily data for both price as well as non-price variables, for two different sub periods, have been employed in order to explore whether there is any significant change in the relationship between open interest, trading volume and index in two different sub periods. The empirical findings confirm that the open interest based predictors are significant in predicting the spot price index in underlying cash market in both the periods, just after the initiation of the index option in the market and in the later sub period. As far as the volume-based predictors are concerned, the study shows that its impact is insignificant just after the initiation but has shown significant explanatory power in the later sub period. Out of the variables, the trading volume shows more impact as compared to open interest in the matter of price prediction in cash market. The impact of both are significant at 1% level of significance, the value of adjusted R-square and F-statistics in two sub periods also exhibits that these variables in the option market have significant power in discovering the price index in underlying cash market. Pati & Kumar49 (2006) attempted to examine the maturity and volume effects on the volatility dynamics for futures price in Indian Futures Market for the period from January 1, 2002 to December 29, 2005 for near month contract with 1009 sample data points. For empirical analysis, they used ARMA-GARCH, ARMA-EGARCH models. The empirical evidence suggests that there is time varying volatility, volatility clustering and leverage effect in Indian futures market. With respect to volume-volatility relationship, the results suppressed the Mixtures of Distribution Hypothesis. This study concluded that time-to-maturity is not a strong determinant of futures price volatility, but rate of information arrival proxied by volume and open interest are the 22 | P a g e

important sources of volatility. This relationship has important implications for the new futures contracts. This study does not provide support for the Samuelson Hypothesis in Indian futures market, which is found to be informational efficient. The finding of this study had a message for investors, market regulator-market surveillance that risk management practices should be further strengthened to take care of greater market volatility associated with an increased volume of trading. Finally, the result suggests maturity effect does not hold in Indian futures markets, the investors should not base their investment decision on time-to-maturity. Mahmood & Salleh50 (2006) examined the relationship between return, trading volume and market depth for two futures contracts, namely Stock Index Futures and Crude Oil Futures traded at the Kaula Lumpur Option and Financial Futures and Commodity and Monetary Exchange for the period from 15th December 1995 to 19th January 2001. They tested with the two famous hypothesis one, whether the sequential arrival of new information to the market move both the trading volume as well as price. The second one is about the mixture of distribution hypothesis where information may be considered as mixing variable. They used the diagnostic tests like Unit root Test, Ljung-Box Test and ARIMA (10,1,0) and evaluated with the help of GARCH (1,1). The effects of volume as well as open interest, proxy of market depth, on volatility and vice versa were also studied. Since both volume and open interest were found highly serially correlated, these variables were divided into expected and unexpected components. Finally, the results showed a positive expected and unexpected volume and market depth effect on volatility. Misra, Kannan and Sangeeta51 (2006) have investigated the existence of volatility surfaces in S&P CNX Nifty index option for the period January 2004 to December 2004. The result of the study shows that deep in-the-money and deep out-of-the-money options are having higher volatility than at-the-money options. The implied volatility of out-of-the-money call options is more than in-the money call options. The implied volatility is higher for far the month contracts than for near the month contracts. Deep in-the-money and out-of-the-money options with shorter maturity have higher volatility than those of with longer maturity. Put options have higher volatility than call options. The results show that the shape of the volatility smile in India is similar to that which was prevailing in US before the stock market crash of 1987.

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Maheshwaran and Ranjan52 (2006) examined the ability of implied volatility to predict the realized volatility. They estimated the implied volatility for the Nifty ‘call’ option series and Nifty ‘put’ option series and analyzed their capability to predict the realized volatility separately. They also compared the information content of the implied volatility of Nifty options with the three other Asian indices i.e. Hang Seng (Hong Kong), KOSPI (South Korea) and TWSEW (Taiwan). The R-square for the regression equation for India is 3%, 7% for Korea, 38% for Hong Kong and 39% for Taiwan. The co-efficient of implied volatility is not significant for India, but significant for other countries. They concluded that the implied volatility is a poor and biased estimator of realized volatility in case of Indian and South Korean market but useful in the other two markets namely Hong Kong and Taiwan. Alexakis Panayiotis53 (2007) investigated the effect of the introduction of Stock Index Futures on the volatility of the Spot equity market and contributes in this way to the contrasting arguments with respect to the stability and destabilising effects of such products. The statistical results indicated that the index of Futures trading is fully consistent with efficient market operation as it exerts a stabilising effect in the spot market, reducing volatility asymmetries and improves the quality and speed of the flow of information. Samanta and Samanta54 (2007), analyzed the impact of introducing index futures and stock future on the volatility of underlying spot market in India by taking S&P CNX Nifty, Nifty Junior and S&P 500 and used GARCH model for the study. He found that there is no significant change in the volatility of spot market, but the structural changes in the volatility to some extent. He also found mixed result in spot market volatility in case of 10 individual stocks. Drimbetas55 (2007) studied the effect of introduction of future & options into the FTSE/ASE 20 Index on the volatility of underlying index by using EGARCH model. He reported reduction in the conditional volatility of index and consequently increases its efficiency. Suchismita Bose56 (2007) attempted to understand the volatility characteristics and transmission effects in the Indian stock index and index futures markets by using daily data for the market index of NSE-S&P CNX Nifty for the period from June 2000 to March 2007. U.S Dow Jones Industrial average returns was also included in the analysis. The empirical results indicated that NSE index and its futures return volatility had no tendency to drift upward indefinitely with time, 24 | P a g e

but in fact had a normal or mean level to which they ultimately revert. In the case of volatility transmission, it was found strong bidirectional volatility spillovers between the markets implying that the price and returns dynamics in one market are capable of explaining much of the movement in the other. Sabri57 (2008) explored the impact of change in trade volume on volatility of stock prices as expressed by unified Arab Monetary fund stock price index. He reported increase in both trading volume & stock price volatility. He also found the correlation between volume and price movement was higher in the stock markets of the oil Arab states compared to the nonoil Arab states. Mallikarjunappa and Afsal58 (2008), in their study have examined the implication of the introduction of derivative trading on spot market volatility for S&P CNX Nifty by using GARCH model and concluded that price sensitivity to old news is higher during pre future period than post future period and with introduction of future, market volatility is determined by recent innovation. They also explored effect of future trading on spot market volatility by using GARCH model on CNX Bank Nifty and found that there is no impact of future trading on spot market volatility. However, impact of new news increased and persistence effect of old news decreased in post future period. Malabika & Srinivasan59 (2008) have analyzed the empirical relationship between stock return, trading volume and volatility for select Asia-Pacific Stock Market by applying preliminary test, Granger Causality test and EGARCH (1,1) model. The data set comprises of seven national stock markets for the period spanning from 1st January 2004 to 31st March 2008. The results evidenced a significant relationship between trading volume and the absolute value of price changes. Granger Causality test was used to explore, whether return causes volume or volume causes return. The results suggested that the returns were influenced by volume and volume also was influenced by returns for most of the markets. Mahajan and Singh60 (2008) have investigated the pattern of information flow between trading volume and return volatility using daily data for Nifty index during the period from July 2001 to March 2006. The methods used included Correlation analysis, Unit root tests, VAR modelling, Granger causality test, GARCH (1,1) and EGARCH model. The study provided evidence of low 25 | P a g e

but significant positive contemporaneous relationship between volume and return volatility that was indicative of both mixture of distribution and sequential arrival hypothesis. The differential cost of taking long and short positions were examined by applying asymmetric EGARCH (1,1) model to check the relationship between the variables. The study further confirmed a weak unidirectional causality from volume to return volatility, which also indicates the mild support for sequential information flow directed from volume to price change. The study contributes to the enhance understanding of researchers, regulators, speculators, and other participants in market on market efficiency and information processing. Rashid and Ahmad61 (2008) evaluated the relative performance of linear versus nonlinear models to forecast stock index volatility by using daily data for the period January 2001 to November 2007 for Karachi Stock Exchange. The purpose of this study was to predict the daily stock price index by employing linear and non-linear models like: random walk, autoregressive model, moving average, exponential smoothing, Holt exponential smoothing models, GARCH, EGARCH and PARCHES models, to assess the forecasting performance of the models by considering Root Mean Square Error (RMSE). It was found that, among linear models of stock price index volatility, the exponential smoothing models ranked first using the RMSE criterion. They also found that within the nonlinear models, the GARCH model was superior as compared to the EGARCH and the PGARCH models. Finally, the study concluded based on the RMSE that the nonlinear ARCH-class models clearly dominate the linear models in out-of sample forecasting exercise for stock price index volatility. Satya Swaroop Debasish62(2009) in his paper investigated the effect of Nifty Futures trading on the volatility and operating efficiency of Indian Stock Market in general and the underlying stock in particular. The study covers a period of fourteen years i.e. from 1995 to 2009. The author has applied event study approach to test the change in volatility and efficiency of stock returns by making a comparison between pre and post introduction of Nifty Index Futures. The study revealed mixed results i.e. reduced spot volatility and reduced trading efficiency and in the short run, there is a trade-off gains and costs associated with the introduction of derivatives. The study concluded that the derivatives have led to market stabilization cut the market has to pay a price for it in the future of loss in the market efficiency.

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Maniar Hiren M63(2009), in this paper, he analyzed the effect of the introduction of derivatives (futures and options) in the Indian market on the volatility and on the trading volume of the underlying index. The period examined covers from April 2001 to March 2006. To learn this effect, he used three models of conditional volatility GARCH, EGARCH and GJR. He found significant impact on variance: the proof pointed out that the conditional volatility of the underlying index declines after derivative markets are introduced. The trading volume of NSE (National Stock Exchange of India) Nifty -50 increases significantly. In addition, the introduction of the derivative contracts in India verified a decrease in uncertainty in the underlying market and an increase in liquidity, which possibly enhance their efficiency. Ulkem Basdas64 (2009) investigated the lead lag relationship between the spot index and futures price for the Turkish derivatives exchange by using ISE30 and compare the forecasting abilities of ECM, ECM with COC, ARIMA, and VAR model considering the data from February 4th 2005 to May 9th 2008. The series of futures prices on ISE 30 index was gathered from the Turk DEX Website and the spot value also collected from the same source and for the same period. The Ganger causality test results indicated that the log of spot price significantly Granger cause log of futures but not vice versa. Vasilieios Kallinterakis and Shikha Khurana65 (2009) have investigated volatility persistence and the feedback trading hypothesis from Indian evidence to produce an original contribution to the finance literature by examining the relationship between feedback trading and volatility from a markets evolutionary perspective, and to test internationally established facts regarding feedback trading in an Indian markets contexts. In order to test the feedback trading with the Senatana and Wadhwani Model, the authors applied conditional variance. The daily closing prices from the BSE 30, BSE 100 and BSE 200, and S&PCNX Nifty 50 from 1992 to 2008 were taken in to consideration. The empirical result indicated that positive feedback trading is evident throughout the period from 1999. Volatility was found to maintain significant asymmetries in most of the period under examination. Gahlot Ruchika, Datta Saroj and K. Kapil Sheeba66 (2010), have examined the impact of derivative trading on stock market volatility by taking closing prices of S&P CNX Nifty as well as closing prices of five derivative stocks and five non derivative stocks from April 1, 2002 to March 31, 27 | P a g e

2005. The study used GARCH model to capture nature of volatility over time and volatility clustering phenomenon of data. Results showed mixed effect in case of 10 individual stocks. These results can help investors in making investment decision. It also helps to identify need for regulation. Apart from the above review of literature, chapter-wise specific review of literatures is presented in respective chapters.

NEED FOR THE STUDY From the review of literature, it can be observed that academicians, researchers, and financial organizations both in India and abroad have carried out research studies covering various aspects of Financial Derivatives. However, the present study is different from the above research studies in terms of both period and the sample chosen. This is made clear in the methodology of the study. Objectives: The objectives of the present study are 1. To analyse the nature and growth of Financial Derivatives in India 2. To analyse the impact of Index Futures and Stock Futures on the Stock Market Volatility 3. To analyse the impact of Index Options and Stock Options on the Stock Market Volatility 4. To analyse the impact of non price variables on the underlying Cash Market

The following are the Hypotheses of the Study: HO1: Index Futures and Stock Futures have no impact on stock market volatility HO2:Index Options and Stock Opt ions have no impact on stock market volatility HO3:Non-price variables like Open Interest and Trading Volume have no impact on underlying Cash Market

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CHAPTER 4 : DATA ANALYSIS & FINDINGS

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What is BSE and NSE ?

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COMPARISION BETWEEN BSE AND NSE

Basis

for BSE

NSE

Comparison Introduction

Bombay Stock Exchange is the National Stock Exchange is the biggest oldest financial market in the capital market of the country. The country, which offers high speed exchange is a front runner in the trading to its customers.

introduction of the fully automated, electronic trading system across the nation.

Founded in

1875

Founded by

Mr.Ashish

1992 Chauhan(MD

& M/s. Chitra Ramkrishna (MD &CEO)

CEO) Benchmark

Sensex

Nifty

www.bseindia.com

www.nseindia.com

index

Website Total

listed 5650

1740

companies (April 2015) Market

Around 1.68 trillion

Around 1.5 trillion

Global Rank

10th

11th

Network

Over 400 cities

Over 2000 cities

Capitalization

Key Differences Between BSE and NSE

The major differences between BSE and NSE are as under: 31 | P a g e

BSE and NSE are the top securities exchange of India, where BSE is the oldest one while NSE is the youngest one.

Globally, BSE stood in the 10th position in the list of top stock exchanges which is followed by NSE.

NSE was the first to introduce the modernized trading system in the country in 1992 while BOLT was introduced by BSE in 1995. BSE’s index is known by the name SENSEX (Sensitive Index) which shows 30 top trading companies. Nifty (National Fifty) is the index of NSE, displays 50 most traded companies.

BSE started as an Association of persons in 1875, which was accredited as a stock exchange in 1957. NSE was founded in 1992, as a tax paying company, but later on, in 1993 it was recognized as a Stock Exchange.

TYPES OF DERIVATIVES Broadly, Derivatives can be classified in to two categories Commodity Derivatives and Financial Derivatives. In case of commodity derivatives, underlying asset can be a commodity like wheat, gold, silver, crude oil, gas etc., whereas in case of financial derivatives underlying assets are stocks, currencies, bonds and other interest rate bearing securities etc. Another way of classifying the financial derivatives is into basic and complex derivatives. In this, Forward contracts, Future contracts and Option contracts have been included in the basic derivatives whereas Swaps and other Derivatives are categorized as complex because they are built up from either Forward/Futures or Options contracts or both. In fact, such derivatives are effectively derivatives on derivatives. (Hybrid derivatives). The features of those Derivatives instruments are briefly presented here. FORWARD: A forward contract is an agreement between two parties to buy or sell an asset at a specified point of time in the future. In case of a forward contract the price which is paid/ received by the parties is decided at the time of entering into contract. It is the simplest form of 32 | P a g e

derivative contract mostly entered by individuals in day-to-day life. Forward contract is a cash market transaction in which delivery of the instrument is deferred until the contract has been made. Although the delivery is made in the future, the price is determined on the initial trade date. One of the parties to a forward contract assumes a long position (buyer) and agrees to buy the underlying asset at a certain future date for a certain price. The other party to the contract known as seller assumes a short position and agrees to sell the asset on the same date for the same price. The specified price is referred to as the delivery price. The contract terms like delivery price and quantity are mutually agreed upon by the parties to the contract. FUTURES: Futures is a standardized Forward contact to buy (long) or sell (short) the underlying asset at a specified price at a specified future date through a specified exchange. In the Futures, contracts the exchanges will act as a buyer as well as seller. Exchange sets the standards for quality, quantity, price quotation, date and delivery place (in case of commodity). Futures contracts being traded on organized exchanges impart high liquidity to the transaction. The clearing house, being the counter party to both sides of a transaction, provides a mechanism that guarantees the honoring of the contract and ensuring very low level of default. OPTIONS: In case of Futures contact, both parties are under obligation to perform their respective obligations out of a contract. But in an options contract, as the name suggests, is in some sense, an optional contract. An option is the right, but not the obligation, to buy or sell something at a stated date at a stated price. A “call option” gives the holder the right to buy; a “put option” gives the holder the right to sell. Options are the standardized financial contract that allows the buyer (holder) of the option, i.e. the right at the cost of option premium, not the obligation, to buy options) a specified asset at a set price on or before a specified date through exchanges. Options contracts are of two types: call options and put options. Apart from this, options can also be classified as OTC (Over the Counter) options and exchange traded options. In case of exchange traded options contract, contracts are standardized and traded on recognized exchanges, whereas OTC options are customized contracts traded privately between the parties. A call options gives the holder (buyer/one who is long call), the right to buy specified quantity of the underlying asset at the strike price on or before expiration date. 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. 33 | P a g e

SWAPS: A Swap can be defined as a barter or exchange. It is a contract whereby parties agree to exchange obligations that each of them have under their respective underlying contracts or we can say, a swap is an agreement between two or more parties to exchange stream of cash flows over a period of time in the future. The parties that agree to the swap are known as counter parties. The two commonly used swaps are: i) Interest rate swaps which entail swapping only the interest related cash flows between the parties in the same currency, and ii) Currency swaps: These entail swapping both principal and interest between the parties, with the cash flows in one direction being in a different currency than the cash flows in the opposite direction CONVERTIBLES: Convertibles are hybrid securities, which combine the basic attributes of fixed interest, and variable return securities. Most popular among these convertible bonds, convertible debentures and convertible preference shares. These are also called equity derivatives securities. They can be fully or partially converted into the equity shares of the issuing company at the predetermined specified terms with regards to the conversion period, conversion ratio and conversion price.

What is the difference between Options and Futures trading? Options and futures are two similar sounding trading products, but are very different in practice. Both products are used by retail traders and institutional investors, but often in different ways. Let’s take a deep look at options and futures and their differences. The main fundamental difference between options and futures lies in the obligations they put on their buyers and sellers. An option gives the buyer the right, but not the obligation to buy (or sell) a certain asset at a specific price at any time during the life of the contract. A futures contract gives the buyer the obligation to purchase a specific asset, and the seller to sell and deliver that asset at a specific future date, unless the holder's position is closed prior to expiration.

Stock futures and stock are deadline-based agreements between buying and selling parties for a share of equity. Both contracts provide investor with strategic opportunities to make money ad hedge current investments. Before an investor can decide to trade either futures or options, they must understand the four primary differences between the two. 34 | P a g e

Futures may be great for index and commodities trading, but options are the preferred securities for equities.

Aside from commissions, an investor can enter into a futures contract with no upfront cost whereas buying an options position does require the payment of a premium. Compared to the absence of upfront costs of futures, the option premium can be seen as the fee paid for the privilege of not being obligated to buy the underlying in the event of an adverse shift in prices. The premium is the maximum that a purchaser of an option can lose.

Another key difference between options and futures is the size of the underlying position. Generally, the underlying position is much larger for futures contracts, and the obligation to buy or sell this certain amount at a given price makes futures more risky for the inexperienced investor.

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The final major difference between these two financial instruments is the way the gains are received by the parties. The gain on a option can be realized in the following three ways: exercising the option when it is deep in the money, going to the market and taking the opposite position, or waiting until expiry and collecting the difference between the asset price and the strike price. In contrast, gains on futures positions are automatically 'marked to market' daily, meaning the change in the value of the positions is attributed to the futures accounts of the parties at the end of every trading day - but a futures contract holder can realize gains also by going to the market and taking the opposite position.

Forward Contracts and Call Options

Forward contracts and call options are different financial instruments that allow two parties to purchase or sell assets at specified prices on future dates. Forward contracts and call options can be used to hedge assets or speculate on the future prices of assets. 36 | P a g e

Explaining the Differences between Forward Contracts and Call Options

A call option gives the buy or holder the right, but not the obligation, to buy an asset at a predetermined price on or before a predetermined date, in the case of an American call option. The seller or writer of the call option is obligated to sell shares to the buyer if the buyer exercises his option or if the option expires in the money.

Does the seller (the writer) of an option determine the details of the option contract?

The quick answer is yes and no. It all depends on where the option is traded. An option contract is an agreement between the buyer and the seller of the contract to buy or sell an underlying asset at a certain price, amount and time. These are referred to as the strike price, the contract size and the expiration date, respectively. Options are sold in two places: on option exchanges and over the counter.

Option Exchanges

Option exchanges are similar to stock exchanges in that trade happens through a regulated organization, such as the Chicago Board Option Exchange (CBOE). Exchange-traded options at the basic level are standardized; this means that each option has a set standard underlying asset, quantity per contract, price scale and expiration date

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What is the difference between options and futures? Options and futures are two similar sounding trading products, but are very different in practice. Both products are used by retail traders and institutional investors, but often in different ways. Let's take a deeper look at options and futures and their differences. The fundamental difference between options and futures lies in the obligations they put on their buyers and sellers. An option gives the buyer the right, but not the obligation, to buy (or sell) a certain asset at a specific price at any time during the life of the contract. A futures contract gives the buyer 38 | P a g e

the obligation to purchase a specific asset, and the seller to sell and deliver that asset at a specific future date, unless the holder's position is closed prior to expiration. Stock futures and stock options are deadline-based agreements between buying and selling parties for a share of equities. Both contracts provide investors with strategic opportunities to make money and hedge current investments. Before an investor can decide to trade either futures or options, they must understand the four primary differences between the two.

Option Contracts There are call options and put options. A trader can buy a put or a call, or a trader can write a put or a call. A call option is the right to buy a stock at the strike price before or at expiry ( for American options). For instance, assume there is a call option to buy stock XYZ at a $50 strike price, and the option expires in three months. The stock is currently trading at $49. If before or at expiry the stock is trading above $50 – say at $60 – the call buyer can exercise their right to buy the stock at $50. They buy the stock at $50 from the call writer and are able to sell the stock at $60 for a $10 profit per share. Alternatively, the option buyer can simply sell the call to reap the profit, since the call option is worth $10 per share, plus any time value that remains. If the option is trading below $50 (strike) at expiry, the option is worthless and the call buyer loses what they paid for the option, called the premium. The risk to the call option buyer is limited to the premium paid. This premium is based on a number factors, including how far the strike price is from the current underlying security's price, as well as how long there is still expiry. This premium is received by the option writer.

The option writer is on the other side of the trade. They have unlimited risk because a stock price could go up indefinitely. Assume in the scenario that the stock goes up to $100. The option writer would need to buy stock at $100 because they are obligated to sell shares to the call buyer at $50. For the small premium received this option writer is losing $50 per share. Like the option buyer, the option writer can close their position at any time by buying a call option which brings them back to flat. Their profit or loss is the difference between the premium received and the cost of the premium to buy back the option or to get out of the trade. 39 | P a g e

A put option is the right to sell XYZ at the strike price at or before expiry. A trader buying this option wants the price of the underlying stock to fall. If you own a put that allows you to sell XYZ at $100, and XYZ’s price falls to $80 before the option expires, you’ll gain $20 per share, less the cost of the premium paid. If the price of XYZ is above $100 at expiry, then the option is worthless and you lose the premium you paid for the option. The put buyer can continue to profit all the way to the stock falling to $0. The maximum gain for the writer of the put option is the premium received, yet the risk is that the price falls below the strike price and losses could mount. Assuming they are American options, the put buyer and writer can close out their option position to lock in a profit loss at any time before expiry by buying the option in the case the writer or selling the option in the case of the buyer. The put buyer may also choose to exercise, which means they utilize their right to sell at the strike price.

Futures Contracts

A futures contract is the obligation to sell or buy a commodity (or other asset) at a later date, at an agreed price. Assume two traders agree to $100 on an oil futures contract. The buyer agrees to buy oil at $100 at expiry, and the sellers agrees to sell oil at $100. If the price of oil moves up to $105, the buyer of the contract at $100 is making money because they have an agreement to buy at $100 even though oil is currently trading at $105. The seller on the other hand is losing, because they could be selling at $105, but instead they agreed to sell at $100. Here is where a big difference between institutional and retail traders comes in. Retail traders buy and sell futures contracts betting on the price direction of the underlying security. They want to profit off the change in price of the futures contract. They do not intend to actually take possession of physical barrels of oil, or to have to deliver barrels of oil (or other underlying product of a futures contract). Yet institutions will use futures contracts for this purpose; that is why futures were invented. Futures contracts allow companies to buy products they need or sell products they produce at agreed prices on future dates. This allows them to make plans for their business and guarantee product inflows/outflows down the road. 40 | P a g e

Someone who buys or sells a futures contract is not required to put up the full amount of what the contract represents. For example, an oil futures contract is for 1,000 barrels of oil. An agreement to buy an oil futures contract at $100 represents the equivalent of a $100,000 agreement. But the buyer and seller are not required to put up all this capital up front. Rather, they are only required to put up several thousand dollars, but then may have to put up more money/margin if the contract is going against them.

Contract Premiums Aside from commissions, an investor can enter into a futures contract with no upfront cost, whereas buying an options position does require the payment of a premium. When buyers of call and put options purchase a derivative, they pay a one-time fee called a premium, and sellers of call and put options collect the premium. The value of the contracts decays as the settlement date approaches. However, the premium price rises and falls, allowing users to sell their calls and puts for a profit ahead of the expiration date. Those who sell options can purchase call options to cover the size of their position as well.

Stock futures can either be purchased on single stocks (SSFs) or focus on the broader performance of an index like the S&P 500. However, with stock futures, the buying party pays something other than a contract premium at the point of purchase. Buying parties pay something known as initial margin, which is a percentage of the price to be paid for the stocks. Compared to the absence of upfront costs of futures, the option premium can be seen as the fee paid for the privilege of not being obligated to buy the underlying security in the event of an adverse shift in prices. The premium is the maximum a purchaser of an option can lose. Another key difference between options and futures is the size of the underlying position. Generally, the underlying position is much larger for futures contracts, and the obligation to buy or sell this certain amount at a given price makes futures more risky for the inexperienced investor.

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Financial Liabilities When someone buys a stock option, the only financial liability is the cost of the premium at the time the contract is purchased. However, when a seller opens put options for purchase, they are exposed to maximum liability on the stock’s underlying price. If a put option gives the buyer the right to sell the stock at $50 per share but the stock falls to $10, the person who initiated the contract must agree to purchase the stock for the value of the contract, or $50 per share.

Futures contracts, however, offer maximum liability to both the buyer and seller of the agreement. As the underlying stock price shifts in the favor against either the buyer or seller, parties may be obligated to inject additional capital into their trading accounts to fulfill daily obligations.

Buyer and Seller Obligations at the Time of Expiration Those who purchase call or put options receive the right to buy or sell a stock at a specific strike price. However, they are not obligated to exercise the option at the time the contract expires. Investors only exercise contracts when they are in the money. If the option is out of the money, the contract buyer is under no obligation to purchase the stock. Purchasers of futures contracts are obligated to buy the underlying stock from the seller of that contract upon expiration no matter what the price is of the underlying asset. If the futures contract calls for the purchase of the stock at $100, but the underlying stock is valued at $80 at contract expiration, the buyer must buy at the agreed upon price. Still, it is very rare for stock futures to be held to their expiration date.

How Gains Are Received? The final major difference between these two financial instruments is the way the gains are received by the parties. The gain on an option can be realized in the following three ways: exercising the option when it is deep in the money, going to the market and taking the opposite position, or waiting until expiry and collecting the difference between the asset price and the strike price. In contrast, gains on futures positions are automatically marked to market daily, meaning the change in the value 42 | P a g e

of the positions is attributed to the futures accounts of the parties at the end of every trading day, but a futures contract holder can realize gains also by going to the market and taking the opposite position.

Options and Futures Example Let's look at an options and futures contract for gold. One options contract for gold on the Chicago Mercantile Exchange (CME) has the underlying asset as one COMEX gold futures contract, not gold itself. An investor looking to buy an option may purchase a call option for $2.60 per contract with a strike price of $1600 expiring in Feb 2019. The holder of this call has a bullish view on gold and has the right to assume the underlying gold futures position until the option expires after market close on Feb 22, 2019. If the price of gold rises above the strike price of $1,600, the investor would exercise his right to obtain the futures contract, otherwise, he may let the options contract expire. The maximum loss of the call options holder is the $2.60 premium he paid for the contract.

The investor may instead decide to obtain a futures contract on gold. One futures contract has its underlying asset as 100 troy ounces of gold. The buyer is obligated to accept 100 troy ounces of gold from the seller on the delivery date specified in the futures contract. If the trader has no interest in the physical commodity, he can sell the contract before delivery date or roll over to a new futures contract. If the price of gold goes up (or down), the amount of gain (or loss) is marked to market (i.e. credited or debited) in the investor's account at the end of each trading day. If the price of gold in the market falls below the contract price the buyer agreed to, he is still obligated to pay the seller the higher contract price on delivery date.

Investment Flexibility Stock options provide investors with both the right to buy a stock (but not the obligation) and the right to sell the same stock (but not the obligation) through calls and puts, respectively. But stock options also provide investors with a breadth of flexible strategies unavailable through futures trading. Each strategy offers different profit potentials for investors and speculators. 43 | P a g e

Stock futures, on the other hand, offer very little flexibility once a contract is opened. As noted, investors purchase the right and obligation for fulfillment once a position is opened.

Risk: Futures vs. Options One difference between futures contract and options is that a future is an obligation, whereas an option is the right (not necessarily an obligation). With futures, both parties face a lot of risk as prices could move against them. Companies enter these agreements because they need to buy or sell the underlying product anyway, and are just looking to lock in a price. This differs from an option contract where the buyer has limited risk and seller has large risk. Another difference is that the cost of an option is the premium, while futures traders put up margin and then may have to put up more capital if the price goes against them. The potential to have to put up more capital does not apply to option buyers, but does apply to option writers.

Futures contracts are generally larger than default option contracts. For example, most option contracts are for 100 shares of stock. If the underlying stock is trading at $30, then 100 shares of stocks is $3,000 ($30 x 100). Compare that to a standard gold contract which is 100 ounces of gold. If gold is trading at $1,300 per ounce, the contract represents $130,000. Therefore, the size of futures contracts can pose greater risk, since even small moves in the underlying price of the asset can mean big dollar amounts gained or lost on the futures contract. Option contracts are smaller by default, although it is possible to buy multiple contracts (same with futures) in order to increase the size of the bet.

The Bottom Line Options and futures may sound similar, but they are very different. Futures markets are a bit simpler to understand, but carry considerable risk for an uninformed investor due to the size of many of the contracts. Options trading can be quite complex. Although, if buying options, risk is capped to the premium paid. Options writer assume more risk, and therefore option writing should be left to experienced options traders. 44 | P a g e

Deciding to use stand-alone options, stock futures or a combination of the two requires an assessment of individual expectations and investment goals. One of the first questions an investor must ask is how much risk they are willing to take on in their investment strategies. Options trading provides less upfront risk for buyers given the lack of obligation to exercise the contract. This provides a more conservative approach, particularly if traders use a number of additional strategies like bull call and put spreads to improve the odds of trading success over the long term.

When does one sell a put option, and when does one sell a call option? The incorporation of options into all types of investment strategies has quickly grown in popularity among individual investors. For beginner traders, one of the main questions that arises is why traders would wish to sell options rather than to buy them. The selling of options confuses many investors because the obligations, risks, and payoffs involved are different from those off .Let's look at a put option on Microsoft (MSFT). The writer or seller of MSFT Jan18 67.50 Put will receive a $7.50 premium fee from a put buyer. If MSFT's market price is higher than the strike price of $67.50 by January 18, 2018, the put buyer will choose not to exercise his right to sell at $67.50 since he can sell at a higher price on the market. The buyer's maximum loss is therefore, the premium paid of $7.50, which is the seller's payoff. If the market price falls below the strike price, the put seller is obligated to buy MSFT shares from the put buyer at the higher strike price since the put buyer will exercise his right to sell at $67.50.

Selling a call option without owning the underlying asset - An investor would choose to sell a call option if his outlook on a specific asset was that it was going to fall, as opposed to the bullish outlook of a call buyer. The purchaser of a call option pays a premium to the writer for the right to buy the underlying at an agreed upon price in the event that the price of the asset is above the strike price. In this case, the option seller would get to keep the premium if the price closed below the strike price.

The seller of MSFT Jan18 70.00 Call will receive a premium of $6.20 from the call buyer. In the event that the market price of MSFT drops below $70.00, the buyer will not exercise the call option and the seller's payoff will be $6.20. If MSFT's market price rises above $70.00, however, the call

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seller is obligated to sell MSFT shares to the call buyer at the lower strike price, since it is likely that the call buyer will exercise his option to buy the shares at $70.00.

Another reason why investors may sell options is to incorporate them into other types of option strategies. For example, if an investor wishes to sell out of his or her position in a stock when the price rises above a certain level, he or she can incorporate what is known as a covered call strategy. Many advanced options strategies such as iron condor, bull call spread, bull put spread, and iron butterfly will likely require an investor to sell options.

How to Trade Futures Contracts? Futures contracts are a type of forward contract between a buyer and a seller of an asset. They agree to exchange goods and money at a future date, but at a price and quantity determined today. Future contracts differ from other forward contracts because they are actively traded in secondary markets like the Chicago Mercantile Exchange and the Intercontinental Exchange. Futures contracts have a wide range of underlying assets, from commodities like coffee, corn, wheat, currencies and metals, and from stock indexes like the Nikkei* 225 or S&P 500. Futures markets serve companies or businesses who want to protect themselves from price volatility in different securities, as well as investors or speculators who try to profit from the change in price of an asset. Other aspects to note about futures contracts: They are standardized, regulated and free of counterparty risk since exchange clearinghouses guarantee that traders in the futures markets will honor their obligations. To start trading futures, an investor selects the asset they want to trade, and makes an initial margin deposit with a broker. The broker will then place the trade for the specific asset with the clearinghouse. A maintenance margin is required in order to keep the account active. Consider a long position of three September corn contracts, each of which covers 5,000 bushels. Assume the contract price is $3 per bushel and that each contract requires a margin deposit of $300 and a maintenance margin of $200. The total initial margin deposit would be $900, and the maintenance margin for the account would be $600. If the price of the bushel increases 4 cents to $3.04, then the investor gains $600 (3 contracts x .04 x 5000 bushels). However, if instead it decreases 4 cents (from $3 to $2.96), the investor loses $600, 46 | P a g e

The account deposit would be reduced to $300, and the investor would need to deposit $600 of variation margin in order to get the account back to its initial margin.

How are options different from futures ? The significant differences in Futures and Options are as under:

Futures are agreements/contracts to buy or sell specified quantity of the underlying assets at a price agreed upon by the buyer and seller, on or before a specified time. Both the buyer and seller are obligated to buy/sell the underlying asset.

In case of options the buyer enjoys the right & not the obligation, to buy or sell the underlying asset.

Futures Contracts have symmetric risk profile for both the buyer as well as the seller, whereas options have asymmetric risk profile.In case of Options, for a buyer (or holder of the option), the downside is limited to the premium (option price) he has paid while the profits may be unlimited. For a seller or writer of an option, however, the downside is unlimited while profits are limited to the premium he has received from the buyer.

The Futures contracts prices are affected mainly by the prices of the underlying asset. The prices of options are however; affected by prices of the underlying asset, time remaining for expiry of the contract, interest rate & volatility of the underlying asset.

What are Covered and Naked Calls?

A call option position that is covered by an opposite position in the underlying instrument (for example shares, commodities etc.)is called a covered call. Writing covered calls involves writing call options when the shares that might have to be delivered (if option holder exercises his right to buy), are already owned. For example, a writer writes a call on Reliance and at the 47 | P a g e

same time holds shares of Reliance so that if the call is exercised by the buyer, he can deliver the stock.

Covered calls are far less risky than naked calls (where there is no opposite position in the underlying), since the worst that can happen is that the investor is required to sell shares already owned at below their market value. When a physical delivery uncovered/ naked call is assigned on exercise, the writer will have to purchase the underlying asset to meet his call obligation and his loss will be the excess of the purchase price over the exercise price of the call reduced by the premium received for writing the call.

What is the Intrinsic Value of an option ?

The intrinsic value of an option is defined as the amount, by which an option is in-the-money, or the immediate exercise value of the option when the underlying position is marked-to-market.

For a call option: Intrinsic Value = Spot Price - Strike Price For a put option: Intrinsic Value = Strike Price - Spot Price

The intrinsic value of an option must be a positive number or 0. It cannot be negative. For a call option, the strike price must be less than the price of the underlying asset for the call to have an intrinsic value greater than 0. For a put option, the strike price must be greater than the underlying asset price for it to have intrinsic value

What are the factors that affect the value of an option (premium)?

There are two types of factors that affect the value of the option premium:

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Quantifiable Factors: •

underlying stock price

•

the strike price of the option

•

the volatility of the underlying stock

•

the time to expiration and

•

the risk free interest rate

Non-Quantifiable Factors: •

Market participants" varying estimates of the underlying asset's future volatility

•

Individuals" varying estimates of future performance of the underlying asset, based on fundamental or technical analysis

•

The effect of supply & demand- both in the options marketplace and in the market for the underlying asset

•

The "depth" of the market for that option - the number of transactions and the contract's trading volume on any given day.

What are different pricing models for options ?

The theoretical option pricing models are used by option traders for calculating the fair value of an option on the basis of the earlier mentioned influencing factors. The two most popular option pricing models are: Black Scholes Model which assumes that percentage change in the price of underlying follows a lognormal distribution. Binomial Model which assumes that percentage change in price of the underlying follows a binomial distribution.

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Abstract The study is conducted to establish the framework for comparing the relation in performance of the derivatives of BSE and NSE in India and to analyses the relationship of derivatives with cash market and the market volatility. The exchange traded equity derivatives were considered for the study. It was found that the performance of derivatives in NSE is lot higher than BSE and the NSE is on par with the global exchanges compared to BSE in terms of in terms of the number of contracts traded for Stock Index Options and Futures and also Stock Futures. Hence derivatives market need to strengthen further with the number of contracts traded and turnover in all the derivative instruments with more strong regulations and robust framework protecting the interest of the investors. This study enables Derivative Industry to progress towards its goals and objectives in a more efficient way.

Keywords: Derivatives, Exchange and Index Futures, Options.

Introduction

Following the growing instability in the financial markets, the financial derivatives gained prominence after 1970. In recent years, the market for financial derivatives has grown in terms of the variety of instruments available, as well as their complexity and turnover. Financial derivatives have changed the world of finance through the creation of innovative ways to comprehend, measure, and manage risks. India’s tryst with derivatives began in 2000 when both the NSE and the BSE commenced trading in equity derivatives. India’s experience with the equity derivatives market has been extremely positive. India is one of the most successful developing countries in terms of a vibrant market for exchange-traded derivatives. This reiterates the strengths of the modern development in India’s securities markets, which are based on nationwide market access, anonymous electronic trading, and a predominant retail market. There is an increasing sense that the equity derivatives market plays a major role in shaping price discovery. The present paper is descriptive in nature and based on the secondary data encompasses the prominence of derivative market and many 50 | P a g e

issues underlying which need to be immediately resolved to enhance the investors‟ confidence in the Indian derivative market.

Hypothesis: •

There is a relation in the performance of Index and Stock Futures and Options of NSE and BSE.

•

Derivatives turnover influences the turnover in the Cash and Volatility segment of Indian Market.

•

Indian derivatives market growth trend is in line with the global exchanges.

Scope of the study:

In India, the emergence and growth of derivatives market is relatively a recent phenomenon. Since its inception in June 2000, derivatives market has exhibited exponential growth both in terms of volume and number of contract traded. The market turnover of derivatives of NSE and BSE has grown from Rs.4,038 Cr. in 2000-2001 to Rs.3, 21,58,208 Cr. in 2012-13. Within a short span of twelve years, derivatives trading in India has surpassed cash segment in terms of turnover and number of traded contracts. Hence it is important to critically view the Issues and the challenges revolving around the derivative industry and the Regulations governing them.

Plan of analysis

The statistical data listing of all the variables collected are in tables, wherein mean and standard deviation as been used for continuous variables such as Turnover, Number of Contracts, etc. The pair t-test was applied to test the difference of means in two variables, and one-way ANOVA was applied for more than two means. All statistical tests are two-tailed, at α=0.05. All trends were analyzed and studied by linear regression equation. Statistical Analysis was done through MS-EXCEL (Advance), as the data-base was prepared in MS-EXCEL. Data validation was done by using data validation tool of MS-EXCEL.

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Data Analysis Graph showing the yearly comparison of the Cash & Derivatives Market Turnover of BSE &NSE Comparison of Derivative and Cash Market Turnover of BSE and NSE 35000000 30000000 25000000

Cash Market Turnover at BSE

20000000

Cash Market Turnover atNSE BSE Derivatives Turnover NSE DerivativesTurnover

15000000

The above graph shows the cash market and derivatives turnover from 1992 to 2012. BSE cash market includes BSE Sensex commenced from January 2, 1986 and BSE- 100 Index which commenced from April 3, 1984 and NSE cash market includes S&P CNX Nifty Index which commenced from November 3, 1995 and CNX Nifty Junior which commenced from November 4, 1996. The cash market of BSE was Rs.45,696 crores in 1992-93 and increased till Rs. 10,00,032 crores in 2000-01 the year derivatives was introduced. Derivatives turnover stood at Rs. 1673 crores in 2000-01 and Rs. 808476 crores where it surpassed the turnover of Cash Market. The NSE derivative market by the figure itself reflects the high margin increase in from 2002-03 where the derivatives turnover was Rs. 439866 crores and cash market turnover was Rs.314073 crores.

Graph showing the daily comparison of the Cash segment and Derivatives Turnover of BSE and NSE Daily turnover of Cash and Derivatessegement of NSE and BSE 3,50,000.00

Turnover

3,00,000.00

CASH -BSE

2,50,000.00

CASH -NSE

2,00,000.00

F&O -BSE F&O -NSE

1,50,000.00

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1,00,000.00

Jan-08

Jan-09

Jan-10

Jan-11

Jan-12

The above graph reflects the daily trend growth of Cash and F&O segment turnover where the cash market turnover as on 2nd Jan 2007 was Rs.3, 380.94 crores but the Futures and Options turnover was gained only from 24th Jan 2011 which was Rs.0.03 crores but it surpassed the cash market by 31st December 2012 where the turnover of derivatives was Rs. 20,944 crores but the cash market turnover was Rs. 1,781.61 crores. The F&O segment of NSE has always surpassed the Cash market with the date beginning from 2nd Jan 2007 with Rs. 19,957.26 crores to Rs. 48,894.61 crores on 31st December 2012 and the Cash market turnover beginning with Rs. 5,938.27 crores to Rs. 7,547.27 as on 31st December2012.

Graph showing Monthly comparison of the turnover of Index Futures in BSE and NSE

It is evident from the above graph that there is huge gap in the turnover between the two Stock Exchanges when compared on Index Futures.

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Graph showing Monthly comparison of the turnover of Index Options in BSE and NSE

Handbook of Statistics on Indian Securities Market 2012 It is evident from the above graph that there is huge gap between the turnovers of the two Stock Exchanges when compared on Index Options too.

Graph showing Monthly comparison of the turnover of Stock Options in BSE and NSE

Handbook of Statistics on Indian Securities Market 2012 The above graph also suggests there is huge difference in the monthly turnover of Stock Options in BSE and NSE. 54 | P a g e

Graph showing Monthly comparison of the turnover of Stock Futures in BSE and NSE

The above suggests the same like previous graph that there is huge difference in the monthly turnover of Stock Futures in BSE and NSE.

Graph showing

the

Volatility

of

Major Indices of

Indian Captial Market

Volatility of major indices of Indiancapital market

2.7 2.2 1.5

2.8

2.8 1.5 1.2

1.5

BSE-100

1.1

1.7

2.4 12.9

2.5 1.8

1.1

BSE-500

The price volatility of all the indices of BSE and NSE move in the similar trend over the years but the volatility shows a decrease in 2000-01 which could be the reason of introduction of derivatives and also may be may be due to many other factors, including better information dissemination and more transparency and increase in 2008-09 which could be due to the Global financial crisis. 55 | P a g e

Graph showing the comparison of Index Futures of the Global exchanges with BSE and NSE

CONTRACTS TRADED

Comparison of contracts traded of Global exchanges with BSE and NSE in Stock American Exchanges Index Futures 1400000000.00 1200000000.00

European-African

y = 4E+07x + 5E+08 R² = 0.162

y = 7E+07x + 2E+08

1000000000.00

exchanges BSE Index Options

= 0.858+ 5E+07 NSE Index Options y =R²4E+07x Linear (American R² = 0.896

800000000.00

y = 2E+07x -2E+07

600000000.00

Linear (EuropeanExchanges) African exchanges) Exchanges) Linear (Asia Pacific

= 0.768- 47342Linear ( BSE Index y =R²39847x Options) R² = 0.174

400000000.00

Graph showing the comparison of Stock Index Options of the Global exchanges with BSE and NSE Comparison of contracts traded of Global exchanges with BSE and NSE in Stock Index Options 5000000000.00

CONTRACTS TRADED

American

4000000000.00 3000000000.00

y = 4E+07x +3E+09

Exchanges European-African

R² = 0.032 1000000000.00 0.00 -1000000000.00

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R² = 0.749

R² = 0.78 y = 4E+07x+2E+08

2,003 2,004 2,005 2,006 2,007 2,008 2,009 2,010 2,011 2,012 R² = 0.582

exchanges Asia Pacific Exchanges BSEIndex Options

Graph showing the comparison of Stock Options of the Global exchanges with BSE and NSE

Comparison of contracts traded of Global exchanges with BSE and NSE in Stock American Exchanges Options CONTRACTS TRADED

3500000000.00 3000000000.00

y = 2E+08x + 8E+08

2500000000.00

R² = 0.757

2000000000.00

y = 2E+07x - 2E+07 R² = 0.786

R² = 0.008

Asia Pacific Exchanges BSE Index Options NSE Index Options

y = 3E+06x - 6E+06Linear (American Exchanges) R² =0.741 Linear (European-African

1500000000.00 1000000000.00

R² = 0.203

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Graph showing the comparison of Stock Futures of the Global exchanges with BSE and NSE Comparison of contracts traded of Global exchanges with BSE and NSE in Stock

800000000.00

Futures y = 8E+07x - 8E+07 600000000.00

European-African exchanges

R² =0.776 AsiaPacific

400000000.00 200000000.00 0.00

y = 2E+07x +5E+06 y = 1E+07x - 3E+07Linear (Europeany = 1E+07x - 3E+07 R² = 0.779

R²=0.779 2012

Linear (Asia Pacific Africanexchanges) Linear (Asia Pacific Exchanges) Exchanges) Linear (NSE Index

The above four graphs in relation to the comparison of BSE and NSE with Global exchanges suggests that BSE and NSE along with Global exchanges is showing upward trend in respect to all the derivative instruments which is evident from the Regression equation but still way behind in comparison with the growth rate. NSE is still in the comparison mode to the Global exchanges but BSE needs to upscale itself to be on par with the growth rate of the derivative market of the Global exchanges.

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Summary of findings Derivative market is growing very fast in Indian Economy. The turnover of derivative market is increasing year by year in the India’s largest stock exchange NSE. The turnover of NSE is 97 percent higher than BSE. The number of derivative contracts traded in NSE is 75% higher than BSE. NSE meanwhile is ranked third among the top thirty derivative exchanges in terms of number of contracts traded or cleared in the calendar year 2012. Nifty Options have Retained their rank as the world‟ssecondmosttradedoptionincalendaryear2012aswell.Andsecondposition respectively. Though the NSE derivative market is much larger compared to the BSE but it lags way behind the global exchanges which rejects the hypothesis that Indian derivatives market is in line with the global exchanges.

NSE Derivatives segment surpasses the Cash and Derivative market turnover of not only BSE but also the cash market turnover of its own in daily and yearly trend. There is an impact of introduction of derivatives on Cash market segment as the investors preferring derivatives to hedge their risks in the highly fluctuating price trend in India.

For the first time the turnover in the derivatives market of BSE has crossed the equity market turnover in 2011-12 driven mainly by the incentives offered by the exchange. The NSE derivatives turnover is 91 percent higher than equity turnover of its own.

Derivatives market segment contribution to GDP ratio is 92 percent higher than the cash market turnover and thus empowering the growth of economy of India.

The growth of Index and Stock Futures of BSE in terms of turnover and number of contracts traded is variants with the growth number of contracts and turnover of Index and Stock Futures of NSE and rejecting the hypothesis that there is a correlation within the Index and Stock Futures of BSE and NSE. 58 | P a g e

The Index Call and Put Option of BSE is statistically insignificant which means that average increase in the Index Call and Put Option of NSE may lead to the average increase in the Call and Put Option of NSE in the number of contracts traded but it is statistically significant for the Single Stock Call and Put Option where increase in one does not affect the latter. This partially accepts the hypothesis of the increase in the number of contracts traded for Index Options of BSE leads to the increase in the Index Options of NSE but not the same with the Single Stock Options.

The average increase in the turnover of Index Call and Put Option of NSE leads to the increase in the turnover of Index Call and Put Option of BSE which is supported by the p-value of two tailed paired t-test but Stock Call Stock Option of BSE is statistically insignificant with Stock Call Option of NSE supporting the hypothesis that there is a correlation between them but Stock Put Option of BSE is statistically signification with Stock Put Option of NSE with 0.005 value rejecting the hypothesis.

Volatility of all the Indices are in line with each other except Nifty Junior which consists of only 50 stock and highly volatile in the beginning compared to other Indices. The volatility has shown a decline in 2000-01 and one of the factor may be due to the introduction of derivatives in India and increase in 2008-09 attributing to the Global crisis supporting the hypothesis that derivatives is one of the factor impacting the volatility of Market.

The growth in the number of contracts of Stock Index Option for Asia Pacific and European exchanges have increased considerably but still is variant with the number of contracts traded in American exchanges. In case of Index Future there is a phenomenal increase in the number of contracts traded in Asia Pacific and European exchanges but the American exchanges still showed not a perfect secular trend over the years? European exchanges have surpassed the American exchanges in the year 2012 in the number of Index Future contracts traded.

National Stock exchange stands on par with Global exchanges in terms of the number of contracts traded for Stock Index Options and Futures and also Stock Futures but the Stock Options has not made it to the Top 5 exchanges though the options available for trading were changed from American to European style in2011. 59 | P a g e

Index Options holds the majority in the volume of Contracts traded and turnover in BSE but it differs in the turnover of NSE. The majority of the turnover for NSE is from Stock Options segment with minimal contracts which indicates the high amount traded on each contract on an average over the years and again Index options holds majority in the number of contracts traded even in NSE.

BSE Sensex and Derivatives turnover has shown a decline post 2008 could be attributing to the factor of global financial crisis. NSE tops BSE in terms of monthly turnover and number of contracts traded in a relatively high margin in all the derivative instruments rejecting the hypothesis that there is a relation in the increase of BSE and NSE derivative turnover and Number of contracts traded. National stock exchange has made it to the Top 5 exchanges in terms of the contracts traded but when compared with the Total number of contracts traded of all the American exchanges, Asia Pacific and European exchanges, NSE still stands behind but it is ahead of BSE. Hence both BSE and NSE still needs to grow to reach to the global level which in fact rejects my hypothesis that NSE and BSE are in par with global exchanges in derivatives market.

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CHAPTER 5 : THE CONCLUSION

Conclusions In terms of the growth of derivatives markets, and the variety of derivatives users, the Indian market has equaled or exceeded many other regional markets. While the growth is being spearheaded by retail investors, private sector institutions and large corporations, smaller companies and state-owned institutions are gradually getting into the act. Foreign brokers are boosting their presence in India in reaction to the growth in derivatives.

The variety of derivatives instruments available for trading is also expanding. In the past, there were major areas of concern for Indian derivatives users. Large gaps exist in the range of derivatives products that are traded actively. In equity derivatives, NSE figures showed that almost 90% of activity was due to index options, index futures & stock futures, whereas trading in options is limited 61 | P a g e

to a few stocks, partly because stock options were of American style & they are settled in cash and not the underlying stocks.

But with the start of 2011 all stock options available for trading were changed to European style. This change has led to the liquidity in stock options not only close to ATM strikes but also across multiple strikes just as in case of index options. This change has encouraged the options writers to go ahead eliminating the assignment risk prior to expiry which will eventually benefit them. The study concluded that there is a huge difference in the way BSE and NSE functions in terms of derivatives which is evident with the turnover and the number of contracts traded. The Indian derivatives market has shown a tremendous growth but is still not in line with the global derivatives market. Considering

many

changes currently, derivatives market in India is poised to grow and mature

further to accommodate larger participation across varied asset classes by wide range of participants.

There is a lot of scope of growth for Indian Derivatives Market and it is showing in its signs on the global platform. With the robust regulations, strengthening of our financial structure and more knowledge on derivatives market would gain more of investor confidence in the market and more of trading on derivatives for hedging purpose which is the very purpose for the reason for the existence of derivatives market.

There is a scope to further study the Single Options growth, Currency derivatives, Interest rate derivative, and Credit derivatives in comparison to the global market as they are all in the growing stages in the Indian derivatives market.

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rces/589748-