Do stock prices underreact to SEO announcements? Evidence from SEO Valuation

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1 Do stock prces underreact to SEO announcements? Evdence from SEO Valuaton Amyatosh K. Purnanandam Bhaskaran Swamnathan * Frst Draft: December 2005 Comments Welcome * Purnanandam s an Assstant Professor of Fnance at the Ross School of Busness at the Unversty of Mchgan, Ann Arbor and Swamnathan s Professor of Fnance at Cornell Unversty and Drector of Research at LSV Asset Management. We thank the partcpants at the Unversty of Mchgan brown bag workshop for helpful comments and suggestons. Any errors are our own.

2 Do stock prces underreact to SEO announcements? Evdence from SEO Valuaton Abstract Ths paper examnes whether the market underreacts to the negatve nformaton mplct n SEO announcements. We fnd that t does but condtonal on the valuaton of SEO frms pror to the SEO ssue date. SEO frms that are overvalued relatve to ther ndustry peers experence a smaller declne n market value on the SEO announcement day but experence a larger declne over the next fve years. The results are robust to varous ways of choosng ndustry peers and valuaton multples and varous methodologes for computng rsk-adjusted abnormal returns. Cross-sectonal regressons ndcate SEO P/V ratos (offer-prce to value rato based on relatve valuaton technques) are sgnfcantly postvely related to announcement day returns and sgnfcantly negatvely related to long-run returns even after controllng for expected growth rates, accruals, and B/M ratos. Addtonal tests ndcate overvalued SEOs earn lower returns around future quarterly earnngs announcement dates and do not exhbt superor ex-post operatng performance. Yes! Stock prces do underreact to SEO announcements.

3 1. Introducton There are two well known emprcal fndngs wth respect to seasoned equty offerngs (SEO henceforth): (a) Frms that announce SEOs experence, on average, a declne of 2% of ther market value relatve to the overall market on the announcement day and (b) Over the next 3 to 5 years, the SEO frms underperform varous style benchmarks by about 3 to 4% a year. The announcement day effects are typcally attrbuted to an explanaton based on the adverse selecton model of Myers and Majluf (1984). Accordng to ths explanaton, snce only overvalued frms are lkely to ssue equty (when they cannot ssue debt) the market ratonally lowers ther market prce to the ntrnsc value on the announcement day. The explanatons for long-run SEO underperformance fall under three categores: (a) overoptmsm on the part of managers and nvestors about the future prospects of the ssung frm whch leads to ntal overvaluaton, under-reacton to the SEO announcement and subsequent slow reverson to ntrnsc value (Loughran and Rtter, 1995), (b) model msspecfcaton n measurng rskadjusted abnormal returns gvng rse to spurous underperformance (Fama, 1998) and (c) a rsk-based explanaton that suggests ssung frms are less rsky (Eckbo, Masuls, and Norl, 2000). The effcent market vew of SEO announcement effects and long-run returns s that the market correctly reacts to the SEO announcement and lowers the value of the SEO frm to ts ntrnsc value whle the long-run underperformance s due to ether model msspecfcaton or lower rsk. The neffcent market vew s that the market underreacts to the ntal announcement (that s the market value does not fall suffcently after learnng about the SEO) and contnues to move n the same drecton over the long run. These explanatons are a source of great debate and controversy n the lterature. In ths paper, n one of the frst attempts to systematcally value seasoned equty offerngs, we estmate the values (as of the offer date) of about 1,700 SEOs from 1978 to 2000 based on the market valuatons of ther non-ssung ndustry peers and use these valuatons to explan the cross-secton of short-run announcement effects and long-run abnormal returns. 1 Unlke earler studes, the use of ex ante valuatons allows us to drectly examne a key mplcaton of the 1 Purnanandam and Swamnathan (2004) use a smlar approach to value IPOs. 1

4 Myers and Majluf (1984) model: the more overvalued s the SEO frm pror to the SEO announcement the larger should be the declne n market value on the announcement day. 2 In addton, f the market value declnes to ntrnsc value on the announcement day as expected under effcent markets, there should be no relatonshp between ex-ante valuatons and long-run abnormal returns once we carefully control for rsk. In contrast, the neffcent market explanaton predcts that the most overvalued SEOs should under-react more to the SEO announcement and underperform the most n the long run. The ndustry peers are chosen by carefully matchng the SEO frm to a non-ssung frm n the same ndustry (usng Fama and French (1997) 48 ndustry groups) on past sales growth, current EBITDA proft margn, and sales (as a proxy for sze). We value the SEOs usng a varety of valuaton multples: prce-to-earnngs multple (both based on tralng earnngs and analyst forecasts of earnngs), prce-to-sales multple, prce-to-ebitda multple, Enterprse Value-tosales multples and Enterprse Value-to-EBITDA multple. We also experment wth dfferent ways of choosng ndustry peers to ensure that our methodology s robust and our fndngs are not specfc to the choce of a partcular multple or a partcular way of choosng ndustry peers. Our results are as follows. At the offer prce, the medan SEO frm s overvalued by 15% to 90% relatve to ts ndustry peers dependng on the multple and the methodology used to select ndustry peers. In the cross-secton, the frms that are the most overvalued pror to the SEO announcement date (or as of the offer date) relatve to ther ndustry peers experence the smallest declne (under-react more to the SEO announcement) n market value on the announcement day. These frms also underperform the most over the next fve years. The top 40% of the most overvalued frms underperform the bottom 40% of the most undervalued or the least overvalued frms by 3% to 5% a year over the next fve years dependng on the benchmark 2 In Myers and Majluf (1984), the nformaton that the frm s overvalued s prvate known only to the managers. The SEO announcement conveys ths prvate nformaton to nvestors. Investors know only the dstrbuton of overvalued and farly valued frms n the populaton. In contrast, our valuaton measure s based on publc nformaton. However, ndvdual nvestors are unlkely to have access to the knowledge or nformaton necessary to do valuatons of the knd we undertake n ths paper. Therefore, from ther perspectve, these valuaton measures can be consdered prvate nformaton. Emprcally, these valuaton measures are lkely to represent nosy proxes of the managers prvate valuatons. 2

5 and the methodology used to compute abnormal returns. The long-run results are robust to varous ways of measurng abnormal returns and are strongly confrmed n cross-sectonal regressons that control for varous frm characterstcs such as accruals, B/M ratos, and longterm growth that are known to predct long-run returns. The more overvalued SEOs also experence sgnfcantly more negatve prce reactons around future quarterly earnngs announcements (compared to the less overvalued SEOs) suggestng that the nvestors earnngs expectatons are too hgh for the overvalued SEOs as suggested by the overoptmsm hypothess. Thus, the cross-sectonal dsperson n the long-run underperformance documented n ths paper s unlkely to be all due to model msspecfcaton. Furthermore, our analyss of post-ssuance operatng performance shows that overvalued SEOs have lower proftablty than ther undervalued counterparts. They exhbt hgher sales growth n the frst few years, but n the long-run there s no dfference n growth rates across two groups. Thus, overvalued SEOs are unable to convert ther ntal hgh growth rates nto hgh profts. It seems that the SEO nvestors (just as n the case of IPOs) focus too much on ntal growth and too lttle on proftablty n valung SEOs. Overall, our results suggest that the most overvalued SEOs experence the smallest prce declne on the SEO announcement date whle underperformng the most n the long run. Our results support the underreacton hypothess and are nconsstent wth the effcent markets explanaton. The rest of the paper proceeds as follows. Secton 2 descrbes sample selecton and the SEO valuaton methodology. Secton 3 presents the valuaton results. Secton 4 presents the crosssectonal results wth respect to the announcement effects. Secton 5 presents long-run results and Secton 6 concludes. 2. Sample Selecton and SEO Valuaton Methodology 2.1. Sample Selecton Data on SEOs s obtaned from the Securtes Data Corporaton (SDC) database for the 1978 to 2000 tme perod. We start n 1978 to obtan suffcent number of SEOs per year for our sample and to ensure that our analyss does not suffer from any COMPUSTAT data back-fllng bases. 3

6 We stop n 2000 n order to be able to compute fve-year returns for our sample frms. For ncluson n our sample a SEO has to satsfy the followng crtera: a) The SEO should be of common stocks of US frms (share codes 10 and 11) lsted on NYSE, AMEX and NASDAQ. Unts, REITs, closed-end funds and ADRs are elmnated from the sample. The frms must be covered on Compustat (actve or research) and CRSP (Center for Research n Securty Prces) databases. b) SEOs should be a non-fnancal, non-utlty frm. We remove fnancals and utltes snce these frms ncentve to ssue equty (for example, banks may ssue equty to meet regulatory captal requrements) as well as the applcablty of multple based valuatons to these frms are not comparable to other frms. c) At least part of the SEO ssue should be prmary shares. In other words, 100% secondary ssues are removed n lne wth the earler lterature. d) The SEO should have an offer prce of at least $1. e) Further f a frm ssues multple SEOs wthn a fve-year wndow, we keep only the frst ssue n our sample. Subsequent ssues are dropped. Ths s n lne wth Loughran and Rtter (1995). We repeat the analyss wth these ssues ncluded n the sample and get smlar results. f) For meanngful valuatons we restrct our sample to frms wth postve EBITDA (tem 13 of Compustat) n the pror fscal year only. g) We should be able to fnd a seasoned matchng frm for the SEO frm based on the algorthm descrbed below. There are 1,967 SEOs satsfyng these crtera from 1978 to Our data requrements tend to elmnate many of the smaller SEOs. As a result, the magntude of the underperformance n our sample s lkely to be lower than that reported n the pror lterature. The SDC database also provdes flng dates, whch we use to compute announcement day returns. Snce the flng date s not avalable for all frms the sample sze for computng announcement effects falls to 1,561 frms. 3 3 Ths s consstent wth earler papers such as Jegadeesh, Wensten and Welch (1993). Usng Factva search, we checked the actual SEO announcement dates for a sub-sample of about 300 frms durng We fnd that 4

7 Summary statstcs on our SEO sample and matchng frms are provded n Table 1. The medan offer prce for SEO frms s $19.25, medan new shares offered as a percentage of pre-ssue shares outstandng s 17.11% and the medan pre-ssue market cap s $ MM. The medan sales of the SEOs n our sample s $82.11 mllon, medan EBITDA proft margn s 13.34%, medan net proft margn s 4.82% and medan sales growth rate s 24.02%. Thus, SEOs are frms wth hstorcally hgh growth rates and proft margns. The matchng frm sample, by desgn, has smlar characterstcs. The next secton explans the procedure for choosng matchng frms. 2.2 Choosng Industry Peers We choose ndustry peers followng the methodology outlned n Purnanandam and Swamnathan (2004). For each SEO n our sample, we fnd a non-seo ndustry peer wth comparable sales, EBITDA proft margn (as of pror fscal year) and sales growth that dd not ssue equty n the last three years. Sales growth s computed by takng the average of yearly sales growth of last three fscal years. As explaned n Purnanandam and Swamnathan (2004), matchng on ndustry allows us to fnd frms wth smlar operatng rsks. We use sales as a proxy for frm sze. EBITDA margn and past sales growth ensures fndng frms wth smlar proftablty and growth characterstcs. The objectve s to fnd a non-seo matchng frm that s as close as possble to the SEO frms n operatng characterstcs that determne a frm s value. We use EBITDA proft margn nstead of net proft margn n order to maxmze the sample sze snce many frms that have negatve net proft margn mght stll have postve EBITDA proft margn. EBITDA proft margn s also lkely to be a more robust measure of a frm s proftablty than net proft margn, whch s nfluenced by non-operatng tems that tend to be more volatle. The same logc apples to usng sales growth nstead of growth n earnngs or EBITDA. We elmnate from the unverse of potental matchng frms the followng: (a) frms that went publc durng the past three years, (b) frms that ssued seasoned equty n the past three years, (c) frms that are not ordnary common shares, (d) REITs, closed-end funds and ADRs and (e) 90% of SEOs made ther announcements on the same day as ther flng dates. Out of the remanng, the majorty made announcements a day before the flng date. We conduct our announcement-day returns analyss usng both 3- day and 5-day event wndows to make sure that we are able to capture the actual announcement date n our event wndow. 5

8 frms wth stock prce less than fve dollars as of the pror June or December, whchever s later. The remanng frms are grouped nto 48 ndustres usng the ndustry classfcatons n Fama and French (1997), whch are constructed, by groupng varous four-dgt SIC codes (obtaned from CRSP as of the end of the pror calendar year). We group frms n each ndustry nto three portfolos based on past sales and then each portfolo based on sales nto three portfolos based on past EBITDA proft margn (defned as EBITDA/Sales). Wthn each Sales-EBITDA group we fnd the frm wth a sales growth that s closest to the SEO frm. If there s nsuffcent number of frms n an ndustry, we lmt ourselves to a 3 by 2 or a 2 by 2 classfcaton. Each year almost all frms n our sample get unque matchng frms. There are some cases where the same matchng frm may be chosen for more than one SEO frm. We value SEOs based on the prce multples of these matchng frms. The valuaton methodology s descrbed n the next secton. 2.3 SEO Valuaton Usng Prce Multples For each SEO frm, we compute a prce-to-value (P/V) rato where P s the SEO offer prce and V s the far/ntrnsc value of equty computed from comparable frm s equty or enterprse value multples and SEO frm s sales, EBITDA, or earnngs. We use prce-to-sales (P/S), (P/EBITDA), (P/E), (P/E fwd ), (TEV/Sales), (TEV/EBITDA), and (TEV/EBITDA fwd ) as our multples. E fwd s the consensus analyst forecast of next year s earnngs. TEV s total enterprse value computed as Book value of nterest bearng debt + Book value of preferred stock + Market Value of equty Cash, short-term nvestments and marketable securtes. EBITDA fwd s an estmate of forecasted EBITDA computed as E fwd + pror fscal year s dfference between EBITDA and net ncome, (EBITDA E) pror fscal year. The assumpton s that pror year s numbers are the best forecast of next year s numbers. Prce-to-Value (P/V) rato usng prce multples The P/V rato for the SEO s estmated as the rato of the SEO offer prce multple to the comparable frm s prce multple. The offer prce multples for SEOs are computed as follows: P F SEO Offer Prce (Begnnng shares outstandng + Prmary shares offered n the SEO) = (1) Pror Fscal Year Accountng Fundamentals 6

9 where Begnnng shares outstandng s the CRSP shares outstandng as of the week pror to the SEO offer date. The prmary shares offered n the SEO s obtaned from the SDC database. F stands for accountng fundamentals: Sales, EBITDA, and tralng or forecasted earnngs (net ncome before extraordnary tems). All accountng nformaton s for the fscal year endng at least 3 months pror to the offer date. Analyst forecasts are as of the pror month. The prce multples for matchng frms are computed n a smlar manner: P F Match = Market prce CRSP Shares outstandng Pror Fscal Year Accountng Fundamentals (2) The comparable frms stock prces and shares outstandng are as of the week pror to the SEO offer date. The P/V rato for the SEO frm s computed as follows: P V F = ( P F ) SEO ( P F ) Match (3) Prce-to-Value (P/V) rato usng enterprse value multples In ths case, we frst compute the mpled TEV of SEO frm by multplyng the TEV/F rato of the matchng frm wth F of SEO frm. TEV stands for total enterprse value and s defned as market value of equty plus book value of nterest bearng debt plus book value of preferred stocks mnus cash. Cash conssts of cash, marketable securtes and short-term nvestments. The market value of equty of the matchng frm s the product of market prce and shares outstandng as of the week pror to the SEO offer date (see equaton 2). From the mpled TEV of SEO frms, we subtract the book-value of debt and book value of preferred equty, and add cash to get the mpled value of the frm s equty. P/V rato s computed as the rato of SEO frm s market value based on offer prce to the mpled value of the frm s equty as follows: P V F Offer Prce x (Begnnng shares outstandng + Prmary shares offered n the SEO) = TEV x FSEO (BV of Debt + BV of preferred- equty Cash) SEO F Match 7

10 The TEV based models account for leverage of the frm as well. For all valuaton ratos, we requre the mpled value to be postve. For example, the TEV-based value of equty of a frm can be negatve f mpled TEV of the SEO frm s less than the (BV of debt + BV of preferred equty Cash). We drop such observatons from the sample. Fndng a dfferent matchng frm for these SEOs, such that the mpled value s postve, provdes smlar result. 3. SEO Valuaton Table 2 presents the medan P/V ratos based on varous equty multples and enterprse value multples for each year from 1978 to The results show that, overall, SEOs are overvalued at the offer relatve to ther ndustry peers by 15% to 90% dependng on the multples used to perform the valuaton. The least overvaluaton (15%) s obtaned usng the prce-to-earnngs multple (P/E) fwd whch s based on consensus analyst forecasts of next year s earnngs. Usng analyst forecasts of earnngs, however, reduces the sample sze by almost half snce not every SEO frm s covered by securty analysts. The most overvaluaton (87%) s obtaned usng TEV/Sales multple. The overvaluaton s farly robust over tme. Even wth the (P/E) fwd multple the medan SEO s overvalued n sxteen out of 23 years. Wlcoxon rank sum tests strongly reject the null hypothess that the medan P/V ratos are equal to 1. The annual medans also reveal a sgnfcant upward trend n the medan P/V ratos durng the second half of the 1990s, when the US stock market experenced sgnfcant double-dgt gans (see Fgure 1 for an annual plot of P/V ratos based on P/EBITDA multple). Next, we show that our results are not specfc to the specfc methodology we used to choose comparable frms. We consder the followng alternate procedures of choosng comparable frms: Match on sales and EBITDA proft margn Match on sales, EBITDA margn, and analyst consensus long-term growth forecasts Match on sales and hstorcal sales growth Match on sales and analyst consensus long-term growth forecast 8

11 The valuaton results from the alternate matchng procedures are presented n Table 3. The results mrror the fndngs n Table 2 and show that the overvaluaton result s not drven by a specfc matchng procedure. The results ndcate that the medan SEO s overvalued by 7% to 95% dependng on the matchng procedure used. As n Table 2, the least overvaluaton s obtaned when usng prce-to-forward earnngs multple whch, of course, leads to a loss of half of the sample due to the lmted avalablty of analyst earnngs forecasts. Overall, the overvaluaton results n Tables 2 and 3 are consstent wth the long-run underperformance of SEOs reported n the lterature. However, these results are based on aggregatng all SEOs and do not examne the cross-sectonal relatonshp between P/V ratos, announcement day effects and long-run returns. In the followng sectons, we examne such cross-sectonal relatonshps whch can shed lght on the underreacton hypothess and the rsk vs. msprcng explanatons of the long-run underperformance of SEOs. To save space, n the rest of the paper, we present our results based on P/V rato computed usng TEV/EBITDA multple of an ndustry peer chosen based on sales, EBIDTA margn and hstorcal sales growth. We choose ths measure snce TEV approach takes nto account leverage and EBITDA s a farly clean measure of cash flows generated by the frm. 4. SEO Valuaton and Announcement Effects SEOs experence a declne n market value on the announcement day. The most popular explanaton for ths declne s based on Myers and Majluf (1984) accordng to whch the SEO announcement reveals the managers prvate nformaton, that the frm s overvalued, to the nvestors. In an effcent market, nvestors ratonally lower the frm s market value to ts ntrnsc value. The effcent market explanaton suggests that the more overvalued a SEO frm s, the larger should be the declne n ts stock prce on the announcement day. In contrast, the underreacton hypothess suggests that the more overvalued frm should experence a smaller declne n stock prce on the announcement day (under-react more) and a larger (more delayed) declne n the long run. In ths secton, we focus on the short-run announcement effects. In Secton 5, we examne the long-run returns. 9

12 In order to examne the relatonshp between P/V ratos and announcement day returns, we construct three portfolos of SEOs based on ther P/V ratos as follows. At the begnnng of each month, from 1980 to 2000, we construct a cross-sectonal dstrbuton of P/V ratos of frms that ssued seasoned equty durng the pror 24 months. 4 SEOs whose P/V ratos are below the 40 th percentle of ths dstrbuton are termed Low P/V, SEOs whose P/V ratos are above the 60 th percentle are termed Hgh P/V and the rest are termed Medum P/V. Ths procedure ensures that there s no look-ahead bas n the constructon of the three portfolos. It also ensures that there s no calendar tme clusterng n the membershp of the portfolos. Each annual cohort of SEOs s dstrbuted across the three portfolos roughly based on the percentle dstrbuton. Table 4 presents the average and medan announcement day returns for the three SEO portfolos. Note that the sample sze s smaller n ths table because the flng date s not avalable for all SEO frms. The results show that hgh P/V SEOs experence a smaller declne n market value compared to low P/V SEOs on the announcement day. The 3-day mean CAR (5-day CAR) for hgh P/V SEOs s -1.55% (-1.39%) whle the 3-day CAR for low P/V SEOs s -2.46% (-2.65%). The dfference n announcement day returns between hgh P/V and low P/V SEOs s 0.90% for the 3-day wndow and 1.26% for the 5-day wndow. These dfferences are both economcally and statstcally sgnfcant and ndcate a postve relatonshp between P/V ratos and announcement day effects. The postve relatonshp s nconsstent wth the predcton of Myers and Majluf (1984) snce ther model would predct the most overvalued SEOs to experence the largest declne n market value on the SEO announcement day. In contrast, the results n Table 4 ndcate that the most overvalued SEOs experence the smallest declne n market value on the announcement day. Ths s more consstent wth the underreacton hypothess. The results n Table 4, however, provde only a unvarate test of the relatonshp between P/V ratos and announcement day returns. Wll ths relatonshp hold once we drectly control for past growth rates and other frm characterstcs? We examne ths ssue usng the followng crosssectonal regresson: 4 SEOs n 1978 and 1979 are used to construct the ntal dstrbuton. 10

13 R(AnnDay) = a + b LnPV + c LnBM + d LnGrowth + e Accruals + f LnSales + g EBITDA Margn + u (4) The ndex refers to the SEO frm/event. R(AnnDay) s the VW market adjusted three-day cumulatve abnormal returns around the flng/ announcement date. LnPV s the natural log of offer prce-to-value rato. All accountng varables used n the above regressons come from the most recent fscal year of the SEO frm endng at least three months pror to the offer-date. LnBM s the natural log of book-to-market rato where book s the book value of equty (COMPUSTAT tem number 60) for the fscal year just before the SEO date and market s the market value of equty a day before the offer-date. LnGrowth s the natural log of (1+consensus analyst earnngs growth rate for the SEO) or (1+hstorcal sales growth rate). Hstorcal sales growth s taken as the average year-to-year sales growth computed over the past three years. The Accruals varable s the rato of accruals to total assets based on the most recent fscal year before the offer-date. Ths varable s constructed from the statement of cash flows for fscal years after 1987 and from the balance sheet data for the earler perod. Usng the cash flow statement, we construct accrual varable as Income Before Extraordnary Items (tem 123) mnus Cash Flows from Operatons (tem 308 mnus tem 124). For the earler perod, we construct the accrual varable as Change n Current Assets ( 4) mnus Change n Cash ( 1) mnus Change n Current Labltes ( 5) plus Change n Debt ncluded n Current Labltes ( 34) plus Change n Income Tax Payable ( 71) mnus Deprecaton & Amortzaton (14). The accrual varable s scaled by the average of begnnng and year-end total assets (tem 6). LnSales s the log of sales (tem 12) for the pror fscal year and s used as a control for sze. EBITDA Margn (tem 13 dvded by 12) s computed for the same fscal year as the LnSales varable. We estmate regresson (4) wth and wthout growth to examne the effect of growth rates on the relatonshp between P/V ratos and announcement-day returns. The regresson s estmated both as a pooled tme-seres-cross-sectonal regresson and usng the Fama-MacBeth cross-sectonal regresson approach where we estmate a cross-sectonal regresson for each annual cohort of SEOs. In the pooled regressons, the numbers n parentheses are Whte heteroskedastcty 11

14 corrected t-statstcs. In the Fama-MacBeth regressons, the numbers n parentheses are smple t- statstcs. Panel A of Table 5 presents the results from the cross-sectonal regressons. The results reveal an economcally and statstcally sgnfcant postve relatonshp between P/V ratos and announcement day returns confrmng that SEOs wth hgh P/V ratos declne less on the SEO announcement. In contrast, B/M ratos have mxed sgns and are statstcally nsgnfcant. Announcement day returns are postvely correlated wth growth rates suggestng that hgh growth frms are lkely to experence a smaller declne n market value on the announcement day. The relatonshp, however, s not statstcally sgnfcant. The other varables, accruals, sales, and EBITDA margn are not sgnfcantly related to announcement day returns. The varable that best explans announcement day effects s the P/V rato based on the offer prce. Note, however, that the P/V rato s based on offer prce, whch s set well after the SEO announcement day. Ths could gve rse to an endogenety bas f the market reacton to the SEO announcement helps determne the SEO offer prce. In other words, f a less negatve prce reacton causes the SEO frm to set a hgher offer prce, possbly because the frm nterprets the less negatve reacton as an affrmaton of ts growth and captal expendture strategy, ths could gve rse to the postve relaton between P/V ratos and announcement day returns. To address ths concern, we compute an alternate P/V rato based on the market value of the SEO frm the day before the flng date (nstead of the market value based on the SEO offer prce) and estmate the cross-sectonal regresson (n equaton 4) usng ths alternate measure. The results from these regressons, provded n Panel B of Table 5, confrm the fndngs n Panel A of Table 5. The most overvalued SEOs experence the smallest declne n ther market value on the announcement day. In our dscusson so far, we have nterpreted the postve relatonshp between P/V ratos and announcement day returns as beng more consstent wth the underreacton hypothess. However, there s an alternate scenaro n whch the smaller declne n market value observed for hgh P/V SEOs can be consstent wth effcent markets. Table 4 shows that the sales of hgh P/V SEOs grew at about 22% n the pror year whle those of the low P/V SEOs grew at a rate of only about 12

15 16% ndcatng a postve correlaton between P/V ratos and past growth rates. In the context of Myers and Majluf (1984), f nvestors nterpret past hgh growth rates as an ndcaton of superor frm qualty,.e., a greater lkelhood that a frm possesses postve NPV projects, then they are less lkely to punsh such frms on the announcement of a SEO. They would nterpret the SEO as a legtmate acton on the part of the frm to rase captal to nvest n postve NPV projects and not as opportunstc ssuance of overvalued equty. On the other hand, f past hgh growth rates are not sustanable n the future and are poor ndcators of whether a frm possesses postve NPV projects, then the smaller declne experenced by hgh P/V SEOs would be an underreacton to the SEO announcement. One way to dfferentate between these two cases s to examne long-run returns. In the case of ratonal reacton, P/V ratos would not be related to long-run abnormal returns. In the case of underreacton, P/V ratos would be negatvely related to long-run abnormal returns. Thus, the underreacton hypothess requres not only a showng that the most overvalued SEOs experence the least declne n market value on the announcement day but also that they contnue to declne n market value over the long-run. Ths s the essence of the underreacton hypothess: smaller declne than predcted by the effcent market hypothess ntally because nvestors do not revse ther cash flow expectatons down suffcently and contnung declnes over the long run as nvestors slowly realze ther mstake wth the arrval of addtonal nformaton. We examne ths ssue at depth n the next secton. 5. SEO Valuaton and Long Run Returns 5.1 Buy-and-hold abnormal returns (BHAR) Table 6 reports 5-year buy-and-hold abnormal returns for the three P/V portfolos. The returns are computed startng the day after the SEO ssue date and endng fve years after the ssue date or the delstng date whchever s earler. The abnormal returns are measured wth respect to three benchmarks: (a) NYSE/AMEX/NASDAQ value-weghted market ndex, (b) sze matched control frms (these are frms whose market captalzaton as of pror June or December, whchever s later, s closest to the market captalzaton of the SEO frm at close on the offer date) and (c) sze and B/M matched control frms. In addton to computng the tradtonal buyand-hold abnormal returns (BHAR), followng Purnanandam and Swamnathan (2004), we also 13

16 compute log buy-and-hold abnormal returns (LBHAR). The log buy-and-hold abnormal return s calculated as the dfference between the log buy-and-hold return of the SEO frm, log(1+r SEO ) and the log buy-and-hold return of the benchmark frm, log (1+R BM ). 5 Panel A of Table 6 presents tradtonal BHAR and Panel B presents LBHAR. The methodology for the constructon of Low, Medum, and Hgh P/V SEO portfolos s the same as that descrbed n Secton 4 (see Table 4). The results n Panel A show that n the long-run, hgh P/V SEO portfolos underperform low P/V SEO portfolos by 27% to 44% dependng on the benchmark used. In Panel B whch employs LBHAR, the underperformance ranges from 16% to 35%. The lower bound on underperformance s observed, not surprsngly, when abnormal returns are computed wth respect to sze and B/M matched control frms. The t-stats for equalty of means, whch are computed under the assumpton of ndependence and wth heterogeneous varances, reject the null of equalty strongly for sze and market benchmarks and margnally for sze and B/M benchmark. Whle these results provde support for the underreacton hypothess, these are unvarate fndngs that stll leave open the possblty that the P/V mght be an nstrument for other characterstcs such as growth and accruals that are related to the long-run underperformance of SEOs. 5.2 Cross-sectonal regressons We, therefore, turn to cross-sectonal regressons to examne the robustness of the relatonshp between P/V ratos and long-run SEO returns n a multvarate settng: R * = a + b LnPV + c LnBM f LnSales + g EBITDA Margn + d LnGrowth + u + e Accruals + (5) 5 Barber and Lyon (1997), argue aganst usng log (contnuously compounded) returns because log returns tend to yeld negatvely based estmates of long-run abnormal returns. However, snce there s no a pror reason that the bas should be dfferent for the low P/V and the hgh P/V portfolos, the bas s lkely to cancel out when computng the dfference n returns earned by the two portfolos. The advantage s that log returns mght provde a smple and easy way to control for the skewness problem. Also as expected, LBHAR exhbts much less skewness n each SEO portfolo and very lttle dsperson n skewness across portfolos compared to BHAR. 14

17 The ndex represents the SEO frm. R * s the long-run rsk-adjusted return for each SEO estmated as the ntercept from a Fama and French (1993) three factor regresson nvolvng ndvdual SEO monthly excess returns startng from the month followng the ssue date and endng fve years after the SEO month. Thus, R * represents the monthly average abnormal return whch tends to have better dstrbutonal propertes and s statstcally better behaved than buyand-hold abnormal returns. The ndependent varables are the same as those n equaton (4) and descrbed n Secton 4. We nclude analyst growth forecasts because La Porta (1996) has shown that stocks wth hgh analyst growth forecasts subsequently earn lower returns. We nclude B/M ratos because pror work suggests they are related to the cross-secton of stock returns. We nclude accruals because Teoh, Welch, and Wong (1998) fnd SEOs wth hgh accruals earn lower long-run returns. Pror fscal year sales are a proxy for frm sze and pror fscal year EBITDA proft margn a control for proftablty. We estmate regresson (5) usng both the pooled tme-seres cross-sectonal approach and the Fama-MacBeth cross-sectonal regresson approach. In the Fama-MacBeth approach, we estmate annual cross-sectonal regressons usng each annual cohort of SEOs from 1980 to 2000 and compute the tme-seres average of cross-sectonal slope coeffcents. In the pooled approach, the standard errors are corrected for heteroskedastcty usng the Whte (1980) correcton. In the Fama-MacBeth approach, the standard errors are computed usng four Newey- West lags to correct for any autocorrelaton n the cross-sectonal slope coeffcents. The results n Table 7 show that P/V ratos are sgnfcantly negatvely related to long-run rskadjusted returns even after controllng for other characterstcs that are related to long-run returns. The relatonshp s robust n both the pooled regressons and the Fama-MacBeth regressons and s robust to the ncluson or the excluson of growth rates. The slope coeffcents are n the range of 0.17% to 0.39% per month, whch can be nterpreted as the return premum correspondng to P/V ratos. Among other varables, only growth rates and accruals bear a sgnfcant negatve relatonshp to long-run returns. B/M rato has the wrong sgn and s not sgnfcant. The strong negatve relatonshp between P/V ratos and long-run rsk adjusted SEO 15

18 returns s consstent wth the underreacton hypothess and nconsstent wth the effcent markets hypothess. 5.3 Monthly calendar-tme mult-factor regressons We provde addtonal evdence on the robustness of the relatonshp between P/V ratos and long-run SEO returns by estmatng mult-factor regressons nvolvng monthly calendar-tme returns of the low and hgh P/V SEO portfolos. The portfolo returns are computed as follows. Each SEO s allotted to one of three P/V portfolos startng from the month followng the offer date and s held for 60 months (or untl the delstng date whchever s earler) from the end of the offer month. At the end of the holdng perod, the SEO drops out of ts portfolo. The monthly portfolo return s the equal-weghted or value-weghted (based on begnnng of year market cap) average of returns of all stocks n the portfolos for each calendar month from the begnnng of 1980 tll the end of Calendar tme return regressons suffer from fewer msspecfcaton problems than the BHAR approach. Ths approach avods the autocorrelaton problems present n usng overlappng fveyear buy-and-hold returns, takes nto account the cross-correlaton among returns across clustered events, and presents the most relable test statstcs. On the other hand, these tests are not necessarly the most powerful n detectng abnormal performance (see Loughran and Rtter (2000)). Panel A of Table 8 presents results based on the Fama and French (1993) three-factor model. The equal-weghted hgh P/V portfolo earns statstcally sgnfcant negatve abnormal return of 0.35% a month or 4.20% per annum. The dfference between Low P/V and hgh P/V portfolos s 0.25% a month or 3% per annum whch s only margnally sgnfcant. The results based on value-weghted portfolos are stronger. Hgh P/V portfolo earns sgnfcant negatve abnormal return of 0.52% a month or 6.2% per annum. The dfference between low P/V and hgh P/V portfolos s a statstcally sgnfcant 0.57% a month or 6.8% per annum. Panel B presents results from a 4-factor model consstng of the momentum factor. The results are stronger. Now, the dfference between equally-weghted low and hgh P/V portfolos s 0.28% a month or 3.4% per annum and value-weghted low and hgh P/V portfolos s 0.68% a month or 8.2% per annum 16

19 both statstcally sgnfcant. Overall, the results based on calendar-tme portfolo regressons confrm that the hgh P/V SEOs underperform n the long-run. 6. SEO valuaton and return predctablty around quarterly earnngs announcements A ratonal explanaton of our long-run fndngs s that we do not have the rght model of expected returns for long-run returns. Thus, any underperformance we observe could be due to exposure to some unknown rsk factor. We address ths ssue by focusng on return predctablty around future quarterly earnngs announcements. Snce expected returns are unlkely to change sgnfcantly n the short-run, any predctablty n returns around earnngs announcement dates s more lkely due to expectaton errors. Specfcally, we expect overvalued (hgh P/V) SEOs to earn lower returns around future quarterly earnngs announcements compared to undervalued (low P/V) SEOs. Ths s because of the rratonally hgh cash flow expectatons for hgh P/V SEOs on the part of nvestors leadng nto the earnngs announcement. When actual earnngs are released, nvestors are negatvely surprsed leadng to a declne n stock prces, on average, mmedately followng the earnngs announcements. Panel A of Table 9 reports average cumulatve abnormal returns (CAR) wth respect to the NYSE/Amex/Nasdaq value-weghted market ndex around quarterly earnngs announcements over the next 6 quarters. Specfcally, the table provdes average returns over the next 6 quarters (Q1-Q6) and breaks up the results n to those over the next two quarters (Q1-Q2) and over quarters 3 to 6 (Q3-Q6). In order to ensure that the results are robust, the average returns are measured over two wndows: from day -1 to +1 around the earnngs announcement date, CAR (- 1, +1), and day -2 to +2, CAR (-2, +2). The results ndcate that overvalued SEOs do earn lower returns than undervalued SEOs around earnngs announcement days but only startng n quarter 3. We focus on the results based on CAR (-1, +1). Over the frst two quarterly earnngs announcements, hgh P/V SEOs do not underperform low P/V SEOs (the returns for low P/V, medum P/V, and hgh P/V SEOs are also not monotonc). Over the subsequent four quarterly earnngs announcements, however, hgh P/V SEOs underperform low P/V SEOs, on average, by a statstcally sgnfcant 0.64%. The results 17

20 ndcate that t takes at least a couple of quarters for nvestor expectatons to catch up wth the fundamentals. Next, we examne the relatonshp between P/V ratos and average CAR over the next sx quarters n a multvarate settng: AvgCAR = a + b LnPV + c LnBM f LnSales + g EBITDA Margn + d LnGrowth + u + e Accruals + (6) where AvgCAR s the average of CAR (-1, +1) over the next sx quarters and the ndependent varables are as descrbed n Sectons 4 and 5. The regresson s estmated as a pooled tmeseres-cross-sectonal regresson and the results are presented n Table 9. The results reveal a moderately sgnfcant negatve relatonshp between P/V ratos and returns around future quarterly earnngs announcement dates. The results also reveal a moderately sgnfcant negatve relatonshp between accruals and AvgCAR. None of the other characterstcs appear sgnfcantly related to AvgCAR even though growth s negatvely related to AvgCAR as expected. Overall, the results based on quarterly earnngs announcements provde strong support for the underreacton hypothess and ndcate that t s unlkely that mssng rsk factors could be a sole explanaton of our fndngs. 7. Operatng performance Fnally, we examne the future operatng performance of hgh, medum, and low P/V SEOs to rule out the possblty that the overvaluaton of hgh P/V SEOs s due to a mssng growth premum n our valuaton methodology. We consder ths unlkely because our valuaton methodology also matches on growth. Nevertheless, f SEO frms are expected to sustan hgh growth rates n the long-run and our methodology does not capture the expected hgh growth rates, t s possble that a frm mght appear overvalued even though t s not. 18

21 We focus on four measures of operatng performance: growth n sales, EBITDA return on assets (EBITDA/Total Assets), After-tax return on assets (Net Income/Total Assets), and accruals. Growth n sales s a measure of growth opportuntes, return on assets measures proftablty, and accruals measures earnngs qualty. We present both raw and ndustry-adjusted measures of operatng performance. To compute the ndustry adjusted measures, we frst classfy all COMPUSTAT-CRSP frms nto 48 Fama-French ndustres and compute the medan measure of the ndustry for the gven calendar year. The ndustry-adjusted measure of the SEO frm s gven by the dfference between the SEO frm s measure and ndustry medan. Table 10 presents medan operatng performance measures for low, medum, and hgh P/V portfolos. The results are reported startng two years pror to the ssue month and endng fve years after the ssue month. Year 0 represents fscal year endng at least 3 months pror to the SEO ssue month; Year -1 s the fscal year pror to Year 0 and Year 1 s the fscal year after Year 0. Panel A presents sales growth rates. Intally, n the frst 2 years after the ssue date, hgh P/V SEOs grow at a faster rate than low P/V SEOs. However, they are unable to sustan the ntal hgh growth rates for long. By Year 5, the growth rate reverts to that of the medan frm n the ndustry. On the other hand, as shown n Panels B and C, hgh P/V SEOs, consstently earn a lower return on assets than low P/V SEOs and also lower return on assets than the medan frm n the ndustry especally n Year 4 and Year 5. Furthermore, n the frst two years after the SEO, as shown n Panel D, the accruals of hgh P/V SEOs are hgher than that of the low P/V SEOs. What ths suggests s that the hgh P/V SEOs delver hgh growth n the short-run at the cost of poorer earnngs qualty. In other words, they are not successful n convertng ther hgh growth rates to hgh cash flows whch s what ultmately determnes value. Overall, the results n Table 10 effectvely rule out the argument that the estmated overvaluaton of hgh P/V SEOs s due to a mssng growth premum. 8. Concluson The results n ths paper show that the market underreacts to SEO announcements. Overvalued SEOs experence a smaller declne n market value on the SEO announcement day but experence a larger declne over the next 5 years. Ths s nconsstent wth Myers and Majluf (1984) whch suggests hgher qualty frms (mplyng frms wth hgher growth opportuntes and 19

22 postve NPV projects) should experence a smaller declne on the SEO announcement day. Ths s because for ths to be the case, hgh P/V SEOs should not underperform n the long-run and also should exhbt superor operatng performance. Our evdence showed that hgh P/V SEOs do underperform n the long-run and do not face superor operatng performance. Overall, our results are consstent wth a market n whch nvestors overreact to past performance and underreact to the SEO announcement n determnng the valuaton of SEO frms. 20

23 References Barber, Brad M., and John D. Lyon, 1997, Detectng long-run abnormal stock returns: The emprcal power and specfcaton of test-statstcs, Journal of Fnancal Economcs 43, Barbers, Ncholas, Andre Shlefer, and Robert Vshny, 1998, A model of nvestor sentment, Journal of Fnancal Economc, 49, Bhojraj, Sanjeev, and Charles M. C. Lee, 2001, Who s my peer? A valuaton-based approach to the selecton of comparable frms, Cornell Unversty Workng Paper. Danel, Kent, Davd Hrshlefer, and Avandhar Subrahmanyam, 1998, A theory of overconfdence, self-attrbuton, and securty market under- and overreactons, Journal of Fnance 53, Eckbo, E., R. Masuls and O. Norl, 2000, Seasoned publc offerngs: resolutons of the new ssue puzzle, Journal of Fnancal Economcs 56, Fama, Eugene F., and Kenneth R. French, 1993, Common rsk factors n the returns on stocks and bonds, Journal of Fnancal Economcs 33, Fama, Eugene F., and Kenneth R. French, 1997, Industry costs of equty, Journal of Fnancal Economcs 43, Fama, Eugene F., 1998, Market effcency, long-term returns, and behavoral fnance, Journal of Fnancal Economcs 49, Hansen, Lars P., and Robert J. Hodrck, 1980, Forward exchange rates as optmal predctors of future spot rates: An econometrc analyss, Journal of Poltcal Economy 88, Hong, Harrson, and Jeremy C. Sten, 1999, A unfed theory of underreacton, momentum tradng and overreacton n asset markets, Journal of Fnance 54, Jegadeesh, N., M. Wensten, and I. Welch, 1993, An Emprcal nvestgaton of IPO returns and subsequent equty offerngs, Journal of Fnancal Economcs 34, La Porta, Raphael, 1996, Expectatons and the cross-secton of stock returns, Journal of Fnance 51,

24 Loughran, T., and J. R. Rtter, 1995, The new ssues puzzle, Journal of Fnance 50, Myers, S. and N. Majluf, 1984, Corporate fnancng and nvestment decsons when frms have nformaton that nvestors do not have, Journal of Fnancal Economcs 13, Newey, Whtney K., and Kenneth D. West, 1987, A Smple, postve sem-defnte, heterokedastcty and autocorrelaton consstent covarance Matrx, Econometrca 55, Purnanandam, Amyatosh and Bhaskaran Swamnathan, 2004, Are IPOs really underprced?, Revew of Fnancal Studes 17, Spess, Katherne D., and John Affleck-Graves, 1995, Underperformance n the long-run stock returns followng seasoned equty offerngs, Journal of Fnancal Economcs 38, Teoh, S. H., Ivo Welch, and T.J. Wong, 1998, Earnngs management and the post-ssue underperformance n seasoned equty offerngs, Journal of Fnancal Economcs 50, Whte, H., 1980, A Heteroscedastcty Consstent Covarance Matrx Estmator and a Drect Test for Heteroscedastcty, Econometrca, 48,

25 3.00 Medan P/V rato based on TEV/EBITDA multple P/V Year Fgure 1: Ths fgure plots relatve P/V ratos based on TEV/EBITDA multple from 1978 to 2000.

26 Table 1 Descrptve Statstcs Ths table presents the descrptve statstcs for our sample of 1967 SEOs durng Market captalzaton denotes the market value of frm s equty (shares outstandng x market prce) as of the tradng day just before the ssuance of new equty. Shares Offered represents the number of new shares ssued n the SEO as a percentage of the pre-ssue outstandng shares of the frm. SEO and matchng frm characterstcs provde key accountng nformaton about the SEO and matchng frm. Matchng frm s a non-ssung frm n the same Fama-French ndustry group wth smlar sales, EBITDA (earnngs before nterest, taxes, deprecaton and amortzaton) proft margns and sales growth rate. Sales, EBITDA and Net Profts come from COMPUSTAT data tems 12, 13 and 18 respectvely. These numbers are based on the most recent fscal year as of the equty ssuance date. Sales Growth s computed by takng the average year-by-year sales growth of the past three years. Varable Mean Medan Offer Prce ($) Pre-ssue Market Cap. (mn $) Shares Offered 20.99% 17.11% SEO Characterstcs Sales (mn $) EBITDA/Sales 16.27% 13.34% Net Profts/Sales 4.95% 4.82% Sales Growth Rate 61.29% 24.02% Matchng Frm Characterstcs Sales (mn $) EBITDA/Sales 15.98% 12.80% Net Profts/Sales 5.86% 5.01% Sales Growth Rate 27.21% 17.94%

27 Table 2 Yearly Dstrbuton of P/V Ratos Ths table reports the medan offer prce-to-value (P/V) ratos for SEOs from 1978 to In Panel A, the value s the far value of the ssung frm based on market prce-to-sales (P/S), prce-to-ebitda, prce-to-earnngs (P/E), and prceto-forward earnngs ((P/E) fwd) rato of an ndustry peer. In Panel B, the far value s computed usng total enterprse value-to-sales (TEV/S), TEV-to-EBITDA and TEV-to-forward EBITDA ratos. TEV s defned as the sum of the value of frm s equty, preferred equty, and debt mnus the cash balances. Industry peer s a comparable publcly traded nonssung frm n the same Fama and French (1997) ndustry as the SEO frm and has the closest sales, EBITDA proft margns (EBITDA/Sales) and sales growth n the most recent fscal year. EBITDA s the sum of earnngs before nterest and taxes (EBIT) and deprecaton and amortzaton (DA) and represents the operatng cash-flows. Sales Growth s computed by takng the year-by-year average of last three years sales growth. In Panel A, P/V s the rato of offer prceto-sales, offer prce-to-ebitda and offer prce-to-earnngs (current and forward) of the SEO frms dvded by the correspondng multples of the comparable frm. The forward EPS represents the analyst s consensus estmate of the earnngs per shares of the ssung company n the next fscal year. The forward EBITDA s based on forward earnngs and hstorcal nterest expenses and deprecaton and amortzaton and s computed usng a bottom-up approach. Ths nformaton s obtaned from the I\B\E\S. In Panel B, P/V rato s computed as the rato of ssung frm s market captalzaton based on the offer-prce to ts value based on the TEV/Fundamental based multple of ndustry peer. We provde the medan P/V rato for every year n our sample perod along wth the number of observatons used n computng these ratos. The p-value represents the Wlcoxon rank sum test for medan equal to 1. Pooled represents the aggregate sample of SEOs across the years. Panel A P/Sales P/EBITDA P/E (P/E) fwd Year NOBS Medan p-value NOBS Medan p-value NOBS Medan p-value NOBS Medan p-value Pooled