Do Today s Trades Affect Tomorrow s IPO Allocations?

Transcription

1 Do Today s Trades Affect Toorrow s IPO Allocatons? M. Nalendran, Jay R. Rtter and Donghang Zhang February 3, 2006 JLE classfcaton: G24 Keywords: IPOs, brokerage cossons Nalendran s fro the Departent of Fnance, Unversty of Florda, Ganesvlle, FL , Rtter s fro the Unversty of Florda, and Zhang s fro the Moore School of Busness, Unversty of South Carolna, Coluba, SC Nalendran can be reached at (352) or [email protected]. Rtter can be reached at (352) or [email protected]. Zhang can be reached at (803) or [email protected]. Zhang acknowledges fnancal support fro the Unversty of South Carolna Research and Productve Scholarshp Fund. We thank Shngo Goto, Kathleen Hanley, Paul Irvne, Mark Kastra, Greg Nehaus, Erc Powers, Sergey Tsyplakov, Kent Woack (the 2005 AFA dscussant), an anonyous referee, and senar partcpants at the Unversty of South Carolna and York Unversty (Canada) for coents.

2 Do Today s Trades Affect Toorrow s IPO Allocatons? Abstract Underwrters usng bookbuldng have dscretonary power for allocatng shares of ntal publc offerngs (IPOs). Cossons pad to underwrters by nvestors are one of the deternants of IPO allocatons. We test the hypothess that nvestors trade lqud stocks n order to affect ther IPO allocatons. Consstent wth ths hypothess, we fnd that oney left on the table by IPOs affects the tradng volue of the 50 ost lqud stocks close to the offer date. For an IPO that leaves $ bllon on the table, n the sx days endng on the day that tradng coences there s abnoral volue n the 50 ost lqud stocks of 2.7 to 4.%, although only durng the nternet bubble perod s ths statstcally sgnfcant.

3 Do Today s Trades Affect Toorrow s IPO Allocatons?. Introducton Underwrters have dscreton n allocatng shares of ntal publc offerngs (IPOs) when bookbuldng s used. There are three an theores descrbng the allocaton of shares by nvestent bankers: ) the acadec vew, 2) the ptchbook vew, and 3) the proft-sharng vew. The acadec vew, exposted by Benvenste and Spndt (989), argues that IPO allocatons are the soluton to a echans desgn proble n whch regular (.e., nsttutonal) nvestors ust be gven nduceents to honestly reveal ther prvate nforaton about the valuaton of a fr gong publc. The ptchbook vew, exposted by nvestent bankers n ther presentatons to prospectve ssung frs, ephaszes that shares wll be allocated to buy-and-hold nvestors, as proxed by nsttutons that already are large holders of slar frs. The proft-sharng vew, exposted by Loughran and Rtter (2002, 2004) and Reuter (2006), argues that hot IPOs are allocated to nvestors who drect cosson busness to the nvestent bankng fr n return. Ths paper tests an plcaton of the proft-sharng vew of IPO allocatons. Fro 993 to 200, the 3,499 frs gong publc left ore than $93.5 bllon on the table, where the aount of oney left on the table s defned as the nuber of shares offered tes the dfference between the frst-day closng prce and the offer prce. Durng 999 and 2000, the nternet bubble perod, the 803 IPOs left a total of $63.5 bllon on the table. Durng ths perod, the average IPO had a frst-day return of 65% and left $79 llon on the table. When such large wealth transfers are occurrng, t s natural to assue that rent-seekng actvty wll take place. When IPOs are routnely oversubscrbed, and underwrters have dscreton n allocatng shares, underwrters can boost ther profts through a qud pro quo arrangeent by gvng large allocatons to nvestors who are wllng to offer benefts to the underwrter.

4 Consstent wth the proft-sharng vew, regulatory settleents ndcate that nvestent banks allocate IPOs partly on the bass of the tradng cossons generated by nsttutonal nvestors. For exaple, the January 22, 2002 Securtes and Exchange Cosson (SEC) settleent wth Credt Susse Frst Boston (CSFB) states that CSFB allocated hot IPOs to soe clents and n return receved cossons of up to 65% of the clents profts wthn a few days of the IPO. 2 The clents kcked back part of ther profts by payng unusually hgh cossons on stock tradng that n soe cases had no other purpose than to generate cossons. Accordng to the Cosson s coplant, CSFB s clents pad as hgh as $3.00 per share n cossons for block trades executed by CSFB brokers, although the usual cosson for nsttutonal nvestors at the te was 6 per share (Goldsten, Irvne, Kandel, and Wener (2006)). CSFB pad a fne of $00 llon and settled the case wth the SEC (wthout adttng or denyng wrongdong). On January 9, 2003, the forer Robertson Stephens securtes unt of FleetBoston Fnancal Corp. also settled slar accusatons wth the SEC and the Natonal Assocaton of Securtes Dealers (NASD) and pad a fne of $28 llon. Begnnng on Noveber 7, 997, Robertson Stephens used an explct forula to allocate IPO shares. 3 The Syndcate Departent generally allocated shares by usng a forula that was weghted over the course Although we focus on nsttutonal tradng, allocatons of IPOs to ndvduals are also based partly on cossons. For exaple, n Septeber 2005, accordng to ts webste the polcy of Charles Schwab, Inc. was to restrct IPO allocatons to clents who ether ) had a $00,000 balance n ther Schwab brokerage account(s), or ) had a $50,000 balance and had ade at least 40 trades durng the pror 2 onths. 2 See SEC press release and the SEC coplant aganst CSFB for allegatons on CSFB IPO allocatons. In ts January 22, 2002 news release ( NASD Regulaton, Inc. states that "CSFB's IPO proft sharng practce was wdespread, occurrng between Aprl 999 and June The practce affected ore than 300 accounts servced by the fr's Insttutonal Sales Tradng Desk, ts Prvate Clent Servces (PCS) Group and ts PCS Technology Group" and that " durng the last quarter of 999, over 3,000 trades were done at these excessve cosson rates and hundreds of the were executed wth a cosson rate of $ per share or ore." 3 See Mchael Sconolf and Anta Raghavan, Robertson Stephens Tres to Stop Spnnng of Hot IPOs, Wall Street Journal Noveber 8,

5 of 8 onths n favor of those accounts that generated cossons closer n te to the IPO. Ths forula was used to calculate a custoer s Syndcate Rank. The Syndcate Departent also had dscreton to allocate soe IPO shares ndependent of the Syndcate Rank on a case-by-case bass. 4 Robertson Stephens Inc. and CSFB are apparently not the only nvestent banks that allocated IPOs on the bass of cosson busness. Reuter (2006) reports that for IPOs underwrtten by dfferent nvestent banks fro 996 to 999, a fund anager s holdng of an IPO shortly after the offerng s postvely related to ts cosson payents to the lead underwrter of the IPO. Goldsten et al (2006) post that "...cossons consttute a convenent way of chargng...for...tely access to nforaton, prorty handlng of dffcult trades and hgher allocatons of IPO shares." SEC Cossoner Paul Atkns has publcly stated that t s perssble for IPO allocatons to be based on custoer relatonshps. 5 If the lnkage between allocatons of underprced IPOs and cosson busness s too drect, however, then t s a volaton of certan securtes laws and regulatons and self-regulatory organzaton rules such as NASD Rule Ths rule prohbts an NASD eber fr fro sharng, drectly or ndrectly, n the profts or losses n any account of a custoer. To date, the fnance lterature has not addressed the econoc consequences of allocatng IPOs n return for cosson busness. To the degree that soe of the oney left on the table flowed back to underwrters through ether plct or explct proft-sharng arrangeents, ths would suggest that the structure of the underwrtng ndustry allowed ) soe underwrters to acheve total copensaton that exceeded copettve levels, and/or ) ssuers and ther executves to receve addtonal benefts, such as optstc analyst coverage 4 The quotaton s fro page 5 of the Acceptance, Waver and Consent (AWC) No. CAF03000 subtted to the NASD by Robertson Stephens. See press release , the SEC coplant aganst Robertson Stephens, and the AWC for detals on the Robertson Stephens case. 5 As quoted n the Blooberg News artcle of October 3, 2004 by Judy Mathewson, U.S. SEC Proposes New Intal Publc Offerng Rules. 3

6 of ther stock and favorable allocatons of hot IPOs nto personal brokerage accounts. Although there s wdespread agreeent aong practtoners that IPOs have been allocated at least partly on the bass of cosson busness, t s unclear whether ths was based prarly on cossons pad over a long perod of te or over a short perod n close proxty to specfc IPOs. 6 Furtherore, cosson revenue s the product of shares traded and the cosson per share, and the pact of IPO-related tradng on volue has not been docuented. Reuter (2006) fnds that there s a postve relaton between the cossons pad to a gven lead underwrter over a long perod of te and the utual fund s holdngs of recent IPOs fro that underwrter. Our paper exanes the effect of oney left on the table by IPOs on the tradng volue of the ost lqud stocks n the days surroundng the offer date. Thus, we are testng the jont hypothess that ) oney left on the table n IPOs affects cosson revenue, ) soe of the hgher cosson revenue occurs through hgher volue, and ) there s a short-run effect on volue. Bookbuldng, also known as a fr cotent contract, has been the donant ethod for sellng IPOs n the U.S. for any years. All IPO allocaton data are confdental n the U.S., although there have been several acadec studes utlzng such data (e.g., Aggarwal (2000), Boeher, Boeher, and Fshe (2005), and Hanley and Wlhel (995)). The bggest obstacle for any research on ths topc s the avalablty of detaled IPO allocaton and cosson data. In ths study, we use an nnovatve eprcal desgn to solve ths data avalablty ssue. In the proft-sharng vew of IPO allocatons, an nvestor wll receve a large allocaton of a hot IPO f t generates ore cosson revenue. To boost ts cosson rankng, an nvestor ay engage n stock churnng, defned for the purposes of ths paper as tradng wth cosson generaton as the only ntent. Other tradng that an nvestor ay engage n to generate cossons s ore subtle. For exaple, an nvestor could engage n portfolo 6 See, for exaple, Aaron Lucchett, SEC probes rates funds pay for cossons, Wall Street Journal, Septeber 6, 999, p. C. 4

7 rebalancng and te the tradng around IPO dates. An nvestor could also ove routne tradng that s not te-senstve to around IPO dates. For expostonal convenence, we use the ter IPO-related tradng for all tradng wth a whole or partal purpose of generatng cossons to affect IPO allocatons. If the purpose of IPO-related tradng s to generate cossons that transfer profts fro IPO recpents back to the nvestent bankng fr, there s an ncentve to structure the trades n a anner that nzes the leakage to other arket partcpants. Leakage can be reduced by decreasng tradng costs due to bd-ask spreads and prce pact. A varety of tradng strateges could be eployed to nze ths leakage. One echans would be to sultaneously subt buy and sell orders for the dentcal block of stock wth two dfferent securtes frs. For alost all concevable strateges, tradng hghly lqud stocks would be preferred, n order to nze bd-ask spreads and prce pact costs, and to avod the attenton that would coe fro tradng a large block of a less lqud stock. To capture IPO-related tradng, we use the tradng volue of the 50 ost actvely traded stocks. We choose the top 50 stocks for each tradng day based on the rank of a stock s average tradng volue for the past 20 tradng days, after excludng stocks wth hgh volatlty or a prce of below fve dollars. For the 3,499 IPOs durng our saple perod fro 993 to 200, we aggregate the oney left on the table by IPOs by offer dates, and obtan a te seres of the daly aount of oney left on the table. Wth controls for arket oveents, a te trend, and calendar-related patterns n tradng volue, we eploy an autoregressve odel wth four lags to study the relaton between the daly tradng volue of the 50 ost lqud stocks and the aount of oney left on the table by IPOs. If short-run cosson generaton s an portant factor n IPO allocaton, there should be a postve relaton between the aount of oney left on the table and the tradng volue of lqud stocks around the IPO dates. Because of changes n IPO practces, we partton our saple perod nto three subperods: the pre-nternet bubble perod ( ), the nternet bubble perod (999 5

8 2000), and the post-nternet bubble perod (200). For all three subperods, each $ bllon left on the table durng the sx tradng days begnnng on day t generates abnoral volue n the 50 ost lqud stocks of between 2.7% and 4.% on day t. The average aount of oney left on the table durng a sx-day wndow for the three subperods s, respectvely, $07 llon, $756 llon, and $72 llon. Our pont estates thus ply that IPO-related tradng ncreased turnover n the 50 ost actvely traded stocks by a statstcally nsgnfcant 0.4% durng , a statstcally sgnfcant 2.0% durng , and a statstcally nsgnfcant 0.2% durng 200. Snce the 50 ost actvely traded stocks account for approxately 25% of aggregate arket volue, f other stocks were not affected by IPO-related tradng, these nubers suggest that even durng the bubble years aggregate volue was boosted by only 0.5% by IPO-related tradng. Ths suggests that the effect on aggregate tradng volue s econocally nsgnfcant n noral arket condtons, but had a statstcally sgnfcant yet odest effect durng the bubble years. Ths s the central fndng of our paper. The cossons generated fro the ncrease n the tradng volue durng the bubble perod are econocally portant. The extra tradng volue of 2% per day for the lqud stocks would result n an addtonal $656,000 per day n cossons f we assue an average cosson of 0 per share. 7 Ths $656,000 per day n cossons, however, represents only 0.52% of the $26 llon per day left on the table durng the bubble perod, a uch lower payback rato than the 30% or even 65% kckbacks revealed n the CSFB regulatory case. There are several reasons to beleve that our estate of the share of profts flowng back to underwrters s based downwards. Hgher cossons can be generated by ether tradng ore shares or through hgher cossons per trade. We only capture cossons 7 The average cosson rate of 0 s based on a weghted average of 6 per share pad by utual funds and 50 or ore pad on soe trades by hedge funds. Mutual funds receved a uch larger proporton of IPO allocatons than hedge funds dd durng our saple perod. 6

9 generated by hgher tradng volue. In order to generate cossons at a gven underwrter, nvestors ay sply drect tradng to ths underwrter rather than to another entty (such as an electronc councaton network (ECN) or crossng network), wth no ncreental tradng occurrng. Investors ay also trade less lqud stocks, but subt buy and sell orders sultaneously wth dfferent brokers to tgate the arket pact. Most portantly, we only easure the short-run tradng volue that s nduced by rent-seekng nvestors n pursut of IPO allocatons. Our fndngs copleent those of Reuter (2006). Our eprcal evdence suggests that there s not only a relaton between long-ter cosson busness and IPO allocatons (Reuter s fndng), but also a short-run relaton durng the bubble perod between the aggregate aount of oney left on the table and aggregate tradng volue. 2. Data, the etrc for IPO-related tradng, and suary statstcs 2.. Data We use the Securtes Data Copany s (SDC) new ssues database to dentfy IPOs fro 993 to 200. All unt offerngs, Aercan Depostory Recepts (ADRs), Real Estate Investent Trusts (REITs), and closed-end funds are excluded. We also exclude banks and savngs and loans (SIC and 672) and all IPOs wth an offer prce of less than $5. We also exclude all IPOs that are not ncluded n the Center for Research n Securty Prces (CRSP) database. 8 The transacton data used to calculate tradng volue for all stocks coe fro the TAQ database. For each stock, transactons that were executed after the arket close and/or 8 We use the CRSP database to check the IPO offer date and frst-day closng prce. The IPO offer dates reported n the SDC database are often one day earler than the actual frst tradng date (the prcng date usually s the day before the actual tradng date but after the arket close). We use the date when the IPO frst appears n the CRSP database as the offer date when there s only a one-day dfference between the SDC database and the CRSP database. When the dfference s ore than one day apart, the New York Stock Exchange s Trade and Quote (TAQ) database and Yahoo! are used to verfy the dates. 7

10 on regonal exchanges are excluded because the lqudty condtons are usually worse n afterarket tradng and/or on regonal exchanges The etrc for capturng IPO-related tradng We use the tradng volue of the top 50 lqud stocks to capture IPO-related tradng. Ths etrc s constructed as follows. Frst, for each tradng day, we rank all stocks based on the average of the past twenty tradng days ntra-day quote-to-quote return standard devaton. Second, we exclude stocks wth a prce below $5 or wth a volatlty rank hgher than 2,500, where the stock wth the lowest volatlty has a rank of one. These screens elnate roughly two-thrds of CRSP-lsted stocks on any gven day. Stocks wth a low prce or hgh volatlty are unlkely to be good canddates for IPO-related tradng because of ther hgh rsk and lts on cossons per share pad on low prced stocks. Thrd, we calculate the share volue for each reanng stock, durng whch transactons that were executed after the arket close or on regonal exchanges are excluded. For stocks lsted on NASDAQ, we dvde the volue by two to reflect the dfferent conventons of reportng volue on NASDAQ versus the Aercan and New York Stock Exchanges. We then calculate the ean and standard devaton of the daly volue for the past twenty tradng days for each stock. For any tradng day, f the dfference between a stock s current tradng volue and the past twenty day s average s ore than four tes greater than ts past twenty-day standard devaton of volue, the stock s excluded. Ths excludes about 3% of the saple. The reason for dong so s because IPO-related tradng s unlkely to ncrease a lqud stock s daly volue by ths agntude. Soe non-ipo related reasons, such as stock splts or sgnfcant news, ay cause such draatc ncreases n daly tradng volues. To nze the nose n our etrc, we exclude those stocks for those specfc days. Fnally, for each tradng day (day t), all reanng stocks are ranked based on the past twenty-day s average daly volue. The 50 stocks wth the hghest volue are dentfed. We use past volues, nstead of current volues, to rank stocks to avod any potental look-ahead bas. The total tradng volue of these 50 ranked stocks, denoted as TVOL50, s then used as 8

11 the etrc to capture IPO-related tradng on day t. Although IPO-related tradng s ore lkely to be assocated wth large lqud stocks, our choce of the top 50 stocks s soewhat arbtrary. It s plausble that stocks ranked aong the top 200 or 500 could also be good canddates, especally when fund anagers erely try to te tradng otvated by portfolo rebalancng to around IPO dates. Each top stock ranked by tradng volue would capture the IPO-related tradng wth a postve probablty. But t s plausble that the hgher the rank, the hgher the probablty. Meanwhle, stock tradng volues are very volatle, and the daly volue of any gven stock has a lot of nose. So, f we vew the IPO-related tradng as a sgnal we want to capture, we need to nclude a certan nuber of stocks n our easure n order to ncrease the sgnal-to-nose rato. The addton of each stock along the rank of tradng volue would potentally capture ore of the IPO-related tradng, but at a decreasng rate. There are no clear rules that allow us to deterne the axu sgnal-to-nose rato. We use TVOL50 to try to acheve the close-to-optu sgnal-to-nose rato Suary statstcs We partton our saple perod nto three subperods: the pre-nternet bubble perod ( ), the nternet bubble perod ( ) and the post-nternet bubble perod (200). We report the suary statstcs of daly tradng volues of all stocks and the 50 ost lqud stocks n Table. For the three subperods, the nuber of stocks traded per day does not change uch 7,390 stocks for the pre-nternet bubble perod, 7,745 stocks for the nternet bubble perod and 7,26 stocks for the post-nternet bubble perod. However, tradng volue has ncreased draatcally, partly due to stock splts and partly due to hgher turnover. For exaple, the ean daly total tradng volues of all stocks for the three subperods are, respectvely, 65,,496, and,993 llon shares (after dvdng NASDAQ volue by two). For the top 50 stocks (TVOL50), the ean daly total tradng volues are 02, 322, and 53 9 To ake sure better etrcs are not excluded, we also repeated our analyss usng the top 30 stocks, or rankng stocks based on both volue and the bd-ask spread. The results (not reported) are slar but slghtly weaker. 9

12 llon shares, respectvely. The standard devaton of total daly tradng volue has also ncreased over te, although by a lower percentage than the ean has ncreased. Note that the top 50 stocks are selected based on the past twenty day s tradng volue, and they do not necessarly capture the ost heavly traded 50 stocks of the current day. The suary statstcs for IPOs are reported n Table 2. We have 3,499 IPOs n the nne-year saple perod, of whch 2,620 went publc durng the pre-nternet bubble perod, 803 went publc durng the nternet bubble perod, and only 76 went publc durng 200. The suary statstcs for the whole saple and for the dfferent subperods that are reported n Panel A of Table 2 are consstent wth what has been reported n the lterature. We also report the daly suary statstcs of our IPO saple n Panel B of Table 2. Except for the post-nternet bubble perod, there are on average ore than.5 IPOs per day, and there are IPOs on ore than half of the tradng days. There s extree varaton n IPO actvty fro day to day. For exaple, durng the nternet bubble perod, the standard devaton of the aount of oney left on the table s $285 llon per day, whle the ean s only $26 llon per day. Note that all of the oney left on the table fgures exclude the effect of overallotent optons, and the nuber of shares offered s easured as the doestc tranche only. Thus, our estates of the oney left on the table are conservatve. Another notceable feature about IPOs s the day of the week pattern, as shown n Fgure. The lead underwrter and the ssung fr usually fnalze the offer prce and allocate shares to nvestors the day before tradng starts. To avod weekend uncertantes, IPOs rarely start to trade on Mondays. For the other four weekdays, slghtly ore frs start tradng on Thursday and Frday. The frst-day returns also deonstrate a day of the week pattern, wth ean frst-day returns rsng fro Tuesday through Frday. 0 0 The frst-day returns on Mondays are donated by a few outlers because of the sall nuber of IPOs that went publc on Monday. The lower frst-day returns on Tuesdays and Wednesdays relatve to Frdays are probably due to a tendency to delay deals on whch there s buyer resstance fro the latter part of the prevous week untl Tuesday or Wednesday of the followng week. 0

13 3. The effect of oney left on the table on tradng volue 3.. The odel The suary statstcs n Table ndcate that stock-tradng volue s very volatle, and the etrc that we use to capture IPO-related tradng s farly nosy. Durng the nternet bubble perod, for exaple, the coeffcent of varaton (standard devaton dvded by the ean) of total daly tradng volue for the Top 50 stocks s 34 percent. Therefore, t s portant to control for the pact on tradng volue of factors that are unrelated to IPO actvty. The lterature on tradng volue has focused on the conteporaneous relatons between volue and prce oveents (see e.g. Karpoff (987), Capbell, Grossan, and Wang (992), He and Wang (995), Andersen (996), and Llorente, Mchaely, Saar, and Wang (2002)). To control for the te trend n volue, we use Date _ Index as an explanatory varable n our regressons, where Date _ Index s the sequental nuber of each tradng day (t for day t ) dvded by 2268, the total nuber of tradng days n our saple perod. (For the rest of ths paper, the value of a varable s easured on day t unless stated otherwse.) The te seres of tradng volues used n ths paper s a statonary process after de-trendng, whch s consstent wth the lterature (e.g., Andersen (996) and Llorente et al (2002)). The te seres of TVOL50 also deonstrates a correlaton wth general arket condtons n addton to the te trend. We use the nonal level of the S&P 500 ndex to control for ths relaton. The lterature and the analyss of our data also suggest that tradng volues deonstrate calendar-related patterns. IPO actvty, as ndcated n Fgure, also shows day of the week patterns. We use four weekday dues (Tuesday through Frday) and eleven onth dues (January through Noveber) as controls for calendar-related patterns. The volue lterature suggests a strong relaton between tradng volue and prce volatlty (Jones, Kaul, and Lpson (994)). IPOs on the frst day also have asyetrc betas n up and down arkets (Chan and Lakonshok (992)). We use the S&P 500 ndex return and

14 ts absolute value, R and R, to control for arket-wde prce oveents. In su, we use the followng autoregressve odel: Volue = α + η * Date _ Index + η * S & P = * Month + β * R + γ * Money + ε 2 + β * R 2 = + 4 λ * Weekday 4 = δ * Volue () In the odel, the dependent varable, Volue, s the natural log of TVOL50 for day t ultpled by 00. Ths enables us to nterpret any change of Volue n percentage ters. Four lagged varables of Volue are used to reove the autoregressve part of the TVOL50 etrc. The varable Money, easured n hundreds of llons of year 2000 dollars (year 200 s unadjusted), s used to capture the oney left on the table by IPOs n a wndow around day t. We eploy two dfferent easures for the aount of oney left on the table. We frst use the daly aount of oney left on the table by IPOs for the day before the current day ( Money ), the current day ( Money 0 ), and the next nne days ( Money + through Money +9 ). The second easure we use s the aggregate aount of oney left on the table for varous wndow lengths around day t. If our hypothess s correct, we would expect that the coeffcents on Money are postve. The portant goal for the use of daly oney left on the table varables s to gauge the tng of the pact of IPO actvty on volue. We nclude one lagged oney left on the table varable for the daly IPO actvty easure. Regulatory nvestgatons of CSFB ndcate that cosson payents fro hedge funds peaked wthn a narrow wndow relatve to when soe hot IPOs started tradng, reflectng explct proft-sharng agreeents. 2 We nclude the Ths s the sae approach that Naranjo and Nalendran (2000) use to easure the unexpected tradng volue n the U.S. Dollar Geran Deutsche Mark foregn exchange arket. 2 Page 8 of the NASD Regulaton, Inc. Letter of Acceptance, Waver, and Consent No. CAF02000 wth CSFB states Payent of nflated cossons ostensbly for brokerage servces nvolved at least 300 Custoer 2

15 oney left on the table on day t to test whether t was a coon practce for there to be ex post proft-sharng after the IPO. The use of oney on the table on day t + to day t + 9 s based on the assupton that nsttutonal nvestors are able to forecast whch IPOs wll be hot deals several days n advance, and that IPO allocatons are affected by cossons generated n the days edately pror to the IPO. The partal adjustent lterature as well as dscussons wth ndustry partcpants suggests that ths s a reasonable assupton Regresson results and analyss We estate the regresson odel specfed n equaton () for the three subperods. The regresson results for the daly IPO actvty easures are reported n Table 3. The coeffcents for the control varables are consstent wth our expectatons. The postve coeffcents for Date _ Index durng the pre- and nternet bubble perods capture the ncrease n tradng volue over te. S & P500 also explans part of the varaton n tradng volue over te. The te varaton n volue n 200 s captured by Date _ Index, S & P500 and the eleven onth dues. Volue also ncreases when the arket s volatle, and ths s captured by the sgnfcant coeffcent for R n all three subperods. For exaple, the coeffcents on R and R for the pre-nternet bubble perod ply that a % daly arket return s assocated wth a 7.9% ncrease n volue relatve to volue n a flat arket. The coeffcent on R s negatve durng the pre- and nternet bubble perods, reflectng the Accounts. Durng the last quarter of 999, over 3000 trades were done at these excessve cosson rates and hundreds of trades were effected wth a cosson rate of $.00 per share or ore. Over 90% of the excessve cosson transactons executed on the day of, the day before, or the day after a CSFB anaged IPO, were done by accounts that were allocated shares by CSFB n that hot IPO. 3 In unreported results, we have analyzed the ablty of forecasts of frst-day returns ade n an ndustry newsletter (The IPO Reporter) to predct realzed frst-day returns on IPOs fro Each week, ths newsletter assgned an openng consensus preu on a scale of ¼ to 5+ for ost IPOs durng the followng two-to-three weeks. Alost all IPOs wth frst-day returns of 00% or ore were gven 5 or 5+ ratngs several weeks n advance of the offer date (frequently pror to the start of the road show). 3

16 asyetrc relaton between volue and prce oveents n up and down arkets. The frst two lags of the volue varable account for the autocorrelaton n tradng volue, consstent wth our expectatons. The oney left on the table on the day before the current day (day t ) has no sgnfcant pact on the current day volue (day t volue) for all three subperods. Ths result ndcates that explct proft-sharng arrangeents wth ex post settlng up allegedly used by soe ebers of the CSFB sales force were not a wdespread practce. The oney left on the table varables for the rest of the ten days fro t to t + 9 dsplay sgnfcantly postve coeffcents for soe days durng the pre- and the nternet bubble perods. For the pre-nternet bubble perod, only the coeffcent for Money + 2 s sgnfcant. For the nternet bubble perod, the coeffcents for Money 0, Money + and Money + 5 are statstcally sgnfcant at the % or 5% levels. For no subperods are any of the Money + 6 to Money + 9 coeffcents sgnfcantly dfferent fro zero. Ths suggests that oney left on the table s assocated wth hgher abnoral tradng volue durng a sx-day perod pror to the IPO offer date. Ths s consstent wth the proft-sharng hypothess. However, we fnd lttle support for the proft-sharng hypothess for the post-nternet bubble perod none of the coeffcents durng ths perod are sgnfcant. It should be noted that the regulatory scrutny of IPO allocaton practces was frst publczed n Deceber 2000, so t s ndeed possble that a structural shft occurred. The coeffcents for the oney left on the table varables durng the nternet bubble perod suggest that IPOs affect the tradng volue on and before the offer dates, but that there s no evdence of ex post settng up. Rather than focusng on each day separately, n Table 4 we aggregate the oney left on the table by IPOs for a rollng wndow of three dfferent lengths: [ t, t + 2], [, t + 5] [ t, t + 9] t and. We re-estate the equaton () regresson odel by replacng the daly oney varables wth the aggregated varable. The coeffcents for the control varables n Table 4 are 4

17 slar to those n Table 3, and are not reported. The coeffcents for the aggregated oney left on the table varables wth dfferent aggregaton wndows are postve for all three subperods. They are only statstcally sgnfcant for the nternet bubble perod, however. For ths subperod, all three aggregated varables are sgnfcant at the % level. It should be noted that the pont estates are slar for all three subperods n Table 4, but the standard errors are saller n the nternet bubble perod because there s uch ore varaton n the explanatory varable as shown n Panel B of Table 2, allowng ore precse paraeter estates. Besdes statstcal sgnfcance, the coeffcents for the oney left on the table varables also suggest that IPO-related tradng captured by lqud stocks s econocally portant durng the nternet bubble perod. To assess the econoc portance, we assue that new ssues appear wth an equal frequency and all days are average days and we use a sx-day aggregaton wndow. Based on the nubers reported n Table 2, we would have $26 llon (the ean daly aount of oney left on the table) 6 (the nuber of days n the wndow perod) = $756 llon left on the table for an arbtrarly chosen sx-day wndow durng the nternet bubble perod. Ths ndcates that IPO-related tradng could cause a / 00 = 2.04 percent ncrease n the tradng volue on day t, where we dvde by 00 because n the regressons the oney left on the table s easured n $00 llons. For the other two subperods, our Table 4 pont estates ply that oney left on the table by IPOs durng a sx-day wndow ncreased turnover n the 50 ost actvely traded stocks by a statstcally nsgnfcant 0.4% (ean daly oney left on the table fro Table 2 of $8 llon/00 * 6 days * 0.4) durng and 0.2% ($2 llon per day /00 * 6 days * 0.29) durng 200. On an average tradng day durng , the 2.04 percent ncrease n volue attrbutable to rent-seekng actvty would translate nto 6.56 llon shares and $656,000 addtonal cossons f the average per share cosson s 0. For the three-day and the ten-day wndows, the ncreental tradng cossons on a 0 per share bass would be 5

18 $499,000 and $566,000, respectvely. Ths s consstent wth the regresson results wth daly oney left on the table varables. The ten-day wndow of [, t + 9] t ncludes days beyond day t + 5 for whch oney left on the table n the future does not have uch pact on the current day tradng. Ths suggests that nvestors try to act durng the week (fve tradng days) n antcpaton of a hot IPO, and that the sx-day wndow better captures the pact of the oney left on the table on current day tradng volue. The above estates are conservatve. Our etrc does not capture all IPO-related tradng, and the aggregated aount of oney left on the table durng a sx-day wndow affects not only the current day tradng volue, but also the volue over a longer te perod when rent-seekng behavor s present (Reuter (2006)). But we beleve that ths s suffcent to show that these nubers are econocally not trval. The regulatory settleents and dscussons wth practtoners suggest that only hedge funds, whch were allocated approxately 7% of the shares n several of the IPOs featured n regulatory settleents, regularly pad hgh per share cossons wth explct proft-sharng arrangeents. Mutual funds, whch are regulated, are not alleged to have pad extreely hgh per share cossons. Our estate that IPO-related rent-seekng actvty durng led to a 2.04% ncrease n the tradng volue of the ost lqud stocks s lower than the 0% ncrease n aggregate tradng volue that Rtter and Welch (2002) conjecture. Ths s partly due to the fact that we purposely stay conservatve n our above calculatons, and we only easure tradng over a short perod around the IPO. However, Rtter and Welch ay overestate the effect of rent-seekng behavor on aggregate tradng volue to the degree that trades that would have occurred anyway are erely redrected to ntegrated securtes frs that have hot IPOs to allocate rather than to ECNs or other venues where there are no IPOs to hand out. Furtherore, to the degree that proft sharng was pleented va hgher cossons per share rather than va extra tradng, there would be a saller effect on volue. 6

19 For the nternet bubble perod, the 2.04% ncrease n tradng volue per day ples only a 0.52% payback of the $26 llon per day of oney left on the table f we assue an average cosson of 0 per share. Ths estate s far lower than the 30% or even 65% payback ratos alleged n the CSFB regulatory settleent. Knowledgeable practtoners have suppled to us guesstates of the payback rate durng the nternet bubble rangng fro a low of 5% to a hgh of 30%. Our lower payback rate estate s partly due to the fact that our estate s based downwards. Specfcally, wash sales and excessve tradng of less lqud stocks are not ncluded, and we are only estatng the short-run relaton. Our fndng suggests that ost of the paybacks occurred over a longer te perod. In other words, cossons durng the past year, nstead of just ths week s cossons, affect next week s IPO allocatons. 4. Are the results for the nternet bubble perod drven by changes n arket condtons? Our regresson results show that each $ bllon left on the table results n 2.7 to 4.% hgher tradng volue of the top 50 lqud stocks. However, one could argue that other factors ay be the drvng force behnd the coeffcents on the oney varables n equaton (). One alternatve hypothess s that the nforaton envronent for the arket vares over te. When the overall dsperson of prvate nforaton (dsagreeent aong nvestors) s hgh, tradng wll be ore actve. Meanwhle, the ncreased heterogenety of opnons would also nduce hgher IPO underprcng. Ths would nduce a postve coeffcent for the oney varable. Alternatvely, nvestent banks and the ssung copanes ght prefer to te the offerng to concde wth a perod when tradng s actve. Ths would also nduce a postve coeffcent for the oney varable n a regresson setup such as that n equaton (). 4 Both alternatve hypotheses suggest that we could have an otted varable proble. 4 We thank the anonyous referee and Kent Woack for suggestng these alternatve hypotheses to us. 7

20 That s, besdes the lagged volues on the rght hand sde of the regressons, other arket condton varables could be correlated wth the oney varable, and ottng the could cause the estate of the oney varable coeffcent to be based. To address these concerns, n ths secton we perfor two further tests: we re-estate equaton () wth controls for changes n the nforaton envronent and wth controls for arket tng. 4.. Regresson Results wth Controls for Changes n the Inforaton Envronent We use two easures to control for changes n the nforaton envronent. The frst easure we use s the logarth of the daly return volatlty for the past fve days (day t-5 to day t-) of the top 50 lqud stocks, denoted as LN _ STD. Hgher nforaton asyetry and ore actve tradng of the top 50 lqud stocks would be assocated wth hgher volatlty, so we expect a postve coeffcent for LN _ STD. We use the estator proposed by Parknson (980) to calculate the daly return varance. Ths easure s constructed as follows. We frst calculate the daly return varance for each of the top 50 lqud stocks for the past fve days usng the daly hgh and low prces. 2 5 H 0.36 P t Parknson _ VAR = ln 5 j (2) L = Pt In equaton (2), Parknson _ VAR j s the varance of stock j easured over the past fve days (day t-5 to day t-). P and H t P are the ntraday hgh and low prces of day L t t ( =,2,..., 5 ) for stock j. The advantage of the Parknson extree value ethod of calculatng stock varances s that t requres 80% less data copared to the tradtonal easures that use the daly closng prces to acheve the sae effcency n the varance estaton. Usng the estates for the ndvdual stocks we calculate the equally weghted average of the daly return varance for the top 50 stocks. Fnally, we take the natural logarth of the square root of the average daly return varance. That s, on any gven day t, LN _ STD s calculated as follows: 8

21 50 LN _ STD = ln Parknson _ VAR j (3) 50 j= The ean (standard devaton) for LN _ STD s (0.23) for , (0.24) for and -3.8 (0.23) for 200, respectvely. Note that these statstcs are expressed n natural logarths, and the average volatlty (daly return standard devaton) for the three subperods s 2.28%, 3.44% and 4.6%, respectvely. The second easure, PESPRD, s the average percentage effectve spread of the top 50 lqud stocks for the past fve days. Hgher nforaton asyetry would result n greater bd-ask spreads for the top 50 lqud stocks. So we expect that PESPRD wll capture the te varaton n the nforaton envronent. The percentage effectve bd-ask spread s estated usng the TAQ database. To obtan the percentage effectve spread, we frst atch each transacton wth the latest quote that s at least fve seconds pror to the trade. The dollar effectve spread s defned as the absolute dfference between the transacton prce and the d-pont of the quote ultpled by two. The percentage effectve spread s the dollar effectve spread scaled by the average of the bd and ask quotes, expressed n percentages. We frst calculate the daly average percentage effectve spread for each stock, and then calculate the average for the past fve days. We fnally take the average of the percentage effectve spread of the top 50 stocks for the past fve days to obtan PESPRD. For exposton purposes, we ultply PESPRD by 00 n the regressons so that t s expressed n bass ponts. The ean (standard devaton) for PESPRD (n bass ponts) s 5.34 (4.27) for , 8.60 (.07) for and 7.04 (2.6) for 200, respectvely. The decrease n the ean value of the bd-ask spread fro to s consstent wth less adverse selecton due to a lower proporton of tradng by nfored nvestors, possbly due to ore churnng. Snce we expect less IPO-related churnng n 200, however, the contnued decrease n the ean value of the bd-ask spread cannot be plausbly explaned by ths. In 9

22 addton, the huge drop n the percentage bd-ask spread (by ore than 50% fro the frst to the last subperod) s too large to be explaned by erely an ncrease n IPO-related churnng. The regresson odel ncludng the arket condton varable(s) s as follows: Volue = α + η * Date _ Index + η * S & P500 + λ * Weekday + = * Month + β * R 2 + β * R + δ * Volue + γ * Aggregate _ Money[0,5] + θ * Info _ Envronent + ε 2 4 = 4 = (4) We use the logged volatlty and the percentage effectve spread both separately and jontly to replace the varable Info_Envronent. The regresson results are reported n Table 5. We only report the results usng the oney left on the table over the sx-day aggregaton wndow. All the control varables have slar coeffcents to those reported n Table 3, and are not reported. The coeffcent on the logged volatlty s always postve when used alone, and s statstcally sgnfcant for the pre- and post-nternet bubble perods. The coeffcent on the percentage effectve spread s postve when used alone, and s argnally sgnfcant durng the nternet bubble perod. The Table 5 results suggest that, even though we control for conteporaneous arket returns, the nforaton envronent stll has an pact on the current day s tradng volue. For exaple, f the daly return volatlty of the top 50 stocks s ncreased fro 3.44% to 4.44% (approxately one standard devaton), ths % ncrease fro the ean, when used alone to control for the changes n arket condtons, would cause a statstcally nsgnfcant 0.92% ncrease n the current day s tradng volue durng the nternet bubble perod. 5 If the percentage effectve spread s used alone, an ncrease of bass pont (one standard devaton) n the past fve day s average percentage effectve spread would cause a argnally sgnfcant =3.59 ln(4.44/3.44), where 3.59 s the regresson coeffcent n the ddle panel of Table 5. When LN _ STD s ncluded, the coeffcent on volatlty, s slghtly reduced but reans sgnfcant at the % level. R, whch helps to capture the pact of the arket-wde 20

23 .9% ncrease n the current day s tradng volue. For all odel specfcatons and all subperods, however, the coeffcents for the oney varable rean qualtatvely unchanged copared to those n Table 4. Furtherore, our results for the oney left on the table coeffcents are robust to usng three- or ten-day wndows. Ths suggests that the relaton dentfed n Table 4 between the oney left on the table and the volue of the top 50 lqud stocks s not drven by changes n the nforaton envronent Regresson Results wth Controls for Market Tng To further dsentangle the arket tng hypothess and the proft sharng hypothess, we add another varable, the nuber of IPOs, n the regresson odel reported n Table 6: Volue = α + η * Date _ Index + η * S & P = * Month + β * R 2 + β * R λ * Weekday δ * Volue + γ * Aggregate _ Money[0,5] + θ * Nuber _ IPOs + ε 2 = = (5) The new varable, Nuber _ IPOs, s the nuber of IPOs n our saple on day t. If the relaton between the volue of the top 50 lqud stocks and IPO actvty s anly drven by nvestent banks arket tng abltes, the nuber of IPOs would better capture ths relaton than the oney left on the table, whch s jontly deterned by the nuber of IPOs, the sze of the offerngs and the underprcng. In other words, f the relaton between volue and IPO actvty s drven by arket tng rather than proft sharng, we would expect that the coeffcent on the oney left on the table would be draatcally reduced. We report the regresson results n Table 6, where, as n Tables 4 and 5, we do not report the coeffcents on the control varables n the nterest of brevty. For all three subperods, both the oney left on the table and the nuber of IPOs are postvely related to the volue of the top 50 lqud stocks. The coeffcents on the nuber of IPOs and the oney left on the table are only sgnfcant, at the 5% level and the % level, respectvely, durng the nternet bubble perod. Most portantly, the ncluson of ths addtonal varable has only a 2

24 odest effect on the coeffcent of the oney left on the table varable durng , reducng t fro the 0.27 (t=3.99) that we report n Tables 4 and 5 to 0.2 (t=3.34) n Table 6. Ths suggests that the proft sharng we observe durng the nternet bubble perod s not entrely drven by arket tng. The nuber of IPOs, however, s econocally just as portant as the oney left on the table n explanng the volue of the 50 ost lqud stocks. Snce the coeffcent on the nuber of IPOs durng the bubble perod s 0.99, and there are.59 IPOs per day on average, the dfference n volue between an average day and a day wth zero IPOs s.57%. Ths s approxately the sae effect as oney left on the table: the coeffcent of 0.2 ples that there s a dfference of.59% n volue between an average day (where the oney left on the table varable has a value of $756 llon) and a day wth zero oney left on the table. 5. Concluson In recent years the vast ajorty of IPOs have been arketed usng the bookbuldng process. Ths process gves the lead underwrter consderable dscreton n settng the offer prce and allocatng shares of the ssung fr. Acadec researchers have generally assued that the lead underwrter uses ths allocaton dscreton n the best nterest of the ssuer to tgate nforaton asyetry. However, recent regulatory nvestgatons, as well as dscussons wth practtoners, ndcate that allocatons of underprced shares are at least partly based on cosson busness fro nvestors. Cosson revenue equals the product of shares traded and the cosson per share. Cosson revenue can be tabulated over short perods edately surroundng IPOs (hgh-frequency data) or over longer perods (low-frequency data). Ths paper exanes whether there s a hgh-frequency relaton between the oney left on the table by IPOs and tradng volue. IPO allocaton data are confdental, and we use an ndrect easure of abnoral cosson revenue the abnoral tradng volue of lqud stocks to capture IPO-related tradng. 22

25 We fnd that $ bllon left on the table durng the sx tradng days coencng wth day t (days t to t+5 ) generates abnoral volue n the 50 ost lqud stocks of between 2.7% and 4.% on day t, although only durng the nternet bubble perod s ths pont estate relably dfferent fro zero. Ths relaton between the oney left on the table and abnoral tradng volue on lqud stocks just pror to the offer date suggests that the gross spread s not the only source of copensaton for IPO underwrters. Our pont estates ply that durng the tradng volue of the 50 ost lqud stocks was 2.0% hgher than t would have been f rent-seekng behavor was not occurrng. Snce these stocks represented about 25% of aggregate tradng volue, ths would suggest that aggregate volue was boosted by 0.5%, a uch lower nuber than the 0% ncrease that Rtter and Welch (2000) conjectured. Our results are consstent wth the proft sharng hypothess that durng the bubble perod, rent-seekng actvty occurred whereby securtes frs wth hot IPOs to allocate receved cosson revenue fro nvestors n return for favorable IPO allocatons. Our fndng of only odest effects on tradng volue suggests that to the extent that sgnfcant cossons flowed to the brokerage frs n return for favorable IPO allocatons, the data ndcate that the an nstruent was the cosson per share rather than tradng volue. Furtherore, our fndng that tradng n the 50 ost lqud stocks rses only odestly edately pror to oney beng left on the table suggests that the IPO allocatons were prarly deterned by low-frequency cosson busness as suggested by Reuter (2006) and/or explct proft sharng arrangeents usng hgh cossons per share, rather than the hgh-frequency tradng volue relatons that we nvestgate. Other evdence corroborates ths nterpretaton. Insttutonal tradng volue dd not fall draatcally n the post-2000 years, even though less oney has been left on the table by IPOs. Furtherore, average nsttutonal cossons per share have fallen fro 5.9 cents per share n 2000 to 4.7 cents per share n 2004, accordng to data fro Greenwch Assocates reported n Goldsten et al (2006). 23

26 References Aggarwal, Reena, 2000, Stablzaton actvtes by underwrters after ntal publc offerngs, Journal of Fnance 55, Andersen, Torben G.., 996, Return volatlty and tradng volue: An nforaton flow nterpretaton of stochastc volatlty, Journal of Fnance 5, Benvenste, Lawrence M., and Paul A. Spndt, 989, How nvestent bankers deterne the offer prce and allocaton of new ssues, Journal of Fnancal Econocs 24, Boeher, Beatrce, Ekkehart Boeher, and Rayond P. H. Fshe, 2005, Do nsttutons receve favorable allocatons n IPOs wth better long run returns? Journal of Fnancal and Quanttatve Analyss, forthcong. Capbell, John Y., Sanford J. Grossan, and Jang Wang, 992, Tradng volue and seral correlaton n stock returns, Quarterly Journal of Econocs 08, Chan, Lous, and Joseph Lakonshok, 992, Robust easureent of beta rsk, Journal of Fnancal and Quanttatve Analyss 27, Chen, Hsuan-Ch, and Jay R. Rtter, 2000, The seven percent soluton, Journal of Fnance 55, Clff, Mchael, and Davd Dens, 2004, Do IPO frs purchase analyst coverage wth underprcng? Journal of Fnance 59, Goldsten, Mchael, Paul Irvne, Eugene Kandel, and Zv Wener, 2006, Brokerage cossons and nsttutonal tradng patterns, Babson College workng paper. Hanley, Kathleen Wess, and Wlla J. Wlhel, Jr., 995, Evdence on the strategc allocaton of ntal publc offerngs, Journal of Fnancal Econocs 37, He, Hua, and Jang Wang, 995, Dfferental nforaton and dynac behavor of stock tradng volue, Revew of Fnancal Studes 8, Jones, Charles M., Gautu Kaul, and Marc L. Lpson, 994, Transactons, volue, and volatlty, Revew of Fnancal Studes 7, Karpoff, Jonathan M., 987, The relaton between prce changes and tradng volue: A survey, Journal of Fnancal and Quanttatve Analyss 22, Llorente, Gullero, Ron Mchaely, Gdeon Saar, and Jang Wang, 2002, Dynac volue-return relaton of ndvdual stocks, Revew of Fnancal Studes 5, Loughran, T, and Jay R. Rtter, 2002, Why don t ssuers get upset about leavng oney on the table n IPOs? Revew of Fnancal Studes 5,

27 Loughran, T, and Jay R. Rtter, 2004, Why has IPO underprcng changed over te? Fnancal Manageent 33 (3), Luccett, Aaron, 999, SEC probes rates funds pay for cossons, Wall Street Journal, Septeber 6 ssue, C. Mathewson, Judy, 2004, U.S. SEC proposes new ntal publc offerng rules, Blooberg News, October 3. Naranjo, Andy, and M. Nalendran, 2000, Governent nterventon and adverse selecton costs n foregn exchange arkets, Revew of Fnancal Studes 3, Newey, Whtney K., and Kenneth D. West, 987, A sple, postve se-defnte, heteroskedastcty and autocorrelaton consstent covarance atrx, Econoetrca 55, Parknson, Mchael, 980, The extree value ethod for estatng the varance of the rate of return, Journal of Busness 53, Reuter, Jonathan, 2006, Are IPO allocaton for sale? Evdence fro the utual fund ndustry, Journal of Fnance, forthcong. Rtter, Jay R., and Ivo Welch, 2002, A revew of IPO actvty, prcng, and allocatons, Journal of Fnance 57, The IPO Reporter, , New York: Thoson Fnancal. 25

28 Table Suary Daly Statstcs for Tradng Volues Ths table reports suary daly statstcs for tradng volues for all CRSP-lsted stocks and stocks n the etrc that s used to capture IPO-related stock tradng the top 50 stocks based on lagged tradng volue. The saple perod s fro 993 to 200. The TAQ database s used to calculate the daly tradng volue of each stock. We exclude transactons that are executed on regonal exchanges and/or after the arket close. For stocks lsted on NASDAQ, we dvde the volue by two. We report the statstcs separately for three subperods. Std s the standard devaton. Mean daly volue per stock (n 000s) Mean total daly volue (n 000s) Mnu total daly volue (n 000s) Maxu total daly volue ( n 000s) Std of total daly volue (n 000s) Mean nuber of stocks per day Panel A: All Stocks 8 65,246 25,09,698, ,698 7,390 TVOL_50 2,032 0,579 7,773 34,66 50, Panel B: All Stocks 93,495,5 626,049 2,763,978 36,702 7,745 TVOL_50 6,435 32,766 03,73 758,875 09, Panel C: 200 All Stocks 280,992, ,668 3,290,32 394,34 7,26 TVOL_50 0,628 53,393 60, ,99 22,

29 Table 2 Suary Statstcs on IPOs Ths table reports suary statstcs for the IPO saple for the saple perod fro 993 to 200 and for three subperods. Panel A of the table reports descrptve statstcs of the IPO saple, and Panel B reports daly statstcs. The frst-day return s defned as the return fro the offer prce to the frst-day close prce. Money left on the table s defned as the dfference between the offer prce and the frst-day close prce ultpled by the nuber of shares offered (doestc tranche only), assung no exercse of overallotent optons. Both the proceeds and the oney left on the table are adjusted usng the CPI to year 2000 dollars (year 200 s not adjusted). Postve IPOs refer to the IPOs that have postve frst-day returns. In Panel B, all daly statstcs are uncondtonal, except for the aount of oney left on the table n the last row, whch s condtonng on at least one IPO on that day. Panel A: Overall Nuber of IPOs 3,499 2, Mean nuber of shares offered ( 000) 5,282 3,869 7,98 25,459 Mean proceeds (llon dollars) Mean frst-day return (%) Mean oney left on the table (llon dollars) Panel B: Nuber of Tradng Days 2,268, Nuber of Days wth IPOs, Mean Nuber of IPOs per Day Mean Nuber of Postve IPOs per Day Mean Daly Money Left on the Table (llon dollars) Standard Devaton of Daly Money Left on the Table (llon dollars) Mnu Daly Money Left on the Table (llon dollars) Maxu Daly Money Left on the Table (llon dollars) Mean Daly Money Left on the Table Condtonng on at least IPO (llon dollars)

30 Table 3 Regresson of Tradng Volue on Daly Money Left on the Table by IPOs Ths table reports te-seres regresson results for all IPOs for three subperods. The odel specfcaton s as follows: Volue = α + η * Date _ Index + η * S & P = 9 = * Month γ * Money + β * R + ε 2 + β * R 2 = + 4 λ * Weekday 4 = δ * Volue In the regresson, all varables, unless suggested by the subscrpts, are easured on day t, where t s fro to 2,268 (the total nuber of days n our saple perod). The dependent varable Volue s the natural log of the daly total volue of the top 50 stocks on NYSE, Aex and NASDAQ ranked by lagged volue, ultpled by 00. Date _ Index s the sequental nuber of day t dvded by the total nuber of tradng days (2,268). S & P500 s the level of the S&P500 ndex. The weekday dues, Weekday through Weekday 4, correspond to Tuesday to Frday. The eleven onthly dues, Month through Month, refer to January to Noveber. The arket return on day t, R s the return on the S&P500 Index, and R s the absolute value of the arket return. The Money varable s the suaton of the total aount of oney left on the table of all IPOs on day t +, where = -, 0,..., 9. The aount of oney left on the table s easured as the dfference between the frst-day close prce and the offer prce ultpled by the nuber of shares offered, and are adjusted to year 2000 dollars (year 200 s not adjusted). For presentaton purpose, the oney left on the table s easured n $00 llon (ths varable s easured n llons n the prevous table). The sgnfcance of the oney left on the tables varables s ndcated usng ** (sgnfcant at the 5% level) and *** (sgnfcant at the % level). T-statstcs, corrected for heteroskedastcty and autocorrelaton (Newey and West (987)), are n parentheses. We use four lags n correctng the standard errors for possble autocorrelaton. The F-statstcs for the regressons, whch are all sgnfcant at the % level, are otted. The nuber of observatons (the nuber of tradng days) for the three subperods are respectvely,56, 504, and

31 Varable Intercept ,789.5 Date _ Index S & P500 Tuesday Wednesday Thursday Frday January February March Aprl May June July August Septeber October Noveber R R (3.20) (7.99) (4.09) (7.54) (7.68) (-0.32) (5.4) (-2.70) (-.76) (.03) (2.86) (4.62) (2.8) (3.57) (5.0) (8.22) (2.08) (6.2) (3.44) (-0.70) (.47) (4.8) (2.90) (0.20) (3.3) (.27) (-0.00) (3.4) (2.07) (0.03) (3.2) (2.66) (0.06) (.78) (0.28) (-0.45) (.3) (0.33) (-0.70) (.62) (0.2) (-.65) (.27) (-0.57) (-2.65) (.96) (0.6) (-0.48) (2.84) (.34) (-.22) (.02) (0.27) (-.6) (-.80) (-.32) (.68) (0.20) (6.03) (4.49) 29

32 Table 3 Contnued: Varable Volue Volue 2 Volue 3 Volue 4 Money Money 0 Money + Money +2 Money +3 Money +4 Money +5 Money +6 Money +7 Money +8 Money +9 (0.87) (6.62) (5.06) (2.96) (.79) (-.28) (.2) (0.22) (-0.74) (0.59) (-0.53) (0.28) (-0.76) (-0.57) (.00) *** -.2 (0.02) (3.50) (-0.87) *** 0.68 (-0.38) (2.98) (0.57) 2.30*** (2.79) (-0.24) (-0.33) (-0.28) (.5) (0.4) (.50) (0.0) (-.4) ** -.69 (-0.72) (2.27) (-0.85) (-0.4) (-0.68) (-0.55) (.27) (-0.3) (-0.52) (.8) (0.23) (-0.6) (-.3) (-.09) (0.64) 30

33 Table 4 Regresson of Tradng Volue on Aggregate Money Left on the Table by IPOs Ths table reports te-seres regresson results for all IPOs for three subperods. The odel specfcaton s as follows: Volue = α + η * Date _ Index + η * S & P = * Month + β * R + β * R + γ * Aggregate _ Money[, j] + ε 2 2 = + 4 λ * Weekday 4 = δ * Volue In the regresson, the dependent varable, Volue, whch s the natural log of the daly total volue of the top 50 stocks on NYSE, Aex and NASDAQ ranked by lagged volue, ultpled by 00, s the sae as n Table 3. All the control varables are also the sae as those n Table 3. For the easure of oney left on the table, we use the aggregated aount of oney left on the table (easured n unts of $00 llon) fro day t + to day t + j. Three dfferent aggregaton wndows around day t (.e., = 0 ) are used. Aggregate _ Money[0,2] s the aggregate aount of oney left on the table by IPOs over a wndow of [ t, t + 2], for exaple. The other two easured are slarly denoted. The coeffcents for all the control varables are slar to the ones reported n Table 3 and are otted. The sgnfcance of the aggregate oney left on the tables varables s ndcated usng *** (sgnfcant at the % level). T-statstcs, corrected for heteroskedastcty and autocorrelaton (Newey and West (987)), are n parentheses. We use four lags n correctng the standard errors for possble autocorrelaton. The F-statstcs for the regressons, whch are all sgnfcant at the % level, are otted. The nuber of observatons (the nuber of tradng days) for the three subperods are respectvely,56, 504, and 248. Varable Aggregate _ Money[0,2] *** 0.76 Aggregate _ Money[0,5] Aggregate _ Money[0,9] t t t (.4) (3.64) (0.60) *** 0.29 (.32) (3.99) (0.30) *** 0.43 (.7) (3.25) (0.50) 3

34 Table 5 Regresson of Tradng Volue on Aggregate Money Left on the Table by IPOs wth Controls for Inforaton Envronent Change The odel specfcaton s as follows: Volue = α + η * Date _ Index + = * Month + γ * Aggregate + η * S & P500 + λ * Weekday + β * R 2 _ Money [0,5] + θ * Info _ Envronen 32 + β * R 2 4 = 4 + δ * Volue = t + ε The regresson odel s dentcal to that reported n Table 4, except that we add the varable(s) Info _ Envronent as a control for the changes n the nforaton envronent. We use two varables, the logarth of the equally weghted daly return standard devaton ( LN _ STD ) of the 50 ost lqud stocks for the past fve days relatve to day t ( t -5 to t ) and the average percentage effectve spread for the past fve days ( PESPRD, expressed n bass ponts) for the 50 ost lqud stocks. We follow Parknson (980) to estate the return standard devaton. In the table below we report the coeffcents for the aggregated oney varables (easured n unts of $00 llon) and the arket condton varables only. The coeffcents for all of the other control varables are slar to those reported n Table 3. The sgnfcance of the varables s ndcated usng *** (sgnfcant at the % level), ** (sgnfcant at the 5% level), and * (sgnfcant at the 0% level). T-statstcs, corrected for heteroskedastcty and autocorrelaton (Newey and West (987)), are n parentheses. Subperod Varable No Control for Wth Wth Wth Info_Envronent LN _ STD PESPRD Both Aggregate _ Money[0,5] LN _ STD PESPRD Aggregate _ Money[0,5] LN _ STD PESPRD Aggregate _ Money[0,5] LN _ STD PESPRD t t t (.32) (.4) (.26) (.40) 9.7*** 2.30*** (3.25) (3.62) (0.23) (-.33) 0.27*** 0.28*** 0.30*** 0.30*** (3.99) (4.24) (4.37) (4.38) (0.68) (-0.09).9*.24* (.74) (.78) (0.30) (0.27) (0.30) (0.25) 9.86* 24.7** (.88) (2.00) (0.02) (-0.93)

35 Table 6 Regresson of Tradng Volue on Aggregate Money Left on the Table by IPOs and Nuber of IPOs The odel specfcaton s as follows: Volue = α + η * Date _ Index + = * Month + η * S & P β * R 2 + β * R λ * Weekday δ * Volue + γ * Aggregate _ Money [0,5] + θ * Nuber _ IPOs + ε 2 = = Copared to the regresson n Table 4, the addtonal varable Nuber _ IPOs s the nuber of IPOs on day t. In ths table we report the coeffcents for the aggregated oney (easured n unts of $00 llon) varables and the varable Nuber _ IPOs. The coeffcents for all of the other control varables are not reported. The sgnfcance of the varables s ndcated usng *** (sgnfcant at the % level) and ** (sgnfcant at the 5% level). T-statstcs, corrected for heteroskedastcty and autocorrelaton (Newey and West (987)), are n parentheses. Varable Aggregate _ Money[0,5] *** 0.5 Nuber _ IPOs t (.29) (3.34) (0.6) ** 2.8 (0.23) (2.39) (.50) 33

36 Fgure Day of the Week Pattern of IPOs Ths fgure deonstrates the exstence of a day of the week pattern n both the nuber of deals and the average frst-day return for IPOs. We group IPOs by year. Fgures. and.2 report the nuber of IPOs and the ean frst-day return on dfferent weekdays, respectvely. For each year n each fgure, one bar represents one weekday fro Monday through Frday fro left to rght. Over the saple perod, the ean frst-day return and the nuber of IPOs on each weekday are as follows: 35.87% and 44 (Monday), 24.57% and 79 (Tuesday), 25.83% and 737 (Wednesday), 23.93% and 96 (Thursday), and 3.99% and,083 (Frday). Because of relatvely few IPOs on Monday, the ean frst-day return of Monday s senstve to outlers (for exaple, there are only two IPOs on Monday for year 2000, and the average frst-day return s 258%). For expostonal purposes, the frst-day return on Monday s set as zero n Fgure Fgure. Day of the Week Pattern for IPOs Nuber of IPOs Fgure.2 Day of the Week Pattern for IPOs Mean Frst-Day Returns (%) (Return on Monday s set to zero)