Cross-listing, Price Discovery and the Informativeness of the Trading Process. *

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1 Workng Paper Busness and Economcs eres 11 Ocober 2001 Deparameno de Esadísca y Economería Unversdad Carlos III de Madrd Calle Madrd, Geafe pan Fa Cross-lsng, Prce Dscovery and he Informaveness of he Tradng Process. * Robero Pascual 1, Barolomé Pascual-Fuse 2 and Francsco Clmen 3 Absrac Ths paper analyzes he prce dscovery process of a se of pansh socks cross-lsed a he E. Our mehodology dsngushes beeen o sources of nformaon asymmeres. Marke-specfc nformaon ha s revealed hrough he radng process and publc dsclosures smulaneously revealed o boh markes bu subjec o nformed judgmens. We compue he nformaon share of he pansh and U.. radng acvy durng he daly 2-hour overlappng nerval. Emprcal resuls sho ha he E conrbuon o he prce dscovery process s no neglgble. Bu he E nformaon s bascally rade-unrelaed. 1 Deparameno de Economía y Empresa Unversdad de las Islas Baleares and Deparameno de Economía de la Empresa Unversdad Carlos III de Madrd 2 Deparameno de Economía y Empresa Unversdad de las Islas Baleares 3 Deparameno de Economía Fnancera y Maemáca Unversdad de Valenca Keyords: Cross-lsng, prce dscovery, rade-relaed nformaon, ADRs. * Correspondng auhor: Robero Pascual, Deparameno de Economía y Empresa, Unversdad de las Islas Baleares, Cra. Valldemossa Km 7.5, Palma de Mallorca, Islas Baleares, PAIN, Phone: , Fa: R. Pascual s graeful for he hospaly of he Busness Deparmen of he Unversdad Carlos III of Madrd and for her cooperaon durng he developmen of hs research projec.

2 I. Inroducon When an asse s raded a mulple markes, a crucal queson naurally arses: hch marke does conrbue more o he dscovery of he effcen prce. A large par of he research on hs ssue has been focused on dscernng heher U.. regonal markes are nformaonally relevan for he E-lsed socks e.g., Chorda and ubrahmanyam, 1995; n e al., 1995; Blume and Goldsen, Hoever, he ncreasng mporance of non U.. companes lsed on he E see Palakonak and ofanos, 1999 has also movaed a grong neres n he role ha he U.. sock echanges play n fndng ou he effcen value of he nernaonal dually-lsed socks e.g. Werner and Kledon, 1996; Chan e al., Ths paper presens an emprcal analyss ha makes use of nra-daly daa on a se of pansh socks raded as ADRs on he E durng he year The sudy ceners he aenon on he daly overlappng radng nerval beeen boh he E and he Connuous Tradng ysem of he pansh ock Echange E. Our man concern s o deermne ho much of a change n he effcen prce s relaed o he pansh and o he U.. radng acvy. The procedure e propose allos o dscern o ha eend he E conrbues o prce dscovery and heher he nformaon provded by hs marke s rade-relaed or rade-unrelaed nformaon. Harrs e al use a Vecor Error Correcon Model VECM o sudy he adjusmen mechansm of he E and regonal prces oards he common underlyng effcen prce. A sgnfcan error correcon mechansm n he E prce equaon ndcaes ha regonal markes do conrbue o he prce dscovery of E-lsed socks. Hasbrouck 1995 proposes a common rend represenaon o model he E and regonal quoes. In hs model, he fracon of he long-erm varance he varance of he common facor ha s eplaned by each marke s used o measure s nformaon share. Hasbrouck fnds ha he nformaon share of he regonal markes s relavely unmporan. Tse 2000 argues ha hese o economerc models are equvalen and he emprcal dfferences are due o mehodologcal ssues. Recenly, Harrs e al uses he common facor esmaon mehod proposed by Gonzalo and Granger 1995 o evaluae each marke s proporon of he prce dscovery. In hs mehodology he long memory componen of sock prces s characerzed as a eghed average of he conemporaneous rade prces. The eghs sgnfy he ncdence of rades ha permanenly move prces on each marke. Ther fndngs sho changes n he locaon of prce dscovery over me. Hupperes and Menkveld 2000 and Grammg e al

3 adap he Hasbrouck 1995 model o he analyss of non U.. E-lsed socks. eberman e al. 1999, Dng e al and Eun and abheral 2000 do he same h he Harrs e al mehodology. These sudes repor med fndngs. Prevous papers do no dfferenae beeen alernave sources of nformaon because he radng acvy s no openly modeled. In hs paper e consder o possble causes of nformaon asymmeres beeen markes. Frs, he presence of nformed agens endoed h superor nformaon abou he rue value of he sock e.g., O Hara, Ths nformaon, e assume, s revealed hrough radng. Because nformed agens mus decde here o eplo her nformaon advanage e.g., Chodhry and Nanda, 1991, rade-relaed nformaon becomes marke-specfc. o, may cause ransory dfferences n he markes epecaons abou he rue value of he sock. Trade-relaed nformaon becomes publc as soon as s revealed n some marke. Follong ubrhamanyam 1997, e measure he rade-relaed shocks as he unepeced componen of he E and E radng processes. econd, publc announcemens, characerzed as nosy sgnals e.g., Harrs and Ravv, 1993, may also cause nformaon asymmeres. Ths rade-unrelaed nformaon s smulaneously eposed o all markes. Hoever, markes dffer n her ably o process publc dsclosures. Km and Verreccha 1994 develop a model n hch some agens process publc nformaon no prvae nformaon resulng n superor judgmens. In our cone, e epec he agens n he home marke he E o perform more accurae assessmens and o respond more quckly o publc dsclosures han he foregn marke he E. Bu, snce an mporan par of he pansh cross-lsed frms busness acvy akes place n Amerca, some publc shocks mgh be dssemnaed sooner n he E prces. A gven publc announcemen provdes he marke h superor capacy o process h a emporary advanage over he oher marke. Publc dsclosures are refleced n he rade-unrelaed unepeced componens of he E and he E quoes. We movae our emprcal analyss by means of a srucural model for o markes ha smulaneously rade one sock. Each marke forms s sequence of condonal epecaons abou he secury s ulmae value drang on he revsons of her avalable nformaon se. These nformaon ses are updaed because of rade-relaed and radeunrelaed nformaon shocks. A pure saelle marke has an unnformave radng process and s ncapable of nerpreng publc announcemens. I s shon ha he naural 3

4 emprcal counerpar of hs model s a vecor error correcon VEC model ha eplcly models he nformave unepeced componen of he radng process. The correspondng common rend represenaon of he VEC model allos o measure he conrbuon of he radng acvy n each marke o he long-erm volaly of he nernaonally cross-lsed sock. Hasbrouck 2000 conrass he nformaon share approach n Hasbrouck 1995 h he permanen-ransory approach n Harrs e al Hasbrouck shos ha n he case of a o markes model h prvae and publc nformaon, smlar o he one presened n hs paper, he nformaon share approach s more relable. The bound generaed by he nformaon share approach conans up o esmaon error he rue value. Ths canno be sad for he permanen-ransory approach. Therefore, e slghly modfy he nformaon share approach n Hasbrouck 1995 o dfferenae beeen he nformaon share ha corresponds o each marke s rade-relaed nformaon and o her relave capacy o evaluae and quckly dssemnae publc nformaon. The emprcal fndngs sho ha he E conrbuon o prce dscovery s no neglgble. The E quoes and he E quoes are conegraed, so hey share a common long-run componen. Boh markes reac o any devaon beeen her quoes, sgnfyng ha e are facng a o-ay prce dscovery process see Harrs e al., The radng acvy a he E sgnfcanly affecs o he quoes posed by he o markes. Afer a perod of posve ne volume more buyer-naed han seller-naed volume or posve ne radng more buyer-naed han seller-naed rades E and E quoes ncrease. mlarly, he E radng acvy sgnfcanly affecs o he E quoes even hen he pansh acvy s aken no accoun. Is mpac on he E quoes, hoever, s eaker and depends on he radng frequency of he sock. These fndngs sugges ha he nformaon brough n by he E marke s manly radeunrelaed. The nformaon shares compued confrm hs nuon. The 70-90% of he effcen prce s long-run varance s due o non rade-relaed shocks frs dssemnaed n he E quoes. Beeen 10-20% s due o E rade-relaed nformaon and less han he 0.5% s due o E rade-relaed nformaon. The nformaon share due o publc announcemens dssemnaed frs a he E vares beeen he 1% and he 3% dependng on he sock and he radng proy used. Globally, e conclude ha he E s no a pure saelle marke for he pansh cross-lsed socks, bu s conrbuon o prce dscovery s manly due o publc announcemens probably orgnaed a Amerca 4

5 and dssemnaed sooner n he E quoed prces han n he E quoed prces. We also provde srong evdence ha for he E he volume ransaced s more nformave ha he number of rades. On he conrary, for he E e repor eak evdence ha s he occurrence of ransacons per se and no he volume raded ha conrbues o he prce dscovery of he pansh cross-lsed socks. The paper s organzed as follos. In secon II e movae he analyss descrbng a frameork for he quoe formaon of a cross-lsed sock ha dsngushes beeen raderelaed and rade-unrelaed nformaonal shocks. In secon III e nroduce he emprcal VEC model. In secon IV e defne he nformaon share measure for he U.. and he E radng process. In secon V e descrbe he daa se. In secon VI e summarze he resuls of esmang he economerc model. In secon VII e provde he nformaon shares for each marke. Fnally, n secon VIII e conclude. II. Movaon Ths secon presens a useful frameork o movae and nerpre our poseror emprcal analyss. Consder a sock ha s raded a o dfferen markes h radng sessons ha overlap durng a gven me nerval. Indeed, hs s he case for he pansh socks cross-lsed a he E. Frs, e develop a model n hch publc dsclosures are no nosy sgnals. Publc dsclosures may no lead o dfferen nerpreaons. The o markes adjus quoed prces a he same me and by he same amoun afer a radeunrelaed shock. Thus, he unque source of nformaon asymmeres beeen markes s he rade-nferred nformaon. Consder frs ho epecaons are formed. e m be he epecaon abou he rue value of he sock gven he full nformaon se a momen. Tha s, m [ ψ τ φ ] = E, [1] here E[..] s he condonal epecaon, ψ τ s he rue value of he sock n a fuure reference momen τ for eample, he end of radng a he E and φ s he oal nformaon avalable n boh markes a momen. We assume ha hs nformaon s fully nferred from he me seres of prevous quoes and rades. The common nformaon se φ C ncludes he curren and all prevous rade-unrelaed shocks and he hole hsory of rade-relaed shocks ll perod -1. The rade-relaed marke-specfc nformaon s 5

6 nally revealed eher a he E φ or a he E φ. Under hs srucure e C have ha φ = { φ, φ, φ }. Gven ha, a some pon n me, he nformaon ses avalable a he E and E markes may dffer, he epecaon abou ψ τ n each marke may also be dfferen. Therefore, le he epecaon abou he rue value of he sock a marke ={, } a perod be m C [ ψ τ φ, φ ] The marke s epecaons follo he process n equaon [3], = E. [2] m = m * + λ, [3] here * m represens he epecaon abou he rue value of he sock hen only he C common nformaon se s avalable, ha s m E[ ψ τ φ ] 2 2 n [3], h E [ ] = 0, E[ ] = σ and [ ] = 0 * =. The sochasc process j E j 0, characerzes a raderelaed nnovaon ha updaes he marke s nformaon se. The parameer ho much of hs rade-relaed shock s ne nformaon e.g., Hasbrouck, λ measures The epecaon based on he common nformaon se m follos he random alk process [4], * m + * = m 1, [4] h beng a zero-mean uncorrelaed sochasc process represenng an nnovaon n he common nformaon se C C C φ,.e. φ = { φ 1, }, due o a publc dsclosure a perod. Noce ha equaon [4] mples ha any specfc nformaon gven aay a perod -1, eher a he E or a he E, becomes common nformaon he ne perod C { φ 1, φ 1 } φ. Ths mposes a shor-erm convergence n epecaons beeen boh markes. 1 Thus, m = m + λ +. [5] 1 Consequenly, he revsons n he epecaons abou he rue value of he sock a boh markes have a common componen and an dosyncrac componen λ, ={, 6

7 * }. For eample, f = 0 and 0 e have ha m = m = m 1 + and m = m. Tha s, he pansh marke has a more precse epecaon a perod han he E. In hs scenery, he ould behave as a pure saelle marke f all he raderelaed nformaon ere dssemnaed hrough he E radng acvy.e. λ = 0. We mpose he resrcon ha, and are muually uncorrelaed processes. Ths mples ha he rade-relaed shocks are uncorrelaed h he shocks movaed by publc announcemens: [ ] = 0 E, j 0.2 By defnon, dosyncrac shocks a dfferen j markes are also uncorrelaed, [ ] = 0 he complemen of. E j 0 and ={,}, h represenng j In ha follos e descrbe he quoe formaon process. Quoes n boh markes are he resul of he frm demand and offer posons by lqudy provders. In he E he bes quoes may represen he neress of he specals, he floor brokers and he lm orders n he specals s Dsplay Book. On he conrary, he E s a pure elecronc order drven marke and, consequenly, he quoes represen he bes prces a he offer and demand sdes of he elecronc lm order book. In hs paper, e average quoes usng he quoe mdpon of he bd-ask spread, q a + b =, 2 here a and b represen he bes ask and bd quoes n marke ={,}. These quoes ncorporae all he nformaon revealed up o perod, boh specfc and common. The change n quoes a perod ll be q = q q 1. e q = m +, [6] here he process sasfes ha E = 0, E = σ k k k 0. Therefore, he erm represens a covarance-saonary or eak-saonary sochasc componen of quoed prces. 3 prce. The sze of I capures ransory devaons beeen he quoe mdpon and he effcen depends on dspares n marke makng coss, marke frcons lke he ck sze, and oher specfc feaures of he mcrosrucures of boh markes. 7

8 Equaon [6] mples ha q s a non-saonary process snce depends on a long-run componen m ha s negraed of order 1, I1. Neverheless, as hs non saonary * componen s common o he U.. and he pansh quoes, here ess a lnear combnaon of boh quoes ha does s saonary, q q = m m + = [7] = λ λ +. As a consequence, he dfference beeen he quoe mdpons s a saonary sochasc process, meanng ha boh prces are conegraed h a heorecal conegraon vecor [1, 1]. The conegraon condon s necessary o avod profable arbrage opporunes. In he prevous specfcaon s assumed ha boh markes smulaneously reac o publc announcemens. Consder an ereme case n hch all publc sgnals are frs observed by he home marke he E and ransmed o he foregn marke he E h some lag. To ncorporae hs possbly, le he E quoe be gven by m = m 1 + λ. [8] Equaon [8] eplcly ndcaes ha he E epecaons a perod do no accoun for. Under hs specfcaon boh prces are sll conegraed. Moreover, under he convenen assumpon ha s very close o zero, q q 1 + λ. [9] Equaon [9] shos ha, also n hs case, f λ = 0 he radng acvy s no nformave he E ould be a pure saelle marke for he pansh cross-lsed socks. We rela he prevous assumpon ha publc dsclosures are no nosy sgnals. Hence, e allo for a second source of nformaon asymmeres beeen markes: her respecve ably o evaluae publc sgnals. Publc dsclosures consue mperfec nformaon, n he sense ha he valuable nformaon s communcaed h some dsoron. One marke may have more capacy o recognze he useful nformaon eher because more closely monors he frm or because has access o more complee 8

9 nformaon abou he publc sgnal. Therefore, markes dffer n he qualy of her judgmens. Km and Verreccha 1994 develop a model n hch earnng announcemens provde nformaon ha may lead o dfferen nerpreaons see also Harrs and Ravv, 1993, and Bamber e al., Ceran raders posses specal capables ha allo hem o make nformed judgmens ha are superor o he judgmens of oher raders. We jus adap Km and Verreccha s frameork here. Consder ha he publc sgnal s ~ = + δ, [10] here δ s a sochasc process ha represens a dsoron n he announcemen, [ ] = E δ, E [ δ ] =σ and E[ δ ] = 0 δ uncorrelaed. mulaneously o he dssemnaon of δ j j 0. We assume ha ~ each marke observes δ and are muually J = δ + ζ, [11] here ζ measures he nformaon a marke gleans abou he random error by more closely sudyng he frm, s fnancal repors and busnesses. 4 e [ ] = E[ ζ ] = σ and E[ ζ ] = 0 δ and ζ, ζ j j 0, ={,}. Agan, e assume ha E ζ, ζ are muually uncorrelaed. The qualy of he markes judgmen depends on he precson of 2 J. If σ 0 for all hs specfcaon s equvalen o he one n equaons [1]-[5]: he ζ, = o markes perfecly solae he nose δ from he valuable nformaon. Hence, boh marke adjus her epecaons smulaneously and here are no dfferences n her nerpreaons. I follos ha, ceers parbus, he E behavor ll appromae more ha of a saelle marke equaons [8]-[9] f σ σ ends o zero. The judgmens of 2 2 ζ, / ζ, he E agens ould be so mprecse ha he revson n he E epecaons m ould be unrelable and, hence, ransory. We assume ha he realzaon becomes publc knoledge he perod afer he announcemen. Therefore, publc sgnals only provde a emporary advanage o he marke h he mos accurae nformaon abou he sgnal. The perod afer he sgnal markes epecaons ll converge f here are no addonal rade-relaed or rade-unrelaed shocks. The marke s epecaons are updaed follong equaon [12], * ~ m = m + λ + J, [12] 9

10 here he common-knoledge condonal epecaon m s no gven by * m * * = m λ λ. Noce ha f σ 0 he change n he epecaon of ζ, marke has a dsorng componen ha ll be correced he ne perod. e ρ be he correlaon coeffcen beeen ~ and ~ and assume ha J J 1 ρ 0. If ρ=1 boh markes observe he same nformaon and have he same poseror belefs. If ρ=0 he o marke ll have poseror fully heerogeneous belefs. Therefore, he emprcal correlaon beeen he rade-unrelaed unepeced componens of he E and he E quoes ll help o dscern hch one of he prevous frameorks s more realsc. Gven he greaes relave mporance of he pansh cross-lsed socks n he E, seems reasonable o epec ha he agens n he home marke ll make more precse judgmens han he agens n he foregn marke. If hs s he case, publc dsclosures ould be dssemnaed frs n he E quoes. Bu hen he publc sgnal concerns he frm s acvy n Amerca or general nes abou he Amercan economy, he advanage mgh be for he agens n he foregn marke. The conegraon resul beeen he E and he E quoe mdpons sll holds for hs alernave scenaro, meanng ha he approprae emprcal counerpar o our frameork s an error correcon model. Ne secon develops our emprcal specfcaon. III. The emprcal model The mos common effcen parameerzaon of a vecor of conegraed varables s, from he Granger s Represenaon Theorem n Engle and Granger 1987, a VECM. Equaon [13] represens he error correcon represenaon of he E and E quoes for he heorecal model of he prevous secon, α ~ ~ u, [13] q = q 1 βq 1 + Φ q 1 + Φ q 1 + h ={, } and =1-, ha s q = q q. The erms ~ Φ, for k={,-}, are 1 auoregressve polynomals n he lag operaor k y = y -k havng all her roos ousde he un crcle. The componen q β q s he normalzed error correcon erm. 1 1 Presumably, β s equal o 1. The parameer α measures ho faser does marke respond o a dvergence beeen he U.. and he pansh quoe mdpons. If hese parameers are sgnfcan for boh quoe mdpons, ould sgnal ha e are facng a o-ay prce k 10

11 dscovery process see Harrs e al., 1995 and, hence, ha he E s no a pure saelle marke for he pansh cross-lsed socks. The vecor of nnovaons u ' = u, u n [13] ncludes boh he nnovaons assocaed o he radng process and he nnovaons assocaed o he publc announcemens. Eplcly, le u be gven by u ~ ~ = θ + θ +, [14] j j here ~ θ, k={,j}, are fne lag polynomals h all roos ousde he un crcle. k Equaon [14] s specfed general enough as o capure usual feaures of nra-daly daa caused by marke frcons and specfc radng rules. Equaon [14] suggess ha because of marke frcons all he nformaon he rades release a perod may no be refleced nsananeously no marke quoes. 5 Thus, he unepeced componen of rades may have lagged effecs on he quoe mdpon e.g., Hasbrouck, 1991a, and Pascual e al., The vecor of rade-unrelaed shocks ' =, ncorporaes he nformaon nferred from he publc sgnal, ~ and ~ respecvely, bu also dosyncrac J J feaures of each marke ha e do no model eplcly, lke he ck sze. Under he assumpon ha boh markes have he same ably o judge he publc announcemen 0, and should be hghly correlaed see he dscusson a he end of he prevous secon. Hence, e epec E 0 due o a common facor. In order o denfy he componens n [14], e modfy he emprcal model [13]-[14] by allong he quoe process be gven by, q = α + q 1 βq 1 + Φ q 1 + Φ q 1 + θ + θ [15] here s defned as a saonary sochasc process represenng he ne raded volume n perod and marke. A posve value of > 0 mples more buyer-naed volume raded han seller-naed volume. On he conrary, f < 0 means ha he seller-naed raded volume s larger han he buyer-naed one. The generang process of s gven by, = Π + [16], 1 + Π, 1 + Πq, q 1 + Πq, q 1 11

12 12 here, k h Π, for h={, q}, ={,} and k={, -}, are lag polynomals h all roos ousde he un crcle. The ne nformaon nferred from he radng process, {, }, s nerpreed as he unpredcable componen of he ne volume raded. By subsung recursvely [16] no [15], s sraghforard o see ha [15]-[16] and [13]- [14] are equvalen emprcal specfcaons. Noce ha n [16] he radng process does no depend on he conemporaneous change n marke quoes. Ths s because n our model causaly flos from he radng process o he revson of marke quoes. We end h an emprcal model h four equaons, o for he E and he E quoes and o for her respecve radng processes, + + = q q B q q q q A β α α , [17] h = ,0,0,0,0 A θ θ θ θ and Π Π Π Π Π Π Π Π Φ Φ Φ Φ =,,,,,,,, * * * * B q q q q θ θ θ θ, here 1,0 * = j j j θ θ θ. Gven ha e epec 0 E, e have a sysem of seemngly unrelaed equaons ha could be effcenly esmaed by URE Zellner, IV. The nformaon conen of rades IV.A. Informaon share Hasbrouck 1991b defnes he nformaon conen of he radng process as he varance of he epeced mpac of a rade nnovaon on he nformaonally effcen prce. In our case, [ ] [ ] E m E Var 1 φ, [18]

13 here agan ={,}. Epresson [18] s an absolue measure of he amoun of specfc nformaon provded by he radng acvy a marke o form he epecaon abou he effcen prce. From [16], Therefore, equaon [18] s equvalen o Under he esable assumpon ha [ ] E φ =. [19] 1 E[ m ] I Var, =. [20] and are muually uncorrelaed, equaon [20] s an approprae absolue measure of he poron of he prce dscovery arbuable o he radng acvy a marke. Bu e can also measure he nformaveness of he marke s radng process as s conrbuon o all he nformaon rade-relaed and radeunrelaed se avalable for he revson of he epecaon abou he rue value of he sock, I j j E[ m ] mlar measures can be defned for he rade-unrelaed shocks. IV.B. Emprcal measure Var =. [21] Var m As Hasbrouck 1995 remarks, every VECM has an assocaed common rend model represenaon mpled by he conegraon relaonshps. o, he emprcal approaches n Harrs e al and Hasbrouck 1995 are equvalen see Tse, In our case, he emprcal specfcaon [17], has he follong vecor movng average VMA represenaon, h ξ ' = y = Ψ ξ, [22] Ψ beng a lag polynomal, y ' [ q q ] [ ] = and. Follong Hasbrouck 1995, consder he o frs equaons n [22],.e. he equaons ha correspond o he changes n he quoe mdpon of he U.. and pansh echanges, q = ψ ξ, here q ' = [ q q ] and ψ represen he o frs fles n he mar Ψ. By recursve subsuon, 13

14 q = ψ, [23] τ = 1 ξ τ and usng ha ψ = ψ1 + 1 ψ *, h obaned ha, * 1 ψ = ψ ψ11 s q = ψ1 ξ τ = 1 * + ψ ξ τ, [24] here he frs erm on he rgh hand sde RH of [24] s he long-run permanen componen, common o boh quoes because of he heorecal conegraon relaonshp beeen he U.. and he E quoes. The second erm on he RH of [24], * ψ ξ, s a zero-mean eakly saonary ransory componen. The conegraon relaonshp beeen he quoes enals ha δ ' Ψ1 = 0, here δ ' = s he heorecal conegraon vecor. Ths conegraon srucure mples ha ψ 1 1 = ψ2 1 = ψ14, h ψ k 1 represenng he k-h fle n Ψ 1. Inuvely, he esence of a common long-run componen mples ha he long-run mpac of a ne shock on eher he U.. or he pansh marke should have he same permanen mpac on boh quoes. I follos ha ψξ measure he mpac of a shock on he nformaonally effcen prce. Therefore, f Var ξ = Ω44, he long-run varance ll be gven by Var m =ψω ψ'. [25] Our am s o denfy he par of hs oal long-run varance ha s eplaned by each marke s nformaon. Gven he hypohess of no correlaon beeen he nnovaons n he radng acvy, and h he common nformave shocks,, a proper measure of [23], he nformaon share arbuable o he marke s radng acvy, ould be 2 2 here Var E[ ] =ψ σ m and 2 2 ψ σ I =, [26] ψω ψ' ψ s he -h componen of he ro vecor ψ. The numeraor of [21] s he varance of he mpulse-response funcon of model [22] afer a 14

15 rade-relaed shock. If he nnovaons n ' [ ] ξ = are correlaed, he covarance erms n Ω could be arbued o any shock. In hs paper e follo he Hasbrouck suggeson of consrucng upper and loer bounds for he nformaon shares. In order o do ha, e orhogonalze he resdual varance-covarance mar usng he Cholesky facorzaon and roae he orderng of he varables o mamze and mnmze he eplanaory poer of each parcular shock see Hasbrouck, 1995 and These bounds ll be gher as he correlaon beeen he nnovaons approaches zero. V. Daa A. Daabases U.. daa s obaned from he TAQ Trade and Quoe daabase correspondng o he year We consder consoldaed rades and quoes, ha s, all rades and quoes from he prmary E, NAD and regonal markes. All quoe and rade regsers prevous o he openng quoe are dropped. Trades no codfed as regula dscarded. Trades performed a he same marke, a he same prce, and h he same me samp are reaed as jus one rade. Quoes h bd-ask spreads loer han or equal o zero or quoed deph equal o zero have also been elmnaed. U.. rades are classfed as buyer or seller naed rades usng he ee and Ready s 1991 algorhm. When rades and quoes mus be consdered ogeher, he so-called fve seconds rule has been appled. Ths rule assgns o each rade he frs quoe samped a leas fve seconds before he rade self see ee and Ready, The pansh daa s suppled by ocedad de Bolsas B. Ths organzaon as esablshed by he four pansh ock Echanges Madrd, Barcelona, Blbao and Valenca and s responsble for he echncal managemen of he compuerzed radng sysem ha operaes a a naonal level, he pansh ock Echange Inerconnecon ysem IBE. The IBE s an elecronc order-drven marke smlar o hose of he Pars Bourse and he Torono ock Echange, here he mos lqud pansh socks rade. Drang n a leadng-edge echnology, he IBE enables large radng volumes o be handled effcenly and ransparenly. The IBE also provdes real me nformaon and mmedae dssemnaon of radng daa. nce 17 January 2000, IBE operaes n connuous radng beeen 9:00 a.m. o 5:30 p.m. pansh me T h an aucon beeen 8:30 a.m. and 9:00 a.m. ha deermnes he openng prce of he connuous 15

16 sesson. Hence, here s a o-hour overlappng nerval see Fgure 1 beeen he E and E sessons from 15:30 o 17:30 T 9:30-11:30 a.m. Ne York me T. 9 FIGURE 1 The overlappng radng nerval Ne York me 3:00 9:30 11:30 16:00 E open E open E close E close pansh me 9:00 15:30 17:30 22:00 E open E open E close E close As n he TAQ daabase, he pansh daabase ncludes rade and quoe fles. The quoe fle provdes all he adjusmens of he fve bes quoes a he bd and offer sde of he elecronc lm order book, me samped a he neares second. Addonally, he quoe fle ncludes he quoed deph a each of he en quoed prces and he number of orders regsered a each level. The rade fle ncludes nformaon abou all rades eecued, agan, me samped o a he neares second. ome saff members of he B confrmed us ha, due o boh he elecronc neork ha manages radng and he real me dssemnaon of all he nformaon, here are no lags beeen he reporng me of he updaed quoes and he ransacons ha rggered hem. Therefore, he rades are classfed as buyer or seller-naed, dependng on he naor of he rade see Odders-Whe, ocks a he E are quoed n euros and he ck s based on he share prce: 0.01 for prces of less han 50 and 0.05 for prces of more han 50. We ll ransform he E quoes no U$ applyng he correspondng nra-daly echange rae seres provded by Reuers. Ths me seres has a 1-mnue resoluon and conans he las echange rae quoed each mnue. The sample consss of 5 pansh socks raded a he E as Amercan Deposary Receps: Telefónca TEF, a elephone servce provder; Banco Blbao Vzcaya Argenara BBV and Banco anander Cenral Hspano TD, o fnancal groups; Repsol YPF REP, an ol, gas and chemcal company; and Endesa EE, an elecrcy generaor. Henceforh, e ll denoe he socks by s cker symbol. All fve socks are permanenly among he 35 mos lqud socks n he E. They embody a very mporan par of he oal radng acvy of he pansh marke. The fve socks ere admed o 16

17 rade a he E before 1990 and an mporan par of her 2000 revenues come from her busness acvy a Amerca BBV 47.16%, EE 32.68%, REP 28%, TD 58.58% and TEF 50% appromaely. The E, as he home marke, s epeced o conrbue subsanally o prce dscovery. Hoever, gven he mporance of he prevous fgures abou he Amercan acvy of he dually lsed pansh secures and he domnance of U.. sock echanges as leadng ndcaors for he oher echanges around he orld, e also epec he E o sgnfcanly conrbue o prce dscovery. The ssue o dscern s heher he E nformaon comes from s radng acvy or from publc sgnals frs dssemnaed n he U quoes. Table I shos he percenage of volume raded and of rades eecued durng he overlappng nerval a each sock echange. If E and E rades are equally nformave e ould epec he nformaon shares correspondng o he radng acvy n each marke o be close o he percenages shon n ha able. Table I repors mporan dfferences beeen TEF and he remanng socks. [Table I] B. Varables Table II provdes addonal nformaon abou he radng acvy a he E of he fve pansh cross-lsed socks. The overlappng perod 9:30-11:30 T s dvded no equally spaced me nervals from 1 o 5 mnues. Panel A B shos he percenage h a leas one ne quoe rade regser a he TAQ daabase. BBV s an nfrequenly raded sock a he E; TEF can be consdered as frequenly raded; he remanng socks are nermedae cases. [Table II] Gven he mporan dfferences n he E radng nensy beeen he fve pansh ADRs, e consruc he me seres for he prevous fve clock-me perodces. Hence, e esmae fve emprcal models [18] for each of he fve socks. A change n quoes s compued as he dfference beeen he logarhm of he quoe mdpon a he end and a he begnnng of each me nerval. The radng process s represened eher by he ne volume NV ransferred or by he ne number of rades NT eecued durng each nerval. The NV s defned as he dfference beeen he buyer-naed volume and he seller-naed volume a he nerval. In hs case s compued as, 17

18 z = sgn ln vk [27] k= 1 here NV v k = z k= 1 and sgn equals 1 f NV >0 and 1 f NV <0. The NT s defned as he dfference beeen he number of buyer-naed rades and he number of seller-naed rades, and s compued analogously o [27]. Jones, Kaul and pson 1994 sugges ha s he occurrence of ransacons per se and no he volume raded ha generaes volaly. Therefore, he ne volume could no have nformaon beyond ha conaned n he number of rades of he same sgn. Hence, e have esmaed [17] usng hese o alernave radng acvy measures. Dfferences n he nformaon shares obaned h each specfcaon ll help o dscern heher he volume raded or he radng frequency are more mporan for he prce dscovery process of he se of cross-lsed socks. C. Order of negraon and conegraon. In order o proceed h he esmaon of he emprcal model [18] s necessary o confrm ha 1 he vecor of dependen varables q, q,, s saonary and 2 he E and he E quoes are conegraed and h conegrang vecor 1,-1. We employ he augmened Dckey-Fuller 1979 and he Phllps-Perron 1988 procedures o deermne he order of negraon of he me seres of he log of he quoe mdpon n levels, he NV measure n [27] and he analog measure for he NT. In general, for all socks and for all clock-me nervals e canno rejec he null hypoheses of a un roo for he quoe seres and e canno accep for all he rade seres. Regardng conegraon, usng boh he Engle and Granger 1987 and he Johansen 1988, 1991 mehodologes, e oban ha he E and he E quoes are conegraed for all socks and radng nervals, and he normalzed conegrang vecor s, as epeced, 1,- 1. These resuls are no repored because of space lmaon bu hey are avalable upon reques. VI. Esmaon resuls Ths secon summarzes he esmaon of he VECM [17] for he fve pansh crosslsed socks. The approprae lag lengh of he emprcal model has been deermned usng he charz Bayesan Creron BC. 10 For all socks, radng proes, and me nervals, he mamum number of lags has been 6. No overngh reurns have been 18

19 consdered and no lags reached back o he prevous day. If, for eample, he opmal number of lags s four, he dependen vecor begns h he ffh observaon each overlappng nerval. Table III repors he esmaed model for TEF h he 1-mnue me seres. Panel A shos he esmaed coeffcens hen he ransformaon [27] of he NT s employed o proy for radng acvy. The lag lengh s 3. Panel B conans he esmaed coeffcens hen he ransformaon [27] of he NV s used o proy for radng acvy. The lag lengh s 4. Boh panels also repor he resdual correlaon mar and he Breusch and Pagan 1980 ch-square es for ndependence. The model s esmaed by URE usng he FG algorhm e.g., Green, 1997, pg In general, he esmaon resuls are conssen across socks and he man fndngs derved are ndependen of he clock-me nerval and he radng proy used. Hence, he follong commens refer no only o Table III bu also o he oher socks n he sample, all he me nervals consdered, and he o radng proes. Remarkable dfferences ll be eplcly menoned. [Table III] A frs relevan fndng s ha he error correcon erm ECT n he o quoe equaons s sascally sgnfcan for all socks and specfcaons, and he sgn of he coeffcen s he epeced one. If here s a movemen n eher he E or he E aay from he long-run equlbrum n a gven perod, a proporon of he dsequlbrum s correced he ne perod. Thus, f he ECT q q 0 he ne perod 1 1 > q ll decrease and q ll ncrease, recfyng a leas parally he devaon beeen boh markes. As he E quoes also respond o devaons from he E quoes, hs resul evdences ha he prce dscovery process s no compleely drven by he pansh marke. Anoher conssen resul across socks s ha he magnude of he coeffcen assocaed o he ECT of he equaon α s alays smaller n absolue erms han he q coeffcen assocaed o he ECT of he equaon α q. ascal ess performed over he esmaed coeffcens of [17] confrm ha α > α canno be rejeced a he 1% level. Ths resul provdes addonal nsghs no he error correcon process, suggesng ha he reacon of he E o he prce dfferenals s faser and larger han ha of he E. 19

20 Eamnng he coeffcens of he lagged values of q and q on he quoe equaons e observe, on he one hand, a sgnfcan negave auocorrelaon n quoes. Ths fndng could evdence a correcon process ha sars afer an unnformave or ransory change of he quoes posed n a gven marke. On he oher hand, here s a sgnfcan posve effec of he lagged q values on he q equaon, reflecng comovemens of boh quoes leaded by he E. The oppose relaonshp s also rue for TEF for all me nervals: he lagged values of Hoever, sascal ess confrm ha o changes n he lagged values of effec of lagged q on > φ, φ j q, j also affec posvely o, ha s, q q. s more sensve q han he oher ay around. For he oher socks he q s no usually sgnfcan. The radng acvy has an srong posve effec on quoes, ndependenly of he proy used. Table III evdences ha an ncrease n he NV or n NT eher a he E or a he E produces an upard adjusmen of boh quoes. Ths fndng s very mporan because ndcaes ha he radng acvy a he E provdes some nformaon o boh markes, even hen he radng acvy a he E has been aken no accoun. For he oher socks n he sample e oban conssen resuls, alhough he sgnfcance of he effec of he radng acvy a he E on q depends on he me nerval consdered. From he rade equaons e repor an epeced and an unepeced fndng. On he one hand, he epeced resul s a srong posve auocorrelaon n ndependenly of he proy used, eher NV or NT. Ths fndng s conssen h Hasbrouck s 1991a fndngs ha buyer-naed rades end o be folloed by addonal buyer-naed rades. Addonally, e fnd evdence of clusers of sgned radng acvy beeen he E and he E, generally leaded by he pansh marke. Thus, posve lagged values of more buyer-naed han seller-naed radng are assocaed h poseror posve values n. Ths resul suggess radng ransmsson beeen markes. For he mos frequenly raded socks a he E TEF and REP e also found evdence of radng ransmsson from he E o he E. On he oher hand, posve lagged values of q ncrease, ={, }. Tha s, afer a perod here he value of he sock a he E has ncreased, boh markes epermen a larger pressure o buy. Hoever, and hs s he unepeced fndng, for he E e oban he oppose effec. agged posve values of 20

21 ncrease he pressure n he E o sell decreases. Ths relaonshp s no q observed for he E radng acvy. Hence, our eplanaon s ha hs resul capures he margnal effec of nvenory conrol by he specals a he E. Perods of nense demand > 0 are lnked o ncreases n he value of he sock q > 0, as e have observed before. Durng hese perods, he E specals ll be forced o provde lqudy n order o manan sable marke condons. Ths s especally rue for nfrequenly rade socks see Madhavan and ofanos, 1998, and Kavajezc, 1999 and non-u socks see Bacdore and ofanos, As a consequence he specals could be forced o hold an undesred negave nvenory poson n he cross-lsed sock. Durng he ne perod, he specals ll ry o movae raders o nroduce marke orders o sell n order o resae her preferred nvenory poson. Ths s also conssen h he negave auocorrelaon of q prevously commened. In general, he esmaon resuls sugges ha he E leads he prce dscovery process of he pansh cross-lsed socks, bu he role of he E s no merely o be a saelle of he pansh marke. The relevan queson s o deermne heher he E conrbuon o prce dscovery s due o her radng acvy or o rade-unrelaed shocks frs ncorporaed o he E quoes. Ths s he am of he ne secon. VII. Informaon shares Table III repors he resdual correlaon mar for he VECM [17] esmaed usng TEF daa and h a 1-mnue resoluon. As e assumed n he heorecal scenaros n secon II, rade-relaed and rade-unrelaed noses are uncorrelaed. Ths resul s conssen across socks and across me nervals. Addonally, and are sgnfcanly correlaed and, of course, hs correlaon ncreases h me aggregaon. mlarly, and are also sgnfcanly correlaed, suggesng common shocks n he radng process. Ths correlaon also ncreases bu less h me aggregaon. 11 Therefore, e epec he nformaon share bounds descrbed n secon IV o be gher as e decrease me aggregaon. The resdual correlaon marces repored also ndcae ha he scenaro h nosy rade-unrelaed shocks descrbed n secon II beer characerzes he underlyng prce dscovery process. The smulaneous rade-unrelaed shocks are no perfecly correlaed, suggesng ha boh markes dffer n her ably o judge nosy 21

22 publc dsclosures. Ths secon ll also dscern hch marke usually makes he more accurae assessmens. A pror sep needed o proceed h he compuaon of he nformaon shares s o oban he VMA represenaon of he VECM n [17]. Hasbrouck 1995 uses smulaon mehods o derve he VMA represenaon of hs emprcal model. We derve drecly from he esmaed VECM e.g., Wason, The changes n he U$/ echange rae mgh cause some dsorons n he compuaon of he nformaonal shares. Hoever, berman e al conclude ha he correlaon beeen he changes n quoes and he echange raes s neglgble. Moreover, Grammg e al measure he nformaonal share arbuable o shocks n he echange rae, modeled as a random alk process. Ther fndngs sugges ha he echange rae s no a sgnfcan deermnan n prce dscovery. o, e assume ha he possble bases nduced by shocks n he echange rae are also rrelevan. Table IV conans he loer and upper bounds of he nformaonal shares esmaed for he fve cross-lsed socks hence, he values n a gven ro do no sum o 100%. The able repors he nformaon shares for all models esmaed: for he fve clock me resoluons 1 o 5 mnues and for he o possble rade ndcaors NT and VT h he ransformaon n 27. [Table IV] Table IV evdences ha he E s, as e epeced, he leadng marke n he prce dscovery process of he fve pansh cross-lsed socks. The nformaon shares for he E rade-unrelaed nformaonal shocks are beeen 70% and 90% dependng on he sock and he clock me resoluon. Bu Table IV also ndcaes ha he conrbuon of he E s no neglgble. The E rade-unrelaed nformaonal shocks accoun for 1% TEF, TD, BBV o 3% REP, EE of he varance of he effcen prce. Ths nformaonal share s he mos varable across socks. I s also very sensve o me aggregaon for BBV, he less frequenly raded pansh cross-lsed sock a he E see Table II. In he scenaro presened n secon II, hese nformaon shares mply ha he E generally does more precse judgmens abou he nformaon conen of publc sgnals and dssemnaes hs nformaon qucker han he E. Hoever, for some nes, probably nes ha concern he busness acvy of he pansh socks a Amerca or he Amercan economy n general, he E seem o have an advanage over he EE. 22

23 The rade-relaed nformaonal shares sho a compleely dfferen pcure. On he one hand, he E rade-relaed shocks eplan beeen 10% and 20% of he long-erm varance of he pansh cross-lsed socks, agan dependng on he sock and he clock me resoluon. An neresng resul s ha he nformaonal share of s larger hen he NV measure s used o proy for radng acvy. These dfferences sugges ha he volume ransferred a he E s more nformave for he prce dscovery process of he pansh cross-lsed socks han he occurrence of rades per se. Ths fndng conrass h Jones, Kaul and pson 1994 conclusons. On he oher hand, he nformaon share for he E rade-relaed shocks Addonally, he Panel B of Table IV ndcaes ha he s less han 0.5% n almos all he cases. hen e use he NT proy s no ganed by he E rade-relaed shocks. s nformaon share ha s los A more accurae assessmen of he E radng acvy s conrbuon durng he overlappng perod ould be o compare he relave rade-relaed nformaonal shares h he radng shares n Table I. The relave rade-relaed nformaonal shares are compued as he nformaon share of he marke s radng acvy over he sum of all he nformaon shares arbued o radng acvy. The resuls hen he volume n shares s used as a proy for radng acvy are very conclusve: he number of shares ransaced a he E s no nformave. For eample, 23% of he TEF raded volume akes place a he E. Hoever, he correspondng relave rade-relaed nformaonal share usng loer bounds s only he 1-2%. mlarly, for REP he E volume sh and he relave rade-relaed nformaonal share s beeen 1-3%. If e consder he number of rades as he appropraed source of nformaon resuls are no so conclusve. For TEF and EE he rade shares 5.93% and 4.17% respecvely are usually nferor o he correspondng relave rade-relaed nformaonal shares for all me resoluons % and 6.06%-9.73% respecvely. Ths resul provdes eak evdence ha, for he E, s he occurrence of ransacons per se and no he volume raded ha conrbues o he prce dscovery of he pansh cross-lsed socks. Ths resul seems reasonable: n he marke h he hghes radng frequency, he volume raded s ha provdes ne nformaon. Bu n he marke h he loes radng frequency, he nformaon s nferred from unusual shor duraons e.g., Easley and O Hara, 1992 beeen rades. 23

24 VII. Conclusons Ths paper has suded he role played by he E n he prce dscovery process of four pansh cross-lsed socks raded as ADR s n he U marke. Our mehodologcal conrbuon resdes n dsngushng beeen o alernave sources of nformaon asymmeres: rade-relaed shocks and nosy publc dsclosures. The sudy ceners on he daly overlappng radng nerval beeen boh he E and he E. Our man concluson s ha he E canno be characerzed as a pure saelle marke of he E. Boh E and he E reac o any devaon beeen her quoes. Ths ndcaes ha e are facng a o-ay prce dscovery process. Moreover, e conclude ha he E conrbuon o prce dscovery s manly due o rade-unrelaed shocks ha are earles dssemnaed a he U marke han a he E. The nformaon shares of boh markes confrm ha he E leads he prce dscovery process of he pansh cross-lsed socks. The nformaon share due o publc announcemens frs dssemnaed a he E s, hoever, remarkable. I vares beeen he 1% and he 3% dependng on he sock and he radng proy used. On he conrary, less han he 0.5% of he long-run varance s due o E rade-relaed nformaon. For he E e evdence ha he volume raded s more nformave han he number of rades. On he conrary, for he E e fnd eak evdence ha s he occurrence of ransacons per se ha maers. 24

25 Foonoes 1. The fuure reference perod τ can be aken as he end of radng eher a he E or a he E. In he frs case e do no mpose he full convergence n epecaons a he end of he overlappng perod. If 0, h j close o zero, he specfc nformaon generaed a he U.. may no be compleely τ j ncorporaed o he E quoes a momen τ. 2. Ths s a srong assumpon because mples ha he radng acvy movaed by he announcemen does no provde any addonal nformaon. We ll see ha hs assumpon s no srcly necessary, bu s adoped for smplcy of eposon and s esed n he emprcal secons. 3. An alernave specfcaon ould be o assume ha he publc announcemen provdes each marke h a dfferen sgnal, for eample ~ δ. In hs case, a marke may be provded h an nferor sgnal han he oher. = + 4. Emprcally, he homokedasc characerzaon of he ransory componen s no srcly necessary for our purposes, bu s assumed o smplfy he eposon. 5. The E rules sae ha he specals should manan a far and orderly marke. Ths ncludes he responsbly of sablzng prces n her assgned socks. The specals ensures ha radng n he socks moves smoohly hroughou he day e.g. Hasbrouck e al., In he E here s no specals or fgure alke. Hoever, he esence of hdden orders and sopped orders may also delay he full revelaon of he nformaon behnd he rades. Alernavely, raders h heerogeneous prors and prvae nformaon may ake some nervals of radng o have her epecaonal dfferences resolved e.g., Kyle, 1985; Harrs and Ravv, Chang and n 1999 shos ha he esence of a mnmum prce varaon and he bd-ask bounce may nduce a bas n he esmaon of a VECM usng hgh-frequency ransacon prce daa. Hoever, he auhors also sho ha by usng quoe mdpons hs bas n consderably reduced. 7. Hasbrouck 1995 poned ou ha he nformaon shares depend on he orderng of he varables n he Cholesky facorzaon of he resdual covarance mar. The frs las varable n he orderng ll end o have a hgher loer nformaon share. The dscrepancy could be large f he resduals across markes are hghly conemporaneously correlaed. 8. Recenly, o conemporaneous sudes, Ells e al and Odders-Whe 2000, have compared alernave classfcaon rules. On he one hand, Ells e al. and Odders-Whe have found ha he ee and Ready s algorhm ouperform oher classfcaon rounes lke he quoe rule and he ck rule. Hoever, boh papers found ha he algorhm msclassfes ransacons eecued nsde he quoes. Ells e al. propose o apply he ck-rule no only o he mdpon rades, as n ee and Ready s algorhm, bu also o all he rades nsde he quoes. The auhors sho ha, for Nasdaq-lsed socks, hs procedure mproves over ean classfcaon rules. Hoever, here s no es evdencng ha hs alernave mehod mproves he classfcaon for E-lsed socks. We appled boh algorhms and dd no fnd remarkable dfferences. In any case, Odders-Whe 2000 observes ha he bases nroduced by he classfcaon rules are more relevan for large and frequenly raded socks. The pansh E-lsed socks are neher large nor frequenly raded comp ared h he larges socks lsed n he U.. marke. On he oher hand, Blume and Goldsen 1997 shoed ha he fve-seconds rule could no be generalzed o all sample perods and markes. Hoever, Odders-Whe 2000 also shos ha he fve-seconds rule does no seem o eplan much of he bas nduced by he ee and Ready s algorhm. 9. Before 17 January 2000 connuous radng as from 9:30 o 17:00 T; herefore, he overlappng radng perod h he E as jus one hour and a half. Addonally, he begnnng of he daylgh savng me n Ocober for pan and U concdes. Hoever, he end of hs daylgh savng me s he frs unday of Aprl n he U and he las unday of March n pan. Hence, durng he las eek of March, he overlappng radng perod reduces o one hour. 10. Ths creron s chosen because ends o pck up more parsmonous specfcaons and because has superor large sample properes han oher procedures, for eample he Akake nformaon creron e.g., Enders, 1995, pg and For eample, he TEF resdual correlaon mar for he 5 mnue case and usng NT as he proy for radng acvy shos ha Corr, = and hen NV s used. Addonally, Corr, =0.099 and for he NT and he NV specfcaon, respecvely. 25

26 References Bacdore, Jeffrey M. and George ofanos, E specals radng n non-u socks, E Workng Paper, # Bamber, nda mh, Ore E. Barron and Thomas. ober, 1999, Dfferenal nerpreaons and radng volume, Journal of Fnancal and Quanave Analyss, 34, 3, Blume, Marshall E., and Mchael A. Goldsen, 1997, Quoes, order flo, and prce dscovery, The Journal of Fnance, 52, Breusch, T. and A. Pagan, 1980, The M es and s mplcaons o model specfcaon n economercs, Reve of Economc udes, 47, Chan, K.C., Wa-Mng Fong, Bong-Chan Kho and René ulz, 1996, Informaon, radng and sock reurns: lessons from dually lsed secures, Journal of Bankng and Fnance, Chang, Kevn C.H. and J-Cha n, 1999, Inferrng prce dscovery from frconal markes, Workng Paper, E.J. Ourso College of Busness Admnsraon, ousana ae Unversy. Chorda, Tarun, and Advandhar ubrahmanyam, 1995, Marke makng, he ck sze, and paymen-for-order flo: heory and evdence, Journal of Busness, 68, 4, Chodhry, Bhagan and Vkram Nanda, 1991, Mulmarke radng and marke lqudy, Reve of Fnancal udes, 4, 3, Dckey, D.A. and W.A. Fuller, 1979, Dsrbuon of he esmaors for auoregressve me seres h a un roo, Journal of he Amercan ascal Assocaon, Dng, D., Frederck H. deb. Harrs,.T. au and Thomas H. McInsh, 1999, An nvesgaon of prce dscovery n nformaonally-lnked markes: equy radng n Malasa and ngapore, Journal of Mulnaonal Fnancal Managemen, 9, Easley, Davd, and Maureen O Hara, 1992, Tme and he process of secury prce adjusmen, The Journal of Fnance, 47, 2, Ells, Karna, Ron Mchaely and Maureen O Hara, 2000, The accuracy of rade classfcaon rules: evdence from Nasdaq, Journal of Fnancal and Quanave Analyss, 35, 4, Enders, Waler, 1995, Appled Economerc Tme eres, Wley eres n Probably and Mahemacal ascs, John Wley and ons. Engle, Rober, and C. Granger, 1987, Co-negraon and error correcon: Represenaon, esmaon and esng, Economerca, 35, Eun, Cheol. and anjv abheral, 2000, Prce dscovery for nernaonally raded secures: evdence from he U..-lsed Canadan socks, Workng Paper, DuPree College of Managemen, Georga Tech, Alana. Foser, F. Douglas, and. Vsanahan, 1993, Varaons n radng volume, reurn volaly, and radng coss: evdence on recen prce formaon models, The Journal of Fnance, 48, Gonzalo, Jesus and C. Granger, 1995, Esmaon of common long-memory componens n conegraed sysems, Journal of Busness and Economc ascs, 13, 1-9. Grammg, Joachm, Mchael Melvn and Chrsan chlag, 2000, Prce dscovery n nernaonal equy radng, Workng Paper, CORE, Unversé Caholque de ouvan la Neuve. Green, Wllam H., 1997, Economerc Analyss, Prence-Hall, Ne Jersey. Harrs, Mlon, and Arhur Ravv, 1993, Dfferences of opnon make a horse race, The Reve of Fnancal udes, 6, Harrs, Frederck H. deb, Thomas H. McInsh, Gary. hoesmh, and Rober A. Wood, 1995, Conegraon, error correcon, and prce dscovery on nernaonally lnked secury markes, Journal of Fnancal and Quanave Analyss, 30, 4, Harrs, Frederck H. deb, Thomas H. McInsh and Rober A. Wood, 2000, The dynamcs of prce adjusmen across echanges: an nvesgaon of prce dscovery for Do socks, Workng Paper, Babcock Graduae chool of Managemen, Wake Fores Unversy. 26

27 Hasbrouck, Joel, 1991a, Measurng he nformaon conen of sock rades, The Journal of Fnance, 46, Hasbrouck, Joel, 1991b, The summary nformaveness of sock rades: An economerc analyss, The Reve of Fnancal udes, 4, Hasbrouck, Joel, 1995, One secury, many markes: deermnng he conrbuons o prce dscovery, The Journal of Fnance, 50, 4, Hasbrouck, Joel, 2000, alkng he effcen prce n marke mcrosrucure specfcaons: An overve, Workng Paper, ern chool of Busness, Ne York Unversy. Hasbrouck, Joel, 1993, Assessng he qualy of a secury marke: a ne approach o measurng ransacon coss, Reve of Fnancal udes, 6, Hasbrouck, Joel, George ofanos, and Deborah osebee, 1993, Ne York ock Echange sysems and radng procedures, E Workng Paper # Hupperes, Erk and Ber Menkveld, 2000, Inra-daly analyss of marke negraon: Duch blue chps raded n Amserdam and Ne York, Workng Paper, The Waron chool, Unversy of Pennsylvana. Johansen,., 1988, ascal analyss of conegraon vecors, Journal of Economc Dynamcs and Conrol, 12, Johansen,., 1991, Esmaon and hypohess esng of conegraon vecors n Gaussan vecor auoregressve models, Economerca, 59, Jones, Charles M., Gauam Kaul and Mark. pson, 1995, Transacons, volume, and volaly, Reve of Fnancal udes, 7, 4, Kavajecz, Kenneh A., 1999, A specals s quoed deph and he lm order book, The Journal of Fnance, 54, Km, Olver, and Rober E. Verreccha, 1994, Marke lqudy and volume around earnngs announcemens, Journal of Accounng and Economcs, 17, Kyle, Alber., 1985, Connuos aucons and nsder radng, Economerca, 53, ee, Charles M., and Mark J. Ready, 1991, Inferrng rade drecon from nraday daa, The Journal of Fnance, 46, eberman, Offer, Ur Ben-Zon and chmuel Hauser, 1999, A characerzaon of he prce behavor of nernaonal dual socks: an error correcon approach, Journal of Inernaonal Money and Fnance, 18, 2, n, J-Cha C., Gary C. anger, and G. Geoffrey Booh, 1995, Trade sze and componens of he bd-ask spread, Reve of Fnancal udes, 8, Madhavan, Ananh, and George ofanos, 1998, An emprcal analyss of E specals radng, Journal of Fnancal Economcs, 48, Odders-Whe, Elzabeh R., 2000, On he occurrence and consequences of naccurae rade classfcaon, Journal of Fnancal Markes, 3, 3, O Hara, Maureen, 1995, Marke Mcrosrucure Theory, Blackell, Cambrdge. Pascual, Robero, Alvaro Escrbano, and Mkel Tapa, 2000, Adverse elecon Coss, Tradng Acvy and qudy n he E: An Emprcal Analyss n a Dynamc Cone, Workng Paper #00-90, Unversdad Carlos III de Madrd. Phllps, P.C.B., and P. Perron, 1988, Tesng for a un roo n me seres regresson, Bomerka, 75, Pulakonak, Melek and Ge orge ofanos, 1999, The dsrbuon of global radng n E-lsed non-u socks, E Workng Paper, ubrahmanyam, Advandhar, 1997, Mul-marke radng and he nformaveness of sock rades: an emprcal nra-daly analyss, Journal of Economcs and Busness, 49, Tse, Yuman, 2000, Furher eamnaon of prce dscovery on he E and regonal echanges, The Journal of Fnancal Research, 23, 3,

28 Werner, Ingrd M., and Allan W. Kledon, 1996, U.K. and U.. radng of Brsh cross-lsed socks: An nra-daly analyss of marke negraon, Reve of Fnancal udes, 9, Zellner, Arnold, 1962, An effcen mehod of esmang eemngly Unrelaed Regressons and ess for aggregaon bas, Journal of he Amercan ascal Assocaon, 57,

29 TABE I Tradng shares durng he overlappng nerval Ths able repors he percenage of he radng acvy of he pansh cross-lsed socks durng he overlappng perod 15:30-17:30 T ha corresponds o he pansh ock Echange E and o he E. The Panel A repors he percenages of he volume raded measured n housand of shares and Panel B he percenages of he number of rades compleed. ock E E % E % E Panel A: Volume housands of shares BBV EE REP TD TEF Panel B: Number of rades BBV EE REP TD TEF TABE II Acvy durng he overlappng nerval Ths able s ndcave of he radng acvy of he pansh ADRs lsed a he E durng he overlappng radng nerval beeen he IBE and he E 9:30:00-11:30:00, Ne York me. The overlappng nerval has been dvded no equally spaced me nervals from 1 o 5 mnues. The Panel A repors he percenage of hose nervals h a leas one ne quoe regser a he TAQ daabase. The Panel B repors he percenage of hose nervals h a leas one rade regser a he TAQ daabase. ock 1 mn 2 mn 3 mn 4 mn 5 mn Panel A: Quoes BBV EE REP TD TEF Panel B: Trades BBV EE REP TD TEF

30 TABE III Esmaon of he VECM Ths able repors he esmaed coeffcens of he VECM [17] for TEF. To consruc he me seres, he overlappng radng nerval beeen he E and he E s dvded n 1-mnue nervals. For he defnon of he varables see secon VI.C n he paper. The lag lengh has been deermned usng he BC nformaon creron. Panel A shos he coeffcens of he VECM model ha uses he ransformaon [27] of he ne number of rades as he proy for radng acvy. The ne number of rades s he dfference beeen he number of buyer-naed rades and he number of seller-naed rades eecued durng he correspondng me nerval. Panel B shos he coeffcens of he VECM ha uses he ransformaon [27] of he ne volume as he proy for radng acvy. Ne volume s defned as he dfference beeen he buyer-naed volume n shares and he seller-naed volume n a gven me nerval. Boh panels also repor he resdual correlaon mar and he Breusch and Pagan 1980 ch-square es for ndependence. q Panel A: Ne number of rades ECT * * q q * * * 46.27* q * * * 32.67* q * * *** 19.04* q * * 89.29* * q * * * q * * 4.89* * * * E-06* * * * E E * E-06* 1.04E * ** * * *** * * * E * * E * * R N.Obs.: *, **, *** gnfcance a he 1%, 5% and 10% level respecvely. Correlaon mar of resduals Breusch-Pagan es: ch 2 6 = , Pr =

31 TABE III Esmaon of he VECM Con. q Panel B: Ne volume q ECT * * q * * * * q * * * q * * ** q * * * q * * * q * * * q * * * * q ** * * * * * * * * E * * * E-06* ** * ** E-06* * E-06* * E * * * E * * E * * E * R N.Obs.: *, **, *** gnfcance a he 1%, 5% and 10% level respecvely. Correlaon mar of resduals Breusch-Pagan es: ch 2 6 = , Pr =

32 TABE IV Informaon shares durng he overlappng nerval Ths able conans he esmaed nformaon shares n % for rade-relaed and rade-unrelaed shocks orgnaed a he E and he E. The nformaon share s he proporon of varance n he effcen prce of he sock ha s arbuable o a gven nnovaon, eher rade-relaed, or rade-unrelaed,. The able provdes he loer bound and he upper bounds n parenhess based on he esmaon of he VECM [17]. The able shos he resuls of he VECM esmaed h dfferen clock me resoluons 1 mnue o 5 mnues. Panel A: Ne volume n shares BBV EE REP 1m m m m m Panel B: Ne number of rades 1m m m m m

33 TABE IV Informaon shares durng he overlappng nerval Con. TD Panel A: Ne volume n shares 1m TEF m m m m Panel B: Ne number of rades 1m m m m m