heterogeneous expectations and stock prices in segmented markets: application to chinese firms

The Quarterly Review of Economics and Finance44 (2004) 521–538

Heterogeneous expectations and stock prices in segmentedmarkets: application to Chinese firms

Lianfa Li, Belton M. Fleisher∗

Department of Economics, The Ohio State University, 1945 N. High Street, Columbus, OH 43210, USA

Received 8 November 2002; received in revised form 12 May 2003; accepted 28 July 2003Available online 6 November 2003

Abstract

We explain the price discount and high returns for B shares relative to their A-share counterparts inChinese stock markets. We report evidence that the higher the dispersion of domestic analysts’ forecasts,the lower are A-share returns, implying that the short-sales restriction is binding for trading in A shares.In contrast, there is no evidence that the short-sales restriction is binding for trading in B shares. Anotherfactor contributing to low B-share prices and high returns is the near- or total absence of non-domesticanalysts’ forecasts for a significant proportion of companies. Our evidence that “neglect” increasesB-share returns is significant and robust.© 2003 Published by Board of Trustees of the University of Illinois.

JEL classification: G12, G14, O53

Keywords: China’s stock market; Market segmentation; Neglected firms; Short-sales restriction; Heterogeneousexpectations

1. Introduction

Many investors choose to diversify their portfolios by including an international cross-sectionof equities. In countries where all equities are available to foreign investors, foreigners pay thesame price as do domestic investors for shares in a given company. However, some countriesrequire that a minimum proportion of a company’s equity be owned by domestic investors,and to implement this requirement they have created two or more classes of shares. In mostcases, shares designated for foreign ownership have the same claim on cash flow and assets

∗ Corresponding author. Tel.:+1-614-292-6429; fax:+1-614-292-3906.E-mail address: [email protected] (B.M. Fleisher).

1062-9769/$ – see front matter © 2003 Published by Board of Trustees of the University of Illinois.doi:10.1016/j.qref.2003.07.003

522 L. Li, B.M. Fleisher / The Quarterly Review of Economics and Finance 44 (2004) 521–538

as those available to domestic investors. However, significant price discrepancies between thedomestic and foreign share classes are frequently observed. Understanding the causes of thesepricing anomalies has challenged analysts and scholars. In this paper, we address the case ofa persistent price discount for foreign shares in an important emerging market, namely, thePeople’s Republic of China.

Scholarly concern for the price anomalies exhibited in stock markets where foreign investorsare segmented from domestic investors is reflected in research published over the past twentyyears or more. Examples include Switzerland, where foreign investors could not buy restrictedshares, which were registered shares available only to resident investors, before November17, 1988. Foreigner purchases were confined unrestricted shares, which were bearer sharesavailable to all investors irrespective of their residence or citizenship. The unrestricted shareswere sold at a premium price. In Thailand before 1992, shares held by foreigners traded onthe Alien Board, while domestic investors traded separately on the Main Board. Alien Boardshares were priced higher than their counterparts traded on the Main Board. In Mexico prior to1993, there were multiple classes of shares available to various classes of investors; regulationsdifferentiated between domestic and foreign investors, individual and institutional investors,and between general and financial shares. In contrast to these and other examples not cited,scholars have concluded that the China appears to be atypical in that foreign shares (B-shares)traded in domestic stock markets have consistently traded at a discount to domestic shares(A-shares).Fernald and Rogers (2002)addressed this anomaly in their “Puzzles in the ChineseStock Market” andBailey, Chung, and Kang (1999)referred to “The Strange Case of China.”

In order to understand the strange Chinese puzzle alluded to in the titles cited above, we extendL’Her and Suret’s (1995)model of heterogeneous expectations to include multiple classes ofinvestors. We also consider the role of the neglected-share effect1 in the Chinese foreign-sharediscount puzzle. Our findings are two-fold: first, we find that heterogeneous expectations inthe context of multiple investor classes has significant power in explaining the lower returnsand relatively high prices exhibited by China’s A-shares; second, we identify foreign analysts“neglect” of B-shares as a significant contributor to the high returns and price discount for theseshares relative to their A-share counterparts.

The rest of the paper proceeds as follows.Section 2contains a brief description of China’sstock markets. We also discuss the situation for earnings forecasts in China.Section 3relatesour study to previous literature.Section 4presents our econometric model, andSection 5reportsempirical results. The final section contains the summary and conclusion.

2. The institutional and legal environment of China’s stock markets

China’s stock markets were opened in 1990 (Shanghai Stock Exchange—SHSE) and in 1991(Shenzhen Stock Exchange—SSE). Many of China’s corporatized enterprises have been issu-ing multiple classes of shares in these exchanges since the early 1990s. One class is designatedA shares and may be purchased by domestic Chinese investors. Another class of shares is des-ignated B shares, which are foreign-invested shares issued domestically by Chinese companies.B shares are also known as Special Shares. They are subscribed and traded in foreign currenciesand are listed and traded in securities exchanges inside China, either the SHSE or SSE. The first

L. Li, B.M. Fleisher / The Quarterly Review of Economics and Finance 44 (2004) 521–538 523

Table 1Number of firms listing various classes of stocks, end of 2001a

Share classes Number of listed firms

All Firms listing A-shares 1136Firms listing only A-shares 1023Firms listing both A- and H-shares 25Firms listing both A- and B-shares 88

All Firms listing B shares 112Firms listing both A- and B-shares 88Firms listing only B-shares 24

aSource: China Securities Regulatory Commission (CSRC).

B-share was issued in the SSE in 1992. Until February 19, 2001, the B-shares market was openonly to foreign investors. The third major exchange where Chinese shares are traded—HongKong, offers H shares, and many of the firms issuing H shares also offer A shares in one of themajor domestic Chinese markets.2 Table 1shows the distribution of listed stocks as of the endof 2001.

Before July 1, 1999, the legal documents governing China’s stock market were not integrated.Various regulations and rules were contained in diverse documents. The Securities Law of Chinatook effect on July 1, 1999. According to Article 2 of the law, “this Law is applicable to theissuing and trading in China of shares, corporate bonds and such other securities as are lawfullyrecognized by the State Council.” In other words, the law applies to both A- and B-shares. InArticle 36, the law states “Securities companies may not engage in securities trading activitiesthat are financed by funds or securities obtained from their clients.” In other words, short sellingactivities are prohibited on both A- and B-share markets.

A major interest of stock-market analysts and researchers over the past 10 years has been thesignificant price “discount” for B-shares relative to their A-share counterparts. Two exceptionsare the first several months of 1992, when the Renminbi exchange rate was volatile and A shareswere sold at a relative discount, and June to July 1994, when the A-share market collapsed.Since both exceptions took place when the market was abnormal, we do not consider them in ouranalysis.Fig. 1presents a sketch of the price ratio of A-shares over B-shares (PA/PB − 1) fromFebruary 1, 1998 to March 1, 2002. The average price ratio of A-shares over B-shares (PA/PB−1)was 5.3 from 1/1/99 to 2/26/01 and 1.1 from 2/26/01 to 12/31/01 (Karolyi & Li, 2003).

A major concern of our research is the influence of stock-market analysts’ earnings forecastsfor stock-price behavior. A-share investors typically do not have easy access to foreign analysts’projections, which in any event, apply only to those enterprises issuing B shares. In contrastto most foreign firms, Chinese securities firms treat their earnings forecasts as internal dataand are reluctant to publicize them. Moreover, limited research budgets restrict the ability ofmost firms to make reliable earnings forecasts for most stocks. Indeed, many lengthyReportsof Investment Value3 have no quantitative earnings forecasts.

In this study, we use earnings forecasts from domestic analysts for the A shares of 218 firms.We collected these forecasts from several securities firms and one research institution, namelyGuoTai-JunAn Securities, ShenYin-WanGuo Securities, Hai-Tong Securities, Dong-fang Secu-


Feb-99

Feb-98

Feb-01Feb-00

Mar-020

12

34

56

7

89

Mar-97 Jul-98 Dec-99 Apr-01 Sep-02

Time

Cu

rren

cy-a

dju

sted

rat

io o

f A

-sh

are

pri

ce t

o B

-sh

are

pri

ce (

Pa/

Pb

-1),

sa

mp

le m

ean

mean of the price ratio best-fitting trendlineSource: The Datastream International.Note: The solid line is a trend line. The sample is computed as the average of 76 firms' currency-adjustedratio of A-share price to B-share price, (PA/PB - 1) at each monthly time point

Fig. 1. Relative price of A-shares to B-shares for Chinese stocks.

rities and the Xin-Lande Research Institute. Given the large market share of these institutions,we believe that they constitute a representative sample of analysts’ forecasts. For B shares, weuse data available from the Institutional Brokers Estimate System (IBES). IBES collects earningforecasts of analysts in major international financial institutions, such as Goldman Sachs, Mer-rill Lynch, CS First Boston, Salomon Brothers, etc. In the IBES data, 584 of 76 enterprises thathave dual-listed shares (i.e., enterprises that issue both A- and B-shares) do not have two or moreearning forecasts from foreign analysts. Because the standard deviations of earnings forecastsfor these 58 B shares are not defined (see Table 3a), we define these shares to be neglected shares.

3. Relation to the previous literature

Our paper combines two bodies of studies, consisting of research on the discount puzzle inChina’s stock market and research on the role of analysts’ earnings forecasts in determiningstock prices. We apply a revised model of heterogeneous expectations that includes multipleinvestor classes and incorporates the neglected-share effect to extend the work ofSwidler (1988)andL’Her and Suret (1995). Here we review these two literatures, respectively.

3.1. Studies related to the price discount puzzle in China’s stock markets

Hietala (1989)analyzed the prevalence of price premiums for Finnish shares allocated toforeign buyers, who are allowed to invest in all stocks of all companies, subject to a maximumforeign-ownership restriction. Foreign-owned shares must display a unique “stamp.” He con-cluded that foreign investors required lower rate of return than did domestic investors, becausethe foreign-ownership constraint was effectively binding.Bailey (1994)attributed the B-sharediscount in China to a lower opportunity cost of investable funds for Chinese citizens, who havebeen highly constrained in investment opportunities for their savings.Stulz and Wasserfallen


(1995)argued that price discrimination in the presence of differences in domestic and foreigninvestors’ demand elasticities explains the price premium observed for foreign-class shares inSwitzerland, andDomowitz, Glen, and Madhavan (1997)argued that Stulz and Wasserfallen’smodel applies to the Mexican case, as well.Ma (1996)proposed the hypothesis the A- andB-share investors in China have different attitudes toward risks.Ariff and Khan (1998)doc-umented that the foreign ownership restriction, liquidity and systematic risk were significantin explaining the price premium for foreign shares in Singapore’s stock market.Chakravarty,Sarkar, and Wu (1998)found evidence for their hypothesis of informational asymmetry in Chi-nese markets by using coverage in media as an explanatory variable. In a study of segmentedstock markets in 11 countries,Bailey et al. (1999)regarded China as a “. . . strange case. It isdifficult to explain why Chinese investors pay large premiums for restricted shares relative towhat foreigners typically offer for matching unrestricted shares.” They raised the hypothesis thatA-share traders follow a momentum strategy.Sun and Tong (2000)suggested that the A-shareprice premium could be explained by the existence of substitutes for the B-share market in HongKong, such as H-shares and “red-chip” shares. They claimed that their argument is consistentwith the differential-demand hypothesis.Chen, Lee, and Rui (2001)attributed the price differ-ence primarily to illiquidity of the B-share market.Fernald and Rogers (2002)echoedBailey(1994)and presented evidence that domestic investors have lower expected rates of return thando foreign investors in Chinese shares and as a consequence require lower returns and payhigh prices for companies of a given risk.Karolyi and Li (2003)studied price responses to theregulation change of February 19, 2001 and find support for the hypotheses of differential riskand asymmetric information. This paper extends this literature by applying the revised modelof heterogeneous expectations that incorporates the neglected-share effect as described above.

3.2. Research on analysts’ earning forecasts and the ‘neglected-share’ effect

There are some studies showing that the dispersion of analyst forecasts and neglected-shareeffects are negatively and positively related to excess returns, respectively.Arbel and Strebel(1983)used the number of analysts regularly following a stock to measure that stock’s degreeof neglect.Carvell and Strebel (1987)concluded that the neglected firm effect can dominate thesmall firm effect.Swidler (1988)adopted a simple CAPM to evaluate the simultaneous effects ofshort-sales constraints and dispersion of earning forecasts.L’Her and Suret (1996)found the av-erage and dispersion of analysts’ earning forecasts are, respectively, positively and negatively re-lated to stock prices.Jones and Lamont (2001)reported evidence that binding short-sales restric-tions can lead to overpriced stocks.Lamont and Thaler (2003)asserted that with short-sales con-straints the law of one price needs not apply to identical assets. Their empirical research showedthat shorting costs could be high enough to eliminate arbitrage opportunities. We extend thisliterature by adapting existing models to explain the price puzzle of China’s dual-listed stocks.

4. A model of earning forecasts, heterogeneous expectations and stock prices

The effect of heterogeneous expectations in CAPM was addressed byMiller (1977), and hisexposition remains cogent. With a fixed supply of shares and a short-sales restriction, optimistic


Table 2Summary of notations

Ak andBj Absolute risk aversion coefficients for domestic and foreign investors

Wkt Wealth level of investork at timet

P andX M × 1 price vectors at timet = 0 and 1

N1 andN2 Number of domestic and foreign investors

EAk (X), E

Bj (X) Estimates for prices vectors at timet = 1 for domestic and foreign investors

Ω The same beliefs for the covariance matrix of risky assets prices

RAf andRB

f Risk-free returns for domestic and foreign investors

µAk , µB

j Mean ofWk1 for domestic and foreign investors

σAk , σB

j Variance ofWk1 for domestic and foreign investors

uAk , uB

j , uAkl, u

Bjl M × 1 Lagrange multiplier vector for short-sales restrictions for domestic and foreign

investors, withuAkl, u

Bjl being the multipliers for risky assetsl

qAk , qB

j M × 1 demand vector for risky assets for domestic and foreign investors, respectively

Dp M ×M diagonal price matrix with the elements ofp on the diagonal

vAk , vB

j vAkl, v

Bjl M × 1 implicit return vector for short-sales restrictions for domestic and foreign

investors, withuAk = Dpv

Ak , uB

j = DpvBj , and withvA

kl, vBjl being multiplier for risky

assetslvl vl represents eithervA

kl or vBjl

τ∑N1

k=1A−1k R

Af +∑N2

j=1B−1j R

Bf

αAk

(∑N1k=1A

−1k R

Af

)/[∑N1

k=1A−1k R

Af +∑N2

j=1B−1j R

Bf

]αBj

(∑N2j=1B

−1j R

Bf

)/[∑N1

k=1A−1k R

Af +∑N2

j=1B−1j R

Bf

]QA ,QB,Q M × 1 equilibrium aggregate quantities for domestic, foreign and all investors

R,Rl M × 1 random return vector for risky assets and random return of risky assetl

Rm Random return of market portfolio of risky assets,Q′X/Q′P

β, βl M × 1 beta vector for risky assets, withβl being beta for risky assetl

investors bid up share prices, generating lower returns. Pessimistic investors cannot short themarket due to the short-sales restriction. A testable hypothesis is that share prices and returnsare, respectively, positively and negatively correlated to the dispersion of investors’ opinions.L’Her and Suret (1995)have modeled this idea in a fairly standard framework. They haveshown that, in the case of heterogeneous expectations and a binding short-sales restriction,the CAPM’s result that beta is the only measure of risk in the market is no longer valid.We extend their model to accommodate heterogeneous expectations held by multiple types ofinvestors.

We first solve the utility maximization problem with short-sales constraints for both domesticand foreign investors (indexed byk andj, respectively) to obtain their demand vectors for riskyassets,qA

k , qBj for all k and j (seeTable 2for definitions of notations). Second, we find the

equilibrium price vectorP by aggregation. We then transform the equilibrium price equationinto an equilibrium return equation (Eq. (1)). All assumptions and derivations are described in


appendix.

N1∑k=1

αAk

EAk (Rl)

RAf

+N2∑j=1

αBj

EBj (Rl)

RBf

− 1

= β1l

N1∑k=1

αAk

EAk (Rm)

RAf

+N2∑j=1

αBj

EBj (Rm)

RBf

− 1

−

N1∑k=1

αAk

vAkl

RAf

+N2∑j=1

αBj

vBjl

RBf

for l = 1,2, . . . ,M (1)

Eq. (1) is the equilibrium return equation for an asset market with multiple types of in-vestors who have heterogeneous expectations and different risk-free returns, under a bind-ing short-sales restriction. The first term on the right side would be the return provided thatthe short-sales restrictions were not binding. The second term on the right represents the im-plicit return due to the short-sales restriction. All the terms are weighted by the ratio of theproduct of investors’ risk tolerance and risk-free return to the sum of investors’ products ofrisk tolerances and risk-free returns. The main reason that we cannot consolidate multipletypes of investors into one type is that the different types of investors face different risk-freereturns.

There are two more scenarios related to the above model. In these cases, the market isaccessible only by a single type of investor, and other types of investors are excluded. Case Iwould be that only domestic investors are allowed to trade, and foreign investors are excluded.In this case, the equilibrium returns equation with binding short-sales restriction isEq. (2),simply imposing the constraintN2 = 0.

N1∑k=1

αAk

EAk (Rl)

RAf

− 1 = β2l

(N1∑k=1

αAk

EAk (Rm)

RAf

− 1

)−

N1∑k=1

αAk

vAkl

RAf

for l = 1,2, . . . ,M

(2)

Case II would be that only foreign investors are allowed to trade, and domestic investors areexcluded. In this case, the equilibrium returns equation with binding short-sales restriction isEq. (3), simply imposing the constraintN1 = 0.

N2∑j=1

αBj

EBj (Rl)

RBf

− 1 = β3l

N2∑j=1

αBj

EBj (Rm)

RBf

− 1

−

N2∑j=1

αBj

vBjl

RBf

for l = 1,2, . . . ,M

(3)

In China’s stock markets,Eq. (1)represents the B-share market after February 19, 2001;Eq.(2) (case I) represents the A-share market; andEq. (3)(case II) represents the B-share marketbefore February 19, 2001.

Assuming that the numbers of domestic investors trading simultaneously cross-listed firmsare equal, then subtractingEq. (2)from Eq. (1)yields the “excess return” of B shares over Ashares after February 19, 2001, as follows:


(1)− (2) =N2∑j=1

αBj

EBj (Rl)

RBf

= β1l

N1∑k=1

αAk

EAk (Rm)

RAf

+N2∑j=1

αBj

EBj (Rm)

RBf

− 1

−β2l

(N1∑k=1

αAk

EAk (Rm)

RAf

− 1

)−

N2∑j=1

αBj

vBjl

RBf

for l = 1,2, . . . ,M (4)

Assuming again that the numbers of domestic investors trading simultaneously dual-listed firmsare equal, then subtractingEq. (2)from Eq. (3)yields the “excess return” of B shares over Ashares before February 19, 2001:

(3)− (2)=N2∑j=1

αBj

EBj (Rl)

RBf

−N1∑k=1

αAk

EAk (Rl)

RAf

= β3l

N2∑j=1

αBj

EBj (Rm)

RBf

− 1

− β2l

(N1∑k=1

αAk

EAk (Rm)

RAf

− 1

)

+N1∑k=1

αAk

vAkl

RAf

−N2∑j=1

αBj

vBjl

RBf

for l = 1,2, . . . ,M (5)

Eqs. (4) and (5)are derived from the first three equations. Thus, we focus on the first threeequations in our testing.

Finally, as inL’Her and Suret (1995), the multiplier of a short-sales restrictionvl is theaverage opportunity cost induced by the restriction, which is positive and a linear function ofthe dispersion of beliefs under a normality assumption.

vl = dispersion of beliefs√2π

(6)

In short, an increase in the dispersion of beliefs will decrease expected returns under a bindingshort-sales restriction (seeEqs. (1)–(3)), which implies that the coefficient before the dispersionof analysts’ forecasts should be negative in explaining expected returns.

In the model specified above, the dispersion of opinions affects returnsnot through systematicrisk but through a short-sales constraint. Therefore, a negative coefficient for dispersion ofanalysts’ forecasts also implies that the short-sales constraint is binding. An unusual caseoccurs when the standard deviation of analysts’ forecasts cannot be calculated, i.e., when thereis no forecast or only one forecast for a share, which we take as the operational definition of aneglected share. UnlikeArbel and Strebel (1983), we use both a continuous variable in additionto a discrete variable to represent cases in which the standard deviation of forecasts is definedand when it is not, respectively.


We relate multiple types of analysts’ forecasts with the returns on multiple types of securi-ties, based on institutional features of the securities market. We include domestic and foreignanalysts’ forecasts in the same regression to explain stock returns.5

5. Empirical analysis

5.1. Data description

Our data are collected from several sources. Stock returns come from Datastream Interna-tional. Our sample includes data for 76 cross-listed stocks for the period February 1, 1998–February 1, 2002 (Tables 3b and 3c). We gathered earnings forecasts of domestic analystsfor 2186 A-share stocks for the period February 1, 1999–February 1, 2002.7 Betas are fromBloomberg with respect to the corresponding Shanghai and Shenzhen market indices for Ashares and MSCI World Price Index for all the B shares. To establish the robustness of ourresults, we use three horizons—1, 2 and 3 years to compute annual returns and beta. In cal-culating beta, we use weekly data for the 2- and 3-year horizons and daily data for the 1-yearhorizon.8,9 We gathered domestic analysts’ earning forecasts from several Chinese securitiesfirms. Although our collection of analyst’s forecast is not complete, it still worth studying as

Table 3aSummary statistics of the sample (I)

Firms listingA-shares

Firms listing as bothA- and B-shares

Sample size 218 76Number of firms having domestic earning forecasts 218 76Number of firms with standard deviation of domestic earning forecasts 202 76Average mean-adjusted standard deviation of domestic earning forecasts 0.13 0.79Number of firms with one or less foreign earning forecasts NA 58Number of firms with standard deviation of foreign earning forecasts NA 18Average mean-adjusted standard deviation of foreign earning forecast NA 0.29

Table 3bSummary statistics of the sample (II), firms listing as A-shares

Raw return Residual from CAPM (A-shares)

1-year beta 3-year beta

Number of firmsa Mean Number of firms Mean Number of firms Mean

2/1/2001–2/1/2002 218 −0.237 218 0.059 142 0.0292/1/2000–2/1/2002 169 −0.044 NA NA 142 0.0632/1/1999–2/1/2002 142 0.121 NA NA 139 0.22

aIn Table 4, the left hand side variable is the residual of CAPM. Hence, the sample size in Table 4 is, sometime,different from the sample size here, due to the missing value of beta.


Table 3cSummary statistics of the sample (III), firms listing both A- and B-shares

Raw return Residual from CAPM (B-share)a

Number of firms Mean Number of firms Mean

2/1/2001–2/1/2002 76 0.431 76 0.4222/1/2000–2/1/2001 76 1.206 76 1.2512/1/1999–2/1/2001 76 1.513 76 1.3932/1/1998–2/1/2001 76 0.476 76 0.408

aThree-year beta is used for calculating residuals from CAPM before February, 2001. One-year beta is used forcalculating residuals from CAPM after February, 2001.

a proxy for the available but imperfect information for investors. Foreign analysts’ earningforecasts come from IBES. All the earning forecasts are for earning per share (EPS) for 2001.Since we do not have the earning forecasts data for earlier years, this restricts us to analyze onlycross-section variation over firms, and leave out the variations of price discount over time (aspresented inFig. 1). We assume that the dispersions of earnings forecasts for 2001 are highlycorrelated with dispersions for the periods when the returns are measured.

We check collected forecasts first by deleting outliers. The criterion is to eliminate observa-tions if the mean-adjusted dispersion is larger than three standard deviations. We also drop thedata for which the Datastream International series have obvious errors. Next, we look for rela-tionships with various firm characteristics. In the A-share market, we find that mean-adjusteddispersion of analysts’ forecasts is significantly negatively related with earnings per share andthe dummy variable for listing exchanges. In addition, the dispersion of domestic analysts’ fore-casts is much larger than those of foreigner analysts for the same companies among dual-listedshares (Table 3a). As a result, we believe that our data are reasonable and worth using in thisinvestigation.

Long, Payne, and Feng (1999)found evidence that the Shanghai market follows a random-walk process with drift. Their research implied that Chinese equity markets have weak-formefficiency. This evidence strengthens our use of beta in the regressions.

5.2. The A share market

From Eq. (6), we use the dispersion of domestic analysts’ earning forecasts, measured bytheir mean-adjusted standard deviations, to instrumentvl in Eq. (2). We test this hypothesiswith Eq. (2), moving the systematic component to the left-hand side as follows:

Resj ≡ RAj − βj(R

Am) = constant+ k1 × SDJDj + k2 × controlsj + µj (7)

whereRAj is the excess annual return (raw return minus risk-free return) of stockj, RA

m isthe excess market return (raw market return minus risk-free return), and SDJDj is the dis-persion of earning forecasts of domestic analysts, measured as the mean-adjusted standarddeviation of available earning forecasts. Since SDJDj is a proxy for investors’ earning fore-casts, it may be correlated with variables observable to investors, including earnings per share(EPS), price-earning ratio (PER), trading volume (VO1, VO2, VO3), volatility of stock prices


(VA1, VA2, VA3), the cross-list dummy variable (DL), total shares (Tosh) and the stock ex-change dummy variable (DZ). To isolate the separate effect of the forecasts themselves, wetherefore control for these variables in our regression equations. The dummy variable DD,which represents whether a forecast is recent, is also included.

The null hypothesis isk1 = 0. If the short-sales restriction is binding and optimistic investorsbid up prices, the estimated coefficientk1 should be significantly negative, since the larger thedispersion of opinions, the more the price will be bid up by optimistic investors, thus loweringreturns.10 The results are presented inTable 4. The estimated signs of SDJD, which is the dis-persion of domestic earning forecasts, are negative in all the regressions and highly significant,except for the two estimates based on the 2-year returns and 3-year betas. We note that theconstants are significantly positive in most regressions,11 but we believe that the negative signsof the estimated coefficients of the dispersion measure are robust enough in these regressions.The significantly negative coefficients of the volatility variables (VA1, VA2, VA3) can be inter-preted as reflecting the attitude toward risk of A-share investors; it is consistent with the largeresiduals from CAPM, since CAPM assumes that investors are risk averse.12

In order to identify the channels through which the dispersion of analysts’ forecasts affectsA-share returns, we adopt a nonparametric Spearman rank to test the null of no correlationbetween dispersion of analysts’ forecasts and systematic risk. The resultingp-values are 0.15,0.12 and 0.07 for the periods 2/1/1999–2/1/02, 2/1/2000–2/1/2002 and 2/1/2001–2/1/2002,respectively, so that the null cannot be rejected at reasonable significance levels. We concludethat the dispersion of analysts’ forecasts affects A-share returns primarily through the bindingshort-sales restriction rather than through systematic risk.

Regression results reported inTable 4(column 5) imply that during the period February 22,2001–February 22, 2002 a change in “dispersion of opinion” of one standard deviation (0.255)reduces the dependent variable (residual return) by about 6 percentage points, or about twiceits mean value (0.029 inTable 1).

5.3. The B share market

All B shares in our sample have corresponding A shares, and for these shares we haveearnings forecasts data from both domestic and foreign analysts. Recall that before February 19,2001, only foreign investors were allowed access to the B share market. The regression resultsreported inTable 5(columns 8–13 correspond toEqs. (3) and (8)). They are based on data prior toFebruary 19, 2001 and use only foreign earnings forecasts, SDJFj. The null hypothesis isk1 = 0.

Resj ≡ RBj − βj(R

Bm) = constant+ k1 × SDJFj + k2 × controlj + µj (8)

The results reported inTable 5(columns 16–17 correspond toEq. (9), and are based on datafor the 1-year period following February 2001, and use both foreign and domestic forecasts,SDJFj and SDJDj).


Bm) = constant+ k0 × SDJDj + k1 × SDJFj + k2 × controlj + µj

(9)

Our econometric model implies that we can use both SDJD and SDJF to explain B share returnsafter February 2001. The null hypothesis is thatk0 = 0, k1 = 0. Regressions (8) and (9) are

532L

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.M.F

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(2004)521–538

Table 4Test for the binding short-sales restriction on A share markets1 2 (Res11) 3 (Res11) 4 (Res13) 5 (Res13) 6 (Res23) 7 (Res23) 8 (Res33) 9 (Res33)

Sample size 202 122a 132b 119c 132d 119e 129f 119g

Return period 2/22/01–2/22/02 2/22/01–2/22/02 2/22/01–2/22/02 2/22/01–2/22/02 2/22/00–2/22/02 2/22/00–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02Beta period 2/22/01–2/22/02 2/22/01–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02 2/22/99–2/22/02Constant 0.0620 (6.11)∗∗∗ 0.1897 (5.41)∗∗∗ 0.0353 (2.82)∗∗∗ 0.1377 (3.40)∗∗∗ 0.0657 (4.68)∗∗∗ 0.1142 (2.20)∗∗ 0.2305 (15.82)∗∗∗ 0.1838 (4.73)∗∗∗SDJD −0.0705 (−1.85)∗ −0.0537 (−2.04)∗∗ −0.0806 (−3.55)∗∗∗ −0.5910 (−2.85)∗∗∗ −0.0359 (−1.42) −0.0191 (−0.68) −0.1041 (−4.12)∗∗∗ −0.076 (−3.32)∗∗∗DL 0.0332 (1.47) 0.0144 (0.59) 0.0523 (1.17) 0.0311 (1.05)Tosh −0.004 (−3.03)∗∗∗ −0.0006 (−1.78)∗ −0.0002 (−0.50) −0.0001 (−0.32)EPS 0.0285 (0.49) 0.3771 (0.62) 0.0167 (0.22) −0.0895 (−1.93)∗PER −0.00001 (−1.22) −0.00001 (−0.42) −0.0000 (−2.48) −0.0000 (−2.50)∗∗DD 0.0053 (0.30) Dropped Dropped DroppedDZ −0.0085 (−0.39) −0.0010 (−0.04) −0.0000 (0.00) 0.0311 (1.05)VO1 −0.00005 (0.01) 0.0023 (0.36) 0.0159 (1.87)∗ 0.0032 (0.37)VO2 0.0040 (0.46) 0.0056 (0.54) 0.0033 (0.28) 0.0158 (1.30)VO3 −0.0048 (−0.87) −0.0060 (−0.90) −0.0101 (−1.18) −0.0149 (−2.27)∗∗VA1 −0.0840 (−4.08)∗∗∗ −0.1084 (−4.59)∗∗∗ −0.0831 (−2.92)∗∗∗ −0.0756 (−4.13)∗∗∗VA2 0.0047 (0.18) 0.0167 (0.58) 0.0207 (0.47) −0.1082 (−3.43)∗∗∗VA3 0.0150 (0.68) 0.0336 (1.26) 0.0197 (0.68) 0.1682 (6.89)∗∗∗F-statistic 3.44 6.16 12.57 7.19 2.01 3.69 17.01 16.36R2 0.0187 0.3297 0.0316 0.2984 0.0048 0.2084 0.0388 0.5890

This is a test for whether the short-sales restriction is binding or not on A-share market. Resij is defined as the residual of CAPM, which is(rik − rfi ) − βj(rm − rfi ), whererik is theannual return of stockk in the pasti years,rfi is risk-free rate in the pasti years,rm is market index return in the pasti years,βj is the beta of pastj years. SDJD is the dispersion of earningforecast of domestic analysts, measured by standard deviation of available earning forecast. DL, cross-list dummy variable, 1 if cross-listed as both A and B shares, 0 otherwise. Tosh istotal share of the firm. EPS is earning per share at the end of 2000, the most recent annual EPS available. PER is Price Earning Ratio, measured at the end of2000. DD is dummy variableswhich value is 0 if stocks have been traded for 3 years or more, 1 if stocks have been traded less than 3 years but more than 2 years, and 2 if stocks have been traded for less than 2 years andmore than 1 year. DZ is dummy variable which value is 0 if listed in Shenzhen Stock Exchange and 1 if listed in Shanghai Stock Exchange. VO1, VO2 and VO3 areaverage monthly tradingvolume of the A share in the past 1, 2 and 3 years. VA1, VA2 and VA3 are volatility of stock price in the past 1, 2 and 3 years, measured by the standard deviation. The risk-free returns are4.5%, 2.5% and 2.5% for 3-, 2- and 1-year time intervals, respectively. These risk-free interest rates are collected from IBO20–IBO60 transactions (use the rates having highest volume) inChina Interbank Money Market in the February of 1999, 2000 and 2001. The time intervals to compute betas and returns are 2/22/99 to 2/22/02 for 3-year beta and 2/22/01 to 2/22/02 for1-year beta. We use daily return for 1-year beta and weekly return for 3-year beta. Robustt-statistics are reported in parentheses. The regression (7) in the paper.

aThe sample size reduces due to the fact that we have only 131 firms having data for 3-year volatility and trading volume and, even within these 131 firms, 9 firms have no domesticanalyst forecasts.

bUsing 3-year beta and 1-year return, the sample size for return is 142. With 10 firms having no domestic analyst forecasts, sample size reduces to 132.cStarting with 142 firms, we find that 10 firms have no domestic analysts’ forecasts and 13 firms have no data for volatility and trading volume. Finally, we have 119 firms in this

regression.dIt is the same as Note b.eIt is the same as Note c.f Starting with 139 firms, we find that 10 firms have no domestic analysts’ forecasts in this regression.gBased on Note f, we find that 10 more firms have no data for trading volume and volatility. Hence, we end up with 119 firms in this regression.∗Significant at 10%.∗∗Significant at 5%.∗∗∗Significant at 1%.

L.L

i,B.M

.Fleisher

/The

Quarterly

Review

ofEconom

icsand

Finance

44(2004)

521–538533

Table 5Test for neglected effect and the short-sales restriction on B share markets

1 2 (BfRes13) 3 (BfRes13) 4 (BfRes23) 5 (BfRes23) 6 (BfRes33) 7 (BfRes33) 8 (BfRes13) 9 (BfRes13)

Return Period 2/1/00–2/1/01 2/1/00–2/1/01 2/1/99–2/1/01 2/1/99–2/1/01 2/1/98–2/1/01 2/1/98–2/1/01 2/1/00–2/1/01 2/1/00–2/1/01Sample size 76 76 76 76 76 76 18a 18Constant 0.5394 (5.94)∗∗∗ 1.010 (2.32)∗∗ 0.8067 (5.55)∗∗∗ 1.5355 (2.87) 0.1619 (1.75)∗ 0.1117 (0.34) 0.6890 (6.71)∗∗∗ −0.4676 (−0.44)SDJDSDJF −0.5084 (−3.83)∗∗∗ −0.0082 (−0.03)DN 0.9328 (6.37)∗∗∗ 0.6756 (3.46)∗∗∗ 0.7678 (4.02)∗∗∗ 0.7191 (2.62)∗∗ 0.3222 (2.75)∗∗∗ 0.2746 (1.80)∗Tosh −0.0654 (−2.59)∗∗ −0.0812 (−2.87)∗∗∗ −0.0439 (−2.56)∗∗ −0.0103 (−0.31)BR −1.0480 (−1.19) −2.79 (−3.13)∗∗∗ −1.0555 (−1.91)∗ 1.7337 (1.00)NFF 0.1140 (1.34) 0.1494 (1.34) 0.0598 (0.98) −0.0209 (−0.191)NDF −0.1481 (−1.24) −0.1217 (−0.90) 0.0360 (0.41) 0.0905 (0.49)DZ 0.5969 (3.03)∗∗∗ 0.9806 (4.47)∗∗∗ 0.6839 (5.74)∗∗∗ −0.0116 (−0.05)BfVO1 1.070 (3.88)∗∗∗ −0.1114 (−0.27) −0.1008 (−0.53) 0.7648 (2.15)∗BfVO2 0.5649 (0.72) 2.571 (3.03)∗∗∗ 0.9152 (1.79)∗ 0.1509 (0.13)BfVO3 −1.780 (−2.01)∗∗ −2.702 (−3.10)∗∗∗ −0.8717 (−1.45) −0.9093 (−0.72)VO1VO2VO3F-statistic 40.59 13.47 16.17 8.44 7.57 6.42 14.69 15.72R2 0.2069 0.5620 0.1247 0.4666 0.0675 0.4822 0.1886 0.6927

10 (BfRes23) 11 (BfRes23) 12 (BfRes33) 13 (BfRes33) 14 (AllRes11) 15 (AllRes11) 16 (AllRes11) 17 (AllRes11)

Return Period 2/1/99–2/1/01 2/1/99–2/1/01 2/1/98–2/1/01 2/1/98–2/1/01 2/1/01–2/1/02 2/1/01–2/1/02 2/1/00–2/1/01 2/1/00–2/1/01Sample size 18 18 18 18 76 76 18 18Constant 0.8245 (5.38)∗∗∗ 2.5149 (0.86) 0.1682 (1.73) 0.9784 (0.52) 0.2538 (5.47)∗∗∗ 0.5135 (1.16) 0.2647 (3.64)∗∗∗ −0.0485 (−0.08)SDJD 0.4919 (2.55)∗∗ 0.4252 (1.18)SDJF −0.0604 (−0.16) −0.5507 (−0.67) −0.0216 (−0.15) −0.1974 (−0.37) −0.3303 (−4.46)∗∗∗ −0.2435 (−1.20)DN 0.2199 (3.56)∗∗∗ 0.2034 (2.53)∗∗Tosh −0.0114 (−0.23) −0.0223 (−0.65) −0.0179 (−1.91)∗ −0.0073 (−0.25)BR −3.73 (−0.67) −2.4452 (−0.71) 0.0044 (0.01) 0.7258 (0.65)NFF 0.2173 (0.77) 0.1025 (0.56) 0.0499 (1.44) 0.0077 (0.28)NDF −0.3354 (−0.67) −0.1315 (−0.39) −0.0673 (−0.75) 0.0424 (0.28)DZ 0.9022 (1.47) 0.4453 (0.80) −0.0673 (−1.14) −0.1473 (−0.77)BfVO1 −0.8184 (−1.03) −0.1876 (−0.34)BfVO2 2.6244 (1.07) 0.9593 (0.64)BfVO3 −2.1979 (−0.68) −0.8111 (−0.45)VO1 0.2241 (−2.83)∗∗∗ 0.1237 (0.67)VO2 0.0098 (0.04) 0.1280 (0.25)VO3 −0.2817 (−1.03) −0.2839 (−0.41)F-statistic 0.02 0.81 0.02 0.99 12.70 2.74 21.90 7.74R2 0.001 0.4698 0.003 0.4391 0.0982 0.1794 0.4792 0.6923

This is a test for (1) whether the short-sales restriction is binding or not and (2) whether there is neglected-share effect on B-share market. Resij is defined as residual of CAPM, which is(rik − rfi)− βj(rm − rf

i),

whererik is the annual return of stockk in the pasti years,rfi

is risk-free rate in the pasti years,rm is market index return in the pasti years,βj is the beta of pastj years. BfResij means the current end of time interval isFebruary 1, 2001. AllResij means the current end of time interval is February 1, 2002. SDJD and SDJF are the dispersion of earning forecast of domestic and foreign analysts, respectively, measured by standard deviationof available earning forecast. DN, neglected-share effect dummy variable, 1 if standard deviation cannot be computed and the stock is neglected, 0 otherwise. Tosh is total shares of the firm. BR, the ratio between B shareand total share. NFF is the number of foreign analysts. NDF is the number of domestic analysts. DZ is dummy variable which value is 0 if listed in ShenzhenStock Exchange and 1 if listed in Shanghai Stock Exchange.VO1, VO2 and VO3 are the average monthly trading volume of the B share in 1, 2 and 3 years before February 1, 2002. BfVO1, BfVO2 and BfVO3 are the average monthly trading volume of the B share in 1, 2 and 3 yearsbefore February 1, 2001. The risk-free returns are 5%, 5%, 5.5% and 4.9% for the past 1-, 2-, 3- and 4-year time intervals, respectively. The risk-free rates are obtained after considering the interest rates of governmentbonds or bills in Hong Kong, Taiwan and United States. We use weekly return for 3-year beta. All betas are computed using 3-year data. Robustt-statistics are reported in parentheses. The regressions ((8)–(10)) in thepaper.

aIn the B share market, whenever foreign analysts’ forecasts appear in the regression, the sample size falls to 18. SeeTable 3a.∗Significant at 10%.∗∗Significant at 5%.∗∗∗Significant at 1%.


based on 18 observations. Since we assume independent normal errors, there is no need for asmall sample correction. Although non-normal errors would cause thet-test to be invalid, withonly 18 observations it would be difficult to determine the distribution.

To test the short-sales restriction for the trading in B-shares we accommodate the fact thatwe have only 18 stocks with two or more forecasts by modifying the regression equation to testfor a neglected-share effect (Table 5, columns 2–7 and 14–15), obtaining


Bm) = constant+ h1 × DNj + h2 × controlsj + µj (10)

where DN is a dummy variable= 1 if a stock is neglected by analysts (i.e., has 1 or 0 earningsforecasts). The null hypothesis ish1 = 0.

As above, we control for trading volume (VO1, VO2, VO3, BfVO1, BfVO2, BfVO3), thetotal number of shares (A and B shares) (Tosh), B shares/total shares (BR), the number ofdomestic and foreign analysts (NFF, NDF) and a Shanghai-exchange dummy variable (DZ) inthe regressions.

The results shown inTable 5(columns 8–13) indicate that before February 19, 2001, theestimated coefficient of SDJF (dispersion of foreign mean-adjusted earning forecasts) is mostlyinsignificant, indicating that short-sales restrictions were not binding for trading in B-shares.Note that the coefficient of the number of analysts is not significant in our regressions as acontrol variable. This suggests that our measure of dispersion of opinion is more informativethan the number of opinions. For the period after February 19, 2001, the coefficients of thedispersions of both domestic and foreign earnings forecasts are insignificant (Table 5, column16, 17) with the control variables. The regression results forEq. (10) in Table 5(columns2–7 and 14–15) show that the sign of the dummy variable representing “neglect” is uniformlysignificantly positive. We can confidently reject the null hypothesis that B-share returns areunaffected by analysts’ neglect.

Note that trading volume is included as a control variable in the above regressions as a proxyfor market liquidity as inChen et al. (2001)and others.Chen et al. (2001)propose that lowmarket liquidity induces investors in B shares to require a high rate of return. Our results forA-share trading, as reported inTable 4, imply that the combination of short-sales restrictionand heterogeneous expectations are better than the liquidity hypothesis in explaining the priceand return behavior of A shares. The results for B shares as reported inTable 5suggest that theneglected-share effects are more important. We conclude that when a measure of dispersion ofopinion is included as a regressor, there is no evidence that the relatively high return to investingin B shares is a result of market illiquidity.

6. Conclusions

The results of our study complement the explanation ofFernald and Rogers (2002)in termsof differential investment alternatives of domestic and foreign investors, and the findings ofKarolyi and Li (2003)in terms of differential risk attitudes and asymmetric information accessbetween domestic and foreign investors. They compete with the liquidity hypothesis proposedbyChen et al. (2001), in that holding constant dispersion of opinion; the liquidity effect appearsto be ineffective in the A-share trading and is at most weak in B-share trading. Given the


number of control variables used and the robustness of our results to alternative specifications,we conclude that short-sales restrictions and the neglected-share effects are strong candidatesfor explaining the pronounced discount of B shares relative to A shares in Chinese stock markets,a problem that has challenged stock-market research over the past 10 years.

Notes

1. A “neglected” firm is one that is ignored, or neglected, by market analysts.2. Although a few companies’ shares are traded on the NYSE (N shares), Singapore (S

shares), London (L shares), NASDQ and OTC markets, the volumes of transactions inthese markets are small.

3. The Report of Investment Value is not a Journal. It is research report publicized bysecurities firms at irregular frequency.

4. Among 76 firms issuing B-Shares in our sample, 58 firms are neglected by foreignanalysts, 31 firms having no foreign forecast, and 27 firms having only one.

5. There is an additional complexity in that according to many reports in the Asian financialpress, some domestic investors bought B shares illegally prior to February 2001. Thisarbitrage evidently did not eliminate the B-share discount because such activity wasprobably quite risky and costly. We, therefore, believe that our assumption of strictsegmentation of the A- and B-share markets remains a useful abstraction.

6. The A-share sample size is 218. Compared to over 1000 total A shares, it does seemthat A shares are “neglected.” But, in fact, the relatively small sample size of A sharesis not due to the rest of shares being neglected. We simply cannot obtain forecasts forthe remaining of A shares.

7. The sample size is limited by our ability to access domestic analysts’ forecasts.8. We have checked our results with three kinds of beta and return (1-, 2- and 3-year). To

conserve the space, we only report part of our regression results in Tables 4 and 5.9. In the literature about the stationarity of beta coefficients, there is a debate about whether

daily data should be used. In contrast to earlier studies,Daves, Ehrhardt, and Kunkel(2000)suggested that daily data should be used to estimate beta with less than a 3-yearhorizon. We, therefore, use daily data for computing 1-year beta.

10. Given that foreign investors are not allowed to trade on the A share market, we do notuse earnings forecasts from foreign analysts as an explanatory variable. In fact, foreignanalysts do not forecast earnings of firms that issue only A shares.

11. Ideally, the constant in these regressions should be zero. We cannot completely explainwhy there are not. We conjecture that our sample of A shares is selective in the sensethat only those stocks having domestic earnings forecasts are included. Ideally, weshould use all the A-share stocks to test whether the short-sales restriction is binding toavoid sample-selection bias. This requires data for domestic earning forecasts for all theA-share stocks, which we do not have.

12. As Tables 3b and c indicate, the CAPM is not effective in explaining the cross-sectionvariations of stock returns.

13. Exchange-rate risk was minimal in China during the period of our sample due to recog-nized and well-conducted government policy toward maintaining an exchange rate that


fluctuated within narrow, well-defined bounds. Therefore, we do not consider exchangerate risk in our model.

14. If investors have heterogeneous beliefs about the covariance matrix, the CAPM no longholds and there might be substitution effects between stocks as described inSwidler(1988).

Appendix A

The problem is similar toL’Her and Suret (1995). We have two types of investors (domesticand foreign), who face different risk-free interest rates.

This economy is single period and hasM risky assets. TheseM risky assets have the samecovariance matrix for all the domestic and foreign investors on each market. The end of period(period 1) wealthWA

k1 andWBj1 follow normal distributionsN(µA

k , (σAk )

2) andN(µBj , (σ

Bj )

2)

respectively. The domestic and foreign investors on each market maximize their end-of-periodwealth level by adjusting their portfolios. The assumptions are summarized as follows:

• A1: There are two groups of investors, say domestic and foreign, whose absolute risk aversioncoefficients areAk andBj (both positive), respectively.k andj are the indices for domesticand foreign investors, respectively. The utility can be written in the form ofU(Wkt) =−exp(−AkWkt) for domestic investors andU(Wjt) = −exp(−BjWjt) for foreign investors,whereWkt is the wealth of investork at timet.

• A2: There areM risky assets for both domestic and foreign investors. The prices of these riskyassets are normally distributed. TheM × 1 price vectors at timet = 0 and 1 areP andX,respectively. The prices are denominated in the same currency. There are no exchange-raterisks.13

• A3: The number of domestic and foreign investors isN1 andN2, respectively. Domestic andforeign investors hold different estimates for the price vectorsEA

k (X) andEBj (X), respec-

tively, at timet = 1. However, they share the same beliefs for the covariance matrix of riskyassets prices.ΩA

k = ΩBj = Ω, for all k andj.14

• A4: Short sales are not allowed. The quantity of any risky assets held by investors at timet = 0 is either positive or zero.

• A5: The risk-free returns for domestic and foreign investors areRAf andRB

f , respectively.• A6: Investors are price-takers.

The domestic investors solve the following problem:

maxqAk

Ek[−exp(−AkWk1)] = maxqAk

µAk − Ak(σ

Ak )

2

2

= maxqAk

(qAk )

′(EAk (X)− RA

fP)+ RAfWk0 − Ak

2(qAk )

′ΩqAk

subject to :qAk ≥ 0 (constraint on short sales) (A.1)

whereqAk = (qA

k1, . . . , qAkM)

′ is the quantities vector of risky assets hold bykth domesticinvestors.


The foreign investors solve the similar problem:

maxqBj

Ej[−exp(−BjWj1)] = maxqBj

µBj − Bj(σ

Bj )

2

2

= maxqBj

(qBj )

′(EBj (X)− RB

fP)+ RBfWj0 − Bj

2(qBj )

′ΩqBj

subject to :qBj ≥ 0 (constraint on short sales) (A.2)

whereqBj = (qB

j1, . . . , qBjM) is the quantities vector of risky assets hold byjth foreign investors.

The first-order conditions for domestic and foreign investors are as follows:

qAk = (AkΩ)

−1(EAk X − RA

fP)+ (AkΩ)−1µA

k , k = 1, . . . , N1 (A.3)

qBj = (BjΩ)

−1(EBj X − RB

fP)+ (BjΩ)−1µB

j , j = 1, . . . , N2 (A.4)

By aggregating individual demand equal to aggregate supply, equilibrium price is solved, exceptthat two types of investors have been considered in determining equilibrium price, which is

p =

N1∑k=1

αAk

EAk X

RAf

+N2∑j=1

αBj

EBj X

RBf

− τ−1ΩQ

+

N1∑k=1

αAk

µAk

RAf

+N2∑k=1

αBj

µBj

RBf

where

τ =N1∑k=1

A−1k R

Af +

N2∑j=1

B−1j R

Bf αA

k =∑N2

k=1A−1k R

Af∑N1

k=1A−1k R

Af +∑N2

j=1B−1j R

Bf

αBj =

∑N2j=1B

−1j R

Bf∑N1

k=1A−1k R

Af +∑N2

j=1B−1j R

Bf

(A.5)

Next step would be to transfer price equilibrium into CAPM format, which is return equilibrium.First, compare to the step 1 on the page 656 ofL’Her and Suret (1995), after considering the

case when short sales is not binding,τ is in more complicated form as follows:

τ−1 =∑N1

k=1αAk (E

Ak Rm/R

Af )+∑N2

j=1αBj (E

Bj Rm/R

Bf )− 1

Pmσ2(Rm)(A.6)

wherePm = Q′PNext, by multiplyingEq. (A.5)by D−1

p , Eq. (A.7)is obtained.

1 =N1∑k=1

αAk

EAk R

RAf

+N2∑j=1

αBj

EBj R

RBf

− τ−1D−1p ΩQ +

N1∑k=1

αAk

D−1p µ

Ak

RAf

+N2∑k=1

αBj

D−1p µ

Bj

RBf

(A.7)

Note that

τ−1ΩQ = Dpβ

N1∑k=1

αAk

EAk Rm

RAf

+N2∑j=1

αBj

EBj Rm

RBf

− 1

(A.8)

PuttingEqs. (A.7) into (A.8), we getEq. (1)in the main text of the paper.


References

Arbel, A., & Strebel, P. J. (1983, Winter). Pay attention to neglected firms!Journal of Portfolio Management, 9(2),37–42.

Ariff, M., & Khan, A. W. (1998). The effects of international intermarket investment barriers on asset pricing: Thecase of the Singapore Stock Exchange.Quarterly Journal of Business and Economics, 37(2), 17–32.

Bailey, W. (1994). Risk and return on China’s new stock markets: Some preliminary evidence.Pacific Basin FinanceJournal, 2(2/3), 243–260.

Bailey, W., Chung, Y. P., & Kang, J.-k. (1999, December). Foreign ownership restrictions and equity price premiums:What drives the demand for cross-border investments?Journal of Financial and Quantitative Analysis, 34 (4).

Carvell, S. A., & Strebel, P. J. (1987, Summer). Is there a neglected firm effect?Journal of Business Finance &Accounting, 14(2), 279–290.

Chakravarty, S., Sarkar, A., & Wu, L. F. (1998). Information asymmetry, market segmentation and pricing ofcross-listed shares: Theory and evidence from Chinese A and B-share.Working paper, Purdue University.

Chen, G. M., Lee, B. S., & Rui, O. (2001, Spring). Foreign ownership restrictions and market segmentation inChina’s stock market.The Journal of Financial Research, XXIV(1), 133–155.

Daves, P. R., Ehrhardt, M. C., & Kunkel, R. A. (2000, Spring). Estimation systematic risk: the choice of returninterval and estimation period.Journal of Financial and Strategic Decisions, 13(1), 7–14.

Domowitz, I., Glen, J., & Madhavan, A. (1997). Market segmentation and stock prices: Evidence from an emergingmarket.Journal of Finance, LII(3), 1059–1085.

Fernald, J., & Rogers, J. H. (2002). Puzzles in the Chinese stock market.Review of Economics and Statistics, 84,416–431.

Hietala, P. T. (1989). Asset pricing in partially segmented markets: Evidence from the Finnish market.Journal ofFinance, XLIV(3), 697–718.

Jones, C. M., & Lamont, O. A. (2001, October). Short sale constraints and stock returns.NBER Working Paper No.8494.

Karolyi, A. G., & Li, L. (2003).A resolution of the Chinese discount puzzle. Working paper, The Ohio State University.Lamont, O. A., & Thaler, R. H. (2003, Spring). Can the market add and subtract? Mispricing in tech stock carve-outs.

Journal of Political Economy, 111(2).L’Her, J.-F., & Suret, J.-M. (1995, November). Heterogeneous expectations, short sales regulation and the risk return

relationship.Financial Review, 30(4), 637–662.L’Her, J.-F., & Suret, J.-M. (1996, Spring). Consensus, dispersion and security prices.Contemporary Accounting

Research, 13(1), 209–228.Long, D. M., Payne, J. D., & Feng, C. Y. (1999). Information transmission in the Shanghai equity market.Journal

of Financial Research, 1, XXV(1), 81–98.Ma, X. (1996). Capital controls, market segmentation and stock prices: Evidence from the Chinese stock market.

Pacific-Basin Finance Journal, 4, 219–239.Miller, E. (1977). Risk, uncertainty, and divergence of opinion.Journal of Finance, 32, 1151–1168.Stulz, R. M., & Wasserfallen, W. (1995). Foreign equity investment restrictions, capital flight, and shareholder wealth

maximization: Theory and evidence.The Review of Financial Studies, 8(4), 1019–1057.Sun, Q., & Tong, W. H. S. (2000). The effect of market segmentation on stock prices: The China syndrome.Journal

of Banking & Finance, 24, 1875–1902.Swidler, S. (1988, Winter). An empirical investigation of heterogeneous expectations, analysts’ earnings forecasts,

and the capital asset pricing model.Quarterly Journal of Business and Economics, 27(1), 20–41.

heterogeneous expectations and stock prices in segmented markets: application to chinese firms

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