William E. Simon Graduate School of Business Administration. IPO Market Cycles: Bubbles or Sequential Learning?

Transcription

1 Universiy of Rocheser William E. Simon Graduae School of Business Adminisraion The Bradley Policy Research Cener Financial Research and Policy Working Paper No. FR January 2000 Revised: June 2001 Forhcoming Journal of Finance IPO Marke Cycles: Bubbles or Sequenial Learning? Michelle Lowry Penn Sae Universiy G. William Schwer William E. Simon Graduae School of Business, Universiy of Rocheser This paper can be downloaded from he Social Science Research Nework Elecronic Paper Collecion: hp://papers.ssrn.com/paper.af?absrac_id=242755

2 Forhcoming THE JOURNAL OF FINANCE VOL?? 200? IPO Marke Cycles: Bubbles or Sequenial Learning? MICHELLE LOWRY and G. WILLIAM SCHWERT * ABSTRACT Boh IPO volume and average iniial reurns are highly auocorrelaed. Furher, more companies end o go public following periods of high iniial reurns. However, we find ha he level of average iniial reurns a he ime of filing conains no informaion abou ha company s evenual underpricing. Boh he cycles in iniial reurns and he lead-lag relaion beween iniial reurns and IPO volume are predominanly driven by informaion learned during he regisraion period. More posiive informaion resuls in higher iniial reurns and more companies filing IPOs soon hereafer. THE PHENOMENON OF "HOT IPO MARKETS" has been recognized for a long ime in he financial communiy. Ibboson and Jaffe (1975) and Ibboson, Sindelar, and Rier (1988, 1994) show ha here are pronounced cycles in he number of new issues per monh and also in he average iniial reurn per monh. Furher, here appears o be a lead-lag relaion beween he wo series. Figure 1 shows monhly IPO volume and iniial reurns beween 1960 and I seems ha periods of high and rising iniial reurns end o be followed by spurs of IPOs, which are hemselves followed by periods of lower iniial reurns. For example, he high iniial reurns of early 1961 were followed by large numbers of companies going public in lae 1961 and early 1962, and hen by especially low average iniial reurns in lae This paern is repeaed many imes over he 41-year period. Noably, neiher he saisical reliabiliy of hese lead-lag relaions nor he economics underlying hese paerns have been examined. Consequenly, we have lile undersanding of he facors ha drive hese flucuaions or of he implicaions of such phenomena for companies considering an IPO. As a firs sep oward undersanding hese paerns, we examine heir saisical significance. In conras o he impression given in Figure 1, saisical ess show only weak evidence of a negaive relaion beween IPO volume and fuure iniial reurns. However, consisen wih * Penn Sae Universiy, and Universiy of Rocheser and he Naional Bureau of Economic Research. An earlier version of his paper was iled IPO marke cycles: An exploraory invesigaion. The Bradley Policy Research Cener, William E. Simon Graduae School of Business Adminisraion, Universiy of Rocheser, provided suppor for his research. We are indebed o Jay Rier for he use of his daa. We received helpful suggesions from Harry DeAngelo, Craig Dunbar, Gregg Jarrell, Alexander Ljungqvis, Tim Loughran, Vojislav Maksimovic, Harold Mulherin, Jay Rier, Jerold Warner, Ivo Welch, Jerold Zimmerman, and seminar paricipans a he Universiy of Rocheser, MIT, and he Ausralasian consorium of universiies videoconference. We especially appreciae many helpful commens from Richard Green (he edior) and from an anonymous referee. The views expressed herein are hose of he auhors and do no necessarily reflec he views of he Naional Bureau of Economic Research. Michelle Lowry and G. William Schwer,

3 2 Forhcoming The Journal of Finance Figure 1, we find a significan posiive relaion beween iniial reurns and fuure IPO volume. I appears ha increased numbers of companies go public afer observing ha IPOs are being underpriced by he greaes amoun. As firs noed by Ibboson and Jaffe (1975), his paern is puzzling. Assuming ha firms prefer o raise as much money in heir IPO as possible, i would seem ha companies would prefer o go public when iniial reurns were he lowes. Having esablished he saisical significance of he posiive relaion beween iniial reurns and subsequen IPO volume, we ask wheher companies ha file IPOs during periods of especially high iniial reurns can hemselves expec o also be exremely underpriced. We also invesigae he specific facors ha lead increased numbers of companies o go public following periods of high iniial reurns. We firs analyze he relaion beween average iniial reurns a he ime a company files is IPO and ha company s evenual underpricing. We find ha he level of iniial reurns a he ime a company files o go public conains no informaion abou ha company s evenual underpricing. In fac, our resuls show ha he serial correlaion in iniial reurns is enirely driven by changes in he ypes of firms ha go public over ime and by informaion ha becomes available during he regisraion period bu is only parially incorporaed ino he offer price. Noe ha a firm canno conrol eiher of hese componens of is iniial reurn by filing he offering a a differen ime. Managers generally canno subsanially aler basic firm characerisics, such as size and indusry, meaning hey canno affec his componen of underpricing. Furher, a he ime he offering is filed, managers do no know wha informaion will become available during he regisraion period or how such informaion will affec he offer price. Thus, i seems ha a company canno affec he magniude of is underpricing by alering he iming of is IPO. To undersand why companies go public following periods of high iniial reurns, we look more specifically a he porion of iniial reurns o which IPO volume is relaed. We find ha he posiive relaion beween iniial reurns and subsequen IPO volume is driven by he informaion ha is learned during he regisraion period bu only parially incorporaed ino he offer price. In he process of markeing he IPO (afer he IPO has been filed), he firm and is underwriers glean informaion from informed invesors abou heir valuaion of his new firm. This informaion is a deerminan of boh he pricing of ha IPO, and also of he number of privae companies ha find i opimal o issue public equiy in he near fuure. More posiive informaion in he form of higher expeced valuaions resuls in higher iniial reurns and more companies filing o go public soon hereafer. In summary, a firs glance he cycles in iniial reurns and IPO volume presen wo puzzles. Firs, he serial correlaion in iniial reurns suggess ha underwriers ignore he marke s valuaion of recen IPOs in heir pricing of new offerings. Periods of high iniial reurns appear o represen avoidable bubbles, ha is, such periods could be avoided if he marke for underwriing services was more compeiive. Second, in spie of his serial correlaion, more companies choose o go public afer observing high average iniial reurns. I would seem ha companies could raise more money if hey filed heir offerings when average iniial reurns were low. Our findings address boh of hese apparen puzzles. Firs, we find ha he cycles in iniial reurns predominanly reflec invesmen bankers learning process. Because he regisraion periods of many IPOs overlap, he informaion ha underwriers learn during one firm s regisraion period conribues o he firs-day reurns of many IPOs, hereby causing iniial reurns o be serially correlaed. Second, while more companies go public following periods of

4 IPO Marke Cycles 3 high iniial reurns, his does no mean ha hey also will be especially underpriced. The level of iniial reurns a he ime a company files is IPO conains no informaion abou ha firm s evenual underpricing. Raher, we find ha more companies file IPOs following periods of high iniial reurns because he high reurns are relaed o posiive informaion learned during he regisraion periods of hose offerings, suggesing ha companies can raise more money in an IPO han hey had previously hough. The conclusion ha firms can raise more money immediaely afer a period of high iniial reurns is consisen wih Rier (1984). Secion I discusses he daa ha we use o examine he ime-series relaions in IPO volume and iniial reurns. Secion II invesigaes he saisical properies of he relaions beween IPO volume and pas and fuure iniial reurns. In Secion III, we examine he exen o which firms and/or heir underwriers manage he iming of he IPO process, condiional on he iniial reurns of oher firms going public. Secion IV invesigaes he facors ha conribue o iniial reurns, hus providing he foundaion for he analyses in Secions V and VI. In Secion V, we examine he relaion beween average iniial reurns a he ime a company files is IPO and ha company s evenual underpricing, and Secion VI invesigaes he reasons ha more companies go public afer observing especially high average iniial reurns. Secion VII describes he ouof-sample resuls for Finally, Secion VIII summarizes he resuls in he paper. I. Daa To sudy he behavior of aggregae IPO marke aciviy, we sar wih wo basic sources of daa on iniial reurns and volume. These daa are described below. Laer secions of he paper also employ firm-level iniial reurns, and hose daa will be described a ha poin. A. Daa Sources and Definiions The Ibboson, Sindelar, and Rier (ISR) daa [hp://bear.cba.ufl.edu/rier/ipoall.hm] include average, equal-weighed monhly IPO iniial reurns (IR EW ) and he number of IPOs per monh (NIPO ISR ). The exac sample composiion and he calculaion of iniial reurns differ somewha over he sample period, and a more complee descripion of he procedures used o calculae hese saisics is in Ibboson, Sindelar, and Rier (1994). In general, ISR s iniial reurns represen he average, across all IPOs each monh, of he percenage difference beween a closing price wihin he firs monh afer he IPO and he offer price. Each IPO is weighed equally, so ha IPOs of small firms have he same influence as IPOs of large firms. We also use daa on all firm-commimen IPOs offered or filed beween 1985 and 1997 from Securiies Daa Company (SDC). Uni IPOs, closed end funds, real esae invesmen russ (REITs), and American Deposiary Receips (ADRs) are excluded. These daa include he dae he IPO was filed wih he Securiies and Exchange Commission (SEC), he range of prices wihin which he company expecs o price he issue as indicaed in he preliminary or amended prospecus (file range), he dae each issue is offered or wihdrawn, he offer price, and he prices a he close of he firs day, second day, and firs week of rading. IPO volume is defined as he number of IPOs each monh (NIPO SDC ). We also measure he number of offerings filed per monh (NFIL ) and he number of offerings wihdrawn per monh (NWD ). 1 Finally, we 1 SDC records 48 wihdrawals in January 1990, compared o 4 wihdrawals he previous monh and 1 he subsequen monh. We srongly suspec ha his observaion is incorrec, so we omi i.

5 Monhly Percenage Reurn o IPOs IPO Volume, NIPO ISR IPO Iniial Reurns, IR EW Number of IPOs per Monh 4 Forhcoming The Journal of Finance Figure 1. Ibboson, Sindelar, and Rier s (1994) monhly daa on aggregae US iniial public offerings per monh (NIPO ISR ) and average iniial reurns o IPO invesors (IR EW ). Updaed on Jay Rier s web sie [hp://bear.cba.ufl.edu/rier/ipoall.hm] o cover he period January February 2001.

6 IPO Marke Cycles 5 calculae he average lengh of ime in regisraion, equal o he number of days beween he filing and offer daes, weighed by proceeds raised in he IPO (REGTIME PW ). For he SDC sample, we measure boh he iniial reurn and he price updae of each issue. The iniial reurn equals he percenage change beween he offer price and he firs closing price, weighed by proceeds raised in he IPO (IR PW ). To deermine he firs closing price of a paricular issue, he firs closing price from he Cener for Research in Securiies Prices (CRSP) is used if price daa are available wihin 14 days of he offer dae. If CRSP daa are no available, we ry o obain he closing price from SDC. The SDC closing price equals he close on he firs day of rading. If ha is no available, he close on he second day or oherwise he end of he firs week of rading is used. The price updae beween he iniial filing and he final offer is measured as he percenage difference beween he midpoin of he file range and he offer price. The average price updae for offers made in a paricular monh, weighed by proceeds raised in he IPO, is denoed P PW. B. Descripive Saisics Table I conains he mean, median, sandard deviaion, minimum, and maximum of he various daa series, along wih 12 auocorrelaions and he large sample sandard error of he auocorrelaions. Consisen wih he earlier findings of Ibboson and Jaffe (1975) and Ibboson, Sindelar, and Rier (1988, 1994), boh he number of IPOs and he average iniial reurns are highly auocorrelaed. Noe ha he number of observaions for iniial reurns is smaller han he sample size for he number of IPOs, since he iniial reurn is missing in monhs when no IPOs occur. In erms of he number of IPOs, in he period ISR's daa include more issues, bu he general characerisics of he alernaive measures NIPO ISR, NIPO SDC, and NFIL are similar. The number of issues wihdrawn (NWD) is small, and he ime in regisraion for offers ha occur averages 72.1 days. REGTIME is no highly auocorrelaed, indicaing ha he cyclical behavior of he number of IPOs is no he resul of variaion in regisraion imes. Raher, i appears o be driven by he number of companies filing and wihdrawing offerings each monh. Furher empirical ess suppor his proposiion. ISR's measure of iniial reurns (IR EW ) is higher on average and more volaile han he SDC measure of iniial reurns (IR PW ). This is mos likely driven by wo facors: firs, ISR s daa weigh small issues more heavily, and second, over pars of he sample period he ISR daa include bes effors offerings and uni offerings, boh of which end o have higher average iniial reurns. For he period, he auocorrelaions of proceeds-weighed iniial reurns are highes for he firs wo monhly lags. The auocorrelaions of equal-weighed iniial reurns from are larger and more persisen (decaying from.60 o.11 beween lags 1 and 12). The average proceeds-weighed price updae beween he iniial filing and he offering ( P PW ) is 3.6 percen, and he auocorrelaion is large a lag one, bu is small for higher order lags (less han.25 in absolue value for lags 2 hrough 12).

7 Table I Descripive Saisics for Aggregae IPO Reurns and Volume The mean, median, sandard deviaion, minimum, and maximum of he number of iniial public offerings per monh (NIPO) and he percenage iniial reurn o IPO invesors (IR). In general, he iniial reurn is he percenage reurn from he offer price o he closing price on he firs day of rading. Auocorrelaions for 12 lags ( 1 o 12 ) and heir large sample sandard error, under he hypohesis of no auocorrelaion, S( ), are also shown. The firs wo rows are from Ibboson, Sindelar, and Rier (ISR) from (IR EW and NIPO ISR ). Remaining rows of he able use daa from In addiion o he ISR daa, we use informaion from Securiies Daa Corporaion (SDC). NIPO SDC is he number of IPOs per monh, NFIL is he number of offerings filed per monh, and NWD is he number of offerings wihdrawn per monh. REGTIME PW is he average lengh of ime in regisraion, he number of days beween he file and offer daes, weighed by proceeds raised in he IPO. The average percenage reurn o issues offered in a paricular monh, IR PW, is weighed by proceeds raised in he IPO. Finally, here is a measure of he price updae ha occurs beween he iniial filing and he offer (i.e., he percenage difference beween he mid-poin of he iniial offer range and he final IPO price). P PW is he average percen price updae for offers made in a paricular monh, weighed by proceeds raised in he IPO. Mean Median Sd Dev Min Max Sample Size, T S( ) NIPO ISR IR EW Number of IPOs per Monh NIPO ISR NIPO SDC NFIL NWD Forhcoming The Journal of Finance Time in Regisraion in Days REGTIME PW Average Iniial Reurns IR EW IR PW Average Price Updaes beween Filing and Offer Daes P PW

8 IPO Marke Cycles 7 II. The Relaion Beween Volume and Iniial Reurns Before analyzing he deerminans of he lead-lag relaion beween IPO volume and iniial reurns, i is helpful o review he exising evidence on he deerminans of he flucuaions of IPO volume and he flucuaions in iniial reurns individually. Several possible explanaions have been suggesed for he cyclical paern in each of hese series. A. IPO Volume Lowry (2001) shows ha he observed flucuaions in IPO volume are relaed o hree facors: changes in privae firms aggregae demand for capial, changes in he adverse selecion coss of issuing equiy, and variaion in invesor opimism. More companies end o raise public equiy for he firs ime when privae firms oal demands for capial are higher, he adverse selecion coss of issuing equiy are lower, and invesors are especially opimisic and herefore willing o overpay for IPO firms. Lee and Henderson (1999), Bayless and Chaplinsky (1996), Choe, Masulis, and Nanda (1993), Rajan and Servaes (1997), Lee, Shleifer and Thaler (1991), Helwege and Liang (1996), Pagano, Panea, and Zingales (1998), and Cook, Jarrell, and Kieschnick (1999) provide addiional evidence ha equiy issuance is relaed o one or more of he above facors. More generally, boh Persons and Warher s (1997) and Soughon, Wong, and Zechner s (2000) models sugges ha he cycles in IPO volume are poenially consisen wih efficien markes and do no necessarily reflec irraional bubbles. Persons and Warher show ha if firms raionally condiion heir decision o go public on he oucome of recen IPOs, hen we may observe clusering of IPOs in cerain periods. Soughon, Wong, and Zechner posi ha he clusering of IPOs is he resul of informaion effecs. One firm s IPO provides informaion abou indusry prospecs, hus causing many similar companies o go public soon afer. B. Iniial Reurns Variaion in average IPO iniial reurns can also be caused by a number of differen facors. Rier (1984) finds ha underwrier monopsony power and differences in he average risk of companies going public are imporan. Specifically, he higher average iniial reurns during he early 1980s were driven by a large number of small, risky, naural resource companies going public and by he underwriers of hese IPOs sysemaically pricing hem far below heir subsequen marke value. In addiion, Rier (1991) provides evidence ha invesor over-reacion during cerain periods conribues o he flucuaions in iniial reurns. When invesors are overopimisic, hey bid up he afer-marke price of he IPO firms, resuling in especially high iniial reurns. Finally, Loughran and Rier s (2000) prospec heory explanaion says ha iniial reurns are relaed o public informaion ha becomes available during he regisraion period. Such informaion is only parially incorporaed ino he offer price, meaning ha offerings whose regisraion periods coincide wih periods of high marke-wide reurns will end o be especially underpriced. Because he regisraion periods of IPOs close o one anoher in ime overlap, his generaes cycles in iniial reurns. C. Informaion Spillover and IPO Cycles Neiher changes in he average risk of companies going public nor ime-variaion in underwrier monopsony power seem likely o cause iniial reurns o be relaed o subsequen or lagged IPO volume. However, suppose ha iniial reurns are relaed o some value-relevan informaion. For example, Loughran and Rier (2000) find ha iniial reurns are relaed o

9 8 Forhcoming The Journal of Finance public informaion learned during he regisraion period, and Hanley (1993) finds ha iniial reurns are relaed o privae informaion learned in his same period. In addiion, van Bommel and Vermaelen (2000) find ha firms wih higher firs-day reurns spend more money on invesmen afer he IPO, suggesing ha iniial reurns are posiively relaed o he marke s assessmen of he firm s prospecs. In a similar spiri, Soughon, Wong, and Zechner (2000) show ha firms wih higher firs-day reurns should gain larger marke share in he produc marke. Consisen wih Soughon, Wong, and Zechner s predicions, Ward (1997) finds ha when a firm announces an IPO, he sock price reacions of compeior firms are srongly negaively correlaed wih he IPO firm s evenual underpricing. Benvenise, Busaba, and Wilhelm (2000) noe ha he informaion produced by firms ha go public influences no only heir own producion decisions bu also hose of heir rivals. Consisen wih his idea, Benvenise, Wilhelm, and Yu (1999) find ha issuing firms srucure heir IPOs condiional on various feaures of recen offerings. If high iniial reurns indicae ha privae companies can raise more money in an IPO han hey previously hough, hen hese prior findings sugges ha high iniial reurns should be followed by periods of high volume. Informaion spillovers can similarly explain he negaive relaion beween IPO volume and subsequen iniial reurns. As more firms go public, companies have beer informaion abou how much money hey can expec o raise in an IPO. Thus, he uncerainy surrounding he rue value of hese companies decreases, and average iniial reurns decrease. 2 D. Evidence on Iniial Reurns and Volume Figure 2 shows he cross correlaions beween iniial reurns in monh and IPO volume in monh +k for several versions of hese variables, for 12 monhs before and afer he monh of he IPO. Panel A uses Ibboson, Sindelar, and Rier s (ISR) daa for , IR EW and NIPO ISR k. Consisen wih he impressions from Figure 1, hese daa show a srong paern of negaive correlaions beween curren iniial reurns and pas numbers of IPOs, along wih srong posiive correlaions beween curren iniial reurns and fuure numbers of IPOs. Panel B shows ha he paern of cross-correlaions is similar over he shorer ime period, , on which he majoriy of our empirical ess focus. The cross-correlaions using iniial reurns and he number of filings, IR PW and NFIL +k, are shifed by abou one monh (so reurns o IPOs filed in monh are relaed o he number of IPOs filed in monhs +1 and beyond). This is consisen wih he lag beween he ime an IPO is filed and he ime of he offer. These figures are descripive in naure, however, and one mus be cauious in drawing conclusions from hem. To es he reliabiliy of hese relaions, we use hird order vecor auoregressive (VAR) models. The VAR models allow for he subsanial serial correlaion in boh iniial reurns and volume ha can make inferences abou he cross-correlaions in Figure 2 difficul. These models enable us o es he incremenal predicive abiliy of lagged iniial reurns o predic fuure volume and vice versa. Such ess are referred o as Granger (1969) F- ess, since he suggesed and popularized hem. The VAR models as well as he Granger F-ess are shown in Table II. 2 Alhough Benvenise, Busaba, and Wilhelm s (2000) informaion spillover model differs slighly from he inuiion presened here, hey arrive a a similar predicion. They model iniial reurns as compensaion o invesors for learning he rue value of firms, and hey show ha as more firms go public, invesors mus expend fewer resources o learn he rue value of subsequen IPOs, hereby causing iniial reurns o decrease.

10 IPO Marke Cycles 9 A. Cross Correlaions of Monhly IPOs and IPO Reurns, NIPO ISR k vs. IR EW B. Cross Correlaions of Monhly IPOs and IPO Reurns, NIPO ISR k vs. IR EW NIPO SDC k vs. IR PW NFIL SDC k vs. IR PW Figure 2. Cross correlaions of he number of IPOs in monh +k wih he reurn o IPOs in monh, for k = -12,..., 12. The large sample sandard error for hese correlaions is.05 for and.08 for NIPO ISR is he number of IPOs per monh and IR EW is he equalweighed average iniial reurn o IPO invesors in monh boh from Ibboson, Sindelar, and Rier (1994). NIPO SDC is he number of IPOs per monh and IR PW is he proceeds-weighed average iniial reurn o IPO invesors in monh boh using daa from SDC.

11 Table II Do IPO Iniial Reurns Predic he Number of IPOs, or Vice Versa? Third order vecor auoregressive (VAR(3)) models for iniial reurns and he number of IPOs using ISR's daa on aggregae IPO aciviy in he U.S., and IR EW is he equal-weighed reurn o IPO invesors and NIPO ISR is number of IPOs offered in he monh. Also, VAR(3) models for iniial reurns and he number of IPOs using SDC daa on aggregae IPO aciviy in he US, IR PW is he proceeds-weighed reurn o IPO invesors and NIPO SDC is he number of IPOs offered in he monh. The -saisics use Whie's (1980) heeroskedasiciy-consisen sandard errors, and he Granger F-ess for incremenal predicabiliy ("causaliy") are also correced for heeroskedasiciy. The F-ess indicae he incremenal explanaory power of he hree lags of he predicor variable, given hree lags of he dependen variable. R 2 is he coefficien of deerminaion, adjused for degrees of freedom. S(u) is he sandard error of he regression. Dependen Variable IR EW ISR Daa, ISR Daa, SDC Daa, NIPO ISR IR EW NIPO ISR IR PW NIPO SDC Coef -sa Coef -sa Coef -sa Coef -sa Coef -sa Coef -sa Regressors Consan IR IR IR NIPO NIPO NIPO R S(u) Granger F-ess: Lagged NIPO (p-value) (0.132) (0.551) (0.964) Lagged IR (p-value) (0.0001) (0.0001) (0.002) 10 Forhcoming The Journal of Finance Sample Size, T

12 IPO Marke Cycles 11 The lef and middle panels of Table II show resuls for ISR's equal-weighed daa over he and periods, and he righ panel is based on proceeds-weighed SDC daa beween 1985 and These ess confirm ha here is a significan posiive relaion beween iniial reurns and he fuure number of IPOs. Using eiher ime period and eiher equal-weighed or proceeds-weighed iniial reurns, Granger F-ess srongly rejec he hypohesis ha hree lags of iniial reurns have no power o predic IPO volume, wih p-values for hese ess all below In conras, he relaion beween he number of IPOs and fuure iniial reurns is negaive, bu no significan a convenional levels. Thus, he impression from Figure 2 ha higher numbers of IPOs are associaed wih lower average reurns in he fuure is somewha misleading. 3 The cross-correlaions in Figure 2 are misleading because boh iniial reurns and IPO volume are highly auocorrelaed. Tess using 6 and 12 lags in he VAR models yield qualiaively similar resuls. Thus, he F-ess in Table II srenghen and formalize he impression given by he crosscorrelaions in Figure 2 ha pas iniial reurns have a significan posiive effec on fuure IPO volume. However, pas IPO volume plays a weak role, if any, in predicing fuure iniial reurns. III. Do Firms Manage he Timing of he IPO Process? The srong posiive relaion beween iniial reurns and subsequen IPO volume suggess ha companies are iming heir IPOs in response o he size of recen iniial reurns. The finding ha high iniial reurns are followed by increased numbers of IPOs suggess ha high iniial reurns represen good news o privae companies considering an IPO. In his secion, we look more specifically a he poenial firm acions ha could conribue o his relaion. There are hree ways ha companies and/or underwriers can affec he iming of he IPO in response o recen IPO iniial reurns. Firs, companies mus file he issue. Second, hey have he opion o change he planned issue dae. A delay would exend he amoun of ime beween he filing dae and he offer dae. Third, hey have he opion o cancel he issue. This secion examines he relaions beween average iniial reurns and he number of IPO filings, he average regisraion ime, and he proporion of IPO cancellaions. If high iniial reurns provide posiive informaion abou he marke s valuaion of IPOs, hen more privae companies should file IPOs afer periods of high iniial reurns. Thus, iniial reurns should be posiively correlaed wih he number of subsequen filings. In conras, we expec iniial reurns o be negaively relaed o he number of subsequen cancellaions. If large average iniial reurns represen posiive informaion for a company considering an IPO, hen fewer firms should cancel IPOs afer observing such reurns. Similar facors would cause iniial reurns o be negaively correlaed wih he average regisraion ime of subsequen IPOs. When average iniial reurns are high, companies have an incenive o expedie he offering process, meaning ha high (low) iniial reurns will be followed by shorer (longer) regisraion imes. Table III conains Granger F-ess from hird order VAR models (similar o Table II) relaing wo measures of iniial reurns (IR EW and IR PW ) wih pas and fuure measures of IPO iming. NFIL is he number of offerings filed per monh. REGTIME PW is he average lengh of ime in days beween he filing dae and he offer dae for all issues offered in monh. NWD* is he 3 The finding of no significan relaion beween IPO volume and fuure iniial reurns conrass wih he resuls of Booh and Chua (1996). However, heir resuls are based on cross-secional regressions ha do no consider he auocorrelaion in eiher IPO volume or iniial reurns.

13 12 Forhcoming The Journal of Finance Table III Relaions beween IPO Iniial Reurns and IPO Filings, Timing, or Wihdrawals, Granger F-ess for he incremenal explanaory power of he hree lags of he predicor variable, given hree lags of he dependen variable in VAR(3) models for iniial reurns and he measures of IPO iming. IR EW is he equal-weighed reurn o IPO invesors in IPOs offered in he monh from ISR. IR PW is he proceeds-weighed reurn o IPO invesors in IPOs offered in he monh from SDC. REGTIME PW is he average lengh of ime in regisraion, he number of days beween he file and offer daes, weighed by proceeds raised in he IPO, from SDC. NWD* is he number of offerings wihdrawn per monh divided by he number of offers filed for he prior four monhs, also from SDC. The Granger F-ess are correced for heeroskedasiciy. Iniial Reurn Measures IR EW IR PW IPO Timing Measures F-es p-value F-es p-value NFIL (1) Reurns predic Filing Sample Size 153 REGTIME PW (2) Reurns predic Timing Sample Size 153 NWD* (3) Reurns predic Wihdrawals Sample Size 119

14 IPO Marke Cycles 13 number of offers wihdrawn in monh, scaled by he number of issues filed in he prior four monhs. The saisical ess in Table III show ha he posiive relaion beween iniial reurns and he number of IPOs is driven by he iming of firm filings and of offer wihdrawals. Consisen wih he evidence in Figure 2, boh equal-weighed and proceeds-weighed average monhly iniial reurns are significanly posiively relaed o he number of subsequen IPO filings (F-ess have p-values of and 0.003, respecively). Also, boh equal-weighed and proceeds-weighed iniial reurns are srongly relaed o fuure wihdrawals (p-values of and 0.006, respecively). More companies file IPOs and fewer companies wihdraw offerings following periods of high iniial reurns. Finally, alhough here is some evidence ha proceeds-weighed iniial reurns predic iming (p-value of using IR PW ), he coefficiens of he VAR models (no shown) are posiive for lagged iniial reurns. This implies ha high iniial reurns are associaed wih longer regisraion imes in fuure monhs. A firs glance, his resul seems inconsisen wih he evidence ha iniial reurns represen good news for companies considering an IPO. However, i is possible ha high iniial reurns lead so many companies o file IPOs ha he SEC is no able o process he regisraion saemens in a imely manner, or ha invesmen banks canno provide service o all of hese firms simulaneously, resuling in longer regisraion imes. In summary, he posiive relaion beween iniial reurns and fuure IPO volume is driven by more companies filing IPOs afer periods of high iniial reurns and by he likelihood of cancellaion, no by variaion in he lengh of regisraion. IV. The Informaion Conen of Iniial Reurns The fac ha more companies file o go public and fewer companies wihdraw heir offerings afer observing ha recen IPOs have earned especially high iniial reurns suggess ha iniial reurns conain valuable informaion for privae companies considering an IPO. This secion, along wih Secions V and VI, examines he pricing process of IPOs a he firm level o learn more abou he informaion conen of iniial reurns. Secion IV.A reviews he mos relevan exising lieraure, and Secion IV.B defines he firmlevel daa used in he remainder of he paper. Secion IV.C presens a brief empirical analysis of he deerminans of iniial reurns. We noe ha mos of he cross-secional resuls in Secion IV.C confirm he findings of he prior lieraure. The main purpose of his analysis is o faciliae our aggregae ime series ess in Secions V and VI. Secions V and VI employ he resuls of Secion IV.C o deermine wheher iniial reurns a he ime a firm goes public are relaed o ha firm s evenual underpricing and, more generally, o deermine why more firms go public following periods of high iniial reurns. A. Overview of he IPO Pricing Process Iniial reurns equal he difference beween he underwriers valuaion of he firm, as represened by he offer price, and he secondary marke s valuaion. However, prior evidence shows ha underwriers do no fully incorporae all available informaion ino he offer price. Iniial reurns represen some informaion known ahead of ime by he underwriers plus some incremenal informaion provided by he marke. When a company files an IPO, i mus file a prospecus conaining a variey of firm- and offer-specific informaion. Eiher in his prospecus or in an amended prospecus ha is filed laer, he company mus also provide a range of anicipaed IPO prices. During he regisraion

15 14 Forhcoming The Journal of Finance period, he company and is underwrier go on a road show o marke he issue o insiuional invesors, and hese invesors have he opporuniy o express ineres in he offering. If he invesors accuraely reveal heir privae informaion hrough hese expressions of ineres, hen he informaion exchange will conribue o a more accurae pricing of he new issue. However, hese invesors can poenially benefi by no revealing posiive informaion abou a new issue, causing he offer price o be se oo low and enabling hem (assuming hey buy in a he offer price) o reap significan gains. To proec hemselves agains his poenial loss, Benvenise and Spind (1989) hypohesize ha underwriers only parially incorporae posiive informaion learned during he regisraion period ino he final offer price. This ensures he invesors of some posiive reurn as compensaion for revealing heir privae informaion, bu also enables underwriers and he newly public company o share in he gains. Consisen wih his heory, Hanley (1993) finds a significan posiive relaion beween a firm s price updae and is iniial reurn. Evidenly, iniial reurns consis of some informaion known prior o he offering, as well as some incremenal informaion provided by he secondary marke. Loughran and Rier (2000) noe ha Benvenise and Spind s model implies ha underwriers should only parially incorporae privae informaion learned abou firm value during he regisraion period, bu ha public informaion should be fully refleced in he offer price. However, Loughran and Rier find ha here are srong posiive correlaions beween he pre-offer marke reurn and he price updae and also beween he pre-offer marke reurn and he iniial IPO reurn, indicaing ha he price adjusmen o his publicly available informaion is only parial. In oher words, he parial adjusmen phenomenon discussed by Benvenise and Spind exiss for observable public informaion, such as he marke reurn, even hough heir heory would no predic his. Finally, Baron (1982) posis ha issues ha are characerized by greaer uncerainy end o be more underpriced o compensae invesors for learning abou heir rue values. Rier (1984) noes ha Rock s (1986) model has a similar implicaion, and Beay and Rier (1986) develop Rier s asserion in more deail, ha is, issues characerized by greaer uncerainy should be more underpriced on average. Beay and Rier (1986) and Megginson and Weiss (1991), among ohers, find empirical suppor for hese ideas. Iniial reurns are significanly relaed o a variey of firm-specific characerisics, many of which are known a he ime he IPO is filed. In summary, prior evidence indicaes ha he iniial reurn consiss of informaion relaed o he ype of firm going public, privae and public informaion learned during he regisraion period bu no fully incorporaed ino he offer price, and finally he new informaion ha is provided by he secondary marke when he issue sars rading. Our finding of a significan posiive relaion beween average iniial reurns and subsequen IPO volume indicaes ha a leas one of hese informaion sources represens an imporan deerminan of he iming of firms IPOs. B. Daa on Individual IPOs and Sample Selecion Bias To esimae he porion of iniial reurns ha represens informaion known ahead of ime, we analyze he predicabiliy of iniial reurns a he firm level. We use SDC and CRSP daa from o invesigae hese relaions, and his secion discusses hese daa. The empirical ess are found in Secion IV.C.

16 IPO Marke Cycles 15 The variables we use include: (1) IR, he iniial reurn, equals he percenage change beween he offer price and he firs closing price (previously described in Secion I.A); (2) RANK is he underwrier rank, from Carer, Dark, and Singh (1998) (underwriers no covered by Carer, Dark, and Singh are assigned a rank of zero); (3) TA equals he logarihm of real oal asses (in 1983 dollars) before he IPO; (4) NYSE equals one if he IPO is lised on he New York Sock Exchange, and zero oherwise; (5) NMS equals one if he IPO is lised on he Nasdaq Naional Marke Sysem, and zero oherwise; (6) AMEX equals one if he IPO is lised on he American Sock Exchange, and zero oherwise; (7) TECH equals one if he firm is in a high ech indusry [bioech, compuer equipmen, elecronics, communicaions, and general echnology (as defined by SDC)], and zero oherwise; (8) P is he percenage change beween middle of he original file price range and he offer price; (9) P + equals P when i is posiive, and zero oherwise (o capure asymmeric effecs of price updaes); (10) MKT is he reurn o he CRSP equal-weighed porfolio of NYSE, Amex, and Nasdaq-lised socks for he 15 rading days prior o he offer dae, and (11) MKT + equals MKT when i is posiive, and zero oherwise (again, o capure asymmeric effecs). C. Regression Models for Firm-level Iniial Reurns I is well known ha he percen change beween he offer price and he secondary marke price (he iniial reurn) is large on average, bu also highly variable across firms. Table IV conains esimaes of regression models ha explain his iniial reurn, IR i = + 1 RANK i + 2 TA i + 3 NYSE i + 4 NMS i + 5 AMEX i + 6 TECH i + 7 P i + 8 P i + 9 MKT i + 10 MKT i + i, (1) where he variables have been defined above. The rank of he invesmen banker (RANK), he size of he IPO firm (TA), he marke on which he new issue will rade (NYSE, NMS, or AMEX), and he firm s indusry (TECH) are known a he ime of he iniial prospecus. The price updae ( P) and marke reurns during he 15 rading days prior o he offer (MKT) are no known unil he IPO price is se, ypically one day before he offering. The cross-secional regressions in Table IV have many poenial saisical problems. For example, since IPOs are clusered in ime he regression errors in Table IV are likely o be correlaed. Moreover, he coefficiens may no be consan over ime. Our main ineres in hese cross-secional regressions is o idenify firm and deal characerisics ha are likely o be sysemaically relaed o iniial reurns so ha we can aggregae he predicions and he predicion errors from hese models o learn more abou aggregae IPO marke cycles. For his

17 16 Forhcoming The Journal of Finance Table IV Firm and Deal Characerisics Relaed o IPO Reurns Across Firms, Regression models for he reurns o IPO invesors in he U.S. using SDC daa from The dependen variable is he percenage iniial reurn. RANK is he underwrier rank from Carer, Dark, and Singh (1998). TA equals he logarihm of real oal asses before he IPO. NYSE equals one if he IPO firm will be lised on he New York Sock Exchange, and zero oherwise. NMS equals one if he IPO firm will be lised on he Nasdaq Naional Marke Sysem, and zero oherwise. AMEX equals one if he IPO firm will be lised on he American Sock Exchange, and zero oherwise. TECH equals one if he firm is in a high ech indusry [bioech, compuer equipmen, elecronics, communicaions, & general echnology (as defined by SDC)], and zero oherwise. P is he percenage difference beween he mid-poin of he iniial offer range and he final IPO price. P + equals P when i is posiive, and zero oherwise. MKT is he reurn o he CRSP equal-weighed porfolio for he 15 rading days before he offering dae. MKT + equals MKT when i is posiive, and zero oherwise. The -saisics use Whie's (1980) heeroskedasiciyconsisen sandard errors. R 2 is he coefficien of deerminaion, adjused for degrees of freedom. S(u) is he sandard error of he regression. The sample size is 3,976 IPOs. Informaion a Time of Regisraion Informaion a Time of Offering (1) (2) (3) (4) Coefficien -saisic Coefficien -saisic Consan RANK TA NYSE NMS AMEX TECH P P MKT MKT R S(u)

18 IPO Marke Cycles 17 purpose, we are no really concerned abou he reliabiliy of he -saisics in columns (2) and (4). Furher, we do no include any variables ha would proxy direcly for recen iniial reurns o IPOs, such as ime rends or yearly dummy variables. The predicions from Table IV reflec only he firm and deal characerisics, no he recen sae of he IPO marke. The regression in column (1) of Table IV includes only independen variables ha are known a he ime he IPO is filed. We find ha larger IPO firms, hose ha lis on AMEX, and hose ha are no echnology firms have he leas underpricing. Noe ha he coefficien of deerminaion R 2 is abou 2.9%, so only a small par of he variaion in iniial reurns is explained by hese characerisics ha are known a he ime of he iniial regisraion. Moreover, he sandard error of he regression is 23.4%, implying ha here is a lo of unexplained dispersion in iniial reurns. Column (3) adds explanaory variables ha are no known unil he acual offering. Thus, he difference beween he porion of iniial reurns explained in he column 1 regression versus he column 3 regression represens he effecs of informaion learned during he regisraion period. Hanley (1993) shows ha iniial reurns are significanly relaed o he price updae, and Loughran and Rier (2000) show ha iniial reurns are significanly relaed o marke reurns during he 15 days prior o he offering. We include boh of hese variables, P and MKT. We also allow for any asymmeric effecs by including P + and MKT +. Consisen wih Lowry and Schwer (2001), we find ha he price updae has an asymmeric effec on iniial reurns. Specifically, we find ha a 10% increase in he IPO price from he midpoin of he iniial filing range predics a 8.65% ( ) higher iniial reurn, while a 10% decrease in he IPO price predics a 1.85% lower iniial reurn. Thus, he iniial reurn responds more o posiive price updaes han o negaive price updaes. Invesmen bankers and issuing firms incorporae negaive informaion more fully ino he offer price han posiive informaion. This is consisen wih underwriers rying o avoid losses on overpriced issues while allowing informed invesors o share he gains on underpriced issues. The effec of marke reurns is more ambiguous. Given he price updae and he firm and deal characerisics ha are known a he ime of he IPO, here is lile evidence ha MKT and MKT + are srongly relaed o iniial reurns. Boh MKT and MKT + have modes -saisics (1.47 and 1.26, respecively), even given he likely problems wih hese -saisics menioned above. However, if we had specified he asymmeric marke reurn variable o be zero when MKT is posiive and equal o MKT when i is negaive (call i MKT - ), he esimae of he coefficiens of MKT and MKT - would be and wih -saisics of 5.02 and As menioned earlier, he purpose of including marke reurns in he regression is o capure informaion learned during he regisraion period. The quesion raised by Loughran and Rier (2000) of wheher public informaion learned during he regisraion period is or is no fully incorporaed ino he offer price is beyond he scope of his paper. V. Cycles in Iniial Reurns Given he serial correlaion in iniial reurns, i seems surprising ha more companies choose o go public afer observing high iniial reurns. However, Secion IV shows ha iniial reurns are predicably relaed o several facors. The exen o which a company can affec is own underpricing by alering he iming of is IPO depends on which of hese facors drive he serial correlaion in iniial reurns.

19 18 Forhcoming The Journal of Finance A. Auocorrelaions of Iniial Reurns By definiion, he serial correlaion in iniial reurns indicaes ha underwriers do no incorporae all available informaion ino he IPO offer price. If he IPOs in a given monh are especially underpriced, one can expec ha IPOs in he subsequen monh will also be underpriced by a large amoun. However, he regressions in Table IV show ha here are predicable relaions beween he characerisics of IPO firms and he iniial reurn. Thus, he auocorrelaion in aggregae iniial reurns in Table I could simply reflec paerns in he ypes of firms going public. Table IV also shows ha he iniial reurn is relaed o informaion learned during he regisraion period bu only parially incorporaed ino he offer price. Because he regisraion period averages wo monhs, IPOs ha are close in calendar ime will end o have overlapping regisraion periods. This could also conribue o he serial correlaion of iniial reurns. To examine he source of he serial correlaion in iniial reurns, we aggregae he predicions of iniial reurns ha are implied by he cross-secional regression models in Table IV ino expeced componens and he residuals ino unexpeced componens, where boh are weighed by proceeds raised in he IPO. Table V shows he mean, median, sandard deviaion, minimum, maximum, and 12 auocorrelaions of he iniial reurn, and is expeced and unexpeced componens from We use he predicions from column (1) in Table IV o represen he expeced iniial reurns (E F (IR)) for firms having IPOs in monh, condiional on informaion available a he ime he IPO is filed (informaion in he preliminary prospecus). This expeced reurn measure should capure he porion of iniial reurns ha is relaed o he ypes of firms going public. The unexpeced iniial reurn, [IR E F (IR)], is he proceeds-weighed residual or forecas error from he same Table IV regression and consiss of informaion learned during he regisraion period plus he incremenal informaion provided by he secondary marke when he firm sars rading. Row (2) of Table V shows he auocorrelaions of expeced iniial reurns a he ime of he filing, E F (IR). Many of hese auocorrelaions are reliably differen from zero, indicaing ha a leas par of he serial correlaion in observed iniial reurns is aribuable o he mix of firms going public. There are paerns in he ype of firms going public, and (consisen wih he informaion asymmery hypohesis) similar firms end o earn similar iniial reurns. In addiion, he firs lag of he unexpeced iniial reurn in row (3), [IR E F (IR)], equals 0.34, and many of he higher order lags are also significanly differen from zero. This indicaes ha informaion learned during he regisraion period bu only parially incorporaed ino he offer price and/or unexplained biases in underwrier pricing also conribue o he serial correlaion in iniial reurns. To deermine he effec of informaion learned during he regisraion period, we use he predicions from column (3) in Table IV o represen he iniial reurns condiional on informaion in he preliminary prospecus and informaion learned during he regisraion period. The corresponding measure of unexpeced iniial reurns, [IR E O (IR)], consiss of he incremenal informaion provided by he secondary marke when he firm sars rading. Noe ha if similariies in he ypes of firms going public and informaion learned during he regisraion period enirely accoun for he serial correlaion in iniial reurns, hen hese unexpeced iniial reurns will no be serially correlaed. The las row of Table V shows ha he auocorrelaions of his measure of unexpeced iniial reurns, [IR E O (IR)], are in fac close o zero a all lags. This suggess ha he cross-secional model in column (3) of Table IV capures all of he ineresing dynamics in predicing iniial

20 Table V Auocorrelaions of Expeced and Unexpeced Iniial Reurns o IPOs, In addiion o he auocorrelaions, we show he mean, median, sandard deviaion, minimum, and maximum of he iniial reurn o IPO invesors (IR). The iniial reurns are weighed by proceeds raised in he IPO wihin each calendar monh. Auocorrelaions for 12 lags ( 1 o 12 ) have a large sample sandard error of 0.08 under he hypohesis of no auocorrelaion. The measure of expeced iniial reurns in row 2, based on column (1) in Table IV, uses daa known a he ime he IPO is filed (from he preliminary prospecus), where E F [IR] is he expeced iniial reurn and IR E F [IR] is he unexpeced iniial reurn. The measure of expeced iniial reurns in row 4, based on column (3) in Table IV, uses daa known a he ime he IPO is offered (including he price updae and marke reurns), where E O [IR] is he expeced iniial reurn and IR E O [IR] is he unexpeced iniial reurn. Mean Median Sd Dev Min Max Percenage Iniial Reurns (proceeds-weighed average of issues offered in monh ) (1) IR Expecaions a he ime he IPO is filed, based on informaion in he preliminary prospecus [column (1), Table IV] (2) E F [IR] (3) IR E F [IR] Expecaions a he ime of he IPO, based on informaion in he final prospecus [column (3), Table IV] (4) E O [IR] (5) IR E O [IR] IPO Marke Cycles 19

21 20 Forhcoming The Journal of Finance reurns, despie he fac ha here are no measures of IPO marke condiions in his regression. The finding ha [IR E O (IR)] is uncorrelaed hrough ime shows ha he serial correlaion in iniial reurns can be explained by he effecs of firm characerisics and informaion learned during he regisraion period. As menioned previously, a firm canno know wha value-relevan informaion will become available afer i files is offering (during is regisraion period), and i presumably canno subsanially aler is basic characerisics (such as size, indusry, ec.) Thus, i seems ha companies have lile abiliy o conrol he size of heir iniial reurns by filing heir IPO a differen imes. 4 In summary, he level of recen average iniial reurns conains no informaion abou he expeced underpricing of new IPOs being filed, meaning ha a company can neiher gain nor lose by filing during a period of high versus low iniial reurns. B. Fama-MacBeh Regressions As a check on he robusness of our resuls, we also employ an alernaive es of he relaion beween average iniial reurns a he ime a company files an IPO and ha company s evenual underpricing. Specifically, we regress he iniial reurns of a company ha files in monh on he average iniial reurns of offerings in monh -1 as well as he firm and deal characerisics used in Table IV. If a company can predic is level of underpricing a he ime i files based on he iniial reurns of recen offerings, hen we would expec o find a significan relaion. As menioned above, pooled cross-secional regressions such as hose in Table IV can give misleading inferences because IPOs are clusered in ime, resuling in correlaed errors. To es wheher recen iniial reurns in he IPO marke predic a firm s iniial reurn, we use Fama- MacBeh (1973) boosrap esimaes in Table VI. We esimae cross-secional regressions each year from , hen average he year-by-year coefficien esimaes. The -saisics in Table VI are based on he sandard error of he mean of hese 13 year-by-year esimaes. Column (1) includes he firm-specific characerisics known a he ime he offering was filed, and column (3) also includes he price updae and marke reurn informaion ha is available a he ime of he offering. Consisen wih he resuls in Table V, he average iniial reurn o IPOs in he monh before filing is insignifican in boh regressions (-saisics of and 0.23). Moreover, he poin esimaes are negaive, which is opposie of he posiive auocorrelaion seen in he unadjused aggregae iniial reurns. The resuls in Table VI provide furher evidence ha he iniial reurns of a company filing in monh are unrelaed o he average iniial reurns observed in recen offerings. I seems ha a company canno conrol is level of underpricing by filing during a period of high versus low average iniial reurns. C. Discussion In summary, firms end o regiser o go public when average iniial reurns are especially high, bu hose firms should no hemselves expec o be especially underpriced. In fac, he average iniial reurns of hese firms are largely unpredicable. The serial correlaion in aggregae iniial reurns is explained by similariies in he ypes of firms going public over ime 4 While he price updae is no known unil he day before he offering (when he offer price is se), if firms could predic he price updae a he ime of he filing hey may be able o predic heir iniial reurn a he same ime. However, he finding ha he price updae is only auocorrelaed a lag one (Table I) combined wih he fac ha he regisraion period averages wo monhs miigaes his concern. As a furher check, we disaggregae he price updae ino expeced and unexpeced componens, condiional on informaion available a he ime of he filing. When we include his expeced price updae measure in expeced iniial reurns he resuls are similar.

22 IPO Marke Cycles 21 Table VI Effecs of Average IPO Iniial Reurns in Monh -1 on Iniial Reurns o Firms Filing in Monh, Fama-MacBeh Boosrap Esimaes, Fama-MacBeh esimaes for he reurns o IPO invesors in he U.S. using SDC daa from Coefficien esimaes are an average of he year-by-year regression coefficiens and he -saisics are based on he sandard deviaion of he ime-series of coefficien esimaes. The dependen variable is he percenage iniial reurn. RANK is he underwrier rank from Carer, Dark, and Singh (1998). TA equals he logarihm of real oal asses before he IPO. NYSE equals one if he IPO firm will be lised on he New York Sock Exchange, and zero oherwise. NMS equals one if he IPO firm will be lised on he Nasdaq Naional Marke Sysem, and zero oherwise. AMEX equals one if he IPO firm will be lised on he American Sock Exchange, and zero oherwise. TECH equals one if he firm is in a high ech indusry [bioech, compuer equipmen, elecronics, communicaions, & general echnology (as defined by SDC)], and zero oherwise. P is he percenage difference beween he mid-poin of he iniial offer range and he final IPO price. P + equals P when i is posiive, and zero oherwise. MKT is he reurn o he CRSP equal-weighed porfolio for he 15 rading days before he offering dae. MKT + equals MKT when i is posiive, and zero oherwise. IR -1 is he proceeds-weighed average iniial reurn o IPO invesors in he monh before his IPO is firs regisered wih he SEC. R 2 is he average coefficien of deerminaion, adjused for degrees of freedom. The sample size is 3,976 IPOs. Informaion a Time of Regisraion Informaion a Time of Offering (1) (2) (3) (4) Average Coefficien -saisic Average Coefficien -saisic Consan RANK TA NYSE NMS AMEX TECH P P MKT MKT IR R

23 22 Forhcoming The Journal of Finance and informaion learned during he regisraion period. Thus, he cross-secional predicabiliy of iniial reurns also explains he apparen ime-series auocorrelaion of aggregae iniial reurns. Our resuls indicae ha several of he heories ha were developed o explain he crosssecional paerns in iniial reurns can also explain he ime-series dynamics. For example, he finding ha a porion of he serial correlaion in iniial reurns is driven by similariies in he ypes of firms going public, combined wih he evidence ha iniial reurns vary predicably wih firm characerisics, is consisen wih he informaion asymmery hypohesis. Similarly, he finding ha informaion learned during he regisraion period bu only parially incorporaed ino he offer price conribues o he serial correlaion in iniial reurns is consisen wih he parial updaing heory and possibly he prospec heory explanaion. To he exen ha he relevan informaion learned during he regisraion period is all privae informaion (as represened by he price updae in Tables IV and VI), he evidence is consisen wih Benvenise and Spind s parial updaing heory. However, o he exen ha public informaion learned during his period (as represened by marke reurns in Tables IV and VI) is similarly only parially incorporaed ino he offer price, our resuls indicae ha he Loughran and Rier s prospec heory explanaion also explains a leas a porion of he serial correlaion in iniial reurns. VI. The Informaion Conen of Iniial Reurns We nex examine he source of he informaion in average iniial reurns ha leads more companies o file IPOs following periods of high average underpricing. Table VII shows Granger F-ess from hird order VAR models (similar o Tables II and III) relaing iniial reurns wih fuure measures of boh he number of IPOs filed per monh (NFIL) and he number of IPOs offered per monh (NIPO). I also shows he relaions beween he expeced and unexpeced componens of iniial reurns, condiional on various informaion ses, wih hese measures of IPO volume. By focusing on he relaions beween iniial reurns and subsequen IPO volume, we hope o learn more abou he sources of informaion ha companies rely on as hey decide when o go public. The firs column shows F-ess for he VARs beween acual IR and he subsequen NFIL and NIPO. As previously shown in Tables II and III, we find ha IR is significanly posiively relaed o boh measures of subsequen IPO volume. The second and hird columns employ he resuls from he previous secion o decompose he iniial reurn ino expeced and unexpeced componens, based on various informaion ses, o deermine more specifically he source of hese relaions. In rows 1 and 2 he expeced iniial reurn is condiional on he firm-specific informaion conained in he preliminary prospecus (he Table IV, column 1 regression). Thus, he expeced iniial reurn conains informaion abou he ypes of companies going public, while he unexpeced iniial reurn incorporaes all of he informaion learned during he regisraion period plus he incremenal informaion provided by he secondary marke. Resuls show ha he expeced iniial reurn has lile power o predic eiher NFIL or NIPO (p-values of and 0.766), while he unexpeced iniial reurn is a highly significan predicor of boh (p-values of and 0.003). This suggess ha he relevan informaion mus be relaed o eiher informaion learned during he regisraion period or o he incremenal informaion provided by he secondary marke a he ime of he offer, bu no o he ypes of companies going public. In rows 3 and 4, he expeced iniial reurn includes firm-specific informaion conained in he preliminary prospecus plus informaion learned during he regisraion period (he Table IV, column 3 regression). When informaion learned during he regisraion period is included in he

24 IPO Marke Cycles 23 Table VII Relaions beween Iniial Reurns o IPOs and IPO Filings or Offers, Granger F-ess for he incremenal explanaory power of he hree lags of he predicor variable, given hree lags of he dependen variable in VAR(3) models for iniial IPO reurns and he measures of IPO volume. The reurn o IPO invesors, IR, is he proceeds-weighed reurn o IPOs from SDC sudied in Table V. The columns labeled Expeced represen VAR(3) models using he prediced iniial reurn from he cross-secional regression models in Table IV. Similarly, he columns labeled Unexpeced represen VAR(3) models using he forecas errors for he iniial reurn from he cross-secional regression models in Table IV. For he IPO reurns, wo forecass are sudied: firs, using public informaion available a he ime he IPO is filed [col. (1) in Table IV], and second, using public informaion available a he ime of he IPO [col. (3) in Table IV]. The Granger F-ess are correced for heeroskedasiciy. Componens of Iniial Reurns, IR Acual Expeced Unexpeced F-es p-value F-es p-value F-es p-value Expecaions based on public informaion a he ime he IPO is filed [col. (1) in Table IV] (1) IR predics NFIL (2) IR predics NIPO Expecaions based on public informaion a he ime of he IPO [col. (3) in Table IV] (3) IR predics NFIL (4) IR predics NIPO

25 24 Forhcoming The Journal of Finance expeced iniial reurn, he expeced iniial reurn is a highly significan predicor of boh fuure filings and fuure offerings (p-values of and 0.002). Thus, i seems ha he posiive relaion beween iniial reurns and new offerings reflecs informaion learned during he regisraion period. When he informaion ha becomes available during a new offering s regisraion period is posiive, ha company experiences a posiive iniial reurn and a larger number of oher companies choose o go public, resuling in an increase in he numbers of subsequen filings and offerings. These findings sugges ha posiive informaion learned during he regisraion period indicaes ha oher companies can go public a higher valuaions han hey had previously expeced. This inerpreaion is consisen wih he prior findings of Pagano, Panea, and Zingales (1998) and Lowry (2001) ha more companies end o go public when he average marke-o-book raio (M/B) of public firms in heir indusry is especially high. Posiive informaion learned during an IPO s regisraion period resuls in a high iniial reurn and consequenly a higher M/B for he IPO firm. Assuming ha such informaion likewise affecs already public firms, he average M/B of he similar public firms will also increase. Thus, posiive informaion ha becomes available during an IPO s regisraion period is associaed wih higher iniial reurns for ha offering, higher M/B raios for similar public firms, and more privae companies choosing o go public soon afer. Ineresingly, he unexpeced iniial reurns in rows 3 and 4 are no significanly relaed o he fuure number of filings (p-value of 0.199), bu hey are significanly relaed o he number of fuure offerings (p-value of 0.011). Furher, he relaion beween unexpeced iniial reurns and fuure offerings is negaive. Togeher, hese resuls sugges ha companies do no rely on his secondary marke informaion in heir decisions of when o file heir offerings, ye such informaion does affec he ime in regisraion. Companies appear o go public less quickly when he incremenal informaion provided by he secondary marke is more posiive. This is consisen wih he finding in Table III ha proceeds-weighed iniial reurns are significanly posiively relaed o he lengh of he regisraion period of subsequen IPOs (p-value of 0.018). In summary, he resuls in Table VII show ha privae companies rely heavily on informaion learned during he regisraion periods of recen IPOs in heir decisions of when o go public. The ypes of firms ha have recenly gone public have no influence on he filing or issuing decisions of oher privae firms. The incremenal informaion provided by he secondary marke similarly does no affec firms decisions o file offerings, bu i does affec he speed wih which IPOs are brough o marke. VII. Ou-of-sample Resuls, As can be seen in Figure 1, he IPO marke was very acive in , wih a large number of IPOs and high average iniial reurns. This occurred afer we had iniially consruced and analyzed he daa in his paper. A naural quesion arises as o wheher our resuls would hold up when exended pas We have analyzed many of he quesions addressed above using daa hrough 1999 and he conclusions drawn are sensiive o he mehods used. In paricular, a simple applicaion of he mehods used in Tables I hrough VII causes many of he parameer esimaes o change subsanially from heir values in he sample. This occurs because he dispersion of iniial reurns across IPOs is exremely high in Figure 3 shows he cross-secional sandard deviaion of iniial reurns for each monh from I is clear from his graph ha

26 200 Cross-secional Sandard Deviaion of Iniial Reurns o IPOs Figure 3. Cross-secional sandard deviaion of iniial reurns o IPOs monhly, , using daa from SDC and CRSP IPO Marke Cycles 25

27 26 Forhcoming The Journal of Finance no only were average reurns high in , bu he dispersion of reurns was also exraordinary. The mehods in his paper are all based on leas squares echniques, so daa from dominae he res of he sample. To correc his problem, we have compued weighed leas squares (WLS) Fama-MacBeh boosrap esimaes of he models in Table VII. The yearly cross-secional regression coefficien esimaes are weighed by he esimaes of heir sandard errors. The WLS esimaes are quie similar o he resuls from he sample repored in Table VII. Thus, when he ou-of-sample daa from are adjused o reflec heir unusual dispersion and included wih he daa, our conclusions do no change. We decided no o presen he sample resuls as he focus of his paper because he exra complexiy associaed wih he weighed leas squares boosrap esimaes probably disracs from he economic analysis of he problem, and he sample was he basis for he firs several drafs of his paper. Neverheless, researchers who sudy IPO markes in he fuure will have o deal wih he unusual evens of ha are refleced in he high average reurns shown in Figure 1 and he even larger dispersion of reurns shown in Figure 3. Perhaps a varian of our WLS procedure will help preven hese daa from dominaing he inferences drawn from IPO samples. VIII. Conclusion Our resuls show ha he dynamic behavior of iniial reurns and IPO issues is a complicaed funcion of many facors. There are significan biases in IPO offer prices (as forecass of secondary marke rading prices) ha arise from underwriers no fully incorporaing all available informaion when hey se offer prices. These biases affec boh he serial correlaion in iniial reurns and he lead-lag relaion beween iniial reurns and IPO volume. A firs glance, he cycles in iniial reurns sugges ha underwriers fail o accoun for he marke s valuaion of recen IPOs in heir pricing of new offerings, resuling in avoidable high firs-day reurn bubbles. However, we find ha he serial correlaion in iniial reurns is predominanly driven by informaion learned during he regisraion periods of recen IPOs bu only parially incorporaed ino he offer price. Alhough invesmen bankers do no fully incorporae informaion learned during he regisraion period ino he offer price, hey do seem o fully incorporae he marke s valuaion of recen IPOs ino heir pricing of new offerings. The average iniial reurns a he ime a company files an IPO conain no informaion abou he exen o which ha company will be underpriced. Thus, here exiss no evidence ha companies can achieve lower underpricing by filing IPOs during periods of low versus high average iniial reurns. The observaion ha more companies file IPOs following periods of high underpricing suggess ha he iniial reurns of recen IPOs conain informaion on he marke s valuaion of fuure IPOs. We find ha i is informaion learned during he regisraion period ha is posiively relaed o fuure IPO volume. The porion of iniial reurns ha reflecs firm characerisics is no reliably relaed o eiher he number of subsequen filings or he number of subsequen offerings. The porion of iniial reurns ha reflecs informaion provided by he secondary marke is similarly unrelaed o he number of subsequen filings, bu i does appear o be relaed o he lengh of he regisraion period. Thus, he apparen IPO cycles ha have been sudied previously reflec wo facors. Firs, similar ypes of firms choose o go public a abou he same ime. To he exen ha his

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