A Study on Relative Volatility in Spot and Futures Market in Selected Stock Indices of NSE

Transcription

1 A Study on Relative Volatility in Spot and Futures Market in Selected Stock Indices of NSE Dr.Saya Swaroop Debasish This study attempts to investigate e change, if any, in e volatility observed in e Indian stock market due to e introduction of futures trading. The change in e volatility is compared in terms of e structure of e volatility. This is done to give insights into e way e futures market is influencing e Indian spot market's volatility. The main objective of e study is to investigate wheer ere has been significant change in relative volatility of e underlying spot return and futures return. The st st period of study is from 1 January 2000 to 31 December 2010 for e spot prices. The study used ree stock indices of NSE namely Nifty, CNX IT and CNX Bank. The index futures time series analyzed here uses data on e near mon contract as ey are most heavily traded. The study has used four measures of volatility. The study finds at for e ree NSE indices, e study rejects e null hypoesis of 'no significant change in relative inter-day volatility between spot prices and futures prices' over e entire period , but cannot reject e hypoesis fully for all e individual years. There is significant change in relative intra-day volatility between spot prices and futures prices for all e ree NSE indices. Key Words: Volatility, India, NSE, Indices, Futures Market transferred from e spot market to e futures market at can dampen spot market volatility. Since e proposed logical arguments bo support and reject e proposition of futures markets having a destabilizing effects on spot markets, it is self- evident at e eoretical debate on how futures markets affect underlying stock markets still remains raer inconclusive. In e Indian scenario, e NSE ( national stock exchange) introduced stock index futures and options on e National Stock Exchange's index of 50 stocks (S&P CNX NIFTY) in June 12, 2000 and June 4, 2001 respectively. Subsequently single stock futures were launched at NSE on November 9, The advent of stock index futures has profoundly changed e nature of trading on stock exchanges. The concern over how trading in futures contracts affects e spot market for underlying assets has been an interesting subject for investors, market makers, academicians, exchanges and regulators alike. Any increase in stock market volatility at has Introduction Derivatives play a very important role in e price discovery process and risk management. It is widely used by mutual funds and institutional investors for risk management purposes. Two main bodies of eories exist in e literature about e relationship between derivatives markets and underlying spot markets. The eoretical literature proposes bo a 'destabilizing forces' hypoesis at predicts increased volatility and a 'market completion' hypoesis in which decreased volatility is predicted. For e former hypoesis, it is argued at e inflow and existence of speculation in futures markets may induce destabilizing forces, which among oer ings create undesirable 'bubbles'. However, e contrary view is at e introduction of futures trading leads to more complete markets, enhances information flow, and ereby improves e investment choices faced by e investors. Moreover, futures trading may bring more (private) information to e market and allow for a quicker dissemination of information. Furer, speculative activity may be 5

2 followed e onset of futures trading has generally been taken as justifying e traditional view at e introduction of futures markets induces destabilizing speculation. This has led to a necessity for greater regulation to minimise any detrimental effects. An alternative view is at futures markets provide an additional route by which information can be transmitted and erefore, increased spot market volatility may simply be a consequence of e more frequent arrival and more rapid processing of information. Thus, futures trading may be fully consistent wi efficiently functioning markets. There has been widespread interest in e effects of futures trading on prices in e underlying spot market. It has been often claimed at e onset of derivative trading will destabilize e associated spot market and us lead to increase in spot price volatility. Oers have argued to e contrary, stating at e introduction of futures trading will stabilize prices and so lead to decrease in price volatility. Why should e introduction of futures trading increase e volatility of cash market? Conventional wisdom suggests, to e contrary, at futures trading should bring more traders to e cash market, making cash market more liquid and erefore, less volatile. The view at futures trading may increase volatility appears to stem from a belief at futures markets bring wi em uninformed (or irrational) speculators who en trade in e cash market as well as e futures market. Such speculators, it is argued, drive prices up or down in e quest for short-run 'bandwagon' profits. Economists have analysed is irrational speculation argument and have concluded at it would take a considerable number of such speculators to destabilize e cash markets. Since futures encourage speculation, e debate on e impact of speculators intensified when futures contracts were first introduced for trading, beginning wi commodity futures and moving on to financial futures. Before furer regulations are introduced, it is essential to determine wheer in fact ere is a causal link between e introduction of futures and spot market volatility. It, erefore becomes imperative at we seek answers to questions like: What is e impact of derivatives upon market efficiency and liquidity of e underlying cash market? To what extent do derivatives destabilize e financial system, and how should ese risks be addressed? Can e results from studies of developed markets be extended to emerging markets? The launch of derivative products has significantly altered e movement of e share prices in e spot market. The spot and futures market prices are linked by arbitrage, i.e., participants liquidating positions in one market and taking comparable positions at better prices in anoer market, or choosing to acquire positions in e market wi e most favourable prices. If, for example, e observed futures price is above (below) e eoretical futures price, arbitrageurs sell (buy) futures and buy (sell) e underlying security, driving down (up) e price of e futures and driving up (down) e prices of security. This raises important questions about e effect at index derivatives have on volatility of e spot market. While ere is still disagreement as to wheer futures trading increases or decreases e volatility of spot prices, e question is still an empirical one Objectives and Hypoeses This study attempts to investigate e change, if any, in e volatility observed in e Indian stock market due to e introduction of futures trading. The change in e volatility is compared in terms of e structure of e volatility. This is done to give insights into e way e futures market is influencing e Indian spot market's volatility. The main objectives of e study is to investigate wheer ere has been significant change in relative volatility of e underlying spot return and 6

3 futures return. The following null hypoeses were tested for significance: a) There is no significant change in Relative Inter-Day volatility between spot prices and futures prices. b) There is no significant change in Relative Intra-Day volatility between spot prices and futures prices. The above two hypoeses were tested for e ree NSE indices. Review of Literature There is a common belief at stock index futures are more volatile an e underlying spot market because of eir operational and institutional properties. The close relationship between e two markets makes possible e transference of volatility from futures market to e underlying spot market. It is, erefore, not surprising at since e inception of index futures contracts in 1982 e issue of volatility of futures contracts relative to e stock market has attracted e attention of researchers world over. In eir study, Chu and Bubnys (1990) examined relative volatility using daily returns for e S&P 500 and e NYSE for e period 1982 to They reported at futures volatility was higher in comparison to e underlying indices. Yadav and Pope (1990) used several volatility measures such as ose based on daily close-to-close, open-to-open prices and e Parkinson Extreme Value Estimator to compare FTSE 100 index and futures volatility. They found futures volatility to be higher in comparison to e FTSE index. In one study on e Japanese market, Brenner, Subramanyam and Uno (1990) examined daily closing prices of e Nikkei Futures contract traded on SIMEX. They found at e volatility of e underlying Nikkei Stock index was marginally higher an e futures contracts traded in Osaka but no different from at of SIMEX. In anoer study, Koutmas and Tucker (1996) reported at e volatility in bo e futures and stock markets were persistent. Choudhury (1997) studied e short-run relative volatility on e Hang Seng, e Australian All Ordinaries, and e Nikkei. He reported at wi e exception of e Nikkei, e oer futures contracts were found to be more volatile an eir underlying spot markets. Several studies have been conducted to examine e behaviour of spot market volatility since e inception of futures trading. Edwards (1988) tried to gaer evidence to verify e fact at stock index futures trading have destabilised e spot market in e long run. Using variance ratio F tests from June 1973 to May 1987, he found at e introduction of futures trading has not induced a change in e volatility in e long run. He observed at ere was some evidence of futures-induced short-run volatility, particularly on futures contract expiration days, but is volatility did not appear to carry over to longer periods of time. It is seen at e results on e effect of index futures on e underlying spot market volatility are mixed. One view is at derivative securities increase volatility in e spot market caused by more highly levered and speculative participants in e futures market. The introduction of stock index futures causes an increase in volatility in e short run while ere is no significant change in volatility in e long-run (Edwards 1988). This is because futures markets result in uninformed (irrational) speculators trading in bo futures and cash markets, shocking prices in search of short-term gains. Ross (1989) demonstrated at, under conditions of no arbitrage, variance of price change must be equal to e variance of information flow. This implied at e volatility of e asset price will increase as e rate of information flow increases. If is is not e 7

4 case, arbitrage opportunities will be available. It persistent. The study also provided evidence of follows, erefore, at if futures trading increase volatility linkages between e spot and futures e flow of information, en in absence of markets. Contemporaneous transmission effects arbitrage opportunities e volatility of e spot across volatilities of e Indian (NSE) Stock and price must change. Index futures markets were tested on daily data, using an asymmetric (reshold) GARCH Gordon and David (2002) examined e intra-day framework. These results had implications for and intra-week volatility patterns and tests e understanding e pattern of information flows wait-to-trade hypoesis using 24-hour inter-day between e two markets. The results indicated returns and 15-minute intraday returns on e at e futures market plays a leading role in Hang Seng Index (HSI) and Hang Seng Index assimilating information and us moderating, Futures (HSIF). Empirical results showed at for ough to a small extent, e spot market volatility. all weekdays, inter-day returns of HSIF are more volatile an ose of HSI. An intra-week pattern Pati and Kumar (2007) examined e volatility had existed at 2.45 P.M. for bo markets wi dynamics and investigated e Samuelson highest volatility on Monday. For e intraday Maturity Hypoesis ( a source of non-stationary in returns, HSI was found to be significantly more e volatility of futures price) in e context of e volatile an HSIF for e first minutes after Indian Futures Market by taking Nifty Index e markets open on all weekdays except Monday Futures traded on NSE. The sample data consisted on which HSI is more volatile for e first one hour. of daily closing price, volume and open interest of An intra-week pattern exists at A.M. for bo Nifty Index futures from e period January 1, markets wi lowest volatility on Thursday to December 29, 2005 for near-mon Through an analysis on e intraday correlations contract wi 1009 sample data points. They between HSI and HSIF, ey argued at e constructed data sample by switching or rolling significantly larger open intraday volatility in HSI, over to e next maturing contract, four days before which is inconsistent wi e wait-to-trade e expiration date. For empirical issues, hypoesis, is mainly caused by noise trading univariate GARCH, E-GARCH family models was unrelated to information arrival. employed. The conditional variance was augmented by including open interest and trading A study by Bose (2007) examined e volume as exogenous explanatory variables. The characteristics of return volatilities in e equity empirical evidence suggested at ere was timemarket and e index futures market in India. varying volatility, volatility clustering and leverage Volatility in e NSE Nifty index and at in its effect in e Indian futures market. Their study futures market were bo seen to exhibit features of found a positive contemporaneous relationship mean reversion, volatility clustering and a fair between futures price volatility and volume. Their degree of volatility persistence, estimates of which study concluded at time-to-maturity is not a give an idea of e impact and duration of a strong determinant of futures price volatility, but particular information shock to e market. The e rate of information arrival proxied by volume returns volatility was found to exhibit significant and open interest are e important sources of asymmetric response in times of market retreats volatility. and advances, wi volatility arising in times of market decline being much sharper and more Bagchi (2007) analyzed e relative impact of 8

5 derivatives market. The study observed at price innovations appeared first in e derivatives market and were en transmitted to e equities market. The dynamics of such information transport between stock market and derivatives market were studied using e information eoretic concept of entropy, which captures non- linear dynamic relationship also. Data and Sources The study has used data on daily opening, low, high and closing prices of e selected indices and individual stocks traded in e spot market. The futures data include e near-mon prices of daily opening, low, high and closing. The spot prices and e one-mon futures prices of e selected stocks and indices are taken for e study. The futures time series analyzed here uses data on e near mon contract as ey are most heavily traded. The study used data on daily opening, low, high and closing prices of e selected indices and individual stocks traded in e spot market. The futures data include e near-mon prices of daily opening, low, high and closing. The spot market volatility of selected NSE indices was studied by a statistical comparison of volatility between pre-futures and post-futures (i.e., after e introduction of futures trading). The two kinds of volatility studied were inter-day volatility and intra-day volatility. The study investigated presence of any significant changes in spot volatility between ese sub-periods. The Null hypoesis of 'no significant difference in spot volatility between pre-futures and post-futures period' was tested at 1%, 5% and 10% levels of significance. volatility measure computed from e four parameters, such as closing, high and low quotes of e day as well as a combination of ese ree on e stock index return. In addition, various timesteps were also selected for such computation. The study selected a middle capitalization stock index in India called CNX Midcap 200, which represented around 72% of middle order firms listed on e National Stock Exchange (NSE) of India. He used an entropy of volatility to measure information content on various time steps as well as using various pricing parameters. The study used GARCH (1,1) to find out e impact of volatility. Based on e analysis of entropy, e results indicated at ere had been a relatively high impact of e volatility computed on high-low- closing prices and e lowest impact is found for volatility computed on high prices of e securities. The above results also confirmed at e entropy of volatility was a valuable indicator for evaluating e performance of e volatility. Bodla and Kiran (2008) attempted to investigate e impact of equity derivatives on e trading volume of underlying Indian stock market. Their study found a positive impact of expiration of derivatives on trading volume of sample stocks. For is purpose, e daily traded value data of cash market and 22 individual stocks were collected and analyzed by using before-and-after control sample technique. The results of e study also showed at Compound Annual Grow Rate (CAGR) of trading volume had declined slightly after e introduction of derivatives. Reddy and Sebastin (2008) studied e temporal relationship between e equities market and e derivatives market segments of e stock market using various meods and by identifying lead-lag st st The period of study is from 1 January 1997 to 31 relationship between e value of a representative December 2010 for e spot prices. The futures index of e equities market and e price of a trading on most of e individual stocks at NSE corresponding index futures contract in e commenced from 9 November 2001 and for few at 9

6 a later period. Hence, e futures data on indices and stocks covers period from eir futures trading st commencement till 31 December For e futures data, e trading on stock indices started on spot-futures period is tested using F-test. This is repeated for several sub-periods. Next, e study measure relative volatility between spot prices and futures prices taking half-yearly sub-periods 12 June 2000 for NSE Nifty, 29 August 2003 for starting from e commencement of futures CNX IT and on 12 June 2005 for CNX Bank. The index futures time series analyzed here uses data on e near mon contract as ey are most heavily traded. For e futures data, e trading on stock indices started on 12 June 2000 for Nifty, 29 August 2003 for CNX IT and on 13-June-2005 for CNX Bank. S&P CNX Nifty S&P (Standard & Poor) NSE Nifty is a well diversified 50 stock index accounting for over 23 sectors of e Indian economy. S&P NSE Nifty is owned and managed by India Index Services and Products Ltd. (IISL), which is a joint venture between NSE and CRISIL. Nifty stocks represent about 59.49% of e total market capitalization as st on 31 December 2010 (i.e., e last date of our study period). Research Meodology The study starts wi analyzing absolute intra-day and inter-day volatility on spot prices and comparing ese during e pre-futures and post- futures period. The study has used four measures of volatility. These are (a) volatility based upon close-to-close prices, (b) volatility based upon open-to-open prices, (c) Parkinson's Extreme Value Estimator (intraday price range estimator), & trading on e concerned indices and stocks. All e above four measures of volatility are again utilized for is purpose and F-test is employed for null hypoesis testing of significant difference in volatility between spot and futures prices during e post-futures period. In e first place, e daily returns based on spot and futures prices were computed. The price series consisted of open price, low, high, and closing prices for bo spot and futures market. The returns for e futures contract and e spot index are defined as RF = {Ln (F / F )}and t t t-1 t RS = {Ln (S t / S t-1) }, respectively where F t and S t are e futures prices and spot prices on day t, respectively The study has used four measures of volatility as provided by research studies of Ibrahim, Oman and Bacha (1999). These are (a) e first is based upon close-to-close prices,(b) e second is based upon open-to-open prices, c) Parkinson's High- Low Extreme Value Estimator, and (d) Garman- Klass volatility (GKV) measure. (a) Close-to-Close Volatility (CCV): This measure of volatility is based upon close-toclose prices. Close-to-Close Volatility is computed from e variance of close-to close daily return as given by eq.(1): T 2 CCV = Σ t=1 (R t R m) / T-1 (1) where R = Ln( C / C ) (2) t t t-1 (d) Garman-Klass volatility (GKV) measure. The null hypoesis of significant difference in volatility in spot prices between pre-futures and wi C t and Ct-1 being e closing prices on day t and t-1 respectively; R m representing e return on day t; representing e mean or average return based on closing prices. 10

7 (b) Open-to-Open Volatility (OOV) close and open prices respectively. This measure of volatility is based upon close-to- close prices. Close-to-Close Volatility is computed from e variance of close-to close daily return as given by eq.(3): T 2 OOV = Σ t=1 (R t R m) / T-1 (3) For measuring relative volatility, e study computes e volatility of spot prices and futures prices using each of e 4 volatility measures. The null hypoesis tested is as follows: Null Hypoesis: There is no significant difference where R t = Ln( O t / O t-1) (4) between e relative volatility of e post market and e futures market i.e., e volatility of e wi Ot and Ot-1 being e closing prices on day t and underlying spot market is not significantly t-1 respectively; R m representing e return on day different from e volatility of e futures market. t; representing e mean or average return based In statistical terms, e null and alternative on opening prices. hypoesis is specified as under: (c) Parkinson's High-Low Volatility Estimator (PHLE) This measure of volatility estimates intra-day volatility. Parkinson's High-Low Volatility Estimator (PHLE) can be computed using eq.(5) as given below. PHLE H : σ (spot) = σ (futures) 0 H : σ (spot)? σ (futures) 1 where H0 and H1denote e null and alternative hypoesis, respectively; is e standard deviation ( measure of volatility); 'spot' represent e spot ln( H market ; 'after' denote e futures market. t / Lt ) 2 PHLE = K N The volatility is computed for yearly periods after where K=0.601; ln symbolized log; N is e total e introduction of futures trading, ie. from year number of trading days considered; H t and Lt 2001 to year 2010 and e entire post-futures denote intra-day high and low prices respectively. period of This is because for most of e Beckers (1983) has empirically concluded at selected Nifty indices, e futures trading started Parkinson's high-low estimator contains new after year For NSE Nifty, e volatility is information and is an accurate estimator of true computed from year 2000 since futures started on volatility Nifty on 12 June,2000. But for oer two indices (d) Garman-Klass Volatility (GKV) measure Garman-Klass Volatility (GKV) uses four intra-day variations of prices namely, daily opening prices, daily highest price, daily lowest prices and daily closing prices. GKV can be computed as given in eq.(6). namely CNX IT and CNX Bank, e volatility is computed after futures introduction in year 2003 and 2005, respectively. The relative volatility of e two markets (futures and spot) have been studied on a contemporaneous basis and tested for statistical significance by using F-Test. Analysis and Findings where H, L, C, and O denote intra-day high, low, t t t t Inter-day Relative Volatility in Spot and Futures Market for Selected NSE Stock 11

8 Indices Table-1 presents e inter-day volatility of spot and futures market year-wise for e ree selected NSE indices. For NSE Nifty, e volatility is higher for futures market for all e individual years under study. Furer, e inter-day volatility of NSE Nifty futures is in comparison for spot market over e entire period of Only for year 2004, e relative inter-day volatility of Nifty is statistically significant wi futures volatility higher at and spot volatility at For CNX-IT and CNX-Bank, e futures volatility is relatively higher an spot inter-day volatility for all e years. Table-1 Relative Inter-day Volatility of Spot and Futures market using Close-to-close prices (CTCP) in NSE Stock Indices Year Type of Market / Relative volatility using CTCP: Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2000 Spot Futures N.A. N.A. F-test Prob Spot Futures N.A. N.A. F-test Prob Spot Futures N.A. N.A. F-test Prob Spot Futures N.A. F-test Prob *** 2004 Spot Futures N.A. F-test Prob *** 0.023** 2005 Spot Futures F-test Prob ** 2006 Spot Futures F-test Prob *** ** 2007 Spot Futures F-test Prob ** ** 2008 Spot Futures F-test Prob Spot Futures F-test Prob * Spot Futures F-test Prob *** *** Spot Futures F-test Prob ** * 0.046** Note: F-test Prob. denotes e probability of e F-test on e two sub-periods, called pre-futures and post-futures. *,** and *** denote significance at 1%, 5% and 10% levels, respectively. N.A.- Not applicable; Futures trading in NSE CNX IT and NSE CNX-Bank commenced on 29 August 2003 and 13 June,2005, respectively. Futures trading on NSE Nifty started on 12 June,

9 During e period , e inter-day volatility of CNX-IT for spot and futures was found to be and respectively, and for CNX- Bank e volatilities were and for period, e spot volatility of NSE Nifty is lesser (0.0142) an futures market (0.0166) wi statistical significance at 1% level. Spot volatility was found to be highest in year 2004 (0.0178) while spot and futures market, respectively. Thus, e highest futures volatility was observed in year 2001 futures market volatility is lesser an at of spot (0.0208). For CNX-IT, highest spot volatility was volatility for e ree indices. Furer, it is in year 2006 (0.0272) and lowest in year 2004 observed at e values of inter-day spot volatility of all e ree indices consistently decreased from (0.0146). For all e individual years under study, futures volatility is found to be relatively higher year 2001 to year This indicates a stabilizing an spot market wi highest value in year 2006 effect of futures introduction on spot volatility for e selected NSE indices. (0.0283) significant at 5% level, and lowest in year 2005 (0.0186) wiout any statistical significance. For CNX-Bank, highest spot volatility was in year Table-2 presents e open-to-open prices based 2000 (0.0232) and lowest in year 2007 (0.0164). inter-day volatility for e ree selected NSE For all e years, futures volatility is relatively indices in spot and futures market over e period higher an spot market. Over e entire study The spot volatility of NSE Nifty is period , e spot volatility of CNX-Bank relatively higher an at of futures market for all was lower (0.0145) an futures market (0.0163) e years under study, and is has decreased from wi statistical significance in 2001 to in 2010.Over e entire Table- 2 : Relative Inter-day Volatility of Spot and Futures market using Open-to-Open prices (OTOP) in NSE Stock Indices Year Type of Market / Relative volatility using OTOP: Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2000 Spot Futures N.A. N.A. F-test Prob * 2001 Spot Futures N.A. N.A. F-test Prob * 2002 Spot Futures N.A. N.A. F-test Prob Spot Futures N.A. F-test Prob ** 2004 Spot Futures N.A. F-test Prob Spot Futures F-test Prob *** 2006 Spot Futures F-test Prob * **

10 Year Type of Market / Relative volatility using OTOP: Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2007 Spot Futures F-test Prob Spot Futures F-test Prob Spot Futures F-test Prob * Spot Futures F-test Prob * Spot Futures F-test Prob * ** * Note: F-test Prob. denotes e probability of e F-test on e two sub-periods, called pre-futures and post-futures. *,** and *** denote significance at 1%, 5% and 10% levels, respectively. N.A.- Not applicable; Futures trading in NSE CNX IT and NSE CNX-Bank commenced on 29 August 2003 and 13 June,2005, respectively. Futures trading on NSE Nifty started on 12 June,2000. Thus, from table 2 and table 3, we can reject e null hypoesis of no significant change in Relative Inter-Day volatility between spot prices and futures prices over e entire period , but we could not reject e hypoesis fully for all e individual years. Intra-day Relative Volatility in Spot & Futures for Selected NSE Stock Indices Table-3 : Relative Intra-day Volatility of Spot and Futures market using High-Low prices (HLP) in NSE Stock Indices BANKYear Type of Market / Relative Intra-day volatility using HLP: Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2000 Spot Futures N.A. N.A. F-test Prob * 2001 Spot Futures N.A. N.A. F-test Prob * 2002 Spot Futures N.A. N.A. F-test Prob * 2003 Spot Futures N.A. F-test Prob * ** 2004 Spot Futures N.A. F-test Prob * *** 2005 Spot Futures F-test Prob * ** ** 14

11 BANKYear Type of Market / Relative Intra-day volatility using HLP: Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2006 Spot Futures F-test Prob * * * 2007 Spot Futures F-test Prob * * *** 2008 Spot Futures F-test Prob * ** Spot Futures F-test Prob * ** Spot Futures F-test Prob * ** Spot Futures F-test Prob * * * Note: F-test Prob. denotes e probability of e F-test on e two sub-periods, called pre-futures and post-futures. *,** and *** denote significance at 1%, 5% and 10% levels, respectively. N.A.- Not applicable; Futures trading in NSE CNX IT and NSE CNX-Bank commenced on 29 August 2003 and 13 June,2005, respectively. Futures trading on NSE Nifty started on 12 June,2000. Table-3 presents e intra-day (high-low) volatility volatility. Highest intra-day futures volatility for of spot and futures market for e NSE indices. It is CNX- Bank was witnessed during year 2006 observed at for all e ree indices, e relative (0.1540) and lowest during year 2005(0.0781). volatility of futures market is lower an e corresponding spot volatility wi statistical Over e entire period, e intra-day volatility of CNX-Bank is relatively lower for futures market significance. For e period , futures (0.1131) an spot market (0.1275). market volatility of NSE Nifty is lower (0.0952) an spot volatility (0.1023) and is difference is significant at 1 % level. For CNX-IT, e spot volatility is highest in year 2000 (0.1455) and lowest in year 2006 at (post- futures). This supports our view at intra-day spot volatility has stabilized after futures introduction. The relative intra-day volatility of CNX-IT over period is lesser for futures market (0.1204) an spot market (0.1429) but wi statistical significance. Highest futures volatility of CNX-IT was observed during year 2005 (0.1564) and lowest futures volatility during year 2003 (0.0941). Similarly for CNX-Bank, e futures volatility in all e individual years is significantly lower an spot Table-4 depicts e intra-day GKV volatility of spot and futures market for e NSE indices over e period For NSE Nifty, e spot volatility was higher an futures volatility during e years 2001, 2002, 2003 and 2007, and e opposite for e remaining years under study. Over e entire study period, ere was significant difference between spot (0.0011) and futures (0.0017) volatility in NSE Nifty. For CNX-IT, e intra-day spot volatility was higher an futures volatility for all e years wi spot volatility being highest in year 2001 (0.0382) and lowest in year 2007(0.0192). Highest futures volatility of CNX-IT was observed during year 2003 (0.0209) and 15

12 lowest futures volatility during year 2005 (0.0148) (0.0201) and lowest during year 2007 There was evidence of difference between spot and futures intra-day volatility tested statistically significant at various levels for all e years under study. Similarly, for CNX-Bank, e intra-day futures volatility was lesser an spot volatility for all e years under study. Highest intra-day futures volatility for CNX- Bank was witnessed during year (0.0167). Over e period , e volatility is found to be lower in futures market (0.0015) an spot market (0.0023) wi e difference being significant at 1% level. The intra-day spot volatility is always found to be higher an futures volatility for most of e individual years under study period. Table- 4: Relative Intra-day GKV Volatility of Spot and Futures market in NSE Stock Indices Year Type of Market / Relative Intra-day GKV volatility : Standard Deviation (S.D.) Indices Test Measure NSE Nifty NSE CNX-IT NSE CNX-BANK 2000 Spot Futures N.A. N.A. F-test Prob * 2001 Spot Futures N.A. N.A. F-test Prob * 2002 Spot Futures N.A. N.A. F-test Prob * 2003 Spot Futures N.A. F-test Prob ** 2004 Spot Futures N.A. F-test Prob ** * 2005 Spot Futures F-test Prob * ** 2006 Spot Futures F-test Prob *** * 2007 Spot Futures F-test Prob * ** *** 2008 Spot Futures F-test Prob ** * ** 2009 Spot Futures F-test Prob * * 2010 Spot Futures F-test Prob *** *** Spot Futures F-test Prob * * * Note: F-test prob. denotes e probability of e F-test on e two sub-periods, called pre-futures and post-futures. *,** and *** denote significance at 1%, 5% and 10% levels, respectively. N.A.- Not applicable; Futures trading in NSE CNX IT and NSE CNX-Bank commenced on 29 August 2003 and 13 June,2005, respectively. Futures trading on NSE Nifty started on 12 June,

13 Thus, from table 3 and table 4, we can reject e null hypoesis of No significant change in Relative Intra-Day volatility between spot prices and futures prices for all e ree selected NSE indices. Conclusion account for movements in e world market portfolio, asynchronous data and conditional heteroskedasticitv. 4. Forecasting futures prices of stocks and indices using Neural Network analysis is anoer potential area of furer research. For e ree NSE indices, e study rejects e null 5. An area of furer research could be a study hypoesis of 'no significant change in relative inter-day volatility between spot prices and futures prices' over e entire period , but cannot reject e hypoesis fully for all e individual years. There is significant change in relative intra-day volatility between spot prices and futures prices for all e ree NSE indices. Anoer area of research could be a study on stock market volatility before and after e introduction of index on intra-day return dynamics between e cash and futures market. 6. Yet anoer area of research could be e References study on measuring e effect of futures trading on e stability of stock index returns across various nations. futures trading in multi-county scenario, using 1. Abhyankar, A., (1995), Return and Volatility models at account for movements in e world Dynamics in e Ft-Se 100 Stock Index and market portfolio, asynchronous data and Stock Index Futures Markets, Journal of conditional heteroskedasticitv. Futures Markets, 15.4, pp Scope for Furer Research 2. Aggarwal, R., (1988), Stock Index Futures and There is still scope for furer research. Few of e potential areas of research are mentioned below. 1. An extension to our study is an empirical analysis examining e role of certain non- price variables, namely open interest and trading volume, from e stock option Cash Market Volatility, Review of Futures Markets, 7.2, pp Bagchi, D., (2007), An Analysis of Relative Information Content of Volatility Measures of Stock Index in India, ICFAI Journal of Derivatives Markets, 4.4, pp market in determining e price of 4. Ball, C. A., and Torous, W. N., (1986), Futures underlying shares in cash market. Options and e Volatility of Futures Prices, 2. A potentially allied area of research having Journal of Finance, 61.4, pp much practical utility could be a study on 5. Bessembinder, H. and Seguin, P. J., (1992), designing an optimum portfolio of stocks Futures Trading Activity and Stock Price for maximizing return. Volatility, The Journal of Finance, 57.5, 3. Anoer area of research could be a study on pp stock market volatility before and after e 6. Bodla, B. S. and Kiran, J., (2008), Equity introduction of index futures trading in Derivatives in India: Grow Pattern and multi-county scenario, using models at Trading Volume Effects, ICFAI Journal of 17

14 Derivatives Markets, 5.1, pp Intraday and Intraweek Volatility Patterns of Hang Seng Index and Index Futures, and a 7. Bose, S., (2007), Understanding e Volatility Test of e Wait-To-Trade Hypoesis, Characteristics and Transmission Effects in Pacific-Basin Finance Journal, 10.4, pp e Indian Stock Index and Index Futures 495. Market, Money & Finance. ICRA Bulletin, 3, pp Hogson, A. and Nicholls, D., (1991), The Impact of Index Futures Market on Australian 8. Brenner, M., Subramanyam, M. and Uno, J., Share Market Volatility, Journal of Business (1989), The Behaviour of Prices in e Nikkei Finance and Accounting, 18, pp Spot and Futures Market, Journal of Financial Economics, 23, pp James, T. W., (1993), How Price Discovery by Futures Impacts e Cash Market, Journal of 9. Choudhury, T., (1997), Short-Run Deviations Futures Market, 13.5, pp and Volatility in Spot and Futures Stock Returns: Evidence from Australia, Hong Kong 15. Kamara, A., (1992), Issues in Futures and Japan, The Journal of Futures Markets, Markets: A Survey, Journal of Futures 17, pp Market, 11, pp Chu, C.C. and Bubnys, E. L., (1990), A 16. Pati, P. C. and Kumar, K. K., (2007), Maturity Likelihood Ratio Test of Price Volatilities: City and Volume Effects on e Volatility: of London, Scottish Journal of Political Evidences from Nse Nifty Futures, ICFAI Economy, 36.1, pp Journal of Derivatives Markets, 4.4, pp Edwards, F.R., (1988), Futures Trading and Cash Market Volatility: Stock Index and 17. Yadav, P. K. and Pope, P. F., (1990), Stock Interest Rate Futures, The Journal of Futures Index Future Arbitrage: International Markets, 8, pp Evidence, The Journal of Futures Markets, 10, pp Gordon, Y. N. T., and David, T. W., (2002), Dr. Saya Swaroop Debasish is a Reader in P.G.Department of Business Administration, Utkal University, Vani Vihar, Bhubaneswar , Orissa, India. The auor can be reached at sayaswaroop2000@yahoo.com 18