The Relative Infonnativeiiess of and Earnings Forecast Revisioiis
Transcription
The Relative Infonnativeiiess of and Earnings Forecast Revisioiis
journa- of -Vccuiitirsg Researt VoL 35 No. 2 Atitiimf!. :9y7 Printed In ;',-^V/i. The Relative Infonnativeiiess of and Earnings Forecast Revisioiis JENNIFER FRANCIS* AND LEONARD SOFFERf /. Introduction In this paper we examine the a.ssociation between security returns and two attributes of sell-side analyst reports, stock recomtnendations (new and. reiterated) and earnings forecast revisions: other itiformation in analyst reports is usually presented to support these two assessments of ex.pected future firm performance, \^Tiile prior research examines sectiritv price reactions to either earnings forecast revisions o? stock recomtnendations (or revisions therein), we provide evidence on how investors respond to each of these signals conciitional on the other. We view stock recommendations as expressions of analysts' beliefs about share valties relative to their market prices. These beliefs incorporate earnings forecasts, which may independently provide information a!)otu share values. Our tests attempt to distniguish the view that these *lJn;versity of Chicago; tNorthwestern University, lids re.search was supported by the janies S. Kemper FoundaticiB Factilty Research Fund, by the h;stittite of Professiotial J\ccotintmg. (iradaate School 'Of BiLsiriess, l''niver.sity oi (ihicag<:>. anci bv the .Accotititing Research Center. J. L. Kellogg (iradaate .School of Management, Northwestern University, We appreciate (he con)ment,s and stiggestions of an anonymous reviewer, workshop participants at the thiiversity of Chicago. University of Illinois at (.Chicago. M.l.'l), l.'niversitv of Notre Dame, Ol'n'o State 1,'niversity. Ihiiversitv of Texas, the 1994 A.A.-^ anntiai meeting, the May 1995 bistitutioual Investoi Research Roundtable. and from L. Brown, R. Biishtnan. C. Cofler, R. Dve, R. Freemati. P. Healy., T Lys, D, May, R, Mendeohail. S, Na'&ar, P, O'Brien, D, Phiihriek, .S, StickeS, C. Stinson, B. rruemati, D Vickrev, L. Miicetit. R. 'Willis, and R, Young. We especially thank F. Gigler and L. Maiiies for their inptit. FuiaBy. we th,ank S. Lakh.a for hi.s research a.ssissance. •93 Copyright v^:. liistitme of Proies.sional .^cctninnng, i997 194 JOURNAL OF ACCOUNTINC, RESEARCH, AU'i'UMN 1997 signals convey distinct information from the view that one signal subsumes the other. On the one hand, we expect recommendations to be informative even in the presence of earnuigs forecast revisions since the latter are but one input to the analyst's valuation model. On the other hand, because analysts report discrete ratlier than continuous assessments of security misprieing,* and because we believe the degree of mispricing is important to investors, we expect investors to tuse information about the inputs to the analyst's valuation model (such as earnings forecasts) to help uncover the unreported continuous signal. Thus, we expect that earnings forecasts are informative even in the presence of stock recommendations. We also predict that investors' reactions to earnings forecast revisions depend on the contemporaneously reported stoc:k recommendations. This conjecture is related to Hirst, Kooisce, and Simko's [1995] laboratory test of whether subjects seek out other information in an analyst's report when the recommendation disconfirms their prior beliefs. They argue that because investors expect analysts to issue favorable recommendations, subjects are more likely to search for other information in analysts' reports when thev observe unfavorable recommendations. In contrast, we predict that investors react more strongly to earnings forecast revisions accompanying favorable (buy) recommendations than to revisions accompanying tmfavorable (sell) recommendations because buys are less informative than sells about the analyst's beliefs about share values. The lower precision of buys relative to sells derives from the observed distribution of stock recommendations, 'vvhich is skewed toward favorable recommendations (e.g.. Beneish [1991] and Schultz [1990]); this skewness is believed to stem from certain features of the analyst's work environment which generally encourage the issuance of favorable information about client firms.^ In the presence of stich incentives, we expect analysts to expend greater care and effort before issuing an unfavorable report, which would suggest that sells contain lower valuation errors than buys. In addition, we show (in Appendix A) that given plausible assumptions about the distribution of analysts' valuations, skewed reporting of recommendations concentrates valuation errors in buy stocks. For a sample of 576 analyst reports ptiblished between January i, 1988 and June 30, 1991, we find that stock recommendations and earnings forecast revisions together explain about 5% of the variation in excess returns c.imitilated over days {-l,+ 'l) relative to the report publication dates. Although infc>rmation is lost when analyst.s report recommendations rather than valuations, the results indicate that recomnieodations ' Tliat is. analysts tvpicailv pro'*'ide buy, bold, or sell recomiriendations rather than direct estimates of mispricing. ^'For example, Francis and Philbrick [1993] describe ati:iiysts' incentives to cultivate management relations., Lii) and McNic'nois [19951 and Dtigar and Nathan [i995] analyze the influence of investment ban'King and titiderwriting relarions, and Hayes [19951 models analysts' incentives to getierate trading cotnmis.sions. IXEORMATIVEXESS OF .ANALYSTS' STOCK RECOMMEND.AI'iON.S 195 are informative. As a group, and after ctjntrolling for earnings forecast revisions, variables capturing the level of and the revision in stock recommendations explain a significant (at the .02 level) portion of the variation in ctimuilative abnormal returns. Further tests indicate that this inforiiiativeness derives from revisions (not levels! in recommendations. W'e aiso find that investors attach significantlv fat the ,02 level) larger weights to t'ne earnings forecast revisions in reports containing btiy recomtnendations than they do to revisions in reports contaitiing holds or sells. While this result conflicts with Hirst. Roonce. and 8imko's [1995] experimental findings that subjects' stock perforinance judgments are more affected by other information in the analvst's report when thev observe an ttnfavorable recommendation than when thev observe a favorable recommendation, it is consistent with our prediction that, given the existetice of incentiyes for analysts to issue favorable recomtnendations, inyestors weight otiier information in the analyst's report more heavily when, they observe a btiv than when they observe a hold oi" a sell. Section 2 reviews related research, and section ,^ develops the predictions outlined above. Section 4 describes the data and sample, section 5 reports the empirical work, and section 6 summarizes the restilts. 2. Related Resecirch Our analysis of investors' reactions to analysts" reports is related to four stratids of research. The first includes doctimentations of the association between anah'sts' earnings foreca.st revisions (froti- IBESor Standard and Poor) and cotitempoi'aneotts security price moyernents ie.g.. Givoly and Lakonishok [1979], Brown, Foster, atid Noieen [1985], and Lvs and Sohn [1990]), A separate stream of research investigates market reactions to stock recommendations, including those reported in the Wall Street Jourr,al CitVamrk "Hearci on the Street." (Llovd Davit;.s arid Cranes [1978], Liu. Smith, and Syed [1990], and Beneish [1991]). More recent research examines the market reactions to tlie initial release of a recommendation (Flton. Gruber, and (irossman [1986] and Womack [1994]), These studies generally exclude reiterations and find that the market reacts positively to tipgrades to buy and negatiyely to dowtigrades to sell. As disctissed in section 3, we extend these studies by including reactions to reiterated recommendations and by conditioning on earnings news and on both the level of and the revi.sion m stock recommendations, A third set of studies examines the relation between anah%\sts' earnings forecasts and their stock recomtnendations. Using Canadian data. Bandyopadhyay, Brow-n, and Richardson [1995,1 find that forecasted oneyear-ahead earnings explain about 30% of the variation in forecasted 12-month-ahead stock prices (the explanatory power increases to 60% when the forecast horizon iticreases to 3 - 5 years). While this result suggests that price forecasts and earnings forecasts convey different information, the autliors do not investigate the relative weights investors place 196 JENNIFER FRANCilS ANTi LEONARD .SOFFER on the two signals. We provide evidence on this issue; while Bandyopadhyay. Brown, and Richardson use direct assessnx'nts of share values (in the form of fore(,:asted stock prices;), we analyze the discrete stock recommendations (buy, hok'i, and sell) commonly observed in the United States. In conciirrent work, Lin. [1994] analyzes market reactions to the information, conveyed in analysts' earnings forecasts and their stock recommendations. Our analysis differs from his in that we distinguish between levels and revisions in recotnmendations, and (as discussed below) we examine whether the relative informativeness of earnings forecast revisions differs across recommendations. Finally, Hirst, Roonce, and Simko [1995] tise an experimental approach to examine how subjects interpret one piece of an analyst's report conditional on other information in the report. Based on psychological theories, they predict (and their results confirm) that w'hen a report conve)'s unfavorable information (such as a sel! recommendation), subjects are more likelv to seek out other information in the report because the unfavorable recoinmeiidatiori is contrary to their expectation that analysts will isstie a favorable recommendation. In partictilar, they find that st.ibjects are more likely to consider disclosures of investment banking relationships between the subject company and tiie analyst firm when the report contains a sell recommendation than when it contains a buy recommendation. In contrast, we predict that investors place greater reliance on other information in the analyst's report when tiie report contains a buy recommendation tfian when it contains a sell recommendation. Our reasoning (described more full)' in the next section) is that because analysts' propensities and incentives to issue favorable stock recoinmendations and optitnistic forecasts are well documented (e.g.. Abarbanell [199.1], Dugar and Nathan [199.5], Lin and McNichols [1995]. Francis and Philbrick [1993], and McNichols and O'Brien [1997]), we expect buy recommendations to be less informative abotit the analyst's assessments of intrinsic value. We test this prediction t>y investigating whether the share price response to earnings forecast revisions is consistent with investors placing greater w'eight on the forecast revisions accompanying favorable (buy) recommendations than on those accompanying tmfavorable (sel; or hold) recommen.datis)ns. 3. Empirical Predictions Our analysis oi the relation between security returns and tfie earnings forecast and stock recommendation components of analysts' reports is based on otir tmderstanding of how' analysts formulate stock recommendations. Specifically, tising a variety of information, including earnings forecasts, the analyst jtidges whether a company is over- or undervaltied. The degree of over- or tindervaluation is a contintious variabie that would presumably be of interest to an investor whose valuation model is correlated with the analyst's. Rather than reporting the contintiotis vari- {N'FORM.VrAXNtS.S OF ..\NAl.Y.STS' .STOCK RECO>!\{END.VriONS 197 able, however, the analyst typically makes a buy. hold, or sell stock recommendation, along with an earnings fbrecast. Ihtis, oalv the existence and direction of mispricing (not its magnitude) are reported. There is 'an information loss when the analyst reports a stock recommenclation rather than his assessment of intrinsic value. (Appendix A derives the optimal ctUofls for classifying buvs. holds, and sells which minimize this information loss, defin.eci as the niean-squared difference between analysts' unobservable valuations atid the valuations investors infer from analysts' recommendations.) To the extent earnings forecasts are inputs to the analyst's valuation model, they provide information abotit the unobservable valuation. However, because the recommendation impounds many pieces of information (see Balog [1991] and Heitner [1991]), it is not obvious how nnich incremental information is conveyeei bv an eartiings forecast revision made conctirrent with a recommendation. While prior research suggests that both earnitigs forecast revisions and recommenciations are informative when considered independently, there is no pttblished evidence of the relative informativeness of the two signals consiciered jointly.'- The formal test of whether the two signals convey differem information is; HI: Neither analyst."*' earnings forecast revisions nor their stock recommendations (or reyisi(.>ns therein) sttb.sume the information in the other. If neither signal subsumes the other, price reactions will vary erosssectionallv based on the relative precision of the two signals. In partictilar, if an analyst report contains a precise (imprecise) recommendation, then investors will place less (more) reliance on the earnings forecast revision. We expect that, relative to sells, buys are imprecise^ meastires of the analyst's tmderlying valuation, both bec?aise incentives to issue favorable reports will force aiialvsts to expctid greater care anci effort before making unfavorable assessments, artel because the incremental information loss attributable to positively skewed reporting of recommendation.'* is concentrated, in buy stocks.* Both arguments lead to the prediction that: iri: Investors place greater weight on earnings forecast revisions included in reports with buy recommendations than they do on the revisions accompanving sell or hold recotnmendations. tnctirect. Bandyopadh)'ay. Brown, and Richard.son's [i995i finding that carrentyear earnings forecasts explain only abcittt 50% oi 'he variatioti in onf.-\'ear-aliead price fore, casts stiggest.s that the two sigisal.s are iinlikeiv to convey the same information to investors. ' 'i'his result is denxinstratec! in .^tpj>t:ndix .\, wheie 'sve also sliow that if the distribiuion of the atiaivst's cotitinucms valuatic^rts is .sj'mnietric. the cutoffs wi'iich tnit'iinii/e itiforniatioii loss are sytRmetric. In this case, skewed reporting of stock recommeiKlations (i.e.^ is.stling more buvs 'and fewer sells shar, suggested by the oytimai cutoffsi results in greater total itiforinatioF; loss for buys than for selis. While we 'ase tiiis restili to predict that irtvestor.s attach iarg'ci weights to the earnings forecast revisions accompanving buv recomiriendanons 198 JENKIEER FR.'\N(;i,S AND EEON.ARD SOEEER W^hile prior research on investors' reactions to stock recommendations focuses on revisions, we iacltidc both levels of and revisions in recommendations, because we believe both are informative,^ Intuitively, a recommendation is a statement of the analyst's belief about the stock's intrinsic value relative to its market valtte; therefore, a buy (sell) recommendation, whether new or reiterated, implies that the analyst believes the security is ursderpriced (overpriced), while a hold recommendation implies that tlie stock is fairly priced, A revised recommendation draws investor attentif)n to a stock, W^e expect that investors use the new i-ecommendation and other information in the report to determine a revised security value, W^iile a reiterated recommendation could be interpreted as evidence that the analyst believes a stock continties tC) be mispriced, investors who responded to the initial recommendation may believe the mispricing has been eliminated. Therefore, a new recommendation is expecteci to evoke a stronger market reaction than a reiteration. Based, on these arguments, we examine whether recommendation levels, recommendation revisions, or both are informative, and whether reiterated recoiiimeiiciations are associated with weaker market reactions than new recommendations. 4. Sample and Dcita We examine 1,483 .'•eports written by sell-side analysts at 51 brokerage firms and available c.>n Investexl. The reports were isstied between January 1, 1988 arid June 30, 1991 for 54 companies with December yearends. To arrive at this sample, we first randomly chose 100 Compusiat firms with absolute Exchanges less than 80% in 1988 and 1989,^ Of the than to tbe revisions accompanying sell recommendations, we are cautious about drawing concltisioris about the relative precision of buys and selis becs-ase our mode! does not con,|;ider any l;)erief:ts iroiv, reporting skewed recommendations. For example, skewed reporting may provide analysts with better access to company management, which results in a more timely fi<.>w- of information to analysts and more precise estitnates of intrinsic values; this precision red-dces t'ne ijiformation loss for securities given 'Duy recomtnendatiorks. '•' Because stock prices are affected by earnings expectations, it is the revision in, raiher than the level of, t'ne earnmgs forecast that we expect to be corrt-ialed with securitv price movements. "Based on Stickef's [19S9J finding that analyst revision activity is greater the larger the unexpected earnings, we expected that oyersampling from the extreme earnings change (greater thar! ,80%) groups would increase the n-amber of analyst reports issued and. containing revisions. Therefore, in addition to the 100 firms selected from the nonextreme portion of the EPS ch-ange distri'oution, we randomh- selected 50 firms from the extreme positive tail and 50 firnis from the extreme negati^'e tail, 'f'iventy-eight firms in eat:h of these extreme samples had at least cjne analyst report; iti total, l,:'iIO research reports were o'btained and read fbr these 56 stibject companies. Because tiiese data showed no greater revision activity for the ,56 extretiie firnss as compared to the 54 nonextreroe firms, we report results ba,sed csn only the ri on extreme sample. We also perforrneci all tests on -tlie ftiil sample of reports with available data. These restiks {not reported) are .similar- in all respects to those based on the nonextretne sample. INFORM,A:1 IVKNE.S.S OF A N A L Y S T S ' S T O C K RECC)X!MENDAT'K)NS 199 100 firms, b4 have at least one analyst report on Inxuistext dtsring the sample period. The ntimber of anaivsts supplving at least one report on a .subject compan)' during the sample period ranges frt)m f to 18, with a mean (median) of 6 (4). The number of sample reports per firm varies from I to 123, mth a mean (tnedian) of 28 (12), ,A.nalysts frequentlv f'orecast earnings for one or more ftittire vear.s and for the ctirrent vear, defined as the earliest vear for which earnings had not been announced by the subject companv. Panel . \ of table 1 reports the distribution of research reports by current vear. Panel B, table 1 sutrimarizes the distributions of stock recommendations and revisions therein, and the frequency of earnings forecast revisions fc.ir the "full sample" (1,48.3 reports with, data on any variable) and the "restricted sample" (.^76 containing a stock recommendation [RI\.C], a stock recommetidation revision (AMTC), and a ctirrent-\'ear earrnngs forecast revi.sion iAFPS)).' Wliile most of the reports (1.415/1,483 or 95%) contain a short-term (6-12 month.s ahead) stock recommendation, onh' abo'at half (839/1,483 or 56%) indicate whether the recointnendation i.s a reiteratiori. or a revision.^ We do not compute revisions from two .successive-intime reports becatise the analvst may revise 'nis recommendation beuveen the two report dates and disseminate the revision eitlier throtig'h informal discussions or through a report missing from Iniie.stext. Wiile neariv all of the reports contain a curretu-year earnijigs forecast (1,454/1,483 or 98%. not reported in tab'le I), less than half (708/ 1,483 or 48%) contain information abotit forecast revisions. As with ARFC, we require that individtial repoits contain a valtie for AFF'S, or the informatioti necessary to compute it.-' Ftirther. by using otih" the information in a single report, ratfier than successi\e-i;i-time reports, we eliminate forecast revisions arising fiovA shifts in the analyst's ciefinition of earnings. For the restricted .sample, about, 469c of the stock reccinin:iendatic>iis are btxys. 43% arc holds, and about ]09f are sells, '.['bis di.'^n'ibution is similar to that reported by Schultz [1990] for a sample of 1,500 recommendations compiled bv Zacks Investment Research. Inc. (4^1.i3%' b'uvs. 45.6% holds, and 9.7% .sells). About 38%. of the revision.s in current £P5'forecasts are negative, while abotu 20% are positive. The mean change in the current-year £P.S'forecast as a percentage of tiie prior forecast is -5.18%: •About 2O''/c. of the reports also 'na\e a long-term (12-18 montiis ahead': stoc'K recommendation: of t'hese. 8S% are 'buvs. }>}% are holds, anci ;'"c are selis. .Vuou! %r>'^: of t'rie reports contain information on revisions in one-yeai-ahead eariungs forecasts: 14^- of these are upgrades. 5 1 % are reiierations. and 35% are dov.T.sjrades. Beca^c.se s.r: few reports 'nave these variables, we exclude 'botl; from further ariaiysis. - Most of the analysts iti otir sample i;se a t'nree-cate^orv system for ranking stocks ; huy, hold, and sell): a few tise a five-categorv .svsten^i istrong btiv. 'btrv, ho)d, seit. strong sel'i). In tertiis of defining REC, we treat strong hiiyi as bi:\s and strong sclis as seils, in lernis of defining ARE.Cve recognize •aptjrades frcjm 'btiv to strong b^iiy anci riowns;rades from sell to strong sell. •'.A. reiterateci earnings forecast results m a ibj^ecast re\isiori equal to zero. 200 JENNIFER FRANCIS AND LEONARD .SOFFER TABLE 1 Descriptive Statistics on Sample Analyst Reports Published between January}, 19S8 a7idjune 30., 199! Paiief A: Number (%) of Sample Reports by Year for Wliich Earnings Are Forecast" 1987 1.5 (1.0) 1988 .^17 (21.4) 1989 454 (30.6) 1990 512 (34.5) !99i 185 (i.2.5) Total L48?.{100.0) Panel B: Distributions of Stock Reconimeudations, Revisions in Recommendations, and Earnings Forecast Revisions Full Sample''' Restricted Sample'" REC Btiv Hold Seil N o RF:.C Totai AREC Upward Reiteration Downward No AREC Total &EPS AEPS>(t AEPS<0 No AEPS 781(55.2) 537(38.0) 97 (6.9) 68 1.483 91(10.3) 662(78.9) 86(10.8) 644 1.483 268(46.5) 248(43.1) 60(10.4) n.''a 576 15.13( 00) 49 (8.5) 474(82.3; 5$ i{>.2) n/a 2.76(.25) 576 2.20(.33) 160(22.6) 274.: .38.7) 775 Difl'erence'' 221(38-4) n/a 1.483 576. Total -.0471 Mean AEP.S/¥rio!- EPS 0.13(.72) -.05 IS 0.07 (.79) Mean A£ra/Price -.0038 -.0045 ^ ^The year hir whieS; eannngs are forecast h the earliest year ibr whk:h earriiugs had not beeii announced by the subject coiripaiiy. For example, Ib analvst reports issued afser January I, ;9B8 contained forecasts of 1987 earnisigs, 1987 earnings of these rinns bad noi been reporied ai the time of the analyst's report. ^The full sample consists of 1 ^483 reports for 54 liniiis wHh at least one anatyst. report, during the sasiipie period. The restricted sample consists of 576 reporLs with informatioi.- iu;cessary to discern or cojnpiUe a stock recommendation {,/(!/VC), the revision in the slock.recoir.mendatJon {ARI-X-). arid the revision jn the earnings forecast scaled bv share i^rice at day -50 relative to the repor! puhiication date (Ai:/*.S'), '^x'"" statistics are used to test whether the distributioEis of REC (bu\, fif)ld. sell), of hRhlC (upgrade... reiteration, downgrade), and of the sign of M%PS (negative, zero, posidve) diflet betweei; the full sample and the restricted sample. y'-statisti( s (significance levels) lest whether the average earnings forecast revisions of the two sainples differ. (significant, at the .0002 level); as a percentage of share price the mean earnings forecast revision is --0.45% (significant, at the .0017 level).'-' The third column of panel B reports tests of whether the distribtitiorts of REG, AREG, and the sign of AEPS for the restricted sample (which is '"Share price: is measureci a.s of day -50 relative to the publication date of the analyst report. INl-ORMATIX'ENESS OE ANALYSTS' S'l'Ot^K RECX>MMENDATK)XS 201 used in the empirical tests) differ from those of the hill sample. With the exception of RliC (where we observe fewer bu)'s and more holds and sells t^or the restricted sample). );--statistics fail to reject (at cotiventional levels) the hypothesis that the distributions do not diO'er across the two samples. Also, /'-statistics show no significant differences in the average earnings forecast revision,s of the two samples. We mea,sure security /'s market reac-tion to an anaivst report published, on day 0 as its compounded abnormal return over days -1 to -^1, CARi-l,+ l)j. Tlie abnormal return on day t equals the return on security i minus the ayerage return on day •' for all securities in the same Cfiy^ standard deviation of returns portfolio as security ;,'• 5, Empirical Work labte 2 reports the share price reactions to EFS forecast reyisiotis, stock recommendations, and stock recommendation revisions. We report mean and median three-day C4/fe conditioned on both the level and the change in the stock recotnmendation: we also show the mean AFFSfor each subset of reports conditioned on i ^ C a n d AREC Several points about these results are noteworthy. First, the mean three-day cumulative abnormal return around all btiv recomtnendations indicates that investors bid up share prices by an average of 0.85% (significant at the .02 level); there are significant positive reactions to both upgrades to btiy (1.28%-, significant at the .06 level) and reiterated buys (0,86%, significant at the ,0,'> level). Second, while the median reaction of -,44% (significant at the .05 level) to all Iiold recotnmendations is consistent with investors interpreting these recommendations as sells, the mean re.sponse is indistinguishable from zero. Third, while we observe no significant reaction to sell recommendatiotis in general, the 14 reports containing downgrades to sell are associateci w-ith an average decline of 4,76% (significant at the .03 level). Taken together, we view the re,sulLs in table 2 as indicating that both i?£'C and ARI-:C-dre important in explaining excess returns. The results in table 2, however, do not take account of ccmtemporaneously released earnings information; the mean earnings forecast revision for the sample is -.45%- (significant at the .00 level) and varies across the EEC and ARIX: categories. Because we expect AEPS to explain some of the excess returns at the release of the analyst's report, and because the magnitude of .\FFS differs across RliC and AREC, it is possible that differences in market reactions between, for example, upgrades and downgrades are driven tiiore bv changes in earnings forecast,s than by revisions in stock recommendations. We explore this possibilitv by first investigating liow well earnings fore(;ast revisions alotre explain variation in G4A*(-L + 1), The first column of table 3 reports the coefficient estimates •' Similar resttlts are obtained using beta-adjusted excess returns and nw 202 JENNIEKR FR.\NCIS .A.ND LEONARD SOFEER TABLE 2 Cumulative AAt)norwial Returns and Earnings Eorecast Revi.nons Associated vdth 576 t Reports Published between January 1, I9fiS and June 30, 1991 REC Buy (K) Mean CAi?(-l,+ l) Median a4/f(-l, + i) Mean .fiEPS Hold («) Mean C-V^C-l.+ l) Median G'LR(-;,+ !) Mean Ai'F.S Seii(n) Mean C4if(-l..^'^rt Median C4i?(-1.^1) Mean A£PS Total Meat; CAfi(-l.+Ti Medina CAR(-i,+ 'i) Mean Upgrade Reiterated (.35) .OTaS'^Oo)" (227) ,0086(,03; .;)049(,()2.i -.OOlTi.OO) (20.?) ,0020(.70) .0042{.l0) .0010{.i4) (12) .(1068(,63! ,0181 (.42) .()O3 7{.55) (2) .0008(.98) .0008(.99) .0006(.S5) (49) ,0075(.20; .0004(,33) .()003(.71) -,0()54(.28) -.0067(.0S') (44; -.0005i:,95) .0015(.95) -,0066(,01) (474) .0Oi9(.lJ) .001J(.3S) -,O04B(.Ol) Downgrade -,0;95(,23) -.0106(.22) -.0013(.40) -.0149(A7) -.018S(,06) .0089(.01) (14) -,(M76(.03''i -.O2O1(.OO) -,0]82{,lJ) (5S) •.0241(.01) -.()i67(.00) -.0l()5(.00) Total (268) ,0085(,02) .OOidi.Ol) .00i3(,0'i) (248) ,0006(,89) ,OO44(.O5) 0067(.03) (60) .0114(.15) .0072(.l7) ,0092(,()0) (576) .0025(.36) .0006(.9i) .0045(.00) ^'arlabk definitions; CAJl{~l.i I) is the ctimulative abnorrria! returs 1 over cia^ys (-'1,+ li relative to the 'DHcation date of tht: analyst's report; RKC is the analyses sti>c'^ reci inirrieiidatior- (huy. hold, or sell); AEFS is h the revision •;!! r'!it- anaiyst's stock recomuiendation (upgrade ri:iteradori. dovnsjzdt): t)ie revi.sion in rhc ana.iysl's ciirrenr earning.s foreca.s! scaled bv .share f.•rice on ciav -50, 'VSigirificance levels for cross-sectional /,test and Wiicoxoi; tes! oi v .'iiether ti:te mean (niediani vaiue differs from zeny are re[)orted it; paieutheses. (significance levels) for the regression of CAR(-i . + 1), on AEPS.'-''^ Cotisistent with, previous research, we find a sigtiificant (at the .01 level) positive relation between excess returns ap.d the signed magnitude of the earnings forecast revision. The second and tliird columns of table 8 pro\'ide information on the market reactions to recommendation levels and tt) recommendation revisions, based on the following regressions:'-^ CARi-1,-^ CAR(-l, J ) , = fijBm'i ^ ^2^fOLD.i + B^SELL, + s, (1) (2) where the following indicator variables take oti a value of 1 if the condition is met and 0 otherwise: BUY, = 1 if report i contained a buy recommendation; H()LDi= f if report /'contained a hoid recommendation; SEFI.,^ = I if report i contained a sell recommendation; UPGRADF',;^ = 1 if '-The results in table 3 exclude ohseryatiotis identified as outliers bv BeLsiey, Kuh, and Welsch [1980] diagnostic tests. The number of ohservatioiis excluded ranges between .3 and 25 dependitig on the regression. '*The difference bet^sveen the resuks iis table $ and the average abnorn:tal i'eturn.s documented iii table 2 is due to the exclusion of outliers from the regres.sioti te.sts. INFORM.AT;\'ENE.S.S OF ANALYSIS' STOCK RE(::O.N!.\1END.-VT1ON.S 203 TABLE 3 Market Reactiom tu 576.Analyst Reports Fnblished bftxi'efn Jar,nar^ 1. !9SS and jui.'e 30.. I99l 'Conditioned on Stock Ftecommeridatioas and Fanwugs J^ifonm-tion Pane! A: OLS Coefficient Estimates (Significance Level) Intercept .OOOR(.Oii ^EPS .!239i.O:! 3LT .0046i:,02: HOIJJ -.00."2i.09) SELF -.0066(.!i9) VPGPJiDF m'JTEFL\TF DXGRADF .:OS-::.05j .0075;.OS) .0011 (.52; -.0>05>.OJ) UPBLT liFBlT .012^:.04; .0045:.08; -.0195{.20i -.()0bHi.55; -.001&;..!S; 0:27.05; .004;t.l;) -.0194;.2;! -.0067;.54: -.0012;.65: DXHOITJ -.0144;.OS) -.O135f.O5: I'FSELF FiESFFF DS'SEFL F- .0008;.98: .00(iS;.89': -.03:5::.'M:i: .(Mi4(.0i; .000S:;.07;.00;5f.S0; -.029-h.0;; .04S6:;.O0; .0)2j<i.i.>l) Oi3Oi.O7) .0275;.00: Panel B: /"-Statistics (Significance Levels) for Tests of E.stimated Coefficients AFFS, Conditional or, REC and ARFC HQ.AEFS^G 5.24(.!i2i RFC Mid Afif-G. (.(.mditiorta! oti AFPS >= rPSFFF. FEBl-Y^ 'J.XBIT - DXFIOFD = DXSEFF = 0 :ia; on RFC III,: i'FBlT--- UPHOU)= UFSELF, Ri^Bin'^ RFHOID ^liESEFF, iind FJXBUY = D.XHOW ^ D.XSEFF RFC. Ouridinoria! or; AFU:C llr.. UFBIT^ FEBl'}'-. D.XBli: UFHOII.)-. Rt.HOl.t! - DXHOII), and Ul'.sELl. .-- l.iEMil.L = DS'SEl.L 2.25: .02; 2.S)7:.00) l.3'\ < .2S . 2.!3iO2i • .00.;..! 4 : Reiterated versus Revised Recontmendadcris Hij: RFBUY^ i'PBUY 1451.24) 1.55::.2n Hu. M'.HOllI- I'PIiOlI) MQ. REHOLF)-. DXHOW F]Q: F£SFJ.F= I'PSFFF H,y RE.SEEE = FlWStFF 0.19i.»?; 2.90f.05:: 0.00(.09} 7.28. .OOi 0.2?v.79! 2.78:.06; O.OO:.99) (3.60;.00: The number of observations tn eacii regressi.ari ranges, htn'ween ooi and ."'7.'^. tiepetjding on the iiitniber of otitiitrs idetitified by Belsiey. Ku'h. and ''.Veisch [ 1'9SC'• diagtiostic tests. In ai: regressions, tfie depe!:d.e:'.t v<uiabie is C.\R-.-l.^ 1.-. the cumulative abnorma: rettirr>. over days .:'-!.-*-i; leiati^e to the p'.ihiication date of' tfie anai\st's repoit A.^.^.S is tiie revision ill the analvst's carrent eartiings forecast scaled 'D^' the s'''i.ire price on cia\ -.?0. I h e ternaimnp x'ana'Dies take or. '.'. ^'aliie of 1 if the ti.oted corriitioi; is trict and (* other\^ise. PtCY.; - I if report ; c.oiit.dried ?.. hu\ teroinmetidiitioa. HOIJ^. -- 1 ii report (' contained a hoid reri'ttimetidatior:; SLLL; = 1 if reptirt : contained ii if report ; upgraded, tiie stock recoiiiinendatior;; REJTERATE^ - I if report f reitei .'.ted tfif prtniotts stock recommendation; DNGRADE;' if report i dowtigraded the stock recotr.inondatioi;: ITBIT.-• ] if report , upat'aded the stuck re;.omniciidr.tioi'i to a bti\'; fti.BlT^ = I if repov; :. reUc-rated ;: 't.ttiy reconinicndatior:; DXBi'}) - ; i: repot t .' dov. ngr'aded the rer.omiiietldation to a bti\; CPHOI£\ • I if report, c t'.*.:igraded the stock rec.rK d.-tion :o 2 hoid; RE.HOLS!. ^ ) if report ( reiterated il hoid recotiin'ieiidatior.; D\"IJ()JJ), - \ if report .' d'.nMiy:rade o stock reeottnTictidatioi; t(. a hoid; CPSEtJ^^ = I if repor't ;' upgraded the stock rrcottiuiendatior; tf> ;; .se!!: RESELI , = if r;'t;>ort / reiterated a stdi recorntnetir.ation. DXSFLL. - ; tf report .' dovtigraded the stock recotriniertdrition to a st 204 JENNIEER ERANCIS AND EEONARi:* SOEFER report ?'upgraded the stock reconimendation; REFFEKAFEj = 1 if report ?• reiterated the previous stock recommendation; DNGRADE,^ =- 1 if report i downgraded the stock recommendation.. Results of estimating eqtiati<;ni (1) indicate that the- ordering of market reactions to recommendations is consistent with expectations (buys > holds > sells); we reject the hypothesis that pj = fig = p;.^ (F= 3,60, significant at the ,03 level). The restilts also show that the individual coefficients are significant in the expected directions: btiys are assoe;iated with an average response of ,46% (significant at the .02 lei'el), and holds and sells are associated with ayerage price declines of .32%^ and .66% (both significant at the .09 level). Finally, consistent with allegations in the popular press (e.g.. Greenberg [1992]), we find that investors appear to interpret holds as sells, insofar as we are unable t(;> reject tbe equality of p9 and p^ (the /-statistic is 0.35). The results of estimating equation (2) alsc;* show the expecteci ordering of cocfficieot.s (upgrades > reiterations > downgrades), and /-'-tests reject the hypothesis that 5, = Sg = 83 iF= 7.70, significant at the .01 level). We find that upgrades are associated with an average market response of ,75?4 (significant at the .08 level) and that downgrades evoke nearly a 2% price decline (sigtiificant at the .01 level). We next investigate the market reactions to earnings forecast revisions, stock, recommendations, and reyisions in stock recommendations, each conditional on the others. Eqtiation (3) investigates the effects of recommendations levels and reconimc^ridation revisions on market prices, and equatioti (4) atigments (3) by adding earnings forecast revisions: 1).,; = aj UPBUYj -f -j + at^REFIOID, + af^DNHOLD-,- + ayUPSELLj ^ * duDNSELL, + E^ 1- a^DNBUY^ + a,iUFHOLDj + ^ , c / -f a-jUFSELL-^ * a-f^RESEEL, + a,J)NSFLL., + E. (3) , (4) where the following indicator variables take on a value of 1 if the condition is met and 0 othenvise: UPBUY-^ = I if report ? upgraded the stock recommendation to a buy; REBl^^ -•- 1 if rejjort t reiterated a buy recommendation; DNBL^'j = 1 if report / downgrsfled the stock recommendation t.() a buy; UPHOLDf = 1 if report i upgraded the stock recommendation to a hold; REHOLDj = 1 if report i reiterated a hold recommendation; DNFfOII); =- I if report i downgraded a stock recommendation to a hold; UPSELLj = 1 if report ,•' upgraded the stock recommendatioti to a sell; RESELL.^ = 1 if report i reiterated a sell recommendation; D.NSELL-- - 1 if report ?' downgraded the stock recommendation to a sell. Table 3 reports tests of HI (whether the information in either earnings forecast revisions or in stock recommendations siibsumes the ENFORM.VnVENESS OF .-\N,-\i,y.ST.S' SIOCK RECOMNiEND.VTlONS 20.O Other). The tests foctis on the iticremeotal explatiatory power of AFPS relative to the set of recommendation variables, and vice versa. For example, a comparison of the R'-s of equations (3) and (4) indicates the incremental informativeness of earnings forecast revisions conditional on stock recomtnetidatiotis. I'hc f-statistic for this cotnparison. reported in patiel B, is significant at the ,02 level. We also reiect the hypothesis that the set of variables capturing the level and the revision in recommendations provides no explanatory pow'er be^'orsd that provided bv .\FPS. Specifically, the /--statistic rejects (at the ,02 level) the nuii hypothesis that 0; = a^ = , . . aci = 0 for eqttation (4). In terms of f/l, tliesc results indicate that neither .stock recommendations tior earnitigs forecast revisions stibsume the ini'orination in the other. Our first specification test (whether (he levei of and the revision iit the stock recommendation explain stock rettirns conditional on the other) investigates the incremental explanatory power of equation (3! relative to eqtiations (1) and i2). In particular, if the Tccommendation level is an important factcir explaining stock rettirns, bevond the rec(.)mmendation revision, theti we would reject the null hypothesis that QI a_x = 07. a.j = Or., = a^. and a.> = a^ = ag. A joijit test of I'Uese restrictions is provicied Liy an /•"-test of the incremental explanatory power of equatiori (3) relative to eqtiation il). Similarly, the /'-test comparing tlie /f-'s of eqtiations (3) and (2) provides e^s'idence on whether the re^islon in the reconimendatioii adds explanatory power bevond that conveyed bv the level (i.e., it is a joint test of aj = aj =ft-^,a,;. = a-, = a,:;, Pdid a- - a,.; - a-.i). /'-statistics corresponding to these comparisons are reported in the first column of panel R. The secotid coltumi reports /'-statistics for comparisons performed after conditioning on earnings forecast revisions (that is, we add Ai:'P.S'to the right-hand side of (I) and (2) and con^ipare the explanatory j:)ower of these augmented regressiorss to the explanatorv powe: of (4)). Both .sees of /"-statistics reject (at the .02 level or l>et.ter.: the joint hvp(>t.hesi.<i that a; - a^ ~ a.-^, a., = ar, = a,^, an.d a^ = a.^ -" aa. However, thev fail to reject (at conventional levels) the joint hypothesis that at - a.j = 07, tty = a,-., = a,s. and Otj =ttfj= c^. Overall, these results indicate that while the recommendation revision matters after controlling for the recommendation level, the re^'erse is not trite. The second specification test (wfiether reiterations are associated with weaker reactions than new recotumendatioiis) holds constant the recommendation level and compares the securny price moNemetit.'. associated M'ith reiterated and new recomniendations. Panel Ii reports F-statistic.s investigating wliether the coefficient estimates exhibit the following paiiwise relations: a^ = Qj. a» = a^, cir., = a.j, as, = a,::,, as. = a7, and tts. = Kg. "We interpret the significance (at the .10 level or better) of three of the six /'-statistics in cotubination with the pre<iicted signs of the differences (a^ > a,;, ar; > a^,, and a^ > cxe) as pi'oviding at least some support for the prediction that reiterations are associated with weaker share price responses than new recomtnendations. FtirSher. the fact that al! of the significant /-statistics compare reiterated recommetidations tti 206 JENNLI^ER FR.ANCLS AND LEONARD SOFFER downgrades indicates that do'ivngrades are the most important, factor in explaining ihi.s result. Tests of H2 (whether AEPS conveys different information for buys than for sells or hold.s) are reported in table 4. We report the coefficient, estimates (significance levels) for regressions of CARi-l, + l) on AEPS, run separately on reports containing buy, hokl, and sell recommendations; based on the results in table 3, which sho'wed significantly negative and indisting'aishable reactions to hoki and sell recommendations, we also combine reports containing either holds or sells. A comparison of the intercepts confirms an average increase in risk'•adjusted share prices in response to buy recommendations (significant at the .02 level) and an average decline in risk-adjtisted prices in response to sells (significant at the .10 level). While the results indicate that investors react significantly (at the .03 level or better) positively to earnings news accompanying buy and hold reports (no significant response to AEPS for sell reports is observed), the response coefficient on the forecast rc;visions accompanying buv recommendations is significantly (at the .02 levei) larger than the coefficient on the forecast revisions accompanying either hokl or sell recommendations. This result is consistent with ctur prediction that investors place greater weight on earnings forecast revisions accompanying reports with favorable recommendations.'^ We test the sensitivity of the results in tables 3 and 4 to data issues, including outliers, report clustering, and contemporaneous disclosures. While the explanatory power of the regressions is lower when outliers are included, the same pattern of significant coefficients emerges. W^e also note that while the number of reports containing sell recommendations is relatively small (60), over 65% of them have nonzero earnings forecast revisions, which implies that even for this smallest category, there is a sample of 39 observations to estimate the responsiveness of investors to earnings forecast revisions.'''' Clustering of reports from different analysts following the same firm mav occur wheii one analyst's report prompts other analysts to issue re-*AR alternative explanation is that the three-day event window fails to capture the !narket\s reaction to t'ne earrJngs news conveyed in hold (.ir sell reports. For example, if analysts disseminate bad news (such as sell or hold reconiincridations and downward earnings forecast revisions) prior to the formal ptiblication date of the report., our measure of security price response {CA.R{-\..-^l)) will be incomplete. The diffictiity in testing this explauatioi^ is that we caiMiot distinguish empirically i-iet\veen price changes ca'iised by early dissemination of the ar.alyst's report and price chap.ges that cause ariaiysts to revise earniiigs fosecasts and issue stock recommendations. ^'•'As an additional check o!i the restiits ic tabie 4. we replicate these tests after incStiding the reports c:c)ded for the extreme earnings change samplf, describeci ir! n. 6. The sample sizes across btiy, hoid, and sell categories increase to 417. 387, and 85, and the percentage of nonzero earnings forecast revisions in each category is 60%, 68%., and 73%. With the exception of a significant negatix'e ii'itercept for sells and a weaker positive intercept for buys., the results for thi.s expanded sample are sin'iilar to those reported; in partictiiar. we find sigiiificaritly higher response coefficients on AEPS thr 'bays than for either holds or sells. INEORN-LAEIVENES.'i OE ,\N,\EY,STS' .STOCK. RE(;C)^{^,!END,AT[OXS 207 TABEE 4 The Importance of Earnings Infitrpiation (.onctitional t'n Stock Reconnnendanons !h. ''16 -:Vnahst Reports Puhii-'Jied betu'een faniiar-i I. ! OSS and ftnii jn. }'-!91 Stock Recommendation in Anaivst Repor; BUY .() U:^^ 2; &.ERS t poi' I t -- )tf 1 If S>"3 - - i t t < I- ^ ! + Q AZ.PS y - S3 >n tof I r S\ V" h( ni t 1 '^ r es t « f II I \'i{.it ! f p 1 c MCI 1^ II n vs i»- P ~i "1" ) i b lit*. SII / sta ISO ft 1 KiV f lt(. cist s -.00 2o ;- ^0 Oh; 13 '>O 1 I ^ A ) t{ C \ f.k 1 I tl It f-p tr '.03 5.;?4 t I it-^ ^ 1 t 1 ( 1 \ i st 1 lel ' y?' '•• .O2; ; 0^>: 5.5.i (.i)2; i' llf f,; 5.64 ;.O2; Rcu:i:ilii^ -)") HOU)'SFI. - . 0 5 9; 5S (i pi SELL .8 264 /-'-Statistics iSignifjcance Eevehi &.EPS{BVYS\ - i.EPS\HOLDS) ^EPSiBUYS') -- AEPSiSELLS) AEPS<BUYS'i = AEPSiHOIDSlSELLSi \> HOIJJ 1, } e s f oiio i 1 " II I •! \\ fiul 'ifa i -i nds 'i 1 ! I II ' -. 1 i t' ^ >) 1 t' f \ X \ K .• I ol ^11 1 es III tt 1 1 1 1 ^l( ports containing forecast revisions and recommendations similar to those made by the first analyst. If succeeding reports con^ey no new information, including them biiises our tests against finding significant reactions to report components. On the other liand, reports issued conctirrently or withit; a day of each other ititroduce dependence among the sample, obseryatiotis which oyerstates our significance levels. To explore these issues, we comptited the ntimber of days between the sample reports made by different analysts follo^ving the same firm,''-' The -iieaB ntimber of days betweeti two reports about tiie same firm is 30 and the n;icdian is 1,5: 69 sample reports are made within one clav oi another report. We reran the analyses in tables 3 and 4 excluding these ()9 reports and found the same pattern of results with slightly liigher significance levels (results not reported). W'e also itivestigate whether the significant relatioti bet^v'een ctimulative abnormal returns and earnings forecast revisions is due in part to the existence of other disclosures which (;atise both tlie contemporaneous stock price movements and the forecast reyision. For example. 8tickel [1989] documents an increase in the frequency of analysts' earnings forecast reyisions foliowing interim earnings annotincen!erit,s and stiggests that such activity may link prior studies' findings of a'bnortnal returns iollowitig earnings annotincements and a'tjnormal rettxrns after forecast revisions, Tb determine whether atialysts' reports issued after earnings announcements drive the restilts, we re-estimate the regressions in tables 3 atid 4 after deleting the 93 reports made within three davs of •*'"K} avoid oyerstatitig the number of days between reports, we use ihe fuH sample of i,483 reports to determine tlic proximitv of otie report to anot'ner 208 JENNIEER FR.\NCIS AND LEONARD SOFFER a q'uarterly earnings announcement. The results :'not reported) are similar to those reported. 6. Conclusion This paper provides evidence on the market reactions to earnings forecast revisions, stock recommendations, and revisions in stock recommendations contained irs 576 sell-side analyst reports published between Jantiary 1, 1988 and June 30, 199!. As a grotip, variables capturing these attribtites of analyst reports explain about 5% of the variation in excess returns cumulated over days (-i,-^l) relative to the report ptiblicadon dates, "We find that neither earnings forecast revisions nor stock recommendations stibsume the information in the other. The significance of stock recommendations controlling for earnings news suggests that while the reporting of categorical stock recommendations (as opposed to assessments of intrinsic value) may reduce the informativeness ol' these signals, the information loss is not complete. Further analysis indicates that the informativeness of stock recomtnendatiotis derives from the revision in the recommendation rather than the level; that is, the recommendation level does not appear to matter, after controlling for the change in the recommendation. Tlie results also show that, holding the recommendation level constant, the reaction to reiterated recommendations is generaiiy weaker than the reaction to new rec:ommendations. Most importantly, the results show that investors place greater reliance on other information in the analyst's report—specifically, earnings forecast revisions—when that report conveys a favorable stock recominendation. 'W'e Bnd a significantly (at the .02 level) larger response coeflicient on the earnings forecast revisions accompanying buys than holds or sells. Ho'SA'ever, the fact that we observe a significant (at the .02 level) positive reaction to the average btiy recomniendation. stiggests that investors do not completely discotxnt these recommendations. This study coiUribtites to the literature on security analysts' w'ork products in several ways. By documenting that market reactions to analysts' reports are significantly related to both earnings forecast revisions and stcK:k. recommendations, our analysis confirms the intuition that neither of these signals about share values subsumes the other. Otir result showing similar negative market reactions to hold and sell recommendations also confirms anecdotal evidence which asserts that investors interpret holds as sells. Finally, like Hirst, Koonce, and Simko\s [1995] analysis, otir study indicates that investors' responses to one type of information in an analyst's report (e.g., the earnings forecast revision) depend on characteristics of other information in the report (e.g., whether t.he stock recomniendation is favorable or unfavorable). The fact that otir results are opposite to theirs (i.e., they find that subjects seek otit more information when recommendations are tinfavorable) suggests either that investors'' responses INFORMATIVK.NKSS OF ..\N.\LYS'i'S' ST<:)<:K R E C O M M F . N I > . \ T I ( 1 N . S 2C>S> are driven by factors other than the behavioral forces thev posit, or that the interaction between report signals is more complicated than the one <;aptured in tiieir experimental setting.'' Otir archival tests ass'tmie investors seek out '"true" information about a stock's valuation; that is, whilt' investors may care abotit whether a report disconfirms their prior beliefs, we as.sume they also care about whether those beliefs are sufficiently acctirate to warrant taking a positiori in the stock. In contrast, Hirst. Koonce,, and Simko's analy.sis depetids less on stibjects seeking out trtnh thiin it does on subjects' propensities to seek otit information which confirtns their prior beliefs. If subjects' beliefs do not converge with the actions of wealth-maximizing investors (which we believe are reflected in the empirical-archival data), the restilts of the two studies will differ.''"' APPENDIX A Information Eoss Due to Reporting Discrete and Skewed Recommendations Define the total information lo.ss from reporting discrete recommendations rather than the contintious underlying valuations as the sinii of the squared differences between the underlying valuations (x) and the valuations investors optiinallv infer from the observed recommendations (^). As.sume there are r^vo cutoffs, a and b, for classifying stocks as buy, hold, and. sell stich that .x < a ior sells, a < x < h for holds, and x > h for btiys. We seek valties of a and /; which minimize the inforriiaEion loss function, V= -^j" ix- \.\)~ fix)dx. The aggregate loss functicji's over the three categories of recommendations can also be written as: ' \.i-{aM [F{b) ->(«)] -rikoojll-Fim 'vv'here f.M-«>. a), u(.a.l>). anci p(&. =») are the conditional rnean.« of the valuations of the stocks in the sell, hold, and buy categories, respectively; and/(•) and F(-) denote the pdf und erf/of .t, respectively. ' ' Re;;alt that wiiiSc both studies examine how investors use other inforntation accompanying tavorable verstis '.infavorabic stock recommendations, the two studies differ in the type of other 'information examined. We focus on earnings forecast revision^ while ilirsi. Koosice. and .Simko n99."i] examine disclosu.res of investment barsking relationshtps 'between tl'ie client Brni axid the analyst's eir.pioyer. It is pos.sibie that diii'erence.<i in I'jow these tvpes of other injcsriiiation iiiteract with the information in recommcntiations accoutit {OT the disparitv iti results. '"'' Some stipport for (he view that the realisn'; of the investment decisioti i.s important is provided by Botnvmari. Frishkoff. atid FrisJikofT s [199.5] protocol atialysis exatrihtitig rhe types oi' iisforniation 'used by ana'lvsts isi an investmenl screening decision. They report treat analysts who spent less liian ;10 niiir.ises eyakiating the case company typically rejecied it, asserting thai once they had identified a reason to reject the conipanv. Ihev were not iriferested in reviewing aciditional information. ."Analysts who viewed the comparty tnoie favorably .spent snore tinie exarnining all available inforiiiatioti.. 210 JE.NNIEER ER.ANCES .'\ND EEON.A,RD ,SOEEER W'e impose the first-order conditions dV/da = 0 and dV/db = 0 to obtain the following o})tinia! cutoffs: b* = These ciitoffs minimize the information loss from reporting recommendations rather than valuations. Additional information loss occurs when a* and b* are not chosen. For example, if b' < b'* is chosen, more stocks will be classified as bu)'s than dictated by the optimal cutofF. If the underlying distribution of x is symmetric;, the optimal distribution of recommendations will also be symmetric, WTiile the distribution of X is unobservable, the fact that we obser\'e many more bu}'s than sells stiggests that x follows some skewed distribution, or that x is symmetric but the observed cutofF (b') is not optimal. The next result demon,strates that if x has a symmetric disnibittion and if b' < b*, the information loss due to skewed reporting will be concentrated in bu)' stocks.'-' Assume that x is symmetrically distributed and, withotit loss of generality, that its mean is zero; further assume that. /'(.«) > 0 for x < 0 and fix) < 0 for X > 0. The condition that the cutoiF for buy stocks is set too low implies b' < -« = b* and ^i(^',°o) < u(-«.,!»). We show that the information loss in buys, y/'^ (x - \i{b',^))-f{x)dx, is greater than the information loss in sells, _«.,f''(,'i - u{-°^,a))- fix)dx. The information loss in buys can 'he written as: ^))- f{x)dx aT ^ f {AY) Since ij(-fl.,oc) is the best estimate of the valuation of buys (i.e., b* = -a minimizes V"). it follows tliat: .Substituting A2 into Al: j/fix- ii{b',°°'}'i'^'f{x)d-x = a ///"''' (X - M (l>'^'^-'})" /(x)d-x + _.a,f°° [x- ii[-a,°o')Yi f{x)dx = fi J" " (X - ^i (//,oo)) - f{ x) dx + ..^.J" ( x - u(-oc-,ff))2/i;x)(fx. (A3) Since i:f~"ix - ii(b',o^))'^f{x)dx > 0, it is clear that f/J^ix - p.(o',<>o))2 /(X') dx > .,^. / " (X - fi (-oc, a)) ^ /(X) dx. *'--' It seer.is reasonable to 'Delieve that tbe underlying distribution of vai-uations, which is based on the expected returns of stocks, i.« symmetricaliy distributed ai-ound the expected retiirn or; the tnarket portfolio. 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