The effect of meeting or missing earnings expectations on information asymmetry

Transcription

1 The effec of meeing or missing earnings expecaions on informaion asymmery Sephen Brown # Sephen A. Hillegeis Kin Lo Augus 2006 Absrac: We examine wheher he previously documened pricing premium for firms equiy when hey mee or bea earnings expecaions (MBE) is aribuable o a reducion in he cos of equiy capial via a reducion in informaion asymmery. We measure he laer using he probabiliy of informed rading (PIN) from Easley e al. (997). We find ha PIN decreases (increases) when firms mee or bea (miss) earnings expecaions and ha hese changes increase wih he magniude of he earnings surprise. In addiion, firms ha regularly MBE show a sronger decline in PIN compared wih hose achieving MBE irregularly. Furhermore, we find ha he reducion in asymmery for MBE firms disappears in cases where expecaions managemen was likely used o mee he earnings benchmark, bu we find no evidence ha earnings managemen affecs he reducion in asymmery aribuable o MBE. Broadly, our resuls correspond o findings regarding he pricing premium associaed wih MBE, suggesing ha he MBE pricing premium is a leas parially aribuable o a denominaor effec where invesors discoun fuure cash flows a lower raes because of reduced levels of informaion asymmery. Key Words: Informaion asymmery; meeing or beaing expecaions; earnings expecaions; expecaion managemen; invesor recogniion hypohesis. JEL Classificaion: G2; G4; M4; M43. Commens and suggesions by workshop paricipans a he London Business School and paricipans a he 2006 Conemporary Issues in Capial Markes & Financial Economics Conference a he Universiy of Cyprus are sincerely appreciaed. We graefully acknowledge he financial suppor of he Goizuea Business School, INSEAD, he KPMG Research Bureau a UBC, and he Social Sciences and Humaniies Research Council of Canada. # Deparmen of Accouning, Goizuea Business School, Emory Universiy Accouning and Conrol Area, INSEAD. Sauder School of Business, The Universiy of Briish Columbia.

2 . Inroducion Several recen sudies, including Barh e al. (999), Barov e al. (2002), and Kasznik and McNichols (2002), have documened ha invesors assign a valuaion premium o firms ha mee or bea a benchmark level of earnings expecaions (MBE). In searching for a raional explanaion for he MBE premium, prior lieraure has focused on a signaling explanaion whereby MBE signals beer han expeced fuure performance (cash flow or earnings). We label his explanaion he numeraor effec, consisen wih common valuaion erminology. We examine an alernaive bu muually non-exclusive explanaion ha we erm he denominaor effec whereby meeing (missing) earnings expecaions leads o a decrease (increase) in he cos of capial (COC). Kasznik and McNichols (2002) speculae ha he premium could be parly due o changes in COC since hey find ha he numeraor effec does no fully explain he MBE valuaion premium. We analyze he relaion beween MBE and he level of informaion asymmery, which is posiively associaed wih he COC (Easley e al. (2002), Easley e al. (2004), and Healy e al. (999)). (As explained below, we choose his indirec approach because we canno generae reliable evidence by direcly examining he associaion beween MBE and he COC.) We hypohesize ha MBE (is complemen, Miss ) firms experience changes in heir rading and informaion environmens ha lead o a decrease (increase) in informaion asymmery. We conduc ime-series ess of he associaion beween a firm s earnings performance in one quarer and he change in informaion asymmery in he subsequen quarer. Our proxy for While no dispuing he exan evidence, he signaling sory is unsaisfying because i is unlikely ha meeing earnings expecaions can serve as an economically-valid separaing signal; condiional on he curren level of earnings, i is no clear ha exceeding a benchmark imposes addiional coss ha would vary beween firms wih differen earnings prospecs. The signaling explanaion is more applicable in cases when (differenially) cosly earnings managemen echniques are used o mee expecaions.

3 informaion asymmery is he probabiliy of informed rade, or PIN, which we esimae using an exension of he popular EKO marke microsrucure model (Easley e al. (997)). We rely on he consensus analyss forecas o proxy for he marke s earnings expecaions because Brown and Caylor (2004) find ha he MBE phenomenon has he sronges associaion wih his earnings benchmark during our sample period. We find ha informaion asymmery declines significanly when a firm mees or beas is earnings expecaions bu rises significanly when a firm misses he benchmark level of earnings. Uilizing he componens of he PIN measure, we examine he underlying link beween earnings performance and informaion asymmery. We find ha MBE firms experience an increase in he volume of rading by uninformed invesors boh in absolue and relaive erms (compared wih invesors who rade on privae informaion). This evidence suggess good earnings performance increases he firm s invesmen visibiliy and aracs unsophisicaed invesors. 2 Such a dynamic is consisen wih he Invesor Recogniion Hypohesis of Meron (987). The MBE pricing lieraure has examined he associaion beween MBE and he marke premium in more deail and has documened a number of cross-secional differences in he MBE premium. We conduc supplemenary ess ha correspond o several of hese resuls because evidence ha parallels prior pricing premium resuls increases he likelihood ha he informaion asymmery effec is capuring he denominaor effec. Firs, we find ha he change in informaion asymmery is posiively relaed o he magniude of he earnings surprise. Second, our evidence indicaes he decrease (increase) in informaion asymmery is larger for MBE (Miss) firms who have regularly me/beaen expecaions over he prior eigh quarers. Indeed, 2 This finding suggess ha MBE firms experience improved liquidiy. Archarya and Pedersen (2005) and Brennan and Subrahmanyam (996) find liquidiy is negaively associaed wih he COC. Togeher, hese findings sugges a complemenary MBE denominaor effec. Also, if more uninformed rading represens an expansion of he shareholder base, hen MBE firms experience an improvemen in aggregae risk sharing, furher reducing he COC. 2

4 our resuls indicae ha he average reducion in asymmery ha arises hrough MBE is significan only when i is par of a repeaed paern. Finally, we examine firms ha are likely o have used expecaions managemen or earnings managemen in order o mee expecaions. We find he decrease in informaion asymmery is largely eliminaed for expecaions managemen firms. For earnings managemen firms, we find no evidence for any differences in he MBE effec on informaion asymmery. Overall, hese findings ariculae wih corresponding resuls in Barh e al. (999), Barov e al. (2002) and Kasznik and McNichols (2002), furher supporing he exisence of a denominaor effec. 3 Graham e al. (2005) provide survey evidence consisen wih he MBE premium. They repor ha more han eighy percen of Chief Financial Officers (CFOs) agree ha meeing earnings benchmarks helps mainain or increase he sock price and build credibiliy wih capial markes. Seveny-eigh percen of CFOs also believe ha missing a benchmark creaes uncerainy abou he firm s fuure prospecs. Our evidence ha informaion asymmery is relaed o earnings benchmarks gives credence o CFOs beliefs abou he cos of capial benefis of meeing earnings benchmarks. In addiion, our evidence is more direc as i reflecs wha invesors acually do, raher han wha CFOs believe invesors do. This paper conribues o he lieraure by providing evidence consisen wih an alernaive bu non-exclusive denominaor explanaion for he MBE pricing premium documened in he prior lieraure. Indirecly, our evidence suggess ha changes in he cos of capial, caused by changes in informaion asymmery, conribue o he MBE valuaion premium. The associaions beween MBE paerns and informaion asymmery ariculae wih 3 The expecaions managemen resuls are no fully congruen wih Barov e al. (2002) in ha Barov e al. show evidence ha here is only a parial reducion in he pricing premium for expecaions managemen firms. However, addiional ess show ha in our sample, he MBE pricing premium essenially disappears in cases where expecaions managemen had likely occurred; hese findings are consisen wih our informaion asymmery resuls. 3

5 corresponding relaions beween MBE paerns and marke pricing documened in he prior lieraure. By providing evidence consisen wih he denominaor effec, his paper suggess a raional explanaion for why firms and analyss play he earnings game whereby firms engage in cosly aciviies o mee exernal forecass: firms receive cos of capial benefis while analyss benefi from more accurae earnings forecass and higher rading volumes. Thus, he effors aken by managers o mee earnings expecaions are no necessarily conrary o he ineress of shareholders, as is ofen implied (Jensen (2005)). We also conribue o he lieraure by providing insighs ino he role earnings benchmarks play in affecing invesors rading decisions and informaion search aciviies. We documen how informed and uninformed invesors aler heir rading behaviors based on how acual earnings compare o earnings benchmarks. These findings are consisen wih he Invesor Recogniion Hypohesis (Meron (987)) whereby good (bad) earnings performance increases (decreases) a firm s invesmen visibiliy. We do no follow an alernaive and more direc approach of analyzing he relaion beween MBE and he COC for several reasons. Firs, Eason and Monahan (2005) find ha accouning-based ex ane proxies for he COC are generally unreliable. Second, exising echniques rely on he curren sock price and analys forecass of fuure earnings or cash flows. As a resul, increases (decreases) in sock prices mechanically lead o decreases (increases) in he implied COC when here are delays in he updaing of analyss forecass. Kasznik and McNichols (2002) find ha he fuure profiabiliy of MBE firms is no immediaely refleced in analys forecass made afer earnings are released. Thus, implied COC echniques have sysemaic errors ha are biased in favor of he hypohesized denominaor effec. Third, relying on ex pos realized reurns o measure expeced reurns is invalid when expeced reurns are 4

6 changing, as we expec o be he case in our seing, because realized and expeced reurns move in opposie direcions. Given he limiaions surrounding he use of COC esimaes in our seing, we insead rely on prior heoreical and empirical research ha has documened a posiive associaion beween PIN and he equiy COC (Easley e al., 2002) and indirecly proxy for he COC by using PIN. Nex, we develop our hypoheses regarding he associaion beween earnings performance and informaion asymmery. In Secion 3, we inroduce he PIN measure of informaion asymmery. Secion 4 discusses daa sources, variable consrucion, and descripive saisics. Secion 5 presens he resuls of our empirical ess, and Secion 6 concludes he paper. 2. Relaion beween meeing or beaing earnings expecaions and informaion asymmery In he idealized seing of informaionally efficien sock markes, all poenial invesors are assumed o coslessly process all public informaion. However, hese idealized condiions are no me in pracice. Invesors mus a leas be aware of he firm before hey can consider i as a poenial invesmen. While invesors will no buy he sock of every firm of which hey become aware, hey canno buy he sock of a firm of which hey are unaware. Meron (987) and Fishman and Hagery (989) show ha decreases in coss of obaining and processing public informaion abou a firm leads o increases in he number of non-privaely informed invesors. This Invesor Recogniion Hypohesis is suppored by several sudies ha demonsrae he imporance of visibiliy on he size and composiion of he firm s ownership base. 4 For example, Falkensein (996) shows ha muual funds have significan preferences for socks wih heavy newspaper coverage while Barber and Odean (2005) find ha individuals are ne buyers of 4 Aggarwal e al. (2002) and Demers and Lewellen (2003) find ha IPO underpricing is reduced by increased aenion by he media and non-affiliaed analyss. Similarly, Grullon e al. (2004) find ha firms wih greaer produc marke adverising expendiures have more individual and insiuional invesors. Also see Foerser and Karolyi (999) and Kadlec and McConnell (994). 5

7 socks on days when he firms are in he news. In addiion, Lehavy and Sloan (2005) provide more direc suppor for he Invesor Recogniion Hypoheis by documening an associaion beween recogniion and curren and fuure sock reurns. We expec ha reporing good earnings news (i.e., above expecaions) generally increases he number of invesors who are boh aware of he firm and, given he good earnings performance, more likely o inves. Consisen wih our expecaion, Nofsinger (200) finds ha individuals significanly increase heir buying aciviy afer good earnings news, bu no following bad earnings news. His evidence indicaes ha while bad news may generae increased aenion from uninformed invesors, i does no lead hem o inves in he sock. 5 Thus, we expec ha good earnings performance resuls in more uninformed rading because i increases invesmen visibiliy and reduces he coss of obaining public informaion abou he firm. Accordingly, we expec ha good earnings performance is associaed wih relaively more rading by uninformed invesors, and hence, lower informaion asymmery. Good earnings performance also decreases he level of informaion asymmery by reducing he incenives o search for privae informaion. We hypohesize ha when a firm mees or beas is earnings arge, invesors believe ha i is more likely o hi is arge in he fuure. 6 In his case, here are fewer shor-erm incenives o search for privae informaion abou nex period s earnings (Goel and Thakor (2003)). 7 In addiion, he expansion of he invesor base discussed above will furher reduce he incenives o search for privae informaion. Peress (2004) demonsraes ha a broader invesor base will reduce he incenives for exising 5 Nofsinger (200) also finds ha individuals respond more srongly o good news han insiuional invesors do, which suggess ha good news predominanly draws in uninformed raders. 6 In our sample, he uncondiional probabiliy of a firm meeing or beaing is earnings expecaions is 0.76, while he probabiliy condiional on MBE in he prior quarer is There are sill incenives o discover informaion abou he exen o which firms will bea or miss expecaions. However, his is he same as searching for privae informaion o predic he level of earnings. We are ineresed in wheher here is an addiional effec for meeing or missing a benchmark. 6

8 shareholders o produce privae informaion. Since we expec he new invesors o be predominanly uninformed, he ne effec is less privae informaion producion. Accordingly, we expec ha afer good earnings performance, here will be fewer days on which cerain invesors are rading on privae informaion (which we refer o as privae informaion evens). We expec bad earnings performance will lead o an increase in informaion asymmery hrough a similar bu no idenical dynamic. While missing he marke s earnings expecaions may generae addiional invesor recogniion (hrough negaive press coverage), i is unlikely o generae addiional invesmen aciviy. Insead, bad earnings performance will cause he level of uninformed rading o decrease. In addiion, he expeced amoun of privae informaion abou he firm s fuure earnings performance will increase. Ciccone (2003) finds ha analyss ypically disagree more afer bad news han good news, which indicaes here is increased uncerainy and more privae informaion available afer bad news. The findings in Graham e al. (2005) are also consisen wih his noion. They repor ha CFOs commonly believe ha no meeing an earnings arge will be inerpreed by he marke as evidence of hidden problems. Increased uncerainy abou he firm s fuure prospecs afer i fails o mee is earning expecaions will lead o more search aciviies, and hence, more frequen privae informaion evens. Accordingly, we examine he following hypoheses (all hypoheses are saed in alernae form): H: Meeing or beaing (missing) earnings expecaions is associaed wih less (more) informaion asymmery during he subsequen period. H2: Meeing or beaing (missing) earnings expecaions is associaed wih: (a) more (less) rading by uninformed invesors, (b) relaively less (more) rading by privaely-informed invesors, and (c) less (more) frequen privae informaion evens in he subsequen period. Prior lieraure on he MBE phenomenon indicaes ha MBE premium is generally larger when firms rouinely deliver good earnings performance compared o firms which only 7

9 sporadically mee heir earnings arges. One possible explanaion for hese findings is ha i akes repeaed good earnings performance o subsanially increase he firm s invesmen visibiliy and/or aler incenives o search for privae informaion. In his case, we also expec ha he effec of a Miss will be greaer for firms ha had previously delivered good earnings performance on a rouine basis. Consisen wih his reasoning, Barh e al. (999) find a significan decrease in he valuaion premium when a firm breaks a previously increasing earnings paern. Thus, if he valuaion premium is relaed o differences in informaion asymmery as we propose, hen he relaion beween informaion asymmery and boh good and bad earnings performance should be sronger when firms have rouinely delivered good earnings performance. Thus, we es he following hypohesis: H3: Firms ha have repeaedly me or beaen earnings expecaions in prior periods experience larger decreases (increases) in informaion asymmery afer meeing or beaing (missing) earnings expecaions. We hypohesize ha he effecs of good earnings performance on firm visibiliy will depend on how he earnings arge was me. To he exen ha a firm uses eiher earnings managemen or expecaions managemen o mee an earnings arge and hese effors are parially observable, hen we expec he reducion in informaion asymmery will be lessened for wo reasons. Firs, he benefis of increased invesmen visibiliy will be lower o he exen he marke believes ha he firm did no acually achieve good earnings performance. Second, here will be more uncerainy abou fuure earnings, which will increase incenives o search for privae informaion. We expec hese facors will ameliorae he negaive associaion beween informaion asymmery and good earnings performance when eiher expecaions or earnings managemen echniques have been used. Thus, we es he following hypohesis: 8

10 H4: The associaion beween meeing or beaing expecaions and informaion asymmery is less negaive when i is more likely ha he good earnings performance is due o: (a) expecaions managemen, or (b) earnings managemen. 3. The PIN measure of informaion asymmery Informaion asymmery manifess iself when cerain invesors rade on privae informaion. Hence, informaion asymmery resuls in abnormally large imbalances beween buy and sell orders on days when informed invesors are rading on heir privae informaion. This observaion forms he inuiion behind he EKO microsrucure model of informaion asymmery (Easley e al. (997)), which we use o esimae he uncondiional probabiliy of informaionbased rading for a given sock based on he observed order flow. Easley e al. (997) models rading as a repeaed game beween he marke maker and wo ypes of raders: informed and uninformed. A he beginning of each rading day, naure deermines wheher a privae informaion even occurs wih probabiliy α. On such days, informed raders receive privae informaion abou he firm s value. The privae informaion conains bad (good) news wih probabiliy δ ( δ), where bad (good) news indicaes ha he profi maximizing rade is o sell (buy) he sock. 8 Uninformed raders submi buy and sell orders each day according o independen Poisson processes a he daily rae ε. On days wih good (bad) news, informed buy (sell) orders also arrive a a rae proporional o he amoun of uninformed rading, νε. Therefore, on a nonews day, boh buys and sells are Poisson disribued wih parameer ε. On bad-news days, buys are Poisson disribued wih parameer ε and sells are Poisson disribued wih parameer 8 By assuming ha he ype of news is unambiguous, he model does no allow for boh informed buying and selling on he same day, as in Kim and Verrecchia (99); insead, informaion asymmery is one-sided, as in Kyle (985). 9

11 (ε +νε) = ε(+ν); vice versa on good-news days. The marke maker ses prices o buy or sell one uni of sock and execues orders as hey randomly arrive. 9 The marke maker knows he uncondiional probabiliy of, and expeced order flow associaed wih, a privae informaion even and uses he acual order flow o updae her beliefs hroughou he rading day. By he end of he day, all privae informaion has been impounded ino price hrough informed rading. An imporan simplifying assumpion of he EKO model is ha he daily arrival raes of uninformed buy and sell orders are drawn from independen Poisson disribuions ha have consan parameers over he esimaion period. This assumpion causes he daily numbers of uninformed buys and sells o be uncorrelaed. However, his assumpion is violaed in pracice because cerain public informaion evens affec he rading inensiy of boh uninformed buyers and sellers on a paricular day. These evens can be boh firm-specific, such as earnings announcemens, and marke-wide, such as he release of macroeconomic saisics (Chordia e al. (2000)). If hese evens affec he rading inensiies of all uninformed raders similarly, hen he daily arrival raes of uninformed buy and sell orders will be posiively correlaed. Evidence in Brown and Hillegeis (2005) and Vener and de Jongh (2004) srongly suppors he idea ha here are common shocks o he daily level of uninformed rading, and hus, he assumpion of idenical daily Poisson disribuions does no hold in pracice. To overcome his limiaion, Vener and de Jongh (2004) exend he EKO model by specifying he arrival of uninformed buy and sell orders as a bivariae Inverse Gaussian Poisson process. The exended model assumes ha on each rading day, he average rading inensiies of uninformed invesors are subjec o a scaling facor W, where W is drawn from an inverse 9 The model assumes ha each rade is equally informaive regardless of is size. This assumpion is plausible as informed invesors disguise heir privae informaion by mimicking he rade sizes of uninformed raders (Barclay and Warner (993), Chakravary (200)). Jones e al. (994) provide evidence suggesing ha he loss of informaion due o ignoring rade size is small. 0

12 Gaussian disribuion wih parameer ψ > 0. As E[W ] = (and Var[W ] = (/ψ 2 )), he uncondiional expecaion of he daily number of uninformed buys (sells) remains equal o E[εW ] = ε. 0 Since he scaling facor affecs boh uninformed buyers and sellers equally, he exended model induces a posiive correlaion beween he daily number of buy and sell orders. We provide a more deailed descripion of he exended model in he Appendix. The exended model s parameers (α, δ, ψ, ε, ν) are esimaed by maximizing he likelihood funcion given in Equaion (A5) in he Appendix using he daily number of buys and sells as inpus. PIN is calculaed as follows: ανε PIN =. () ανε + 2ε PIN is he uncondiional expecaion of he fracion of oal daily rades ha are based on privae informaion since ανε is he expeced number of orders from privaely informed invesors and ανε + 2ε is he expeced number of oal orders. Equaion () shows ha asymmery increases wih he frequency of privae informaion evens (α), and he relaive inensiy of informed rading (ν), and decreases in he level of uninformed rading (ε). 4. Sample and measuremen The daa originaes from hree primary sources. Inraday rade daa comes from he Trades and Quoes (TAQ) daabase. Second, earnings expecaions are based on he consensus of analyss forecass compued by Firs Call. For consisency wih forecased numbers, we also use Firs Call s record of he acual earnings o deermine wheher a company mees/beas or misses is 0 As ψ, he mass of he disribuion becomes concenraed a W = and he exended model reduces o he original EKO model. To be consisen wih prior lieraure, we also replicae our analyses using PINs from he original model. The unabulaed resuls are qualiaively similar o hose repored in he ables in ha when significan resuls are repored, hey remain significan a convenional revels using he basic PINs. However, consisen wih basic PINs esimaes being more noisy, he significance levels are reduced and he absolue values of he coefficien esimaes are closer o zero.

13 earnings expecaions. Third, we use daa from Compusa o esimae he likelihood of earnings managemen and o measure firm size. The sample comprises all firm-quarers in he inersecion of hese daa sources, wih Firs Call being he mos resricive daabase. The sample period begins in he firs quarer of 995, when Firs Call daa seems o have become reliable, and ends wih he second quarer of 2004, he ime when he Firs Call daa was obained. We use non-linear opimizaion procedures o maximize he likelihood funcions in equaion (A5) o esimae he PIN and is componen parameers. We exclude observaions in he few cases where he average daily number of buys or sells is greaer han 2,000 as he compuaional coss of esimaing he likelihood funcion is prohibiive. In oal, we have 65,69 firm-quarer observaions. We measure PIN in even ime, wih he five rading days cenered on he quarerly earnings announcemen dae acing as he divider beween quarers. Thus, each firm-quarer esimae is based on rade daa over approximaely 2 weeks. As shown in Table, he mean and median PIN esimaes are 8.40% and 6.5%, respecively. These values are similar o he values repored in Brown e al. (2004) even hough ha paper uses he original, as opposed o he exended, EKO model. This similariy is no surprising because he correlaion beween PIN compued under boh models is high (unabulaed Pearson correlaion coefficien = 0.80). However, we find ha he exended model fis he rade daa significanly beer. In our sample, he median value of ψ is 2.3 and 99% of all esimaed values are less han 0.2. Recall ha he original model is a subse of he exended model, bu wih /ψ equal o 0. We define MBE as an indicaor variable ha equals if firm i s acual EPS is greaer han or equal o he consensus forecas of EPS for quarer, where he consensus is he laes Furher examinaion indicaes ha he basic EKO model fis he daa approximaely as well as he exended model only when he rading inensiy is exremely low; for ψ o reach 25 or higher (indicaing he original model fis he daa reasonably well), he median level of oal uninformed rading is less han hree rades per day. 2

14 value prior o he acual earnings release dae repored by Firs Call. In our sample, firms mee or bea expecaions 76% of he ime. In comparison, Barov e al. repor ha 70% of heir sample observaions in , and 50% in , mee or bea expecaions. Thus, i appears ha he incidence of MBE has increased over ime. As discussed more horoughly in he nex secion, our analysis focuses on quarer-oquarer changes in informaion asymmery. Consequenly, we only need o employ conrol variables ha change subsanially from one quarer o he nex. We use wo conrol variables: (changes in) he number of analyss and firm size. Analyss is he number of analyss conribuing o he consensus esimae of EPS repored by Firs Call for firm i and quarer. Size is he naural log of firm i s marke value of equiy (in millions of dollars) a he end of he fiscal quarer corresponding o he EPS repor. The mean (median) number of analyss is 5.99 (4) and he mean (median) firm size is $608 ($550) million. Table 2 presens he marix of Pearson correlaions. All values are significan a he 0.0 level. By consrucion, PIN and he PIN parameers (α, ν, ε) have high correlaions. The correlaions beween MBE and PIN (and is componen parameers α, ν, and ε), are all consisen wih he hypohesized relaions, alhough he correlaion wih α is modes (-0.04). In addiion, he large negaive correlaions beween PIN and Size (-0.57) and beween PIN and Analyss (-0.47) are expeced and consisen wih he prior lieraure. 5. Analysis and resuls In his secion, we describe he regression analyses we carry ou o es our hypoheses. Before doing so, we firs presen preliminary evidence based on a bivariae analysis relaing PIN o he number of consecuive quarers for which a firm has me/beaen or missed expecaions. We hen formally es he associaion beween PIN and MBE (H), and beween he componen 3

15 parameers of PIN and MBE (H2). Nex, we es wheher here is an incremenal associaion beween PIN and MBE when a firm habiually mees or beas expecaions (H3). Finally, we examine wheher he relaion beween PIN and MBE depends on wheher he good earnings performance was likely achieved hrough expecaions or earnings managemen (H4). 5.. Preliminary evidence Table 3 and Figure show he level of PIN according he number of consecuive quarers for which a firm mees/beas or misses he analys consensus forecas of earnings. Negaive values indicae he number of consecuive quarers ha a firm has missed expecaions. Daa for he numbers of quarers below 4 and exceeding +24 have been winsorized a 4 and +24, respecively, because here are relaively few observaions wih values exceeding hese cuoffs. Figure clearly shows an almos monoone decrease in PIN from jus over 20% down o jus over % as he MBE sring increases from o 24 quarers. This preliminary evidence suppors our expecaion ha meeing or beaing earnings expecaions is associaed wih he level of informaion asymmery. Firms ha have missed expecaions experience higher PIN han MBE firms. While here is no apparen paern beween PIN and he number of consecuive Miss quarers, he average value of PIN (over 20.5%) is quie high for hese firms. The above analysis is only suggesive since i does no conrol for oher confounding effecs, such as he negaive correlaion beween Size and PIN and he posiive correlaion beween Size and MBE. We address such issues wih our formal regression analyses Associaion of PIN and MBE ess of H and H2 We examine wheher PIN decreases in he quarer afer a firm mees or beas is benchmark level of earnings. To accomplish his, we express changes in PIN as a funcion of MBE and changes in he conrol variables, as follows: 4

16 ΔPIN + = 0 + βmbe + β2δanalys + + β3δsize + + μ + β (2) where ΔPIN + = PIN + PIN, and analogously for ΔAnalys + and ΔSize +. Recall ha PIN is measured in even ime, so ΔPIN + measures he change in PIN from he approximaely welve-week period immediaely prior o he earnings announcemen for quarer o he welveweek period immediaely aferwards. The inercep (β 0 ) represens he average change in PIN for firms ha miss expecaions (i.e., MBE = 0) condiional on no changes in size or analys following. Based on Hypohesis H, we predic ha β 0 > 0 and β < 0. Panel A of Table 4 shows ha here is a significan increase in PIN when a firm fails o mee or bea is earnings expecaions. On average, PIN increases by a significan 0.23% (-saisic = 5.7) during he following quarer afer missing is earnings benchmark. In conras, he significan negaive coefficien on MBE (-saisic = -4.98) indicaes ha PINs are lower by 0.27% when a firm mees or beas, raher han misses, is arge level of earnings. We also esimae a levels version of equaion (2) where PIN is included as an addiional conrol variable. The unabulaed resuls are similar as he coefficien on MBE is (-saisic = -6.46). 2 Togeher, hese findings provide srong suppor for hypohesis H. To he exen he ype of informaion risk capured by PIN is priced in he marke, he MBE valuaion premium is a leas parially explained by a reducion in he cos of capial for MBE firms. In addiion, he coefficiens for he conrol variables are srongly significan and consisen wih our expecaions. Specifically, increases in firm size and he exen of analys coverage are associaed wih reducions in he level of informaion asymmery. We nex examine he associaion beween MBE and he componens ha comprise he PIN esimae using equaions ha are analogous o equaion (2), bu wih he dependen variable 2 In addiion, he resuls of levels versions of he analyses presened in Tables 5 7 are all qualiaively similar o he changes specificaions and he inferences remain he same excep where specifically noed. 5

17 being an individual PIN parameer (α, ν, and ε). These analyses provide insighs ino he source of he negaive associaion beween MBE and informaion asymmery. As shown in Panel B of Table 4, we find no evidence ha he probabiliy of an informaion even (α) is affeced by wheher a firm mees or misses expecaions. However, as prediced, we do find in Panel C ha he amoun of informed relaive o uninformed rading (ν) decreases (coefficien = -0.08, -saisic = -4.9) and in Panel D ha he absolue amoun of uninformed rading (ε) increases (coefficien = 4.0, -saisic =.87) in he following quarer when a firm mees or beas is earnings benchmark. The magniude of he MBE coefficien in he ε regression indicaes ha in he quarer afer a firms mees or beas is benchmark he number of rades by uninformed invesors increases on average by abou 8 rades per day ( ). This represens an increase of 3.4% (0.0%) relaive o he mean (median) value of ε shown in Table. In comparison, he change in ν is more modes, a 2% (2.5%) of he mean (median) value. In summary, he resuls in Panels B D provide parial suppor for hypohesis H2. The resuls indicae ha MBE firms experience a significan increase in he amoun of rading by uninformed invesors, boh in absolue erms and relaive o he amoun of informed rading. However, we find no evidence indicaing ha MBE is associaed wih reduced incenives o search for privae informaion abou earnings. To furher explore he relaion beween MBE/Miss and he level of informaion asymmery, we examine wheher he magniude of he earnings surprise is incremenally associaed wih he change in informaion asymmery. Tha is, we look a wheher he associaion beween asymmery and earnings performance varies depending on wheher he firm jus mees or slighly beas (misses) is earnings benchmark or exceeds (misses) he arge by a wide margin. We caegorize firms ino four groups using four indicaor variables: 6

18 BigMee = if MBE = and (acual EPS consensus EPS forecas) > $0.02; SmallMee = if MBE = and (acual EPS consensus EPS forecas) $0.02; SmallMiss = if MBE = 0 and (acual EPS consensus EPS forecas) -$0.02; BigMiss = if MBE = 0 and (acual EPS consensus EPS forecas) < -$ We examine wheher he associaion beween PIN and earnings performance varies depending on he size of he earnings surprise using equaions ha are analogous o equaion (2), bu including in he regression hree of he four indicaors (BigMee, SmallMee, and SmallMiss) in place of MBE. The inerpreaion of hese coefficiens is relaive o he effec of a relaively large earnings shorfall (BigMiss = ) on informaion asymmery. The resuls of hese analyses are presened in Table 5 and show he effec of differen magniudes of earnings surprises on he quarerly change in PIN. The coefficiens on all hree earnings surprise variables are significanly negaive, indicaing ha relaively large misses resul in he larges increases in informaion asymmery. Consisen wih larger posiive surprises leading o larger declines in PIN, he coefficien on BigMee (-0.47) is more negaive han he SmallMee coefficien (-0.33), which in urn is more negaive han he SmallMiss coefficien (-0.24). F-ess indicae ha he BigMee coefficien is significanly more negaive han he oher wo coefficiens (boh p-values < 0.0), bu ha he SmallMee and SmallMiss coefficiens are no significanly differen from each oher (p-value = 0.25). 4 These resuls sugges ha bigger posiive earnings surprises lead o increased invesor recogniion, which in urn leads o larger reducions in informaion asymmery. Likewise, larger negaive earnings surprises lead o larger increases in asymmery compared o smaller earnings shorfalls. 3 These cuoffs were deermined o ensure an adequae number of observaions in each caegory. Approximaely 4%, 0%, 49%, and 26% of observaions fall ino he BigMiss, SmallMiss, SmallMee, and BigMee caegories, respecively. The resuls are no sensiive o using alernaive cuoff values. 4 Unabulaed resuls for he levels specificaion are similar excep he SmallMiss coefficien is no longer significan, bu he difference beween he SmallMee and SmallMiss coefficiens becomes significan. 7

19 5.3. Associaion of PIN and MBE hisory es of H3 According o hypohesis H3, MBE (Miss) firms ha have repeaedly me or beaen expecaions in prior periods experience larger decreases (increases) in he level of informaion asymmery compared o firms ha have done so less regularly. We define an indicaor variable, Habiual, ha equals if in quarer, firm i has me or beaen expecaions in a leas six ou he eigh previous quarers (i.e., quarers 8 o ). We hen esimae he following equaion: ΔPIN + = δ + δ MBE δ ΔAnalyss + δ Habiual δ ΔSize + δ MBE η + Habiual To avoid survival bias, we include only observaions ha have a a minimum of 8 quarers of (3) pas daa. Hypohesis H3 predics ha δ 2 > 0 and δ 3 < 0. Noe ha δ 2 capures he incremenal effec of a quarer Miss for firms ha had habiually me expecaions in quarers prior o. The resuls in Table 6 show ha here are indeed addiional benefis o repeaedly meeing or beaing expecaions, consisen wih hypohesis H3. The coefficien on MBE Habiual is significanly negaive (-saisic = -.89; one-sided p-value = 0.03). In addiion, he MBE coefficien is no longer significan, as i was in Table 4. F-ess srongly rejec he hypoheses ha he coefficiens on MBE Habiual and MBE are boh equal o zero (F-saisic = 4.5; p-value = 0.02) and ha he sum of he wo coefficiens is equal o zero (F-saisic = 8.26; p-value < 0.0). Togeher, he resuls indicae ha he average reducion in PIN ha arises hrough meeing or beaing expecaions is minimal unless i is par of a repeaed paern. The significan posiive coefficien on Habiual (δ 2 = 0.233, = 2.6) indicaes ha PIN increases more when a habiual beaer misses expecaions compared wih non-habiual firms ha miss expecaions. This relaion beween informaion asymmery and MBE (Miss) for firms ha had habiually me or beaen he benchmark level of earnings is similar o he associaion beween he MBE valuaion premium and habiual MBE firms documened in Barh e al. 8

20 (999), Barov e al. (2002) and Kasznik and McNichols (2002), among ohers. This similariy furher suppors our argumen ha he observed pricing premium associaed wih MBE is a leas parially explained by a denominaor effec driven by changes in informaion asymmery Effec of expecaions or earnings managemen on he associaion beween PIN and MBE ess of H4 In his secion, we examine wheher he relaion beween MBE and informaion asymmery is weakened when a firm is more likely o have managed expecaions or earnings in order o mee he earnings benchmark (H4). As expecaions and earnings managemen aciviies are no direcly observable, we can only idenify insances in which such aciviies are more or less likely o have occurred. Following Barov e al. (2002), we compare he consensus forecas a wo poins in ime o idenify insances where expecaions managemen is more likely o have occurred. We idenify MBE firms where he laes EPS forecas before he earnings announcemen dae for firm i is lower han he earlies EPS forecas following he prior quarer s earnings announcemen, and acual EPS is less han he earlies EPS forecas. In oher words, he firm did no MBE is beginning-of-period earnings arge bu did so relaive o is end-ofperiod arge. In hese cases, we se he indicaor variable ExpMan = ; oherwise he variable equals zero. This classificaion scheme causes 27% of observaions o be idenified as likely o have managed expecaions downwards in order o mee or bea heir earnings arge. To idenify firms ha are more likely o have managed earnings, we esimae he level of discreionary accruals using he residuals from he following modified-jones model: ToAccr / TA = κ 0 +κ ( / TA ) +κ 2 (ΔSales ΔRec )/TA +κ 3 PPE / TA + ι. (4) ToAccr is oal accruals, measured as he change in non-cash curren asses (Compusa quarerly iem 40 iem 36) less he change in non-deb curren liabiliies (iem 49 iem 45) less 9

21 depreciaion (iem 5). TA is oal asses (iem 44), Sales is iem 2, Rec is accouns receivable (iem 37), and PPE is propery, plan and equipmen (iem 42). The model is esimaed separaely for each quarer and for each 2-digi SIC code. We require a minimum of 8 observaions per regression. Based on hese esimaes of discreionary accruals, we classify firms as having managed earnings upwards in quarer if he residual from equaion (4) is posiive, MBE =, bu MBE would have equaled zero if discreionary accruals had been zero. Tha is, when he firm was only able o mee he earnings arge because i had posiive discreionary accruals, we se he indicaor variable EarnMan equal o ; oherwise, i equals zero. This classificaion scheme resuls in 40% of observaions being idenified as likely o have managed earnings upwards in order o mee or bea heir earnings benchmark. We hen esimae he following equaion o es hypohesis H4: Δ PIN = φ 0 + φmbe + φ2expman + φ3earnman + φ4δanalys + + φ5δsize + + ξ + (5) We coninue o expec ha firms benefi from meeing or beaing expecaions, so φ < 0. However, we predic ha firms ha are more likely o have managed expecaions or earnings will have an aenuaed MBE effecs o he exen hese effors are observed by he marke. Therefore, we expec φ 2 > 0 and φ 3 > 0. Table 7 presens he resuls of his regression. The sample is reduced o abou half of ha used in Table 4 because of he addiional daa requiremens. We find ha he MBE coefficien is significanly negaive (φ = -0.48, -saisic = -5.24) and similar in magniude o ha repored in Table 4. We find ha he coefficien on ExpMan is significanly posiive as prediced (φ 2 = 0.50, -saisic = 7.93) and in fac is slighly larger han he MBE coefficien in magniude. Thus, he MBE effec is aenuaed o such an exen ha here are no significan benefis for meeing or beaing expecaions (φ + φ 2 = 0.092, F-saisic =.06, p-value = 0.30) when i 20

22 likely has been accomplished by managing expecaions. In comparison, we find no evidence ha engaging in earnings managemen reduces he associaion beween PIN and MBE. The coefficien on EarnMan is quie small in magniude and is insignificanly differen from zero (φ 3 = 0.089, -saisic =.4). Overall, we find evidence ha he associaion beween informaion asymmery and meeing/beaing expecaions subsanially weakens for firms ha manage expecaions bu no earnings. We conjecure ha he differences in resuls for he wo managemen echniques are due o he relaive ease of idenifying expecaions managemen, which only requires ha one is able o observe analys forecass a he beginning and end of each quarer. In conras, i is much more difficul o conclusively idenify cases of earnings managemen. The resuls are also consisen wih here being subsanially more measuremen error for he earnings managemen variable (Dechow e al. (995)). However, i is unclear if invesors have a beer measure of earnings managemen Effec of expecaions and earnings managemen on he associaion beween MBE and reurns. The analyses in he prior secion correspond o similar analyses in Barov e al. (2002). Based on a sample period ( ) ha largely predaes ours ( ), hey find ha he reducion in he pricing premium remains saisically significan alhough somewha small in magniude in cases where earnings managemen is suspeced, while he premium is reduced by over 50% in cases where expecaions managemen is likely. As such, heir findings and our informaion asymmery resuls are no fully consisen wih each oher. One possible explanaion for he differences beween resuls is ha he repored earnings game beween analyss, invesors, and firms has evolved over ime (Brown and Caylor (2004)). Accordingly, we examine he associaions beween MBE and he pricing premium in 2

23 he presence of expecaions and earnings managemen in our sample, and deermine o wha exen hey correspond o he asymmery resuls in Table 7. Following Barov e al. (2002), we use he following regression equaion o assess he MBE pricing premium in cases where earnings or expecaions managemen were likely o have been used o mee he earnings expecaions: CAR = α 0 + αfcerrori, + α 2MBE + α3mbe Manage + ε (6) where Manage equals ExpMan or EarnMan depending on he specificaion. CAR is he cumulaive abnormal (bea-adjused) reurn beginning wo days following he dae of he firs forecas for he quarer subsequen o he prior quarer s earnings announcemen o one day afer he curren earnings announcemen. FCError is he difference beween he acual earnings per share and he earlies consensus (median) forecas during he quarer deflaed by beginning of quarer share price. 5 Due o he addiional daa requiremens, he number of firm-quarer observaions is reduced o 2,025. The resuls from esimaing equaion (6) when Manage ExpMan are presened in Table 8, Panel A. Consisen wih he prior lieraure, he coefficien on MBE is posiive and significan (-saisic = 6.84). The magniude of he coefficien indicaes ha MBE firms are priced a a 5.4% premium relaive o oher firms, which is consisen wih he prior lieraure. As expeced, he MBE pricing premium is significanly lower in cases where expecaions managemen is more likely o have aken place. Adding he ineracion coefficien wih he MBE coefficien (φ 2 + φ 3 ) indicaes ha he MBE premium is reduced o.7% in cases where expecaions managemen is likely. This amoun, while saisically significan (p-value = 0.000), is economically small. Furhermore, unabulaed analyses indicae ha when we 5 Unabulaed analyses show ha our resuls are qualiaively unchanged if cumulaive raw reurns are used insead of cumulaive abnormal reurns or if he firs forecas is used insead of he firs consensus forecas. 22

24 include ExpMan as a separae variable in he regression (i.e., he main effec, in addiion o he ineracion wih MBE), he MBE premium in cases of expecaions managemen is reduced o an insignifican 0.67%. This finding corresponds o he resul in Table 7 ha here is no significan reducion in informaion asymmery for MBE firms ha likely engaged in expecaions managemen. The resuls from esimaing equaion (6) when Manage EarnMan are presened in Table 8, Panel B. The MBE coefficien remains posiive and significan (3.7%, -saisic =.8), andhe ineracion erm is close o zero and is no saisically significan (-saisic = 0.04). Thus, we find no evidence of a reducion in he MBE premium in cases where i is more likely ha he firm used earnings managemen in order o mee is earnings benchmark. Our inferences remain he same when EarnMan is included as an addiional regressor. This finding corresponds o he resul in Table 7 ha he reducion in informaion asymmery for MBE firms does no depend on wheher hey likely engaged in earnings managemen. 6. Summary and Conclusions This sudy proposes a discoun rae denominaor effec explanaion for he previously documened pricing premium for firms ha are able o mee or bea invesors earnings expecaions. We hypohesize ha meeing or beaing (missing) earnings expecaions leads o real changes in firms rading and informaion environmens ha resul in a decrease (increase) in informaion asymmery. Relying on prior heoreical and empirical sudies ha link he cos of equiy capial o he level of informaion asymmery, documening a negaive relaion beween MBE and informaion asymmery provides indirec evidence supporing he proposed denominaor effec. 23

25 The resuls of our ime-series ess indicae ha informaion asymmery decreases over he subsequen quarer when a firm mees or beas earnings expecaions and increases afer a firm misses is earnings expecaions. We conduc addiional analyses ha correspond o several of he findings in he MBE pricing lieraure in order o provide addiional evidence on crosssecional variaions in he relaions. These ess indicae () he magniude of he change in asymmery is posiively relaed o he absolue magniude of he earnings surprise; (2) he decrease (increase) in informaion asymmery is larger for MBE (Miss) firms who have regularly me or beaen expecaions over he prior eigh quarers; and (3) he decrease in informaion asymmery is unaffeced (eliminaed) for firms ha likely used earnings (expecaions) managemen in order o MBE. Overall, hese findings mimic corresponding MBE pricing resuls in Barh e al. (999), Barov e al. (2002) and Kasznik and McNichols (2002) and provide furher suppor for our proposed denominaor effec. Our analyses of he componens of our informaion asymmery proxy reveal ha he benefis of MBE derive primarily from an increase in he amoun of uninformed rading, which causes he relaive amoun of informed rading o decrease. These resuls are consisen wih he Invesor Recogniion Hypohesis of Meron (987) and Fishman and Hagery (989). In addiion, we do no find ha he probabiliy ha a privae informaion even occurs is associaed wih a firm s earnings performance, suggesing ha he MBE does no srongly affec he incenives o search for privae informaion. Our resuls provide suppor for a denominaor explanaion for he observed MBE pricing premium: MBE firms experience a decrease in informaion asymmery, which lowers he COC, which in urns leads o higher sock prices. Idenifying he relaive conribuion of various 24

26 numeraor (cash flow or earnings) effecs and denominaor effecs is an unresolved issue ha is beyond he scope of his paper. We leave his quesion for fuure research. 25

27 Appendix: Vener and de Jongh (2004) Exension of EKO Model While he exended EKO model mainains he assumpion ha uninformed buy and sell orders arrive each day based on a Poisson disribuion, i allows he daily inensiy of he arrival rae o vary. The arrival rae of uninformed buys and sells is given by εw, where W is a random variable wih E[W] =. On good-news (bad-news) days, informed raders also place buy (sell) orders a arrival rae νεw ; hus, he disribuion of buys (B) and sells (S) on day is given by: (B, S ) no-news, W ~ Independen Bivariae Poisson (εw, εw ) (B, S ) bad-news, W ~ Independen Bivariae Poisson (εw, ε(+ν)w ) (B, S ) good-news, W ~ Independen Bivariae Poisson (ε(+ν)w, εw ). The likelihood funcion induced by he model for a paricular rading day, condiional on he Poisson rading inensiies λ B and λ S for buys and sells, respecively, is given by: L (B,S λ B,λ S ) = f POISS (B,S λ B,λ S ) = (λ B ) B B! * (λ S ) S S! * e λ B λ S. (A) The overall likelihood funcion is a mixure model where he weighs on he hree componens (no news, bad news, and good news) reflec he probabiliies of heir occurrence in he daa. Denoe he rading inensiy of boh buys and sells ha arises on a paricular no-news day by: λ N = εw, so he rading inensiy depends on he day-specific value of he random variable, W. Similarly, he combined rading inensiy (by boh informed and uninformed) on a news day is: λ I = ε(+ν)w. Therefore, we can wrie he likelihood of observing a paern of B buys and S sells, condiional on hese parameers, as: L (B,S λ N,λ I ) = L (B,S ε,μ,w ) =( α) f POISS (B,S λ N,λ N ) + αδ f POISS (B,S λ N,λ I ) + α( δ ) f POISS (B,S λ I,λ N ) where f POISS (B, S λ B, λ S ) denoes he probabiliy of observing B buys and S sells on a paricular day given ha buy orders are arriving wih Poisson inensiy λ B, and sell orders are 26