When Two Anomalies meet: PostEarningsAnnouncement. Drift and ValueGlamour Anomaly


 Madison Owen
 1 years ago
 Views:
Transcription
1 Whe Two Aomalies mee: PosEarigsAouceme Drif ad ValueGlamour Aomaly By Zhipeg Ya* & Ya Zhao** This Draf: Sepember 009 Absrac I his paper, we ivesigae wo promie marke aomalies documeed i he fiace ad accouig lieraure  pos earigs aouceme drifs ad he valueglamour aomaly. Prior sudies show ha value ad glamour socks reac o earigs aoucemes differely ad earigs aouceme abormal reurs (EARs) are sigificaly relaed o posearigsaouceme drifs. This paper aims o lik he valueglamour aomaly direcly o he posearigsaouceme drifs. We firs sor firms io quiiles accordig o a measure of value. We he allocae firms io six caegories i erms of he sigs of he quarerly earigs surprise (+//0) ad he EARs (+/). We fid ha glamour socks are more volaile aroud earigs aouceme daes. The drif paers of value ad glamour socks are differe: glamour socks exhibi much larger egaive drifs followig egaive earigs surprises ad EARs, while value socks exhibi much larger posiive drifs followig posiive earigs surprises ad EARs. A radig sraegy of akig a log posiio i value socks whe boh EARs ad earigs surprises are posiive ad a shor posiio i glamour socks whe boh are egaive ca geerae 6.6% o8.8% aual reurs. This aomaly is maily a logside pheomeo. Preveig ivesors from shor sellig glamour socks will o preve ivesors from earig a value premium. * Ya: New Jersey Isiue of Techology, School of Maageme, Uiversiy Heighs, Newark, NJ 070, TEL: , FAX: **Zhao: Deparme of Ecoomics, Ciy College of New York, Elecroic copy available a: hp://ssr.com/absrac4866
2 . Iroducio The posearigsaouceme drifs ad he valueglamour aomaly are wo promie marke aomalies ha have bee iesely sudied i he fiace ad accouig lieraure. Prior sudies show ha value ad glamour socks reac o earigs aoucemes differely (Lakoishok e al. (LLSV), 997) ad earigs aouceme abormal reurs (EARs) are sigificaly relaed o posearigsaouceme drifs (Brad e al., 008). This paper aims o lik hese wo aomalies direcly by sudyig drifs of various value ad glamour porfolios; examie he differe drif paers of value ad glamour socks; ad desig a ew radig sraegy codiioal o he sig of he earigs surprise (+//0) ad he sig of he earigsaoucemeabormal reur (EAR, +/). The posearigsaouceme drif was firs documeed by Ball ad Brow (968). I is he edecy for sock prices coiue o move i he direcio of he earigs surprise up o a year afer earigs are aouced. Tha is, if a firm s aouced earigs exceed (fall below) he marke expecaio, he subseque abormal reurs o is socks are usually above (below) ormal for mohs. This predicabiliy of sock reurs afer earigs aoucemes had araced subsaial research ad has bee documeed cosisely i umerous papers over he decades. Redlema e al. (98), Foser e al. (984), Berard ad Thomas (989) ad Liva ad Medehall (006) are amog he may who replicae he pheomeo wih large scale sample ses. They show ha a log posiio i socks wih uexpeced earigs i he highes decile, combied wih a shor posiio i socks i he lowes decile, yields high abormal reurs. There is a sizeable lieraure aempig o explai he drifs. Ivesor learig (Chordia ad Shivakumar, 006), disclosures (Shi, 005), idiosycraic sock reur volailiy (Medehall, 004), iformaio uceraiy (Fracis e al., 007), liquidiy (Chordia, e al. i press), ad so o are provided as explaaios for drifs. The value ad glamour aomaly refers o he empirical regulariy ha fuure reurs of value socks ouperform he glamour socks (Graham ad Dodd, 934; Lakoishok, Shleifer, ad Vishy (LSV), 994 ad Fama ad Frech (FF), 99). Value socks are Elecroic copy available a: hp://ssr.com/absrac4866
3 ouoffavour socks which are perceived o have low growh poeial. These socks usually have low prices relaive o earigs, divideds, book value, or oher measures of value. O he oher had, glamour socks are socks which are perceived o have high growh poeial, ad are characerized by srog pas performace ad high prices relaive o value. Several explaaios have bee provided o explai he reur differeial bewee value socks ad growh socks. FF (99, 996) argue ha value sraegies are fudameally riskier. I heir view, he higher average reurs of value socks reflec compesaio of risk. LSV (994) ad LLSV (997), however, aribue he superior fuure performace of value socks o he assumpio ha ivesors make sysemaic errors i predicig fuure growh i earigs of ouoffavour socks. Fially, Fama (998) ad Kohari, Sabio, ad Zach (999) claim ha he reur differeial may reflec mehodological problems wih he measureme of logerm abormal reurs. Several sudies ry o explai he valueglamour aomaly by ivesigaig he reur differeial bewee value ad growh socks aroud quarerly earigs aouceme daes. LLSV (997) fid ha sizeadjused EARs are subsaially higher for value socks ha for glamour socks ad he reur differeial accous for up o abou 30 perce of he aual value premium repored i prior sudies. Skier ad Sloa (00) show ha growh socks perform similarly o oher socks i respose o posiive earigs surprises, bu ha growh socks exhibi a much larger egaive respose o egaive earigs surprises. Afer corollig for he asymmeric respose of growh socks o egaive earigs surprises, here is o loger evidece of a sock reur differeial bewee growh socks ad oher socks. A few relaed sudies, hough do o direcly address he valueglamour aomaly, fid ha he EARs are sigificaly relaed o he posearigsaouceme drifs. By sorig firms o EARs, boh Cha e al. (996) ad Brad e al. (008) repor ha he porfolios wih higher EARs geerae subsaially larger drifs ha he porfolio wih lower EARs. A aural coclusio draw from he fidigs of hese sudies is: if value socks reac o earigs aoucemes differely from glamour socks ad if EARs are sigificaly Doukas, Kim ad Pazalis (00) fail o fid evidece supporig he exrapolaio hypohesis. 3
4 relaed o posearigsaouceme drifs, he he drif paers of value socks mus be differe from hose of glamour socks. This is he focus of his sudy. We aim o ivesigae he drif paers of various value ad glamour porfolios ad desig a profiable radig sraegy ha ca capure abormal reurs iroduced by hese wo aomalies. The posearigsaouceme drifs demosrae ha he iformaio i he earigs has predicive power  if acual earigs differ from expeced earigs, he marke ypically reacs i he same direcio. I real life, however, we ofe observe ha he direcio of he earigs aouceme abormal reur is opposie o ha of earigs surprise,3. The exisece of oher iformaio raher ha earigs aroud earigs aouceme daes may lead o his wrog marke reacio (Liu ad Thomas, 000; Jegadeesh ad Liva, 006). This is oe of he reasos for he low explaaory power of earigs surprises for drifs (Kiey, Burgsahler, ad Mari (00)). By explorig he posearigsaouceme drifs of value ad glamour porfolios uder six differe caegories i erms of he sigs of he EARs (+/) ad earigs surprises (+//0), we ca separae groups of observaios where earigs surprises ad EARs move i he same direcio from oher groups; ad we fid posearigsaouceme drifs of boh value ad glamour socks are amplified. We have a umber of ew fidigs i his paper: ) Glamour socks are more volaile aroud earigs aouceme daes. Whe EARs are posiive, glamour socks have higher EARs (more posiive) ha value socks. Whe EARs are egaive, glamour socks have lower EARs (more egaive) ha value socks. For example, Apple Compuer Ic. released quarerly earigs o Ja 7, 00. Alhough he earigs were below expecaios, aalyss were cheered by ews ha he compay had sharply cu iveories of compuers o reailers' shelves. Apple's shares, jumped perce he followig day. The Wall Sree Joural, More Quesios Abou Opios for Apple, Augus 7, For aoher example, o May 4, 006, Procer & Gamble Co. repored e sales rose perce o $7.5 billio, ad earigs rose o 63 ces a share for he quarer eded March 3, which was higher ha expeced earigs of 6 ces a share. However, aalyss surveyed by Thomso Fiacial had expeced higher sales of $7.6 billio. A he ed of he day, ivesors se P&G shares umblig, disappoied ha sales ad he compay's oulook fell shor of aalyss' expecaios. he Eveig Wrap, May 4,
5 ) Whe boh EARs ad earigs surprises are posiive, value socks have bigger posiive drifs ha glamour socks. Whe boh are egaive, glamour socks have bigger egaive drifs ha value socks. Whe EARs ad earigs surprises move i differe direcios, he drif paers are mixed ad smaller i magiude. 3) A radig sraegy of akig a log posiio i value socks whe boh earigs surprises ad EARs are posiive ad a shor posiio i glamour socks whe boh are egaive ca geerae almos wice he quarerly abormal reur ha he commoly used value ad growh sraegy which akes a log posiio i value socks ad a shor posiio i glamour socks wihou codiioig o he sigs of EARs ad earigs surprises. 4) We explore four valueglamour proxies by usig bookomarke raio (BM), earigsoprice raio (EP), cash flowoprice raio (CP) ad pas growh i sales (SG). We fid cosise of drif paers for value ad glamour socks. Our paper coribues o he lieraure by relaig posearigsaouceme drifs wih he valueglamour aomaly, ad ehacig he drifs for he valueglamour ivesig by codiioig o he sigs of earigs surprise ad EARs. The res of he paper is orgaized as follows: Secio explais he sample selecio ad mehodology; Secio 3 preses he empirical fidigs; Secio 4 coducs he robusess checks; ad Secio 5 cocludes.. Sample selecio ad mehodology The mea aalys forecass, quarerly earigs per share (EPS), earigs aouceme daes ad acual realized EPS are ake from he IsiuioalBrokersEsimaeSysem summary saisics files (I/B/E/S). Our sample period rus from Jue 984 o December 008 ad we iclude all he firms from I/B/E/S durig his period. We mach he earigs forecass for each compay wih sock daily reurs. The reurs are provided by he Ceer for Research o Securiy Prices a he Uiversiy of Chicago. Care is ake o adjus for divideds, sock splis ad sock 5
6 divideds so ha all curre ad pas reurs, earigs figures, ad forecass are expressed o a comparable basis. The BM, EP, CP ad SG are compued usig daa from Compusa aual file ape. Prior sudy (FF, 99) shows he abormal reurs vary accordig o firm size, o corol he firmssize effec; we use valueweighed reurs o e FamaFrech socks formed o size as bechmark reurs o compue he abormal reurs. We explicily avoid usig a bechmark which adjuss for he bookomarke effec, because our objecive o sudy he bookomarke effec ogeher wih he posearigsaouceme drifs. All he bechmark reurs ad breakpois of each decile are ake from Keeh Frech s olie daa library.. Esimaio of EARs, Earigs surprise ad posearigsaouceme drifs Followig LLSV (997), we measure EARs as he equallyweighed sized adjused abormal reurs i a 3day widow ceered o he earigs aouceme dae. + + EAR i (. ) (. ), q = + Ri + Rb EARi,q is he EARs for firms i i quarer q recorded over a 3day widow ceered o he aouceme dae. We cumulae reurs uil oe day afer he aouceme dae o accou for wo reasos. Oe is for he possibiliy of firms aoucig earigs afer he closig bell. The oher is for he possibiliy of delayed sock price reacios o earigs ews, paricularly sice our sample icludes NASDAQ issues, which may be less frequely raded (Cha, Jegadeesh ad Lakoishok,996). R i, is he daily reur for firms i i day. R b, is he daily valueweighed bechmark reur o FamaFrech size porfolio o which sock i belogs. The e FamaFrech size socks are cosruced a he ed of each Jue usig he Jue marke equiy ad NYSE breakpois. Earigs surprises are measured as he differece bewee acual ad expeced EPS divided by he absolue value of expeced EPS 4 : 4 This defiiio is he same as ha used by Zacks Ivesme Research, 6
7 EarigsSurprise i, q = Acual abs Expeced i, q ( Expecedi, q ) i, q Where, Acuali,q is he acual EPS aouced o he earigs aouceme dae for firms i i quarer q, ad Expecedi,q is he mea aalys forecas of EPS for firms i i quarer q. Size adjused posearigsaouceme drifs are calculaed i a similar maer o he calculaio of EARs: Drif, = ( + R. ) (+ Rb. ) i i Where Drif i, is he sized adjused cumulaive abormal reur for firm i from he secod day o he h day afer he aouceme.. Compuaio of BM, EP, CP ad SG Followig LSV (994), we use four empirical proxies o capure he valueglamour effec: BM, EP, CP ad SG. We compue he BM as he raio of he fiscal yeared book value of equiy o he marke value of equiy. EP is he operaig icome afer depreciaio scaled by he marke value of equiy. CP is he cash flow from operaios scaled by he marke value of equiy. We measure he SG as he average of aual growh i sales over he previous hree years. Size is he marke value a he ed of Jue of each year. Marke value of equiy is defied as commo shares ousadig muliplied by price per share. Cosise wih LSV (994) ad Desai, Rajgopal ad Vekaachalam (DRV, 004), we do o remove firms wih egaive EP ad CP raios because he umber of firms akig oeime charges o earigs has icreased subsaially i rece years leadig o sigifica egaive earigs observaios (Collis, Picus ad Xie, 999). I fac, elimiaio of egaive EP ad CP firms would resul i losig approximaely 0% of he sample. Neverheless, our resuls are robus o excludig egaive values of EP ad CP raios. We do elimiae firms wih egaive bookomarke raios. 5 Our resuls are o, 5 Ja ad Ou (008) fid ha he frequecy ad he magiude of egaive book value of equiy have 7
8 however, sesiive o he iclusio of such firms..3 Socks assigme We firs examie he posearigsaouceme drifs for he valueglamour porfolios. A he ed of each Jue from 984 o 008, 0 porfolios are formed based o four valueglamour proxies i ascedig orders. Value socks refer o socks rakig highes o BM, EP, CP ad rakig lowes o SG. Glamour socks refer o socks rakig lowes o BM, EP, CP ad rakig highes o SG. We furher impleme he valueglamour radig sraegy by codiioig o he sigs of earigs surprise (+//0) ad EARs (+/). A he ed of each Jue from 984 o 008, we sor socks io quiiles based o four valueglamour proxies. Afer he sorig, each sock has a ag of which quiile i is i. We he allocae each sock io six subsamples i erms of he sigs of earigs surprises(+//0) ad EARs(+/): boh are posiive; boh are egaive; posiive earigs surprises ad egaive EARs; egaive earigs surprises ad posiive EARs; zero earigs surprises ad posiive EARs, zero earigs surprises ad egaive EARs. I his way, he valueglamour socks are predeermied a he ed of each Jue, o maer wha he followig earigs surprises ad EARs aroud he earigs aoucemes are. We examie he drif paers i each subsample i he subseque periods, sarig from he secod day afer he earigs aouceme up o moh ( radig days), 3 mohs (63 radig days), 6 mohs (6 radig days), 9 mohs (89 radig days) ad year (5 radig days) afer he earigs aouceme. For readers ieresed i a implemeable radig sraegy, we also look a he drif sarig from he secod day afer curre quarer s earigs aouceme day ad edig o he d day prior o he ex quarer s earigs aouceme 6. Sice his drif is almos he same as he 3moh (63 radig days) drif, we do o repor he relaed grow subsaially over ime. R&D, especially R&D cumulaed over ime, o oly coribues o he icreasig red of egaive book value icideces bu also plays a impora role i he marke's valuaio of hese firms. 6 Tha drif is over a roughly 3moh widow ( q +, q+ ), where q represes quarer Q ad represes earigs aouceme day. 8
9 resuls for he sake of simpliciy..4 Summary saisics Pael A of Table repors summary saisics for key variables for he sample period bewee Jue 984 ad December 008. There are 43,07 firmsquarer observaios durig he sample period. To reduce ifluece of exreme values, all he values are wisorized a % ad 99% 7. The mea of EARs is 0.% ad he media is 0.09%, which implies he disribuio is posiively skewed. Quarerly earigs surprise, o he oher had, is egaively skewed, wih he mea of 0.5% ad he media of.%. The meas of BM, EP, CP, ad SG are 0.58, 0.08, 0.3, ad 0.38, respecively. Boh meas ad medias of hese value measures i our sample are smaller ha hose i DRV (004). We believe he differeces are largely due o differe sample periods ad wisorizaio 8. The correlaio marix i Pael B suggess several ieresig paers. The correlaio bewee BM ad size is large ad egaive (Pearso correlaio is 0. ad Spearma correlaio is Boh sigifica a % level), he correlaio bewee EP ad size is small ad posiive, while he correlaio bewee CP ad size is close o zero (Pearso correlaio is 0 ad o sigifica, while Spearma correlaio is 0.0 ad sigifica), ad he correlaio bewee SG ad size is small ad egaive. This idicaes ha a small firm may be a value firm i erms of BM, bu a growh firm accordig o is EP or SG. Secodly, EP ad CP are highly correlaed wih each oher (Pearso correlaio is 0.87 ad Spearso correlaio is 0.9), which is cosise wih he fidigs of DRV (004), who claim ha CP as measured by he fiace lieraure is esseially EP i disguise. Table coais he umber ad frequecy of oal firmsquarer observaios i 7 Oe cavea abou wisorizaio: if he disribuio of a variable is o symmeric aroud zero, wisorizaio will affec he mea ad sadard deviaio of he disribuio. For example, i heory, he smalles daily reur is  ad sice he bechmark porfolios are much less volaile ha a sigle sock, he smalles daily abormal reur cao be far below . I fac, durig our sample period, he smalles daily reur for ay size porfolio is 9.7%. O he oher had, he larges daily reur ca be very large. Acually, he larges oe day icrease i sock price is 90% durig he sample period. Therefore, wisorizaio makes mea reurs smaller. 8 To our udersadig, DRV (004) did wisorize variables for Table. 9
10 each subsample over our sample period. Six subsamples are formed accordig o differe sigs of earigs surprises (+//0) ad EARs (+/). Pael A shows he oal umber of observaios i each subsample. Pael B shows he frequecy of oal observaios i each caegory. I oal, abou 53.% of observaios have EARs ad earigs surprises ha move i he same direcio; 35.4% of observaios have boh ha move i he opposie direcio; ad for he res of observaios, he earigs surprises are equal or close o zero (0 or less ha 0.00). 4.% of observaios have posiive EARs whe earigs surprises are egaive ad.3% of observaios have egaive EARs whe earigs surprises are posiive. Three possible explaaios ca be provided for hese wo ypes of aomalies. Firs, hese may be some exraordiary good (bad) iformaio beyod earigs for a sock o have a posiive respose o he egaive (posiive) earigs surprise; Secod, ivesors have updaed expeced earig ad prospecs for he firm bewee whe aalyss are surveyed ad whe he earigs are aouced (sale earigs forecas); Third, he aouced earigs may be a flawed measure if i is coamiaed by oe ime iems ha lack persisece (Johso ad Zhao (007)). Whe earigs surprises ad EARs move i he same direcio, here are also hree possibiliies. Firs, o ews bu earigs iformaio is aouced. Secod, some oher posiive (egaive) iformaio, ogeher wih posiive (egaive) earigs surprises, is revealed ad reiforces earigs surprises. Lasly, some oher posiive (egaive) iformaio is released, alog wih egaive (posiive) earigs iformaio, bu i is o srog eough o overur he impac of earigs surprises. Table also reveals a ieresig resul: he umber of firms wih posiive EARs is very close o he umber of firms wih egaive EARs (47.9% vs. 5.%), while, o he oher had, he umber of firms wih posiive or o earigs surprises is sigificaly larger ha he umber of firms wih egaive earigs surprises (6% vs. 38%). Oe possible explaaio o hese asymmerical earigs surprises is ha, faced wih iese pressure o mee earigs esimaes from aalyss ad ivesors, execuives may 0
11 someimes mage earigs over accouig periods o achieve or bea he forecas resul. Foruaely, he marke is o fooled as evideced by roughly equal umber of posiive ad egaive resposes o earigs surprises. 3. Empirical Evidece 3. posearigsaouceme drifs for valueglamour socks To provide a bechmark ad compariso for our aalysis i he subseque secios, we firs provide descripive evidece o he relaio bewee he valueglamour effec ad he posearigsaouceme drifs. A he ed of each Jue from 984 o 008, 0 porfolios are formed based o valueglamour proxies, amely BM, EP, CP, ad SG. Value porfolios coai socks ha have highes BM, EP ad CP ad lowes SG. Glamour porfolios coai socks ha have lowes BM, EP ad CP ad highes SG. We he calculae he moh, 3moh, 6moh, 9moh ad year drifs for each decile porfolio. Pael A of Table 3 repors resuls o posearigsaouceme drifs for value ad glamour porfolios based o BM classificaio. Firs of all, he 3day, buyadhold EARs are higher for he value porfolio ha for he glamour porfolio. The average 3day EARs is 0.08% for he glamour porfolio ad 0.3% for he value porfolio. The value porfolio has he larges posiive drifs, while he glamour porfolio has he larges egaive drifs. For example, he average 3moh drifs icrease moooically from 0.3% for he glamour porfolio o.0% for he value porfolio. This spread of.4% is sigifica a 5% level. This fidig is cosise wih Skier ad Sloa (00). This moooic paer exiss i all oher holdig periods. Furhermore, he magiude of drifs is asymmeric for value ad glamour socks. The absolue values of he drifs of he value porfolio are sigificaly greaer ha he absolue values of hose of he glamour porfolio. Thus, he spread bewee he value ad glamour porfolios maily comes from he abormal reurs of value socks. This is cosise wih Phalippou (008). For example, he average 3moh drif of.0% for he value porfolio accous for 8% of spread of.4%. O average, across all differe holdig periods, he drifs for he value
12 porfolio accou for 80% of he spreads. Fially, he drifs of glamour socks cumulae a a slower pace ha he value socks 6 mohs afer he earigs aoucemes. For example, he 9moh drif for he value porfolio is 4.43% which is 74% higher ha he 6moh drif of.54%; while he 9moh drif for he glamour porfolio is .4% which is 3% lower ha he 6moh drif of.08%. This shows he price correcio for he value socks is subsaially more dramaic eve 6 mohs afer earigs aoucemes ha he glamour socks. Table 3 Pael B, C, ad D repor resuls o posearigsaouceme drifs for value ad glamour porfolios based o EP, CP ad SG classificaios. The drif paers are very similar o hose i Pael A. We sill see clear evidece of he valueglamour effec i drifs. The average drifs icrease gradually, hough o ecessarily moooically, from glamour porfolios o he value porfolios. The spreads of value ad glamour porfolios are all saisically sigifica. Ad agai, he spreads bewee he value ad glamour porfolios maily come from he abormal reurs of value socks; drifs of glamour socks cumulae a a slower pace ha he value socks 6 mohs afer he earigs aoucemes. 3. Valueglamour drifs codiioal o sigs of EARs ad earigs surprises Table 4 repors posearigsaouceme drifs for valueglamour ivesig based o BM classificaio. A he ed of each Jue of year, we sor firms io quiiles usig he BM raio. The value socks are i he highes quiile of he BM raio ad he glamour socks are i he lowes quiile of he BM raio. I each quarer (durig he period of July of year o Jue of year +), we allocae each sock io oe of he six subsamples based o he sigs of he sock s EARs (+/) ad earigs surprise (+//0). For example, a value sock may have posiive earigs surprise ad posiive EAR i oe quarer ad have egaive earigs surprise ad posiive EAR i aoher quarer. Our goal is o ivesigae wheher value ad glamour socks have differe posearigsaouceme drifs codiioal o he sigs of EARs ad earigs surprises. Several ieresig resuls warra deailed discussio.
13 Firs of all, he posearigsaoucemedrif aomaly is evide i our sample. Mos drifs are posiive whe earigs surprises are posiive (Pael A ad Pael D) ad mos drifs are egaive whe earigs surprises are egaive (Pael B ad Pael C). I seems ha sock prices coiue o move i he direcio of he earigs surprise for a exeded period of ime afer earigs are aouced. Secodly ad more ieresigly, glamour socks are more volaile durig he 3day aouceme widow ha value socks. Whe EARs are posiive (Pael A, C ad E), regardless of he sigs of earigs surprises (+/0/), glamour socks have higher posiive 3day EARs. O he oher had, whe EARs are egaive (Pael B, D ad F), glamour socks have more egaive 3day EARs. This fidig is differe from, hough o ecessarily icosise wih, he evidece from LLSV (997), who fid ha earigs aouceme reurs are sysemaically more posiive for value socks, by poolig all firms ogeher, wihou cosiderig he sigs of EARs ad earigs surprises. Our fidig reveals ha if EARs are posiive, glamour socks have larger posiive EARs ha value socks; whe EARs are egaive, glamour socks have larger egaive EARs ha value socks. This resul is raher iuiive. Value socks are ouoffavour socks ha have low sock prices relaive o pas growh ad fudameals, while glamour socks are favourable socks for ivesors; hus here are more aalyss followig glamour socks ha value socks. I fac, he Pearso correlaio bewee he BM ad he umber of aalyss followig is 0.9, which is sigifica a % level. The sigifica egaive correlaio shows socks wih low BM (glamour socks) have more aalyss followig. Thus, ay deviaio from he aalyss expecaio may lead o bigger marke resposes durig he 3day earigs aouceme widow. Thirdly, across all he paels, he valueglamour effec is emie  he value porfolios always have higher abormal reurs ha he glamour porfolios. They eiher have larger posiive drifs or have smaller egaive drifs. I Pael A, whe EARs ad earigs surprise are posiive, value socks have lower posiive EARs ad larger posiive subseque drifs ha glamour socks. Value socks are ouoffavour socks followed by fewer aalyss ha glamour socks. Thus he 3
14 immediae marke reacios (EARs) o he earigs surprise are smaller ha glamour socks ad may be due o he less aeio. Limied aeio ca cause ivesors o igore useful iformaio aroud earigs aouceme daes; herefore, hey are uable o isaaeously icorporae he ews io prices. This leads o sock price uderreacio. Prices coiue o drif i he same direcio of he earigs ews afer he aoucemes as he iformaio gradually ges impouded io prices (Hirshleifer, 003; Hou, Peg, ad Xiog, 008; Dellaviga ad Polle, 008). Tha is why he subseque drifs are larger for value socks ha for glamour socks. I Pael B, however, he sory is oally differe. Whe boh EARs ad earigs surprise are egaive, glamour socks have higher egaive EARs ad larger egaive subseque drifs ha value socks. I seems ha aeio effec is o a domia facor ay more (a leas pos earigs aoucemes) whe glamour socks have egaive earigs surprises. Glamour socks are favourable socks for ivesors ad are followed by more aalyss ha value socks. Ay deviaio from he aalyss expeced may lead o bigger marke resposes (EARs) durig he 3day earigs aouceme widow. Furhermore, he fac ha missig aalyss forecass, eve by small amous, causes disproporioaely large sock price declies eve i he subseque periods (Skier ad Sloa, 00). Ivesors coiue o puish misshearge glamour socks up o year afer earigs aoucemes. Thirdly, we ca easily desig a profiable radig sraegy based upo our fidigs. Whe EARs ad earigs surprises are boh posiive (Pael A) value socks have he larges posiive drifs across all paels. Whe boh are egaive (Pael B) glamour socks have he larges egaive drifs across all paels. A radig sraegy of akig a log posiio i he value porfolio i Pael A ad a shor posiio i he glamour porfolio i Pael B ca geerae 4.68% quarerly abormal reurs. Thus, by separaig socks where EARs ad earigs surprises move i he same direcio from oher groups, ad we fid posearigsaouceme drifs are amplified. Figure shows he hreemoh (63 radig days) abormal reurs o a sraegy akig a log posiio i value socks whe boh earigs surprises ad EARs are posiive 4
15 ad akig a shor posiio i glamour socks whe boh are egaive. We employ quarerly earigs aouceme daa i our aalysis. Tha is, we review ew iformaio every quarer ad cosruc our hedge porfolios quarerly. The aualized mea reur i he sample period is 8.73% before rasacio coss. We icur losses i.05% of quarers i our sample periods 9. The hedge porfolio s reur mosly comes from he logside (he value porfolio) ad o a lesser degree from he shorside (he glamour porfolio). This is cosise wih Phalippou (008) who fids ha he value premium is a logside aomaly ad i is a value premium puzzle, o a growh discou puzzle. Thus, his sraegy has relaively less severe cosrais i erms of shorig socks. Whe EARs ad earigs surprised move i differe direcio, he resuls are show i Pael C ad D. we sill observe he drifs, bu due o he wo opposie sigals, he magiude of he drifs are smaller ha hose i Pael A ad B. Fially, we look a he special groups of he firms wih o earigs surprises (Pael E ad F). The drifs are ormally egaive across quiiles, which migh idicae ha faced wih iese pressure o mee earigs esimaes from aalyss ad ivesors, he execuives i hese firms may maage earigs over accouig periods o achieve he forecased resul. However, he subseque egaive drifs reflec he firms rue sauses ha he firms operaio is o as good as he earigs iformaio shows. 3.3 Posearigsaouceme drifs usig oher value proxies Table 57 repor posearigsaouceme drifs for value ad glamour socks based o hree oher value proxies: EP, CP, ad SG. Whe usig SG, we ake a special sep o exclude socks wih oposiive earigs. A impora issue usig SG o defie value socks is ha firms wih he lowes pas sales growh raios may o all be value socks, some of hem may be issued by saga firms whose fuure reurs are o promisig. To 9 Two cavea for readers who pla o impleme his sraegy i heir radig. Firs, sice o all firms aouce quarerly earigs o he same day, a ivesor has o dyamically balace his porfolio. Foruaely, sice we kow wheher a sock is a value sock or a glamour or ohig beforehad, as log as he sigs of is earigs surprise ad EAR are available (boh are available a he ed of he secod day afer he earigs aouceme), we should be able o kow wheher o log or shor he sock or do ohig. Secodly, ou of 95 quarers, his sraegy geerae raher large egaive reurs (he loss is greaer ha 0%). We sugges readers moior he porfolio closely ad pu some risk corol mechaisms i place. 5
16 differeiae hese saga firms from value firms, we require firms mus have posiive earigs o be cosidered as value firms. Agai, we defie glamour socks as socks rakig highes o EP or CP, ad lowes o SG; value socks as socks rakig lowes o EP or CP, ad highes o SG. The drif paers are mosly cosise wih our fidigs i Table 4 whe we use BM as a measure of value. Glamour socks have very large absolue values of EARs ad are more volaile durig he 3day aouceme widow. Whe EARs ad earigs surprises are boh posiive (Pael A) value socks have he larges posiive drifs across all paels. Whe boh are egaive (Pael B) glamour socks have he larges egaive drifs across all paels. By separaig socks where EARs ad earigs surprises move i he same direcio from oher groups, ad we agai fid posearigsaouceme drifs are amplified, which is illusraed i Figure 4. Figure shows he hreemoh (63 radig days) abormal reurs o a sraegy based o EP classificaio. The aualized mea reur is 7.9% before rasacio coss. The icidece of losses is 6.3% ad he aualized Sharpe raio is Figure 3 ad 4 show he aualized mea reur is 8.85% or 6.6% whe we use CP or SG as a value proxy. Oe aomaly we eed o poi ou is ha whe usig SG as a value measure ad whe boh earigs surprises ad EARs are posiive, he posearigsaouceme drifs of he value porfolio is slighly smaller ha ha of he glamour porfolio whe ime period is loger ha moh. This is icosise wih our fidigs wih oher value proxies. However, he differece of he drifs bewee he wo porfolios is o sigifica. Moreover, we suspec ha previous sales growh rae aloe ca capure he real differece bewee value socks ad glamour socks. Sudies i firm life cycle reveal ha firms over leghy periods ofe fail o exhibi he commo life cycle progressio exedig from birh o declie (Liu, 008; Ahoy ad Ramesh, 99; ad Miller ad Friese, 984). A maure, less glamour firm, may revive or eve grow fas agai. This migh be he reaso for LLSV (997) o use a CP ad GS woway classificaio. However, o be cosise wih LSV (994) ad o illusrae he differeces amog commoly used value proxies, we decide o ivesigae each proxy separaely. I a urepored able, we use he same 6
17 woway classificaio ad he resuls are exacly cosise wih hose i Table Robusess checks 4. Porfolios formed usig socks from differe exchages Our porfolios formed above iclude socks from four differe securiies exchages: NYSE, NASDAQ, Alerex, ad NYSE Arca. As show i Table 8, NYSE socks accou for 47% of oal observaios. The socks lised i NYSE are sigifica larger ha socks lised i oher exchages (53% of oal observaios). I his secio, we examie wheher he drif paers are robus i differe exchages. Table 9 show he porfolio drifs i NYSE ad onyse exchages. The drif paers are similar o he previous discussio i boh exchages, bu he magiude of drifs is differe. There is o cosise evidece o show he spreads bewee value ad glamour socks are bigger i oe exchage over he oher. For he spreads based o BM ad SG, he differece bewee he spreads over moh holdig period i he NYSE ad onyse are o saisically differe; while he spreads over 3moh, 6moh, 9moh ad year i he onyse are sigificaly higher ha he spreads over he same periods i he NYSE. For he spreads based o EP ad CP classificaios, he differece bewee he spreads over moh, 3moh ad 6moh holdig periods i he NYSE ad onyse agai are o saisically differe; while he spreads over 9moh ad year i onyse are sigificaly lower ha he spreads over he same periods i he NYSE. 4. Oher robusess checks We also use 5day Earigsaoucemeabormal reurs (from day o day+) isead of 3day Earigsaoucemeabormal reurs, employ differe bechmark  S&P 500 idex reurs while compuig cumulaive abormal reurs, form porfolios o he sixh radig day 0 afer earigs aoucemes isead of he secod radig day, elimiae egaive values of earigsoprice raios ad cashflowoprice raios. All he 0 Tha is o say, we wai for 5 days afer earigs aoucemes o ake acio. 7
18 mai resuls remai he same. 5. Coclusio We are moivaed by wo promie marke aomalies documeed i fiace ad accouig lieraures: he valueglamour aomaly popularized by LSV (994) ad posearigsaouceme drifs firs documeed by Ball ad Brow (968). The goal of his paper is o lik hese wo aomalies direcly by sudyig drifs of various value ad glamour porfolios; examie he differe drif paers of wo ypes of socks; ad desig a ew radig sraegy codiioal o he sigs of earigs surprises ad EARs. We fid ha glamour socks are more volaile aroud earigs aouceme daes. Value porfolios almos always have higher pos earigs abormal reurs ha glamour porfolios regardless of he sigs of earigs surprises ad EARs. They eiher have more posiive drifs or have less egaive drifs. A radig sraegy of akig a log posiio i value socks whe boh earigs surprises ad EARs are posiive ad a shor posiio i glamour socks whe boh are egaive ca geerae 6.6% o8.8% aual reurs before rasacio coss. This aomaly is maily a logside pheomeo; preveig ivesors from shor sellig glamour socks will o preve ivesors from earig a value premium. We furher explore differe defiiios of value ad glamour socks by usig BM, EP, CP, ad SG, ad fid drif paers are cosise. 8
19 Referece Ahoy, J., Ramesh, K., 99. Associaio bewee Accouig Performace Measures ad Sock Prices. Joural of Accouig ad Ecoomics 5, 037 Ball, R., Brow, P., 968. A Empirical Evaluaio of Accouig Icome Numbers. Joural of Accouig Research 6, Berard, V., Thomas, J., 989. Posearigsaouceme Drif: Delayed Price Respose or Risk Premium? Joural of Accouig Research 7, 48. Brad, M., Kishore, R., SaaClara, P., Vekaachalam, M., 006. Earigs Soucemes are Full of Surprises. Workig paper (Duke Uiversiy). Cha, L., Jegadeesh, C., Lakoishok, J., 996. Momeum Sraegies. Joural of Fiace 5, Chordia, T., Goyal, A., Sadka, G., Sadka, R., Lakshmaa, S., Liquidiy ad he Posearigsaouceme Drif. Fiacial Aalyss Joural, forhcomig. Chordia, T., Shivakumar, L., 006. Earigs ad Price Momeum. Joural of Fiacial Ecoomics 80, D. Collis, Picus, M., Xie, H., 999. Equiy Valuaio ad Negaive Earigs: The Role of Book Value of Equiy. The Accouig Review 74, 96. DellaViga, S., Polle, J., 008. Ivesor Iaeio ad Friday Earigs Aoucemes. Joural of Fiace, forhcomig. Desai, H., Rajgopal, S., Vekaachalam, M., 004. ValueGlamour ad Accruals Mispricig: Oe Aomaly or Two? The Accouig Review 79, No. : Fama, E., 998. Marke Efficiecy, Logerm Reurs, ad Behavioral Fiace, Joural of Fiacial Ecoomics 49, Fama, E., Frech, K., 99. The Crosssecio of Expeced Sock Reurs. Joural of Fiace 46, Fama, E., Frech, K., 996. Mulifacor Explaaios of Asse Pricig Aomalies. Joural of Fiace 5, Foser, G., Olse, J., Shevli, T., 984. Earigs Releases, Aomalies, ad he Behavior of Securiy Reurs. The Accouig Review 59, Fracis, J., LaFod, R., Olsso, P., Schipper, K., 007. Iformaio Uceraiy ad he Posearigsaouceme Drif. Joural of Busiess Fiace & Accouig 34, 34, Graham, B., Dodd, D., 934. Securiy Aalysis. McGraw Hill, New York. Hirshleifer, D., Teoh, S., 003. Limied Aeio, Fiacial Reporig ad Disclosure, Joural of Accouig ad Ecoomics 36, Hou, K., Peg, L., Xiog, W., 008. A Tale of Two Aomalies: The Implicaios of Ivesor Aeio for Price ad Earigs Momeum. Workig paper (Ohio Sae Uiversiy). 9
20 Ja, C., Ou, J., 008. Negaive Book Value Firms ad Their Valuaio. Workig paper (Califoria Sae Uiversiy, Eas Bay). Jegadeesh, N., Liva, J., 006. Posearigsaouceme Drif: he Role of Reveue Surprises. Fiacial Aalyss Joural 6,, 34. Johso, B., Zhao, R., 007. Coraria Share Price Reacios o Earigs Surprises. Workig paper (Uiversiy of Iowa). Kiey, W., Burgsahler, D., Mari, R., 00. Earigs Surprise Maerialiy as Measured by Sock Reurs. Joural of Accouig Research 40, 5, Kohari, P., Sabio, S., ad Zach, T., 999. Implicaios of Daa Resricios o Performace Measureme ad Tess of Raioal Pricig. Workig paper (Massachuses Isiue of Techology). La Pora, R., Lakoishok, J., Shleifer, A., Vishy, R., 997. Good News for Value Socks: Furher Evidece o Marke Efficiecy. Joural of Fiace 5, Lakoishok, J., Shleifer, A., Vishy, R., 994. Coraria Ivesme, Exrapolaio, ad Risk. Joural of Fiace 49, Liva, J., Medehall, R., 006. Comparig he Pos earigs aouceme Drif for Surprises Calculaed from Aalys ad Time series forecass. Joural of accouig research 44, Liu, M., 008. Accruals ad Maagerial Operaig Decisios over he Firm Life Cycle. Workig paper (Pesylvaia Sae Uiversiy). Liu, J., Thomas. J., 000. Sock Reurs ad Accouig Earigs. Joural of Accouig Research 38, 70. Medehall, R., 004. Arbirage Risk ad Posearigsaouceme Drif. Joural of Busiess 77, Miller, D., Peer, F., 984, A Logiudial Sudy of he Corporae Life Cycle. Maageme Sciece 30, 0, 683 Phalippou, L., 008. Where Is he Value Premium? Fiacial Aalyss Joural 64, Redlema, R., Joes, C., Laae, H., 98. Empirical Aomalies Based o Uexpeced Earigs ad he Imporace of Risk Adjusmes. Joural of Fiacial Ecoomics 0, Shi, H. S., 005. Disclosure Risk ad Price Drif. Joural of Accouig Research 44,, Skier, D., Sloa, R., 00. Earigs Surprises, Growh Expecaios, ad Sock Reurs or Do Le a Earigs Torpedo Sik Your Porfolio. Review of Accouig Sudies 7, 3,
21 Table Summary Saisics Pael A repors he summary Saisics of key variables for he sample period from Jue 984 o December 008. Obs: oal umber of firmsquarer observaios. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: + + i (, q i. b. hreeday earigs aouceme abormal reurs are calculaed as EAR = + R ) (+ R ), where R i, is he daily reur for firms i i day. R b, is he daily valueweighed bechmark reur o FamaFrech size porfolio o which sock i belogs. ES: earigs surprises are defied as EarigsSurprise i, q Acual = abs Expeced i, q ( Expecedi, q ) i, q. BM: he raio of he fiscal yeared book value of equiy o he marke value of equiy. EP: he operaig icome afer depreciaio scaled by he marke value of equiy. CP: he cash flow from operaios scaled by he marke value of equiy. SG: he average of aual growh i sales over he previous hree years. I Pael B, lower (upper) diagoal repors Pearso (Spearma) correlaios. Pael A Descripive saisics Variable Obs Mea Media Sd Mi Max ME 38,00 3, , ,39 EARs 9,304 0.% 0.09% 7.53% 3.89% 4.47% ES 39,430.5%.% 03.46% % 9.86% BM 36, EP 36, CP 7, SG 0, Pael B Correlaio saisics for overall sample Variable ME BM EP CP SG ME 0.5*** 0.05*** 0.0*** 0.04*** BM 0.0*** 0.39*** 0.50*** 0.0*** EP 0.0*** 0.9*** 0.9*** 0.*** CP *** 0.87*** 0.7*** SG 0.03*** 0.08*** 0.09*** 0.0*** Noe: *** represe saisical sigificace a he % level.
22 Table Number ad frequecy of observaios i each subsample For every quarer bewee Jue 984 ad December 008, subsamples are formed accordig o differe sigs of earigs surprises ad earigs aouceme abormal reurs. The umbers preseed i he able are he oal firmsquarer observaios ad frequecy. EARs: hreeday earigs aouceme + + i (, q i. b. abormal reurs are calculaed as EAR = + R ) (+ R ), where R i, is he daily reur for firms i i day. R b, is he daily valueweighed bechmark reur o FamaFrech size porfolio o which sock i belogs.. ES: earigs surprises are defied as EarigsSurprise i, q Acual = abs Expeced i, q ( Expecedi, q ) i, q. Pael A: Number of observaios ES >0 ES <0 Sub Toal ES =0 Toal EARs>0 69,880 34,89 04,69,35 6,494 EARs<0 5,765 59,38,093 5,60 6,73 Sub Toal,645 93,67 5,6 7,945 43,07 Pael B: Frequecy of observaios EARs>0 8.73% 4.0% 4.83% 5.07% 47.90% EARs<0.8% 4.39% 45.68% 6.4% 5.0% Sub Toal 50.0% 38.49% 88.5%.49% 00.00%
23 Table 3: Posearigsaouceme drifs Valueglamour ivesig A he ed of each Jue from 984 o 008, 0 porfolios are formed based o valueglamour proxies, amely bookomarke raio (BM), earigsoprice raio (EP), cashflowoprice raio (CP) ad pas growh i sales (SG). BM: he raio of he fiscal yeared book value of equiy o he marke value of equiy. EP: he operaig icome afer depreciaio scaled by he marke value of equiy. CP: he cash flow from operaios scaled by he marke value of equiy. SG: he average of aual growh i sales over he previous hree years. Value socks are socks ha have high BM, EP, CP ad low SG. Glamour socks refer o socks ha have low BM, EP, CP ad high SG. Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: hreeday earigs aouceme abormal reurs are calculaed + + i (, q i. b. as EAR = + R ) (+ R ), where R i, is he daily reur for firms i i day. R b, is he daily valueweighed bechmark reur o FamaFrech size porfolio o which sock i belogs. ES: earigs surprises are defied as EarigsSurprise i, q Acual = abs Expeced i, q ( Expecedi, q ) i, q. mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig from he secod day afer earigs i (, i. b. aoucemes are calculaed as Drif = + R ) (+ R ). Rak obs ME BM EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael A: Bookomarke Glamour Value Spread ** 3.6*** 5.85*** 9.6*** rak obs ME EP EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael B: Earigsoprice Glamour Value Spread 0.69* 0.70*.54** 4.3*** 5.7*** 7.3*** 3
24 Table 3coiued rak obs ME CP EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael C: Cashflowoprice Glamour Value Spread 0.74* 0.7*.64** 4.40*** 6.0*** 8.70*** rak obs ME SG EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael D: Salesgrowh Value Glamour Spread *.5**.80*** 3.3*** Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 4
25 Table 4: Pos Earigs Aouceme drifs bookomarke raio porfolios A he ed of each Jue from 984 o 008, socks are sored io quiiles based o bookomarke raio (BM) which is he raio of he fiscal yeared book value of equiy o he marke value of equiy. Value socks refer o he socks rakig highes o BM. Glamour socks refer o he socks rakig lowes o BM. We he group each quiile io six subsamples i erms of he sigs of earigs surprises (+//0) ad EARs (+/). Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: + + i (, q i. b. hreeday earigs aouceme abormal reurs are calculaed as EAR = + R ) (+ R ). mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig i (, i. b. from he secod day afer earigs aoucemes are calculaed as Drif = + R ) (+ R ). BM_rak obs ME BM EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael A: Earigs Surprises>0 & EARs>0 Glamour Value Pael B: Earigs Surprises <0 & EARs<0 Glamour Value Spread.9***.5** 4.68*** 8.68***.50*** 3.65*** Pael C: Earigs Surprises <0 & EARs >0 Glamour Value Pael D: Earigs Surprises >0 & EARs <0 Glamour Value Pael E: Earigs Surprises =0 & EARs >0 Glamour Value Pael F: Earigs Surprises =0 & EARs <0 Glamour Value Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 5
26 Table 5: Pos Earigs Aouceme drifs Earigsoprice raio porfolios A he ed of each Jue from 984 o 008, socks are sored io quiiles based o earigsoprice raio (EP). EP: he operaig icome afer depreciaio scaled by he marke value of equiy. Value socks refer o he socks rakig highes o EP. Glamour socks refer o he socks rakig lowes o EP. We he group each quiile io six subsamples i erms of he sigs of earigs surprises (+//0) ad EARs (+/). Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: hreeday + + i (, q i. b. earigs aouceme abormal reurs are calculaed as EAR = + R ) (+ R ). mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig from he i (, i. b. secod day afer earigs aoucemes are calculaed as Drif = + R ) (+ R ). EP_rak obs ME EP EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael A: Earigs Surprises>0 & EARs>0 Glamour Value Pael B: Earigs Surprises <0 & EARs<0 Glamour Value Spread.43***.66** 4.48*** 7.69*** 0.09***.7*** Pael C: Earigs Surprises <0 & EARs >0 Glamour Value Pael D: Earigs Surprises >0 & EARs <0 Glamour Value Pael E: Earigs Surprises =0 & EARs >0 Glamour Value Pael F: Earigs Surprises =0 & EARs <0 Glamour Value Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 6
27 Table 6: Pos Earigs Aouceme drifs Cashflowoprice raio porfolios A he ed of each Jue from 984 o 008, socks are sored io quiiles based o cashflowoprice raio (CP). CP: he cash flow from operaios scaled by he marke value of equiy. Value socks refer o he socks rakig highes o CP. Glamour socks refer o he socks rakig lowes o CP. We he group each quiile io six subsamples i erms of he sigs of earigs surprises (+//0) ad EARs (+/). Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: hreeday earigs aouceme abormal reurs are calculaed as + + EAR = ( + R ) (+ R. ) i, q i. b =. mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig from he secod day afer i (, i. b. earigs aoucemes are calculaed as Drif = + R ) (+ R ). CP_rak obs ME CP EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael A: Earigs Surprises>0 & EARs>0 Glamour Value Pael B: Earigs Surprises <0 & EARs<0 Glamour Value Spread.95***.50** 4.7*** 8.65***.***.89*** Pael C: Earigs Surprises <0 & EARs >0 Glamour Value Pael D: Earigs Surprises >0 & EARs <0 Glamour Value Pael E: Earigs Surprises =0 & EARs >0 Glamour Value Pael F: Earigs Surprises =0 & EARs <0 Glamour Value Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 7
28 Table 7: Pos Earigs Aouceme drifs pas sales growh porfolios A he ed of each Jue from 984 o 008, socks are sored io quiiles based o pas salesgrowh (SG). SG: he average of aual growh i sales over he previous hree years. Value socks refer o he socks rakig lowes o SG. Glamour socks refer o he socks rakig highes o SG. We he group each quiile io six subsamples i erms of he sigs of earigs surprises (+//0) ad EARs (+/). Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: hreeday earigs aouceme abormal reurs are calculaed as + + EAR = ( + R ) (+ R. ) i, q i. b =. mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig from he secod day afer i (, i. b. earigs aoucemes are calculaed as Drif = + R ) (+ R ). SG_rak obs ME SG EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) Pael A: Earigs Surprises>0 & EARs>0 Value Glamour Pael B: Earigs Surprises <0 & EARs<0 Value Glamour Spread.7***.35** *** 8.5*** 8.*** Pael C: Earigs Surprises <0 & EARs >0 Value Glamour Pael D: Earigs Surprises >0 & EARs <0 Value Glamour Pael E: Earigs Surprises =0 & EARs >0 Value Glamour Pael F: Earigs Surprises =0 & EARs <0 Value Glamour Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 8
29 Table 8 Marke capializaio i differe securiies exchages Our sample covers socks lised i he followig four securiies exchages: NYSE (47% of oal observaios), NASDAQ (5% of oal observaios), Alerex (3% of oal observaios), ad NYSE Arca (0.04% of oal observaios). Table 8 shows he mea ad sadard deviaio of marke capializaio for firms lised i differe securiies exchages. Exchage STAT Marke Capializaio NYSE MEAN % STD 896 NASDAQ MEAN % STD 897 Alerex MEAN 37.6% STD 763 NYSE Arca MEAN % STD 37 9
30 Table 9: Robusess Check Differe exchages We spli our sample io groups. Socks lised i NYSE ad socks lised i NASDAQ, Alerex, ad NYSE Arca. A he ed of each Jue from 984 o 008, socks are sored io quiiles based o BM, EP, CP or SG. BM: he raio of he fiscal yeared book value of equiy o he marke value of equiy. EP: he operaig icome afer depreciaio scaled by he marke value of equiy. CP: he cash flow from operaios scaled by he marke value of equiy. SG: he average of aual growh i sales over he previous hree years. Value socks are socks ha have high BM, EP, CP ad low SG. Glamour socks refer o socks ha have low BM, EP, CP ad high SG. We he group each quiile io six subsamples i erms of he sigs of earigs surprises (+//0) ad EARs (+/).Obs: he average umber of firms i a quarer. ME: he marke value a he ed of Jue of each year, i millio dollars. I is defied as commo shares ousadig muliplied by price per share. EARs: hreeday earigs aouceme abormal reurs are calculaed as + + EAR i, q = ( + Ri. ) (+ Rb. ). mh, 3mh, 6mh, 9mh, year: cumulaive abormal reurs up o, 63, 6, 89, 5 radig days sarig from he secod day afer earigs aoucemes are calculaed i (, i. b. as Drif = + R ) (+ R ). Rak Obs ME Raio Group EARs(%) mh(%) 3mh(%) 6mh(%) 9mh(%) year(%) NYSE Pael A: Bookomarke raio Value 68,98.8 ES>0 & EARs> Glamour 43 7, 0.0 ES<0 & EARs< Spread 9.8***.08* 3.63*** 6.47*** 8.5*** 0.43*** Pael B: Earigsoprice Value 76 3, ES>0 & EARs> Glamour 57 3, ES<0 & EARs< Spread 9.69***.67** 4.06*** 6.64*** 8.75*** 0.00*** Pael C: Cashflowoprice Value 69 3, ES>0 & EARs> Glamour 48 4, ES<0 & EARs< Spread 9.98***.44** 3.96*** 7.59*** 9.64***.88*** Pael D: Salesgrowh Value 53 3,483.0 ES>0 & EARs> Glamour 68 3, ES<0 & EARs< Spread 9.70***.6** 3.4*** 4.56*** 5.45*** 7.8*** NASDAQ, Alerex, NYSE Arca Pael A: Bookomarke raio Value ES>0 & EARs> Glamour 58, ES<0 & EARs< Spread 3.49***.56** 4.93*** 8.36***.0*** 3.4*** Pael B: Earigsoprice Value ES>0 & EARs> Glamour ES<0 & EARs< Spread.4***.69** 4.3*** 6.8*** 8.6*** 8.70*** Pael C: Cashflowoprice Value ES>0 & EARs> Glamour ES<0 & EARs< Spread 3.4***.4** 4.4*** 6.95*** 8.5*** 7.94*** Pael D: Salesgrowh Value ES>0 & EARs> Glamour ES<0 & EARs< Spread 3.49***.33** 4.79*** 7.97*** 0.*** 0.73*** Noe: *, **, ad *** represe saisical sigificace a he 0%, 5% ad % level, respecively. 30
31 Figure : Threemoh (63 radig days) posearigsaouceme drifs o a sraegy akig a log posiio i firms i value socks whe boh earigs surprises ad EARs are posiive ad akig a shor posiio i glamour socks whe boh earigs surprises ad EARs are egaive. 3mh posearigsaouceme drifs are calculaed as Drif = + R ) (+ R ). i (, i. b. Bookomarke raio is he raio of he fiscal yeared book value of equiy o he marke value of equiy. Bea is he correlaio of he porfolio drifs wih he S&P500 idex reurs. Icidece of loss is he perceage of quarers where he porfolios icur losses. The Sharpe Raio is he excess porfolio reur over riskfree rae divided by he sadard deviaio. Aualized reur 8.73% Bea Icidece of loss.05% Aualized Sharpe raio
32 Figure : Threemoh (63 radig days) posearigsaouceme drifs o a sraegy akig a log posiio i firms i value socks whe boh earigs surprises ad EARs are posiive ad akig a shor posiio i glamour socks whe boh earigs surprises ad EARs are egaive. 3mh posearigsaouceme drifs are calculaed as Drif = + R ) (+ R ). i (, i. b. Earigsoprice raio is he operaig icome afer depreciaio scaled by he marke value of equiy. Bea is he correlaio of he porfolio drifs wih he S&P500 idex reurs. Icidece of loss is he perceage of quarers where he porfolios icur losses. The Sharpe Raio is he excess porfolio reur over riskfree rae divided by he sadard deviaio. Aualized reur 7.9% Bea 0.4 Icidece of loss 6.3% Aualized Sharpe raio
33 Figure 3: Threemoh (63 radig days) posearigsaouceme drifs o a sraegy akig a log posiio i firms i value socks whe boh earigs surprises ad EARs are posiive ad akig a shor posiio i glamour socks whe boh earigs surprises ad EARs are egaive. 3mh posearigsaouceme drifs are calculaed as Drif = + R ) (+ R ). i (, i. b. Cashflowoprice raio is he cash flow from operaios scaled by he marke value of equiy. Bea is he correlaio of he porfolio drifs wih he S&P500 idex reurs. Icidece of loss is he perceage of quarers where he porfolios icur losses. The Sharpe Raio is he excess porfolio reur over riskfree rae divided by he sadard deviaio. Aualized reur 8.85% Bea 0.9 Icidece of loss 5.6% Aualized Sharpe raio
34 Figure 4: Threemoh (63 radig days) posearigsaouceme drifs o a sraegy akig a log posiio i firms i value socks whe boh earigs surprises ad EARs are posiive ad akig a shor posiio i glamour socks whe boh earigs surprises ad EARs are egaive. 3mh posearigsaouceme drifs are calculaed as Drif = + R ) (+ R ). i (, i. b. Salesgrowh is he average of aual growh i sales over he previous hree years. Bea is he correlaio of he porfolio drifs wih he S&P500 idex reurs. Icidece of loss is he perceage of quarers where he porfolios icur losses. The Sharpe Raio is he excess porfolio reur over riskfree rae divided by he sadard deviaio. Aualized reur 6.6% Bea 0.0 Icidece of loss 8.95% Aualized Sharpe raio.4 34
The effect of the increase in the monetary base on Japan s economy at zero interest rates: an empirical analysis 1
The effec of he icrease i he moeary base o Japa s ecoomy a zero ieres raes: a empirical aalysis 1 Takeshi Kimura, Hiroshi Kobayashi, Ju Muraaga ad Hiroshi Ugai, 2 Bak of Japa Absrac I his paper, we quaify
More informationUsing Kalman Filter to Extract and Test for Common Stochastic Trends 1
Usig Kalma Filer o Exrac ad Tes for Commo Sochasic Treds Yoosoo Chag 2, Bibo Jiag 3 ad Joo Y. Park 4 Absrac This paper cosiders a sae space model wih iegraed lae variables. The model provides a effecive
More informationAre Under and Overreaction the Same Matter? A Price Inertia based Account
Are Under and Overreacion he Same Maer? A Price Ineria based Accoun Shengle Lin and Sephen Rasseni Economic Science Insiue, Chapman Universiy, Orange, CA 92866, USA Laes Version: Nov, 2008 Absrac. Theories
More informationKONSTANTĪNS BEŅKOVSKIS IS THERE A BANK LENDING CHANNEL OF MONETARY POLICY IN LATVIA? EVIDENCE FROM BANK LEVEL DATA
ISBN 9984 676 20 X KONSTANTĪNS BEŅKOVSKIS IS THERE A BANK LENDING CHANNEL OF MONETARY POLICY IN LATVIA? EVIDENCE FROM BANK LEVEL DATA 2008 WORKING PAPER Lavias Banka, 2008 This source is o be indicaed
More informationI M F S T A F F D I S C U S S I O N N O T E
I M F S T A F F D I S C U S S I O N N O T E February 29, 2012 SDN/12/01 Two Targes, Two Insrumens: Moneary and Exchange Rae Policies in Emerging Marke Economies Jonahan D. Osry, Aish R. Ghosh, and Marcos
More informationWhen Should Public Debt Be Reduced?
I M F S T A F F D I S C U S S I ON N O T E When Should Public Deb Be Reduced? Jonahan D. Osry, Aish R. Ghosh, and Raphael Espinoza June 2015 SDN/15/10 When Should Public Deb Be Reduced? Prepared by Jonahan
More informationExchange Rate PassThrough into Import Prices: A Macro or Micro Phenomenon? Abstract
Exchange Rae PassThrough ino Impor Prices: A Macro or Micro Phenomenon? Absrac Exchange rae regime opimaliy, as well as moneary policy effeciveness, depends on he ighness of he link beween exchange rae
More informationThe concept of potential output plays a
Wha Do We Know (And No Know) Abou Poenial Oupu? Susano Basu and John G. Fernald Poenial oupu is an imporan concep in economics. Policymakers ofen use a onesecor neoclassical model o hink abou longrun
More informationThe Macroeconomics of MediumTerm Aid ScalingUp Scenarios
WP//6 The Macroeconomics of MediumTerm Aid ScalingUp Scenarios Andrew Berg, Jan Goschalk, Rafael Porillo, and LuisFelipe Zanna 2 Inernaional Moneary Fund WP//6 IMF Working Paper Research Deparmen The
More informationDoes Britain or the United States Have the Right Gasoline Tax?
Does Briain or he Unied Saes Have he Righ Gasoline Tax? Ian W.H. Parry and Kenneh A. Small March 2002 (rev. Sep. 2004) Discussion Paper 02 12 rev. Resources for he uure 1616 P Sree, NW Washingon, D.C.
More informationFollow the Leader If You Can, Hedge If You Must
Journal of Machine Learning Research 15 (2014) 12811316 Submied 1/13; Revised 1/14; Published 4/14 Follow he Leader If You Can, Hedge If You Mus Seven de Rooij seven.de.rooij@gmail.com VU Universiy and
More informationWhy Have Economic Reforms in Mexico Not Generated Growth?*
Federal Reserve Bank of Minneapolis Research Deparmen Saff Repor 453 November 2010 Why Have Economic Reforms in Mexico No Generaed Growh?* Timohy J. Kehoe Universiy of Minnesoa, Federal Reserve Bank of
More informationBoard of Governors of the Federal Reserve System. International Finance Discussion Papers. Number 1003. July 2010
Board of Governors of he Federal Reserve Sysem Inernaional Finance Discussion Papers Number 3 July 2 Is There a Fiscal Free Lunch in a Liquidiy Trap? Chrisopher J. Erceg and Jesper Lindé NOTE: Inernaional
More informationNo One Benefits. How teacher pension systems are failing BOTH teachers and taxpayers
No Oe Beefits How teacher pesio systems are failig BOTH teachers ad taxpayers Authors Kathry M. Doherty, Sadi Jacobs ad Trisha M. Madde Pricipal Fudig The Bill ad Melida Gates Foudatio ad the Joyce Foudatio.
More informationOUTOFBAG ESTIMATION. Leo Breiman* Statistics Department University of California Berkeley, CA. 94708 leo@stat.berkeley.edu
1 OUTOFBAG ESTIMATION Leo Breiman* Saisics Deparmen Universiy of California Berkeley, CA. 94708 leo@sa.berkeley.edu Absrac In bagging, predicors are consruced using boosrap samples from he raining se
More informationThe Arithmetic of Investment Expenses
Fiacial Aalysts Joural Volume 69 Number 2 2013 CFA Istitute The Arithmetic of Ivestmet Expeses William F. Sharpe Recet regulatory chages have brought a reewed focus o the impact of ivestmet expeses o ivestors
More informationThE Papers 07/02. Do sunk exporting costs differ among markets? Evidence from Spanish manufacturing firms.
ThE Papers 07/02 Deparameno de Teoría e Hisoria Económica Universidad de Granada Do sunk exporing coss differ among markes? Evidence from Spanish manufacuring firms. Blanes Crisóbal, José Vicene. Universidad
More informationThe Simple Analytics of Helicopter Money: Why It Works Always
Vol. 8, 201428 Augus 21, 2014 hp://dx.doi.org/10.5018/economicsejournal.ja.201428 The Simple Analyics of Helicoper Money: Why I Works Always Willem H. Buier Absrac The auhor proides a rigorous analysis
More informationImproved Techniques for Grid Mapping with RaoBlackwellized Particle Filters
1 Improved Techniques for Grid Mapping wih RaoBlackwellized Paricle Filers Giorgio Grisei Cyrill Sachniss Wolfram Burgard Universiy of Freiburg, Dep. of Compuer Science, GeorgesKöhlerAllee 79, D79110
More informationISSN 15183548. Working Paper Series
ISSN 583548 Working Paper Series Nonlinear Mechanisms of he Exchange Rae PassThrough: A Phillips curve model wih hreshold for Brazil Arnildo da Silva Correa and André Minella November, 006 ISSN 583548
More informationare new doctors safe to practise?
Be prepared: are ew doctors safe to practise? Cotets What we foud 02 Why we ve writte this report 04 What is preparedess ad how ca it be measured? 06 How well prepared are medical graduates? 08 How has
More informationHow Has the Literature on Gini s Index Evolved in the Past 80 Years?
How Has the Literature o Gii s Idex Evolved i the Past 80 Years? Kua Xu Departmet of Ecoomics Dalhousie Uiversity Halifax, Nova Scotia Caada B3H 3J5 Jauary 2004 The author started this survey paper whe
More informationJ. J. Kennedy, 1 N. A. Rayner, 1 R. O. Smith, 2 D. E. Parker, 1 and M. Saunby 1. 1. Introduction
Reassessig biases ad other ucertaities i seasurface temperature observatios measured i situ sice 85, part : measuremet ad samplig ucertaities J. J. Keedy, N. A. Rayer, R. O. Smith, D. E. Parker, ad M.
More informationAdverse Health Care Events Reporting System: What have we learned?
Adverse Health Care Evets Reportig System: What have we leared? 5year REVIEW Jauary 2009 For More Iformatio: Miesota Departmet of Health Divisio of Health Policy P.O. Box 64882 85 East Seveth Place, Suite
More informationTurning Brownfields into Greenspaces: Examining Incentives and Barriers to Revitalization
Turig Browfields ito Greespaces: Examiig Icetives ad Barriers to Revitalizatio Juha Siikamäki Resources for the Future Kris Werstedt Virgiia Tech Uiversity Abstract This study employs iterviews, documet
More informationLeadership Can Be Learned, But How Is It Measured?
Maagemet Scieces for Health NO. 8 (2008) O C C A S I O N A L PA P E R S Leadership Ca Be Leared, But How Is It Measured? How does leadership developmet cotribute to measurable chages i orgaizatioal performace,
More informationTeaching Bayesian Reasoning in Less Than Two Hours
Joural of Experimetal Psychology: Geeral 21, Vol., No. 3, 4 Copyright 21 by the America Psychological Associatio, Ic. 963445/1/S5. DOI: 1.7//963445..3. Teachig Bayesia Reasoig i Less Tha Two Hours Peter
More informationWhen the People Draw the Lines
Whe the People Draw the Lies A Examiatio of the Califoria Citizes redistrictig Commissio by Raphael J. Soeshei with Geerous Support from The James Irvie Foudatio Whe the People Draw the Lies A Examiatio
More informationWhich Archimedean Copula is the right one?
Which Archimedean is he righ one? CPA Mario R. Melchiori Universidad Nacional del Lioral Sana Fe  Argenina Third Version Sepember 2003 Published in he YieldCurve.com ejournal (www.yieldcurve.com), Ocober
More informationCrowds: Anonymity for Web Transactions
Crowds: Aoymity for Web Trasactios Michael K. Reiter ad Aviel D. Rubi AT&T Labs Research I this paper we itroduce a system called Crowds for protectig users aoymity o the worldwideweb. Crowds, amed for
More information