Speculative Trading and Stock Prices:

Transcription

1 Speculatve Tradng and Stock Prces: n nalyss of Chnese - Share Prema * Janpng Me, José. Schenkman and We Xong Ths verson: June 2003 bstract In ths paper we use data from Chna s stock markets to analyze non-fundamental components n stock prces. Durng the perod , several dozen Chnese frms offered two classes of shares: class, whch could only be held by domestc nvestors, and class, whch could only be traded by foregners. Despe ther dentcal rghts, - share prces were on average 400% hgher than the correspondng shares. We use a model of nvestor overconfdence (Schenkman and Xong (2003)) that produces correlatons among prces, turnover, and volatly, to explan ths premum. y adoptng a panel regresson method, we fnd that the turnover rate of shares s able to explan 20% of the cross-sectonal varaton n - share premum. We also conduct varous specfcaton analyses, and examne the relaton between float, turnover rate, and volatly. * Me s at Stern School of usness, New York Unversy. Schenkman and Xong are at the Department of Economcs, Prnceton Unversy. Schenkman thanks the Natonal Scence Foundaton and The lase Pascal Research Char for research support. We thank Ed Glaeser for valuable suggestons, and Chunhu Mao and ureo de Paula for able research assstance. We are grateful to Mng Ca, Kent Hargs, Shenzhen GT Informaton Technology Inc. and osh Fund Management Company for provdng us wh the Chnese market data. 1

2 I. Introducton In classc asset prcng models stock prces are determned by frm fundamentals,.e., the future stream of dvdends and the dscount factors that apply. 1 The recent Internet bubble presents a challenge to ths methodology for asset prcng. For example, several recent studes 2 show that n some extreme carve-out examples the value of a frm can be less than s subsdary, suggestng the exstence of a non-fundamental component n stock prces. lthough the Internet bubble was dramatc, s stll dffcult to use to examne n more detal the behavor of the non-fundamental component of stock prces because s dffcult to measure the fundamental value of a stock. Chnese stock markets provde a unque opportuny to nvestgate nonfundamental determnants of stock prces. Durng the perod , there were several dozen frms that offered two classes of shares, class and class, wh dentcal rghts. Untl 2001, domestc nvestors could only buy shares whle foregn nvestors could only hold shares. Despe ther dentcal payoffs, class shares traded on average at 400% more than the correspondng shares. In addon, shares turned over at a much hgher rate 500% versus 100% per year for shares. The strkng prce dfference and bg share turnover are often attrbuted to speculatve bubbles by commentators. In ths paper, we formally conduct such an analyss. The dentcal payoff structure of and shares makes possble to control for stock prce fundamentals. The relatve large sample allows a formal statstcal analyss of the non-fundamental component n stock prces. The large panel also perms to control for cross-sectonal dfferences n rsk and lqudy, as well as the tme varaton of nterest rates and rsk premum. Our emprcal analyss s based on a theory of speculatve bubbles developed n Schenkman and Xong (2003), whch lnks nvestors speculatve behavor caused by overconfdence to a non-fundamental component n stock prces. When nvestors have heterogeneous belefs about the value of a stock and short sales are costly, the ownershp of a share of the stock provdes an opportuny to prof from other nvestors' overvaluaton (Harrson and Kreps (1978)). Schenkman and Xong (2003) use 1 See Malkel (2000) for an ntroducton of ths approach. 2 e.g., Lamont and Thaler (2003), Ofek and Rchardson (2003), and Mchell, Pulvno and Stafford (2002). 2

3 overconfdence, the belef by nvestors that ther opnons are more precse than they actually are, to derve an explc dynamcs for heterogeneous belefs among nvestors and a resultng speculatve component for stock prces. Schenkman and Xong also show that cross-sectonally, there should be a posve assocaton between the volume of speculatve tradng, the sze of the non-fundamental component and the volatly of stock prces. Chnese stock markets are well sued for testng the model of speculatve bubbles by Schenkman and Xong. Frst, Chnese stock markets were only recently re-opened n early 1990s after beng closed for nearly half a century. s a result, most domestc nvestors are new to stock tradng, and are more lkely to be subject to behavoral bases such as overconfdence. Second, not only short-sales of stocks by nvestors and dervatve secures are llegal, but also equy ssuance by frms, a common practce that frms use to arbrage the over-valuaton of ther own stocks s severely constraned by the restrctve quota rules mposed by Chnese government. Ths suggests that the -share prces are more lkely to dsplay departures from fundamentals than -share prces. Our analyss emphaszes the cross sectonal correlaton between the - share prema and the turnover rates. We show that the -share turnover s able to explan 20% of the cross sectonal varaton of the - prema. In a panel regresson we fnd that a model wh frm random effects and a tme fxed effect s not rejected by the data, when compared to a model wh both frm and tme fxed effects. In the frm random effect and tme fxed effect model a one standard devaton change n turnover of the share of a frm adds 22 percentage ponts to the - share premum. In addon the varatons n the tme effect coeffcents s well explaned (R 2 =85%) by a lnear combnaton of Chnese and world nterest rates and Chna s rsk premum as measured n the dollar denomnated Chnese soveregns. fter February 2001, Chnese resdents could purchase shares usng foregn currency. We show that after the rule change -share prces, turnover rates and prce volatles all went up dramatcally, ndcatng that the -share market became more smlar to the -share market. We also examne the effect of share float on the - premum and share turnover rate, and the correlaton between turnover rates and the volatly of the - premum. The results are agan consstent wh speculatve tradng. 3

4 Cochrane (2002) ponted out a cross-sectonal correlaton between the market/book rato of US stocks and ther turnover rates durng the Internet bubble perod of However, he does not provde a formal analyss of ths emprcal regulary. Prevous studes on Chnese stock prces, e.g., Fernald and Rogers (2002), and Chen, Lee, and Ru (2001), have emphaszed the effects of cost of capal, payout rato, sales growth, and lqudy factor, but no one has examned the change n the crosssectonal varaton of the - share prema over tme, and s relaton to speculatve tradng. The rest of the paper s organzed as follows. Secton II provdes a bref revew of the model n Schenkman and Xong (2003) that gudes the emprcal analyss. In Secton III, we descrbe some basc facts of the Chnese stock markets. In Secton IV, we analyze the - share premum and other varables related to speculatve tradng. Secton V concludes the paper. II. Theory on Speculatve Tradng and sset Prces In ths secton, we provde a bref revew of a model, analyzed n Schenkman and Xong (2003), whch connects speculatve tradng to hgh stock prces. The basc nsght s that when nvestors have heterogeneous belefs about the value of a stock and short sales are costly, the ownershp of a share of the stock provdes an opportuny (opton) to prof from other nvestors' over-valuaton (Harrson and Kreps (1978)). Schenkman and Xong (2003) use overconfdence to derve the dynamcs of heterogeneous belefs among nvestors, and explcly study a speculatve market for a sngle rsky asset wh lmed supply and many rsk-neutral agents, n a contnuous tme model wh nfne horzon. They show that the resale opton leads to speculatve tradng, and contrbutes a speculatve component to stock prces. In addon, fluctuatons on the opton value add to stock prce volatly. In the model n Schenkman and Xong (2003), the fundamental varable, that determnes future dvdends of the asset, s unobservable to all nvestors. The current dvdend of the asset s a nosy observaton of ths fundamental varable. In addon to the dvdends, there are two other sets of nformaton avalable at each nstant. Ths nformaton s avalable to all agents, however nvestors are dvded n two groups, whch 4

5 dffer on the nterpretaton of the sgnals. Ths dfference s a result of nvestors overconfdence, a behavoral bas that has been observed n psychologcal experments. 3 ecause of overconfdence, when forecastng future dvdends, each group of nvestors places dfferent weghts on the three sets of nformaton, resultng n dfferent forecasts. lthough nvestors n the model know exactly the amount by whch ther forecast of the fundamental varable exceeds that of nvestors n the other group, behavoral lmatons lead them to agree to dsagree. s nformaton flows, the forecasts by agents of the two groups fluctuate, and the group of agents that s at one nstant relatvely more optmstc may become n a future date less optmstc than the agents n the other group. These changes n relatve opnon generate trades. Schenkman and Xong (2003) show that the dfference n belefs between the two groups of nvestors s a lnear mean-revertng process, wh the mean-revertng speed and the volatly parameters determned by exogenous varables such as the nvestors overconfdence level, the asset s fundamental volatly, and the nformaton contaned n the sgnals. When decdng the value of the asset, nvestors consder ther own vew of the fundamental as well as the fact that the owner of the asset has an opton to sell the asset n the future to the nvestors n the other group. In equlbrum, the asset prce has two parts: the current owner s expectaton of all future dscounted dvdends and the value of the resale opton to the current owner. The resale opton can be exercsed at any tme, and the new owner gets n turn another opton to sell the asset n the future. These characterstcs makes the opton mercan and gves a recursve structure. Schenkman and Xong demonstrate that when a trade occurs, the buyer has the hghest valuaton of dscounted future dvdends among all agents, and because of the resale opton, the prce he pays exceeds hs valuaton of future dvdends. gents pay prces that exceed ther own valuaton of future dvdends, because they beleve that n the future they wll fnd a buyer wllng to pay even more. Ths dfference between the transacton prce and the hghest fundamental valuaton can be reasonably called a bubble. numercal example shows that the magnude of the bubble component can be large relatve to the fundamental value of the asset. 3 See Hrshlefer (2001) and arber and Odean (2002) for revews of ths lerature. 5

6 The opton value fluctuates wh the dfference n belefs among nvestors. Snce nvestors n both groups use all avalable nformaton to form ther own belefs, the shocks to the dfference n belefs are orthogonal to shocks to the asset owner s belef. Therefore, the two components n asset prces are ndependent, and the fluctuatons n the value of the resale opton contrbute an extra component to prce volatly. The frequency of asset turnover s determned by the asset owner s optmal exercse strategy of hs resale opton. The asset owner trades off the value of wang versus the opportuny cost of the funds ted n the asset. In equlbrum, an asset owner wll sell the asset to agents n the other group, whenever hs vew of the fundamental s surpassed by the vew of nvestors n the other group by a crcal amount. Passages through ths crcal pont determne turnover. When tradng costs are small, the crcal amount s low, and ths results n hgh share turnover. To summarze, Schenkman and Xong (2003) show that the speculatve motve that orgnates from heterogeneous belefs among overconfdent nvestors, may lead to hgh stock prces, hgh prce volatly, and large share turnover, phenomena that have been observed n varous hstorcal epsodes such as the stock market boom of 1929 or the recent nternet bubble. In partcular, the model ndcates that the opton value (bubble), volatly of the opton value, and the share turnover move n the same drecton when other exogenous varables, such as nvestors overconfdence, amount of nformaton n sgnals and tradng costs change. lthough the dfference of belefs among nvestors s not drectly observable, the comovement among these three varables can be drectly tested. In Schenkman and Xong (2003), nvestors are rsk neutral. However, when nvestors are rsk averse, and when only a lmed number of overconfdent nvestors partcpate n tradng the asset, the total rsk bearng capacy of nvestors and the total amount of floatng shares wll affect the magnude of the bubble. Hong, Schenkman and Xong (2003) analyze such a suaton n a model wh three perods. mong other thngs, they show that when nvestors are rsk averse and tradng costs are zero, the crcal pont n dfference of belefs at whch trades occur s no longer zero, as n the rsk neutral case. The crcal pont ncreases wh the total amount of floatng shares and decreases wh nvestors rsk bearng capacy. These results suggest that, n a cross secton of assets 6

7 subject to common causes resultng n speculatve tradng, the sze of the bubble should vary negatvely wh an asset s float. III. Introducton to the Chnese Stock Market and Data Descrpton. bref Hstory of the Chnese Stock Market Chna made a dramatc transon from a planned economy to a market economy, startng n In 1990, stock exchanges were establshed n Shangha and Shenzhen. These stock exchanges lsted shares of partally prvatzed state enterprses. Growth was spectacular by 2001 each exchange lsted more than 500 companes and the total market cap of Chnese stocks exceeded US$500 bllon. The number of shareholders ncreased 160 tmes, from 400,000 n 1991 to more than 64 mllon n s other emergng markets, Chna dsplayed remarkable booms and busts. Fgure 1 llustrates the behavor of the Shangha share and share ndces. egnnng n 1991, the Shangha ndex went from 100 to 250 n less than a year and then exploded to 1200 by the frst quarter of y md-1992, multples of 50 to 100 tmes earnngs became the norm on the Shangha Stock Exchange and some "hot" ssues fetched even hgher multples. 4 crash started n June 1992, and the Shangha stock market dropped by more than 60 percent n a perod fve months. Whn a few days of htng bottom, speculaton pushed the market rght back up. In just three months, the overall market ndex rose from 500 to a new heght of 1300, but by md 1994 the ndex was back to 500. In the second half of the decade the market generally trended upwards, but as can be seen from the fgure, there were numerous epsodes n whch the ndex lost several hundred ponts n a short perod. For example, durng the perod, there were 20 mn-crashes 4 s an example, Happy Flyng, a consumer electroncs company, sold for over 1,000 tmes s prevous year's earnngs at one pont. pparently nvestors beleved that the earnngs of Happy Flyng would rse astronomcally as a result of equppng 1.2 bllon consumers wh TVs and VCRs, and quckly brng the prce-earnngs rato to a more reasonable level. When the market fell, Happy Flyng not only led the way but also crashed more spectacularly than any other stock, droppng from Yuan to 2.60 Yuan. See Malkel and Me (1997) for more detals. 7

8 when the Shangha market Index lost more than 10% n a month whle smlar mncrashes only happened 8 tmes n the Nasdaq durng the same tme perod. In addon to hgh volatly, the Chnese stock market had very hgh turnover. From 1991 to 2001, class shares turned over on average at an annual rate of 500%, whch s even hgher than the 365% turnover of DotCom frms n ther heyday, and fve tmes the turnover rate of the typcal NYSE stock. 5 There are two mportant features of the Chnese market durng ths tme that makes deal for testng the mplcatons of the model n Schenkman and Xong (2003). The frst s the presence of the two classes of common shares wh dentcal rghts. The second s that regulaton restrcted short sales and the ssuance of seasoned equy offerngs. n mportant obstacle to testng theores of devatons of prces from fundamentals s that the latter are typcally not observable. The Chnese stock markets provde a unque sample. Many Chnese companes ssued two classes of common shares wh dentcal votng and dvdend rghts. They are also lsted on the same stock exchanges. Class shares were restrcted to domestc resdents. Foregners could hold Class shares, but untl February 2001 resdents could not legally purchase ths class of shares. Capal controls however contnue to serve as a restrcton for resdent Chnese to acqure these shares, snce purchase requres foregn currency. oth classes of shares are lsted n the Shangha or Shenzhen stock exchanges. In the perod , at least 73 companes had both class and class shares. Fgure 2 shows the premum of over shares of an equally weghted portfolo. The average premum n exceeded 420% and even after the changes n February 2001, the premum was stll around 100%, reflectng the effect of capal controls. 5 Ofek and Rchardson (2001). 8

9 Chnese resdents also face a very strngent short-sale constrant. Chnese nvestors accounts are kept centrally at the stock exchanges, and s llegal to short-sell. n exchange s computer always check an nvestor s poson before executes a trade. Ths tradng system makes very dffcult for fnancal nstutons to lend stocks to ther clents for short sellng purposes. Moreover, there s no dervatves market for tradng stock futures or optons. 6 So far, there are no legal ways for arbrageurs to take a short poson on eher ndvdual stock or the overall market n Chna. Normally, when equy prces exceed ther fundamental values, companes wll ncrease the supply of eques to arbrage the dfference. aker and Wurgler (2002) present strong evdence of U.S. corporate market tmng, showng that frms tend to ssue equy when ther market value s hgh. Ths automatc market correcton mechansm s mpared n Chna due to tght government's control over IPOs and seasoned equy offerngs (SEOs). Chnese companes need government approval to sell ther equy. The process s hghly polcal and companes often have to wa years for ssung shares. Due to strct quotas, whch generally bnd, many qualfyng companes are unable to take advantage of favorable market condons to sell ther shares.. Speculatve Tradng n the Chnese Market: Some Prelmnary Evdence Our sample covers prces and other characterstcs for all frms that lsted both and shares from However to provde some general descrpton of speculatve behavor n the Chnese market, we also collected data for the much larger set of all companes that lsted shares, though typcally not shares, durng the perod of The data nclude daly closng prces, monthly returns (wh dvdend renvested), annual dvdends and earnngs per share, turnover, and the number of floatng shares. 7 6 The government banned bond futures market n 1994 because of a prce manpulaton scandal and has shut down the dervatves market ever snce. 7 The data are obtaned from Shenzhen GT Informaton Technology Inc., whch has compled s data usng smlar technques as CRSP. 9

10 Table 1 provdes some summary statstcs. Snce our sample perod overlaps wh the U.S. tech bubble, we spl our sample nto two groups: Hgh tech frms and the rest (called low-tech). We classfy frms that belong to Informaton Technology, otech, Telecom, and Computers as hgh-tech companes. 8 For shares, we fnd that the hghtech frms are generally larger n market capalzaton, have hgher prces, and tend to trade more heavly. The monthly turnovers were a staggerng 43% for the hgh-tech frms and 39% for the low-tech frm, whch are equvalent to annual rate of 516% and 468% respectvely. In comparson, even durng the heydays of the U.S. Internet bubble, the average annual turnover of DotCom frms was only 365% and the average annual turnover of NYSE stocks was 98% (see Ofek and Rchardson (2002)). Hgh-tech frms also delvered hgher mean returns to ther shareholders, but they also had hgher market volatly. In comparson wh what was found by Ofek and Rchardson (2002) on Internet stocks n the U.S., the dfferences n behavor between Chnese hgh-tech and the low-tech frms are much smaller. Ths s consstent wh fndngs of Morck, Yeung and Yu (2000), whch shows that Chnese stocks tend to move together. For ths reason we wll not dfferentate between the two type of frms n what follows. IV. Emprcal nalyss. Speculatve Tradng and - Share Prema One of the man huddles n testng a model of asset bubbles s that devatons from fundamental value are unobservable. The presence of the two classes of shares of Chnese stocks wh dentcal votng and dvdend rghts wh a substantal prce dfference suggests the presence of a bubble component n the prce of the more expensve class. Of course, some of ths premum could result from dfferent dscountng of future payoffs by domestc and foregn nvestors, ncludng the rsk of future expropraton of foregners. 9 However, dscountng dfferences cannot explan the cross sectonal varaton of the prema or the correlaton between tradng volume and premum. On the other hand s reasonable to attrbute some of the prema to Chnese nvestors 8 We classfed G (nfo tech ncludng telecom and computer), C5, C51, C5110, C5115 (electroncs), C85, C8501, C8599 (botech, Pharmersutcals), L20, L2001, L2005, L2099 (nfo servces) as hgh tech, and all others as low tech. 9 Fernald and Rogers (2002). 10

11 overconfdence. Overconfdence s more pronounced n the face of more dffcult tasks. 10 The Chnese stock market only resumed s operaton n early 1990s after beng shut down for near half a century and domestc nvestors had ltle prevous experence wh nvestng. It s thus natural to assume that Chnese nvestors are less sophstcated than the typcal foregn nvestors n Chnese stocks. Our sample covers the perod of 1993 to Ths perod covers the market slump from , a major bull market n and a tech stock boom from that concdes wh the tech bubble n the U.S. There s also the mportant regme change n February 2001, when the Chnese government changed the regulatons on -shares, allowng domestc nvestors to legally own and trade them f they have foregn currency. 11 Table 2 and 2 provde some smple comparson between and shares. The comparson s based on matchng and shares of the same companes n the sample. On average, shares had about 10 tmes the market capalzaton of the correspondng shares. shares were also more actvely traded than shares. The average turnover of shares was four tmes that of shares durng the sample perod. There was also more cross-sectonal varaton of turnover n shares than n shares. The average crosssectonal varaton of monthly turnover n shares was 18.5% compared to 5.3% for shares. On the other hand, shares had slghtly larger cross-sectonal varaton of log market capalzaton durng the sample perod. Table 2 also provdes some smple statstcs on the -share prce premum over the correspondng share. On average, shares fetched a 421.8% premum over - shares, even though they were entled to exactly the same legal rghts and clam to dvdends. 12 In addon, average (over tme) cross-sectonal standard devaton of the 10 See Lchtensten, Fschhoff, and Phllps (1982). 11 Some Chnese companes lst ther foregners-only shares on the Hong Kong Stock exchange (Called H shares). Our study does not nclude the H shares, snce we lke to mnmze the mpact of overseas market on the prce movement of foregners-only shares. ekaert and Uras (1999) shows that the prce of mercan Depos Recepts (DRs) of foregn companes lsted n the U.S. are often nfluenced by the prce market movements n New York. The Hong Kong Stock exchange also has more strngent lstng requrements such as more rgorous accountng and dsclosure rules. s a result, H share companes tend to be much larger, comparng to -share companes. 12 Snce shares were traded n dollars and shares n Yuans, the dfference depends on the 11

12 prema s 167.3%. The presence of such a large domestc share premum s que strkng, gven the fact that domestc shares generally sell at a dscount n many emergng and developed markets. Hetala (1989), aley (1994), aley and Jagtan (1994), and Stulz and Wasserfallen (1993) have all found prce dscount for domestc shares n Fnland, Indonesa, Malaysa, the Phlppnes, Sngapore, Swzerland, and Thaland. These authors have used lqudy factors, supply and demand factors to explan the dscount. ut they have not lnked the prce dfference to speculaton. Fgure 2 presents a graphc plot of the equally weghted average shares premum over tme. The premum rose from 300% n prl 1993 to about 800% n March 1999 and then fell to 100% at the end of The relaxaton of restrctons on purchase of shares by domestc nvestors n February 2001 dd not elmnate all prema, snce domestc Chnese nvestors have lmed access to the necessary foregn currency. Fgure 2 also provdes the number of frms used n our study of - prema. Ths number changes over tme because of lstngs and de-lstngs and grows, n the sample perod from less than 10 to over 70. Fgure 3 plots the cross-sectonal standard devaton of prce prema over tme. It fluctuates from 50% to over 400%. casual comparson between Fgure 1 & 3 ndcates that ths varaton may be related to the prce level n the shares market. Could the exstence of a speculatve bubble help explan the large varaton of prema on shares? In ths secton, we propose a formal regresson analyss to test ths vew. ccordng to the theory of speculatve bubbles descrbed n Secton II, -share prces can be decomposed as the sum of two components, a fundamental component and a bubble component. The fundamental component s the current expected value of dscounted future dvdends and we assume, n analogy to Gordon s Growth Formula, that can be wrten as R E ( t) g, where E s the expectaton of current (unobservable) earnngs, g s growth rate and R (t) the dscount rate that apples. R (t can be determned by a verson of CPM: ) exchange rate. We used the offcal rate of the ank of Chna. black market rate would lower the average premum, but would not affect the cross sectonal results that we emphasze. 12

13 Chna R ( t) = r ( t) + β µ, Chna where (t) r Chna s the domestc nterest rate avalable to Chnese nvestors and β µ Chna s the rsk premum of the frm wh β as the beta of the frm s shares and µ as the market premum n Chnese stock market. The speculatve component s proportonal to σ, the volatly of E, and a non-lnear functon q of the dfference of belefs among Chnese nvestors about the frm s fundamental value, x. That s, the frm s -share prce s P E t ) = + σ q ( x ). R ( t ) g ( Chna Smlarly, P E t ) = + σ ˆ q ( x ), R ( t ) g ( where qˆ would determne the bubble n -share market. For smplcy, we wll assume frst that the -share prce provdes a reasonable measure of the fundamental component of the frm value, that s q ˆ = 0. Later we wll treat the case when qˆ > 0. The dscount rate R ( t) s gven by R ( t) = r ( t) + β µ + λ, wh (t) as the world World World p r World nterest rate, β as the beta of the frm s share, µ s the world market premum World and λ p s a soveregn rsk premum assocated wh Chna. Thus, a frm s and share premum can be expressed as P P R g σ ρ = = + q( x ) 1 (1) P R g P If we gnore the dfference n the dscount rates for and shares, and assume that earnng volatly σ s proportonal to -share prce, then ρ q x ). We start wh ths smplfcaton, although we wll brng back later the term nvolvng the dfference n dscount rates. 13 (

14 lthough the dfference of belefs x s not drectly observable, the theory descrbed n secton II mples that s an ncreasng functon of the turnover rate of frm s shares. To explan the cross-sectonal varaton n and share premum gven n Fgure 3, we run the followng regresson of the rato between and -share prces on ther turnover rates: ρ c 0 t + c1tτ + c 2t = τ, (2) where τ = log(1 + turnover ) and τ = log(1 + turnover ). Here, we expect the coeffcent c1t to be posve. We ncorporate the turnover of shares n the regresson, snce s possble that a speculatve bubble may also exst n shares. If ths s the case, then the coeffcent c 2t should be negatve. nother explanaton for - share premum s a lqudy dscount for shares, snce shares, whch have on average 10% of the - share float, mght be llqud. If so, we expect that frms wh smaller share turnover would have a bgger prce dscount n shares and a hgher - share premum. Thus, the share llqudy argument would also mply a negatve value for coeffcent c 2t. The results of ths regresson are reported n Table In the perod between prl 1993 and December 2000, and -share turnovers explan on average 25% of the cross-sectonal varaton n - share premum. The average c 1t, the coeffcent on - share turnover, s posve and hghly sgnfcant wh a Fama-Maceth t- statstcs of 8.3, 14 and -share turnover explans 20% of the cross sectonal varaton of the premum. 5% ncrease n -share turnover would ncrease a stock s - premum by more than 15%. We also observe that c 2t coeffcent s posve on average, nconsstent wh eher the bubble or the lqudy dscount explanaton of shares, but s t-stat s nsgnfcant. 13 Durng the perod of , the frst day returns for Chnese IPO averaged 211% n hghtech ndustres and 141% n other ndustres. For ths reason we exclude from our data set observatons that correspond to the frst twelve months after an IPO. 14 The Fama-Mceth t-statstcs are computed by takng the tme seres mean dvded by standard devaton of the parameter estmates and tmes the square root of the number of tme perods mnus one. 14

15 . Specfcaton Test In the regresson specfcaton of equaton (2), we have gnored the dfference n the dscount rates for and shares. To ncorporate ths dfference, a natural extenson s to nclude a frm fxed effect and a tme effect. To conserve degrees of freedom, the followng parsmonous form s employed by mposng constant c 1t and c 2t : ρ + = u + c0 t + c1τ + c2τ ε (3) The terms u and c come from lnearzng the term 0t R R g g n equaton (1). The frm fxed effect term u deals wh the effect caused by the frm s growth rate and betas, whle the tme effect term c 0t summarzes varables such as the Chnese nterest rate, the world nterest rate, and the rsk premum assocated wh Chna s polcal rsk. To avod perfect collneary, we set c 01 = 0. Whle the above model s a reasonable extenson to model (2), the downsde s that consumes many degrees of freedom snce we need to estmate each u ndvdually. We can smplfy ths estmaton, f we vew the frm specfc terms as randomly dstrbuted across cross-sectonal uns. More precsely we wll assume that the component u are uncorrelated and wh dentcal varances, and orthogonal to the regressors. That s, 15 E[ε ] =0, E[ε 2 ] = σ 2 ε, var[u 2 ] = σ 2 u, cov[u u j ] = 0 f j, E[ε u j ] = 0 for all, t, and j, E[ε ε js ] = 0 f t s or j. (4) The combnaton of model (3) and assumptons (4) constutes a random effects model. y the same token, we may mpose the random effects restrcton on the tme dmenson nstead of the cross-sectonal dmenson. Ths would mply that c 0t vary randomly over tme. Moreover, we may further smplfy model (3) by elmnatng eher the tme or frm effect. 15 Here we gnore the Chnese as well as the world market premum, snce the ex ante market premums are hard to measure. 15

16 In order to determne whch model should be used, we wll perform a specfcaton test descrbed by Hausman (1978). 16 Under the hypothess gven n (4), both the OLS estmate of (3) and the GLS estmate of the random effect model descrbed n Greene (2002) are consstent, but OLS s neffcent. Therefore, under the null hypothess, a test that s based on the dfference, W = [c θ] -1 [c-θ], = Var[c θ]= Var[c] Var[θ], (5) should be asymptotcally dstrbuted as a ch-square wh 2 degrees of freedom. 17 Here, c and θ and are vector of estmates for c 1 and c 2 wh or whout mposng (4). Table 4 gves the coeffcent estmates for the dfferent model specfcatons as well as results for the specfcaton tests for the perod. The crcal value from the ch-square table wh two degrees of freedom s In our estmaton process, we have used both balanced panel (stocks that have no mssng observaton durng the sample perod) and unbalanced panel (all stocks durng the sample perod). The results are que smlar. Thus, we report most of our results usng the balanced panel but we also report the result for selected model usng unbalanced panel for comparson purposes. ased on the crcal value, we can see that the two most restrctve specfcatons D and E, wh only eher the tme effect or frm effect, are strongly rejected. 18 The model specfcaton C, wh fxed frm effect but random tme effect, s not rejected for the sample perod, but s strongly rejected for the perod wh a χ 2 = Ths s to be expected, snce Fgure 2 shows that the prema vary over tme and are autocorrelated, what volates the orthogonaly assumptons of (4). On the other hand, the model specfcaton, wh tme effect but random frm effect, s not rejected by the data. Ths mples that, whle the fxed tme-effects are mportant for capturng the tmevaryng average premum n Fgure 2, the frm effect s also present but could be treated as a random effect. Whle there could be other cross-secton varables such as rsk and lqudy that nfluence an ndvdual share average premum, these varables are 16 See also Wu (1973). 17 See Greene (2002) for detals. 18 We have also performed two F-tests of specfcatons D and E aganst specfcaton. oth of D & E are strongly rejected as well. 16

17 uncorrelated wh turnover. 19 s a result, these varables do not affect the consstency of the turnover estmates. Under ths specfcaton, ( n Table 4), we can see that turnover has a statstcally and economcally sgnfcant effect on the prema. onestandard devaton ncrease n turnover rases the - premum by 22%. Comparng specfcatons and F, we see that the pont estmates for balanced panel and unbalanced panel are almost dentcal. However, turnover s now statstcally sgnfcant, once we use the extra data. The coeffcent of turnover s smlar to that obtaned n the balanced panel, and the sgn s consstent both wh the exstence of a bubble n shares and wh llqudy n shares. Equaton (1) suggests that the tme effect term, c, s proxng for varables that nclude, at least, Chnese nterest rates, world nterest rates, and the rsk premum from Chna s polcal rsk. Ths suggests that we examne the specfcaton: 0t c 0t ϑ 0 + ϑ1rchna + ϑ 2rworld + ϑ 3ChnaSprd = (6) Intuvely, an ncrease n Chnese nterest rates should lower -share prce due to an ncrease n the dscount rates. Thus, we would expect ϑ 1 to be negatve. lso, an ncrease n world nterest rates should lower -share prces and thus ρ. Moreover, an ncrease n Chna s polcal/soveregn rsk, whch we proxy by usng the spread between Chnese long-term bond and US 10-year bond ( ChnaSprd ), should also lower -share prces. 20 Ths mples that ϑ2 and ϑ 3 should be posve. Here we use the Chnese three- month depos for Chnese rsk free rate r and US three-month Treasury bll rate to proxy for world nterest rate r world Chna. Table 5 presents the results for the tme perod March 1994-December The R 2 s 85%,ϑ1 and ϑ 3 have the rght sgns and are hghly sgnfcant, whle ϑ 2 has the rght sgn but s not statstcally sgnfcant. Hence the tme 19 These varables are constant over tme but vary across stocks and tend to affect the mean premum of ndvdual stocks. 20 Km and Me (2001) dscover that Chna s polcal rsk affect stock prces n Hong Kong. Ths mply that polcal rsk could affect share prces as well, snce nvestors n Hong Kong shares are lkely to nvest n shares as well. 21 Our sample here s a ltle short snce the Chnese Long-term bond data starts at March

18 fxed effect s well descrbed by a combnaton of Chnese nterest rates, world nterest rates and a measure of polcal rsks and each of these varables contrbute wh the rght sgn. C. The 2001 Relaxaton of Restrctons On February 28, 2001, Chnese authores opened up the markets for shares to domestc nvestors provded they used foregn currency. Ths change allows us to further examne the behavor of and share markets. Table 6 reports the market reacton to the change. Panel shows that from February 16, 2001 to March 9, 2001, -share prces on average decreased by 0.5%, and the drop s statstcally nsgnfcant wh a standard devaton of 22%. On the other hand, -share prces jumped on average by 63% and the jump s hghly sgnfcant wh a standard devaton of only 7.3%. Therefore, most prce reacton came from shares. Panel shows the change n share turnover rates around the change n regulaton. efore the event, shares have an average turnover of 12.3%, whle post-event becomes 44.4%, whch s smlar to the -share turnover rate reported n Table 2. Panel C shows the change n -share prce volatly around the event. On average, -share prce volatly ncreased by 236% after the event. ll these observatons ndcate that after allowng Chnese domestc nvestors to buy shares, -share markets behaved lke -share markets,.e., shares turned over faster, prces became hgher, and share prce volatly ncreased. To further nvestgate the behavor of -share markets after February 2001, we report the result of cross-sectonal regresson of - premum to -share and -share turnover n the perod of March 2001 to December 2001 n Panel of Table 3. The coeffcent of -share turnover s stll posve and sgnfcant, whle the coeffcent of - share turnover becomes negatve and also sgnfcant. Ths suggests that after the event, a speculatve component mght have appeared n -share prces. D. Float and Turnover To nvestgate the nature of -share and -share turnover, we run the followng cross-sectonal regressons: 18

19 τ = α + α Log ( MarketCap ) + ε 0 t 1t (7) The results are shown n Table 7. Panel shows that, n the perod between prl 1993 to December 2000, a frm s -share turnover decreases wh s own market capalzaton, and the coeffcent s hghly sgnfcant. On the other hand, Panel ndcates that, n the same perod, a frm s -share turnover ncreases wh s own market capalzaton, and the coeffcent s also hghly sgnfcant. posve relatonshp between -share turnover and s capalzaton s consstent wh the speculatve tradng theory. s shown n Hong, Schenkman and Xong (2003), when nvestors are rsk averse, a larger dfference n belefs s requred to turnover all shares when more shares are floatng. s a result, share turnover rates drop when float ncreases. The negatve relaton between share turnover and share capalzaton s consstent wh the lqudy story, as opposed to a bubble n -shares. shares are usually less lqud. When a frm s -share float becomes larger, more foregn nvestors wll be nterested n tradng n ths share market, and lqudy mproves. s a result, more shares turn over faster. 22 To further nvestgate the behavor of -share turnover after February 2001, the bottom of Panel and of Table 7 reports the cross-sectonal regresson result of and -share turnover rates on ther share capalzaton after the rule change. Ths tme, whle the -share coeffcent remans posve, the share coeffcent becomes negatve and sgnfcant, whch s oppose to the posve coeffcent found for the perod before the event. Ths result further suggests that share markets became more speculatve after they were opened to domestc nvestors. In our basc cross-sectonal regresson of - share premum, we do not control for the market capalzaton of and shares. If nvestors are rsk averse and f each frm has a group of under-dversfed nvestors, the frm sze may affect the share premum. To control for ths potental effect, we add the logarhm of -share market capalzaton and -share market capalzaton to the basc regresson: 22 Chorda, Subrahmanyam and nshuman (2001) provde evdence of posve lnk between frm sze, lqudy and turnover n US stocks. 19

20 ρ = c ) + 0 t + c1 tτ + c2tτ + c3 t Log( MarketCap ) + c4t Log( MarketCap ε (8) The results are reported n Table 8. For the perod prl 1993 to December 2000, the market capalzaton of shares has a negatve and hghly sgnfcant effect on - share premum, consstent wh the hypothess that nvestors n each frm may be undversfed. -share turnover s stll hghly sgnfcant wh a t-stat of 7.15, and explans 14% of cross-sectonal varatons n - share premum. gan, the market capalzaton of shares has a negatve and hghly sgnfcant effect on - share premum, consstent wh the lqudy story. E. Speculatve Tradng and Volatly The speculatve component n -share prces also contrbutes an extra component n -share prce volatly, snce the bubble component fluctuates wh the dfference n belefs among nvestors and these movements are orthogonal to that of the frm s fundamental value. For smplcy, we gnore the dfferences n dscount rates for shares and shares. Then, the fundamental component R E g n -share prce can be approxmated by the correspondng component n -share prce, and the prce dfference between and shares volatly s P P = σ q x ) ( represents the bubble component, and s Vol ( P P )] = σ q'( x ) Vol( x ), [ whch ncreases wh the dfference of belefs among domestc nvestors, x. s we have dscussed already, x can be proxed by the turnover rate of shares. For the perod January 1997 to December 2000, we use the daly stock prces of shares and shares to estmate the monthly volatly of the prce dfference between and shares, 20

21 Vol[ ( P P )]. 23 To examne the effect of speculatve tradng on prce volatly, we further run the followng cross-sectonal regresson: Vol[ ( P P P )] = d + d τ + d τ + d Log ( Shares ) + d Log ( Shares ) + ε 0 t 1t 2t 3t 4t (9) The results are reported n Table 9. On average, the turnover rates and market caps of and shares explan 20% of the cross-sectonal varatons n the bubble component volatly. The coeffcent of share turnover s posve and sgnfcant, consstent wh our hypothess. V. Concluson nalyzng data on Chnese - share prema, we argue that speculatve tradng can contrbute to a sgnfcant non-fundamental component n stock prces. lthough ths s a specal data sample, s behavor s que smlar to that of the recent Internet bubble n the US, and therefore we expect that our results wll help understand speculatve bubbles n more general contexts. Our study also contrbutes to the market segmentaton lerature n nternatonal fnance. Prevous studes, such as Hetala (1989), aley (1994), aley and Jagtan (1994), and Stulz and Wasserfallen (1995) have used capal controls, nformaton asymmetres, corporate governance, lqudy, as well as prce dscrmnaton to explan the prce dfference between foregn and domestc shares. Our analyss ndcates that overconfdence and the resultng speculatve tradng could also help explan ths prce dfference. 23 We use only data from the perod due to a lmaton on access to daly data. 21

22 References aley, W., and J. Jagtan, 1994, Foregn Ownershp Restrctons and Stock Prces n the Tha Capal Market, Journal of Fnancal Economcs 36, aley, W.,1994, Rsk and Return on Chna s New Stock Market, Pacfc-asn Fnance Journal, aker, M. and J. Wurgler, 2002, Market Tmng and Capal Structure, Journal of Fnance 57, arber,. and T. Odean, 2001, The Internet and the Investor, Journal of Economc Perspectves, 15, ekaert, G. and Mchael S. Uras, 1996, Dversfcaton, Integraton and Emergng Market Closed-End Funds, Journal of Fnance 51, Chen, G.,. Lee, and O. Ru, 2001, Foregn Ownershp Restrctons and Market Segmentaton n Chna's Stock Markets, Journal of Fnancal Research 24, Chorda, T.,. Subrahmanyam and V. nshuman, 2001, Tradng ctvy and Expected Stock Returns, Journal of Fnancal Economcs 59, Cochrane, J. (2002), Stocks as Money: Convenence Yeld and the Tech-stock ubble, NER Workng Paper Fama, E. and J. Maceth, 1973, Rsk, Return, and Equlbrum: Emprcal Tests, Journal of Polcal Economy 81, Fernald, J. and J. Rogers, 2002, Puzzles n the Chnese Stock Market, Revew of Economcs and Statstcs 84, Greene, W., 2002, Econometrc nalyss, Prentce Hall. Harrson, M. and D. Kreps, 1978, Speculatve Investor ehavor n a Stock Market wh Heterogeneous Expectatons, Quarterly Journal of Economcs 92, Hausman, J., 1978, Specfcaton Tests n Econometrcs, Econometrca 46, Hetala, P., sset Prcng n Partally Segmented Markets: Evdence from the Fnnsh Market, Journal of Fnance 44, Hrshlefer, D., 2001, Investor Psychology and sset Prcng, Journal of Fnance 56, Hong, H., J. Schenkman, and W. Xong, 2003, Float and ubbles, n preparaton. 22

23 Lamont, O. and R. Thaler, 2003, Can the Market dd and Subtract? Msprcng n Tech Stock Carve-outs, Journal of Polcal Economy 111, Km, K and J. Me, 2001, "What Makes the Stock Market Jump?---n nalyss of Polcal Rsk on the Hong Kong Stock Returns", Journal of Internatonal Money and Fnance, Lchtensten, S.,. Fschhoff, and L. Phllps, 1982, Calbraton of Probables: The State of the rt to 1980, n Danel Kahneman, Paul Slovc, and mos Tversky, ed.: Judgement under Uncertanty: Heurstcs and ases, Cambrdge Unversy Press, Cambrdge. Malkel,., 2000, Random Walk Down Wall Street, W. W. Norton & Company. Malkel,., and J. Me, 1997, Global argan Huntng, Smon and Schuster, New York. Mchell, M., T. Pulvno, and E. Stafford, 2002, Lmed rbrage n Equy Markets, Journal of Fnance 57, Morck, R.,. Yeung, and W. Yu, 2000, Why Do Emergng Markets Have Synchronous Stock Prce Movements? Journal of Fnancal Economcs 58, Ofek, E. and M. Rchardson, 2003, Dotcom Mana: The Rse and Fall of Internet Stock Prces, Journal of Fnance 58, Schenkman, J. and W. Xong, 2003, Overconfdence and Speculatve ubbles, Journal of Polcal Economy, forthcomng. Stulz, R.M. and W. Wasserfallen, 1995, Foregn Equy Investment Restrctons and Shareholder Wealth Maxmzaton: Theory and Evdence, Revew of Fnancal Studes, Wu, D.-M. (1973) lternatve tests of ndependence between stochastc regressors and dsturbances, Econometrca 41 (4),

24 Table 1: Summary statstcs for monthly data ( shares) (1/ /2000) Varables Hgh tech Mean Medan Std Market Cap (llon) Yes No Prce (Yuan) Yes No Turnover Yes No Volume (Mllon) Yes No Monthly return (%) Yes No Std (%) Yes No

25 Table 2: Summary statstcs of - pars.. Market capalzaton of the pars of and shares (4/ /2001) Mean Medan Mn Max Std. shares (bllons of Yuans) shares (bllons of Yuans) Rato ( / ) 10.3% 8.6% 1.5% 85.2% 10.5%. Comparson between and shares usng Monthly Data (4/ /2001) Turnover Log(1+Turnover) Log (market cap) Premum Mean % verage S.D.* % * ndcate average cross-sectonal standard devaton over tme. 25

26 Table 3. Summary Of verage Cross-Sectonal Regresson Of - Share Premum On Log Turnover P P ρ = = c 0 t + c1tτ + c 2t P. Cross-Sectonal Regressons (prl 1993-December 2000) C 0t C 1t C 2t verage dj.r 2 verage Coeff FM t-stat verage Margnal R τ. Cross-Sectonal Regressons (March 2001-December 2001) C 0t C 1t C 2t verage dj.r 2 verage Coeff FM t-stat verage Margnal R Note: τ = log(1 + turnover ) and τ = log(1 + turnover ). verage Coeff. provde the tme-seres average of coeffcents and FM t-stat s computed by T 1 * verage Coeff. dvded by the standard devaton of coeffcents based on Fama-Macbeth (1973). T s the number of tme perods. verage Margnal R 2 s the tme-seres average of margnal R 2 for the cross-sectonal regresson over tme. 26

27 Table 4: Specfcaton Test for Pooled Tme-seres and Cross-Sectonal Regressons for - premum (prl 1993-December 2000) P P ρ τ + ε = = u + c0 t + c1τ + c2 P C 1 C 2 djusted R 2. Tme-varyng C 0t, Coeff Frm fxed effects t-stat Tme-varyng C 0t, Coeff * Frm Random Effect t-stat Economc Sgnfcance Specfcaton Test aganst : χ 2 = 1.46 Not Rejected C. Frm fxed effects, Coeff * Tme Random Effect t-stat Specfcaton Test aganst : χ 2 = 3.23 Not Rejected** D. Tme-varyng C 0t Coeff Only t-stat Specfcaton Test aganst : χ 2 = 76.3 Rejected E. Frm fxed effects Coeff Only t-stat Specfcaton Test aganst C: χ 2 = Rejected F. Tme-varyng C 0t, Coeff Frm Random Effect t-stat Unbalanced Panel Specfcaton Test aganst : χ 2 = 0.0 Not Rejected Note: Specfcatons -E are estmated based on a balanced panel of 28 stocks wh no mssng data from 4/ /2000. Specfcaton F s estmated based on an unbalanced panel of 73 stocks wh mssng data from 4/ /2000. * djusted R 2 not reported due to the use of generalzed least squares. ** Ths specfcaton s rejected for the Jan 1997-Dec 2000 perod wh χ 2 =

28 Table 5. Explan the Varaton of c 0t (March 1994-December 2000) c 0t = ϑ 0 + ϑ1rchna + ϑ 2rworld + ϑ 3ChnaSprd ϑ 0 ϑ 1 ϑ 2 ϑ dj.r 2 3 Coeff t-stat Note: The t-statstcs are computed usng Newey-West autocorrelaton-consstent standard errors wh 6 lags. Here we use the Chnese three- month depos for Chnese rsk free rate rworld bond. r Chna and US three-month treasury bll rate to proxy for world nterest rate. s defned as the spread between Chnese long-term bond and US 10-year ChnaSprd 28

29 Table 6. Market Reacton To The Event Of Openng Shares To Domestc Investors In February Prce reactons (2/16/2001 3/09/2001) N Mean STD share prce changes % 22% share prce changes 73 63% 7.3%. Changes n monthly turnover of shares (6 months before and after) N Mean Medan STD Pre-event turnover % 10.5% 7.7% Post-event turnover % 44.7% 15.8% Rato (Post/Pre) C. Ratos of post-event and pre-event share prce volatly (6 months before and after) N Mean Medan STD Rato Note: The tradng of three frms had been halted durng the perod. 29

30 Table 7. Explanng Cross-Sectonal Varaton of Turnovers by Market Capalzaton. Summary Of verage Cross-Sectonal Regressons for shares τ = α + α Log ( MarketCap ) + ε 0 t 1t prl 1993-December 2000 α 0t α 1t verage dj.r 2 verage Coeff FM t-stat March 2001-December 2001 α 0t α 1t verage dj.r 2 verage Coeff FM t-stat Summary Of verage Cross-Sectonal Regressons for shares τ = α + α Log ( MarketCap ) + ε 0t 1t prl 1993-December 2000 α 0t α 1t verage dj.r 2 verage Coeff FM t-stat March 2001-December 2001 α 0t α 1t verage dj.r 2 verage Coeff FM t-stat Note: τ = log(1 + turnover ) and τ = log(1 + turnover ). verage Coeff. provde the tme-seres average of coeffcents and FM t-stat s computed by T 1 * verage Coeff. dvded by the standard devaton of coeffcents based on Fama-Macbeth (1973). T s the number of tme perods. verage Margnal R 2 s the tme-seres average of margnal R 2 for the cross-sectonal regresson over tme. 30