expressed here and the approaches suggested are of the author and not necessarily of NSEIL.

Transcription

1 I. Inroducion Do Fuures and Opions rading increase sock marke volailiy Dr. Premalaa Shenbagaraman * In he las decade, many emerging and ransiion economies have sared inroducing derivaive conracs. As was he case when commodiy fuures were firs inroduced on he Chicago Board of Trade in 86, policymakers and regulaors in hese markes are concerned abou he impac of fuures on he underlying cash marke. One of he reasons for his concern is he belief ha fuures rading aracs speculaors who hen desabilize spo prices. This concern is eviden in he following excerp from an aricle by John Suar Mill (87): The safey and cheapness of communicaions, which enable a deficiency in one place o be, supplied from he surplus of anoher render he flucuaions of prices much less exreme han formerly. This effec is much promoed by he exisence of speculaive merchan. Speculaors, herefore, have a highly useful office in he economy of sociey. Since fuures encourage speculaion, he debae on he impac of speculaors inensified when fuures conracs were firs inroduced for rading; beginning wih commodiy fuures and moving on o financial fuures and recenly fuures on weaher and elecriciy. However, his radiional favorable view owards he economic benefis of speculaive aciviy has no always been accepable o regulaors. For example, fuures rading was blamed by some for he sock marke crash of 987 in he USA, hereby warraning more regulaion. However before furher regulaion in inroduced, i is essenial o deermine wheher in fac here is a causal link beween he inroducion of fuures and spo marke volailiy. I herefore becomes imperaive ha we seek answers o quesions like: Wha is he impac of derivaives upon marke efficiency and liquidiy of he underlying cash marke? To wha exen do derivaives desabilize he financial sysem, and how should hese risks be addressed? Can he resuls from sudies of developed markes be exended o emerging markes? This paper seeks o conribue o he exising lieraure in many ways. This sudy seeks o examine he impac of financial derivaives inroducion on cash marke volailiy in an emerging marke, India. Furher, his sudy improves upon he mehodology used in prior sudies by using a framework ha allows for generalized auo-regressive condiional heeroskedasiciy (GARCH) i.e., i explicily models he volailiy process over ime, raher han using esimaed sandard deviaions o measure volailiy. This esimaion echnique enables us o explore he link beween informaion/news arrival in he marke and is effec on cash marke volailiy. The sudy also looks a he linkages in ongoing rading aciviy in he fuures marke wih he underlying spo marke volailiy by decomposing rading volume and open ineres ino an expeced componen and an unexpeced (surprise) componen. Finally his is he firs sudy o our knowledge ha looks a he effecs of boh sock index fuures inroducion as well as sock index opions inroducion on he underlying cash marke volailiy. * Ass. Professor, Deparmen of Finance, Clemson Universiy, USA. The views expressed here and he approaches suggesed are of he auhor and no necessarily of NSEIL.

2 The resuls of his sudy are crucial o invesors, sock exchange officials and regulaors. Derivaives play a very imporan role in he price discovery process and in compleing he marke. Their role in risk managemen for insiuional invesors and muual fund managers need hardly be overemphasized. This role as a ool for risk managemen clearly assumes ha derivaives rading do no increase marke volailiy and risk. The resuls of his sudy will hrow some ligh on he effecs of derivaive inroducion on he efficiency and volailiy of he underlying cash markes. The sudy is organized as follows. Secion II discusses he heoreical debae and summarizes he empirical lieraure on derivaive lising effecs, Secion III deails he model and he economeric mehodology used in his sudy, Secion IV oulines he daa used and discusses he main resuls of he model and finally Secion V concludes he sudy and presens direcions for fuure research. II. Theoreical foundaions and survey of he empirical lieraure. The inroducion of equiy index fuures markes enables raders o ransac large volumes a much lower ransacion coss relaive o he cash marke. The consequence of his increase in order flow o fuures markes is unresolved on boh a heoreical and an empirical fron. Sein (987) develops a model in which prices are deermined by he ineracion beween hedgers and informed speculaors. In his model, opening a fuures marke has wo effecs; (). The fuures marke improves risk sharing and herefore reduces price volailiy, and (). If he speculaors observe a noisy bu informaive signal, he hedgers reac o he noise in he speculaive rades, producing an increase in volailiy. In conras, models developed by Danhine (978) argue ha he fuures markes improve marke deph and reduce volailiy because he cos o informed raders of responding o mispricing is reduced. Froo and Perold(99) exend Kyle s(98) model o show ha marke deph is increased by more rapid disseminaion of marke-wide informaion and he presence of marke makers in he fuures marke in addiion o he cash marke. Ross (989) assumes ha here exiss an economy ha is devoid of arbirage and proceeds o provide a condiion under which he noarbirage siuaion will be susained. I implies ha he variance of he price change will be equal o he rae of informaion flow. The implicaion of his is ha he volailiy of he asse price will increase as he rae of informaion flow increases. Thus, if fuures increase he flow of informaion, hen in he absence of arbirage opporuniies, he volailiy of he spo price mus change. Overall, he heoreical work on fuures lising effecs offers no consensus on he size and he direcion of he change in volailiy. We herefore need o urn o he empirical lieraure on evidence relaing o he volailiy effecs of lising index fuures and opions. The firs sock index fuures conrac inroduced in he world was he Value line conrac, inroduced by he Kansas Ciy Board of Trade in 98 in he USA. Since hen we have seem numerous markes all over he world launch new derivaive conracs every year. Following he inroducion of derivaive conracs in developed markes like he US and UK, researchers have sough o analyze he impac of derivaives inroducion on he volailiy and efficiency of he underlying cash marke. The empirical evidence is however quie mixed. Mos sudies summarize ha he inroducion of derivaives does no desabilize he underlying marke; eiher here is no effec or perhaps only a very small decline in volailiy. The impac however, seems o vary depending on he ime period sudied and he counry sudied. For example, in a sudy of counries, Gulen and Mayhew () find ha fuures rading is associaed wih increased For a deailed summary of his lieraure, see surveys by Hodges (99), Damodaran and Subrahmanyam (99), Sucliffe (997) and Mayhew (999).

3 volailiy in he Unied Saes and Japan. In some counries, here is no robus, significan effec, and in many ohers, volailiy is lower afer fuures have been inroduced. Nahan Associaes (974) was he firs o sudy he impac of lising opions on he Chicago Board of Exchange. He repored ha he inroducion of opions seemed o have helped sabilize rading in he underlying socks. This resul has been suppored by Skinner (989) and also by oher auhors for he UK, Canada, Swizerland and Sweden. More recen work by Lamoureux and Pannikah (994), Freund, McCann and Webb (994) and Bollen (998) have found ha he direcion of he volailiy effec is no consisen over ime. Afer 987, he residual variance of boh opioned socks and socks in a mached conrol group increased a he ime of he opion lising. This migh be inerpreed in wo ways; viz. perhaps he lising has no rue impac on volailiy and here is some common unknown facor ha is driving he magniude of he idiosyncraic risk for differen socks. Or perhaps, here are spill over effecs associaed wih lising opions for some socks, such ha he dynamics of oher socks also changes (Deemple and Jorion, 99, and Cao 999). In looking a he effec on liquidiy, Nahan Associaes (974) found ha he rading volume did no change wih opion inroducion. However, laer sudies like Kumar, Sarin and Shasri (99) have found ha he volume in he underlying sock does increase afer he inroducion of sock opions. Sudies have also found ha afer he inroducion of opions, prices end o reflec new informaion more quickly, bid-ask spreads narrow, and he adverse selecion componen of he spread becomes smaller. Relaively few auhors have sudied he impac of sock index opions lising on volailiy in he cash marke. Evidence repored by Charah, Kamah, Chakornpipa and Ramchander (99) indicaes ha S&P sock index opions rading had a sabilizing effec on he underlying sock index. Sudies of volailiy effecs of individual equiy opions have also repored mixed resuls; some find ha volailiy is unchanged, while some repor a small decrease in volailiy. Only one paper Wei, Poon and Zee (997) repor an increase in volailiy for opions on OTC socks in he USA. However no consensus resul emerges, which is probably a resul of differen daa and ime-periods sudied, as also he inheren endogenous naure of he opion lising decision. III. Model and Mehodology The impac of sock index fuures and opion conrac inroducion in he Indian marke is examined using a univariae GARCH (,) model. The ime series of daily reurns on he S&P CNX Nify Index is modeled as a univariae GARCH process. Following Pagan and Schwer (99) and Engle and Ng (99), we need o remove from he ime series any predicabiliy associaed wih lagged world reurns and/or day of he week effecs. I is imporan o remove marke-wide influences on Nify reurns, if we are o isolae he impac of fuures inroducion. In order o do his we need a proxy ha is no associaed wih any fuures conrac, and ye capures marke-wide influences in India. For example, informaion news releases relaing o economic condiions like inflaion raes, growh forecass, exchange raes, ec are likely o affec he whole marke. I is necessary o remove he effecs of all hese facors on price volailiy. Since he Nify Junior has no fuures conracs raded on i, i serves as a perfec conrol variable for us o isolae marke wide facors and hereby concenrae on he residual volailiy in he Nify as a direc resul of he inroducion of he index derivaive conracs. We herefore inroduce he reurn on In a recen working paper, Mayhew and Mihow () explicily model he exchanges opion lising choice using a logi model o accoun for his endogeniey. Alernaive GARCH models were esimaed, he GJR-GARCH, EGARCH AND TGARCH, bu we find he GARCH (,) model o provide he bes fi for he daa in his sudy.

4 he Nify Junior index as an addiional independen variable. The following condiional mean equaion is esimaed: nify, = + Rsp, + Rnifyunior, + = R DAY + u Equaion R nify where, is he daily reurn on he S&P CNX Nify Index calculaed as he firs difference of he log of he index, R sp, is he lagged S&P index reurn, and DAY are day-of-he-week dummy variables for Tuesday o Friday. The lagged S&P index reurn is used as an independen variable o remove he effecs of worldwide price movemens on he volailiy of he Nify Index reurn. For example, if he Indian marke is influenced by US markes, his will be refleced hrough he lagged S&P reurn. The advanage of a GARCH model is ha i capures he endency in financial daa for volailiy clusering. I herefore enables us o make he connecion beween informaion and volailiy explici, since any change in he rae of informaion arrival o he marke will change he volailiy in he marke. Thus, unless informaion remains consan, which is hardly he case, volailiy mus be ime varying, even on a daily basis. In sudying he links beween informaion, cash marke volailiy and derivaives rading, wo issues are ineresing. Firs, how he iniial inroducion of derivaive conracs impac cash marke volailiy. Second, wheher he exisence of fuures rading affecs daily volailiy in he cash marke. To address he firs issue, we inroduce a dummy variable ino he condiional variance equaion. If he coefficien on he Dummy is saisically significan hen he inroducion of fuures has an impac on he spo marke volailiy. To address he second issue, we divide he sample ino he pre-fuures and pos- fuures subsample and a GARCH model is esimaed separaely for each sub-sample. This allows us o compare he naure of volailiy before and afer he onse of fuures rading. Secion IV. Daa and Resuls Daily closing prices for he period h Oc 99 o s Dec for he SNX Nify and he Nify Junior were obained from he CD-ROMs provided by NSE and he NSE websie. Daa on Nify fuures conrac volume and open ineres were downloaded from he NSE websie. Daa on he S&P index were obained from Reuers Inc. All esimaions in his sudy are done using SAS. The SNX Nify is an index of socks raded on he Naional Sock Exchange and represens approximaely % of he oal marke capializaion of he marke. Nify Junior is an index of he nex mos liquid socks. The firs index fuure in India was inroduced on he SNX Nify on June,. The firs index opions conrac was inroduced on 4h June,. Table provides summary saisics for he Nify and Nify Junior indices. All reurns are calculaed as he firs difference of he log of he index daily close price and Char graphs he reurns on he Nify index over ime. As seen in Table, he overall sample has 8 ime series observaions. The mean reurn on he Nify is.% per day wih a sandard deviaion of.67% per day. The mean daily reurn on he Nify Junior is.7% wih a sandard deviaion of.9%. If we divide he sample period ino pre-fuures vs. pos-fuures using he June, cuoff dae, he mean daily reurn on he Nify is a posiive.9% before and a negaive.44% afer he fuures was inroduced. A similar paern in Nify Junior reurns is also apparen. The average daily sandard deviaion for he Nify reurn pre-fuures is.79% and.4% pos-fuures. However, he daily sandard deviaion for he Nify Junior, for which no index fuures were raded, pre-fuures is % and pos fuures is.7%. A very similar paern emerges when one examines he pre-opions and pos-opion sub-sample means and sandard deviaions. 4

5 As menioned earlier, in order o esimae he impac of he inroducion of he fuures and opions conracs, we inroduce a Dummy variable in he condiional volailiy equaion. A significan posiive co-efficien would indicae an increase in volailiy; a significan negaive coefficien would indicae a decrease in volailiy. The resuls of he esimaion for he impac of fuures inroducion are presened in Table. The coefficien on he fuures dummyγ, is no significanly differen from zero, indicaing no impac on volailiy. There appear o be significan day-of-he-week effecs as evidenced by he coefficiens on he dummies for Tuesday and Friday. γ can be viewed as a news coefficien, wih a higher value implying ha recen news has a greaer impac on price changes. I relaes o he impac of yeserday s news on oday s price changes. In conras, γ reflecs he impac of old news', i.e. i is picking up he impac of prior news on yeserdays variance and as such indicaed he level of persisence in he informaion effec on volailiy. Table 4 presens he resuls of he model wih an Opions dummy. Index opions were inroduced on June 4 h,. The Dummy-Opions is zero before and on/afer June 4 h. The inroducion of opions has had no saisically discernable effec on spo marke volailiy. The resuls hus far sugges ha he inroducion of fuures and opions has had no effec on spo marke volailiy. However, in realiy, one migh expec a lo of uncerainy in he marke leading up o he inroducion of he derivaive conracs, which our cu-off daes are unable o capure in he model. Table presens some basic saisics on he means and sandard deviaions of he reurns for he six monhs leading up o he inroducion of he fuures conracs in June. The sandard deviaion of nify reurns up unil Dec 999 was.7%. Beween Jan and June, he sandard deviaion rose o.% and hen afer June dropped back o.4%. Ineresingly, a similar paer emerges for he Nify Junior reurns, even hough no underlying fuures conracs were being inroduced for socks in his index. This was also an exremely volailiy period in world sock markes, especially he US sock markes. The increase in volailiy in he Indian marke migh have been a consequence of increased volailiy in he US markes. This effec is picked up by he lagged reurn on he S&P index in our model. In conclusion, we find lile evidence ha he spo marke volailiy changed significanly as a resul of fuures or opions inroducion. Char plos he GARCH model prediced condiional error sandard deviaion over ime. Clearly, he model is able o capure he emporary increase in he volailiy leading up o he inroducion of he fuures conracs in he firs six monhs of. Furher, one can see ha if we ignore his 6 monh period, he volailiy has no changed much before and afer he fuures inroducion. I is ineresing o explore furher wheher he naure of he GARCH process was alered as a resul of he fuures inroducion. We herefore esimae he GARCH model separaely for he pre-fuures and he pos-fuures period separaely. Table presens he resuls of his esimaion. The firs poin o noe in comparing he resuls before and afer fuures inroducion is ha he onse of fuures rading has alered he naure of he volailiy. Before fuures, he ARCH and he GARCH effecs are significan, suggesing ha boh recen news and old news had a lingering impac on spo marke volailiy. The resuls also show he presence of day-of-he-week effecs for Tuesday and Friday. Afer he fuures inroducion, he day-of-he-weeks effecs are no longer saisically significan. Also he coefficien on he GARCH variable is no longer significan, suggesing ha old news has no impac on oday s spo price changes. However our sample period pos fuures is fairly small, only 97 observaions, so we mus rea hese resuls wih some cauion.

6 We have hus far, esed wheher here appears o be any srucural change in he underlying spo marke a he ime of fuures and opions inroducion. Now we es o see if here is any relaionship, afer he fuures are inroduced, beween he level of fuures rading aciviy and he volailiy of he spo marke reurn. We follow Bessembinder and Sequin (99) and using an ARIMA (p,q) model, decompose he ime series of he fuures rading volume and open ineres ino expeced and unexpeced componens. The expeced componen represens a hreshold level (or average) of fuures rading, and he unexpeced componen picks up any sudden increase in rading volume as a resul of unexpeced price changes. Bessembinder and Sequin find ha spo marke volailiy in he US marke is posiively relaed o he unexpeced componens of volume and open ineres, and negaively relaed o he expeced componen, suggesing an increase in volailiy due o unexpeced informaion, bu an oherwise sabilizing influence of fuures rading aciviy. Using an ARIMA (,) model for he conracs volume and an ARIMA (,) model for he Open Ineres, we decompose each series ino an expeced and an unexpeced componen. We hen inser hese componens as addiional variables in he condiional variance equaion: h = 7 γ h ε D 4CONTex CONTunex 6OIex OIunex The resuls of his esimaion are presened in Table 6. None of he coefficiens on he rading aciviy variables are saisically significan. This however, may be an arifac of he raher low sample size in he pos fuures period. As more daa becomes available, i will be ineresing o reesimae his model o evaluae he impac of coninuing rading aciviy in he fuures and/or opions marke on he underlying spo marke. Also, in decomposing he volume indicaor variables, no adusmen was made o remove any seasonal effecs like conrac expiry monhs, ec. An ineresing opic for furher research would be o see if adusing for his seasonaliy will have a significan impac on he decomposiion of he permanen and emporary componens of rading aciviy. V. Conclusion In his sudy, we have examined he effecs of he inroducion of he Nify fuures and opions conracs on he underlying spo marke volailiy using a model ha capures he heeroskedasiciy in reurns ha characerize sock marke reurns. The resuls indicae ha derivaives inroducion has had no significan impac on spo marke volailiy. This resul is robus o differen model specificaions. ** We hen esimaed he model separaely for he pre and pos fuures period and find ha he naure of he GARCH process has changed afer he inroducion of he fuures rading. Prefuures, he effec of informaion was persisen over ime, i.e. a shock o oday s volailiy, has an effec on omorrow s volailiy and he volailiy for days o come. Afer fuures conracs sared rading he persisence has disappeared. Thus any shock o volailiy oday has no effec on omorrow s volailiy or on volailiy in he fuure. This migh sugges increased marke efficiency, since all informaion is incorporaed ino prices immediaely. However, we prefer o rea our resuls here wih some cauion since we are esimaing he GARCH model wih only wo and a half years of daa. ** In he ineres of breviy, he esimaion resuls of he various GARCH specificaions are no presened. All he models showed no effec of fuures or opions inroducion on spo marke volailiy. 6

7 Nex, using a procedure inspired by Bessembinder and Sequin (99), we find ha afer he inroducion of fuures rading, we are unable o pick up any link beween he volume of fuures conracs raded and he volailiy in he spo marke. As more daa becomes available, i will be ineresing o explore his link once more. I is imporan o emphasize ha alhough we have sough o analyze he impac of he inroducion of fuures/opions on spo marke volailiy, in realiy he lising of index derivaive conracs is hardly an exogenous even. The lising is usually preceded by many decisions made by regulaors and sock exchange officials, who in urn may be reacing o world developmens. Furher, i is quie possible ha he inroducion of fuures and opions has differen impac on spo volailiy depending on he rading mechanisms, conrac designs and regulaory environmens. This migh explain he raher mixed resuls reached by researchers in differen markes. Furher research needs o explore he relaionship beween hese facors and he naure of spo marke volailiy before and afer derivaives rading began. As more daa becomes available in he Indian marke, such a sudy would be immensely beneficial o invesors, insiuional raders and regulaors alike. Furher, i should be noed ha a relaively long ime series, is required o obain reliable GARCH parameer esimaes. For he model esimaed over he enire sample period, Oc 99- Dec, his migh no be a problem. However in our esimaions for he pos fuures period, clearly his is affecs he reliabiliy of our esimaes. Unforunaely, he only soluion is paience and persisence. In summary, we find lile evidence ha he inroducion of new sock index fuures or opions conracs in emerging markes like India will desabilize sock markes. On he conrary, i appears ha he sock markes become more efficien and informaion is incorporaed ino prices a lo faser. Engle and Mezrich (99) sugges using a leas eigh years of daily daa for proper GARCH esimaion. 7

8 CHART : Reurn on he SNX Nify reurn CHART : Esimaed error sandard deviaion from he GARCH (,) model Uncondiional error sandard deviaion=.9 SHAT JAN9 JAN96 JAN97 JAN98 JAN99 JAN JAN JAN JAN d 8

9 Table : Descripive Saisics Means and sandard deviaions of firs fferences di of he log of he Nify and he Nify Junior daily price indices, Oc 99 o Dec Period NOB Nify Nify Junior Mean Sd.Deviaion Mean Sd.Deviaion Pre-Fuures Pos-Fuures Pre-Opions Pos-Opions Fuures conracs were inroduced on June, and Opions conracs on June, 4. Table : Descripive Saisics Means and sandard deviaions of Index reurns for sub -periods Period NOB Nify Nify Junior Mean Sd.Deviaion Mean Sd.Deviaion Jan-Jun Jun

10 Table : Esimaes of he GARCH(,) model wih Fuures dummy nify, = + Rnifyunior, + Rsp, + = h = γ h ε D R DAY + where D is a dummy variable ha akes a value of afer June h and before. u Inercep -.6* -.69 Nify reurn.76 * 77. Lagged S&P.8 * 7. Dummy-Tue.4 *.9 4 Dummy-Wed..69 Dummy-Thur.8.6 Dummy-Fri.7*.7 6 γ Arch. * 4. γ Arch.*.4 γ Garch.9 * γ Dummy-Fuures.. * Saisically significan a he % level. Toal R-square=.674 N=67 Uncondiional variance=.84 7

11 Table 4: Esimaes of he GARCH(,) model wih Opions dummy nify, = + Rnifyunior, + Rsp, + = h = γ h ε D R DAY + where D is a dummy variable ha akes a value of afer June 4 h u and before. Inercep -.6* -.69 Nify reurn.7 * Lagged S&P.7 * 6.94 Dummy-Tue.4 *.9 4 Dummy-Wed..7 Dummy-Thur.8.6 Dummy-Fri.7*.7 6 γ Arch. *.9 γ Arch.*.4 γ Garch.97 * 68. γ Dummy-Opions.. * Saisically significan a he % level. Toal R-square=.674 N=67 Uncondiional variance=.8486

12 Table : Esimaes of he GARCH(,) model before and afer fuures inroducion. nify, = + Rnifyunior, + Rsp, + = = γ h ε R DAY + h BEFORE AFTER Esimae -sa Esimae -sa Inercep -.48* Nify reurn.8649 * * 4.7 Lagged S&P.8 * *.49 Dummy-Tue.89 * Dummy-Wed Dummy-Thur..7.. Dummy-Fri.9* γ Arch. *.4.6 * 6.6 γ Arch.768* γ Garch.96 * 6... Toal R-square N Uncondiional variance.97.7 * Saisically significan a he % level. u

13 Table 6: Esimaes of he AUGMENTED GARCH (,) model afer fuures inroducion. nify, = + Rnifyunior, + Rsp, + = = γ h ε R DAY + h u Esimae -sa Inercep Nify reurn.99 *.4 Lagged S&P.76 *.8 Dummy-Tue..8 4 Dummy-Wed.4.9 Dummy-Thur.8.9 Dummy-Fri γ Arch.6 *. γ Arch.9*.64 γ Garch.88. γ Con-expeced..9 γ 4 Con-unexpeced γ OI-expeced.. γ OI-unexpeced.. 6 Toal R-square.64 N 94 Uncondiional variance.69 * Saisically significan a he %level. Con=change in he log of he oal number of conracs raded for all expiry for he nify fuures. OI=change in he log of he open ineres for all expiry horizons for nify fuures conracs. An ARIMA (, ) is used o decompose con racs series ino expeced and unexpeced componens. An ARIMA (, ) model is used o decompose he OI series ino expeced and unexpeced componens.