The Impact of Option Listing on the Trading Activity of Turkcell s American Depository Receipt (ADR)*

Transcription

1 The Impac of Opion Lising on he Trading Aciviy of Turkcell s American Deposiory Receip (ADR)* Aslı Aşçıoğlu** Mura Aydoğdu*** Lynn Phillips Kugele**** Bryan Universiy Rhode Island College The Universiy of Mississippi Absrac We invesigae he impac of he inroducion of opions on he marke microsrucure aspecs of he NYSE-raded Turkcell İleişim Hizmeleri A.Ş., (Turkcell) ADR by sudying changes in fundamenal marke liquidiy merics before and afer he opion (TKC) lising. We find ha boh daily relaive quoed spreads and daily effecive spreads decrease afer he opion inroducion. Addiionally, we show ha he number of rades increases saisically significanly, while volailiy, rade size and rading volume show no saisically significan change. We conclude ha he inroducion of opions has a posiive impac on he rading of he underlying asse, Turkcell s ADR, reducing rading coss significanly while increasing liquidiy. JEL Codes: G10; G15; G14 Keywords: opion lising, liquidiy, rading coss, Turkcell Ileisim Hizmeleri A. Ş.,Turkcell ADR * The auhors hank Sam Agyei-Ampomah for his insighful commens and paricipans of he Mulinaional Sociey Annual Meeing 2010 for heir helpful discussions. Commens and suggesions from an anonymous referee on an earlier version of his manuscrip are graefully acknowledged. Any errors are he responsibiliy of he auhors. ** Aslı Aşçıoğlu is a Professor in he Deparmen of Finance a Bryan Universiy, 1150 Douglas Pike, Smihfield, RI , U.S.A. ascioglu@bryan.edu. *** Mura Aydoğdu is an Associae Professor in in he School of Managemen a Rhode Island College, 600 Moun Pleasan Avenue, Providence, RI , U.S.A. maydogdu@ric.edu **** Lynn Phillips Kugele is a Clinical Assisan Professor in he Deparmen of Finance a The Universiy of Mississippi, 5107 W.E. Ross. Parkway, Souhaven, MS 38671, U.S.A. lpkugele@olemiss.edu 1

2 Turkcell Amerikan Depo Serifikası (ADR) Opsiyonunun Borsaya Kaydedilmesinin Turkcell ADR Piyasa Harekeleri Üzerine Ekisi Öze Bu çalışma Turkcell İleişim Hizmeleri A.Ş. (Turkcell) ADR opsiyonunun New York Borsası na kaydedilmesinin, Turkcell ADR piyasa yapısı üzerindeki ekisini incelemekedir. Yapığımız çalışmada günlük piyasa alış-saış fiyaları arasındaki farkın ve günlük efekif alış-saış fiyalari arasindaki farkın opsiyonun borsaya kaydedilmesi sonrası azaldığını bulmakayız. Bunlara ek olarak, oplam günlük işlem adedinin isaisiksel açıdan anlamlı olarak arığını ancak volailie, işlem büyüklüğü ve işlem hacminin değişmediğini gösermekeyiz. Sonuçlar, Turkcell ADR opsiyonunun New York Borsası na kaydedilmesinin, Turkcell ADR piyasa yapısını olumlu ekileyerek işlem maliyelerini azalığını ve likidieyi arırdığını deseklemekedir. JEL sınıflandırması: G10; G15; G14 Anahar kelimeler: opsiyon borsa kaydı, piyasa likidiesi, Turkcell Ileisim Hizmeleri A. Ş, Turkcell ADR Turkcell İleişim Hizmeleri A.Ş., (Turkcell from here forward) is a Turkish-based, mobile elecommunicaions company esablished in Turkcell became a publicly raded company on July 11, 2000 by lising is common sock on he Isanbul Sock Exchange (İsanbul Menkul Kıymeler Borsası, or İMKB) under he icker symbol TKCELL. Turkcell simulaneously lised on he New York Sock Exchange as an ADR (NYSE, icker symbol: TKC), becoming he firs Turkish company raded on he NYSE. While TKCELL is one of he mos acively raded securiies on he İMKB, TKC is raded only moderaely on he NYSE. On December 22, 2005, he Pacific Sock Exchange (1) inroduced opions on Turkcell's ADR, an especially significan even as here is no esablished opion marke in Turkey. The exisence of Turkcell common sock shares, ADRs and opions on he ADR provides a unique opporuniy o furher invesigae he impac of opion inroducion on he asse underlying he opion (he ADR) as a proxy for he primary underlying asse, Turkcell shares. Furher, he srucure of he rading venues involved and he specific rading characerisics of he wo underlying securiies are sufficienly differen o offer he (1) The Pacific Sock Exchange was acquired in 2005 by he New York Sock Exchange via is purchase of ArcaEx. 2

3 possibiliy ha he effecs of opion inroducion may well differ from convenional expecaions. In his sudy, we analyze he impac of he inroducion of TKC opions on he marke microsrucure aspecs of he NYSE-raded ADR by sudying changes in merics measuring hree fundamenal marke liquidiy variables before and afer TKC s opion lising: he bidask spread, rade volume and reurn volailiy. In sudying he bid-ask spread, we uilize boh he quoed and effecive spread in our analysis. Trade volume is examined using number of rades, share volume and rade size. We find ha boh daily relaive quoed spreads and daily effecive spreads decrease afer he opion inroducion. Addiionally, we show ha he number of rades increases saisically significanly, while he volailiy, he rade size and he rading volume show no saisically significan change. We conclude ha he inroducion of opions on TKC has a posiive impac on he rading of TKC, Turkcell s ADR, reducing rading coss while increasing liquidiy. We believe ha hese resuls are indicaive of and consisen wih expecaions regarding he impac on equiy rading of he opions marke in Turkey. Derivaives rading has a very shor hisory in Turkey, wih TURKDEX, he Turkish Derivaives Exchange rading fuures conracs esablished in A Turkish equiy opions marke has ye o come o fruiion. I is generally agreed ha derivaive markes allow raders o beer shape he risk and reurn characerisics of heir porfolios, hereby increasing heir welfare and enriching he economy in which hey operae (Kalib, 1999: 6) According o Saaçioğlu, Karagül and Volkan (2005), markes ha provide a venue for acive rading in derivaive producs arac a larger share of oal global foreign direc invesmen han hose wih no acive derivaives markes. Turkish companies are increasingly influenced by global financial developmens, increasing he need for risk managemen ools. Saaçioğlu, e al. conclude ha his resuls in he need for he esablishmen of acive derivaives exchanges in Turkey, rading boh fuures and opion conracs. Saaçioğlu, Karagül and Volkan (2005) expec he following impacs on Turkish markes when here is sock opion rading in Turkey: Reduced volailiy of reurns Enhanced professional repuaion for Turkish capial markes in he inernaional arena. 3

4 Increased sock rading volumes. Improved sock marke efficiency and liquidiy. An improved price-adjusmen process. Significanly decreased bid-ask spreads. Availabiliy of risk diversificaion avenues for fund and porfolio managers. Provision of a high comfor level o foreign invesors who wish o rade in Turkish sock opions, leading o an increase in long-run and/or permanen foreign direc and porfolio invesmens flowing ino Turkey (Saaçioğlu, Karagül and Volkan, 2005: 44). Given he solid evidence supporing he benefis accruing o markes implemening rading in sock opions, we believe our resuls, hough limied o rading in one opion, can be exrapolaed o suppor he posiive impac sock opions rading will have on relaed equiy marke efficiency in Turkey as well as aracing more foreign invesmen o he counry. Background Trading Characerisics The New York Sock Exchange is a highly liquid aucion marke wih he majoriy of rades occurring beween acual buyers and sellers. Each lised firm has a single designaed marke-maker, he specialis, who is charged wih overseeing all rading in ha firm s sock. The specialiss obligaions include mainaining wo-sided quoes and generally insuring an orderly marke in he firm s sock. Priced orders (limi orders o buy or sell shares a a specific price) are recorded in he specialiss limi order book. Incoming marke orders may be execued agains an exising limi order, wih a floor rader or agains he specialiss own quoes. Orders are filled a eiher he bes available price (highes bid/lowes ask) or a a price inside he quoes, known as price improvemen, an even repored o occur 25% of he ime. In conras, he Isanbul Sock Exchange (İMKB) is a very acive bu highly volaile marke wih over 50% of lised shares owned by foreign and inernaional insiuional invesors. The İMKB is a compuerized, order-driven marke wih no marke-makers or specialiss and no opening call procedures for eiher is morning or afernoon sessions (9:30 am o 12 noon and 2:00 pm o 4:30 pm respecively). A disinc feaure of he İMKB is ha 4

5 during rading hours, order cancellaion or change is deemed almos impossible, a resricion designed o improve quoed deph and avoid sudden liquidiy shifs during he rading day. In addiion, due o he insiuional srucure of he İMKB, price improvemen or rades occurring inside he quoes, a major aracion of he New York Sock Exchange, is no possible on he İMKB. Typical sudies of he effecs of opion inroducion focus on he impac on he underlying securiy which is usually an acively raded common sock. In our sudy, he underlying securiy is a moderaely raded ADR raher han he rue primary asse, Turkcell common shares. Overall Effecs of Opion Lisings Lieraure on he impac of opions lisings generally agrees ha he inroducion of opions serves o complee he marke for he underlying securiy, expanding he opporuniy se for invesors. This case is made by many researchers, among hem Breeden and Lizenberger (1978), Hakansson (1978), Ardii and John (1980), John (1981), Damodaran and Lim (1991), Fedenia and Grammaikos (1992), Sahlsröm (2001), and Saaҁioğlu, Karagül and Volkan (2005). Typical explanaions cener around increases in liquidiy, reducions in informaion asymmery and greaer pricing efficiency as a resul of opions lising, wih hese resuls driven primarily by changes in he bid-ask spread, volailiy and rading volume. In explaining hese changes, Fedenia and Grammaikos (1992) and Sahlsröm (2001) sugges ha opions may allow raders o avoid shor sale consrains, allowing marke paricipans more freedom o profi from privae informaion. Several researchers sugges ha informed raders, viewing opions as superior speculaive insrumens, may migrae o he opions marke, reducing he level of informed rading in he underlying asse. A lower probabiliy of rading agains informaion drives a reducion in he adverse selecion componen of he sock s bid-ask spread and poenially higher liquidiy. In somewha conrary findings, DeTemple and Jorion (1991) find ha he sock prices of asses underlying recenly lised opions increased hrough 1980 bu his effec underwen a shif in 1981, wih prices exhibiing decreases hereafer. Their resuls are consisen wih hose of Conrad (1989), Kabir (1999) and Mayhew and Mihov (2000) who find sock price increases up o Sorescu (2000) and Danielsen and Sorescu (2001) also confirm ha he pre-1981 sock price increases ye price decreases afer DeTemple and Jorion sugges 5

6 ha his regime shif may be aribued o he inroducion of index opions in 1982 which serve he purpose of compleing he marke hus reducing he need for individual sock opions o serve his purpose. While his may be a conribuing facor in he marke impac of opions on U.S. socks, we believe ha he effec will be mued for an ADR based on a Turkish sock since, a he ime of he TKC opion lising, here was no index opion based on he Turkish marke index. The ishares MSCI Turkey Invesable Marke Index Fund was inroduced on March 26, Wih such srong and overall consisen previous resuls, we expec he inroducion of opions on TKC o have a posiive impac in he marke for he ADR. In order o es our expecaions, we focus on hree merics ypically associaed wih marke qualiy: he bid-ask spread, he volailiy of sock reurns, and rading volume. Hypohesis 1: Impac of Opion Lising on he Bid-Ask Spread Previous research on he impac of opions lising on he bid-ask spread of he underlying securiy consisenly finds a decline in spread, driven primarily by a decrease in he adverse selecion componen. Skinner (1989), Damodaran and Lim (1991), Rao, Tripahy and Dukes (1991), Schulz and Zaman (1991), Fedenia and Grammaikos (1992), and Kim and Dilz (1999) sudying U.S. markes concur in heir findings ha opions inroducion resuls in a decrease in he bid-ask spread of he underlying asse. Addiionally, Sahlsröm (2001), invesigaing Finnish socks, finds bid-ask spread levels are lower afer he opion lising, wih he adverse selecion componen, as well as he order processing, invenory and holding componens decreasing. Kumar, Sarin and Shasri (KSS, 1998) are represenaive of hese findings, reporing a decrease in he spread, driven by a reducion in he adverse selecion componen and persising even afer conrolling for changes in rading volume, volailiy and price. Fedenia and Grammaikos (1992), however, qualify hese overall resuls on he spread, finding ha highly liquid (NYSE) socks experience spread increases, while he bid-ask spread of illiquid (OTC) socks ends o decrease. While Turkcell shares are very acively raded on heir home marke, Turkcell s ADRs (TKC) and opions are lighly raded on he NYSE. Thus, we expec he bid-ask spread of he ADRs on he NYSE [BAS(NYSE)] o respond o opion inroducion in a manner more in line wih he OTC socks in Fedenia and Grammaikos and hus o experience a decline. 6

7 H 1 : BAS(NYSE) decreases wih he inroducion of opion rading. Hypohesis 2: Impac of Opions Lising on he Volailiy of he Reurns on he Underlying Asse The effec of opion lising on he volailiy of he reurns on he underlying asse is probably analyzed more han any oher aspec of marke impac. The resuls end o be fairly conclusive, wih researchers almos consisenly reporing a decline in volailiy afer opion lising. Hayes and Tennenbaum (1979), Whieside, Duke, and Dunne (1983), Ma and Rao (1988), Bansal, Prui and Wei (1989), Conrad (1989), Skinner (1989), DeTemple and Jorion (1990), Damodaran and Lim (1991), Rao, Tripahy, and Dukes (1991), and Schulz and Zaman (1991) find ha sock reurn volailiy in U.S. markes is lower afer opion inroducion. Similar resuls are found by Wa, Yadav, and Draper (1992) sudying he UK marke, Chaudhury and Elfakhani (1995) invesigaing he Canadian marke, Sucki and Wasserfallen (1994) he Swiss markes, Sahlsröm (2001) sudying Finnish socks, and Chen and Chang (2008) Taiwan. Damodaran and Lim s (1991: 647) findings are represenaive of hese resuls, reporing ha he lising of opions leads o significanly lower (emphasis in he original) variance in he daily reurns of he underlying socks Conversely, Kabir (1997) sudying he Duch marke, Calado, Garcia and Pereira (2005) sudying Poruguese markes and Mazouz and Bowe (2009) sudying NYSE socks lised on he CBOE find no significan change in risk following opion lising. In much he spiri of Fedenia and Grammaikos s findings on he bid-ask spread, Ma and Rao (1988) qualify heir resuls, suggesing ha differences in rading paerns of uninformed and informed raders resul in volaile socks becoming more sable afer opion lising, while sable socks become more volaile. In line wih Ma and Rao s findings combined wih he relaively ligh rading of TKC on he NYSE, we expec he volailiy of reurns on he ADRs on he NYSE [σ(nyse)] o decrease: H 2 : σ (NYSE) decreases wih he inroducion of opion rading. 7

8 Hypohesis 3: Impac of Opions Lising on Trading Volume of he Underlying Asse An increase in rading volume in he underlying asse following opion lisings in U.S. markes is repored by Hayes and Tennenbaum (1979), Skinner (1989), Schulz and Zaman (1991), Shasri, Sulan and Tandon (1996), Kumar, Sarin and Shasri (1998), and Jubinski and Tomijanovich (2007). Conversely, a decrease in volume is repored by Damodaran and Lim (1991) and no change in rading volume is documened by Whieside, Dukes and Dunne (1983) and Chamberlin, Cheung, and Kwan (1993), he laer sudying Canadian socks. Heer, Trede, and Wahrenburg (1997) find an increase in volume in German markes, Chen and Chang (2008) repor similar resuls in he Taiwan marke as do Yip and Lai (2009), sudying warran lisings in Malaysia. Kumar, Sarin and Shasri (1998) specifically find an increase in rading volume, rading frequency, and ransacion size afer opion lising, an effec which persiss even afer conrolling for changes in volailiy and price. They aribue he increase in rading volume o a combined effec of higher rading frequency and larger average ransacion size. In accord wih previous research resuls, we expec rading liquidiy measures, rading volume, rading frequency and he ransacion size on he NYSE o increase [Liquidiy(NYSE)]: H 3 : Liquidiy (NYSE) increases wih he inroducion of opion rading. Daa and Analysis Daa We obain all quoes and ransacions daa from 60 business days before and 60 business days afer he opion lising day, December 22, 2005, for TKC from he NYSE Transacion and Quoe (TAQ) daabase. We use he following filers: a) Only BBO eligible NYSE quoes are reained. b) Quoes and rades mus have a ime samp beween 9:30 am and 4:00 p.m. c) Trade price mus be > 0 d) Ask price mus be > 0 e) Bid price mus be > 0 f) Trades mus have a correcion code value greaer han or equal o one. g) Pre-opening quoes are excluded. 8

9 Analysis Mehodology We measure he relaive quoed spread as he difference beween he bid and ask quoes scaled by he quoe mid-poin (Ask Bid Relaive Quoed Spread (1) I is well esablished ha he quoed spread overesimaes he cos of ransacing as i does no accoun for rades occurring a prices inside he quoes, a relaively common occurrence on he NYSE. For mos orders execued on he New York Sock Exchange, he effecive spread paid by invesors averages half he quoed spread. Thus, we calculae he relaive effecive spread as follows: P M Effecive Spread 2 * (2) M where P is he ransacion price and M is he midpoin of he mached quoe. We also measure price improvemen given by a specialis, as he difference beween he relaive quoed spread and he effecive spread. M ) Overall Analysis As a firs es of our expecaions, we average relaive quoed spreads, effecive spreads, price improvemen, number of rades, rade size, rading volume and volailiy for each day for 120 days around he opion lising day. We use a T-Tes and a Wilcoxon Nonparameric Signed-Rank es o deermine wheher our liquidiy measures are saisically differen 60 days before and 60 days afer he opion lising. We expec o observe an increase in liquidiy, he number of rades, average rade size and oal rading volume, and a decrease in relaive quoed spreads, effecive spreads and volailiy. Specific Tess of Hypohesis 1: Impac on he Bid-Ask Spread We employ wo regressions o deermine wheher percenage bid-ask spreads decrease due o he inroducion of opions rading afer conrolling for rading characerisics. Basically, we follow Kim and Dilz (1999), wih he addiion of four ineracion erms o provide for finer uning of he resuls. Furhermore, an even like opion lising can aler he naure of he relaionship beween spread and he explanaory variables. Using ineracion 9

10 erms sheds ligh on wheher he sensiiviy of spread o he explanaory variables changes afer he opion lising. We divide each day ino 30-minue 13 inervals, and measure all variables for 30-minue inerval for each day. For he firs regression, he quoed spread is he dependen variable: SPR 1DUMMY 2LNTRADES 3LNVOLUME 4SIGMA 5 LNPRICE INTTRDS INTVOL INTSIGMA INTPRICE (3) Where: SPR is he average relaive quoed spread calculaed as he difference of he bid and ask quoes scaled by he quoe midpoin (Equaion 1) DUMMY is a dummy variable equal o zero for days prior o he opion lising period and one oherwise. LNTRADES is he naural log of oal number of rades LNVOLUME is he naural log of oal rading volume SIGMA is naural log of he difference beween he percenage maximum midpoin quoe price and he minimum midpoin quoe price LNPRICE is he naural log of average rading price INTTRDS is he ineracion variable for number of rades: DUMMY*LNTRADES INTVOL is he ineracion variable for rading volume: DUMMY*LNVOLUME INTSIGMA is he ineracion variable for volailiy: DUMMY*SIGMA INTPRICE is he ineracion variable for price: DUMMY*LNPRICE The second regression uses he relaive effecive spread as he dependen variable wih he same independen variables as described above. EFFSPR 1DUMMY 2LNTRADES 3LNVOLUME 4SIGMA 5 LNPRICE INTTRDS INTVOL INTSIGMA INTPRICE (4) We expec a negaive coefficien for he dummy variable if he spread is smaller following he opion lising afer conrolling for oher rading variables. We expec negaive coefficiens for boh LNTRADES and LNVOLUME, indicaing a reverse relaionship beween spreads and rading aciviy. (2) We expec a posiive coefficien for SIGMA consisen wih McInish and Wood (1992), who find a direc relaionship beween he level (2) McInish and Wood (1992) have a deailed discussion of deerminans of spreads, and esablish he relaionship beween spreads and oher rading aciviies. 10

11 of risk and spreads. Kim and Dilz (1998: 400) find all of he regression coefficiens for rading characerisics are saisically significan and consisen in sign wih prior microsrucure research. While he sign of he dummy variable is negaive in heir work, i is no saisically significan, leading hem o inconclusive findings. We expec resuls consisen wih Kim and Dilz, confirming a decrease in he bid-ask spread pos lising. In he case of boh regressions, we approach he analysis in a hree sep manner. For each specificaion, he firs regression (#1) includes he dummy, number of rades and volume variables along wih he number of rades and volume ineracion erms. In he second ieraion (#2), we add volailiy and he volailiy ineracion variable. In he final ieraion (#3), we add price and he price ineracion variable. Resuls Overall Resuls Table 1 displays he resuls of he T-ess and he Wilcoxon Nonparameric es on each of our variables of ineres, comparing pre-lising averages o pos-lising averages. The decreases in boh relaive spreads and effecive spreads are saisically significan a he 1% level. The sandard deviaions of boh spread merics also decline afer opion lising indicaing ha no only do spreads decline bu also become less volaile. The decline in price improvemen is also significan a he 1% level. Since he effecive spread decreases significanly from o , reducing he profi of a specialis (or a liquidiy provider o he marke), he price improvemen a specialis is providing o oher invesors also declines As visual confirmaion, Graph 1 shows boh spread variables and price improvemen for 120 days around he opion lising day, illusraing he rend of decreasing spreads and price improvemen afer he lising. Therefore, we find evidence of decreasing ransacion coss and suppor of Hypohesis 1. [Pu Table 1 abou here] [Pu Graph 1 abou here] The risk measure, a sandard deviaion of 30-minue inerval reurns, shows no saisically significan change in Table 1. Therefore, we rejec our Hypohesis 2 and do no find a decline in volailiy afer opion lising. On he oher hand, he median of volailiy shows a decrease from % o % afer he lising. This indicaes ha here are more days wih less volailiy afer he opion lising. 11

12 [Pu Graph 2 abou here] The hree rading level merics display conflicing resuls. Graph 2 clearly shows he increase in he number of rades around he opion lising day. On he oher hand, Graph 3 and Graph 4 visibly illusrae he decline in average rade size per day and daily oal rading volume respecively. [Pu Graph 3 abou here] [Pu Graph 4 abou here] Table 1 shows ha he number of rades increases by a saisically significan amoun from 374 rades per day o 477 rades per day, ye average rade size and overall rading volume decrease bu are no saisically significan excep he average rade size variable (significan a 5% based on T saisics). A possible explanaion for he decrease in rade size migh be ha raders shif from rading he underlying wih large size o rading he opion when i becomes available. In conclusion, we suppor our hypohesis 3 only for a liquidiy measuremen of number of rades, bu no for rade size and rading volume variables. Overall, hese findings indicae a significan improvemen in rading coss and he number of rades of TKC on he NYSE afer he inroducion of an opion. Specific Resuls on Hypohesis 1: Impac on he Bid-Ask Spread In furher analysis of he impac of opions inroducion on he bid-ask spread, we repor he resuls of our regressions in Table 2, Panels A and B. Panel A repors resuls using relaive quoed spread as he dependen variable in a sep-wise regression o analyze he impac of rading characerisics on he spread. Panel B repeas he analysis using effecive spread as he dependen variable. [Pu Table 2 abou here] The mos ousanding resul is ha he dummy variable is negaive and significan in all hree regressions in boh panels. This consisen resul clearly indicaes ha he inroducion of raded opions reduces boh he quoed and effecive spreads. Addiionally, he srengh of he relaionship (magniude of he coefficien) increases in each hree-regression se, even as addiional variables are added o conrol for rade characerisics. Looking a each regression in order, for Panel A, regression #1, he dummy variable coefficien is negaive and saisically significan as expeced, confirming ha he relaive quoed spread decreases afer opion lising. Addiionally, he number of rades is also 12

13 negaive bu no significanly so while he volume coefficien is posiive and significan a he 5% level. The negaive relaionship beween he spread and number of rades is consisen wih McInish and Wood (1992). Regression #2 adds he volailiy variable, measured by difference beween he percenage maximum midpoin quoe price and he minimum midpoin quoe price during he 30-minue inraday inerval, and he volailiy ineracion erm as explanaory variables. The coefficien of volailiy (SIGMA) is posiive and significan a he 1% level, again, consisen wih expecaions, as high (low) volailiy would increase (decrease) he bid-ask spread. Boh he dummy variable and number of rades reain heir appropriae sign and now boh are significan a he 1% level. The volume variable is now also negaive bu has los significance wih he enrance of he volailiy variable. Regression #3 adds price and he price ineracion erm as explanaory variables. Price is ypically included as a conrol variable in cross-secional analysis. Since we are sudying ime-series daa for a single securiy, is inerpreaion in his consrucion is less clear. Ineresingly, volume loses significance while volailiy reains significance. As price becomes significan (and he coefficien negaive) he dummy variable gains srengh. In fac, wih each sep of he regression, he dummy variable gains srengh. While hese findings are consisen wih Kim and Dilz (1991) in boh sign and significance, he meaning of he price variable resuls is less obvious. Since we are using only one sock in his analysis and, over he span of he sudy, he price of he sock increased while he spread decreased, our resuls could simply reflec ha change raher han a causal relaionship. Table 2, Panel B repeas he analysis described above, using effecive spread as he dependen variable. The resuls are consisen wih hose for relaive quoed spread in erms of sign and coefficien significance for all hree regressions. Focusing on he ineracion erms in regression #3 provides an analysis of he combined impac of opion lising and oher variables on he dependen variable, he bid-ask spread. Taking he dummy variable represening opion lising as he focal variable, we define number of rades (TRDS), rade volume (VOL), volailiy (SIGMA), and price (PRICE) as our moderaor variables. All four of hese along wih heir respecive ineracion variables are included in regression #3 in boh panels of Table 2. By adding he coefficien of each ineracion erm o he coefficien of is relaed moderaor variable we can deermine wheher he inroducion of opion rading resuls in he 13

14 spread being more or less sensiive o ha variable AFTER he opion lising. These combinaions and he resuling sensiiviies are shown in Table 3, Panels A and B. [Pu Table 3 abou here] Resuls are consisen for boh represenaions of he spread repored in Panels A and B. The ineracion of he dummy variable wih number of rades (TRDS) and volailiy (SIGMA) resuls in he spread being less sensiive o he moderaor variable, demonsraed by he sum of he coefficiens being smaller han he coefficien of he pure moderaor variable. In he case of rade volume (VOL), he spread is more sensiive while he ineracion of he dummy variable wih price (PRICE) resuls in a change in he sign of he addiive coefficien bu wih a smaller absolue magniude. Conclusions In his sudy, we analyze he impac of he inroducion of opions on he marke microsrucure aspecs of he underlying asse, he NYSE-raded Turkcell İleişim Hizmeleri A.Ş., (Turkcell) ADR, by sudying changes in fundamenal marke liquidiy variables before and afer he opion (TKC) lising. We find ha boh daily relaive quoed spreads and daily effecive spreads decline afer he opion inroducion. Our mulivariae regression analysis wih conrol variables for rade characerisics indicaes ha he inroducion of raded opions reduces boh he quoed and effecive spreads even afer conrolling number of rades, rade volume, and price. Addiionally, we show ha he number of rades increases by a saisically significan amoun. This indicaes improved liquidiy afer he opion lising. Reurn volailiy, rade size and rading volume show no saisically significan change, couner o our hypohesized expecaions. However, he sandard deviaions of average rade size and oal rading volume decrease pos-lising, indicaing a more sabilized marke. Overall, we conclude ha opion rading improves he rading characerisics of he TKC ADR on he NYSE mainly by reducing rading coss while improving liquidiy measured by number of rades. Given he solid evidence of he benefis accruing o markes implemening rading in sock opions, we believe our resuls, hough limied o rading in one lighly raded opion, can be exrapolaed o suppor he posiive impac sock opions rading will have on relaed equiy marke efficiency as well as by aracing more foreign invesmen in Turkey. 14

15 According o Saaçıoğlu, Karagül, and Volkan (2005: 45) in heir conclusion, Sock opions allow invesors, especially porfolio and fund managers, o paricipae in price movemens wihou commiing he large amoun of funds needed o buy he sock ourigh and lead o more permanen and long-run foreign capial invesmen in he Isanbul Sock Exchange Sock marke as foreign invesors ake advanage of his new hedging insrumen. Despie he significanly differen marke srucures of he NYSE and he IMKB, we anicipae similar liquidiy improvemens, assuming informed raders from he IMKB ake advanage of he opporuniy o rade opions. These implicaions are based on subsanial heoreical and empirical evidence confirming he abiliy of opions o complee he marke for he underlying securiy, resuling in improved liquidiy, wihou regard for he marke srucure of he rading venue. References Anderson, A. and Dyl, E. (2005). Marke Srucure and Trading Volume, Journal of Financial Research, 28(1): Ardii, F. and John, K. (1980). Spanning he Sae Space wih Opions, Journal of Financial and Quaniaive Analysis, 15: 1-9. Bansal, V.K., Prui, S., and Wei, K.C.J. (1989). An Empirical Reexaminaion of he Impac of CBOE Opion Iniiaion on he Volailiy and Trading Volume of he Underlying Equiies, Finance Review, 24: Bildik, R., (2004). The Effecs of Trading Hals and he Advanage of Insiuional Invesors: Evidence from he Isanbul Sock Exchange, Working paper, December. Breeden, D. and Lizenberger, R. (1978). Prices of Sae-coningen Claims Implici in Opion Prices, Journal of Business, 51: Calado, J.P.T., Garcia, M.T.M., and Pereira, S.E.T.M. (2005). An Empirical Analysis of he Effecs of Opions and Fuures Lising on he Underlying Sock Volailiy: The Poruguese Case, Applied Financial Economics, 15: Chamberlain, T.W., Cheung, C.S., and Kwan, C.C.Y. (1993). The Impac of Opions Lising on Sock Behavior and Marke Liquidiy, Journal of Business Finance and Accouning, 20(5): Chaudhury, M. and Elfakhani, S. (1995). The Volailiy Effec of Opions Lising: Some Canadian Experience, Quarerly Review of Economics and Finance, 35(1): Chen, D. and Chang, P. (2008). The Impac of Lising Sock Opions on he Underlying Securiies: The Case of Taiwan, Applied Financial Economics, 18:

16 Conrad, J. (1989). The Price Effecs of Opion Inroducion, The Journal of Finance, 44(2): Damodaran, A. and Lim, J. (1991). The effecs of opion lising on he underlying socks reurn processes, Journal of Banking and Finance, 15(3): Danielsen, B.R. and Sorescu, S.M. (2001). Why do Opion Inroducions Depress Sock Prices? A Sudy of Diminishing Shor Sale Consrains, Journal of Financial and Quaniaive Analysis, 36(4): DeTemple, J. and Jorion, P. (1990). Opion Lising and Sock Reurns, Journal of Banking and Finance, 14(4): Fedenia, M. and Grammaikos, T. (1992). Opions Trading and he Bid-ask Spread of he Underlying Socks, Journal of Business, 65(3): Hakansson, N.H. (1978) Welfare Aspecs of Opions and Supershares, The Journal of Finance, 33: Hayes, S.L. and Tennenbaum, M.E. (1979). The Impac of Lised Opions on he Underlying Shares, Financial Managemen, 8: Heer, B., Trede, M., and Wahrenburg, M. (1997). The Effec of Opion Trading a he DTB on he Underlying Sock s Reurn Variance, Empirical Economics, 22: John, K. (1981). Efficien Funds in a Financial Marke wih Opions: A New Relevance Proposiion, Journal of Finance, 36: Jubinski, D. and Tomljanovich, M. (2007) Opions Lisings and Individual Equiy Volailiy: A Survey, The Journal of he Fuures Marke, 27(1): Kabir, R. (1999). The Price and Volailiy Effecs of Sock Opion Inroducion: A Reexaminaion, Working paper, Tilburg Universiy, Neherlands. Kim S. and Dilz J.D. (1999). The Effec of Opion Trading on he Srucure of Equiy Bid/Ask Spreads, Review of Quaniaive Finance and Accouning, 12: Kumar R., Sarin A., and Shasri K. (1998). The Impac of Opions Trading on he Marke Qualiy of he Underlying Securiy: An Empirical Analysis, The Journal of Finance, 53 (2): Long D.M., Schinski M.D., and Officer D. (1994). The Impac of Opion Lising on he Price Volailiy and Trading Volume of Underlying OTC Socks, Journal of Economics and Finance, 18 (1): Ma, C.K. and Rao, R.P. (1988) Informaion Asymmery and Opions Trading, The Financial Review, 23:

17 Mayhew, S. and Mihov, V. T. (2005). Shor Sale Consrains, Overvaluaion, and he Inroducion of Opions, (Ocober 7, 2005). AFA 2005 Philadelphia Meeings. Available [online] a: SSRN: hp://ssrn.com/absrac= Mazouz, K. and Bowe, M. (2009) Does Opion Lising Impac Time-varying Risk Characerisics of he Underlying Socks? Evidence from NYSE Socks Lised on he CBOE, Applied Financial Economics, 19: McInish, T. and Wood, R. (1992). An Analysis of Inraday Paerns in Bid/ask Spreads for NYSE Socks, The Journal of Finance, 47(2): Rao, R.P., Tripahy, N. and Dukes, W.P. (1991) Dealer Bid-ask Spreads and Opions Trading on Over-he-couner Socks, Journal of Financial Research, 14: Saaçioğlu, E., Karagül, I., and Volkan, A. (2005). Usefulness of Derivaive Insrumens in Emerging Markes: Turkish Experience, Inernaional Business and Economics Research Journal, 4(2): Sahlsröm P. (2001). Impac of Sock Opion Lising on Reurn and Risk Characerisics in Finland, Inernaional Review of Financial Analysis, 10(1): Schulz, P.H. and Zaman, M.A. (1991). Opion Inroducion and he Underlying Sock s Trading Volume and Bid-ask Spread, Working paper. Shasri, K., Sulan, J., and Tandon, K. (1996). The Impac of he Lising of Opions in he Foreign Exchange Marke, Journal of Inernaional Money and Finance, 15(1): Skinner, D.J. (1989) Opions Markes and Sock Reurn Volailiy, Journal of Financial Economics, 23(1): Sorescu, S. (2000). The Effec of Opions on Sock Prices: , Journal of Finance, 55: Sucki, T. and Wasserfallen, W. (1994). Sock and Opion Markes: The Swiss Evidence, Journal of Banking and Finance, 18: Wa, W.H., Yadav, P.K., and Draper, P. (1992). The Impac of Opion Lising on Underlying Sock Reurns: The UK Evidence, Journal of Business Finance and Accouning, 19: Whieside, M.M., Duke, W.P., and Dunne, P.M. (1983). Shor Term Impacs of Opion Trading on Underlying Securiies, Journal of Financial Research, 6 (Winer): Yip, Y. and Lai, M. (2009). Impac of Warran Lisings on Is Underlying Socks: The Malaysian Evidence, Academy of Accouning and Financial Sudies Journal, 13(3):

18 $ Graph 1: Spreads Dollar Relaive Spread Effecive Dollar Spread Price Improvemen Relaive o even day Graph 2: Number of Trades Number of Trades Relaive o even day 18

19 Graph 3: Average Trade Size Average Trade Size Relaive o even day Graph 4: Trading Volume Trading Volume Relaive o even day 19

20 Table 1 Summary Saisics and Comparison Tess for Pre-lising and Pos-Lising Time Period All summary saisics are daily averages over 60 days before he opion lising (prelising period) and 60 days afer he opion lising (pos-lising period), including he opion lising day. Each variable excep volailiy measure is calculaed for every rade during he day, and hen averaged per day. Volailiy is 30-minue rade-o-rade reurns over a day. Relaive quoed spread is calculaed as difference of he bid and ask quoes scaled by he quoe mid-poin. Effecive spread is he absolue difference beween he ransacion price and he quoe mid-poin scaled by he quoe mid-poin. Price improvemen is he difference beween he quoed spread and he effecive spread. We use he T_es and he Wilcoxon Nonparameric Rank Saisics o es wheher liquidiy measures are saisically differen 60 days before and 60 days Afer he opion lising. T-Tes (Suden- Values) Wilcoxon Rank Tes (Z values) Variable Pre-Lising Period Pos-Lising Period Mean Median Sd. Dev Mean Median Sd. Dev Relaive Quoed Spread (x100) *** -2.90*** Effecive Spread (x100) *** -2.72*** Price Improvemen (x100) *** -2.50** Number of Trades *** 3.19*** Average Trade Size ** Trading Volume 334, , , , , , Volailiy % % % % % % Average Trade Price $14.30 $14.26 $1.05 $17.26 $17.33 $ *** 8.96*** Noes: 1. *, **, and *** denoe significance a he 10%, 5%, and 1% levels, respecively. 20

21 Table 2 OLS Regression Analysis of Quoed and Effecive Spread This able shows he sep-wise regression resuls when spread measure is regressed agains rading characerisic variables. In Panel A, he dependen variable (SPR) is he daily average relaive quoed spread calculaed as he difference of he bid and ask quoes scaled by he quoe mid-poin. In Panel B, he dependen variable (EFFSPR) is he daily average relaive effecive spread calculaed as he absolue difference beween he ransacion price and he quoe mid-poin scaled by he quoe mid-poin. Each variable is calculaed for 30-minue 13 inervals for each day. We esimae he following ime series regression: SPR DUMMY LNTRADES LNVOLUME SIGMA LNPRICE 1 The descripion of he variables provided below: 2 INTTRDS INTVOL INTSIGMA INTPRICE, DUMMY: LNTRADES: LNVOLUME: SIGMA: LNPRICE: INTTRDS: INTVOL: INTSIGMA INTPRICE: 1 for days afer opion lising day, 0 oherwise naural log of oal number of rades naural log of oal rading volume naural log of he difference beween he percenage maximum midpoin quoe price and he minimum midpoin quoe price naural log of average rading price ineracion variable for number of rades: DUMMY*LNTRADES ineracion variable for rading volume: DUMMY*LNVOLUME ineracion variable for volailiy: DUMMY*LNSIGMA ineracion variable for rading price: DUMMY*LNPRICE Panel A: Regressions wih Relaive Quoed Spread as dependen variable Dependen Variable: Relaive Quoed Spread (SPR) Regression # (1) (2) (3) Consan 0.294*** (7.73) 1.126*** (24.05) 2.041*** (14.33) DUMMY *** (-3.31) *** (-4.91) *** (-6.02) LNTRADES (-5.23) *** (-9.5) *** (-9.41) LNVOLUME 0.014** ( 2.41) ( -0.60) ( 0.22) SIGMA 0.103*** (23.57) 0.098*** (22.40) LNPRICE *** (-7.01) INTTRDS 0.036** (2.29) 0.032** (2.47) 0.029** (2.30) INTVOL (0.37) (0.89) (0.39) INTSIGMA *** (-4.00) *** (-3.26) INTPRICE 0.412*** (5.10) Number of Observaions Adjused R 2 F-Value (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) 21

22 Table 2 (coninued) Panel B: Regressions wih Relaive Effecive Spread as dependen variable Dependen Variable: Relaive Effecive Spread (EFFSPR) Regression # (1) (2) (3) Consan 0.206*** 0.294*** 0.762*** 1.126*** 1.35*** 2.041*** 1.126*** 2.041*** 1.126*** 2.041*** (7.73) (7.73) (22.51) (24.05) (13.47) (14.33) (24.05) (14.33)(24.05) (14.33) DUMMY *** ***-0.228*** ***-0.866*** *** ***-1.379*** ***-1.379*** (-3.31) (-3.31) (-4.45) (-4.91) (-5.21)(-6.02) (-4.91) (-6.02)(-4.91) (-6.02) LNTRADES *** *** *** *** *** *** *** *** *** (-5.63) (-5.63) (-7.61) (-9.5) (-7.49)(-9.41) (-9.5) (-9.41)(-9.5) (-9.41) LNVOLUME 0.007* 0.014** ( 1.72) ( 2.41) ( -1.22) ( ( -0.60) ( -0.49) ( 0.22) -0.60) ( 0.22) ( -0.60) ( 0.22) SIGMA *** 0.103*** 0.066*** 0.098*** 0.103*** 0.098*** 0.103*** 0.098*** (21.76) (23.57) (20.68) (22.40) (23.57) (22.40)(23.57) (22.40) LNPRICE *** *** *** *** (-6.25)(-7.01) (-7.01) (-7.01) INTTRDS ** ** ** ** 0.029** ** 0.029** (1.44)(2.29) (1.35) (2.47) (1.19) (2.30) (2.47) (2.30) (2.47) (2.30) INTVOL (0.94)(0.37) (1.49) (0.89) (1.03) (0.39) (0.89) (0.39) (0.89) (0.39) INTSIGMA *** ***-0.012*** *** *** *** *** *** (-3.39) (-4.00) (-2.71)(-3.26) (-4.00) (-3.26)(-4.00) (-3.26) INTPRICE 0.256*** 0.412*** 0.412*** 0.412*** (4.37) (5.10) (5.10) (5.10) 2.041*** (14.33) *** (-6.02) *** (-9.41) ( 0.22) 0.098*** (22.40) *** (-7.01) 0.029** (2.30) (0.39) *** (-3.26) 0.412*** (5.10) Number of Observaions Adjused R F-Value (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) (Pr<0.0001) Noes: 1. *, **, and *** denoe significance a he 10%, 5%, and 1% level, respecively (Pr<0.0001) 22

23 Table 3 Analysis of Ineracion Effecs This able draws from he regression #3 resuls shown in Table 2, Panels A and B. Column #3 in each panel repeas he resuls from Table 2. The +INT column combines he coefficien of each moderaor variable wih is associaed ineracion variable. The resuling sensiiviy of he dependen variable (bidask spread) o his ineracion is refleced in he SENS column by he direcion of he arrows. Panel A SPR Panel B ESPR #3 + INT SENS #3 + INT SENS CONSTANT DUMMY (1.3790) (0.8660) TRDS (0.0849) (0.0559) (0.0490) (0.0380) VOL (0.0010) SIGMA PRICE (0.3720) Δ (0.2400) Δ INTTRDS INTVOL INTSIGMA (0.0208) (0.0120) INTPRICE ADJ R F-STAT