AN EMPIRICAL INVESTIGATION OF IPO UNDERPRICING IN CHINA

AN EMPIRICAL INVESTIGATION OF IPO UNDERPRICING IN CHINA Lu T Senor Fellow/Executve Manager Research Center Shangha Stock Exchange Summary Chna enjoys the hghest level of ntal returns of ntal publc offerngs (IPOs) n the world, wth an average market-adjusted ntal return of 132.49%, usng data on 354 new ssues n Chna from 1 January 1999 to 31 December 2002. Ths paper advances an explanaton of ths phenomenon. It proposes some possble reasons for the hgh returns and fnds that most of the hypotheses based on nformaton asymmetry, such as the wnner's curse, sgnalng, market feedback and the bandwagon hypothess, fal to fully explan the phenomenon of underprcng. The paper fnds only weak evdence for the wnner's curse hypothess. Only the IPO sze has a statstcally sgnfcant postve relatonshp wth the level of the market-adjusted ntal returns. The paper argues that the underprcng of IPOs s the result of the nteractve process between the offer prce and the tradng prce on the secondary market, whle the nformaton asymmetry hypotheses only focus on the determnaton of the offer prce. A new explanaton focusng on the nterplay of supply and demand n both prmary and secondary markets s advanced and tested usng the sample data. The results show that IPO underprcng n Chna s the result of overprced secondary market shares under the condton of de facto segmented markets. IPO underprcng s postvely related to the tradng prce n the secondary market,.e., the hgher the P/E rato of the market (used as a proxy for tradng prce level n the secondary market), the more underprcng Ths paper was frst publshed as the Chna Project Report No. 4 by the Chna Project, a research project run jontly by the Royal Insttute of Internatonal Affars and Cambrdge Unversty (http://www.ra.org/pdf/research/asa/ InvestgatonofIPO_Chna.pdf). I am grateful to Stephan Green, Stu Danan, Zeng Gang, Wang Fenghua, and Zhang Bo for ther valuable comments. I would also lke to acknowledge fnancal support from the Manson House Scholarshp of the Lord Mayor of the Cty of London.

that occurred n the IPO. Chna's prmary and secondary markets are n practce segmented,.e., n general money from one does not flow to the other. Under these condtons, the returns n the two markets show lttle tendency to converge. Ths theory suggests that secondary market reform s essental to mature the prmary market. Among all the reform measures, makng non-tradable shares tradable and ntroducng shortsellng or a day-tradng mechansm are most mportant to lowerng secondary market prces to more reasonable levels. 2

Contents 1 Introducton 1 2 A Hstory and Insttutonal Framework 2 3 Key Statstcal Characterstcs 4 3.1 Data and Methodology 4 3.2 Descrptve Statstcs 8 3.3 Key Features Compared to Other Markets 10 4 Emprcal Analyss Based on Informaton Asymmetry 10 4.1 Hypothess Explanng IPO Underprcng 10 4.2 Models and Emprcal Results 15 5 Towards a New Explanaton 17 6 Concluson and Polcy Implcatons 22 References 25

Lst of tables and fgures Table 1 Equty Structures of Chna's Lsted Companes, 1997-2002 28 Table 2 Number of IPOs n Chna by the year of ssung, 1999-2002 28 Table 3 Number of IPOs n Chna by the month of ssung, 1999-2002 29 Table 4 Correlatons between Monthly IPO Number and Monthly Return of Shangha A Index, 1999-2002 29 Table 5 Number of IPOs by Industry, 1999-2002 30 Table 6 Number of IPOs by Prcng Method, 1999-2002 31 Table 7 Number of IPOs by Share Allocaton Method, 1999-2002 32 Table 8 Key Descrptve Statstcs of IPOs n Chna, 1999-2002 33 Table 8 Key Descrptve Statstcs of IPOs n Chna, 1999-2002 (Contnued) 34 Table 9 Intal Returns and Market-Adjusted Intal Returns of IPOs n Chna, 1999-2002 35 Table 10 Odds-Adjusted Intal Returns and Odds-&-Market- Adjusted Intal Returns of IPOs n Chna, 1999-2002 35 Table 11 Annual Return and Market-Adjusted Annual Return of IPOs n Chna, 1999-2002 36 Table 12 Weghted IPO Intal Returns n Chna (weghted by IPO Value), 1999-2002 36 Table 13 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Industres, 1999-2002 37 Table 14 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Prcng Method, 1999-2002 38 Table 15 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Share Allocaton Method, 1999-2002 39 Table 16 Average Intal Returns of IPOs n 33 countres or markets 40 Table 17 Dstrbuton of IPO Intal Return n the US from 1980-2000 41 Table 18 Correlaton Matrx of the Varables used n Model 1 and Model 2 41 Table 19 Estmates for Model 1 and Model 2 of IPO Underprcng n Chna 42 Table 20 Correlaton Matrx of the Varables used n Model 3 and Model 4 43 Table 21 Estmates for Model 3 and Model 4 of IPO Underprcng n Chna 44 Fgure 1 Equty Structures of Chna's Lsted Companes, 2002 45 Fgure 2 Number of IPOs n Chna by the year of ssung, 1999-2002 45 Fgure 3 Number of IPOs n Chna by the month of ssung, 1999-2002 46 Fgure 4 Monthly IPO Number and Return of Shangha A Index, 1999-2002 46 Fgure 5 Dstrbuton of IPO Market-adjusted Intal Returns n Chna, 1999-2002 47 Fgure 6 Dstrbuton of IPO Market-adjusted Annual Returns n Chna, 1999-2002 47 Fgure 7 Dstrbuton of IPO Intal Returns n the US from 1990-1996 48

1 Introducton Intal publc offerng (IPO) underprcng exsts n almost every stock market, although the degree of underprcng vares from country to country. Numerous studes document the phenomenon, showng that nvestors n IPOs, on average, earn abnormally hgh frst day return, and a number of hypotheses have been advanced and tested aganst the data of both developed and emergng markets. IPO underprcng has been noted as one of the ten puzzles facng fnancal research snce there s lttle consensus n ths feld (Brealey & Myers, 1991). Ths paper studes IPO underprcng n Chna's stock market. IPO underprcng n Chna s severe compared wth other countres. The average amount of underprcng (measured by the frst day or ntal return, whch s defned as the dfference between frst day closng prce mnus the IPO prce dvded by the IPO prce) of 354 IPOs durng the perod from 1 January 1999 to 31 December 2002 was 135.01%, whle the market-adjusted ntal return was 132.49%. 1 Another strkng feature s that there s absolutely no rsk n Chna's IPO market. In the same perod, all IPOs had postve ntal returns. 59% of the 354 new ssues had returns above 100%. 86.4% got ntal returns more than 50%. Only 3.7% of the 354 new ssues got frst day postve returns below 25%. Ths paper attempts to explan why IPO underprcng n Chna s so severe by frst testng the man hypotheses advanced for mature markets. The results show that theores based on nformaton asymmetry fal to explan Chna's IPO underprcng, though the wnner's curse does exst n Chna. The paper advances a new explanaton by focusng on the nterplay of supply and demand n both the prmary and secondary markets. The results show that IPO underprcng n Chna s the result of overprced secondary market prces under the condton of de facto segmentaton between the prmary and secondary markets. IPO underprcng s postvely related to the tradng prce n the 1 Other studes have found hgher returns for the early stage of Chna's stock markets. For example, Su and Flesher (1999) found the average ntal return was 948.59% n 1990-1995, whle Datar and Mao (1998) found 388% for 1990-1996. 1

secondary market,.e., the hgher the P/E rato of the market (used as a proxy for tradng prce level n the secondary market), the more underprcng that occurred n the IPO. Chna's prmary and secondary markets are n practce segmented,.e., n general money from one does not flow to the other. Under these condtons, the returns n the two markets show lttle tendency to converge. The remander of the paper s organzed as follows. A bref hstory and some nsttutonal detals are provded n Secton II. Secton III ntroduces some of the key statstcal characterstcs of IPO underprcng n Chna, compared wth other markets. Secton IV examnes the man hypotheses and tests them aganst a data set of 354 new ssues. In Secton V, the paper adopts a new approach to explan Chna's IPO underprcng phenomenon. Secton VI concludes wth summary of the fndngs and ther polcy mplcatons. 2 A Hstory and Insttutonal Framework Chna's stock markets date back to the 1860s when brokerage frms emerged n Shangha to market and trade shares of foregn companes (Lu, 1999). In the 1930s, the Shangha stock market was the largest n Asa for a tme. After the foundng of the socalst People's Republc of Chna, the Shangha Stock Exchange and two other exchanges were closed n 1949 and 1952 respectvely. Along wth Chna's reform and openng polcy, frms began to ssue shares agan n md-1980s and two stock exchanges the Shangha Stock Exchange and the Shenzhen Stock Exchange were establshed n 1990. There are several characterstcs of the share ssuance and lstng processes whch dstngush Chna's IPO market from that of other countres. Frst and foremost, most stock sales are partal sales. Ths may be explaned by the fact that the government stll needs to control lsted companes to mantan the country as a socalst country. However, the prvately controlled companes also do the same. As a result of the partal sale method, shares of lsted companes n Chna are categorzed nto two types: tradable shares and non-tradable shares. Non-tradable shares can be classfed n terms of ownershp nto three man types: state-owned shares, legal-entty-owned shares, and employee-owned shares. There are two types of shares lsted and traded n Chna's stock exchanges: A-shares and B-shares. Orgnally, A-shares were desgned for domestc Chnese nvestors and B-shares were exclusvely for foregners. However, recent developments have allowed domestc Chnese nvestors to trade B-shares and qualfed foregn nsttutonal nvestors (QFII) to nvest n A-shares. A-shares are traded n domestc currency (RMB Yuan), whle B-shares are traded n US dollars on the Shangha Stock Exchange and Hong Kong dollars on the Shenzhen Stock Exchange. Table 1 presents the varous proporton of the dfferent knds of shares n Chna's lsted companes. 2

At the end of 2002, non-tradable shares comprsed about two-thrds of the total shares. Most of the non-tradable shares were state-owned shares, accountng for more than 70% of the non-tradable shares. 17.3% of the total shares were legal-entty shares, whch are owned by state-owned enterprses (SOEs) and, n some cases, prvate companes. The tradable A and B shares make up, respectvely, about 26% and 3% of the total shares. It s worth notng that the tradable and non-tradable markets are segmented, and the A-share and B-share markets are segmented too. Non-tradable shares are usually traded at a prce around the net asset value per share, whch was 2.75 RMB Yuan per share on average at the end of 2002, whle the average last day closng prce of A shares n 2002 was 9.20 RMB Yuan per share. That s to say, the average A-share prce s 3.35 tmes that of the non-tradable share. The stuaton n the B share s smlar. On average, the prce of an A-share s more than two tmes that of the B-share of the same company. Second, the government controls the total IPO sze and process. Chna used a quota system for new share ssues before 2000. The quota (the aggregate amount of IPOs) was determned by the State Plannng Commsson and Chna Securtes Regulatory Commsson (CSRC) (or the People's Bank of Chna, thecentral Bank, n the early stages of the stock market). The quota was then allocated among the provnces and natonal mnstres and commssons, who chose whch frms could go publc. The CSRC made the fnal decson about whether an IPO was permtted. Seasoned equty offerngs (SEOs) also requred permsson from the CSRC. In 2000, the process was changed. Chna's Securtes Law (enacted n December 1998 but brought nto effect n July 1999) abolshed the quota system, though the CSRC's permsson s stll necessary for an IPO to take place. The new rules are called the "sancton system". Investment banks can choose or recommend frms to the CSRC for ssung and lstng. The CSRC does the formal examnaton. If the frm meets the formal crtera set by the CRSC, the CSRC wll then send the IPO applcaton to the IPO Audtng Commttee. The IPO Audtng Commttee s composed of CSRC offcals and outsde experts. The IPO Audtng Commttee wll decde whether or not to approve the IPO. Thrd, n terms of the prcng method of IPOs, the fxed P/E rato method was used before md-1999. Most IPOs' P/E rato was between 12 and 15. In July 1999, n the sprt of the Securtes Law, the CSRC enacted a rule whch permtted companes whch were ntendng to ssue more than 400 mllon total shares to negotate the IPO prce wth the underwrter. The 400 mllon total shares lmtaton was removed n Aprl 2000, allowng all frms to negotate the IPO prce. Snce 2001, the bookbuldng method has also become popular n Chna's prmary market. Ths nvolves the company and the underwrter determnng the prelmnary offer prces range (fle prce range). The underwrter wll then measure the demand of nsttutonal nvestors for these partcular shares, and revse the offer prce accordng to demand. 3

Fourth, the allocaton mechansm for IPO shares s very partcular compared wth other countres. There were numerous methods used to allocate new shares before 1996, such as applcaton forms, subscrptons related wth bank deposts, onlne blnd auctons, etc. From 1996 to md-1998, a lottery mechansm was used to allocate new shares, n whch subscrbers bd for a quantty of shares at a fxed offer prce. The odds of wnnng the lottery depends on how much money the subscrber used n hs subscrpton. The CSRC ntroduced another allocaton method durng 1998 and 1999 whch gave nvestment funds and strategc long-term nvestors (usually SOEs) the prorty n purchases of IPO shares. 1 Wthout jonng the onlne lottery, they were allocated about 25-75 of total new shares. However, the lottery method was also needed for these preferental nvestors when there was a strong demand for the IPO. A preferental method for secondary market nvestors was mplemented n 2000. Investors who already owned tradable shares could subscrbe to a quantty of new shares, ths quantty dependent upon the market value of ther shareholdngs. The lottery system also functons n the case of oversubscrpton. Few IPOs adopted the market value allocaton method n 2000 and 2001, but snce md-2002, most IPOs have used ths method. 3 Key Statstcal Characterstcs 3.1 Data and Methodology The sample data-set used n ths paper s comprsed of 354 companes whch ssued and lsted ther A-shares n Chna's stock market, ether at the Shangha Stock Exchange or the Shenzhen Stock Exchange, from 1 January 1999 to 31 December 2002. 2 Ths tme perod has chosen snce t was only from 1999 that IPO prces were negotated and not set admnstratvely. Before ths, the IPO prce was fxed and determned by the government, and the underprcng of IPOs was not a market phenomenon. Companes whch ssued shares before 1999 but lsted them n the sample perod are excluded from the sample. Three companes whch ssued shares n December 2002 but lsted n 1 There are exceptons for IPOs of less than 50 mllon total shares, where nvestment funds were not gven the prorty for IPO allocaton. For strategc nvestors, the stuaton was true for IPOs wth less than 400 mllon total shares. The restrcton for strategc nvestors was removed n Aprl 2000.Strategc nvestors were gven preferental treatment for all IPOs. 2 I do not dstngush shares lsted n the two exchanges n the followng analyss as the lstng crtera for both stock exchanges are the same, and t s the government, not exchanges, who decde the ssung or lstng processes. 4

2003 are ncluded. The prmary data source s from Guo Ta An (GTA) Informaton Technology Company's Chna's IPO Database, and the Wnd Informaton Company's Securtes Markets Database. I have also made thousands of correctons to ther data, and compled mssng nformaton for hundreds of observatons from other sources, usng data from Informaton Center and Lstng Department of the Shangha Stock Exchange, as well as from drect nspecton of the frms' IPO prospectuses. Table 2, Fgure 2, Table 3 and Fgure 3 summarze the number of IPOs on an annual and monthly bass. Durng the sample perod, there were an average of 88.5 IPOs per year. The number of IPOs peaked n 2000 wth a record of 124. Most IPO shares were lsted on the Shangha Stock Exchange snce the Shenzhen Stock Exchange was not allowed to lst new shares after late 2000. The number of IPOs usually reach ther lowest number n February because of the two-week Chnese Sprng Festval holday, and reach ther peak usually n July followng the dsclosure of annual report from January to Aprl and the one-week Labor Day holday n May. Contrary to the fndng of Ch and Padgett (2002), I fnd that there was a weak relatonshp between the monthly ndex returns and the number of monthly IPOs, as shown n Table 4 and Fgure 4. The hypothess that the CSRC chooses to launch IPOs when the market s performng well (.e., a bull market) s thus not supported by the evdence. The 354 companes are dvded nto sx ndustres, fnance, publc utltes, real estate, dversfed conglomerate, manufacturng, and commerce and servces. Table 5 reports the number of IPOs by ndustry durng 1999-2002. There were 222 manufacturng frms n the 354 sample IPOs, accountng for 62.7% of the total. The second largest ndustry was the dversfed conglomerates wth 68 IPOs, accountng for 19.2% of the total. Commerce and servces, and real estate companes follow the conglomerates, accountng for 8.5% and 6.2% of the total, respectvely. The fnance ndustry ranks last wth only 5 IPOs n the sample. Durng the sample perod, companes used two methods to prce ther IPOs: the fxed prce and the bookbuldng methods. Bookbuldng became popular n Chna after late 2001. Table 6 reports the number of IPOs by prcng method n the sample. There were 269 IPOs wth fxed prce, accountng for 76% of the total, whle there were 85 IPOs usng bookbuldng method, accountng for 24% of the total. Two man methods were used to allocate the offered shares when there was a huge demand. One was the lottery mechansm based on the amount of money subscrbers used to bd for IPO shares. The other was the lottery mechansm based on the market value of the tradable shares the subscrbers held. Many IPOs used both methods at the same tme. Table 7 presents the number of IPOs by the share allocaton method. 239 IPOs (67.5% of the total) used the lottery by money, 47 5

IPOs (13.3%) used the lottery by market value, 66 IPOs (18.6% of the total) used both methods, and only two IPOs used other methods not mentoned here. Intal returns to IPOs are measured usng the standard methodology, though I also ntroduce four other measures to explan Chna's specal stuaton. The ntal return of the IPO of stock "" s defned as: R = ( P 1 P 0 ) / P 0 where R s the ntal return of the IPO of the stock "", P 0 s the IPO offerng prce of stock "", and P 1 s the frst tradng day's closng prce of stock "". The market-adjusted (abnormal) ntal return of the IPO of stock "" s defned as: MAR = m ( 1+ R ) /(1 + R ) 1 where MAR s market-adjusted ntal return, between the IPO and the frst tradng date, whch s defned as: R m s the market ndex return durng the perod R m = ( Pm 1 Pm 0 ) / Pm 0 1 where P m0 s market's closng ndex on the day of the IPO, and P m1 s the market's closng ndex on the frst tradng day of the stock. In ths paper, Shangha A-share Index and Shenzhen A-share Index are used as correspondng benchmarks. The ntal returns weghted by the market value of the IPOs are also calculated. The weghted ntal returns are defned as: WR WR m = R = R MV m MV 1 /( n 1 /( n n = 1 MV ) n = 1 MV ) where WR and market-adjusted ntal return of stock "", whle WR m are, respectvely, the weghted ntal return and the weghted MV s the market value of the IPO of stock "", whch equals the offer prce multpled by the number of new shares ssued of stock "". Four new measures are ntroduced n the followng analyss whch are essental for measurng IPO underprcng n Chna. Snce there s always a large demand for IPO shares (as a result of hgh ntal returns), the lottery mechansm s used to allocate IPO shares. The odds of wnnng the 6

lottery are very low (usually below 1%). From the nvestors' pont of vew, the return on ther nvestment s not calculated by the ntal return on the IPOs, but by the ntal return on IPOs dvded by the total money they used to apply IPO shares. Therefore, the odds of wnnng the lottery become an mportant determnant of ther total returns. In Chna, the average subscrpton tme for an IPO s 4-5 days. That means nvestors need to put ther money n the prmary market for about one week (excludng the weekend when the market s closed) to apply for one IPO. Hence, an nvestor can apply to buy IPO shares many tmes wth the same money n a year. As a result, the annual nvestment return, whch undoubtedly nterests nvestors, can be calculated. For the above reasons, the concept of the odds-adjusted ntal return, odds-&-market-adjusted ntal return, annual return, and market-adjusted annual return are used n ths paper. These four measures are calculated as follows: OAR = R LotRate OMAR = MAR LotRate AnnR = R LotRate n j= 1 X j MAAnnR = MAR LotRate n j= 1 X j where LotRate s the odds of wnnng the lottery, OAR s the odds-adjusted ntal return, OMAR s the odds-&-market-adjusted ntal return, AnnR s the annual return, and MAAnnR s the market-adjusted annual return, whle X j s the money an nvestor can use to apply for an IPO at tme j, and n s the total tmes an nvestor can apply for IPOs n a year. X j s defned as: X X X 1 2 n = 1 = X (1 LotRate ) = X 1 n 1 (1 LotRate ) 7

There are about 240 tradng days n a year n Chna, so n can be defne as 48, that s, an nvestor can apply for IPOs 48 tmes wth the same money (mnus the money used to buy allotted IPO shares when successful) n a year. 1 3.2 Descrptve Statstcs Table 8 presents the key statstcs on the 354 sample IPOs. The average IPO prce durng the four years was 7.71 Chnese RMB Yuan, wth a maxmum of 36.68 Yuan and a mnmum of 2.2 Yuan. The average IPO quantty was 116.6 mllon shares, wth a maxmum of 5 bllon shares and a mnmum of 4 mllon shares. As to IPO's prce-earnng rato, the average P/E rato was 25.3, wth a maxmum of 74.2 and a mnmum of 12.1. The frst day closng prce was, on average, 2.3 tmes the average offer prce. There are several nterestng features of the odds of wnnng the lottery and the frst day turnover rates. The average wnnng probablty for the four years was 1.06%. The year 2001 saw the hghest rate of 2.59%, whle the lowest was only 0.17% n 2002. The man reason for the low lottery-wnnng rate n 2002 was a change n the share allocaton method. Before 2002, the vast majorty of IPOs were allocated by the amount of money subscrbers used for the subscrpton, whle most IPOs n 2002 were allocated by the market value of the tradable shares held by subscrbers. The average amount of money used for one IPO n Chna was 155.28 bllon Yuan, whle the average market value of the tradable shares subscrbers held was 510.25 bllon Yuan, and 224.84 bllon Yuan for the mxed method. As Table 8 shows, Chna may have the hghest turnover rate for the frst tradng day of new shares n the world. The average turnover rate was 60%, wth a maxmum of 84.6% and a mnmum of 5.2%. Ths phenomenon suggests that most nvestors n Chna's prmary market are only nterested n the prmary market tself, and not n long-term nvestment. In the early stages of Chna's stock market, the average tme elapsng between the IPO announcement and the frst day of lstng and tradng was qute long. In Su and Flesher's (1999) 1 Investors may subscrbe to more than 48 new ssues as they can dvde ther money nto several parts to apply for several new ssues at the same tne. The renvestment return of the ntal returns s not ncluded n the calculaton as the tme elapsng between an IPO and the frst tradng day vares between dfferent IPOs. 8

samples, t was 260 days for A-shares from 1990 to 1995. The fgure has dropped n recent years. As shown n Table 8, the average tme between the IPO announcement and the frst day tradng between 1999 and 2002 was 23 days, and 15 days for 2002. Table 9 reports the ntal returns and market-adjusted ntal returns of the sample offerngs. The average market-adjusted ntal return of the 354 IPOs was 132.49% wth a maxmum of 478.41% and a mnmum of 3.47%. On average, the market-adjusted ntal returns are slghtly lower than the ntal returns. However, the stuaton was dfferent for the years of 2001 and 2002. Ths suggests that most IPOs suffered from the market declne n 2001 and 2002 though they benefted from the market rse n 1999 and 2000. However, the return was very low when one consders the odds nvolved n the lottery. As shown n Table 10, the average odds-&-market-adjusted ntal return of the 354 IPOs was 0.79% wth a maxmum of 31.15% and a mnmum of 0.02%. Table 11 reports the annual returns and market-adjusted annual returns. The average annual returns and market-adjusted annual returns of the 354 samples were, respectvely, 35.7% and 38.0%. These rates were very hgh compared wth other types of nvestment n Chna. The tme-weghted one-year savngs nterest rate was only 2.36% durng the sample perod. The weghted returns of the above sx measures were also calculated, as Table 12 shows. The average weghted ntal return, market-adjusted return, odds-adjusted return, odds-&-marketadjusted return, annual return and market-adjusted annual return were 88.19%, 88.28%, 2.73%, 3.02%, 121.81% and 144.18%. It s nterestng that the weghted returns and market-adjusted returns were consderably lower than the unweghted ones, whle the weghted odds-adjusted and annual returns are sgnfcantly hgher than the unweghted ones. Ths may be explaned by the fact that IPOs wth large market values usually have lower ntal returns, and that IPOs wth a large market value have hgher lottery-wnnng rates. The average market-adjusted ntal returns and market-adjusted annual returns classfed by ndustres, prcng method and share allocaton method are presented n Tables 13, 14 and 15. In terms of market-adjusted ntal returns ranked n terms of ndustres, conglomerates rank frst and publc utltes rank last, whle manufacturng ranks frst and commercal and servce ndustry ranks last for the market-adjusted annual returns. There was no sgnfcant dfference for market-adjusted ntal returns between the fxed prce offerng and bookbuldng methods, though a large dfference exsted for market-adjusted annual returns. The average market-adjusted annual return of IPOs usng the bookbuldng exercse was 2.4 tmes that of IPOs usng the fxed prce method. 9

The stuaton for share allocaton method was smlar. There were lttle dfferences for marketadjusted ntal returns among the varous share allocaton methods, whle the market-adjusted annual returns for lottery by money, lottery by the market value of tradable shares, lottery both by money and market value, and other methods were, respectvely, 24.98%, 4.71%, 109.23%, and 23.02%. 3.3 Key Features Compared to Other Markets Hgh returns and an absence of any rsk are the two statstcal characterstcs that dstngush Chna from other markets. Su and Flesher (1999) found that the average ntal return of 308 IPOs n Chna durng 1990-1995 was 948.59%. Datar and Mao (1998) found that the average ntal return of 226 A-share ssues n Chna durng 1990-1996 was 388.0%. Lu and L (2000) found that the average market-adjusted return for the 781 stocks lsted on the Shangha and Shenzhen Stock Exchanges durng 1991-1999 was 139.4%. Ch & Padgett (2002) studed 668 new ssues n Chna from 1 January 1996 to 31 December 2000 and found an average market-adjusted ntal return of 129.16%. The average market-adjusted ntal return of my sample form 1999 to 2002 was 132.49%. Though all these fndngs show that IPO underprcng has been mprovng over the tme, t s stll very hgh compared wth other markets. Table 16 gves a summary of the average ntal returns (equally weghted) of IPOs n varous markets around the world. Chna ranks frst. The average ntal return of IPOs n Chna durng 1999-2002 was 3.3 tmes the average emergng markets' ntal return (excludng Chna) and 6.9 tmes that of developed countres. Another strkng feature of Chna's prmary market s that there s absolutely no rsk at all. Fgure 5 and Fgure 6 present the dstrbuton of the market-adjusted returns and the market-adjusted annual returns n the 354 samples. No company had negatve market-adjusted returns. Only 13 IPOs (3.7% of the total sample) got a return below 25%. 306 IPOs (86.4%) got a return over 50%, 209 IPOs (59.0%) got a return over 100%, and 61 IPOs (17.2%) got a return over 200%. As to market adjusted annual returns, 42 IPOs (11.9%) got a return below 5%, 141 IPOs (39.8%) got a return over 20%, whle 171 IPOs (48.3%) had a return between 5% and 20%. Ths stuaton s completely dfferent from other markets, such as the Unted States where many IPOs have negatve ntal returns as shown n Table 17 and Fgure 7. 4 Emprcal Analyss Based on Informaton Asymmetry 4.1 Hypotheses Explanng IPO Underprcng Academcs agree that fundamental market rsk, lqudty constrants and asset-prcng rsk 10

premum are unlkely to explan the unusual phenomenon of IPO underprcng, and have offered a number of dfferent hypotheses snce Stoll and Curley (1970), Relly (1973), and Logue (1973) frst documented the phenomenon. Most of the hypotheses, whch wll be tested n ths paper, are based on the problem of nformaton asymmetry. 4.1.1 Dfferentally-nformed Investors and the Wnner's Curse One mportant explanaton for IPO underprcng s the "wnner's curse". Rock (1986) argues that nformaton asymmetres ext between nformed and unnformed nvestors. Snce nformed nvestors are more lkely to buy new shares when they are underprced, then the amount of excess demand wll be hgher for the more underprced IPOs. So the unnformed nvestors face a wnner's curse: they are allocated only a fracton of the most desrable new ssues, whle they are allocated a large proporton of the least desrable ssues. That s to say, f they wn the allocaton, t s because the nformed nvestors do not want the shares. To keep the unnformed nvestors n the market, therefore, requres an addtonal premum (the underprcng of IPOs) suffcent to compensate them. The evdence of numerous studes s consstent wth the wnner s curse hypothess, though other explanatons also exst. Beatty and Rtter (1986) extend Rock s hypothess by ntroducng uncertanty about an IPO's market clearng prce. Beatty and Rtter argue that hgher uncertanty results n hgher underprcng. Ths theory suggests that small frms should have hgher IPO ntal returns snce the rsk assocated wth smaller frms s hgher than wth larger frms. In Chna, most IPOs are partal sales. Government or the legal enttes (most of them state-owned-enterprses, SOEs) own about two-thrds of a company's total equty after the IPO. The tradable shares are purchased by ndvduals, nvestment funds, and strategc long-term nvestors. As Ch and Padgett (2002) pont out, to keep the unnformed ndvdual nvestors n the market, the government has to underprce IPOs and leave much money on the table for the further development of the IPO market. To test the above theory, I adopted a smlar method used by Ch and Padgett (2002), defnng the percentage of tradable shares as the proxy for the sze of the nformaton asymmetry, and the IPO 11

sze as a proxy for the frm's rsk. 1 The offer sze s calculated by the offer prce multpled by the quantty of share ssued. Accordng to the wnner's curse theory, IPOs wth the fewer tradable shares or/and nvolvng smaller frms wll experence hgh underprcng. Hypothess 1: There s a postve relatonshp between the percentage of tradable shares and the market-adjusted ntal return. Hypothess 2: There s a negatve relatonshp between the offer sze and the market-adjusted ntal return. 4.1.2 Informaton Asymmetry and the Sgnalng Hypothess Welch (1989), Allen and Faulhaber (1989), Grnblatt and Hwang (1989), and Chemmanur (1993) have developed a seres of sgnalng models to explan IPO underprcng. These models are based on the nformaton asymmetres that exst between the ssuers and the nvestors. If the ssuers have superor nformaton than nvestors about the value of the IPO, ratonal nvestors fear a lemon problem: only ssuers wth a worse-than-average qualty wll be wllng to sell ther shares at the average prce (Welch and Rtter, 2002). Underprcng, whch s a cost that bad frms cannot proftably sustan and whch deters lower-qualty ssuers from mtatng, s an equlbrum outcome for ssuers to dstngush themselves from the pool of low-qualty ssuers and sgnal ther qualty to the nvestors. Some sgnalng models have examned the government's behavor n SOE IPOs and have argued that government ssuers underprce IPOs to sgnal the owner's fath and ts commtment to pro-market prvatzaton polces (Perott, 1995; Mok and Hu, 1998). Perott argues that the government may choose to retan a large percentage of a lsted companes and underprce a partal sale to sgnal ts ntent to commt to future pro-market prvatzaton polces. Mok and Hu argue that a hgh level of equty retenton by the government may reflect the owner s fath n the busness and thus lowers the ex-ante uncertanty, though t may also sgnal the neffcency of the frm's management. 1 Ch and Padgett (2002) defne the percentage of shares owned by the government and government-owned companes as a proxy for the sze of the nformaton asymmetry. 12

The testable hypotheses deduced from the sgnalng theores are as follows: 1 Hypothess 3: There s a postve relatonshp between the proftablty of the ssung frm and the market-adjusted ntal return. Hypothess 4: There s a negatve relatonshp between the percentage of government-owned or SOE-owned shares and the market-adjusted ntal return. In other words, there s a postve relatonshp between the percentage of tradable shares and the market-adjusted ntal return, as stated n Hypothess 1. 4.1.3 Informaton Gatherng and the Market Feedback Hypothess Another approach based on nformaton asymmetres s assumng that nvestors are more nformed than the ssuer, for example about the market demand for shares. In ths stuaton, the ssuer faces a placement problem. Benvenste and Spndt (1989), Benvenste and Wlhelm (1990), and Spatt and Srvastava (1991) argue that the underwrter may underprce the IPO to nduce nvestors to reveal ther valuatons of the company durng the pre-sale bookbuldng perod. Hanley (1993) also fnds that the underwrter does not fully adjust the IPO prce when demand s strong. As Welch and Rtter (2002) pont out, the underwrter must underprce ssues for whch favorable nformaton s revealed by more than those for whch unfavorable nformaton s revealed, and there wll only be a partal adjustment of the offer prce from the orgnal fle prce ranges. That s to say, those IPOs for whch the offer prce s revsed upwards wll be more underprced than those for whch the offer prce s revsed downwards. In Chna, the bookbuldng method was ntroduced n 2000. 24% of the IPOs n the 354 sample adopted ths method. It s nterestng that the underwrter adjusted the offer prce upward for almost all IPOs. Ths ncreases the dffculty of analyzng the bookbuldng effect on IPOs. On the 1 Many emprcal studes examned the relatonshp between the number of subsequent equty offerngs (SEOs) and the ntal returns of IPOs. I do not consder SEOs for two reasons. Frst, t s dffcult to examne the SEOs effects n the 4 year sample. Second, almost every SEO n Chna s a rght ssue for the shareholders, not for the publc, and t s underprced severely too. 13

assumpton that the ntal prce ranges of IPOs wth bookbuldng were determned usng the same method as IPOs whch used fxed prces, t can be nferred that IPOs wth fxed prces should be more underprced than the IPOs whch used bookbuldng. In other words, IPOs usng a fxed prce method wll be also adjusted upward f they adopt the bookbuldng method. Hypothess 5: IPOs whch use the fxed prce method are more underprced than IPOs whch use bookbuldng. 4.1.4 Informaton Cascade and the Bandwagon Hypothess Welch (1992) argues that an ssuer may underprce ts IPO to avod a negatve cascade. In an nformatonal cascade, nvestors make ther decsons by judgng the nterest of other nvestors. They only subscrbe to new shares when they beleve that the offerng s gong to be popular. That s to say, the IPO market may be subject to bandwagon effects (Rtter, 1998). A postve bandwagon or cascade means that the IPO s underprced, and vce versa. The hypothess s supported by Amhud, Hauser, and Krsh (2001). They found that IPOs tend to be ether undersubscrbed or hugely oversubscrbed, wth very few moderately oversubscrbed. The share allocaton method and nvestors' demand for shares can be used as proxes for the bandwagon effect n Chna's IPOs. The odds of the lottery reflect the nvestors' demand for the IPOs. It should be negatvely related to the degree of IPO underprcng. The lottery mechansms themselves may contrbute to underprcng for the cost to nvestors of the lottery based on money s dfferent from the cost of the lottery based on the market value of tradable shares held. Hypothess 6: There s a negatve relatonshp between the odds of wnnng the lottery and the market-adjusted ntal return. Hypothess 7: IPOs usng a lottery method based on money should have a hgher return than IPOs whch use the lottery based on the market value of tradable shares held by subscrbers. The above four hypotheses are based on nformaton asymmetres. There are other theores based 14

on symmetrc nformaton, such as the nvestment banker's monopoly power hypothess, the lawsut avodance hypothess, the ownershp dsperson hypothess, the tradng volume n the aftermarket hypothess, etc. (Rtter, 1998; Welch and Rtter, 2002) However, these hypotheses are not used n ths paper snce the nsttutonal framework s suffcently dfferent n Chna to make them redundant. 1 4.2 Models and Emprcal Results To test the above seven hypotheses, the followng emprcal models are used. Model 1: MAR = β 0 + β 1 IPOSIZE + β 2 PubOwn + β 3 ROE + β 4 LotRate + β 5 Fx Pr ce + β 6 LotMoney + β 7( k ) Indus ( k ) Model 2: OMAR = β 0 + β 1 IPOSIZE + β 2 PubOwn + β 3 ROE + β 4 Fx Pr ce + β 5 LotMoney + β 6( k ) Indus ( k) In the frst regresson, I use the market-adjusted ntal return (MAR) as the dependent varable, whle odds-&-market-adjusted returns (OMAR) s used as the dependent varable n Model 2. The LotRate s omtted n Model 2 snce the OMAR s calculated by MAR multpled by the odds of wnnng. The correlaton coeffcents of the varables are provded n Table 18. The ndependent varables used n the regresson are defned as follows: IPOSIZE (1-) PubOwn (2, 4 +) The logarthm of the offer value of an IPO, calculated as the ssung quantty of shares multpled by the offer prce The percentage of tradable shares 1 The tradng volume n the aftermarket hypothess, nvestment banker's monopoly power hypothess and the lawsut avodance hypothess are not applcable because the market-makng system, nvestment banker's monopoly power, class acton and dervatve lawsut arrangements do not exst n Chna. The ownershp dsperson hypothess s also less useful n Chna snce nearly all IPOs n Chna are partal sales and the ssuer stll controls the company after IPO. 15

ROE (3+) The return on equty of the frm a year before the IPO date FxPrce (5+) The dummy to show whether a frm adopts the fxed-prce method to prce ts IPO, 1-yes, 0-no LotRate (6-) The odds of wnnng the lottery, calculated as a percentage LotMoney (7+) The dummy to show whether an IPO s allocated based on a lottery by money, ncludng IPOs based on lotteres by both money and the market value of the tradable shares, 1-yes, 0-no Indus(k) Industry dummy, k = 1, 2,, 6, where 1 represents the fnance ndustry, 2 the publc utlty ndustry, 3 the real estate ndustry, 4 the dversfed conglomerates, 5 manufacturng, 6 commerce and servce ndustry, 1-yes, 0-no Note: fgures n ( ) are the related hypotheses to be tested. "+" represents an expected postve relatonshp, whle "-" represents an expected negatve relatonshp. The left-hand sde of Table 19 presents the OLS estmates for Model 1. The results are dsappontng. Only IPO sze has a sgnfcantly postve relatonshp to the market-adjusted ntal return. Ths means that the wnner's curse hypothess does hold n Chna's prmary market. I also fnd a postve relatonshp between the lottery mechansm by money and the market-adjusted ntal return at the sgnfcance level of 0.07. Ths ndcates that there are bandwagon effects to some extent n Chna. However, I do not fnd a negatve relatonshp between the lottery-wnnng rate and the ntal return as others dd (Lu and L, 2000; Ch and Padgett, 2002). 1 Ths can be explaned by the fact that the lottery-wnnng rate tself s determned by other varables used n the regresson. The argument s llustrated n the results of Model 2. I do not fnd any sgnfcant relatonshp between the percentages of tradable shares, the frm's ROE, the IPO prcng method and the market-adjusted ntal returns. The results allow us to reject the sgnalng and market feedback hypotheses. The rght sde of Table 19 reports the OLS estmates for Model 2. In fact, Model 2 s useful to test the relatonshp between the lottery-wnnng rate and other ndependent varables used n the 1 In fact, the lottery-wnnng rate s not a good varable for IPO underprcng as the odds tself may be determned by other varables used n the explanaton, as shown n the emprcal estmates n Model 2. 16

regresson snce the odds-&-market-adjusted ntal return s determned by the market- adjusted ntal returns multpled by the lottery-wnnng rate. The lottery-wnnng rate s a sgn of nvestors' demand for IPOs and contrbutes a great deal to the odds-&-market-adjusted ntal return. All ndependent varables except the ndustry dummes are sgnfcant n Model 2. There are postve relatonshps between the percentages of tradable shares, the IPO sze, the lottery by money and the odds-&-market-adjusted ntal return. The results show that there are hgher lottery-wnnng rates or lower demand for the IPOs wth a larger IPO sze, a larger tradable shares rato, and IPOs whch use the lottery money method. There are negatve relatonshps between the frm's ROE and the odds-&-market-adjusted ntal return. Ths ndcates that there are hgher demand or lower lottery-wnnng rate for the ssung frms wth hgher proftablty. The estmates of Model 2 also show IPOs whch use the fxed prcng method have a lower wnnng lottery rate than IPOs whch use bookbuldng. The reason for ths s the prces of IPOs wth fxed prces are relatvely low snce the offer prces of nearly all bookbuldng IPOs are adjusted upwards. 5 Towards a New Explanaton Academcs have so far explaned the underprcng puzzle by focusng on the determnaton of the offer prce. Snce the theores based on nformaton asymmetres cannot gve a reasonable explanaton of IPO underprcng n Chna, I try to advance a new explanaton by focusng on the nterplay of supply and demand n both the prmary and secondary markets,.e., focusng on both the offer prce and the tradng prce of the secondary markets. The hypothess advanced here s that IPO underprcng n Chna s the result of over-valued secondary market prces under the condton of segmented markets. 1 Ths explanaton has three nterrelated theoretcal assumptons. 1 It s dffcult to say whether the secondary market shares are over-valued. However, the market P/E ratos can be used for comparng the prce levels of dfferent markets. The average year-end market P/E rato n the Shangha Stock Exchange durng 1999-2002 s 41.86, whle the market P/E rato n the developed markets such as the New York Stock Exchange, the London Stock Exchange, the Frankfurt Stock Exchange and the Euronext, s usually around 20. 17

Frstly, that the secondary market tradng prces are overprced compared to the IPO prces. That s, IPO underprcng s postvely related to the tradng prce n the secondary market by controllng for other varables. If the market P/E rato s used as a proxy for the level of the secondary market prce, the hgher the P/E rato of the market, the more underprcng that occurred n the IPO. Hypothess 8: There s a postve relatonshp between secondary market P/E rato and the market-adjusted ntal return on IPOs. Secondly, IPO prces are not adjusted (or fully adjusted) to the secondary market tradng prces when the latter are overprced. Why does the ssung frm not rase ts offer prce when there s a very hgh ntal return for the new ssue? There are two possble explanatons. On the one hand, the IPO prce s closely related to demand. If the IPO s prced too hgh, demand for t wll decrease accordngly. The success of a new ssue then wll not be assured. The IPO P/E rato s used here as a proxy for the IPO prce level. Accordng to ths argument, there should be a negatve relatonshp between the IPO P/E rato and the odds-&-market-adjusted ntal return (or lottery-wnnng rate). On the other hand, the man purpose of frms gong publc n Chna s to rase money. However frms care less about how much money they rase than the money rasng tself, as argued by some Chnese scholars (Hu, 2003). The reason s that there s lttle dluton of control rghts, snce most ssung frms reman controlled by the government or SOEs. A prvate company wll pay more attenton to the dluton effect on control than the government. So a prvate company wll try to rase ts offer prce when the secondary market prce s relatvely very hgh. In other words, f a large percentage of shares are sold to prvate nvestors, then the government or SOEs wll try to get as much money as possble from the IPO. Hypothess 9: There s a negatve relatonshp between the IPO P/E rato and the odds-&-market-adjusted ntal return. Hypothess 10: Issung frms controlled by prvate companes have lower market-adjusted ntal returns than ssung frms controlled by the government or SOEs. Thrdly, the prmary market and the secondary market are segmented n practce, though law does not segregate them. Investors n the prmary market are manly nterested n the IPO market and are not nterested n the secondary market tradng, and vce versa. In general, money n the secondary market wll not move to the prmary market when there are hgher returns n the 18

prmary market. Under these condtons, the returns n the two markets show lttle tendency to converge. There s consderable evdence for ths market segmentaton hypothess. (a) The average turnover rate of more than 60% on the frst tradng day, as shown n Table 8, shows that most nvestors are only nterested n the prmary market. 1 They sell the new shares once they are lsted. (b) The expected returns of secondary market nvestors are also very hgh snce the market s hghly speculatve. The turnover rate n Shangha Stock Exchange from 1999 to 2002 was, respectvely, 399.22%, 449.06%, 244.27%, and 197.40%, whch are among the hghest n the world. Besdes, the Chnese are extremely short-term nvestors. Accordng to a survey by the Shangha Stock Exchange (SSE, 1999), 12.68% of ndvdual nvestors hold shares for less than one week, 61.46% of them hold shares for one to three months, 20.49% of them hold for about half a year, and only 4.88% of them hold for about one year. For nsttutonal nvestors, the average percentage of share holdng perod for less than one week, one to three months, sx months, one year are, respectvely, 6.45%, 64.52%, 29.03% and 9.68%. The survey also shows that almost no nvestors hold a frm's shares for two years. As a result of the hghly speculatve market, the expected returns of the secondary market nvestors are also very hgh. They wsh to become rch overnght. So many nvestors are unwllng to dvert ther money to the prmary market. (c) The fact that the lottery-wnnng rate s postvely related to the IPO sze,.e., the bgger the IPO, the more chance subscrbers have of wnnng, as shown n table 18, suggests that money n the prmary market s relatvely stable, a sgn that lttle money moves n or out of the IPO market for dfferent new ssues. (d) Investors are restrcted by ther cash flow. Investng n the prmary market requre more money than nvestng n the secondary market. An nvestor s gven one lottery number when he put asde enough money for 1000 shares. There s lttle chance to get the new shares for nvestors wth only 1 All sales on the frst tradng day must be done by prmary market nvestors because the shares other nvestors bought (e.g., from the IPO nvestors n the frst day) cannot be sold on the same day. In fact, almost all nvestors n the prmary market who are enttled to sell the new shares on the frst day do so, snce the long-term nvestors who receve blocks of IPO shares must hold ther new shares for at least sx months. 19

one lottery number snce the odds of wnnng the lottery are very low. Ths also deters secondary market nvestors from nvestng n the prmary markets. (e) In the case of lottery based on the market value of the tradable shares owned by secondary market nvestors, the money put nto the secondary market s a qualfcaton for subscrbng to the IPO. Then there s no need for the money to be transferred to the prmary market. If nvestors n the secondary market sell shares n the secondary market, they wll lose the entry qualfcaton to IPO market. (f) Lqudty s also mportant. Snce there are many days between the IPO date and the tradng date, lqudty-senstve nvestors prefer to reman n the secondary market where they can buy today and sell tomorrow, or sell and then buy on the same day. The turnover rate of the ssung frm's shares on the frst day and the IPO sze are used to test the segmented market hypothess. Accordng to the above analyss, the turnover rate should be postvely related to the market-adjusted ntal return, whle the IPO sze should be negatvely related to the odds-&-market-adjusted ntal return. Hypothess 11: There s a postve relatonshp between the frst day turnover rates and the market-adjusted ntal return. Hypothess 12: There s a negatve relatonshp between the offerng sze and the odds-&-market-adjusted ntal return. To test the above hypotheses, the followng models are used. Model 3: MAR = β + β IPOSIZE β 5 9 0 β Fx Pr ce 1 IPOPE + β + β 10 6 + β 2 LotMoney PubOwn Pr vate + β 11 + β + β 7( k ) 3 Turnover ROE Indus ( k) + β 4 + β 8 LotRate MarketPE + + Model 4: OMAR = β + β IPOSIZE β β 5 9 0 1 LotMoney Pr vate + β + β 10 + β 6( k ) 2 Indus ( k) Turnover PubOwn + β + β 7 3 ROE MarketPE + β Fx Pr ce + 4 + β 8 IPOPE + 20

In addton to the ndependent varables used n Model 1 and Model 2, the turnover rate on the frst tradng day of an IPO (Turnover), the prce-earnng rato of an IPO (IPOPE), the weghted prce-earnng rato for all lsted companes n the Shangha Stock Exchange (MarketPE), and the dummy of whether an ssung company s controlled by a prvate company (Prvate) are added to the enlarged models. The correlaton coeffcents of the varables are provded n Table 20. The addtonal ndependent varables used n the enlarged models are defned as follows: MarketPE (8+) The P/E rato of all companes lsted at the stock exchanges weghted by the market value of the frms. I use the weghted P/E of lsted companes n the Shangha Stock Exchange nstead of the P/E of all Chnese lsted companes because of the unavalable data and because there s lttle dfference n terms of the average market P/E ratos of the two stock exchanges IOPPE (9+) The P/E rato of an IPO, calculated as the offer prce dvded by the earnngs per share Prvate (10-) The dummy to show whether an ssung frm s controlled by a prvate company, 1-yes, 0-no Turnover (11+) The turnover rate of a frm n the frst tradng day IPOSIZE (12+) Note: fgures n ( ) are the related hypotheses to be tested. "+" represents an expected postve relatonshp, whle "-" represents an expected negatve relatonshp. Table 21 presents the OLS estmates for Model 3 and Model 4. The adjusted R-squares for the enlarged models are mproved to a consderable extent compared wth Model 1 and Model 2. The left-hand sde of Table 21 shows the estmaton results for Model 3. I fnd a sgnfcant postve relatonshp between the market P/E rato and the market-adjusted ntal returns, whch s consstent wth the secondary market overprcng hypothess. The same relatonshp exsts for the frst day turnover rate, ndcatng that the prmary and secondary markets are segmented. The relatonshp between the ssung frms controlled by prvate companes and the market-adjusted ntal returns are nsgnfcant. Ths shows that prvately owned frms also do not care much about how much money they rase snce there s lttle dluton n control rghts as a result of a partal sale. It s also reasonable consderng the dffculty of gong publc of the prvately owned companes n Chna. They felctate themselves for gong publc even less money s rased. Hypothess 10 s thus rejected. The rght-hand sde of Table 21 reports the estmaton results for Model 4. I fnd a sgnfcant postve relatonshp between the IPO P/E rato and the odds-&-market-adjusted ntal return, showng that there s low demand when the IPO prce s hghly prced. That s to say, the IPO prce s not adjusted (or fully adjusted) to the tradng prce even the latter s hgh. 21

There s a sgnfcant postve relatonshp between the market P/E rato and the odds-&-market -adjusted ntal return, whch s consstent wth hypothess 8. I also fnd a sgnfcantly postve relatonshp between the IPO sze and the odds-&-market-adjusted ntal return, whch means the lottery-wnnng rate s postvely related to the IPO sze, and shows that the money n the prmary market s relatvely stable, a sgn of the segmented markets. 6 Concluson and Polcy Implcatons Ths paper has focused on explanng the phenomenon of underprcng of IPOs n Chna. I confrm that Chna's IPOs enjoy some of hghest ntal returns n the world. I suggest that share allocaton method plays a crucal role n IPO underprcng by ntroducng new measures of ntal returns based on the lottery-wnnng rate: odds-adjusted and annual returns of IPOs. I have also emprcally dentfed some of the causes of the hgh ntal returns usng data from 354 IPOs from 1999 to 2002. I test four man hypotheses evolved form theores of nformaton asymmetres and fnd that most of the hypotheses fal to explan underprcng n Chna's IPO market. Only the IPO sze has a statstcally sgnfcant postve relatonshp wth the market-adjusted ntal return, whch means that the wnner's curse hypothess does hold. However, contrary to the fndngs of Mok and Hu (1998), Gu (2000) and Ch and Padgett (2002), I do not fnd a sgnfcant relatonshp between the ownershp stake of nformed nvestors, measured by the percentage of government-owned shares, and the market-adjusted ntal return. Ths s further evdence that the wnner's curse hypothess does not hold. The results also show that the frm's ROE and the IPO prcng method do not have any sgnfcant relatonshp wth the market-adjusted ntal return, whch means we can reject the sgnalng and market feedback hypothess. I fnd a postve relatonshp between the lottery mechansm usng money and the market-adjusted ntal return at a sgnfcance level of 0.07. Ths ndcates that there are bandwagon effects to some extent n Chna. However, I do not fnd a negatve relatonshp between the lottery-wnnng rate and the ntal returns as others have found (Lu and L, 2000; Ch and Padgett, 2002). Ths suggests that the lottery-wnnng rate s not a good varable to explan IPO underprcng snce the lottery-wnnng rate tself may be determned by other varables used n the explanaton. The veracty of ths argument s llustrated n the test of the causes of the odds-&-market- adjusted ntal returns. The lottery-wnnng rate s a sgn of nvestors' demand for IPOs and s sgnfcantly related to the odds-&-market-adjusted ntal return. Thus, the model for the odds-&-market-adjusted ntal return s useful to test the relatonshp between the lottery-wnnng rate and other ndependent varables used n the model. I fnd that all ndependent varables except the ndustry dummes are statstcally sgnfcant. The percentages of tradable shares, the IPO sze, and the lottery usng 22

money method all have a sgnfcant postve relatonshps wth the odds-&-market-adjusted ntal return, showng that there are hgher lottery-wnnng rates or lower demand for larger IPOs, IPOs wth larger tradable share ratos, and IPOs whch use the money-based lottery mechansm. There are negatve relatonshps between the frm's ROE and the odds-adjusted ntal return, showng that nvestors have a hgher demand for ssung frms wth better proftablty. The results also show that IPOs usng the fxed prcng method have a lower odds-adjusted ntal return than IPOs whch use the bookbuldng method. The reason for ths s the prces of IPOs sold wth a fxed prce are relatvely low snce the offer prces of nearly all IPOs usng bookbuldng are adjusted upwards. Theores based on nformaton asymmetres cannot explan the extremely hgh ntal returns of IPOs n Chna. These hypotheses only focus on the determnaton of the offer prce. However, the underprcng of an IPO s n practce the result of an nteractve process between the offer prce and the tradng prce on the secondary market. Therefore, I advance a new explanaton by focusng on the nterplay of supply and demand n both the prmary and secondary markets. I argue that IPO underprcng s the result of over-valued secondary market prces under the condton of the de facto segmented markets. The emprcal results support my argument. I fnd a sgnfcant, postve relatonshp between the market P/E rato and the market-adjusted or odds-&-market-adjusted ntal return, whch shows that the level of IPO underprcng changes wth the prce level on the secondary market. Chna's prmary and secondary markets are n practce segmented,.e., n general money from one does not flow to the other. The returns n the two markets show lttle tendency to converge. The results show that the IPO P/E rato has a sgnfcant, postve relatonshp wth the odds-&- market-adjusted ntal return. Ths evdence ndcates that there s lower demand when the IPO prce s set hgh. In other words, n order to ensure the success of the ssuance, frms and underwrters do not adjust the IPO prce upwards above the average f they beleve the secondary market prce of the shares wll be hgher than average. The same relatonshp exsts for the frst day turnover rate, ndcatng that the prmary and secondary markets are n practce segmented. I also fnd a sgnfcantly postve relatonshp between the IPO sze and the odds-&-marketadjusted ntal return, whch means the lottery-wnnng rate s postvely related to IPO sze, and shows that the amount of money n the prmary market s relatvely stable, a sgn of segmented markets. Ths new explanaton provdes mportant nformaton for polcy makers. The only way to mature the prmary market s to reform the secondary market. If the secondary market over-prcng can be reduced, then the evdence of ths paper suggests that the degree of IPO underprcng wll also be reduced. Among all the reform measures, makng non-tradable shares tradable and ntroducng 23

shortsellng or a day-tradng mechansm are most mportant to lowerng secondary prces to more reasonable level. In addton, ths new theory wll be useful for future studes on Chna's IPO market. It mght also be useful to test IPO underprcng n other markets when there are overprced bubbles, such as the underprcng of Internet IPOs n the Unted States n the late 1990s, snce prces of Internet stocks n the secondary markets were usually consdered overprced durng that perod. 24

References Aggarwal, Reena and Patrck Conway, 2000, Prce dscovery n ntal publc offerngs and the role of the lead underwrter, Journal of Fnance 55, 2093-2922. Allen, Frankln and Gerald R. Faulhaber, 1989, Sgnalng by underprcng n the IPO market, Journal of Fnancal Economcs 23, 303-324. Amhud, Yakov, Shmuel Hauser and Amr Krsh. 2001 Allocatons, adverse selecton and cascades n IPOs: Evdence from Israel, workng paper. Beatty, Randolph P. and Ivo Welch, 1996, Issuer expenses and legal lablty n ntal publc offerngs, Journal of Law and Economcs 39, 545-602. Beatty, Randolph P. and Jay R. Rtter, 1986, Investment bankng, reputaton, and the underprcng of ntal publc offerngs, Journal of Fnancal Economcs 15, 213-232. Benvenste, Lawrence M. and Paul A. Spndt, 1989, How nvestment bankers determne the offer prce and allocaton of new ssues, Journal of Fnancal Economcs 24, 343-362. Benvenste, Lawrence M. and Wllam J. Wlhelm, 1990, A comparatve analyss of IPO proceeds under alternatve regulatory envronments, Journal of Fnancal Economcs 28, 173-208. Benvenste, Lawrence M., and Wald Y. Busaba, 1997, Bookbuldng vs. fxed prce: An analyss of competng strateges for marketng IPOs, Journal of Fnancal and Quanttatve Analyss 32, 383-403. Brealey, R. and Myers, S., 1991, Prncples of Corporate Fnance, 4 th edn. McGraw-Hll, New York.Carter, Rchard B., Frederck H. Dark and Alan K. Sngh, 1998, Underwrter reputaton, ntal returns, and the long-run performance of IPO stocks, Journal of Fnance 53, 285-311. Chemmanur, Thomas J., 1993, The prcng of ntal publc offers: A dynamc model wth nformaton producton, Journal of Fnance 48, 285-304. Ch, Jng and Carol Padgett, 2002, Short-run underprcng and ts characterstcs n Chnese IPO markets, ISMA Dscusson Papers n Fnance 2001-12, Unversty of Readng, UK. Cornell, Francesca and Davd Goldrech, 2001, Bookbuldng and strategc allocaton, Journal of Fnance, 2337-2369. Datar, V. and D. Mao., 1998, Intal publc offerngs n Chna: Why s underprcng so severe, Seattle Unversty Workng Paper. Drake, Phlp D. and Mchael R. Vetsuypens, 1993, IPO underprcng and nsurance aganst legal lablty, Fnancal Management 22, 64-73. 25

DuCharme, Larry L., Shvaram Rajgopal, and Stephan E. Sefck, 2001, Why was nternet underprcng so severe?, Unversty of Washngton workng paper. Feld, Laura C. and Denns P. Sheehan, 2001, Underprcng n IPOs: Control, montorng, or lqudty? Penn State workng paper. Grnblatt, M. and C. Y. Hwang, 1989, Sgnallng and the prcng of new ssues. Journal of Fnance 44, 393-420. Gu, Y. X., 2000, Prvatzaton, frm sze, and IPO performance: Evdence from Chnese A share ssues, Seattle Unversty Workng Paper. Hanley, Kathleen Wess, 1993, The underprcng of ntal publc offerngs and the partal adjustment phenomenon, Journal of Fnancal Economcs 34, 231-250. Hu, Ruyn and Lu T, eds., 2003, Zhong Guo Shang Sh Gong S Cheng Ba Sh Zheng Yan Ju (An Emprcal Study of the Falure and Success of Chna's Lsted Companes), Shangha: Fudan Unversty Press. Jan, Bharat A. and Omesh Kn, 1994, The post-ssue operatng performance of IPO frms, Journal of Fnance 49, 1699-1726. Km, Moonchul and Jay R. Rtter, 1999, Valung IPOs, Journal of Fnancal Economcs 53, 409-437. Lee, Phlp J., Stephen L. Taylor and Terry S. Walter, 1999, IPO underprcng explanatons: Implcatons from nvestor applcaton and allocaton schedules, Journal of Fnancal and Quanttatve Analyss 34, 425-444. Lu, L. and L W.D., 2000, Research on frst day s abnormal returns of IPOs n Chna's securtes market, Chna Accountng and Fnance Revew 2, 4, 26-53. Lu, T, 1999, Zhong Wa Gu Sh Sh Hua: Cong Hua Er Je Dao Wa Tan (A Bref Hstory of Stock Markets: From Wall Street to the Bunds), Shangha: Shangha Fareast Publshng House. Ljungqvst, Alexander, and Wllam Wlhelm, 2002, IPO prcng n the dot-com bubble: Complacency or ncentves? NYU workng paper. Logue, Denns E., 1973, On the prcng of unseasoned equty ssues: 1965-1969, Journal of Fnancal and Quanttatve Analyss 8, 91-103. Loughran, Tm and Jay R. Rtter, 2002, Why has IPO underprcng ncreased over tme? Unversty of Florda workng paper. Loughran, Tm, Jay R. Rtter and Krstan Rydqvst, 1994, Intal publc offerngs: Internatonal nsghts, Pacfc-Basn Fnance Journal 2, 165-199. Maksmovc, Vojslav and Pegaret Pchler, 2001, Technologcal nnovaton and ntal publc 26

offerngs, Revew of Fnancal Studes 14, 459-494. Mello, Antono and John Parsons, 1998, Gong publc and the ownershp structure of the frm, Journal of Fnancal Economcs 49, 79-109. Mchaely, Ron and Wayne H. Shaw, 1994, The prcng of ntal publc offerngs: Tests of adverse-selecton and sgnalng theores, Revew of Fnancal Studes 7, 279-319. Mok, H.M.K. and Y.V. Hu, 1998, Underprcng and after market performance of IPOs n Shangha, Chna, Pacfc-Basn Fnance Journal 6, 5, 453-474. Perott, Enrco C., 1995, Credble prvatzaton, Amercan Economc Revew 85, 847-859. Relly, Frank K., 1973, Further evdence on short-run results for new ssues nvestors, Journal of Fnancal and Quanttatve Analyss 8, 83-90. Rtter, Jay R., 1998, Intal publc offerngs, Contemporary Fnance Dgest 2, 1 (Sprng), 5-30 Rock, Kevn, 1986, Why new ssues are underprced, Journal of Fnancal Economcs 15, 187-212. Shangha Stock Exchange (SSE), 1999, Shangha Zheng Quan Jao Y Suo A Gu Tou Z Zhe Dao Cha (A Survey of A-share Investors of Shangha Stock Exchange), Workng Paper. Shangha Stock Exchange (SSE), 2003, Zhong Guo Gong S Zh L Bao Gao 2003 (Chna Corporate Governance Report 2003), Shangha: Fudan Unversty Press. Sherman, Ann, 2000, IPOs and long-term relatonshps: An advantage of bookbuldng, Revew of Fnancal Studes 13, 697-714. Spatt, Chester and Sanjay Srvastava, 1991, Preplay communcaton, partcpaton restrctons, and effcency n ntal publc offerngs, Revew of Fnancal Studes 4, 709-726. Stoll, Hans R. and Anthony J. Curley, 1970, Small busness and the new ssues market for equtes, Journal of Fnancal and Quanttatve Analyss 5, 309-322. Su, Dongwe and Belton M. Flesher, 1999, An emprcal nvestgaton of underprcng n Chnese IPOs, Pacfc-Basn Fnance Journal 7, 2, 173-202. Welch, Ivo, 1989, Seasoned offerngs, mtaton costs, and the underprcng of ntal publc offerngs, Journal of Fnance 44, 421-450. Welch, Ivo, 1992, Sequental sales, learnng, and cascades, Journal of Fnance 47, 695-732. Welch, Ivo, and Jay Rtter, 2002, A revew of IPO actvty, prcng and allocatons, Journal of Fance 57(4), 1795-1828. 27

Table 1 Equty Structures of Chna's Lsted Companes, 1997-2002 1997 1998 1999 2000 2001 2002 Number of Lsted Companes 745 851 949 1088 1160 1224 Non-tradable shares 65.44% 65.90% 64.98% 64.28% 65.25% 65.33% State shares 31.52% 34.25% 36.13% 38.90% 46.20% 47.20% Legal-entty shares 30.70% 28.35% 26.58% 23.81% 18.29% 17.32% Employee shares 2.04% 2.05% 1.19% 0.64% 0.46% 0.27% Others 1.18% 1.25% 1.07% 0.92% 0.31% 0.54% Tradable shares 34.56% 34.11% 34.95% 35.72% 34.75% 34.67% A shares 22.79% 24.06% 26.33% 28.43% 25.26% 25.69% B shares 6.04% 5.30% 4.59% 4.00% 3.13% 2.85% Others 5.74% 4.75% 4.03% 3.28% 6.36% 6.13% Total 100% 100% 100% 100% 100% 100% Source: Chna Corporate Governance Report, 2003, Shangha: Fudan Unversty Press, 2003. Notes: Other non-tradable shares nclude rght ssues that government transfers to other frms, etc. Other tradable shares nclude H shares (shares traded n Hong Kong), N shares (shares traded n NYSE), etc. Table 2 Number of IPOs n Chna by the year of ssung, 1999-2002 No. of IPOs Percentage Total Shangha Shenzhen Total Shangha Shenzhen 1999 94 48 46 26.55 17.98 52.87 2000 124 83 41 35.03 31.09 47.13 2001 68 68 19.21 25.47 2002 68 68 19.21 25.47 Total 354 267 87 100 100 100 Mean 88.50 66.75 21.75 28

Table 3 Number of IPOs n Chna by the month of ssung, 1999-2002 No. of IPOs Percentage Total Shangha Shenzhen Total Shangha Shenzhen Jan 22 20 2 6.21 7.49 2.30 Feb 15 13 2 4.24 4.87 2.30 Mar 27 18 9 7.63 6.74 10.34 Apr 30 19 11 8.47 7.12 12.64 May 36 25 11 10.17 9.36 12.64 Jun 32 23 9 9.04 8.61 10.34 Jul 50 33 17 14.12 12.36 19.54 Aug 35 26 9 9.89 9.74 10.34 Sept 35 24 11 9.89 8.99 12.64 Oct 17 15 2 4.80 5.62 2.30 Nov 28 26 2 7.91 9.74 2.30 Dec 27 25 2 7.63 9.36 2.30 Total 354 267 87 100 100 100 Table 4 Correlatons between Monthly Number of IPOs and Monthly Returns of Shangha A Index, 1999-2002 Number of IPOs Return of Shangha A Pearson Correlaton 0.085804 Index Sg. (2-taled) 0.562001 N 48 29

Table 5 Number of IPOs by Industry, 1999-2002 Industry 1 2 3 4 5 6 Total 1999 Count 1 8 2 11 68 4 94 % wthn IPO year 1.06 8.51 2.13 11.70 72.34 4.26 100.00 % wthn Industry 20.00 36.36 28.57 16.18 30.63 13.33 26.55 % of Total 0.28 2.26 0.56 3.11 19.21 1.13 26.55 2000 Count 1 10 56 51 6 124 % wthn IPO year 0.81 8.06 45.16 41.13 4.84 100.00 % wthn Industry 20.00 45.45 82.35 22.97 20.00 35.03 % of Total 0.28 2.82 15.82 14.41 1.69 35.03 2001 Count 2 3 1 56 6 68 % wthn IPO year 2.94 4.41 1.47 82.35 8.82 100.00 % wthn Industry 9.09 42.86 1.47 25.23 20.00 19.21 % of Total 0.56 0.85 0.28 15.82 1.69 19.21 2002 Count 3 2 2 47 14 68 % wthn IPO year 4.41 2.94 2.94 69.12 20.59 100.00 % wthn Industry 60.00 9.09 28.57 21.17 46.67 19.21 % of Total 0.85 0.56 0.56 13.28 3.95 19.21 Total Count 5 22 7 68 222 30 354 % wthn IPO year 1.41 6.21 1.98 19.21 62.71 8.47 100.00 % wthn Industry 100.00 100.00 100.00 100.00 100.00 100.00 100.00 % of Total 1.41 6.21 1.98 19.21 62.71 8.47 100.00 Note: The meanng of the fgures n the second lne represent the followng ndustry: 1 for fnance, 2 publc utltes, 3 real estate, 4 dversfed conglomerates, 5 manufacturng, 6 commerce and servces. 30

Table 6 Number of IPOs by Prcng Method, 1999-2002 Prcng method Fxed Prce Bookbuldng Total 1999 Count 94 94 % wthn IPO year 100.00 100.00 % wthn prcng method 34.94 26.55 % of Total 26.55 26.55 2000 Count 121 3 124 % wthn IPO year 97.58 2.42 100.00 % wthn prcng method 44.98 3.53 35.03 % of Total 34.18 0.85 35.03 2001 Count 54 14 68 % wthn IPO year 79.41 20.59 100.00 % wthn prcng method 20.07 16.47 19.21 % of Total 15.25 3.95 19.21 2002 Count 68 68 % wthn IPO year 100.00 100.00 % wthn prcng method 80.00 19.21 % of Total 19.21 19.21 Total Count 269 85 354 % wthn IPO year 75.99 24.01 100.00 % wthn prcng method 100.00 100.00 100.00 % of Total 75.99 24.01 100.00 31

Table 7 Number of IPOs by Share Allocaton Method, 1999-2002 Share Allocaton Method 1 2 3 4 Total 1999 Count 93 1 94 % wthn IPO year 98.94 1.06 100.00 % wthn ssung method 38.91 1.52 26.55 % of Total 26.27 0.28 26.55 2000 Count 64 58 2 124 % wthn IPO year 51.61 46.77 1.61 100.00 % wthn ssung method 26.78 87.88 100.00 35.03 % of Total 18.08 16.38 0.56 35.03 2001 Count 63 5 68 % wthn IPO year 92.65 7.35 100.00 % wthn ssung method 26.36 7.58 19.21 % of Total 17.80 1.41 19.21 2002 Count 19 47 2 68 % wthn IPO year 27.94 69.12 2.94 100.00 % wthn ssung method 7.95 100.00 3.03 19.21 % of Total 5.37 13.28 0.56 19.21 Total Count 239 47 66 2 354 % wthn IPO year 67.51 13.28 18.64 0.56 100.00 % wthn ssung method 100.00 100.00 100.00 100.00 100.00 % of Total 67.51 13.28 18.64 0.56 100.00 Note: The meanng of the fgures n the second lne represent the followng share allocaton method: 1 for lottery usng money, 2 for lottery based on the market value of tradable shares subscrbers held, 3 both 1 and 2, 4 other methods. 32

Table 8 Key Descrptve Statstcs of IPOs n Chna, 1999-2002 Year Number of IPOs Mean Medan Mnmum Maxmum Std. Devaton Std. Error of Mean IPO Prce (RMB Yuan) 1999 94 6.16 5.78 3.05 13.20 2.00 0.21 2000 124 8.23 7.70 3.78 20.00 3.20 0.29 2001 68 9.40 8.27 2.27 36.68 5.84 0.71 2002 68 7.19 6.55 2.20 16.18 3.33 0.40 Total 354 7.71 6.80 2.20 36.68 3.81 0.20 IPO Quantty (mllon shares) 1999 94 90.27 65.00 13.34 400.00 77.46 7.98 2000 124 83.89 58.00 25.00 1877.00 169.78 15.24 2001 68 163.66 57.50 18.00 2800.00 401.62 48.70 2002 68 165.59 42.50 4.00 5000.00 625.62 75.87 Total 354 116.60 58.00 4.00 5000.00 343.48 18.26 IPO Market Value (mllon RMB Yuan) 1999 94 538.27 351.65 108.80 4000.00 513.81 53.00 2000 124 614.19 444.55 144.00 7845.86 817.54 73.42 2001 68 1222.99 509.38 133.20 13440.00 2366.47 286.98 2002 68 739.81 306.53 32.40 11500.00 1871.08 226.90 Total 354 735.10 407.75 32.40 13440.00 1446.09 76.86 IPO P/E Rato 1999 94 17.0462 17.0000 12.0800 22.7000 1.8440 0.1902 2000 124 30.4335 29.1450 17.0600 71.4500 9.5217 0.8551 2001 68 33.3860 32.7800 16.1500 74.2000 12.0671 1.4633 2002 68 19.3112 20.0000 12.2200 21.4700 1.7325 0.2101 Total 354 25.3093 20.0000 12.0800 74.2000 10.3728 0.5513 33

Table 8 Key Descrptve Statstcs of IPOs n Chna, 1999-2002 (Contnued) Year Number of IPOs Mean Medan Mnmum Maxmum Std. Devaton Std. Error of Mean Odds / Probablty to wn the lottery (%) 1999 94 0.8090 0.4295 0.1376 5.6941 0.9641 0.0994 2000 124 0.9043 0.2718 0.0544 40.1600 3.7458 0.3364 2001 68 2.5860 0.2745 0.0558 52.1000 8.8656 1.0751 2002 68 0.1680 0.0712 0.0334 2.7504 0.3598 0.0436 Total 354 1.0606 0.2769 0.0334 52.1000 4.5502 0.2418 Frst Day Closng Prce (RMB Yuan) 1999 94 13.39 11.56 4.86 51.92 7.38 0.76 2000 124 20.49 18.58 6.09 63.55 9.38 0.84 2001 68 20.80 17.85 4.36 92.00 12.40 1.50 2002 68 15.36 14.65 2.87 30.52 6.02 0.73 Total 354 17.68 16.39 2.87 92.00 9.57 0.51 Frst Day Turnover Rate (%) 1999 94 60.0213 63.0000 19.0000 79.0000 12.4684 1.2860 2000 124 57.4129 59.0000 5.2000 81.0000 12.8813 1.1568 2001 68 64.9574 66.1500 27.1000 84.2000 11.0963 1.3456 2002 68 60.0147 57.4500 20.1000 84.6000 13.1035 1.5890 Total 354 60.0545 61.0000 5.2000 84.6000 12.7207 0.6761 Days between IPO & lstng date 1999 94 56.98 50 0 133 29.8065 3.0743 2000 122 26.58 20 7 194 23.2403 2.1041 2001 68 33.37 25 6 380 44.7187 5.4229 2002 68 20.51 15 10 105 17.8881 2.1693 Total 352 34.83 23 0 380 32.5504 1.7349 34

Table 9 Intal Returns and Market-Adjusted Intal Returns of IPOs n Chna, 1999-2002 Year Number of Cases Mean Medan Mnmum Maxmum Std. Devaton Std. Error of Mean Intal Return (%) 1999 94 113.1943 103.8132 7.1429 341.8723 72.9382 7.5230 2000 124 155.4353 141.6428 21.8182 476.7726 85.2153 7.6526 2001 68 136.1010 117.4548 0.7353 413.7931 90.2868 10.9489 2002 68 126.8354 113.9295 24.7826 428.2500 78.1570 9.4779 Total 354 135.0111 123.8835 0.7353 476.7726 83.2157 4.4229 Market-adjusted Intal Return (%) 1999 94 107.5434 91.9204 6.0138 386.2034 70.7564 7.2980 2000 124 149.8867 138.5667 21.7793 478.4055 80.9288 7.2676 2001 68 140.5123 122.2114 3.4660 411.8761 89.5395 10.8583 2002 68 127.2473 117.4633 25.0691 429.9360 79.7601 9.6723 Total 354 132.4935 120.7939 3.4660 478.4055 81.3632 4.3244 Table 10 Odds-Adjusted Intal Returns and Odds-&-Market- Adjusted Intal Returns of IPOs n Chna, 1999-2002 Year Number of Cases Mean Medan Mnmum Maxmum Std. Devaton Std. Error of Mean Odds-adjusted Intal Return (%) 1999 94 0.6588 0.5226 0.0659 6.0354 0.7244 0.0747 2000 124 0.8038 0.4327 0.0757 18.5638 1.9897 0.1787 2001 68 1.4892 0.3186 0.0370 26.0500 4.7415 0.5750 2002 68 0.1369 0.0942 0.0183 0.6816 0.1238 0.0150 Total 354 0.7689 0.3313 0.0183 26.0500 2.4430 0.1298 Odds-&-market-adjusted Intal Return (%) 1999 94 0.6523 0.4597 0.0555 6.7587 0.7989 0.0824 2000 124 0.7714 0.4132 0.0857 17.8340 1.9295 0.1733 2001 68 1.6923 0.3392 0.1156 31.1534 5.5976 0.6788 2002 68 0.1365 0.0930 0.0161 0.8371 0.1310 0.0159 Total 354 0.7947 0.3391 0.0161 31.1534 2.7677 0.1471 35

Table 11 Annual Return and Market-Adjusted Annual Return of IPOs n Chna, 1999-2002 Year Number of Cases Mean Medan Mnmum Maxmum Std. Devaton Std. Error of Mean Annual Return (%) 1999 94 31.5252 25.0250 3.1600 287.0600 34.5047 3.5589 2000 124 37.7634 20.7500 3.6300 811.9200 89.1666 8.0074 2001 68 66.8654 15.2850 1.7600 1108.8500 207.5295 25.1667 2002 68 6.5624 4.5200 0.8800 32.5100 5.9230 0.7183 Total 354 35.7037 15.8950 0.8800 1108.8500 107.8051 5.7298 Market-adjusted Annual Return (%) 1999 94 31.2384 22.0150 2.6600 323.6600 38.2569 3.9459 2000 124 36.9030 19.7900 4.1000 850.0200 92.1115 8.2719 2001 68 80.7374 16.2400 5.5400 1484.8700 266.7843 32.3523 2002 68 6.5269 4.4500 0.7700 40.0800 6.2621 0.7594 Total 354 37.9840 16.2350 0.7700 1484.8700 131.9605 7.0136 Table 12 Weghted IPO Intal Returns n Chna (weghted by IPO Value), 1999-2002 1999 2000 2001 2002 Total Number of Cases 94 124 68 68 354 Intal Return (%) 97.2716 118.4687 67.1598 67.9752 88.1886 (135.0111) Market-adjusted Intal Return (%) 94.7325 114.7957 72.6618 67.4488 88.2765 (132.4935) Odds-adjusted Intal Return (%) 0.8155 1.0211 6.8961 0.3499 2.7289 (0.7689) Odss-&-market-adjusted Intal Return 0.8492 0.9956 7.805 0.3713 3.0226 (%) (0.7947) Annual Return (%) 38.9992 47.8386 303.4948 16.7262 121.8077 (35.7037) Market-adjusted Annual Return (%) 40.6672 47.6235 372.0569 17.7481 144.1777 (37.9840) Notes: Fgures n ( ) n the last column s unweghted returns. 36

Table 13 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Industres, 1999-2002 Industry Total 1 2 3 4 5 6 Market-adjusted Intal Return (%) 1999 No of IPOs 8 2 11 68 4 94 Mean 206.9789 85.9654 63.2010 154.8501 103.3973 88.4033 107.5434 Std.Devaton. 51.8047 33.0654 60.4051 72.2020 71.0824 70.7564 2000 No of IPOs 0 1 10 56 51 6 124 Mean 57.3372 102.4340 170.0452 135.7391 176.5085 149.8867 Std.Devaton. 48.5671 81.5670 83.3985 21.7564 80.9288 2001 No of IPOs 0 2 3 1 56 6 68 Mean 145.6683 163.4312 136.0977 143.4597 100.5615 140.5123 Std.Devaton 41.8426 23.5530. 96.5958 43.3540 89.5395 2002 No of IPOs 3 2 2 0 47 14 68 Mean 139.4785 89.4564 142.7470 136.4316 96.9777 127.2473 Std.Devaton 146.1977 67.1816 82.0825 83.7357 47.3280 79.7601 Total No of IPOs 5 22 7 68 222 30 354 Mean 136.5503 99.1960 128.8842 167.0879 127.9267 112.4574 132.4935 Std.Devaton 116.1982 49.9015 59.9079 77.7971 84.9198 54.8274 81.3632 Market-adjusted Annual Return (%) 1999 No of IPOs 1 8 2 11 68 4 94 Mean 140.3000 43.8738 15.4550 29.3291 29.9719 13.3750 31.2384 Std.Devaton. 36.9188 10.5005 21.1108 39.8868 10.2731 38.2569 2000 No of IPOs 1 10 0 56 51 6 124 Mean 28.2500 27.2170 33.5550 44.6173 20.1650 36.9030 Std.Devaton. 16.4959 74.0963 121.0483 6.2205 92.1115 2001 No of IPOs 0.0000 2 3 1 56 6 68 Mean 13.6950 50.6633 11.4900 92.2323 22.3767 80.7374 Std.Devaton 6.4276 35.6305. 292.9544 17.3826 266.7843 2002 No of IPOs 3 2 2 0 47 14 68 Mean 5.4300 16.1550 6.2900 5.5813 8.5950 6.5269 Std.Devaton 2.8402 12.4380 3.0123 4.3432 9.9565 6.2621 Total No of IPOs 5 22 7 68 222 30 354 Mean 36.9680 31.0391 27.9257 32.5469 43.8779 14.3027 37.9840 Std.Devaton 58.6378 26.4527 30.1569 67.6950 161.6287 12.2706 131.9605 Note: The meanng of the fgures n the second lne represent the followng ndustry: 1 for fnance, 2 publc utltes, 3 real estate, 4 dversfed conglomerates, 5 manufacturng, 6 commerce and servces. 37

Table 14 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Prcng Method, 1999-2002 Prcng Method Total Fxed Prce Bookbuldng Market-adjusted Intal Return (%) 1999 No of IPOs 94 0 94.0000 Mean 107.5434328 107.5434 Std.Devaton 70.75640709 70.756407 2000 No of IPOs 121.0000 3.0000 124.0000 Mean 151.1875 97.4227 149.8867 Std.Devaton 80.84489463 80.0482054 80.928815 2001 No of IPOs 54.0000 14 68.0000 Mean 137.0925 153.7032969 140.51234 Std.Devaton 86.11643677 104.1608 89.5395 2002 No of IPOs 0 68.0000 68.0000 Mean 127.2473103 127.24731 Std.Devaton 79.7601 79.7601 Total No of IPOs 269.0000 85.0000 354 Mean 133.1069067 130.5521348 132.49347 Std.Devaton 80.6874 83.92382174 81.363244 Market-adjusted Annual Return (%) 1999 No of IPOs 94 0 94 Mean 31.2384 31.2384 Std.Devaton 38.2569 38.2569 2000 No of IPOs 121 3 124 Mean 30.0963 311.4400 36.9030 Std.Devaton 56.0107 466.5922 92.1115 2001 No of IPOs 54 14 68 Mean 19.7683 315.9036 80.7374 Std.Devaton 13.6505 539.5011 266.7843 2002 No of IPOs 0 68 68 Mean 6.5269 6.5269 Std.Devaton 6.2621 6.2621 Total No of IPOs 269 85 354 Mean 28.4221 68.2447 37.9840 Std.Devaton 44.3688 256.2779 131.9605 38

Table 15 Market-Adjusted Intal Return and Market-Adjusted Annual Return of IPOs n Chna by Share Allocaton Method, 1999-2002 Share Allocaton Method Total 1 2 3 4 Market-adjusted Intal Return (%) 1999 No of IPOs 93 0 1 0 94 Mean 107.1529 143.8617 107.5434 Std.Devaton 71.0380. 70.7564 2000 No of IPOs 64 0 58 2 124 Mean 155.2652 144.3889 137.2110 149.8867 Std.Devaton 86.1219 76.2964 50.8453 80.9288 2001 No of IPOs 63 0 5 0 68 Mean 146.5252 64.7502 140.5123 Std.Devaton 90.1492 24.0668 89.5395 2002 No of IPOs 19 47 2 0 68 Mean 129.7293 126.5332 120.4503 127.2473 Std.Devaton 78.9370 82.5973 3.6038 79.7601 Total No of IPOs 239 47 66 2 354 Mean 132.2098 126.5332 137.6223 137.2110 132.4935 Std.Devaton 83.3389 82.5973 74.8301 50.8453 81.3632 Market-adjusted Annual Return (%) 1999 No of IPOs 93 0 1 0 94 Mean 31.3704 18.9600 31.2384 Std.Devaton 38.4427. 38.2569 2000 No of IPOs 64 0 58 2 124 Mean 26.3948 48.9769 23.0200 36.9030 Std.Devaton 16.6089 133.1254 11.6531 92.1115 2001 No of IPOs 63 0 5 0 68 Mean 18.4613 865.4160 80.7374 Std.Devaton 13.0746 598.9811 266.7843 2002 No of IPOs 19 47 2 0 68 Mean 10.5216 4.7087 11.3050 6.5269 Std.Devaton 5.6746 5.6580 8.4216 6.2621 Total No of IPOs 239 47 66 2 354 Mean 24.9778 4.7087 109.2320 23.0200 37.9840 Std.Devaton 27.1236 5.6580 292.0047 11.6531 131.9605 Note: The meanng of the fgures n the second lne represent the followng share allocaton method: 1 for lottery usng money, 2 for lottery based on the market value of tradable shares subscrbers held, 3 both 1 and 2, 4 other methods. 39

Table 16 Average Intal Returns of IPOs n 33 countres or markets Country/ Market Tme Perod Sample Sze Intal Return Country/ Market Tme Perod Sample Sze Intal Return Emergng Markets (13) Developed Markets (20) Israel 1993-1994 28 4.5% France 1983-1992 187 4.2% Turkey 1990-1995 138 13.6% Canada 1971-1992 258 5.4% Hong Kong Chna 1980-1996 334 15.9% Unted States 1980-2000 6,169 6.3% Chle 1982-1990 19 16.3% Austra 1964-1996 67 6.5% Sngapore 1973-1992 128 31.4% Netherlands 1982-1991 72 7.2% Mexco 1987-1990 37 33.0% Denmark 1989-1997 32 7.7% Inda 1992-1993 98 35.3% Fnland 1984-1992 85 9.6% Tawan Chna 1971-1990 168 45.0% Belgum 1984-1990 28 10.1% Thaland 1988-1989 32 58.1% Germany 1978-1992 170 10.9% Korea 1980-1990 347 78.1% Australa 1976-1989 266 11.9% Brazl 1979-1990 62 78.5% Unted Kngdom 1959-1990 2,133 12.0% Malaysa 1980-1991 132 80.3% Norway 1984-1996 68 12.5% Chna 1999-2002 354 135.0% Japan 1970-1996 975 24.0% Chna 1990-1996 226 388.0% Italy 1985-1991 75 27.1% New Zealand 1979-1991 149 28.8% Sweden 1980-1994 251 34.1% Span 1985-1990 71 35.0% Swtzerland 1983-1989 42 35.8% Greece 1987-1991 79 48.5% Portugal 1986-1987 62 54.4% Average (excludng Chna) 40.8% Average 19.6% Average (ncludng Chna 1999-2002) 48.1% Total Average (excludng Chna) 27.6% Total Average (ncludng Chna 1999-2002) 30.8% Source: Rtter (1998), Loughran & Rtter (2002). 40

Table 17 Dstrbuton of IPO Intal Return n the US from 1980-2000 Number of IPOS Percent Average Intal Return (%) <0 1692 28.9-2.3 0<IR<10% 1705 29.1 4.7 10%<IR<60% 2025 34.6 25.6 >60% 432 7.4 135.7 Total 5854 100.0 19.5 Source: Loughram and Rtter (2002) Table 18 Correlaton Matrx of the Varables used n Model 1 and Model 2 MAR OMAR IPOSIZE PubOwn ROE LotRate FxPrce OMAR -0.070 IPOSIZE -0.522 PubOwn 0.170 0.348 0.100-0.215 ROE -0.030-0.093 0.149 LotRate -0.165 0.934 FxPrce 0.013-0.129 * 0.402 LotMoney 0.027 0.099 0.127 * 0.025 0.113 * 0.040-0.209 Correlaton s sgnfcant at the 0.01 level (2-taled). * Correlaton s sgnfcant at the 0.05 level (2-taled). -0.092-0.148-0.072-0.177-0.160 0.081 0.675 41

Table 19 Estmates for Model 1 and Model 2 of IPO Underprcng n Chna All regressons use 354 observatons when the sample perod s from January 1999 to December 2002. The dependent varables are market-adjusted ntal returns and odds-&-market-adjusted ntal returns. The ndependent varables are the logarthm of the offer sze measured n RMB Yuan (IPOSIZE), The percentage of tradable shares (PubOwn), Return on equty a year before IPO date (ROE), the odds of wnnng the lottery (LotRate), the prcng method dummy to show whether a frm adopts fx-prce method (FxPrce), the share allocaton method dummy to show whether an IPO s allocated based on the lottery usng money (ncludes IPOs based on the lottery based on both money and market value of the tradable shares subscrbers held) (LotMoney), and the ndustry dummes (ndus1 for fnance, ndus2 publc utltes, ndus3 real estate, ndus4 dversfed conglomerates, ndus5 manufacturng, ndus6 commerce and servces). The estmaton method s the ordnary least squares. The t-statstcs and sgnfcance are provded. Model 1 Dependent Varable: MAR Model 2 Dependent Varable: OMAR Coeffcents t Sg. Coeffcents t Sg. (Constant) 1316.575 12.264 0.000-26.209-7.189.000 IPOSIZE -60.412-11.613 0.000 1.333 7.620.000 PubOwn 0.140 0.289 0.773 0.050 2.783.006 ROE -0.325-0.790 0.430-0.047-3.090.002 LotRate 0.915 1.007 0.315 FxPrce 9.473 0.775 0.439-1.915-4.306.000 LotMoney 30.304 1.806 0.072 1.478 2.358.019 Indus1-93.980-3.110 0.002 -.876 -.771.441 Indus2-91.304-5.745 0.000-0.020 -.033.973 Indus3-70.809-2.743 0.006-0.028 -.029.977 Indus4-24.200-2.322 0.021 -.142 -.362.717 Indus6 2.201 0.124 0.902 -.713-1.068.286 Adjusted R Square Std. Error of the Estmate F-statstcs Sg. 0.351 65.569 18.332 0.000 0.205 2.468 10.100 0.000 42

Table 20 Correlaton Matrx of the Varables used n Model 3 and Model 4 OMAR -0.070 MAR OMAR IPOSIZE PubOwn ROE LotRate FxPrce LotMoney MarketPE IPOPE Prvate IPOSIZE -0.522 PubOwn 0.170 0.348 0.100-0.215 ROE -0.030-0.093 0.149 LotRate -0.165 0.934 FxPrce 0.013-0.129 * 0.402 LotMoney 0.027 0.099 0.127 * MarketPE 0.172 IPOPE 0.111 * 0.111 * 0.308 0.025 0.113 * 0.040-0.209 0.159 0.199-0.092-0.148-0.072-0.177 0.041 0.315 0.139 0.176 Prvate 0.019-0.039 0.005 0.015 0.132 * Turnover 0.460-0.037-0.323 0.075-0.157-0.160 0.081 0.675 0.118 * 0.298 0.410 0.221-0.042 0.125 * -0.130 * 0.269 0.214 0.108 * -0.060 0.155 0.642 0.068 0.119 * -0.115 * 0.035 0.010 Correlaton s sgnfcant at the 0.01 level (2-taled). * Correlaton s sgnfcant at the 0.05 level (2-taled). 43

Table 21 Estmates for Model 3 and Model 4 of IPO Underprcng n Chna All regressons use 354 observatons when the sample perod s from January 1999 to December 2002. The dependent varables are market-adjusted ntal returns and odds-&-market-adjusted ntal returns. In addton to the ndependent varables used n Model 1 and Model 2, the turnover rate n the frst tradng day of an IPO (Turnover), the prce-earnng rato of an IPO (IPOPE), the weghted prce-earnng rato for all lsted companes n Shangha Stock Exchange (MarketPE), the dummy of whether an ssung company s controlled by a prvate company (Prvate) are added to the enlarged models. The estmaton method s the ordnary least squares. The t-statstcs and sgnfcance are provded. Model 3 Dependent Varable: MAR Model 4 Dependent Varable: OMAR Coeffcents t Sg. Coeffcents t Sg. (Constant) 839.681 7.163 0.000-25.705-6.429 0.000 IPOSIZE -48.599-9.710 0.000 0.962 5.549 0.000 PubOwn 0.161 0.359 0.720 0.021 1.261 0.208 ROE -0.040-0.102 0.919-0.035-2.435 0.015 LotRate 0.553 0.573 0.567 FxPrce -3.363-0.189 0.850-4.884-8.634 0.000 LotMoney 7.708 0.482 0.630 1.654 2.857 0.005 MarketPE 2.356 2.823 0.005 0.132 4.510 0.000 IPOPE 0.151 0.316 0.753 0.109 6.572 0.000 Prvate 4.048 0.305 0.761-0.676-1.385 0.167 Turnover 2.274 7.721 0.000-0.005-0.506 0.613 Indus1-24.620-0.740 0.460 3.645 3.037 0.003 Indus2-41.792-1.823 0.069 4.332 5.492 0.000 Indus3-34.278-1.286 0.199 3.451 3.603 0.000 Indus4 13.270 0.876 0.382 3.179 6.094 0.000 Indus6 23.981 1.445 0.149-0.207-0.338 0.736 Adjusted R Square Std. Error of the Estmate F-statstcs Sg. 0.454 60.110 20.584 0.000 0.359 2.216 15.123 0.000 44

Fgure 1 Equty Structures of Chna's Lsted Companes, 2002 B shares 3% Others 7% A shares 26% Legal-entty shares 17% State shares 47% Source: Chna Corporate Governance Report, 2003, Shangha: Fudan Unversty Press, 2003. Fgure 2 Number of IPOs n Chna by the year of ssung, 1999-2002 150 120 90 Total Shangha Shenzhen 60 30 0 1999 2000 2001 2002 45

Fgure 3 Number of IPOs n Chna by the month of ssung, 1999-2002 60 50 40 Total Shangha Shenzhen 30 20 10 0 Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Fgure 4 Monthly Number of IPOs and Returns of Shangha A Index, 1999-2002 45 Number of IPOs Monthly Return of Shangha A Index (%) 30 15 0 199901 199907 200001 200007 200101 200107 200201 200207-15 46

Fgure 5 Dstrbuton of IPO Market-adjusted Intal Returns n Chna, 1999-2002 Percentage of IPOs 15% 12% 9% 6% 3% 0% 0-25% 25-50% 50-75% 75-100% 100-125% 125-150% 150-175% 175-200% 200-225% 225-250% 250-275% 275-300% >300% Fgure 6 Dstrbuton of IPO Market-adjusted Annual Returns n Chna, 1999-2002 Percentage of IPOs 30% 25% 20% 15% 10% 5% 0% 0-5% 5-10% 10-20% 20-30% 30-40% 40-50% 50-100% >100% 47

Fgure 7 Dstrbuton of IPO Intal Returns n the US from 1990-1996 Percentage of IPOs 35% 30% 25% 20% 15% 10% 5% 0% <0 0 0-10% 10-30% 30-50% 50-100% >100% Source: Rtter (1998) 48