Price Discovery in the Absence of Trading: A Look at the Malta Stock Exchange Pre-opening Period

Transcription

1 Price Discovery in he Absence of rading: A Look a he Mala Sock Exchange Pre-opening Period Michael Bowe Suar Hyde Ike Johnson Absrac his paper sudies he conribuion of he pre-opening period o he daily price discovery process and he facors ha impacs he reurn generaed over his period for six socks raded on he Mala Sock Exchange. We uilise boh he weighed price conribuion (WPC) mehod and he Wang and Yang (29) exension of he Hasbrouck (995) informaion share (IS) measure applicable o sequenially rading periods. We deermine he informaion conen of he order book by measuring he impac of he relaive deph and heigh in he overnigh and opening order book and changes o he relaive deph and heigh during he pre-opening aribuable o order submissions and aleraions. We find ha approximaely one hird of daily price discovery is aribuable o he preopening period. he resuls indicaes ha he impac of relaive deph and heigh of he overnigh and opening order book on opening are concenraed a he op of he order book. Furhermore, cumulaive changes o he relaive deph aribuable o order submissions during he pre-opening mos significanly impac he opening reurns of less acive socks. However, we find a srong relaionship beween opening reurns and changes in he relaive heigh along he order book aribuable o order submissions, cancellaions and forward and backward price revisions over he pre-opening period. his version: Sepember, 2 JEL codes: G4, G2, D4, C32 Keywords: price discovery, pre-opening, microsrucure, order book, Mancheser Business School, Universiy of Mancheser, Booh Sree Wes, Mancheser, M5 6PB, UK. mike.bowe@mbs.ac.uk, el: ; fax: Mancheser Business School, Universiy of Mancheser, Booh Sree Wes, Mancheser, M5 6PB, UK. suar.hyde@mbs.ac.uk, el: ; fax: Corresponding auhor. Mancheser Business School, Universiy of Mancheser, Booh Sree Wes, Mancheser, M5 6PB, UK. ike.johnson@posgrad.mbs.ac.uk.

2 . Inroducion his chaper invesigaes he informaion conen of he pre-opening order book and he period s conribuion o daily price discovery by analysing daa for six socks raded on he Mala Sock Exchange. By sudying he informaion conen of he order book in he pre-opening period, we can esablish he exen o which order submissions and aleraion o he book, in he absence of rading, conribues o he price formaion process for securiies rading on his exchange. In essence, he main focus of his chaper is wofold: firs, we measure he proporion of daily price discovery ha is aribuable o he pre-opening and rading periods. o measure he proporional price discovery, we uilise wo mehods, he former is he familiar weighed price conribuion (WPC) and he oher is he Wang and Yang (29) sequenial rading period exension of he Hasbrouck (995) informaion share (IS) measure. Second, we examine which order book characerisic play a pivoal role in deermining he conribuion o price discovery during he pre-opening. We do his by measuring he impac of he relaive heigh and deph of overnigh and opening order books, and changes herein, aribuable o order submissions and aleraions during he pre-opening period. his analysis makes several conribuions o he lieraure on marke microsrucure. o our knowledge, we are he firs o empirically assess which characerisics of he order book informaion during he pre-opening period inform he price discovery process. he previous preopening lieraure such as Vives, (995), Biais e al. (999) Medrano and Vives (2), Madhavan and Panchapagesan (2) and Barclay and Hendersho (23, 28) cusomarily focus on deermining he presence and exen of price discovery. In comparison o prior sudies ha measure he proporional conribuion of he pre-opening o he daily price discovery such as Cao e al. (2) and Barclay and Hendersho (23, 28), we measure and compare he wo main price discovery measures uilised in he lieraure. In addiion, his analysis examines he conribuion of specific elemens of order book informaion and raders order submission sraegy in deermining opening reurns. herefore, no only do we measure he proporion of price discovery ha is aribuable o he pre-opening period bu we also idenify he facors ha impac he reurn generaed over his period. he remainder of he chaper is organised as follows. Secion 2 provides a descripion of he daa used in empirical analysis, where in secion 3 we ouline he mehodology and discuss he 2

3 resuls of our findings relaive o he conribuion of he pre-opening o he daily price discovery process. In secion 4, we develop esable hypoheses, ouline he mehodology employed and presen resuls for he impac of specific order book variables on he reurn generaed over he pre-opening. he conclusions are presened in secion Daa he empirical analyses conduced in his chaper uilize a unique microsrucure daa base obained from he Mala Sock Exchange (MSE). he MSE is a fully elecronic coninuous limi order marke, wih no designaed marke makers providing liquidiy. he sample uilised in his sudy comprises ick-by-ick daa over he period January 2 o June 27. he daa se conains all informaion abou each even ha occurs such as order submissions, revisions or cancellaions, heir associaed price and volume, order idenificaion aribues and any oher submission rule relaing o orders queued in he order book. Hence, by applying he rules governing he order book, we are able o replicae he sae of he order book a every momen in ime. Normal rading a he MSE begins a : am and he rading day comes o an end a 2:3 pm. Preceding he iniiaion of rading is he marke pre-opening period which for he majoriy of he sample begins a 8:3 am and ends a : am. I is he pre-opening period which is he main focus of his empirical analysis. hroughou he pre-opening period, raders submi limi orders ha queue o form he preopening limi order book. A he end of he pre-opening he opening algorihm execues suiable orders. he order book a he end of he pre-opening period, jus prior o execuion of he opening algorihm, is ermed he opening order book. Prior o he execuion of he opening algorihm, raders have he opion o cancel or revise any pending limi orders wihou cos or obligaion. Essenially, he MSE pre-opening period is similar o a single price call aucion process where he marke clearing price is deermined by he opening algorihm. 2 For his analysis, we selec he six MSE socks which over he sample period were he mos acive during he pre-opening. hese correspond o he shares of HBSC Bank Mala plc (HSB), As of 23 Ocober 26, he preopening period changed o 9:3 am o :45 am wih he coninuous open from :45am o 2:3pm. his has been accouned for in our esimaion. 2 See chaper 2 for a more in-deph descripion of he insiuional deails ha governs he MSE. 3

4 Bank of Vallea plc (BOV), Malacom plc (MLC), Middlesea Insurance plc (MSI), Mala Inernaional Airpor plc (MIA) and he Inernaional Hoel Invesmen plc (IHI). We caegorise hese socks ino wo groups. Firs, he hree mos acive socks, ha include BOV, MLC and HSB are caegorised as A socks. Second, he hree remaining less acive socks, which are MSI, MIA and IHI are caegorised as B socks. In effec, hese wo caegories are formulaed o enable us o make a disincion beween he characerisics of mos acive and less acive socks rading on he MSE. able provides a summary of he order book aciviy, including submissions, forward and backward price revisions, and cancellaions for he six socks uilized. 3. Price Discovery 3. Conribuion of Pre-opening o Daily Price Discovery he exen of price discovery which occurs hroughou he marke pre-opening period is he subjec of debae in several heoreical and empirical sudies in marke microsrucure research. he pre-opening is characerised by an absence of rading and he queuing of non-binding orders ha awai execuion a he opening, hereby poenially creaing an environmen for aggregaing informaion and significanly reduced adverse selecion risks (see Madhavan, 992; Economides and Schwarz, 995; Domowiz and Madhavan, 2). I is hese facors ha disinguishes he pre-opening from he coninuous rading period, and highligh is imporance as a feaure o provide price discovery afer a hal in rading. heoreical models of he pre-opening âonnemen process conclude ha pre-opening prices end o converge o heir fundamenal value, alhough such convergence is noisy in models which incorporae manipulaion or specialis inervenion. Vives (995) concludes ha in he presence of informed and uninformed raders boh submiing orders during he pre-opening, prices converge o heir fundamenal value a a rae proporional o he square roo of ime. Following he incorporaion of manipulaive behaviour by informed raders, boh Medrano and Vives (2) and Bursco e al. (23) show ha while prices converges o fundamenals, hey are noisy around his value, a feaure aribuable o he added noise ha manipulaive behaviour induces ino he learning process. Wihin he framework of a quoe driven marke wih a specialis faciliaing he rading process, Madhavan and Panchapagesan (2) demonsraes 4

5 ha invenory and price sabiliy consideraions lead o pre-opening prices being noisy around he fundamenal value of he asse. hese models (Vives, 995; Medrano and Vives, 2; Bursco e al., 23; and Madhavan and Panchapagesan, 2) aribue price discovery o he process of learning undergone by raders paricipaing in he pre-opening. hrough observing he pre-opening order flow and he coninuous updaing of opening prices, raders are claimed o formulae inferences abou he fundamenal value of he asse. Biais e al. (999) empirically assess he pre-opening order flow o specifically ascerain he presence of learning in ligh of he non-binding naure of pre-opening orders. hey conclude ha he pre-opening order flow is indeed informaive and learning occurs only owards he end of he pre-opening period. Since he claim is ha pre-opening period faciliaes price discovery afer a (weekend or overnigh) hal in he rading process, he obvious quesion is; wha is he relaive conribuion of he pre-opening o he overall process of price discovery hrough an enire rading day, considering ha orders are non-binding and no rade execuion occurs in his period? Several sudies, including Cao e al. (2), Barclay and Hendersho (23, 28) and Ellul, Shin and onks (25) among ohers, measure he proporion of price discovery over he rading day ha is aribuable o he pre-opening period by implemening he Weighed Price Conribuion Mehod (WPC), inroduced by Barclay and Warner (993). Barclay and Hendersho (23) aribue he occurrence of approximaely 6% of overall price discovery for seleced socks rading on he NASDAQ o he pre-opening period, and his period accouns for approximaely 74% of close-o-open price discovery. Cao e al. (2), in a similar view, concludes ha price discovery per uni of ime during he pre-opening is he same as ha which occurs during he NASDAQ rading day. In addiion, Barclay and Hendersho (28) conclude ha he proporion of daily price discovery ha occurs a he NASDAQ opening reduced from.8% o.8% over he period 993 o 999 for he sample of socks sudied. Essenially, he auhors find ha he reducion in price discovery a he opening of he marke is aribuable o he pre-opening conribuing more o daily price discovery. he auhors find ha he increased rading on off-exchange ECNs, which operaes concurren wih he NASDAQ pre-opening, conribued significanly o improving price discovery during his period. 5

6 he WPC mehodology is widely used as i provides fairly non-cumbersome mehod for quanifying price discovery occurring in designaed periods wihin a rading day, or for socks raded in separae locaions. However, Wang and Yang (2) argue ha he WPC measure is highly sensiive o serial correlaion in reurns. hey propose an alernaive measure of price discovery based on he Informaion Share (IS) measure developed by Hasbrouck (995). Specifically, Wang and Yang (2) mainain ha he WPC measures proporional weighed reurns over a period only if he variance of reurns is small relaive o he mean reurn. Moreover, hey show ha he WPC is a funcion of mean reurns and reurn serial correlaions. 3 hey argue ha he IS more accuraely measures prices discovery aribuable o sequenial periods wihin he rading day, since he IS capures variaions in he efficien price of an asse raded on an exchange. In his secion, hree basic quesions are answered. () Wha is he relaive conribuion of he pre-opening period o price discovery; (2) how has his relaive conribuion changed over ime and (3) how does he level of order book aciviy during he pre-opening period influence he pre-opening s conribuion o he daily price discovery process for a paricular sock? o empirically assess hese quesions, we uilise boh he WPC and he IS measure proposed by Wang and Yang (2) enabling us o compare he resuls from hese wo measures of price discovery. 3.2 Mehodology 3.2. Informaion Share he price discovery lieraure employs wo dominan o measure he exen of price discovery in he efficien prices for asses rading in differen markes and/or rading venues. Hasbrouck (995) proposes an Informaion Share (IS) mehod ha measures he respecive conribuion of each marke o he deerminaion of he efficien price of an asse raded simulaneously in several separae locaions. he oher mehod includes models developed in he spiri of Gonzalo and Granger (995), which use coefficien raios o measure he conribuion of each marke o he efficien price. Sudies uilising his coefficien measure o esimae price discovery include: 3 See Wang and Yang (2) for a comprehensive proof of hese claims. 6

7 Booh, So and se (999), Chu, Hsieh and se (999) and Harris, McInish and Woods (22). 4 However, Yan and Zio (2) formulaes a srucural coinegraion model which confirms ha while boh mehods idenify changes in efficien prices, only he IS provide informaion on he relaive informaiveness of differen markes in relaion o he price discovery process. An imporan poin o noe is ha he above family of models boh rely on he premise ha he asse rades simulaneously in parallel markes, which resuls in he price in each locaion being parly driven by he no-arbirage argumen. Essenially, hese models hen uilise a coinegraed VAR framework o model he ineracion of hese prices over ime. Consequenly, hese price discovery measures are no direcly applicable in measuring he relaive conribuion of sequenial ime periods wihin a rading day o he overall daily price discovery process. o measure he proporion of price discovery over he rading day aribuable he pre-opening period, we implemen a srucural VAR model in he spiri of Hasbrouck (995), formulaed by Wang and Yang (29, 2) ha measures he conribuion of sequenial markes (or ime periods) o he efficien price of an asse wihin a separae ime period. 5 o illusrae, le p i, and r i, denoe he log price and reurn for period i, respecively, on day for a specific asse. Period i can be furher sub-divided ino n sequenial rading periods. Denoe he daily reurn from close of rade on day -o day as r = r = pn, pn,. Assuming reurns wihin he i h period are subjec o period specific shocks n i= i, η i, ha are serially uncorrelaed I follows ha only he componen of he shock relaed o he fundamenal changes in he asses value will ener he efficien price. herefore, he price a he end of period i can be wrien as p i, mi, + ui, =, where m i, is he unobservable efficien price ha reflecs informaion on he fundamenal value of he asse and u i, is a error erm reflecing ransiory facors. he change in he efficien price from one period o he nex is Δ for i =,...,n. m i, = mi, mi, he changes are serially uncorrelaed and capure he permanen facors in he period specific 4 Sudies ha employ boh mehods includes Chakravary, Gulen, and Mayhew (24) and Covrig, Ding and Low (24). 5 Wang and Yang (29) measure he conribuion of four non-overlapping foreign exchange markes o price discovery in four currency pairs, and Wang and Yang (2) measure he relaive conribuion overnigh and dayime periods o he close-o-close price discovery process. 7

8 shocks η. In he spiri of Hasbrouck (995), ( ) i, Var Δ m i, denoes he informaion flow in period i. Hence, if he change in he efficien price over day is informaion share (IS) of period i on day is defined as n Δm = = Δm i i,, hen he IS i ( Δm ) Var, = Var i ( Δm ) for i =,...,n () Denoe p o, and p c, as he log opening price generaed by he opening algorihm a he end of he pre-opening, and log closing price on day respecively. hus, he close-o-open (opening) and open-o-close reurn are r, = po, pc, and r 2, = pc, po,, respecively. he vecor of reurns is defined as R = r, r )'. 6 Providing reurns are saionary, he vecor R can be (, 2, modelled using a srucural VAR process as follows: Β K R = a + Β k R k + η (2) k = where η = η, η )' is he vecor of serially uncorrelaed srucural shocks ha are specific o (, 2, he pre-opening and he rading periods respecively. In addiion, E( η ) =, E( η η ') = for k and E( η η ') = I, where I is he ideniy marix. Due o he sequenial naure of he preopening and he rading periods wihin one rading day, he close-o-open reurns k r, impacs he open-o-close reurn marix as follows: r 2, bu no vice versa. As a consequence, Β will be a lower riangular Β b = b 2 b 22 (3) he reduced form of he srucural VAR in (2) is, herefore: Ψ ( L) = α + ε (4) R 6 he close-o-close reurn is he sum of boh reurns. 8

9 where Ψ... ( L) = Ι Ψ L Ψ L K k, Ψk = Β Β k, α = Β a and he reduced form errors relaes o he srucural shocks by ε = Β η. herefore, ε, is proporional o η, and ε 2, is a linear combinaion of η, and η 2,. he covariance marix is given by, Ω = E( ε, ε s ) = Β ( Β ). Since Β is a lower riangular marix and Ω is symmeric, he VAR can be esimaed using OLS and Ω can be esimaed using he lower riangular Cholesky facor of he OLS esimaed variance marix of ε Esimaing he Informaion Share From he reduced form VAR in equaion (4) he moving average represenaion based on he Beverage-Nelson (98) decomposiion is as follows: R = μ + Ψ() ε + Ψ ( L) ε (5) where μ () = Ψ α, Ψ ( ) = Ι Ψ... ΨK, Ψ ( ) = Ψ = L, ( L) ( ε ) ~ I () j j j L Ψ and Ψ j converges o zero as j increases. he marix Ψ () capures he cumulaive impac of he reduced form innovaions ( ε ) on he reurns. o derive an expression for he unobservable efficien prices m i,, Wang and Yang (29) conend ha he change in he log price a he end of day is he accumulaion of each period s reurn, such ha: p c, = p + Ψ( ) ε i + uc, = p + ι Ψ() Β ηi + uc, i= i= ι (6) where p is he iniial price a =, u c, = ι Ψ ( L)( ε ) = ι Ψ = j ε j and ι is a vecor of ones. Eviden here is ha equaion (6) is similar o he Sock and Wason (988) common rend represenaion. hus, he price a he end of day consiss of he full informaion value of he asse and a ransiory pricing error, which capures deviaions from efficien prices. Hence, he efficien price can be defined as: j m = lim E τ ( p+ τ F ) = p + ι Ψ() Β i= η (7) 9

10 where F is he informaion se a he end of he day. herefore, he change in he daily efficien price is Δ m Δ m = m m = φ η, ι () + φ η 2 = 2, Ψ Β η = φ η (8) where φ = ( φ, φ ) = ι Ψ( Β. Since E η η ) = Ι, he informaion share for period i is: 2 ) ( 2 Var( φiη i, ) φi ISi = =, for i =,2 (9) Var( φ η ) φ + φ Noe ha in he Hasbrouck presenaion of he IS, he ordering of prices impacs he resuling IS measure and as such upper and lower bounds are necessarily esablished. However, Wang and Yang (29) demonsraes ha in his formulaion, he ordering of reurns does no impac he value of he resuling IS measure Weighed Price Conribuion Barclay and Warner (993) uilise he WPC mehod o deermine he impac of differen rade sizes on rade price. heir mehod is adoped o measure he conribuion of differen periods wihin a rading day o he price discovery process by Cao e al. (2), Barclay and Hendersho (23, 28), Huang (22) and Ellul e al (25). In his sudy, he WPC of he opening and open-o-closing reurn o he daily sock price reurn will be compued and presened along wih he IS measure. As define previously, if r, and r 2, are he opening and open-o-close reurns respecively, such ha r r, + r2, = is he close-o-close reurn, hen he WPC for period i is compued as follows: r = = i, WPC = i r r, for i =,2 () r he second erm in parenheses measures he relaive conribuion of period i o he close-oclose reurn and he produc of he firs wo erm is a weighing facor ha reduces he impac of

11 small absolue daily reurns. Essenially, he WPC relies on he average reurn process over he sample o reduce he effec of ransiory price movemens on he reurn series (Huang, 22) Opening Reurns and Open-o-Close Reurns Ideally, opening reurn is calculaed as he difference beween he log opening price, deermined by he opening algorihm, and he log price of he las rade in he previous rading day. However, wo issues may arise in he case of he MSE. Firs, he las rade price migh no reflec he las valuaion for he sock a marke close. Second, a he end of he pre-opening period an opening price is deermine only when here are maching buy and sell orders such ha he price of he bes buy is a leas equal o he price of he bes sell order. Hence, no in all cases will here be an opening price generaed a he end of he pre-opening. o alleviae hese problems, we se he closing price of each sock o he mid-quoe a he rading day and he opening price is se equal o eiher he opening price if here are execuable orders or o he midquoe a he end of he pre-opening oherwise. 7 able 2 presens a saisical summary of he opening (r ) and open-o-close (r 2 ) reurns for he six socks uilised in his sudy. Eviden from he able is ha he average opening reurn for five of he six socks is posiive and all wih a negaive open-o-close reurn. his indicaes ha here is in general a reversal of reurns afer he opening: if a sock realises a posiive opening reurn, hen i is ofen followed by a negaive reurn during he rading period. For all he socks, here is evidence of excess dispersion as he sandard deviaion in all cases is greaer han heir respecive mean reurn. he able also reveal ha boh he opening and open-o-close reurns for he six socks are significanly serially correlaed, even a large lags as he Ljung-Box es saisics a lags four, eigh, sixeen and hiry six are all saisically significan a he five percen level. his finding indicaes cauion should be exercised when using he WPC as a measure of sequenial price discovery. 7 An opening price is generaed for he hree mos acive socks (BOV, MLC and HSB) beween 77% and 8% of he ime, and beween 5% and 57% for he less acive hree socks (MSI, MIA and IHI) in our sample.

12 3.3 Empirical Resuls he esimaes for boh he sequenial informaion share (IS) and he weighed price conribuion (WPC) measure of he pre-opening period price conribuion are repored in able 3. Resuls are presened for he enire sample and for each year wihin he sample. he IS is esimaed from he srucural VAR in equaion (2) and he WPC is esimaed using equaion (). In addiion, he able repors he correlaion beween he opening and open-o-close reurn, he compued difference beween he WPC and he IS measure, and he number of lags incorporaed in he srucural VAR model used o calculae he IS. he lag lengh of he srucural VAR is seleced using he maximum AIC saisic. able 4 provides a summary of able 3 for boh he mos acive (A) socks and he leas acive (B) socks. Eviden from able 4 is ha, on average, here is a negaive relaionship beween opening reurns and open-o-close reurn for boh he A and B socks for each year in he sample, and also for he full sample. hus, a posiive reurn during he pre-opening ends o be follow by a negaive reurn over he subsequen rading period. For he A socks, he average correlaion ranges beween -.7 and he B socks end o be even more negaively correlaed, wih averages ranging beween -.7 o he conribuion of he pre-opening period o daily price discovery varies depending upon he esimaion mehod chosen. Based on he IS measure, he proporion of price discovery aribuable o he pre-opening period is on average approximaely 3% for he A socks and 32% for he B socks. he WPC esimaes are slighly higher on average for boh ype of sock, wih approximaely 35% and 38% of he daily price discovery aribuable o he pre-opening across he A and B socks respecively. Hence, he pre-opening period seems o accoun for similar levels of price discovery for boh he mos acive and he leas acive socks in our sample. For boh caegories of socks, here is a small reducion in price discovery during he pre-opening over he sample period, irrespecive of mehod used. he WPC shows a more gradual decline over he period as compared o he IS, which exhibis a more volaile paern. For he A socks, he average IS decreased from approximaely 36% o 3% wih a high of 55% and low of 7% in 23 and 26 respecively. he WPC decreases gradually from approximaely 37% o 25% over he sample period, wih a high of 46% and a low of 25% in 2 and 27 respecively. For he B socks, he average IS decreased from approximaely 24% o 2% over he sample wih a high of 47% in 2 and a low of 2% in 27. he WPC for he B socks declines from 2

13 approximaely 44% o 3% over he sample wih a high of 48% in 2 and a low of 3% in 27. On average, he difference beween he IS and he WPC for boh he A and B socks is in he region of 5% - 6% respecively, for he full sample. his suggess ha over he long run, boh mehods may produce similar conclusions. In addiion, he yearly averages of he IS and he WPC for boh A and B socks are close o heir respecive esimaes for he full sample. In conras, he annual esimaes of he WPC and he IS are similar for some year bu reveal large differences for oher years. In he A socks, on average he difference beween he IS and WPC ranges beween -5% and 6% and beween is -3% and 2% for he B socks. hese differences are driven by numerous facors ha affecs he IS and he WPC separaely, such as he correlaion beween he opening and open-o-close reurns, he level of excess dispersion in he reurn series, reurn serial correlaion and he number of lags incorporaed ino he srucural VAR model. However, in conras o he finding of Wang and Yang (2), we find no disinc relaionship beween hese parameers and he difference beween he IS and he WPC. Consequenly, using he IS or he WPC o deermine he level of price discovery migh lead o differen empirical conclusions. Overall, irrespecive of he mehodology employed, he pre-opening period conribues significanly o he daily price discovery process, wih values of beween 3% and 38% for boh he mos and he less acive socks in his sudy. Essenially, we find no evidence ha here is a significan difference beween he conribuions of he pre-opening o he daily price discovery process of socks ha are highly acive compared o socks ha are significanly less acive during he pre-opening period. We also find ha he price discovery aribuable o aciviy in he pre-opening period has been slighly reduced over he 2 o 27 period. 4. Limi Order Book and Opening Reurns he informaion conen of he open limi order book is a major opic of debae in sudies focusing on price discovery. On he one hand, various sudies conend ha only informaion a he op of he order book provides invesors wih informaion abou he full informaion value of he asse. heoreical models of Glosen (994), Rock (996), Angel (997), Seppi (997) and 3

14 Harris (998) show ha informed raders prefers he use of marke orders o profi from heir shor lived privae informaional advanage. Hence, informed raders will rade-off a higher cos and reveal heir privae informaion o guaranee immediae execuion of heir orders, due o he non-execuion risk associaed wih he submission of limi orders. hus, under hese assumpions he order book below he bes quoes provides no informaion abou fuure price discovery. On he oher hand, oher sudies argue ha he order book below he bes quoes provides informaive and i composiion should be a basis of ongoing research. his debae in some insances focuses on he use of limi versus marke orders by informed agens o profi from heir informaional advanage. In essence, if informed rades uilise limi orders which are more discree and reveals less informaion o he marke, hen he privae informaion will be refleced in he limi order book. However, if informed raders uilise marke order ha are cerain and immediae even hough expensive and reveals heir impaience, hen heir privae informaion will no be presen in he limi order book (Cao e al. 29). Bloomfield e al. (25), show ha i is more profiable for informed raders o submi proporionally more limi han marke orders so as o conceal and maximise he payoff from heir privae informaion. he heoreical model of Kaniel and Lui (26) confirms his behaviour, and concludes ha limi orders in he order book will be more informaive when raders posses long-lived informaion. Harris and Panchapagesan (25) provides empirical suppor for his proposiion by showing ha specialiss a he New York Sock exchange (NYSE) uilise informaion from he limi order book o gain advanage over limi order raders. Essenially, he choice beween he submission of marke or limi orders represens a rade-off beween he non-execuion cos and picking off risk associaed wih limi orders and bearing he cos of immediae execuion provided by marke orders (Cohen e al., 98, Copeland and Galai, 983 and Handa and Schwarz, 996). o deermine his rade-off, sudies argue ha in formulaing heir order submission sraegy, raders uilises informaion ha can be inferred from he limi order book, which furher suppors he noion ha he order book is informaive. Specifically, Parlour (998) proposes he crowding ou effec, whereby raders gauge heir submission of limi or marke orders based on he hickness on boh sides of he order book. Foucaul (999) and Foucaul e al. (25) conend ha he proporion of limi order submission 4

15 relaive o marke order depends on he fundamenal asse price volailiy and he bid-ask spread, respecively. Goeler e al. (25) also find ha he level of he spread affecs he rade-off beween he submission of marke and limi orders, such ha larger spreads increase he cos of marke orders and, herefore, reduce heir use by informed agens. Several empirical sudies corroborae hese heoreical predicions, and in he process confirming ha he limi order book is informaive abou order sraegy employed by raders. Biais e al. (995), Al-Suhaibani and Kryzanowski (2), Ranaldo (24) and Ellul e al. (995) show ha he smaller he spread he greaer he probabiliy of marke order relaive o limi order submission. he impac of he order book deph ( crowding ou effec) on order choice and aggressiveness is confirmed by Biais, Hillion and Spa (995), Cao, Hansch and Wang (28), Griffihs e al. (2), Ranaldo (24), Hall and Hausch (26) and Pascual and Veredas (28). In addiion, Cao e al. (28) shows ha he price dimension along he order book, referred o as order book heigh, is also informaive and impacs he use of marke versus limi orders for rade execuions. Hence, from boh a heoreical and empirical perspecive, here is srong evidence supporing he premise ha he order book is informaive and should provide informaion abou fuure prices and by exension price discovery. he conex of he pre-opening period differs, as here are no marke orders per se (due o he lack of order execuion). Orders submied and no cancelled si in he pre-opening order book, awaiing execuion a he opening. he lack of coninuous order execuion during he preopening should ranslae ino an order book ha becomes increasingly informaive as he preopening period progresses and is of is mos informaive a marke opening. Vives (995) mainains ha in he presence of informed and uninformed raders submiing orders during he pre-opening, boh ypes of raders will submi orders unil he subsequen opening price reveals he full informaion value of he asse. In his siuaion, he srucure of he pre-opening order book is informaive regarding he fundamenal value of he asse and, correspondingly, he reurn generaed over he pre-opening. o qualify he above, raders have he opion o revise or cancel orders siing in he order book during he pre-opening period, hereby creaing an opporuniy for raders o game he order book. In oher words, manipulaive behaviour during he pre-opening period could disor inferences abou he informaional conen of he order book. Specifically, in he models of 5

16 Medrano and Vives (2) and Brusco e al. (23), manipulaion by an informed rader will induce addiional noise in he order book, which limis he abiliy of oher raders o make inferences abou he fundamenal value of he asse. If manipulaive behaviour is presen, hen i is expeced ha he pre-opening order submission sraegy will provide lile informaion abou he fundamenal value of he asse and consequenly reurns over he period. In conras, if raders learn abou he fundamenal value of he asse (Biais e al. 995) he order book will be informaive abou reurns over he pre-opening. In his secion, we empirically asses he informaiveness of he sae of he pre-opening order book in relaion o he pre-opening period reurn. Specifically, we invesigae he informaion conen of he overnigh order book, changes o he order book hroughou he pre-opening, and he sae of he opening order book. o our knowledge, his is he firs sudy ha aemps o assess he relaionship beween he evoluion of he pre-opening order book and he reurn realised over he pre-opening period. here are oher empirical sudies ha examine he relaionship beween he limi order book and shor-erm reurns, bu hese focus exclusively on he coninuous rading period. For insance, Huang and Soll (994) show ha he difference beween he deph of he bes buy and sell orders predics fuure price change. Chordia, Roll and Subrahanyam (22) and Boehner and Wu (28) mainains ha rading imbalances impac fuure reurns, while Cao e al. (29) find ha order book imbalances beween he buy and sell side a, and below, he op of he order book impacs fuure shor erm reurns. Of hese sudies, his analysis is mos closely relaed o ha of Cao e al (29). 4. Overnigh Order Book and Opening Reurns A he end of rading each day, orders submied which remain unexecued queued o form he overnigh order book, which subsequenly serves as he iniial basis for inference o raders paricipaing in he pre-opening period. o deermine he informaion conen of he overnigh order book we examine he order book on boh price and liquidiy dimensions. Firs, o examine he volume dimension, we measure relaive volume imbalances along he order book. We mainain ha if here is an excess amoun of demand (supply) pressure in he previous rading session resuling in large unexecued buy (sell) orders relaive o sell (buy) orders queued in he overnigh order book, hen his excess demand (supply) will resul in an upward (downward) 6

17 pressure on pre-opening prices. Alernaively saed, when he order book on he buy (sell) side is hick in relaion o he sell (buy) side, hen subsequen orders submissions and forward price revision in he buy (sell) order book will have o be more aggressive o enhance heir probabiliy of execuion a he opening. his increased aggressiveness in buy (sell) orders submission or forward price revision will resul in an upward (downward) pressure on opening prices. Previous empirical sudies including as Biais e al. (995), Ranaldo (24), Hall and Hausch (26), Pascual and Veredas (28), Cao e al. (28) among ohers find a posiive relaionship beween large buy (sell) side deph and he aggressiveness of prices associaed wih fuure order submissions. Cao e al. (29) empirically idenify a posiive relaionship beween relaive excess demand and shor erm reurns during he regular rading period. Hence, he esable hypohesis is as follows; Hypohesis a: Increase in relaive buy (sell) deph in he overnigh order book posiively (negaively) impacs opening reurns. he informaion conen of imbalances along he price dimension of he overnigh order book is capured by measuring he relaive heigh a differen seps along he order book. Similar o he volume imbalance, he price imbalances along he overnigh order book measures he relaive buy or sell pressure resuling from high demand or supply during he previous rading session. Essenially, he overnigh order book will reflec higher buy (sell) pressure when he prices along he buy (sell) dimension of he book are closer ogeher relaive o he prices along he sell (buy) side of he order book. If he supply side pressure exceeds ha on he demand side in he previous rading session, hen he absolue disance beween he prices of unexecued sell orders along he overnigh order book will be (relaively) smaller han he disance beween prices on he buy side. Similarly, if here was demand side pressure during he previous rading session hen his should be refleced in he disance beween he unexecued buy orders ha queue in he overnigh order book. We argue ha when he relaive buy (sell) side heigh is small, his leads o he submission of aggressive buy (sell) orders and forward revisions which resuls in upward (downward) pressure on opening prices. herefore, he esable hypohesis is; 7

18 Hypohesis b: Decrease in relaive buy (sell) heigh in he overnigh order book posiively (negaively) impacs opening reurns. 4.2 Pre-opening Order Book Evoluion and Opening Reurns A commencemen of he pre-opening period, raders can examine he exan order book when deciding on heir opimal order placemen sraegy. However, as he pre-opening order book evolves and raders are able o make more reliable inferences abou he full informaion value of he sock, we expec he submission and placemen sraegy o be refined accordingly. Inuiively, any changes o he sae of he overnigh order book are aribuable o four main acions aken by raders during he pre-opening period. hese are he submission of new order, revisions of order prices owards and away from he op of he order book (referred o as forward and backward revisions, respecively) and cancellaion of exising orders in he order book during he pre-opening period. During he pre-opening period, buy or sell side pressure can be ascerained by examining he increase in deph on eiher sides of he book as raders submi new orders. Essenially, if during he pre-opening period here is buy side pressure resuling in relaively larger incoming buy compared o sell order being submied, hen his excess demand pressure will place upward pressure on he opening price. In addiion, if he supply volume is relaively greaer han he demand hen his will exer downward pressure on prices. Addiionally, changes in he buy and/or sell side pressure can also be ascerained by observing he order book heigh on boh sides of he order book. If he heigh on he buy side relaive o he sell side reduces as more order submissions on he buy side fill in any price gaps in he buy order book during he pre-opening, hen his is indicaive of an increase in buy side pressure. Consequenly, we expec his increase in buy side pressure o have a posiive impac on prices and as a consequence a posiive impac on opening reurns. he converse of he argumen hold rue as i relaes o he relaive sell side heigh. Hence, a reducion in he relaive sell side heigh aribuable o pre-opening order submission is indicaive of sell side pressure which ranslaes ino downward pressure on prices. Hence, we es he following wo hypoheses; 8

19 Hypohesis 2a: Cumulaive increases in relaive buy (sell) deph aribuable o submissions during pre-opening, posiively (negaively) impacs opening reurns. Hypohesis 2b: Cumulaive decreases in relaive buy (sell) heigh aribuable o submissions during pre-opening, posiively (negaively) impacs opening reurns. One of he main characerisics of he pre-opening period is he abiliy for raders o cancel or revise he price or volume of a previously submied limi order wihou any cos or obligaions anyime before he opening. As new orders are submied o he order book and raders are able o form more reliable esimaes abou he fundamenal value of he sock, hen if heir informaion se is inconsisen wih inferences made from he order book, hen hey have he opion o cancel or revise he price of heir queued orders. 8 Essenially, when raders on he buy side, for insance, revise he price of an order closer o he op of he bid order book, he resul is an increase in buy side pressure since he volume associaed wih he revised order will increase he deph closer o he op of he order book. Conversely, if a buy side rader revises a buy order away from he op of he order book, hen here will be a reducion in buy side pressure on opening prices. he opposie argumen holds rue for order revisions on he sell side. When raders revise he price of heir order owards he op of he order book, here will be a resuling impac on he order book heigh: a forward revision of a buy order resuls in a reducion in he relaive heigh owards he op of order book. his reducion in relaive heigh ranslaes ino an increase in buy side pressure during he pre-opening period. Consequenly, as oher raders observe he decrease in he relaive buy side heigh, hey will have o conemplae revising he price of heir queued order closer o he op of he buy order book in order o resore he desired order execuion probabiliy. Conversely, if he price of a buy order is revised backward from he op of he order book, his resuls in a reducion in buy side pressure and a reducion in he upward pressure on prices. herefore, he esable hypoheses are as follows; Hypohesis 2c: Cumulaive increases in relaive buy (sell) deph aribuable o revisions during pre-opening, posiively (negaively) impacs opening reurns. 8 raders also have he opion o modify he volume and oher aribues associaed wih heir order. However, heir occurrence in our sample is so infrequen ha as a consequence, heir impac is no assessed. 9

20 Hypohesis 2d: Cumulaive decreases in relaive buy (sell) heigh aribuable o revisions during pre-opening, posiively (negaively) impacs opening reurns. A similar argumen can be made for cancellaion of queued limi orders. If sell side raders remove liquidiy from he order book during he pre-opening by cancelling heir orders, here are wo resuling changes ha indicae a reducion in sell side pressure. Firs, he deph a he posiion of he cancelled order is reduced by he amoun of he cancelled volume. Second, he heigh a he posiion of he cancelled order may increase resuling in an increase in he relaive sell side heigh. he consequen reducion in relaive deph and he increase in he relaive heigh combined reduce he downward pressure on prices. Similarly, reducion in he demand pressure due o cancellaions of queued buy orders reduces he upwards pressure on he opening price due o he reducion in relaive buy side deph and he increase in relaive sell side deph. In addiion, he relaive buy side heigh a he posiion of he cancelled buy order may increase and, herefore, increase he relaive buy side heigh. he ensuing reducion in he relaive buy deph and he increase in he relaive buy heigh resuls in a reducion in he upward pressure on prices. Based on hese argumens, he esable hypoheses are as follows; Hypohesis 2e: Cumulaive decreases in relaive buy (sell) deph aribuable o cancellaions during pre-opening, negaively (posiively) impacs opening reurns. Hypohesis 2f: Cumulaive increases in relaive buy (sell) heigh aribuable o cancellaions during pre-opening, negaively (posiively) impacs opening reurns. 4.3 Opening Order Book and Opening Reurn By he end of he pre-opening period, all queued orders consiue he opening order book and awai execuion by he opening algorihm. A his ime he full informaion value of he sock should be refleced by he exan sae of he order book. In an analogous fashion o he argumens presened in relaion o he overnigh order book, we examine he price and volume dimensions of he opening order book o deermine is informaion conen. We argue ha if here is buy (sell) side pressure during he pre-opening which ranslae o an excess demand 2

21 (supply) for (of) he sock, hen his will resul in an upward (downward) pressure on he opening price. herefore, his excess demand (supply) pressure will be refleced along boh he price and volume dimension of he opening order book. Hence, he demand (supply) pressure is presen when he deph on he buy (sell) side is larger relaive o he deph on he sell (buy) side, which ranslaes ino an upward (downward) pressure on opening prices. In addiion, if he relaively larger demand (supply) pressure is refleced along he price dimension of he opening order book hen we expec he relaive heigh on he buy (sell) o be smaller. Hence, he smaller he relaive heigh along he buy (sell) order book, he greaer he upward (downward) pressure on opening prices. herefore, he esable hypoheses are as follows; Hypohesis 3a: Increase in relaive buy (sell) deph in he opening order book posiively (negaively) impacs opening reurns. Hypohesis 3b: Decrease in relaive buy (sell) heigh in he opening order book posiively (negaively) impacs opening reurns. During he opening session, rade execuion occurs only for orders ha locks or crosses he inside spread. 9 he locked or crossed order effecively supply liquidiy a he open, in a similar way o marke orders in he rading session, since hey have execuion prioriy a he opening. In he Cao e al. (2) empirical sudy of he pre-opening period, hey show ha locked or crossed inside spread is informaive abou he fundamenal value of he sock and should impac opening prices. o reveal he impac of a locked or crossed inside spread on he opening price, he side of he marke ha locked or crossed he inside spread will have o be deermined. We herefore argue ha if he buy side locked or crossed he inside spread during he pre-opening, hen his resuls in a posiive signal ha is indicaive of buy side pressure and herefore upward pressure on he opening price. Similarly, if he inside spread was locked or crossed by sell side raders, hen his resuls in a negaive signalling effec and herefore, ranslaes ino downward pressure on he opening price. he esable hypohesis is herefore; 9 he inside spread is locked when he price of he bes bid is equal o he price of he bes ask. Similarly, he inside spread is crossed when he price of he bes bid is less han he price of he bes ask. 2

22 Hypohesis 3c: Buy (sell) side locking or crossing of he inside spread posiively (negaively) impacs opening reurns. 4.4 Economeric Mehodology 4.4. Opening Reurns he empirical analysis focuses on he impac of he characerisics of he pre-opening order book on he reurns generaed from he previous close o he opening of he marke. Similar o he previous secion, he opening (close-o-open) reurn on day is r, = po, pc,, where p o, and p c, denoes he log opening and closing prices on day respecively. From he previous secion, he Ljung-Box es saisics indicaes ha r, is highly serially correlaed even a high lags for all six socks considered in his analysis. o correc for he presence of serial correlaion in reurns, we pre-whien he reurns (similar o Cao e al. (29)) and focus our analysis on he innovaions in opening reurns. Iniially, he opening reurn innovaion is used as he dependen variable insead of he opening reurn in he analysis since hese innovaions represen he porion of reurn ha is no explained by previous changes in reurns. We corroborae our findings using he opening reurns iself. he opening reurn innovaions are obained by esimaing an AR(P) model for each sock and collecing he residuals, such ha ε P = i ϕi L r, α () i= where ε is he opening reurn innovaion, α and ϕ i are he esimaed consan and slope parameers, respecively, from he AR(P) model, L is he lag operaor and he lag lengh P is deermined by he maximum Akaike Informaion Crierion (AIC) value. Since his sudy focuses on he reurn over he pre-opening period which only accouns for a proporion of he oal reurns generaed over an enire rading day, we also conrol for he effec of he open-o-close reurn from he previous day ( p p ) r on he opening reurn. For robusness checks, 2, = o, c, we also use he opening reurns as he dependen variable in his analysis and repor he resuls. 22

23 he -saisics repored are calculaed using he Newey-Wes heeroskedasiciy and auocorrelaion consisen sandard errors Explanaory Variables he hypoheses oulined in secions 4., 4.2 and 4.3, propose ha he upward and downward pressure along he volume and price dimensions, namely he deph and heigh, impacs he opening reurns. For insance, in secion 4. we conend ha he relaive deph and heigh of he overnigh order book impacs opening reurns. o es hese hypoheses, we measure he relaive deph and heigh from he op o sep five in he order book queue. If B D j and S D j denoes he oal volume a posiion j in he buy and sell order book respecively, he relaive deph a posiion j is herefore; RD j B S D j D j =, for j =,...,5 (2) D + D B j S j Hence, he relaive deph a posiion j is he excess demand (supply) proporional o he oal volume a posiion j on boh sides of he order book. Similarly, if B P j and S P j denoes he prices a posiion j in he buy and sell order book respecively, hen he relaive heigh is measured as follows, RH j S S B B ( Pj Pj ) ( Pj Pj ) S S B B ( P P ) + ( P P ) =, for j =,...,5 (3) j j j j where, we se P B = P S. Hence, he relaive heigh measures he relaive disance beween = he prices on eiher sides of he order book. Rearranging he erms in equaion (3) reveals ha he relaive heigh is he difference beween he spread a differen seps along he order book. In addiion, since P B = P S, hen he relaive heigh a j = is he relaive spread. Due o he = exended lack of rading aciviy over he weekend or long holiday period such as during Chrismas, he likelihood is ha he informaion in he overnigh order book ha precedes he pre-opening in hese siuaions has a greaer endency o become sale. o accommodae his 23

24 possibiliy, we incorporae a dummy variable ( DS ) ha akes he value of one if he marke is closed for more han one day prior o day. he firs regression is herefore; n n + γ r2, + θ DS + β j RD j, + λ j RH j, μ (4) j= j= ε α + = In secion 4.2 we argue ha he changes o he relaive order book heigh and deph over he preopening period impac he opening reurn. o measure he change in he relaive heigh over he pre-opening period aribuable o order submissions, we denoe Δ SRH j, i as he change in he relaive heigh aribuable o he price of an order submied a posiion j in period i. herefore, he cumulaive change over he pre-opening will be ΔSRH j = = ΔSRH j i, i. By a similar consruc, if Δ FRH j, i and ΔBRH j, i denoes he change in relaive heigh in period i aribuable o forward and backward order revision o posiion j in he order book, hen he cumulaive changes over he pre-opening are ΔFRH j = = ΔFRH i j, i and ΔBRH j = = ΔBRH i j, i, respecively. In addiion, if Δ CRH j, i is he change in relaive heigh in period i aribuable o cancellaion of an order from posiion j in he order book, hen ΔCRH j = = ΔCRH i j, i is he cumulaive cancellaion change over he pre-opening period. he second regression is as follows; ε = α + γ r + n j= 2, λ CH j + n j= ΔCRH λ ΔSRH SH j j, + μ j, + n n FH λ j ΔFRH j, + j= j= λ BH j ΔBRH j, (5) For changes in relaive deph, analogous o he changes in relaive heigh, we focus on he cumulaive changes over he pre-opening period aribuable o submissions, revisions and cancellaions. If Δ SRD j, i is he change in he relaive deph in period i due o an order submission a posiion j in he order book, hen ΔSRD j = = ΔSRD i j, i is he cumulaive impac 24