Market inefficiency and implied cost of capital models

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1 Make neffcency and mpled cos of capal models Tjomme O. Ruscus Kellogg School of Managemen Nohwesen Unvesy 00 Shedan Road sue 69 vanson IL 6008 Mach 0 BSTRCT In hs pape I examne he mpac of make neffcency on he popees of mpled cos of capal ( models. I develop a smple model of measuemen eo n mpled cos of capal models sang fom he undelyng pmves nvesos and eseache s eanngs foecass and show ha unde easonable assumpons make neffcency wll bas he esmae and he fuue euns n he same decon. Ths esuls n a posve elaon beween esmaes and fuue euns. Usng a vaey of appoaches I show ha fo he medan esmae beween 44% and 69% of he elaon beween esmaes and one-yea-ahead sock euns sems fom mspcng ahe han expeced euns. I also show he effec of mspcng s dascally educed when usng a value weghed analyss whch suggess hs may be a useful way o mgae effec of mspcng on he esmaes. In subsequen analyses I fnd ha whle nuvely appealng conollng fo eanngs and dscoun ae news s unlkely o be effecve n mgang bases nduced by mspcng whn he se of measues I consde n my analyses. I appecae helpful commens fom semna pacpans a he Duke/UNC Fall camp and UCL. I hank Ia Yeung fo excellen eseach asssance. I am gaeful fo fnancal suppo fom he ccounng Reseach Cene a he Kellogg School of Managemen.

2 . Inoducon Cos of capal s an mpoan concep n fnance and accounng eseach. The leaue has long ecognzed ha aveage ealzed euns offe a vey nosy poxy of he cos of equy capal (e.g. lon 999. Impled cos of capal ( models poenally offe a pomsng alenave fo esmang cos of capal even f he esmaes fom hese models conan some nose as well. ccounng eseaches have used hese models o assess he effecs of dsclosue qualy (e.g. Boosan 997 and eanngs qualy (e.g. Fancs LaFond Olsson and Schppe 004 on he cos of equy capal. Many dffeen models have been developed n he leaue and he queson s how o evaluae he qualy of he measues. Common appoaches n he leaue nclude es of he assocaon beween esmaes and a sees of poposed sk facos based on po eseach (e.g. Gebhad Lee and Swamnahan 00; Boosan and Plumlee 005 he assocaon fuue sock euns (e.g. Guay Koha and Shu 005 and he assocaon wh fuue sock euns wh conols fo news (ason and Monahan 005. hd appoach developed n ason and Monahan (005 es o explcly model he measuemen eo n he poxes ahe han ely on any pacula egesson esmae. Whch of hese appoaches s bes s he subjec of an ongong debae (e.g. Boosan Plumlee and Wen 00; ason and Monahan 00. Gven ha he qualy of esmaes s mul-dmensonal s unlkely ha one appoach s suffcen. No only he vaance of he measuemen eo bu also he exen o whch s coelaed wh he ue dscoun ae poenal mspcng and ohe fm chaacescs maes fo eseach puposes. In hs sudy I focus on mpac of poenal make neffcences on he popees of esmaes and n pacula he Recen examples of sudes usng mulple appoaches nclude Gode and Mohanam (003 Boosan Plumlee and Wen 00 Hou Van Djk and Zhang (00 and Lee So and Wang (00.

3 effec on he elaon beween esmaes and fuue euns. Gven ha many of he sk poxes ae dawn fom po leaue based on he ably o pedc fuue euns he fndngs n hs pape have mplcaons fo hose ess as well. To he exen esmaes vay n he ably o capue mspcng can have seous mplcaons fo he selecon of esmaes fo eseach and paccal puposes. In hs pape I develop a model sang fom he undelyng pmves nvesos and eseache s eanngs foecass. Ths appoach complemens appoaches n ason and Monahan (005 and Lee So and Wang (00 whch sa fom he assumpon of a nosy cos of capal poxy. The advanage of sang fom he undelyng pmves s ha povdes moe nsgh no he souces and elave mpoance of measuemen eos n he esmaes. s a esul hs appoach can povde moe gudance as o he decon and magnude of he bases nduced by hese measuemen eos. The model shows ha unde easonable assumpons make neffcency wll esul n a posve elaon beween esmaes and fuue euns and ha hs wll esul n an upwad based esmae on he coeffcen n a egesson of fuue euns on esmaes. In he empcal pa of he pape I y o quanfy he elave mpoance of expeced euns and mspcng. I use he appoach n Hou Van Djk and Zhang (00 as exended by Lee So and Wang (00 n foecasng eanngs and calculang esmaes. Conssen wh hese papes I fnd ha esmaes pedc fuue sock euns. I use wo appoaches o sepaae he compeng hypoheses fo hese euns. Fs I use eanngs announcemen euns o povde a lowe bound on mpoance of mspcng. Based on he fou models I examne eanngs announcemen euns accoun fo 6% o 5% of he euns o a hedge pofolo based on he exeme decles of esmaes. My second appoach es o esablsh an uppe bound

4 on he mpoance of mspcng by lookng a he facon of he aveage hedge pofolo eun ha s no explaned by he Fama-Fench (993 hee faco model. Based on he fou models I examne he facon of he pedced eun unexplaned by he hee facos s beween 59% and 83% of he expeced eun. Oveall hese esuls sugges ha fo equal weghed euns a lage facon of he explanaoy powe s due o mspcng nsead of expeced euns. Resuls fo value weghed euns show a much smalle elave effec of mspcng fo mos bu no all models. Ths suggess ha value weghng s a elavely effecve mehod o mgae he effec of mspcng. Usng value weghng n ess desgned o selec he bes esmaes educes he lkelhood ha esmaes ae chosen because hey ae paculaly affeced by mspcng. I also suggess ha n applcaons usng esmaes one should use a value-weghed analyss when usng esmaes o es whehe a poposed sk faco s pced. ddonally n hese cases s mpoan o es euns aound fuue eanngs announcemens o make sue ha he poposed sk faco s no an anomaly n dsguse. Snce analyses of eanngs announcemens have much hghe sascal powe han annual buy and hold euns hs should no pose an undue buden. The second pa of he empcal wok consdes whehe conollng fo news poxes povdes an effecve conol fo he bases nduced by mspcng. The model shows ha heoecal case fo conollng fo news s ambguous and ha he usefulness depends on he mpoance of measuemen eo n he eseache esmaes of eanngs and by exenson he esmaes. My analyses sugges ha he deconal effecs of he ncluson of news poxes on he coeffcen ae mos conssen wh eseache nduced measuemen eo ahe han eos n ealzed euns. I conclude ha on balance my analyses sugges ha he poenal benefs of ncluson of he news poxes do no ouwegh he sks. 3

5 The analyss n hs pape conbues o he leaue on mpled cos of capal esmaes and should be of use o eseaches neesed n evaluang alenave cos of capal esmaes o applyng esmaes n ess of poposed sk facos. Fom a pofolo selecon pespecve he analyses n hs pape should be helpful n deemnng he exen o whch esmaes can be used o ean abnomal euns. The emande of hs pape s oganzed as follows. In he nex secon I dscuss he model and he pedcons egadng he elaon beween esmaes and fuue euns and he effec of ncludng poxes fo eanngs news and dscoun ae news. Then n secon 3 I dscuss he daa and he calculaon of he fou mpled cos of capal models. In secon 4 I dscuss he eseach desgn and he esuls and I conclude n secon 5.. Modelng mpled cos of capal unde make neffcency In valung a sock nvesos use expecaons of eanngs and dscoun aes o ave a a pce. Impled cos of capal models nve hs pocess by usng he obseved pce of he sock and eseaches esmaes of eanngs o deve a dscoun ae mpled by he obseved make pce. I s well ecognzed n he leaue ha he esulng esmaes wll be nosy f he eseache canno accuaely esmaed he nvesos expecaons of eanngs. lo of he po leaue s focused on modelng he developmen of eanngs afe he fs yea and whehe analyss foecass can be used as a elable esmae of nvesos expecaon of eanngs. In hs secon I focus nsead on he popees of he mpled cos of capal measue when n addon he nvesos expecaons ae nosy vesons of he ue expeced eanngs. The model s sucued as follows. Fo smplcy eanngs ae eaed he same as cash flows heefoe nsead of usng a dscouned cash flow model he model pacpans wll use a dscouned eanngs model. Boh nvesos and he eseache foecas eanngs one peod ahead 4

6 and boh nvesos and he eseache assume ha eanngs ( ae a andom walk afe ha and ha he dscoun ae ( s a me-sees consan. The fm s nfnely lved. Thus he pce of he sock (P can be expessed as follows: P ( The eseache obseves hs pce and foms hs own expecaons of he one peod ahead eanngs o compue he mpled cos of capal. Thus he mpled cos of capal ( can be expessed as follows: ( P The supescp on he expecaon opeaos ndcaes a subjecve expecaon ( = nveso and = eseache. Much of he po leaue on developng and evaluang mpled cos of capal esmaes focuses on he nose noduced by he eseache s choce of he nal eanngs esmaes and he appopae model fo he developmen heeafe (e.g. andom walk o mean eveson. In he model I wll jus focus on he qualy of he eanngs esmae and no on he choce of he eanngs developmen heeafe. Ths smplfcaon s whou much loss of genealy as he choce of eanngs developmen model s also a foecas of eanngs. Nex I wll dscuss fs sepaaely dscuss he popees of he esmae and fuue euns unde make neffcency. Then I deve he elave mpac of he mspcng on he esmaes vesus fuue euns. Ths s followed by an analyss of he effec of mspcng on he Ths pecludes he bases noduced by a sochasc dscoun faco such as hose dscussed n Hughes Lu and Lu (009. 5

7 elaon beween fuue euns and esmaes. Fnally I dscuss he poenal of alenave appoaches o coec fo he effec of mspcng.. Devaon of he mpled cos of capal esmaes The key nnovaon n he model s an examnaon of he effec of poenal make neffcences on he popees of mpled cos of capal esmaes. Ths s mpoan because po leaue has documened a vaey of anomales nsances n whch nvesos do no appea o coecly pce (accounng nfomaon see Rchadson Tuna and Wysock (00 fo a ecen suvey. Ths mspcng can affec he qualy of mpled cos of capal esmaes snce he sock pce s used n he consucon of hese esmaes. In he conex of he model make neffcences ase when nvesos foecas fuue eanngs ncoecly gven he avalable nfomaon a he me of he foecas (Ω. Thus he nvesos eanngs expecaon can be expessed as he ue eanngs expecaon gven he avalable nfomaon plus an eo em (ε: (3 Usng hs defnon fo he nvesos eanngs expecaon he sock pce can be chaacezed as follows: P (4 Ths expesson has a vey nuve nepeaon f nvesos oveesmae (undeesmae fuue eanngs he sock pce wll be hghe (lowe. In devng he own eanngs foecas deally he eseache use he same (poenally based eanngs foecas ha he nvesos used. In ha case he eo n he eanngs foecas would offse he eo n he sock pce and mpled cos of capal esmae would equal he dscoun ae nvesos used. In pacce he nvesos eanngs expecaons ae no eadly obsevable and eseaches have o make he own foecass of eanngs. The naual poxy 6

8 analyss foecass of eanngs s subjec o well documened bases such as analyss opmsm whch has been shown o advesely affec he qualy of esmaes (ason and Sommes 007. Recen advances usng egesson models o esmaed fuue eanngs manage o educe he aveage bases n foecass bu sll conan subsanal measuemen eo (Hou Van Djk and Zhang 00. Theefoe I model he eseache s eanngs foecas as he foecas based on all avalable nfomaon a he me of he foecas (Ω plus measuemen eo (labeled u. The measuemen eo s assumed o have a zeo mean. In ha case: u (5 I s lkely ha he eos n he eseache s and nvesos eanngs foecass ae coelaed fo example f boh ae based n pa on analyss foecass. I heefoe allow hese eos o be coelaed n he model. Usng hese wo subjecve eanngs expecaons he cuen sock pce and he can be expessed as follows: P u (6 Fom hs expesson s clea ha he wo ypes of eos have oppose effecs on he esmae. If he eseache oveesmaes fuue eanngs (u > 0 he wll be hghe han he ue dscoun ae wheeas f he nvesos oveesmae fuue eanngs (ε > 0 he wll lowe han he ue dscoun ae. s dscussed eale f he wo eos ae dencal hen he wll equal he ue dscoun ae. I s also nsucve o consde f he mpac of he eseache s and nvesos eo on he aveages ou n a boad coss-seconal sample. I deved he expeced allowng he wo eo ems o be coelaed wh each ohe bu no wh he ue dscoun ae. Usng a second ode Taylo expanson yelds he followng (deals ae povded n he ppendx: 7

9 cov( u va( (7 Thee ae seveal noewohy feaues n hs expesson. Fs by self he nose n eseache s eanngs esmae aveages ou n he coss-secon. The eason s ha he eseache s eo s assumed o be mean zeo and he s lnea n he eseache s eanngs esmae n he seng consdeed hee nfnely lved fms wh eanngs ha follow a andom walk. 3 Second he effec of mspcng on he does no fully aveage ou even hough he eo has a zeo mean. Usng hs esmaon eo vaance as a measue of he neffcency of he sock make follows ha he s upwadly based fo socks ha ade n less effcen makes alhough he magnude of hs effec s expeced o be elavely small as long as he mspcng s modes. 4 Fnally he upwads bas nduced by make neffcency s mgaed f he eseache s eo covaes posvely wh he nveso s esmaon eo. If he eseache exhbs all he same bases as he nvesos bu o a lage degee hen he covaance em s lage han he vaance em and he pedcons evese. x-ane hs seems unlkely and n he model I only consde he case n whch he covaance s weakly smalle han he vaance.. Chaacezaon of ealzed euns The ealzed euns n he model ae a funcon of he expeced euns and news. Thee ae wo souces of news n he model. Fs hee s news abou fundamenals as eanngs fo 3 Ths lneay does no geneally hold. If one consdes a fnely lved fm unde ohewse smla assumpons he s no longe lnea n he eseache s eanngs esmaes and heefoe he wll be based n he pesence of hese eos. Fo example Lambe (009 consdes a wo-peod fm and shows ha he s downwadly based n he pesence of eos n he eseache s eanngs esmae. To he exen ha he combned assumpon of a andom walk and an nfnely lved fm s a easonable appoxmaon he bas s lkely o be small. 4 Fo example n he case whee he sandad devaon of he nvesos eo s en pecen of he ue eanngs expecaon he upwad bas n he s only one pecen of he dscoun ae (. Fo a dscoun ae of 0% hs would mply an upwad bas of 0 bass pons. 8

10 peod + ae ealzed whch also affecs eanngs foecas fo all fuue peods. Second he eanngs news may gge a change n he amoun of mspcng. The pce a he end of + s hus he sum of he ealzed eanngs (cash flows and he pesen value of expeced fuue eanngs whch can agan ncopoae an esmaon eo em. P n n (8 To be ue news he eanngs news (n has o have zeo mean and be uncoelaed wh he ohe andom vaables n he model. s wh he egula eanngs he news n eanngs s assumed o be a andom walk. To capue he possbly ha he cuen mspcng does no fully evese self n he nex peod I allow he fuue mspcng o be coelaed wh he cuen mspcng. In pacula I decompose he fuue eo no wo componens he facon of he old esmaon eo ha pesss ( and new eo ( +. The pessence paamee ( s expeced o be geae han 0 and scly less han. Ths yelds he followng expesson fo he fuue pce: P ( ( n (9 Usng hs expesson fo he pce a + and he expesson fo he pce a (equaon 4 he ealzed euns can be chaacezed as follows: R P P ( n ( (0 P Thus fuue euns ae nceasng n he dscoun ae ( he eanngs news (n he pessence of pas oveesmaon ( and he amoun of new oveesmaon ( of fuue eanngs. If hee wee no mspcng hs expesson smplfes o ealzed euns equalng expeced euns plus news. s wh he s nsucve o consde he mpac of he make effcency on he 9

11 ealzed euns n a boad coss-seconal sample. Usng a second ode Taylo expanson yelds he followng (deals ae povded n he ppendx: ( va( R ( In hs case even hough he nvesos esmaon eo has a zeo mean and he pce s coec on aveage he ealzed euns no equal he expeced euns on aveage. Ths occus because he mspcng affecs boh he numeao (fuue change n pce and he denomnao (cuen peod pce of he fuue euns. In pacula ealzed euns wll on aveage be hghe han he dscoun ae. The exen of he bas s nceasng n he vaance of esmaon eos and facon of mspcng ha eves whn he peod (-. The magnude of he bas s expeced o be elavely small as long as he mspcng s modes hough lage han he equvalen bas nduced n he sample aveage. 5.3 Relave mpac of mspcng on mpled cos of capal and ealzed euns The po secons demonsae ha boh ealzed euns and mpled cos of capal esmaes ae affeced by mspcng. Consequenly one should be caeful o n usng measues o sepaae sk fom mspcng explanaons of anomales as unde boh hypoheses we would expec a lnk beween he poenally mspced vaable and he mpled cos of capal. s a eseache we canno decly obseve he nose n he nvesos eanngs esmaes bu we may be able o measue some faco ha s coelaed wh he nose. Fo example accodng o Sloan (996 nvesos oveesmae fuue eanngs fo fms wh hgh accuals and as a esul hese fms ae ovevalued. In ha case eseaches usng unbased eanngs esmaes 5 Fo example n he case whee he sandad devaon of he nvesos eo s en pecen of he ue eanngs expecaon he upwad bas n he aveage ealzed euns s one pecen of he sum of he dscoun ae ( and (- wheeas he effec on he s only one pecen of he dscoun ae (see also foonoe 4. Fo a dscoun ae of 0% and a mspcng pessence paamee of 0.4 hs would mply an upwad bas of 70 bass pons vesus 0 bass pons fo he esmae. lso noe ha value weghed aveage euns do no suffe fom hs poblem. 0

12 along wh hese ovesaed sock pces would hen oban downwad based esmaes. Smlaly fms wh low accuals would have an undevalued sock pce and hence upwad based esmaes. Ths ases he queson whehe one of he wo cos-of-capal esmaon mehods s moe sensve o mspcng han he ohe. The naual way o es hs would be o egess boh ealzed euns and esmaes on he mspcng poxy and compae he coeffcens. In boh cases we would expec a negave coeffcen. The moe nvesos oveesmae fuue eanngs he hghe he cuen pces and he lowe he and fuue euns. Snce I am neesed n he elave effecs I can whou loss of genealy use he acual esmaon eo (ε as he mspcng poxy. To make sue he coeffcen s no affeced by he scale of he fm I sandadze he mspcng by he expeced eanngs level:. In ha case he pobably lm of he coeffcen n a egesson of he esmae on he mspcng poxy can be expessed as follows: cov( u Mspcng va( ( If he wo eo ems ae uncoelaed hen he coeffcen wll be equal o mnus one mes he aveage dscoun ae. If he eseache s eanngs esmae suffes fom some of he same poblems as he nvesos eanngs esmae hen he covaance em wll be posve and he coeffcen wll be smalle bu weakly negave. s befoe f he eseache s eanngs esmae pefecly maches he nvesos eanngs esmae hen he s unaffeced by mspcng and he coeffcen wll be zeo. Smlaly we can egess he ealzed euns on he mspcng poxy. In ha case he coeffcen can be expessed as follows:

13 R Mspcng ( (3 Fom hs s clea ha he coeffcen s negave and lage han he coeffcen n he egesson usng he as he dependen vaable. In pacula he gap beween he wo coeffcens s lage f he poon of he mspcng ha eveses whn a yea s lage (meanng he mspcng pessence s smalle. Fo nemedae values of he coeffcen n he ealzed euns egesson wll be seveal mes lage han he coeffcen n he egesson..4 Implcaons fo he elaon beween and fuue euns common mehod of evaluang he level of nose n mpled cos of capal esmaes s by nvesgang he pedcve ably wh espec o fuue sock euns (e.g. Guay Koha and Shu 005; and ason and Monahan 005. The sandad egesson nvolves egessng fuue euns on he esmae. In ha case he pobably lm of he egesson coeffcen can be expessed as follows: cov( R / va( (4 In he full model hs expesson s a funcon of fou andom vaables (ε u and n and once he model s esmaed n a coss-secon he expeced eun ( s a andom vaable as well. Two vaables he news vaable (n and he fuue nnovaon n mspcng ( play no ole n he pobably lm of he coeffcen esmae snce hey ae uncoelaed wh he ohe vaables and ene lnealy n he euns model (hey do howeve affec he vaance of he esmao. Howeve he ohe vaables ae ehe coelaed o ene n a mulplcave manne. s a consequence he esulng equaon s had o nepe. I s heefoe moe nsucve o consde a few specal cases:

14 Random vaables Pobably lm of he egesson coeffcen on he esmae n n ( / u n 0 va( u u n va( / va( va( The fs esul s he deal case he measues ue expeced euns whou eo and he make s effcen hence we ge a coeffcen of one. The second case s he case wh make neffcency bu pefec eseache foecass. The nuon s ha f he mspcng fully eveses one peod lae bu he speads he mspcng effec ove an nfne hozon hen he coeffcen s he capalzaon faco. If he mspcng paally pesss hen he coeffcen wll be smalle bu eman geae han (fo a devaon see he ppendx. In he hd case he only andom componen n he s he eseache nduced nose; hence he coelaon wh ealzed euns s zeo. The coeffcen n he geneal model wll be some weghed aveage of hese hee cases. The fouh case shows how ha ade-off opeaes when he make s effcen bu he eseache s eanngs esmaes have eo and he dscoun ae vaes coss-seconally. The esulng equaon s he mulplcave veson of he sandad aenuaon bas caused by measuemen eo. s he vaance of he measuemen eo becomes lage (small elave o he coss-seconal vaance of he dscoun ae he coeffcen moves o zeo (one. Combnng hese fndngs suggess he followng. Fs snce news s uncoelaed wh he ohe paamees does no bas he coeffcens. Howeve does noduce nose no he egessons. Thus ex pos he ealzaon of news may affec he elaon beween he esmaes and fuue euns. Second mspcng esuls n a hghe coeffcen n a 3

15 4 egesson of fuue euns on esmaes. Thd n conas measuemen eo nduced by he eseache s eanngs esmaes dves down he coeffcen. Fouh boh hese effecs ae mgaed when he measuemen eo n he nvesos and eseache s eanngs esmaes s coelaed..5 Implcaons fo he elaon beween and fuue euns when conollng fo news Tess of he qualy of he mpled cos of capal esmaes usng fuue euns suffe fom a lack of powe. Mos of he coss seconal vaaon n fuue euns comes fom news abou he fms cash flows and changes n he sk ahe han fom vaaon n expeced euns. To conol fo ha he po leaue ncludes poxes fo he cash flow and dscoun ae news n he egesson (e.g. ason and Monahan 005. Whn he conex of he model descbed above he naual way o consuc a poxy fo eanngs news s o ake he dffeence beween he acual eanngs and he eseache s eanngs esmaes (scaled by pce: u n P ansup (5 Recall ha he and he fuue euns can be expessed as follows: n P P P R u P ( ( If he make s effcen (=0 hen he expeced value of he fuue euns wll equal he dscoun ae. Howeve whle n ha case fuue euns povde an unbased esmae of he expeced euns he esmae s vey nosy. If one could conol fo all he news (n hen he nose could be elmnaed. In pacce one needs o esmae he news whch noduces measuemen eo. s can be seen fom he eanngs supse vaable (ansup he

16 measuemen eo n he eanngs news poxy s he same as he measuemen eo n he eseache s eanngs foecas (u and heefoe he and he eanngs supse vaable wll be negavely coelaed. Gven he posve elaon beween eanngs supse and fuue euns hs mples ha he coeffcen on he vaable wll be based upwads afe ncluson of he eanngs supse vaable. In he exeme case n whch he expeced eun s a consan he coeffcen on he wll mo he coeffcen on he eanngs supse vaable n effec pugng he measuemen eo fom he eanngs supse vaable. I can be shown ha n ha case: ansup (6 Ths despe he fac ha unde hese assumpons he s pue nose and he ue elaon beween and fuue euns equals o zeo. Whle admedly hs s an exeme case ha s unlkely o be descpve he geneal pon s ha conollng fo eanngs news nduces an upwad bas n he coeffcen. 6 In pacce when he dscoun ae vaes coss-seconally he magnude of hs bas wll depend on he vaances of he eseache s measuemen eo elave o he vaances of he ue eanngs news and he dscoun aes. In he case of make neffcency he use of news poxes may be moe pomsng. In ha case usng fuue euns as a poxy fo expeced euns yelds boh based and nosy esmaes. Fo he eanngs supse poxy o be effecve n emedyng he make neffcency needs o be eflecve of he nvesos foecas eos. s can been seen fom he eanngs supse poxy equaon above he nvesos foecas eos poenally ene n wo way. Decly because he 6 Noe ha he oppose holds fo poxes fo changes n he dscoun ae f hose poxes ae also based on he same eseache eanngs esmaes. Fo example hs can be accomplshed by usng he change n he as a poxy fo he change n he dscoun ae as n ason and Monahan (005. Ths suggess ha ncludng boh news poxes may mgae any bas on he coeffcen. Snce he model s based on a consan dscoun ae I canno quanfy hs effec. 5

17 nvesos foecas eos affec he sock pce whch s efleced n he denomnao and ndecly f he eseache s foecas eos ae posvely coelaed wh he nvesos foecas eos whch seems plausble. The fs effec by self does no affec he coelaon beween he eanngs supse esmae and he esmae. Theefoe n he case ha he eseache s eanngs esmaes ae whou eo o f he eo s uncoelaed wh eo n he nveso s esmaes conollng fo news has no effec on he bas nduced by mspcng bu may educe he nose n he egesson. In he lkely case ha boh he eseache s and he nvesos eanngs esmaes conan measuemen eo he queson s whehe he ncluson of eanngs news poxes s benefcal. The answe o hs depends on he elave magnude of he effec wo eos. smple es of whehe he effec of he eseache s o he nvesos measuemen eo domnaes s o examne he coelaon beween he and he eanngs supse measue. If he coelaon s negave he eseache s measuemen eo domnaes and he coeffcen on wll be based upwads afe ncluson of he eanngs supse vaable n he egesson..6. The effec of make neffcency on models of measuemen eo vaances The model so fa focuses on he effec of make neffcency on egessons of ealzed euns on he mpled cos of capal poxes. Because he poblems wh ealzed euns he leaue has aemped o decly model he sucue of he measuemen eo n he poxes. The mos developed model s found n ason and Monahan (005. Usng he appoach n Vuoleenaho (00 hey decompose ealzed euns n expeced euns cash flow news and expeced eun news. They hen consde he case n whch he empcal poxy fo each of hese consucs consss of he ue consuc plus measuemen eo. To denfy he measuemen eo n he expeced eun poxy hey assume ha he measuemen eo n a pacula 6

18 poxy s uncoelaed wh he ue undelyng consuc bu may be coelaed wh he ue value of he ohe consucs and he measuemen eos n he emanng poxes (p.534. By allowng he measuemen eo n he poxy o be coelaed wh he measuemen eo n he news poxes hey can avod some of he poblems dscussed n secon.5 asng fom decly lookng a he coeffcens n he egesson. The queson s how hese assumpons compae o he sucue of model developed n hs pape n pacula whehe hese assumpons can accommodae make neffcency. Wh espec o he measuemen eo n he esmaes due o he eseache s eanngs esmaes he assumpon seems o ack closely. s can be seen fom secon. unde make effcency he measuemen eo n s uncoelaed wh (bu no ndependen of he ue dscoun ae. s dscussed n foonoe 3 whle hs esul does no geneally hold o he exen my model s a easonable appoxmaon hs assumpon seems easonable. 7 Howeve as can be seen fom secons. and.3 n case of make neffcency he measuemen eo n he poxy s coelaed wh he ue dscoun ae. Moeove he decomposon does no nclude a specfc em fo he (evesal of he mspcng. One can change he nepeaon of he news vaables o measue news fom he nvesos pespecve ahe han based on objecve expecaons howeve n ha case he nose n he news vaables wll also be coelaed wh he undelyng ue value of he news. In addon s no clea ha one would wan o ea he wo souces of measuemen eo n he esmaes he same. I seems heefoe useful o complemen hese ypes of analyses wh an explc nvesgaon of he mpac of make neffcency on he esmaes as s done n hs pape. 7 Noe howeve ha unde he assumpon ha he s equal o he ue dscoun ae and uncoelaed nose an ease way o evaluae he esmaes s avalable. In ha case he vaance of he esmae s smply he sum of he vaance of he ue dscoun ae and he vaance of he nose. Thus whn sample he esmaes can smply be anked by he elave vaances snce he vaance of he ue dscoun ae wll be he same acoss dffeen poxes. 7

19 3. Daa and measuemen The sample consss of fms lsed on he NYS mex and Nasdaq wh shaecodes 0 o fo he peod fom 97 o 007 wh suffcen daa on CRSP and Compusa o calculae he mpled cos of capal esmaes. In calculang he measues I follow he appoach n Hou Van Djk and Zhang (00 and Lee So and Wang (00. Rahe han usng analyss foecass of eanngs hs appoach s based on a pooled coss-seconal eanngs foecasng model fo yeas + hough +5. The followng model s esmaed each yea usng he pas 0 yeas of daa (mnmum of 6 yeas: j V 0 j T j DIV 3 j DD 4 j 5 j NG 6 j CCT 7 j j whee j+τ (τ = 3 4 o 5 denoes he eanngs befoe exaodnay ems (Compusa em IB of fm j n yea + τ and all explanaoy vaables ae measued a he end of yea : V j s he enepse value of he fm (defned as oal asses (Compusa em T plus he make value of common equy (Compusa em PRCC_F mes Compusa em CSHO mnus he book value of common equy (Compusa em CQ T j s he oal asses (Compusa em T DIV j s he dvdend o common shaeholdes (Compusa em DVC DD j s a dummy vaable ha equals 0 fo f DIV j s posve and ohewse NG j s a dummy vaable ha equals fo fms wh negave eanngs befoe exaodnay ems (Compusa em IB and 0 ohewse and CC j s oal accuals. Toal accuals ae calculaed as he change n cuen asses (Compusa em CT plus he change n deb n cuen lables (Compusa em DLC mnus he change n cash and sho em nvesmens (Compusa em CH and mnus he change n cuen lables (Compusa em LCT. ach vaable n he egesson s wnsozed a he 0.5 and 99.5 pecenles of ha yea o mgae he effec of exeme obsevaons. 8

20 The aveage annual coeffcens and Fama-Macbeh -sascs 8 fom hese egessons ae dsplayed n Table. Oveall he coeffcen esmaes ae elavely smla o Hou Van Djk and Zhang (00 and Lee So and Wang (00. On June 30 h of each yea each fm s foecased eanngs ae calculaed usng he mos ecen hsocal coeffcen esmaes appled o he mos ecen epoed eanngs and ohe explanaoy vaables. These ae hen used o pedc book values usng he begnnng book values and he clean suplus assumpon. The eanngs and book values ogehe wh he make value of he equy (also measued on June 30 h ae hen used o geneae each of he esmaes. I exclude he Fama-Fench (997 bankng ndusy due o a lack of avalable daa fo he accual measues. Lee So and Wang (00 evaluae seven models of mpled cos of capal fou of whch elably pedc fuue sock euns n he yea followng he pofolo fomaon. In he cuen veson of he pape I focus only on hese fou esmaes snce he pupose of my analyss s o quanfy he elave mpoance of make neffcency and expeced euns n he elaon beween and fuue euns. The fou models ae labeled GLS PR GGM and GR. I dscuss hese models n moe deal below. The fs model (GLS s based on Gebhad Lee and Swamnahan (00. Ths model s based on he esdual ncome famewok and uses explc foecass of eanngs fo he fs hee yeas followed by a nne yea peod n whch he eun on equy (RO lnealy eves o he ndusy medan RO (based on he 49 Fama-Fench (997 nduses. The ndusy medan RO s calculaed usng he pas en yeas of daa (mnmum of fve yeas. The emnal value s compued as he pesen value of he capalzed peod esdual ncome. 8 Noe ha hese -sascs ae lkely ovesaed due o he use of ovelappng wndows and a seally coelaed dependen vaable. Ths does no pose any poblems snce only he coeffcens ae used n compung he esmaes. 9

21 0 ( ( ( B RO B RO B MV whee MV s he make value of equy of fm a me B s he book value of equy RO s he eun on equy and s he nenal ae of eun ha solves he equaon. The nex wo models (PR and GGM ae based on he Godon Gowh Model. The models ae based on he dvdend dscoun models wh explc dvdend foecass fo he fs few yeas followed by dscouned eanngs n pepeuy heeafe (mplcly assumng a 00% pay-ou ao n hose lae yeas. Gowh n eanngs and dvdends s only assumed n he explc foecasng peod. ( ( T T T D MV Smla o Lee So and Wang (00 I consde wo dffeen foecas hozons T= and T=5. The fs smplfes o he eanngs o pce ao usng foecased nex peod s eanngs (labeled PR. The second model based on hs uses he explc eanngs foecas fo peod 5 fo he emnal value and use he foecased eanngs mes he hsocal dvdend pay-ou ao o ge he dvdend foecass (labeled GGM. The fnal model (labeled GR s based on an abnomal eanngs capalzaon model poposed by ason (004. The specfc veson consdeed hee s he case wh explc foecass of eanngs fo he fs wo yeas and a pepeual gowh ae n abnomal eanngs heeafe deved fom he foecased mplc gowh ae n yea 3. The exac fomula s as follows (expessed n pe shae amouns: ( ( ( 3 PS DPS PS PS DPS PS PS DPS PS PS P

22 s can be seen fom hs he GR model s essenally he PR model plus a em coecng fo gowh n abnomal eanngs. Conssen wh Lee So and Wang (00 I uncae each esmae a 0% and 00% o mgae he effec of exeme obsevaons. The descpve sascs fo he fou measues and he one-yea-ahead ealzed sock euns ae dsplayed n Table II panel. The ealzed euns ae he compounded monhly aw sock euns n he monhs followng he pofolo fomaon dae (ncludng delsng euns followng he appoach n Beave McNchols and Pce 007. Compang he esmaes o he ealzed euns s clea ha whle he mean esmaes ae easonably smla he vaance of ealzed euns s much hghe. mongs he esmaes PR s has he lowes aveage whch s o be expeced snce hs mehod gnoes any gowh n eanngs afe he fs yea. The coelaon able n panel B shows ha all fou esmaes ae posvely coelaed wh fuue euns and songly posvely coelaed wh each ohe. The hgh sandad devaon of ealzed euns suggess ha ndvdual fms sock euns ae mosly dven by news and hus a vey nosy poxy of expeced euns. s can be seen fom Panel whle he aveage ndvdual fm eun s abou 3.6% he euns ae ghskewed wh he medan eun (3.7% less han he aveage sk fee ae fo he peod (6.6% and a sandad devaon of abou 75%. Snce ealzed euns ae he dependen vaable n he egesson hs news should aveage ou. Howeve gven ha euns ae coelaed n he cosssecon due o common economc shocks and ha he me-sees of daa s elave lmed s an empcal queson as o whehe hee s suffcen daa o acheve hs. To povde nal evdence on hs I examne he effec of aveagng acoss fms and me on he dsbuon of euns. To povde a benchmak I consde he dsbuon of he make sk pemum ahe

23 han he make eun. mnmum es of he effcacy of aveagng should be ha he make sk pemum s elably posve. The effec of coss-seconal aveagng can be seen fom he fs ow n Panel C whch conans he ealzed sk pemum fo he equal-weghed make pofolo. Ths s calculaed as he dffeence beween he ealzed eun on he make (CRSP WRTD and he one-yea easuy ae ove he same 37 annual euns peods sang fom July 97 o June as he man sample. Whle coss-seconal aveagng educes he sandad devaon by abou wo-hds (fom a lle ove 75% o a lle unde 5% sll a sgnfcan facon of yeas expeences a negave ealzed sk pemum. Thus even hough CRSP coves seveal housand fms pe yea he coelaon among he euns s such ha hee s sll sgnfcan vaaon lef. Nex I consde he effec of aveagng ove consecuve 5 yea peods whn my sample peod hee ae 33 ovelappng 5 yea peods. Ths esuls n an addonal dop n he sandad devaon of euns alhough sll moe han 5% of he of he 5-yea peods expeence a negave ealzed sk pemum. xendng he aveagng peod o 0 o 0 yeas fuhe educes he sandad devaon and esuls n a less han 5% chance of expeencng a negave ealzed sk pemum. To ge a sense of he sably of he esmaes n hs pape whch ae based on a 37-yea peod I nex consde non-consecuve 36-yea peods doppng one yea a a me. Ths shows how sensve he esuls ae o he excluson of ndvdual yeas. Unsupsngly hs pocedue esuls n he lowes sandad devaon. In pacula he dffeence beween he 5 h and he 95 h pecenle s less han %. Panel D shows he same analyss wh usng he value weghed make eun. Value weghed euns ae less vaable n geneal bu ohewse he nfeences

24 ae smla. Thus whle even wh housands of fms and 37 yeas he aveagng s sll no pefec s does seem o be easonably effecve. 4. Reseach desgn and esuls The model n secon suggess ha mspcng wll lead o a posve coelaon beween esmaes and fuue sock euns. Ths s also he expeced elaon n he absence of mspcng when he esmaes coecly pedc he expeced eun componen of fuue sock euns. Theefoe a egesson of fuue euns on he esmaes does no povde a clea sepaaon beween hese wo hypoheses. In he nex secon I dscuss he analyss yng o quanfy he elave mpoance of hese wo hypoheses. Then n secon 4. I wll dscuss he effecveness of conollng fo news n emedyng he effecs of mspcng. 4. smang he elave mpoance of expeced euns and mspcng To help quanfy he elave mpoance of mspcng and expeced euns n explanng he elaon beween esmaes and fuue sock euns I use wo mehods. Fs o ge a lowe bound on he effec of mspcng I examne he elaon beween esmaes and he euns aound eanngs announcemens. Ths s a commonly used appoach o sepaae sk and mspcng explanaons fo seemngly anomalous sock euns (e.g. Benad and Thomas (990 Benad Thomas and Wahlen (997. If he mspcng s elaed o nvesos msesmang eanngs as s n he model n secon hen one would expec pa of hs mspcng o be coeced once he eanngs ae eleased. s a esul he euns on he hedge pofolo should be concenaed aound he eanngs announcemen. The second appoach es o esablsh an uppe bound fo effec of mspcng by usng he Fama-Fench hee faco model (Fama and Fench 993. Unde hs appoach euns ha 3

25 ae no explaned by he hee facos ae assumed o be he esul of mspcng. Ths povdes an uppe bound o he magnude of he mspcng because unmodeled sk facos could also povde an explanaon. In fac he seach fo such new sk facos s one of he movaons fo he developmen of mpled cos of capal models (e.g. Boosan 997. Combnng hese wo appoaches allows fo an assessmen fo he magnude of he mspcng effec. Befoe yng o assess he magnude of he poenal mspcng I fs examne he oal explanaoy powe of he esmaes fo fuue euns. On June 30 h of each yea fms ae soed no decles based on he magnude of he esmaes wh Decle conanng he fms wh he lowes. Then he euns fo each fm ae compounded fom July s ll June 30 h of he nex yea. In case he fm delss dung he yea he euns nclude delsng euns followng he pocedue n Beave McNchols and Pce (007. ny delsng poceeds ae hen nvesed n he emanng fms of he especve decle. Table III epos he aveage annual decle euns and hedge pofolo euns fo each of he fou esmaes. Panel dsplays he equal weghed euns (mnus he equal weghed make euns fo each decle and he euns of a hedge pofolo ha s long n decle 0 and sho n decle. The esuls confm fndngs n Lee So and Wang (00 ha each of hese fou esmaes pedc fuue sock euns. Panel B dsplays he value weghed euns (mnus he value weghed make eun. ll fou esmaes connue o have posve hedge pofolo euns whch wh he excepon of GR ae also sascally sgnfcan. To deemne he mpac of mspcng on he euns n Table III I nex examne he euns aound he eanngs announcemen n he yea followng he pofolo fomaon. nnual eanngs announcemen euns ae ceaed by compoundng he euns fo he welve days aound eanngs announcemen (hee day wndows aound each of he fou quaely eanngs 4

26 announcemens. ach yea hese eanngs announcemen euns (mnus he make eun ove he coespondng days ae aveaged by decle. Table IV epos he aveage annual eanngs announcemen euns by decle. The hedge pofolo esuls ndcae sgnfcan dffeences beween decle and decle 0 suggesng ha mspcng explans pa of he elaon beween esmaes and fuue sock euns. The hedge pofolo euns ae posve and sascally sgnfcan fo all fou esmaes. The eanngs announcemen euns explan beween 6% (PR and 5% (GGM of he abnomal buy and hold euns fom Table III (medan 46%. Ths suggess ha mspcng has a lage mpac on he oveall elaon beween esmaes and fuue sock euns. These fndng ae also conssen wh po leaue ha has found ha vaous fundamenals-o-pce adng saeges whch ae elaed o adng saeges yeld a dspopoonae shae of he euns aound eanngs announcemens (e.g. La Poa Lakonshok Shlefe and Vshny 997; l Hwang and Tombley 003. Thee a wo poenal concens wh hs es. Fs gven ha hee ae abnomal euns houghou he yea we would expec o see some abnomal euns aound he eanngs announcemen as well. To coec fo hs I subsac he followng adjusmen faco fom he abnomal euns a he eanngs announcemens: djusmen 5 BHe e The esuls of hs adjusmen ae vually unchanged fom he analyss above he facon of coeced eanngs announcemen euns o he full yea buy and hold euns s now and 0.44 fo GLS PR GGM and GR especvely. second and elaed concen s ha one mgh expec o see hghe han aveage sk pemum on eanngs announcemen days gven he geae nfomaon flows and sk on hose 5

27 days. One ndcaon fo hs s ha he eanngs announcemen euns ae posve on aveage even hough hey have been make adjused. These posve abnomal euns ae conssen wh he po leaue ha documens posve abnomal euns aound eanngs announcemens (e.g. Ball and Koha (99 Chambes Jennngs and Thompson (004 Cohen Dey Lys and Sunde (007. Ths po leaue agues ha posve euns occu because of nondvesfable sk assocaed wh eanngs announcemens fo whch nvesos eque a pemum. Cohen e al. (007 fnd a hee-day aveage excess eun of 0.5% fo a lage sample of eanngs announcemens fom 978 o 00. Whle a po s no clea ha he sk noduced by eanngs announcemens s nondvesfable I y o ule hs ou as an alenave explanaon o he esuls. To addess hs concen I use he followng appoach. I assume ha he popoon of expeced euns n he eanngs announcemen day peod s popoonal o he facon of he oal eun news occung n he eanngs announcemen day peod. Po eseach fnds ha abou % of he annual volaly occus n he day wndow aound he eanngs announcemen oughly double he facon of days ha fall n ha wndow (Basu Duong Makov Tan 00. I confm hs fo my sample and he exeme decles. When usng hs o compue he adjusmen faco he calculaon s as follows: djusmen BHe e Usng he coecon faco he facon of coeced eanngs announcemen euns o he full yea buy and hold euns s now and 0.40 fo GLS PR GGM and GR especvely. 6

28 Panel B of Table IV documens he decle euns when he euns ae value weghed. In geneal he hedge pofolo euns ae lowe han n Panel and only sascally sgnfcan fo one of he fou esmaes (GLS. Compang he value weghed eanngs announcemen euns o he value weghed buy and hold euns of Table III shows ha he eanngs announcemen euns explan beween 9% (GR and 6% (PR of he abnomal buy and hold euns fom Table III (medan 5%. These esuls sugges usng value weghed analyses can help mgae he effecs of mspcng a leas fo he se of esmaes examned hee. The second analyss nvolves an examnaon of he effec of he Fama Fench sk facos on he euns o he hedge pofolo. On June 30 h of each yea fms ae soed no decles based on he magnude of he esmaes. Fo he nex welve monhs he fm emans n he same decle. Fo each monh he decle eun s calculae as he aveage eun of all fms n ha decle fo ha monh. Ths geneaes a mesees of 444 monhly euns fo each decle. I hen subac he sk fee ae and egess he dffeence on he make sk pemum (RMRF he small fm pemum (SMB and he value pemum (HML. Table V epos he coeffcens fom a mesees egesson of he monhly hedge pofolo euns on he hee Fama-Fench facos. Panel dsplays he case whee ndvdual sock euns ae equal-weghed n ceang he decle and hedge pofolo euns. The esuls ndcae ha he hedge pofolo euns fo all fou esmaes load songly on he HML faco pehaps no supsng gven ha esmaes have a smla fundamenals o pce flavo. They also exhb a modeae o song loadng on he SMB faco. Howeve he loadngs on he make faco ae conssenly negave. s a esul whle he hee faco model s easonably successful n explan he mesees vaaon n he hedge pofolo euns does a elavely poo job n explanng he aveage hedge pofolo eun. 7

29 To assess he usefulness of he hee facos n explanng he aveage hedge pofolo eun I compue he ao of he monhly abnomal euns (he necep o he oal monhly expeced eun. The lae s calculaed as he necep plus he faco loadng mes he aveage faco pemum. Ove hs me peod he aveage faco pemums wee 0.46% pe monh fo he make pemum (RMRF 0.6% pe monh fo he small fm pemum (SMB and 0.45% pe monh fo he value pemum (HML. The facon of he expeced monhly eun unexplaned by he hee facos my esmae of he uppe bound on he mspcng mpac anges fom 59% (GLS o 83% (GGM wh a medan of 69%. These esuls ae conssen wh he equal weghed eanngs announcemen euns and sugges ha mspcng has a lage effec on he elaon beween esmaes and fuue euns. s wh he ohe ess I epea he analyss usng value weghed euns nsead of equal weghed euns. The esuls ae dsplayed n Panel B. Wh he excepon of GLS he abnomal euns ae much lowe han n he equal weghed case and no sascally sgnfcanly dffeen fom zeo. Usng he same mehod as above he facon of he expeced monhly eun unexplaned by he hee facos anges fom -34% (GR o 5% (GLS wh a medan of 0%. Ths suggess ha use a value weghed analyss can effecvely mgae he effecs of mspcng agan wh he excepon of he GLS measue. Howeve hs s a b of a doubleedged swod. If he Fama-Fench hee facos effecvely explan he mean euns on he hedge pofolo hen hee s lle oom fo ohe pced sk facos unless hese new facos dsplace he exsng hee facos. 4. Conollng fo news n egesson of fuue euns on esmaes s dscussed n secon.5 he heoecal case fo conollng fo news depends on he mpoance of measuemen eo n he eseache esmaes of eanngs. In lne wh he model 8

30 developed hee I calculae he eanngs supse (S as he ealzed one-yea-ahead eanngs mnus he foecased eanngs scaled by he make value a he pofolo fomaon dae. In he egesson hs s expeced o have a posve elaon wh fuue euns. Whle he model does no speak o changes n he dscoun ae based on po eseach I also nclude a measue fo ha. Followng he po leaue he poxy fo changes n he dscoun ae s he dffeence beween he one-yea-ahead esmae and he cuen esmae (DRS. In he egesson hs s expeced o have a negave elaon wh fuue euns. Table VI epos he aveage coeffcens of annual coss-seconal egesson of fuue euns on he esmaes and poxes fo eanngs supses and changes n dscoun aes (neceps ae ncluded bu no epoed o conseve space. The ealzed euns ae he compounded monhly aw sock euns n he monhs followng he pofolo fomaon dae (ncludng delsng euns followng he appoach n Beave McNchols and Pce 007. Thee ae 8 ses of egessons one se of equal weghed egessons fo each of he fou esmaes and one se of value-weghed egessons fo each of he fou esmaes. Whn each se of egessons he sample s kep he same o enhance compaably. I wll nex dscuss he esuls of he uppe lef se of egessons he equal weghed egessons fo he GLS esmae. The fs egesson shows he smple egesson of one-yea-ahead sock euns on he GLS esmae of mpled cos of capal. The coeffcen s posve and sgnfcan confmng he esuls of he pofolo based appoach n Table III. Noe howeve ha he coeffcen s less han one he pedcon fom he model n he case whou measuemen eo n boh he eseache s and he nvesos eanngs esmaes. lso he fac ha he coeffcen s less han one suggess ha he effec of he eseache s measuemen eos domnaes he effec of he 9

31 nvesos eos 9. The second egesson shows a song elaon beween eanngs news and fuue euns. Howeve hs coeffcen (he RC s much less han he heoecal coeffcen whch s he eanngs capalzaon faco agan suggesng a fa amoun of measuemen eo n he eseache s eanngs esmaes. Conssen wh he pedcons n secon.5 ncludng boh he esmae and he eanngs supse poxy (changes n dscoun ae esuls n a sgnfcanly lage (smalle coeffcen on he esmae. Fnally pung all hee vaables n he egesson esuls n an ncease of he coeffcen elave o he smple egesson and boh he eanngs supse and he change n dscoun ae poxy have he pedced sgn. The esuls fo he ohe seven ses of egessons ae geneally conssen wh he esuls dscussed above. Includng he eanngs supse poxy esuls n an ncease n he coeffcen on he esmae whle ncludng he change n dscoun ae poxy esuls n a decease n he coeffcen on he esmae. Includng boh supse poxes leads o moe ambguous esuls somemes esulng n an ncease n he coeffcen on he esmae and somemes a decease. The queson s wha o conclude fom hese esuls abou he usefulness of conollng fo news. The fac ha he elaons beween he hee vaables can be explaned by measuemen eo n he eseache s esmaes suggess ha ncludng he supse poxes may do moe ham han good. Ceanly ncludng only one of he wo poxes s hamful n undesandng he qualy of he esmaes. The model developed n secon s no ch enough o esablsh whehe ncludng boh news poxes helps neualze o meely mgae he bas nduced by he measuemen eo. Howeve model does sugges some handle on such assessmen. Snce he mspcng should esul n an upwad bas of he coeffcens possble o see whehe he esmaes wh 9 Recall fom secon ha measuemen eo n he eseache s eanngs managemen leads o a downwad bas n he coeffcen whle measuemen eo n he nvesos eanngs esmaes leads o an upwads bas n he coeffcens. 30

32 he mos mspcng (accodng o he eanngs announcemen ess have a moe negave change n he coeffcen afe ncluson of he news poxes. Based on Tables III and IV he GLS GGM and GR esmaes have he hghes facon of euns due o mspcng (45% 5% and 46% esp.. Of hese GLS expeences a lage ncease n he coeffcen GGM a lage decease and GR no much change followng ncluson of he news poxes. The PR esmae has elavely low mspcng (6% bu expeences a lage ncease he coeffcen. Oveall hese esuls do no sugges ha he ncluson of he news poxes s vey effecve n educng he bas nduced by make neffcency. lso n hs seng he ncemenal R-squaed of he news poxes s elavely low suggesng ha he ohe benef of ncludng hem educng nose n euns s no ha mpoan hee. One mgh wonde whehe he fac ha he measuemen eo n he news poxes and he measuemen eo n he esmaes ae coelaed s a good hng ahe han a poblem as dscussed above. fe all eanngs news poxy mgh clean up he measuemen eo n he esmae heeby yeldng a bee coeffcen. Fo example n he case of he equal weghed GLS egessons dscussed above ncludng jus he eanngs news poxy esuls n a jump of he coeffcen on he esmae fom 0.39 o.0 vey nea he heoecal coeffcen of. The counepa of hs appoach n he eanngs-esponse-coeffcen leaue would be Collns Koha Shanken and Sloan (994. Thee ae wo ssues wh hs. The fs ssue concens he eseach objecve. If he eseach objecve s o examne he effec of he undelyng consuc n hs case expeced euns hen havng a conol vaable ha cleans up he nose n he poxy n hs he esmae s a good hng. Howeve f he objecve s o examne he effec of he poxy self hen cleanng ou he measuemen eo hough a conol vaable s no desable. fe all we ae no neesed n whehe expeced 3

33 euns ae elaed o fuue euns bu whehe ou pacula poxy he ndvdual esmae s a elable esmae of hs. Then ncludng poxes fo he nose n hs esmae he effecveness of whch may vay acoss esmaes wll obscue he ue elave ankng of he esmaes. The second ssue s ha as dscussed n secon.5. ncludng he eanngs news poxy wll lead o an ncease n he coeffcen on he esmae even n he case n whch expeced euns do no vay and he esmae s pue nose. Oveall hese consdeaons sugges ha he poenal benefs of ncluson of he news poxes do no ouwegh he sks. 5. Concluson The leaue has long ecognzed ha ealzed euns offe a vey nosy poxy of expeced euns (e.g. lon 999. Impled cos of capal ( models offe a pomsng alenave mehod fo esmang cos of capal even f he esmaes fom hese models conan some nose as well. Many dffeen models have been developed and one appoach o evaluae he level of nose n hese models by nvesgang he pedcve ably wh espec o fuue sock euns (e.g. Guay Koha and Shu 005; and ason and Monahan 005. One concen wh hese ess s ha hese euns mgh be affeced by make neffcency n addon o expeced euns. In hs pape I develop a model sang fom he undelyng pmves nvesos and eseache s eanngs foecass and show ha unde easonable assumpons make neffcency wll esul n a posve elaon beween esmaes and fuue euns. In he empcal pa of he pape I y o quanfy he elave mpoance of expeced euns and mspcng. I use he appoach n Hou Van Djk and Zhang (00 as exended by Lee So and Wang (00 n foecasng eanngs and calculang esmaes. Conssen wh hese papes I fnd ha esmaes pedc fuue sock euns. I use wo appoaches o 3