Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 Han-Chng Huang (awan), Yong-Chern Su (awan), Y-Chun Lu (awan) he performance of mbalance-based radng sraegy on ender offer announcemen day Absrac hs sudy eamnes he process how he ender offer nformaon s ncorporaed no nraday relaon beween reurn and order mbalance. We frs eamne he relaon beween lagged order mbalances and sock reurns. he resul shows ha he mpacs of lagged one mbalance on reurns are sgnfcanly negave. I mples a lkelhood of mbalance-based sraegy. We fnd ha he relaon beween order mbalance and volaly s no srong enough, suggesng ha marke makers have power n mgang volaly. We ake a furher sep o eamne small frm effec durng prce formaon. he resuls show ha nformaon asymmery s severe n small frms. Based on he resuls, we develop an mbalance-based radng sraegy, whch yelds a sascally sgnfcan posve reurn and ouperforms buy and hold daly reurn on ender offer announcemen day. A nesed causaly approach, whch eamnes dynamc reurn-order mbalance relaon durng prce formaon process, eplans he mbalance based radng sraegy. Keywords: ender offer, order mbalance, nformaon asymmery, volaly. JEL Classfcaon: G4, G34. Inroducon Over he pas wo decades, a consderable number of researches have been made on akeover. A frs, a majory of leraure focuses on he sock abnormal reurn mmedaely surroundng announcemen daes (e.g. Agrawal e al., 992; Kanel e al., 22). Recenly, a small body of sudy has eplored long-run pos acquson abnormal reurns (e.g. Dua and Jog, 29; Bessembnder and Zhang, 23). Noneheless, o our knowledge, here s no sudy ha eplores he behavor of he marke mcrosrucure on he announcemen day. Accordng o Cao e al. (25) and Arnold e al. (26), he radng pror o a ender offer announcemen could be manly naed by raders who hold prvae nformaon. Neverheless, he majory of nvesors are unnformed raders and hey could only rade he socks afer hearng he news on he announcemen day. herefore, alhough he radng pror o announcemen s largely orgnaed by nformed raders, he radng on he announcemen day could be manly naed by unnformed raders. he radng sraegy we consruc would be useful for unnformed ndvdual nvesors. Based on he form of offer, akeover could be dvded no wo pars: merger and ender offer. Accordng o Agrawal and Jaffe (2), mergers and ender offers should be nvesgaed separaely as hey could have dfferen mplcaons for frm performance. ender offers are dfferen from mergers manly n ha acqurng frms of ender offers bd for arge shares n he open marke 2. Based on he akeover sample durng 978-2, Dong e al. (26) fnd ha he percenage of ender offer (9.4%) s only one-ffh me han ha of merger (8.6%). Meanwhle, n he academc area, he sudes 3 abou he ender offers are less han hose abou mergers. Because here are nadequae researches on ender offers, n hs sudy, we fll he gap o eamne he convergence process as o how ender offer nformaon s ncorporaed no he bdder s sock prce on he announcemen day. If ender offer nformaon canno be ncorporaed no he prce mmedaely 4, he unnformed raders are heorecally able o develop a radng sraegy, whch yelds a posve reurn durng he announcemen day. Movaed by Chorda and Subrahmanyam (24), we use nraday ransacon daa for he ender offer on he announcemen day o eamne he relaonshp beween he order mbalances and ndvdual sock reurns. We eamne he convergence process wh hree dfferen me nervals (5-, -, 5- mn). In order o make sure ha volaly plays no role n he reurn-order mbalance relaonshp, we employ a me-varyng GARCH (, model o eamne he volaly-order mbalance relaonshp. We epec ha a large volaly s followed by a large order mbalance. Moreover, we develop an mbalance-based radng sraegy, whch could earn a sascally sgnfcan abnormal reurn. Fnally, a nesed causaly beween he order mbalance and reurn s nvesgaed o eplore he nraday dynamcs whch s essenal n he convergence process. Han-Chng Huang, Yong-Chern Su, Y-Chun Lu, 24. A large prevous leraure fnds ha he average abnormal reurns of akeover bdders end o be negave or close o zero. herefore, raonal unnformed nvesors should sell he bdder s socks o make a prof. 2 Accordng o Rau and Vermaelen (998), n he case of ender offers, bdder frms are ofen consdered as hosle and wh cash offer. Mergers occur hrough dscusson beween he bddng frm and arge frm, are ofen frendly, and are usually done hrough share offer (Loughran and Vjh, 997; Marn and McConnell, 99. 3 See Mandelker (974), Dodd and Ruback (977), Bradley (98), Bradley e al. (983), Lebler (997), Ahn e al. (2, and Aanassov (23). 4 From he perspecve of marke neffcency, Chorda e al. (25) shows ha he marke does no converge o effcency mmedaely. Grossman (975) and Grossman and Sglz (98) fnd ha he marke prces canno fully ncorporae all knowable nformaon. hey argue ha someone mus be able o generae reurns by eplong he devaon of prces from fundamenal values. 38
We have several margnal conrbuons. Frs of all, he radng on he announcemen day of he ender offer could be manly naed by unnformed raders. If he nformaon canno be ncorporaed no he prce mmedaely, he unnformed raders could develop a radng sraegy, whch yelds a posve reurn. Secondly, on he announcemen day of he ender offer, marke maker behavor plays a very mporan role n mgang volaly from dscreonary rades hrough nvenory adjusmens. Fnally, we nvesgae he nesed causaly beween order mbalances and reurns as we eplore he nraday dynamcs ha s essenal n he convergence process of he ender offer announcemen. Our sudy s organzed as follows. Secon descrbes daa. Secon 2 ehbs he reurn-lagged order mbalances relaon. In secon 3, we dscuss he volaly-order mbalance GARCH (, relaon. Secon 4 presens he performance of order mbalance based radng sraegy. In secon 5, we ehb he causaly relaonshp n eplanng reurn-order mbalance relaon and he fnal secon concludes.. Daa We nclude ender offer acqurers from he Secures Daa Company (SDC) Merger and Acquson daabase. Our sample perod s from January, 2 hrough December 3, 27. Socks are ncluded or ecluded n our samples accordng o he followng crera. Frs, all socks whose ransacon daa are no avalable n boh SDC and AQ are ecluded from our samples. Second, we delee asses from he followng caegores: cerfcaes, Amercan Deposary Receps, shares of benefcal neres, uns, companes ncorporaed ousde he U.S., Amercus rus componens, closed-end funds, preferred socks and REIs, because of her dfferen radng characerscs. Fnally, we have 5 samples. We use Lee and Ready (99 rade assgnmen algorhm o derve 5-mnue, - mnue, and 5- Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 mnue order mbalances. Average reurn of our sample s -.249%, wh a medan of -.2447%. he sandard devaon of reurn s.32, wh a mamum value s 9.3685% and he mnmum s -4.2692%. 2. Reurn-lagged order mbalances relaon We employ a mul-regresson model o eamne uncondonal reurn-order mbalance relaon. 5 R = - OI -, ( where R s he sock reurn a me of he sample sock. OI are he lagged order mbalances a me of he sample socks. We epec ha wheher lagged mbalances are posvely relaed o sock reurns accordng o Chorda and Subrahmanyam (24). Sgnfcanly posve lagged order mbalances help us o develop an mbalance-based radng sraegy. We use anoher mul-regresson model o nvesgae he relaon beween sock reurns, conemporaneous and four lagged order mbalances. We epec a sgnfcanly posve mpac of conemporaneous mbalances on reurns. Moreover, we conjecure how marke makers dynamcally accommodae he mbalances pressure by eamnng wheher here s a rend among hree dfferen me nervals (5-, -, 5-mn). We run a mulple-regresson model o eamne reurn-lagged order mbalances relaon. he resuls are presened n able. A 5% sgnfcan level, we fnd ha negavely sgnfcan percenages of lagged one mbalance are 4.%, 4.7%, and 6.7% for 5-, - and 5-mn nervals respecvely, whch are larger han hose of posvely sgnfcan mbalances, namely 4.%, 2.7%, and.7% for 5-, -, and 5-mn. hese resuls are nconssen wh Chorda and Subrahmanyam (24). hey argue ha lagged order mbalances, especally he lagged one order mbalances, are sgnfcanly posve relaed o curren sock reurns due o he spl orders of lqudy raders. able. Uncondonal lagged reurn-order mbalance relaon Average coeffcen Percen posve Percen posve and sgnfcan Percen negave and sgnfcan 5-mn nerval OI- -2.7E-8 47.33% 4.% 4.% OI-2 -.9E-8 45.33% 2.7% 5.3% OI-3.3E-8 46.% 4.% 6.% OI-4-7.7E-8 44.% 2.7% 6.7% OI-5 -.4E- 58.67% 2.7% 5.3% -mn nerval OI- -5.4E-8 39.33% 2.7% 4.7% OI-2-2.8E-7 44.% 2.% 6.% OI-3 8.47E-9 47.33%.3% 4.% OI-4-4.6E-9 46.67% 4.7% 2.7% OI-5 4.37E-9 46.% 2.7% 2.% 39
Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 able (con.). Uncondonal lagged reurn-order mbalance relaon Average coeffcen Percen posve Percen posve and sgnfcan Percen negave and sgnfcan 5-mn nerval OI- -3.2E-7 42.67%.7% 6.7% OI-2-7.6E-8 46.67%.3% 4.% OI-3-2.5E-8 44.67%.3% 2.7% OI-4 -.7E-8 48.% 2.7% 2.% OI-5 6.37E-8 49.33% 4.% 2.7% Noes: Sgnfcan denoes sgnfcan a he 5% level. he possble eplanaons of our emprcal resuls are wofold. Frs of all, marke makers have accommodaed a hgh nvenory level around he ender offer announcemen day o mgae mpacs from dscreonary nvesors. Anoher eplanaon s ha, from prevous emprcal resuls, mpacs of he nformaon assocaed wh he announcemen of ender offers are no srong enough. ha s why marke makers do no face a grea nvenory pressure. We nclude conemporaneous and four lagged order mbalances n our regresson o eamne condonal reurn-conemporaneous order mbalance relaon. he resuls are ehbed n able 2. We fnd ha he mpacs of conemporaneous order mbalances on reurns are posvely sgnfcan for all me nervals a all sgnfcan levels. However, he mpacs of lagged one order mbalances are negave for all me nervals a 5% sgnfcan levels. hese resuls are conssen wh Chorda and Subrahmanyam (24). hey use overreacon sory o eplan he reason why negave coeffcens of lagged one mbalance occur. Mos of he nformaon abou curren sock reurns s overreaced n conemporaneous order mbalance, herefore lagged one order mbalances, whch are auocorrelaed wh conemporaneous mbalances, cause he curren sock reurns o reverse. able 2. Condonal conemporaneous reurn-order mbalance relaon Average coeffcen Percen posve Percen posve and sgnfcan Percen negave and sgnfcan 5-mn nerval OI 2.22E-7 9.33% 59.3%.7% OI- -3.64252E-8 46.% 3.3% 9.3% OI-2 -.583E- 48.67% 4.7% 8.% OI-3.4827E-8 47.33% 4.7% 6.7% OI-4-5.84494E-8 47.33% 2.7% 7.3% -mn nerval OI 5.4855E-7 88.% 43.3%.7% OI- -3.4624E-8 4.67% 3.3% 6.% OI-2-3.2594E-8 44.67% 2.% 5.3% OI-3 2.34486E-8 5.% 4.7% 4.% OI-4.2866E-8 5.67% 4.7% 3.3% 5-mn nerval OI 5.3468E-7 9.% 32.%.3% OI- -.2464E-7 4.67%.3% 6.7% OI-2 4.688E-8 48.67%.3% 4.7% OI-3 3.335E-8 52.67% 4.7% 4.% OI-4-8.94373E-9 49.33% 2.%.7% Noes: Sgnfcan denoes sgnfcance a he 5% level. here s one neresng fndng n our emprcal resuls. Snce he percenage of posvely sgnfcan conemporaneous order mbalances s 59.3% and he percenage of negavely sgnfcan coeffcens of lagged one order mbalance s only.7% n 5-mn nerval. I mples ha dscreonary raders have a possbly o oban prvae nformaon before he bdders announce o acqure her arges hrough ender offer deals. If he nformaon hey obaned s rue, hey are gong o ake a long poson, whch enhances a large posve mbalance and boos up sock prce. Marke makers wh nvenory and adverse selecon concerns reac by rasng bd-ask quoe ogeher o accommodae large mbalances. hs releases marke makers nvenory pressure. However, from our emprcal fndngs ha nvenory pressures caused by dscreonary raders are no as serous as hey had epeced. ha s why hey lower he quoe prce o rebalance her nvenory levels, whch resuls n a 4
negave coeffcen of lagged one order mbalance. Durng he convergence process, we observe he decreasng nfluence of conemporaneous order mbalances and he percenages of posvely sgnfcan coeffcens, whch have been decreasng from 59.3% n 5-mn o 32% n 5-mn. 3. Volaly-order mbalance GARCH (, relaon In order o make sure ha volaly plays no role n dynamc reurn-order mbalance relaon, we employ a me varyng GARCH model o nvesgae volaly-order mbalance relaon. R N(, h) (2) 2 h A Bh C OI, where R s he reurn a me, and s defned as ln (P /P - ). OI denoes he eplanaory varable of order mbalance. s he resdual value of he sock reurn a me. h s he condonal varance a me. - s he nformaon se n a me. s he coeffcen measurng he mpac of he order mbalance on volaly of he reurn. We epeced ha nformaon clusers around announcemen of ender offer. Informaon flows from dfferen vews of ender offer volale sock reurns. In order o eamne volaly-order mbalance durng convergence process, we employ a me varyng model. he resuls of dynamc volaly-order mbalance relaon are ehbed n able 3. able 3. he dynamc volaly-order mbalance GARCH (, relaon Posve Percen posve and sgnfcan Percen negave and sgnfcan 5-mn nerval 4.% 6.%.% -mn nerval 33.% 3.%.% 5-mn nerval 35.%.%.% Noe: Sgnfcan denoes sgnfcance a he 5% level. We epeced ha here was a posve correlaon beween volaly and order mbalances, ha s, a large volaly s accompaned by a large order mbalance. Whle he resuls show ha he relaon s no as sgnfcan as we had epeced. A % Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 sgnfcan level, only 8.%, 6.%, and 4.% of order mbalances have a sgnfcanly posve mpac on prce volaly for 5-, -, 5-mn nerval respecvely. A 5% sgnfcan level, he sgnfcan number s even less. Moreover, here s no order mbalance has a sgnfcanly posve mpac on prce volaly respecvely for all me nervals. As epeced, we observe ha he mpacs of order mbalances on reurn volaly are weaker as he me nerval geng longer. We use marke maker behavors o eplan he neresng resuls. From our emprcal fndngs, we fnd ha marke makers wh an nhered oblgaon o reduce prce volales ndeed have ables o mgae large order mbalance effecs from dscreonary raders on ender offer announcemen dae. Anoher possble eplanaon s ha marke makers have obaned prvae nformaon before ender offer announcemen. herefore, hey have enough nvenores o mgae large order effec. 4. Order mbalance based radng sraegy able 4. radng prof under he bass of quoe prce Accordng o our resuls n prevous secons, we fnd ha he conemporaneous order mbalances have sgnfcanly posve nfluence on sock reurns, and he magnudes of mpacs decrease as he me nerval ncreases. And he average daly open-o-close reurn of our 5 ender offer bdders on he announcemen dae s -.249%. In hs secon, we develop an order mbalance based radng sraegy for hree dfferen me nervals. We rm off 9% of small order mbalances, machng wh wo defnons of prce, namely quoe and radng prces. We buy a share a ask prce when posve mbalance appears and sell a bd prce when urns negave. We repor he resuls n Panel A and he sgnfcance es n Panel B of able 4. We generae an average reurn of -2.8%, -.8%, and -2.% wh a 5% sgnfcance for 5-, -, and 5- mn nervals, respecvely. We conclude ha he radng sraegy under he bass of quoe prce underperforms daly reurn. We suspec ha large bd-ask spreads play a role n he emprcal resuls. We hen calculae on he bass of ransacon prce. Panel A: Reurns compared wh zero H :. H : Sample Mean P-value 5-mn reurn of sraegy 37 -.28. -mn reurn of sraegy 87 -.8. 5-mn reurn of sraegy 59 -.2. 4
Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 Panel B: Reurns compared wh reurns of buy-and-hold sraegy 2. H : H : able 4 (con.). radng prof under he bass of quoe prce Mean Orgnal open-o-close reurn -.28 P-value 5-mn reurn of sraegy -.28.2 -mn reurn of sraegy -.8.35 5-mn reurn of sraegy -.2.8 Panel C: Dfferences n reurns among he hree nervals 3. H : j H : j 5-mn reurn P-value 5-mn reurn -mn reurn -mn reurn.795 5-mn reurn.38.695 We buy a share a radng prce when a posve mbalance appears and sell a correspondng radng prce when urns negave. he resuls are repored n Panel A wh a sgnfcance es n Panel able 5. radng prof under he bass of rade prce B of able 5. We earn sgnfcan average posve reurns of.49%,.7%, and.43% respecvely for 5-, -, and 5-mn nervals. We conclude ha hey ouperform daly reurns. Panel A: Reurns compared wh zero H :. H : Sample Mean P-value 5-mn reurn of sraegy 37.49.77 -mn reurn of sraegy 87.6.997 5-mn reurn of sraegy 59.43.48 Panel B. Reurns compared wh reurns of buy-and-hold sraegy 2. H : H : Mean Orgnal open-o-close reurn -.52 P-value 5-mn reurn of sraegy.49.2 -mn reurn of sraegy.6.75 5-mn reurn of sraegy.43.8 Panel C: Dfferences n reurns among he hree nervals 3. H : j H : j 5-mn reurn P-value 5-mn reurn -mn reurn -mn reurn.45 5-mn reurn.387.8557 In concluson, we fnd ha an order mbalance base radng sraegy on radng prce yeld sascally sgnfcan posve reurns and ouperform he benchmark of daly reurns. ha s o say, when a company announces o acqure he oher company by ender offer deal, we apply he mbalance based radng sraegy o earn abnormal reurns. 5. Causaly relaonshp n eplanng reurnorder mbalance relaon In order o eplan he sory behnd mbalance-based radng sraegy, we employ a nesed causaly o eplore he dynamc causal relaon beween reurn and order mbalance. Accordng o Chen and Wu (999), we defne four relaonshp beween wo random varables, and 2, n erms of consrans on he condonal varances of (+ and 2(+ based on varous avalable nformaon ses, where = (, 2,..., ), =, 2, are vecors of observaons up o me perod. Defnon : Independency, 2 : and 2 are ndependen f 42
Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 Var( ) Var(, ) ( ( 2 ~ ~ ~ Var(,, ) and ( 2 2( ~ ~ ~ Var( ) Var(, ) 2( 2 2( 2 ~ ~ ~ Var(,, ) 2( 2 ( ~ ~ ~ (3) (4) Defnon 2: Conemporaneous relaonshp, < > 2 : and 2 are conemporaneously relaed f Var( ) Var(, ) (5) ( ( Var (, ) Var (,, ) (6) ( ( 2( ~ and Var( ) Var(, ) (7) 2( 2( Var (, ) Var (,, ) (8) 2( 2( ( ~ Defnon 3: Undreconal relaonshp, = > 2 : here s a undreconal relaonshp from o 2 f Var( ) Var(, ) (9) ( ( and Var( ) (, ) 2( Var 2( ( Defnon 4: Feedback relaonshp, < = > 2 : here s a feedback relaonshp beween and 2 f Var( ) Var(, ) ( ( ( and Var( ) Var(, ) (2) 2( 2( o eplore he dynamc relaonshp of a bvarae sysem, we form he fve sascal hypoheses n he able 6 where he necessary and suffcen condons correspondng o each hypohess are gven n erms of consrans on he parameer values of he VAR model. able 6. Hypoheses on he dynamc relaonshp of a bvarae sysem ( L) 2 ( L) he bvarae VAR model: 2( L) 22( L), where 2 and 2 are mean adjused varables. he frs and second 2 momens of he error srucure, (, 2), are ha E( ), and E( k) for k and E( k) for k =, 2 where 2. 22 Hypoheses H: 2 2 (L) = 2 (L) =, and 2 = 2 = H2: < > 2 2 (L) = 2 (L) = H3 : > 2 2 (L) = H3 * : 2 > 2 (L) = H4 : < = > 2 2 (L) 2 (L) H5 : >> 2 2 (L)=, and 2 = 2 = H6 : 2 >> 2 (L) = =, and 2 = 2 = H7 : << = >> 2 2 (L) 2 (L), and 2 = 2 = he VAR es o deermne a specfc causal relaonshp, we use a sysemac mulple hypoheses esng mehod. Unlke he radonal par-wse hypohess esng, hs esng mehod avods he poenal bas nduced by resrcng he causal relaonshp o a sngle alernave hypohess. o mplemen hs mehod, we employ resuls of several par-wse hypohess ess. For nsance, n order o conclude ha => 2, we need o esablsh ha < 2 and o rejec ha > 2. o conclude ha <> 2, we need o esablsh ha < 2 as well as > 2 and also o rejec 2. In oher words, s necessary o eamne all fve hypoheses n a sysemac way before we draw a concluson of dynamc relaonshp. he followng presens an nference procedure ha sars from a par of he mos general alernave hypoheses. Our nference procedure for eplorng dynamc relaonshp s based on he prncple ha a hypohess should no be rejeced unless here s suffcen evdence agans. In he causaly leraure, mos ess nend o dscrmnae beween ndependency and an alernave hypohess. he prmary purpose of he leraure ced above s o rejec he ndependency hypohess. On he conrary, we nend o denfy he naure of he relaonshp beween wo fnancal seres. he procedure consss of four esng sequences, whch mplemen a oal of s ess (denoed as (a) o (f)), 43
Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 where each es eamnes a par of hypoheses. he four esng sequences and s ess are summarzed n a decson-ree flow char n Fgure. o eplore dynamc reurn-order mbalance relaon durng prce formaon, we employ a nesed causaly approach. In order o nvesgae a dynamc relaonshp beween wo varables, we mpose he consrans n he upper panel of able 6 on he VAR model. In able 7, we presen he emprcal resuls of ess of hypoheses on he dynamc relaonshp n Fgure. Panel A presens resuls for he enre sample. In he enre sample, we show ha a undreconal relaonshp from reurns o order mbalances s 9.4% of he sample frms for he enre sample, whle a undreconal relaonshp from order mbalances o reurns s 8.72%. he percenage of frms ha fall no he ndependen caegory s 3.2%. Moreover, 48.32% of frms ehb a conemporaneous relaonshp beween reurns and order mbalances. Fnally, 3.36% of frms show a feedback relaonshp beween reurns and order mbalances. he percenage of frms carryng a undreconal relaonshp from order mbalances o reurns s almos he same as ha from reurns o order mbalances, suggesng ha order mbalance s no a beer ndcaor for predcng fuure reurns. I s no conssen wh many arcles, whch documen ha fuure daly reurns could be predced by daly order mbalances (Brown, Walsh and Yuen, 997; Chorda and Subrahmanyam, 24). In addon, he percenage of frms ehbng a conemporaneous relaonshp s abou welve mes han ha reflecng a feedback relaonshp, ndcang ha he neracon beween reurns and order mbalances on he curren perod s larger han ha over he whole perod. Fg.. es flow char of a mulple hypohess esng procedure able 7. Dynamc nesed causaly relaonshp beween reurns and order mbalances 2 < >2 2 2 < = > 2 Panel A: All sze All rade sze 3.2% 48.32% 9.4% 8.72% 3.36% Panel B: Frm sze Small frm sze 3.% 5.% 2.% 6.% 2.% Medum frm sze 34.69% 42.86% 4.8% 2.24% 6.2% Large frm sze 26.% 52.% 2.% 8.% 2.% In order o provde he evdence showng he mpac on he relaon beween reurns and order mbalances, n Panel B, we dvde frms no hree groups accordng o he frm sze. hen we es he mulple hypoheses of he relaonshp beween reurns and order mbalances. he resuls n Panel B ndcae ha he undreconal relaonshp from order mbalances o reurns s 6.% n he small frm sze quarle, whle he correspondng number s 8.% n he large frm sze quarle durng he enre sample perod. he rend of sze-srafed resul s no obvous. 44
Concluson Snce we beleve ha markes do no converge o effcency mmedaely durng ender offers and nvesors are able o earn abnormal reurns from eplong devaon of prces from fundamenal values. In our sudy, we eamne publc announcemen of ender offer o eplore he nraday relaon beween ender offer reurn, volaly and order mbalance. We fnd ha he mpacs of lagged one mbalance on reurns are negave for hree dfferen nervals. hs resul s nconssen wh Chorda and Subrahmanyam (24). he resul can be arbued o marke maker behavors because hey have enough nvenores o mgae he effecs from dscreonary nvesors n ender offers. hs s also confrmed by a low average reurn from ender offers. However, we fnd a conssen resul wh Chorda and Subrahmanyam (24) when we eamne condonal conemporaneous reurn-order mbalance relaon. In order o make sure ha volaly plays no role n reurn-mbalance relaon, we employ a me varyng GARCH (, o eamne relaon beween prce volaly and order mbalance. We epec a posve References Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 relaon beween prce volaly and order mbalances, bu he resuls come ou o be nsgnfcan. Moreover, we observe ha he mpacs of order mbalances on reurn volaly decrease wh he me nerval. Our sory s ha marke makers wh an nhered oblgaon o mgae marke volaly play a good role durng ender offer marke makng. Based on he emprcal resuls, we develop an mbalance based radng sraegy. We fnd ha an mbalance based radng sraegy radng on ransacon prce yelds a sascally sgnfcan posve reurn and ouperform he benchmark of orgnal daly reurns. We also employ a nesed causaly approach o eamne dynamc reurn-order mbalance relaon durng prce-formaon process. hs research could eend o oher corporae announcemen evens such as seasoned equy offerng or spn off socks. In addon, Barclay and Warner (993) and Anand and Chakravary (27) fnd ha mos of he cumulave sock prce change s due o medum-sze rades. herefore, f we focus on medum-sze rades, he performance of mbalance-based radng sraegy should be beer han ha on all-sze rades.. Agrawal, A. & Jeffrey, F.J. (2). he pos-merger performance puzzle, SSRN Elecronc Journal,, pp. 7-4. 2. Agrawal, A., Jaffe, F.J. & Mandelker, G.N. (992). he pos-merger performance of acqurng frms: A reeamnaon of an anomaly, Journal of Fnance, 47, pp. 65-62. 3. Ahn, H.J., Cao, C. & Choe, H. (2. Share repurchase ender offers and bd-ask spreads, Journal of Bankng and Fnance, 25, pp. 445-478. 4. Anand, A. & Chakravary, S. (27). Sealh radng n opons markes, Journal of Fnancal and Quanave Analyss, 42, pp. 67-88. 5. Aanassov, J. (23). Do hosle akeovers sfle nnovaon: Evdence from anakeover legslaon and corporae paenng, nnovaon, Journal of Fnance, 68, pp. 97-3. 6. Arnold,., Erwn, G., Nal, L. & Bos,. (2). Speculaon or nsder radng: nformed radng n opons markes precedng ender offers announcemens, Workng Paper, Unversy of Alabama a Brmngham. 7. Barclay, M.J. & Warner, J.B. (993). Sealh radng and volaly: Whch rades move prces, Journal of Fnancal Economcs, 34, pp. 28-35. 8. Bessembnder, H. & Zhang, F. (23). Frm characerscs and long-run sock reurns afer corporae evens, Journal of Fnancal Economcs, 9, pp. 83-2. 9. Bradley, M. (98). Iner-frm ender offers and he marke for corporae conrol, Journal of Busness, 53, pp. 345-376.. Bradley, M., Desa, A. & Han Km, E. (983). he raonale behnd nerfrm ender offers nformaon or synergy, Journal of Fnancal Economcs,, pp. 83-26.. Brown, P., Walsh, D. & Yuen, A. (997). he neracon beween order mbalance and sock prce, Pacfc-Basn Fnance Journal, 5, pp. 539-557. 2. Cao, C., Chen, Z. & Grffn, J.M. (25). Informaonal conen of opon volume pror o akeovers, Journal of Busness, 78, pp. 73-9. 3. Chen, C. & Wu, C. (999). he dynamcs of dvdends, earnngs and prces: Evdence and mplcaons for dvdend smoohng and sgnalng, Journal of Emprcal Fnance, 6, pp. 29-58. 4. Chorda,. & Subrahmanyam, A. (24). Order mbalance and ndvdual sock reurns: heory and evdence, Journal of Fnancal Economcs, 72, pp. 485-58. 5. Chorda,., Roll, R. & Subrahmanyam, A. (25). Evdence on he speed of convergence o marke effcency, Journal of Fnancal Economcs, 76, pp. 27-292. 6. Dodd, P. & Ruback, R. (977). ender offers and sockholder reurns, Journal of Fnancal Economcs, 5, pp. 35-373. 7. Dong, M., Hrshlefer, D., Rchardson, S. & eoh, S.H. (26). Does nvesor msvaluaon drve he akeover marke, he Journal of Fnance, 5, pp. 725-762. 8. Dua, S. & Jog, V. (29). he long-erm performance of acqurng frms: A re-eamnaon of an anomaly, Journal of Bankng and Fnance, 33, pp. 4-42. 45
Invesmen Managemen and Fnancal Innovaons, Volume, Issue 2, 24 9. Grossman, S.J. (975). On he effcency of compeve sock markes where rades have dverse nformaon, Journal of Fnance, 3, pp. 573-68. 2. Grossman, S.J. & Sglz, J.E. (98). On he mpossbly of nformaonally effcen markes, Amercan Economc Revew, 7, pp. 393-48. 2. Lee, C.M.C. & Ready, M.J. (99. Inferrng rade drecon from nraday daa, Journal of Fnance, 46, pp. 733-746. 22. Lebler, R.J. (997). ender offers o nfluenal shareholders, Journal of Bankng and Fnance, 2, pp. 529-54. 23. Loughran,. & Vjh, A.M. (997). Do long-erm shareholders benef from corporae acqusons, Journal of Fnance, 52, pp. 765-79. 24. Kanel, R., Lu, S., Saar, G. & man, S. (22). Indvdual nvesor radng and reurn paerns around earnngs announcemens, Journal of Fnance, 67, pp. 639-68. 25. Mandelker, G. (974). Rsk and reurn: he case of mergng frms, Journal of Fnancal Economcs,, pp. 33-336. 26. Marn, K.J. & McConnell, J.J. (99. Corporae performance, corporae akeovers, and managemen urnover, Journal of Fnance, 46, pp. 67-687. 27. Rau, R. & Vermaelen,. (998). Glamour, value and he pos-acquson performance of acqurng frms, Journal of Fnancal Economcs, 49, pp. 223-253. 46