Single Stock Futures Trading and Stock Price Volatility: Empirical Analysis

Transcription

1 The Pakisan Developmen Review 48 : 4 Par II (Winer 2009) pp Single Sock Fuures Trading and Sock Price Volailiy: Empirical Analysis SAFI ULLAH KHAN and SYED TAHIR HIJAZI * 1. INTRODUCTION A large number of sudies examine he relaionship beween fuures rading volume and he price volailiy in he underlying asse or marke. Conflicing resuls, however, has been obained o he effec ha fuures rading may increase or decrease volailiy in he underlying marke. Among he previous sudies on he issue of he fuures marke-volume and spo marke price volailiy, Schwer (1990) finds ha, a he ime of high volailiy for he S&P500 index, sock marke and fuures volume are also found o be high. Smih (1989), on he oher hand, observes no effec by S&P500 fuures volume on he changes in he volailiy of S&P500 index reurns. Similar resuls were also repored by Dara and Rehman (1995) for S&P500 sock index reurns. Board, e al. (2001) applied he Sochasic Volailiy (SV) model o he daily sock price daa of London Sock Exchange and he FTSE 100 conracs raded on LIFE. The auhors repor evidence conrary o he hypohesis ha fuures rading volume desabilises he spo marke, or ha an increase in rading volume in one marke relaive o he oher marke desabilises he spo marke. Overall, heir resuls indicae ha conemporaneous fuures rading, afer adjusing for he effecs of informaion arrival and ime rends, does no desabilise he spo marke. Some sudies even find a negaive relaionship beween S&P500 fuures volume and he spo price volailiy [see e.g., Sanoni (1987); Brown-Hruska and Kuserk (1995)]. Bessimender and Seguin (1992) adoped an esimaion procedure proposed by Schwer (1990) by ieraing beween a pair of regression equaions which describe he evoluion of he mean and volailiy of he process in erms of he exogenous and lagged endogenous variables. The auhors include hree rading aciviy variables (spo rading volume, fuures rading volume and open ineres in he augmened condiional reurn sandard deviaion (volailiy) equaion. The auhors observe ha he expeced (i.e. informaionless) S&P500 fuures rading aciviy is negaively relaed o equiy volailiy, when he spo-rading aciviy variables were included in he model. These findings led he auhors o conclude ha fuures rading improve liquidiy provision and deph in he equiy markes, and rejec he heories supporing he hypohesis of he desabilising effec of he fuures rading. Safi Ullah Khan <safiullah75@yahoo.com> is Assisan Professor, Insiue of Managemen Sciences, Koha Universiy of Science and Technology, Koha. Syed Tahir Hijazi <info@ucp.edu.pk> is Pro-Recor and Dean, Universiy of Cenral Punjab, Lahore.

2 554 Khan and Hijazi In conras o hese sudies, Yang, Balyea, and Leaham (2005) find ha unexpeced fuures rading volume is posiively relaed o price volailiy in he underlying marke for mos of commodiy fuures markes seleced. Using a GARCH model, Kyriacou and Sarno (1999) finds ha conemporaneous and lagged fuures volume for he FTSE 100 has increased spo marke volailiy. Ellueca and Lafuene (2003) examine he conemporaneous relaions beween rading volume and reurn in he Spanish sock index fuures marke, using a non-parameric approach for hourly reurn and fuures rading aciviy variables. The oal fuures volume were decomposed in o expeced (informaionless rading aciviy) and unexpeced (shocks in rading aciviy) componens. The sudy documens a posiive relaion beween price volailiy and unexpeced componen of rading volume. The auhors aribue his relaionship o he arrival of new informaion (unexpeced rading aciviy). This paper ess wheher rading in SSFs conracs has an impac on price volailiy of he underlying socks following he inroducion of he SSFs rading in he Pakisan s sock marke. This sudy presens fresh evidence on he fuures rading-volailiy relaionship in Pakisan s equiy marke using he mos recen daa of he single sock fuures conracs inroduced on he Karachi Sock Exchange. Specifically, he sudy examines he impac of fuures rading on he level of price volailiy of he underlying socks. Specifically, single sock fuures rading aciviy variables namely SSFs volume and open ineres were included in he analysis o examine wheher hese fuures rading aciviy variables have any role on he reurn volailiy of he underlying socks. The sudy documens a significan decrease in reurn volailiy for he SSFs-underlying socks following he inroducion of single sock fuures conracs on he Karachi Sock Exchange. The mulivariae analysis in which he spo rading volume, he fuures rading volume and open ineres were pariioned ino news and informaionless componens, he esimaed coefficien of expeced fuures volume componen is saisically significan and negaively relaed o volailiy, suggesing ha equiy volailiy is miigaed when he expeced level of fuures aciviy is high. The findings of he decreased spo price volailiy of he SSFsunderlyned socks associaed wih large expeced fuures aciviy is imporan o he debae of regarding he role of equiy derivaives rading in sock marke volailiy. These empirical resuls for he Pakisan s equiy marke suppor heories implying ha equiy derivaes rading improves liquidiy provision and deph in he equiy markes, and appear o be in conras o he heories implying ha equiy derivaes markes provide a medium for desabilising speculaion. Finally, he SSFs-lised socks are grouped wih a sample non-ssfs socks o conduc cross-secional analysis for comparing reurn volailiy behaviour in he posfuures period. Afer accouning for he effecs of a number of deerminans of volailiy, sufficien evidence is found o suppor ha, his mulivariae es, like he previous analysis, provides no evidence ha he volailiy of he SSFs-underlying socks is posiively relaed o he inroducion of he single sock fuures rading in he Pakisan s sock marke. Raher, he negaive binary coefficien indicaes ha, overall, here is a decrease in reurn volailiy for he SSFs-underlying socks in he pos-fuures period. The res of he paper is organised as follows. Second secion describes he daa, followed by he descripion of he conrol group. The fourh secion provides an in-deph analysis of he mehodology used in he paper. The las secion will provide an analysis of he daa and conclude he paper.

3 Single Sock Fuures Trading and Sock Price Volailiy DATA DESCRIPTION Trading in SSFs on he KSE commenced in July The sample period of his sudy begins June 1, 1999 and ends June, Presenly, 44 socks have SSFs conracs wrien on hem and raded on he Karachi Sock Exchange. The final daa sample consiss of 28 socks, which possesses a complee se of wo years daa of daily price observaions and rading volume on eiher side of he fuures lising daes. Daily closing share prices are obained from he online daabase of Karachi Sock Exchange for each sock for a period of wo years on eiher side of he SSFs lising dae, yielding more han 500 daily observaions per sock for each of he sub-periods. 3. CONTROL PORTFOLIO There may be oher facors, besides he SSFs lising, ha have also affeced he price performance characerisics of he socks. Such facors may include, for insance, ha firm-specific and/or indusry-specific facors or changes in he macroeconomic facors ha may have occurred a he ime of SSFs iniiaion or during he sample period ha have changed he dynamics of he marke. Our ess, herefore, may misakenly aribue such a change, if i occurred, o he inroducion of SSFc conracs. I is herefore, necessary o sudy a sample of non-ssfs socks o separae he effecs of SSFS-iniiaion from oher effecs of oher facors. Following he mehodology of Mckenzie, Brailsford and Faff (2001), such a conrol mechanism is underaken using conrol porfolio of similar socks ha did no have SSF inroduced. In case he SSFsinroduced socks behave differenly o he conrol porfolio in he pos SSFs period, his mechanism will srenghen he conclusions drawn in respec of he impac of inroducion of SSFs conracs. The conrol group sample consised of 28 socks. 4. EMPIRICAL ANALYSIS This secion ess he hypohesis ha rading aciviy in he single sock fuures conracs has an impac on he spo marke price volailiy of he underlying socks following he SSFs rading iniiaion in he Pakisan s sock marke. To his end, we use a measure of daily sock reurn volailiy by adoping a procedure inroduced by Schwer (1989), and furher followed by oher sudies [e.g., Bessimender and Seguin (1992, 1993); Wang (2002)]. The mehod enails ieraing beween he following wo ses of equaions. The condiional mean and condiional volailiy equaions are given by: R n j 1 j R j 4 i 1 d i n j 1 ˆ i j U (1) 4 i 1 i i n j 1 i j n ˆ d ˆ U (2) j 1 j j Where R is he daily sock reurn, d i corresponds o he four dummies for days of he week o accoun for he exensively documened phenomenon of differing mean daily 1 Selecion of daa from wo years prior o he commencemen of SSFs rading consiues he pre-ssfs period for hose socks for which SSFs were inroduced in July There en such socks. Moreover, oher socks ha had SSFs inroduced on differen daes for which pre-ssfs and pos-ssfs periods were seleced a differen ime periods during he sample inerval, sreching up o June 2008.

4 556 Khan and Hijazi reurns [French (1980); Gibson and Hess (1984); Keim and Sambausgh (1984)]. 2 U is he residuals (unexpeced reurns) form Equaion (1), is he esimaed condiional volailiy of reurns a ime, and given by; U (3) 2 R i (lagged reurns) in Equaion (2) as regressors allows for shor erm shifs in expeced reurns. Equaion (2) esimaes condiional sandard deviaion (volailiy) by regressing i on daily dummies (for days of he week), lagged volailiy esimaes and lagged raw residuals from Equaion (1). Lagged sandard deviaion esimaes in he Equaion (2) accouns for he persisence of volailiy shocks [French, Schwer, and Sambaugh (1987); Bessimender and Seguin (1992); Wang (2002)]. To obain volailiy esimaes, Equaion (1) is firs esimaed wihou he lagged sandard deviaion esimaes o obain residuals from he regression. The residuals obained are he unexpeced reurns. These residuals are ransformed by Equaion (3) o obain esimaes of condiional volailiy, and hen we esimae Equaion (2). The process is hen ieraed wih volailiy esimaes (lagged) as regressors in Equaion (1). To examine relaion beween volailiy and rading aciviy, we include spo rading volume, fuures rading volume and open ineres as aciviy variables. Open ineres provides an addiional measure of rading aciviy. Ieraion is, herefore, beween Equaion (1) and an augmened Equaion (4): 3 4 n n m idi iˆ j ju j i1 j 1 j 1 j 1 ˆ A (4) Where A k is he m rading aciviy variables, i.e., spo rading volume, SSFs volume and open ineres. Many sudies [e.g. Chen, Firh and Rui (2001) and Gallen, Rossi, and Tauchman (1992)] documen evidence of ime rends in rading volumes series. To miigae any effecs, herefore, of secular growh in volume, we firs generae a derended aciviy series by deducing 100-day moving average from he original series. 4 Each derended aciviy series is hen decomposed ino expeced (fied values from ARIMA model) and unexpeced (Acual minus expeced values) componens using an appropriae ARIMA (p, I, q) specificaion. The number of lags for ARIMA model were seleced for each aciviy series on he basis of Akaike informaion crierion and Schwarz informaion crierion. The decomposiion of each aciviy series ino expeced and unexpeced componens helps us o evaluae he effec of each componen separaely on he price volailiy. The unexpeced componen of he deerended series represens daily aciviy shock, whereas, he expeced componen represens aciviy which can be forecased, hough highly variable across days. Slower adjusmen changes are capured by he 100-day moving average series. Pariioning he spo rading volume, fuures rading volume and open 2 The day-of-he week effec refers o reurns no being homogenously disribued over he rading days of he week. The main findings have been lowes and on average negaive reurns on Mondays and large reurns on Fridays as compared o oher days of he week [French (1980)]. 3 Besseminder and Seguin (1992) also included hese hree aciviy variables. 4 The same procedure was also followed by Bessimender and Seguin ( 1992). k k

5 Single Sock Fuures Trading and Sock Price Volailiy 557 ineres ino expeced, unexpeced and moving average series resul in nine variables, which were included in he augmened Equaion (4) Spo Trading Volume and Sock Reurn Volailiy Iniially, we esimae Equaions (1) and (4) wih he spo rading volumes as he only aciviy variable. These empirical resuls are repored in he firs column of he Table 1. As he able repors ha all of he esimaed coefficiens for daily dummies are significan, indicaing ha he model has adequaely capured he seasonal effecs. Esimaed coefficien on he unexpeced componen of he rading volume is posiive and highly significan. Moreover, his coefficien is also larger han he esimaed coefficiens on he expeced rading volume and he moving average volume. This implies ha surprises (unexpeced componen) in he spo rading volume convey more informaion, and hus are more imporan in explaining equiy volailiy han eiher he variaions in he anicipaed (expeced rading volume and moving average) level of rading aciviy. These resuls are in line wih he findings of many empirical sudies conduced in oher markes. For insance, Pai (2008) finds posiive relaion of price volailiy o expeced an unexpeced componens of rading volume for he Indian sock marke. The auhor also documens ha an unexpeced componen of rading volume has greaer impac on rading volume han he expeced volume. Table 1 Regression of Daily Reurn Sandard Deviaion Esimaes on Spo Trading Volume and Fuures Trading Dummy FUTDUMY denoes a dummy variable which is equal o one for pos- SSFs period and zero oherwise, for each sock. The able repors resuls for wo regressions. Column (1) conains resuls for he regression model wihou dummy variable and he column (2) repors resuls for he dummy variable regression model. (1) (2) Variable Coefficien -Saisic Coefficien -Saisic Inercep * * FUTDUMY ** Daily Dummies Tuesday * * Wednesday * * Thursday * * Friday * * Trading Volumes Expeced * * Expeced*FUTDUMY Unexpeced * * Unexpeced*FUTDUMY * Moving Average Moving Average*FUTDUMY Lagged Volailiy Esimaes * * Lagged Unexpeced Reurns * * Durbin Wason Adjused R Diagnosic Checks Esimae P-value LB-Q(36) LB-Q 2 (36) Noe: * (**) represens saisical significance a 0.01 (0.05) level, LB-Q(k) and LB-Q 2 (k) are he pormaneau Ljung-Box Q es saisics for esing he join significance of auocorrelaion of sandardised residuals and squared residuals for lags 1 o k respecively.

6 558 Khan and Hijazi 4.2. SSFs Trading and Sock Price Volailiy As an iniial economeric examinaion of he single sock fuures rading on he equiy volailiy of he underlying socks in he spo marke, we include a dummy variable in Equaion (4) ha akes on a value equal o one for pos-ssfs period (wo years ime period, wih almos 500 observaions for each sock), and equal o zero for he pre-ssfs period, conaining almos same number of observaions compared o pos-ssfs period. We also allow he regression inercep and he slope coefficiens on volume variables o shif subsequen o he inroducion of he SSFs rading. Empirical resuls of Equaion (4) are repored in he second column of Table 1. Noable resul of his analysis is ha he observed change in he slope coefficien associaed wih he unanicipaed spo rading volume is negaive and highly significan (a 1 percen significance level). This implies ha he spo volume shocks are associaed wih smaller price movemens subsequen o he inroducion of he SSFs rading. Similarly, he esimaed coefficien for he slope dummy on he moving average volume is negaive hough i is no saisically significan. Again, his also implies a reducion in he magniude of he relaion subsequen o he inroducion of he SSFs. In conras, he esimaed coefficien for he shif in he regression inercep subsequen o he inroducion of SSFs rading is negaive and saisically significan. These findings are consisen wih he view ha sock reurn volailiy (equiy volailiy) has been reduced, and marke deph (as measured by he volume of shares required o move prices) has been increased by he inroducion of SSFs rading. There may have been oher changes in he overall financial and capial markes in Pakisan, or even some of he secors/sock specific facors, during he period examined in he sudy, and hese reducions in equiy volailiy need no be solely aribuable o he inroducion of SSFs rading in Pakisan s sock marke SSFs Trading Aciviy Variables and Sock Price Volailiy Evidence on he relaion beween Single Sock Fuures rading and sock price volailiy repored in he prior secion is no enirely conclusive, a leas in par, because he inroducion of single sock fuures rading consiues bu a single even. To furher augmen he specificiy of he evidence, his sudy furher examines he relaion beween sock price volailiy and levels of fuures rading aciviy by including SSFs rading volume and open ineres. 5 Following he mehodology adoped by Besseminder and Seguin (1992), for each rading dae, fuures volume and open ineres are summed across conracs o obain aggregae fuures aciviy. We again decompose each rading aciviy (spo rading volume, SSFs rading volume and open ineres) in o hree addiive componens namely moving average, expeced and unexpeced componens using he same mehodology as discussed in he previous secion. Empirical resuls of esimaing (4) wih hese aciviy series are repored in he Table 2. Inclusion of SSFs-rading variables does no change he sign of coefficien esimaes on he expeced and unexpeced componens of he spo-rading variables. The coefficien esimae for unexpeced SSFs-rading volume, like ha for unexpeced spo- 5 Open ineres is he sum oal of all ousanding long and shor posiions of fuures conracs ha have no been closed ou, a he end of he rading day.

7 Single Sock Fuures Trading and Sock Price Volailiy 559 Table 2 Regression of Daily Reurn Sandard Deviaion Esimaes on Spo Trading Volume and Fuures Trading Volume Boh spo and fuures rading volumes for each sock are de-rended by subracing 100 day moving average volume from each series before pariioning ino expeced and unexpeced componens. Tes saisics are in parenhesis. Variable Coefficien -Saisic Prob. Inercep (5.84) * Daily Dummies Tuesday (4.16) * Wednesday (4.40) * Thursday (3.43) * Friday (2.08) ** Trading Aciviy Spo Volumes Expeced (5.95) * Unexpeced (12.07) * Moving Average (0.98) SSFs Fuures Volume Expeced (3.27) * Unexpeced (3.12) * Moving Average (0.02) SSFs Open Ineres Expeced ( 0.54) Unexpeced Moving Average Lagged Volailiy Esimaes (5.42) * Lagged Unexpeced Reurn (3.48) * Durbin-Wason 2.03 Adj. R rading volume, is posiive and significan, and is larger in magniude ha he sporading volume coefficien. As Besseminder and Seguin (1992) poins ou ha, his posiive coefficien implies ha informaion shocks move prices and generae rading in boh markes. Unlike he resuls for he expeced (i.e., informaionless) componen of he spo volume, he coefficien esimae for he expeced SSFs-volume is negaive and significan, indicaing decreased sock price volailiy when expeced SSFs-volume is high. On he oher hand, coefficien esimaes on he expeced and unexpeced componens of he open ineres are negaive, bu neiher is saisically differen from zero. These empirical resuls are in line wih he sudy of Besseminder and Seguin (1992) for S&P500 Index. Conrary o he findings of heir sudy in case of moving average, esimaed coefficien on all hree moving average series (spo-rading volume, SSFs-

8 560 Khan and Hijazi volume and open ineres) are saisically insignifican, indicaing ha long-erm variaions may no be relevan for explaining volailiy in Pakisan s equiy marke. To summarise, empirical evidence indicaes ha equiy volailiy is posiively relaed o spo-rading aciviy, wheher expeced (informaionless rading) or unexpeced, and o he conemporaneous fuures rading shocks. Whereas, he parial effecs on equiy volailiy of expeced and moving average (hough insignifican in case of moving average) are negaive, suggesing ha equiy volailiy is miigaed when he expeced level of fuures aciviy is high. The findings of he decreased spo price volailiy associaed wih large expeced fuures aciviy is imporan o he debae of regarding he role of equiy derivaives rading in sock marke volailiy. These empirical resuls for he Pakisan s equiy marke suppor heories implying ha equiy derivaes rading improves liquidiy provision and deph in he equiy markes, and appear o be in conras o he heories implying ha equiy derivaes markes provide a medium for desabilising speculaion Cross-secional Analysis Finally, following he mehodology of Galloway and Miller (1997), SSFs-lised socks are grouped wih non-ssfs socks and he behaviour of he reurn volailiy is examined surrounding he inroducion of single sock fuures rading. The regression model akes he following form: 4 n 1 idi iˆ j 2LNVOL 3LN( Firm) 4 i1 j1 ˆ FUTDUMY (5) where ˆ is he pos-fuures period daily volailiy esimae; LN(Firm) is he naural logarihm of equiy value of he firm; LNVOL is he naural logarihm of spo rading volume, coefficiens for days of he week, lagged volailiy esimaes and a binary variable (FUTDUMY) ha is equal o one for he SSFs-lised socks and 0 for he non- SSFs socks. We are mainly ineresed in esimaing 4 regression coefficien in Equaion (5) which would indicae wheher he sock price volailiy of he SSFs-underlying socks behaves in a differen way han ha of non-ssfs socks in he pos-ssfs rading period, while accouning for oher facors known o influence sock price volailiy. When his coefficien is negaive (posiive), his implies ha he average sock price volailiy of he SSFs-lised sock is lower (higher) han ha of he maching non-ssfs lised socks in he pos-fuures period. In addiion o he binary variable, hree conrol variables were also incorporaed in he Equaion (5). Firs, as argued by Galloway and Miller (1997), if he inroducion of fuures rading improves he liquidiy of he underlying socks wih a resuling decline in sock price volailiy, his effec is more eviden in case of smaller firms wih less liquid socks. In his case, he esimaed coefficien, 3, is expeced o be negaive (i.e., 3 < 0). Consequenly, he firm s marke value of equiy is included in he model o accoun for his size effec. Second, a voluminous body of lieraure exiss ha documens a posiive conemporaneous relaionship beween rading volume and sock reurn volailiy. We herefore, expec he coefficiens on expeced (informaionless) and

9 Single Sock Fuures Trading and Sock Price Volailiy 561 unexpeced rading volumes o be posiive (i.e., 2 > 0). Thus he expeced and unexpeced componens of spo rading volume of he underlying socks and ha of conrol group socks is employed o conrol for his posiive reurn volailiy-volume effec. Table 3 presens resuls for he regression Equaion (5). The esimaed coefficiens for he conrol variables have he expeced signs and are saisically significan. However, our primary ineres lies in he coefficien esimae, 4, of he binary variable. The coefficien esimae ( 4 ) is negaive and highly saisically significan. This mulivariae es, like he previous analysis, provides no evidence ha he volailiy of he SSFs-underlying socks is posiively relaed o he inroducion of he single sock fuures rading in he Pakisan s sock marke. Raher, he negaive binary coefficien indicaes ha, overall, here is a decrease in reurn volailiy for he SSFs-underlying socks in he pos- fuures period. Thus he evidence ends o suppor he noion ha he single sock fuures rading had a negaive impac on he level of price volailiy for he underlying socks. Table 3 Cross-secional Analysis: OLS Regression Resuls Dependen variable is he pos-fuures sock price volailiy. Explanaory variables are: he naural logarihm of he firm s marke value equiy value, he naural logarihm of he spo rading volume for boh SSFs-lised and sample of conrol group socks, coefficiens for daily dummies, lagged volailiy esimaes, and a binary variable equal o one if he firm is SSFs-lised, and zero if he firm belongs o a conrol group. Variable Coefficien -Sa p-value Inercep * Daily Dummies D * D * D * D * FUTDUMY * LOGVOL * LNFV * Lagged Volailiy σ ( 1) * σ ( 2) * σ ( 3) * σ ( 4) * σ ( 5) * σ ( 6) * σ ( 7) * σ ( 8) * σ ( 9) * σ ( 10) * Lagged Unexpeced ( 1) * Adj. R 0.14 D-Wason 2.006

10 562 Khan and Hijazi 5. CONCLUSION This sudy ess he hypohesis ha increases in fuures marke rading aciviy has an impac on he equiy volailiy of he underlying socks by using a measure of daily sock reurn volailiy by following a procedure suggesed by Schwer (1989). Spo rading volume, SSFs rading volume and open ineres analyse he relaion beween sock price volailiy and rading aciviy variables. The daa consiss of daily closing prices of he underlying socks, spo rading volume, SSFs volume and open ineres for he period July, 2001 o February, The sudy examines wheher he effec of spo volume, fuures volume and open ineres on he spo price volailiy of he underlined is homogeneous by pariioning he hree rading aciviy variables ino expeced and unexpeced componens by an appropriae ARMA specificaion and allowing each componen (expeced, unexpeced and moving average series) o have a separable effec on observed spo price volailiy of he underling socks. We adop Schwer s (1989) procedure for volailiy esimaion and including he rading aciviy variables of he wo markes in he volailiy regression equaion. The resuls show ha sock price volailiy of he underlying socks is posiively relaed o boh he expeced and unexpeced componens of he spo rading volume. However, he unexpeced componen of he volume has a greaer impac on he equiy volailiy han he expeced (informaionless) volume. This analysis confirms he findings of many oher sudies showing a posiive relaionship beween spo rading volume and spo price volailiy. Equiy volailiy is also posiively relaed o he conemporaneous fuures shocks (unexpeced componen of fuures volume). Expeced fuures volume is saisically significan and negaively relaed o volailiy, suggesing ha equiy volailiy is miigaed when he expeced level of fuures aciviy is high. The findings of he decreased spo price volailiy associaed wih large expeced fuures aciviy is imporan o he debae of regarding he role of equiy derivaives rading in sock marke volailiy. These empirical resuls for he Pakisan s equiy marke suppor heories implying ha equiy derivaes rading improves liquidiy provision and deph in he equiy markes, and appear o be in conras o he heories implying ha equiy derivaes markes provide a medium for desabilising speculaion. REFERENCES Bessimender, H. and P. J. Seguin (1992) Fuures Trading Aciviy and Price Volailiy. Journal of Finance 47, Bessimender, H. and P. J. Seguin (1993) Price Volailiy, Trading Volume, and Marke Deph: Evidence from Fuures Markes. Journal of Financial and Quaniaive Analysis 28:1, Board, J., S. Gleb, and C. Sucliefe (2001) The Effec of Fuures Marke Volume on Spo Marke Volailiy. Journal of Business Finance and Accouning 2:7, Brown, H. S. and G. Kuserk (1995) Volailiy, Volume and Noion of Balance in he S&P 500 Cash and Fuures Markes. The Journal of Fuures Markes 15:6, Chen, G. M., M. Firh and O. M. Rui (2001) The Dynamic Relaions beween Sock Reurns, Trading Volume and Volailiy. The Financial Review 38, Dara, A. F. and S. Rehman (1995). Has Fuures Trading Aciviy Caused Sock Price Volailiy. The Journal of Fuures Markes 15,

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