The Performance of Seasoned Equity Issues in a Risk- Adjusted Environment?

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1 The Performance of Seasoned Equy Issues n a Rsk- Adjused Envronmen? Allen, D.E., and V. Souck 2 Deparmen of Accounng, Fnance and Economcs, Edh Cowan Unversy, W.A. 2 Erdeon Group, Sngapore Emal: d.allen@ecu.edu.au Keywords: Seasoned equy ssues, rsk adjused performance, long-erm. EXTENDED ABSTRACT We show ha frms ssung seasoned equy possess unque rsk characerscs as capured by bea. We use a benchmark o conrol for hs rsk and hen measure he exen of rsk-adjused underperformance usng a longer me-frame han he fve-year perod used n mos sudes. We examne he mpac of varous facors on pos-ssue performance as well as nal ssue underprcng. Why do companes makng seasoned equy offerngs (SEOs) sgnfcanly under-perform n he pos-ssue perod? Loughran and Rer (997) suggesed ransory over-prcng pror o ssue, or agency and nformaon coss, Healy and Palepu (990) and Masuls and Korwar (986). Rangan (997) and Teoh, Welch and Wong (997) suggesed manageral prce rampng. Are SEOs poor long-run performers? Masuls and Korwar (986) documened sgnfcan underperformance of companes ssung new equy, subsequenly confrmed by Asquh and Mullns (986), Mkkleson and Parch (986) and Schpper and Smh (986). Loughran and Rer (995), exended Healy and Palepu (990), Rer (99) and Loughran, Rer and Rydqvs s (994) work n he area of nal publc offerngs (IPOs), examnng he performance of SEO frms. They observed 5.7% and 33.4% fveyear holdng perod reurns for IPOs and SEOs when he reurns on non-ssung frms mached by capalsaon were 66.4% and 92.8%. Loughran and Rer (995) concluded an nvesor would have had o nves 44 percen more money n he ssuers han n non-ssuers of he same sze o have he same wealh fve years afer he offerng dae. Loughran and Rer (997) sugges possble wndows of opporuny, perods durng whch frms are sgnfcanly overvalued provdng an opporuny o augmen fnancal slack. Allen and Souck (999) sugges he concluson of longrun underperformance s dependen on he defnon of he long-run. 835

2 . INTRODUCTION Allen and Souck (999) repored a sgnfcan relaonshp beween a companes bea and he exen of pos-ssue underperformance. Ths paper nvesgaes hs relaonshp and reassesses facors affecng pos-ssue performance whls conrollng for rsk. We fnd ha ssuers excess reurns are conssen wh prevous sudes SEOs under-perform sgnfcanly followng he offerng, reverse her performances around he fourh year o acually ouperform non-ssuers emporarly bu hs ranslaes no cumulaed under-performance over he medum as well as long erm. The remander of hs paper s srucured no four secons. We revew our research objecves n secon 2 and descrbe he mehodology and daa sources used n secon 3. Our resuls follow n secon 4, whls secon 5 concludes. 2. RESEARCH OBJECTIVES We conrol for he effec of rsk n SEO performance measures and re-examne wheher he ssuers n our sample acually do under-perform wh respec o a non-ssuer benchmark ha specfcally conrols for company beas. We adop: Hypohess : Frms ssung seasoned equy do no under-perform relave o correspondng nonssuers. Hypohess 2a: SEO frms do no crossover from a perod of under-performance o a perod of overperformance relave o non-ssuers. Hypohess 2b: SEO frms do no under-perform non-ssuers, n aggregae, over he exended longrun. When parng ssuers wh non-ssung frms we examne frms age, marke capalsaon, year of ssue and he annual volume of SEO ssues. We regress he performance resuls on he company bea self o confrm he effecveness of our adjusmen for hs facor. Hypohess 3a: The exen of bea-adjused SEO underperformance s no a funcon of age. Hypohess 3b: The exen of bea-adjused SEO underperformance s no a funcon of bea. Hypohess 3c: The exen of bea-adjused SEO underperformance s no a funcon of marke capalsaon. Hypohess 3d: The exen of bea-adjused SEO underperformance s no a funcon of he chronologcal arbue of he ssue. Hypohess 3e: The exen of bea-adjused SEO underperformance s no a funcon of volume of seasoned equy offerngs n he year of ssue. We examne he relaonshp beween he openng reurn and he subsequen rsk-adjused underperformance. Hypohess 4a: SEO frms do no record sgnfcan openng reurns. Hypohess 4b: The exen of SEO underperformance s no a funcon of he sze of nal reurns. 3. RESEARCH METHOD 3.. Daa The raw sample consss of 37 seasoned equy offerngs made beween January 984 and Ocober 993; permng a leas fve years of prce daa for each SEO company n he sample (leadng up o 998). The SEOs mus mee he followng crera: () he company s lsed on he Ausralan Sock Exchange and recorded n he DaaSream Daabase a he me of he ssue, (2) he offer mus be a cash offer for common sock, (3) he book value of asses a he end of he fscal year of ssung mus be a leas $5 mllon n 990 purchasng power and (4) he company underakng he SEO s no a fnancal company or a regulaed uly. In he fve year we remove all ssues by he same company made whn fve years afer he SEO o avod a perod overlap bas. Ths causes a deleon of 35 SEOs from he sample, leavng a oal of 02 ssues made by 94 companes. To analyse long run performance we exend he me frame back o Ocober 986 nsead of 993 o allow for a leas 2 years of daa. Ths reduced he sample o 26 SEOs. Some 5 of hese companes had mulple ssues leavng a sample of 2 frms. Daa was aken from he DaaSream Daabase and crosschecked wh he Secures Daa Company (SDC) daabase. The dae of ncorporaon and he dae of lsng were obaned from he 998 Ausralan Sock Exchange Yearbook and he 998 Ausralan Sock Exchange Invesor Handbook

3 3.2. Mehod Choce of Performance Benchmarks PISS PBM riss = rbm = P P ISS BM A frs, a benchmark was esablshed agans whch he SEO performance would be measured. where frm on day P ISS, = closng prce of he SEO. In he mddle of each ssue year (defned as 30 June), all common socks lsed on he ASX ha have no made an ssue n he las fve years are ranked accordng o her marke bea. 2. Nex, for each ssung frm n he sample a non-ssuer s seleced from he ls ha has bea closes o he ssuer. If he sample frm has already he larges capalsaonhen a mach wh nex hghes marke value s seleced. Ths hen becomes a bea-and-sze mached non-ssuer benchmark. 3. If he non-ssuer becomes delsed before he end dae for he correspondng ssuer, a second (and f necessary hrd, fourh, ec.) machng frm s splced n afer he delsng dae of he frs machng frm Tme seres mehods Tme Defnons We defne each year as conssng of 2 monhs, each monh comprsng 2 radng days. Inal (or openng) reurn s calculaed over he frs radng day on whch he seasoned equy was ssued. Pos-ssue reurns are compued durng he perod followng he offer dae, e excludng he frs day. Three separae me frames are defned:. Shor erm Defned as 3 years followng he offer dae... Medum erm Defned as 5 years followng he offer dae. Long erm Defned as 2 years followng he offer dae. A welve year perod was chosen so as o be long enough for many of SEO s R&D and Capal Projecs o come o fruon hereby permng esng of Hypoheses 2a and 2b. Performance Measuremen We use Cumulave Abnormal Reurns (CAR) mehod o measure he performance of frms ssung seasoned equy. Raw daly reurns for ssuers and non-ssuers are frs calculaed as P BM, = closng prce of he benchmark non-ssung frm on day The abnormal reurn s hen calculaed as he raw reurn from he ssung frm mnus he reurn on he correspondng non-ssuer. Hence ar = riss, rbm Where r ISS, = Raw reurn for SEO on day r BM, = Raw reurn for non-ssuer benchmark frm on day The average abnormal reurn for he day across all SEOs s calculaed as he equally weghed arhmec average of he ndvdual abnormal reurns: AR = where n ar n = n = number of SEOs n he sample The CAR from he frs day afer he offerng unl day s calculaed as he sum of he daly average abnormal reurns unl. Hence CAR = AR d d = To es for he sgnfcance of he resulng cumulave abnormal reurn we use a modfed - sasc ha also accouns for he auocovarance ha may exs n he me seres: ( CAR ) = CAR n var+ 2 ( ) cov where var = average cross-seconal varance over he measuremen perod cov = frs-order auocovarance of he AR seres We also use holdng-perod reurn as an alernave measure of reurns: 837 3

4 b HPR a: b = ( + R, = a where ), R, = Raw reurn of frm on day a = Begnnng of he holdng perod b = End of he holdng perod The above formula wll be used o measure he oal reurns from a buy and hold sraegy n whch a sock s purchased a he frs closng marke prce afer lsng (a=) and held for he subsequen shor-erm (b=3 252=756), medum erm (b=5 252=260) and long erm (b=2 252=3024) perod Cross-seconal mehods In he cross-seconal analyss sage of our sudy we regress he reurns of SEOs (dependen varable) on a number of conrollng facors (ndependen varables): v. Year of Issue ( varable) ISSYR: he year n whch each ssue s made. v. Volume of SEOs n he ssue year (2 varables) TOTVOL = ln( SAMPVOL = + Ψ ln( TOT + Ψ ) SAMP The fnal elemen s o nvesgae he mpac of nal underprcng on he subsequen performance of he ssuer. The nal underprcng wll be R defned as = R RAOI, wh raw reurn (R ) esmaed usng four mehods: CORERT: Calculaes how deeply was each new share n he offer dscouned wh respec o he closng prce on he day of he ssue. P0 CORERT = IP ) CAR = α + β Ω + ε (unvarae) where P 0 = Closng prce on he day of he ssue (=0) CAR = α + β, Ω, + β2, Ω2, βn, Ωn, + ε IP = Subscrpon prce for each new share n (mulvarae) he SEO where CAR = Cumulave abnormal reurn of SEO for a fve year perod Ω = Conrol varable whose effec on SEO performance s beng measured α, β = Regresson coeffcens ABSRT: Compares he closng prce a he offer dae wh he closng prce on he day jus pror o he ssue. P ABSRT = 0 P ε = Regresson error erms. Age (2 varables) INAGE: Number of years from he me of SEO frm s ncorporaon n Ausrala. PUBAGE: Number of years from he me of SEO frm s lsng on an organsed sock exchange n Ausrala.. Company Bea ( varable) BETA. Marke Capalsaon ( varable) EQUITY calculaed marke value of he frm expressed n 990 dollars: DILRT: akes no accoun he proporon of new equy ssued wh respec o he equy n place pror o he offer. ( η + ) P DILRT = 0 η Po + IP where η = Rao a whch new equy s ssued. TOTRT: A holdng perod reurn for an nvesor who acqures he necessary number of shares (η) on he las day before he SEO, exercses he rgh o buy he exra equy, and sells a he close of he day of he ssue. EQUITY = ln( MV adj ) 838 4

5 ( η + ) P TOTRT = η P + IP 0 Each of he marke-adjused defnons of he nal reurns wll be regressed on he hree year and fve year CARs of he ssuers. 4. RESULTS 4.. UNIQUENESS OF BETA We examned wheher he bea-characerscs of SEO frms are unque relave o non-ssung frms. The beas of our SEO are compared wh he,06 frms lsed on he ASX for whch DaaSream currenly compues company beas. See he bea hsogram n Fgure I TIME SERIES PATTERNS usng RISK-adjused benchmark The cumulave abnormal reurns of SEOs observed usng he bea-and-sze mached benchmark are summarsed n Table I Par A, and graphcally presened n Fgure III Panel A. We also nclude me-seres resuls from Allen and Souck (999) where no explc adjusmen for bea has been made, presened as Panel B n Table I and Fgure III. The benchmarks used o form hese unadjused resuls are based on reurns from sze-only mached non-ssuers and ndusry-andsze mached non-ssuers drawn from he same sample. The underperformance s more profound when bea s conrolled for. Fgure II shows ha whle he populaon dsrbuon approxmaes normaly, our sample dsrbuon s skewed o he rgh and exhbs posve kuross. There are dfferences n rsk beween ssuers and non-ssuers. Fve years followng an ssue he cumulave CARs for sze-mached and ndusry-and-sze mached benchmarks sood a -5.03% (-0.95) and % (-2.28), respecvely, compared o he % (-5.06) CAR for he bea-adjused benchmark. The bea-adjused CAR s dramac durng he frs hree years, showng -93.6% (-4.9), and hen reduces n years four and fve. The resuls rejec Hypohess frms ha ssue seasoned equy do under-perform non-ssuers, especally when rsk s accouned for. The underperformance s very marked n he frs hree years, plaeaus n years four and fve and hen downurns agan n he eghh year. However, unlke he performance observed wh sze and ndusry adjused benchmarks, years sx and seven dd no record as sgnfcan an over-performance, and he downurn followng year egh perssed longer (unl year en) before he urnaround fnally emerged. Consequenlyhs leads o a much more economcally sgnfcan aggregae cumulave abnormal reurn of % (-2.28), alhough sascal sgnfcance a a 5% level s comparable o he oher benchmarks. Hypohess 2a canno be 839 5

6 exended long run perod, usng he bea-adjused benchmark. The resuls are summarsed n Par A of Table II and Fgure V, each accompaned by Par B whch hghlghs he fndngs for oher mached benchmarks. Hypohess 2a canno be rejeced as SEO frms do no cross over from a perod of under-performance o a perod of overperformance. We also rejec Hypohess 2b perod SEO frms do under-perform non-ssuers, n aggregae, over he exended long run Cross-Seconal Analyss usng Beaadjused benchmark rejeced gven SEO frms do no cross over from a perod of underperformance o a perod of overperformance. We rejecon Hypohess 2b SEO frms do under-perform non-ssuers, over he exended long run. Allen and Souck (999) sugges ha he long-run underperformance of SEOs was dependen on he defnon of he long-run. We rees he performance n he As a frs sep n he cross-seconal par of our analyss we regressed he fve-year bea-adjused CARs agans he seven conrol varables prevously defned; see resuls n Table III. None of hese varables are sascally nsgnfcan. We hen examned he openng gans for nvesors n he ssung companes, based on he four nalreurn defnons; see Table IV, all are hghly sgnfcan. underprcng has an mpac on he exen of pos-ssue underperformance ndependen of he rsk dfferenal beween ssuers and nonssuers The resuls fal o rejec Hypoheses 3a, 3c, 3d and 3e he exen of underperformance does no appear o be relaed o he ssuer s age, marke capalsaon, year of ssue or he volume of SEOs n he year of ssue. We fal o rejec Hypohess 3b 840 6

7 eroded, and SEOs have an aggregae loss n he medum (5 year) as well as long (2 years) erm. 6. REFERENCES Allen D.E., and Souck, 999, Long Run Underperformance of Seasoned Equy Offerngs: Fac or an Illuson?, Workng Paper, School of Accounng, Fnance and Economcs, Edh Cowan Unversy. Asquh P. and Mullns D., 986, Equy Issues and Offerng Dluon, Journal of Fnancal Economcs, 6-89 ASX, The Ausralan Sock Exchange Yearbook 998, Ausralan Sock Exchange, Sydney, 998 ASX, The Ausralan Sock Exchange Invesor Handbook, Ausralan Sock Exchange, 998 Ed., Brsbane, 997 (ha he relave performance s unrelaed o bea) Hypohess 4a s also rejeced by he resuls, hghlghng he sgnfcan openng reurns recorded by ssung frms. Fnally, we rejec Hypohess 4b; he exen of underperformance s relaed o he openng reurn. 5. CONCLUSION Our resuls are conssen wh prevous sudes. Issuers nally under-perform, bu hen urn around and acually ouperform non-ssuers on an annual bass. Ths mgh be arbued o he mauraon of capal and R&D projecs ha ssuers have aken up a a more rapd han nonssuers followng an SEO (Loughran and Rer, 997). As compeors cach up he advanage s Healy P.M. and Palepu K.G., 990, Earnngs and Rsk Changes Surroundng Prmary Sock Offers, Journal of Accounng Research, Loughran T., Rer J.R. and Rydqvs K., 994, Inal Publc Offerngs: Inernaonal Insghs, Pacfc-Basn Fnance Journal, Loughran T. and Rer J.R., 995, The New Issues Puzzle, Journal of Fnance, 23-5 Loughran T. and Rer J.R., 997, The Operang Performance of Frms conducng Seasoned Equy Offerngs, Journal of Fnance, December:

8 Masuls R. and Korwar A., 986, Seasoned Equy Offerngs: An emprcal nvesgaon, Journal of Fnancal Economcs, 9-8 Mkkleson W. and Parch M., 986, Valuaon Effecs of Secury Offerngs and he Issuance process, Journal of Fnancal Economcs, 3-60 Rangan S., 997, Earnngs Managemen and he Performance of Seasoned Equy Offerngs, Journal of Fnancal Economcs. Rer J.R., 99, The long-run performance of nal publc offerngs, Journal of Fnance, 3-27 Teoh S.H., Welch I. and Wong T.J., 997, Earnngs Managemen and he underperformance of Seasoned Equy Offerngs, Journal of Fnancal Economcs. Schpper K. and Smh A., 986, Comparson of Equy Caveas and Seasoned Equy Offerngs: Share Prce Effecs and Corporae Resrucurng, Journal of Fnancal Economcs, Spess D.K. and Affleck-Graves J., 995, Underperformance n long-run sock reurns followng seasoned equy offerngs, Journal of Fnancal Economcs, Welch I., 989, Seasoned offerngs, maon coss, and he underprcng of nal publc offerngs, Journal of Fnance,