Short-Sale Constraints and A-H Share Premiums Kalok Chan*, Hung Wan Kot and Zhishu Yang First Draft: January 15, 2009 ___

Short-sale Constraints and A-H Share Premiums

Kalok Chan*, Hung Wan Kot and Zhishu Yang

First draft: January 15, 2009

______

* Corresponding author. Chan is from Department of Finance, Hong Kong University of Science & Technology, Phone: (852) 2358 7681, E-mail: [email protected]. Kot is from Department of Finance & Decision Sciences, Hong Kong Baptist University, Phone: (852) 3411 7558, E-mail: [email protected]. Yang is from Department of Finance, Tsinghua University, Phone: (8610) 6277 1769, E-mail: [email protected]. We thank Baolian Wang for his capable research assistance. We acknowledge the financial support from General Research Fund of Hong Kong Research Grants Council (Project Number 242408). All errors are ours.

Short-sale Constraints and A-H Share Premiums

Abstract

We investigate the effect of different short-sale constraints of the H-share stocks on the A-H share premiums, based on H shares from Hong Kong and A shares from Mainland China. When the market goes down, we find that the prices of shortable H-shares decrease faster than those of non-shortable H- shares. As a consequence, the premium of A-H shares becomes larger for the shortable H-shares. We also find that lagged premium of shortable stock portfolio leads the premium of non-shortable stock portfolio, but not vice versa

Keywords: Short-sale constraints, overvaluation, Hong Kong market, China A-share market

Classification: G12, G15, G18

2 1. Introduction

During the financial tsunami in the final quarter of 2008, there are controversies over the short selling activity around the global equity markets. Many major financial markets have banned short- selling to a different extent, ranging from only the financial companies to the stock market as a whole.

One justification used by regulators is that short-sale was used by speculators to sell down the companies, destabilizing the stock market. On the other hand, many industry practitioners voiced opposition against the short-sale ban, citing that short selling plays an important role in the price discovery process. They claimed that short-selling is the reaction of some market participants to negative information about the outlook of the economy. In other words, short-sellers do not make up the bad news, but are simply the messengers.

The debate on short-selling is nothing new to the academics. There is no shortage of academic studies on the effect of short-selling on the market efficiency. A most widely study is Miller (1997) who argues that given the short-sale constraints, negative information cannot be immediately incorporated into stock prices. As a consequence, stock prices reflect only optimistic investors’ opinion, and not pessimistic investors’ ones, leading to overvaluation. The effect of short-selling on overvaluation has received some empirical support in the U.S. market. Chen, Hong and Stein (2002) use mutual fund holdings as a proxy for short-sale constraint, and find that higher short-sale constraints forecast lower future returns. Jones and Lamont (2002) use rebate rate for stock borrowing as a proxy for short-sale constraint, and find that stocks that are expensive to short or which enter the borrowing market have high valuations and low subsequent returns. Asquith, Pathak, and Ritter (2005) use short interest as a proxy for shorting demand and institutional ownership as a proxy for shorting supply, and find that short-sale constrained stocks underperform the less constrained ones.

However, most of the previous studies are confined to the U.S. market. Furthermore, they might not be able to assess the effect of short-sale constraints accurately. This is because short sales are generally allowed in the U.S. markets, even though some stocks are more difficult to borrow. It is, however, not possible to find two stocks that are identical except that one has short-sale constraint while

3 the other does not. Thus, previous studies have to rely on various proxies to measure the extent of the short-sale constraints, and it is possible that these proxies might reflect other effects rather than short-sale constraints.

The objective of this paper is to examine the effect of short-sale constraint on pricing efficiency in the China market. Not only that we provide additional evidence outside the U.S, the unique setting in the China market makes it an ideal laboratory experiment for providing direct evidence on the effect of short-sale constraint on the stock valuation. Many Chinese companies are dually listed in the Mainland and Hong Kong, either as A-shares listed in Shanghai or Shenzhen, or as H-shares in Hong Kong. For example, as of 2007, there are 53 Chinese companies that have both A shares traded in Mainland and H- shares traded in Hong Kong. As of today, all stocks in Mainland are not permitted for short-sale. Due to the short-sale restriction, no investor without holding existing shares can sell any shares during the stock market bubble in 2007 even if he is of the opinion that the stock market was overvalued. In fact, during the stock market peak in August 2007, the P/E ratio for the Mainland stock market has reached 60, becoming one of the highest in the world. On the other hand, for those H shares which are listed in Hong

Kong, they are traded at a more reasonable P/E ratio of around 26 during the same period. As a result, the

A-shares are typically traded at a premium of around 50% during the period. The premium might be a reflection of different investment opportunity set faced by Hong Kong and Mainland investors. Another potential explanation is that short-selling is not permitted in Mainland but allowed in Hong Kong. As a result, H shares are more fairly valued because both pessimists and optimists can participate, while A shares of the same company are overvalued because pessimists are less likely to participate.

What makes our study more unique is that not every H share can be sold short. To be eligible for short-selling, a company must be a constituent stock of an index, or have underlying options or futures, or maintain high liquidity (market capitalization of not less than HK$1 billion and an aggregate turnover during the preceding 12 months of 40% of the capitalization). At the end of 2007, about 30% of H-shares are not permitted for short-selling. Consequently, for those H shares that are subject to short-sale restriction, the lower participation rate of pessimists could mean higher valuation of H shares, resulting in

4 a smaller discount relative to the corresponding A-shares (or a smaller A-H share premium). We therefore compare the A-H share premium between two groups of H shares, one eligible for short-selling and the other ineligible. If the short-sale restriction results in higher valuation for H shares, we will observe the A-H share premium to be higher for those H shares eligible for short selling than for those that are ineligible.

The remainder of paper is organized as follows. Section 2 provides the background of Chinese enterprises list on HKEx. Section 3 provides the related literature. Section 4 contains the data and preliminary analysis. Section 5 presents the regression analysis. We conclude the paper in Section 6.

2. Overview of A and H shares

Since the Chinese government decided to open the door to oversea investors in 1978, they are keen to shift from the central planning economy to the market oriented economy. With the growth of the economy, both state owned enterprises and private enterprises need huge capital for restructuring, expansion, and further development. The Chinese companies also need to integrate with the global economy and follow the international business practices. As the Mainland stock market is still segmented from the global market due to capital control, Hong Kong becomes the primary “overseas” market for the listing of Chinese enterprises.

There are two channels for Chinese enterprises to be listed in Hong Kong. The first one is through the issuance of H-shares. The first state owned enterprise to be listed in Hong Kong, Tsingtao Brewery, issued H-shares on July 15, 1993. By 2008, 110 companies have H-shares listed on the main board of

Hong Kong Exchanges (HKEx). The total market capitalization of H-shares is more than 2.5 trillion Hong

Kong dollars, accounting for 26% of the market capitalization of HKEx main board.

Another channel for listing in Hong Kong is via red chips. Defining “red-chip” stock is difficult, as the term “red chip” is financial jargon used in the securities market rather than the official terminology used in the HKEx. Red-chips are companies incorporated and listed in Hong Kong, although the source of capital and business are mainly from Mainland. By 2008, 89 red chips are listed on the main board of

5 HKEx. The total market capitalization of red chips is more than 2.6 trillion Hong Kong dollars, accounting for another 27% of the market capitalization of the HKEx. Because no red-chips are dually listed in the Mainland stock market, they are excluded from our analysis.

Among these 110 companies that have H shares listed in Hong Kong, 52 are also listed in

Mainland, via the issuance of A shares in Mainland, either in the Shanghai Stock Exchange or in the

Shenzhen Stock Exchange. The A-share and H-shares are legally identical, enjoying the same voting rights and dividend streams. The main difference is that all transactions, dividend payments, trades, and quotes are conducted in different currencies –Renminbi (RMB) for A shares, and Hong Kong dollars for the H shares.

Because they are listed in different exchanges, A and H shares are subject to different listing requirements and disclosure rules. Also, while both Mainland and Hong Kong exchanges use electronic open limit order system and offer continuous trading, the trading hours are different. Shanghai and

Shenzhen exchanges run from 9.30am to 11.30am and 1.00pm to 3.00pm on Mondays through Friday

(except public holidays), while HKEx run from 10:00am-12:30pm and 2:30-4:00pm. Also, the trade settlement follows a “T + 1” rule in the Mainland, and “T+2” rule in Hong Kong.

3. Literature Review

3.1 Previous Studies on Short Selling

As an investment tool, short selling is not as easy as conventional buying new shares or selling existing shares. To short a stock, one must borrow the stock from a current owner, and this stock lender charges the short-seller a lending fee. The short-seller also faces the risk that his short position will have to be involuntarily closed due to recall from the lender. Legal and institutional constraints also inhibit investors from selling short. All of these impediments and costs are referred to as short-sale constraints

(Jones and Lamont (2004)).

According to Miller (1977), with the short-sales constraints, security prices tend to reflect the more optimistic opinion and thus to be upward-biased. This is because pessimistic investors are not able

6 to participate in the stock market due to short-sale constraints, and that the sole participation of optimistic investors will bid prices above the level that all investors are able to participate. Chen, Hong, and Stein

(2002) obtain similar result by developing a model that allows for risk aversion, and show that stocks with short constraints reflect optimistic beliefs and thus have lower future returns. Diamond and

Verrecchia (1987) examine the effects of short-sales constraints in a rational-expectation framework.

They show that the price of a short-sales-constrained stock adjusts more slowly to unfavorable private information than it does to favorable private information. But they argue that a rational investor will recognize the existence of short-sales constraints and will adjust their beliefs such that no overpricing of securities will exist, on average. Bai, Chang, and Wang (2006) even provide an opposite prediction to

Miller (1997). They argue that short-sellers are of two types – one for risk sharing and the other for trading private information. They show that in the presence of information asymmetry, limiting short sales driven by private information increases the uncertainty about the asset as perceived by uninformed investors, which reduces the demand for the asset. When this information effect dominates, short-sale constraints actually cause asset prices to decrease and price volatility to increase.

The empirical evidence on short-sale constraints so far is consistent with the overvaluation effect as hypothesized by Miller (1997). For example, Chen, Hong, and Stein (2002) use mutual fund holdings as a proxy for short-sale constraints, and find that short-sale constraints forecast lower future returns.

Jones and Lamont (2002) study equities on the NYSE over the1926-1933 period and by using rebate rates as a proxy for short-sale constraints, they find that stocks which were expensive to short or which entered the borrowing market had high valuations and low subsequent returns. Using short interest as a proxy for shorting demand and institutional ownership as a proxy for shorting supply, Asquith, Pathak, and Ritter

(2005) find that short-sale constrained stocks underperformed significantly.

A few studies investigate the relationship between short-sale constraints and options markets.

Danielsen and Sorescu (2001) examine the stock price performance following option listing. Since the introduction of traded put and call options arguably offers a lower-cost way of establishing a short position, the listing of options listing will mitigate the short-sale constraints. Consistent with the

7 overvaluation effect, they find the option introductions are associated with negative abnormal returns in underlying stocks. Ofek, Richardson, and Whitelaw (2004) find that violations of put-call parity were asymmetric in the direction of short-sale constraints, and their magnitudes are strongly related to the cost and difficulty of short selling.

Most of the empirical studies on short-sale constraints are based on the U.S. market. One exception is Bris, Goetzmann, and Zhu (2003) who study the short-sales constraints in international stock markets. They employ stock return data from 47 equity markets around the world to examine the effects of short-sales restrictions on market efficiency, comparing markets where short sales are allowed and those where they are not. They find some evidence that stock prices incorporate negative information faster in countries where short sales are allowed and practiced.

Another study on a non-US market is Chang, Cheng and Yu (2007), who investigate the effect of short-sale constraints in the Hong Kong stock market. They take advantage of the short-sale practice in

Hong Kong as only a subset of designated stocks could be sold short. Furthermore, the list of designated securities is revised from time to time, enabling them to analyze the price effects around the changes of the list. They find that when a stock is added to the list of designated securities for short selling (i.e., the stock may be sold short), significant negative abnormal returns are observed. They document even more negative abnormal returns when the sample is limited to events in which no tick rule is in effect (which arguably represents a more thorough lifting of short-sales restrictions). Both findings suggest that stock prices are upward biased when short sales are restricted. More supporting evidence is found for off-the- list events, where the re-imposition of short-sales restrictions on certain stocks results in significantly positive abnormal returns.

Without doubt, Chang, Cheng and Yu (2007) is closest to our paper, as we also attempt to compare the price effects of stocks eligible for short selling and those ineligible. The main difference is that we focus on H shares, and use the A-H share premium as a direct measure of the overvaluation of individual stocks, while Chang et al. only indirectly look at the abnormal returns associated with the change of short selling eligibility. Furthermore, while our study represents a cross-sectional approach as

8 we attempt to investigate the difference between the A-H share premium of H shares eligible for short selling and those ineligible, the study by Chang et al. represents a time-series approach as they attempt to examine stock price changes of companies around the event of joining or leaving the short-sale list. An advantage of cross-sectional comparison of the valuation effect over the time-series approach is that the addition or removal of a company from the short-sale list might create short-term price effect around the event date, but not necessarily persistent effect in the longer term.

3.2 Previous Studies on Price Differentials Among Various Types of Shares in China

Besides A and H shares, there is another type of shares traded in China, namely B shares listed in

Mainland. Similar to H shares, B shares are priced in foreign currency – namely U.S dollars for those listed in Shanghai Stock Exchange and Hong Kong dollars for those listed in Shenzhen Stock Exchange.

Until 2001, B shares can only be bought by foreign investor. After 2001 February, domestic investors who possess the foreign currency could purchase B shares.

Many studies examine the interrelationship among A, B and H shares. Wang and Jiang (2004) find that the A-H share premium is highly correlated with domestic and foreign market returns and respective market illiquidity. Arquette et al. (2008) find that the discounts of Chinese securities, as compared with ADRs traded on the NYSE or H-shares traded on the HKEx, are significantly influenced by the changes in both exchange rate expectations and investor sentiment. Callen et al. (2008) investigate the price disparity of China A-shares to B- and H-shares. They decompose the unexpected price disparity into difference in expected return news and difference in cash flow news. It is found that the difference in expected return news dominates difference in cash flow news in driving the variation of the price disparity, suggesting that market or macro news rather than firm specific news moves the price disparity of the twin shares.

Chakravarty, Sarkar, and Wu (1998), and Chan, Menkveld, and Yang (2007) assert that information asymmetry helps to explain the A- and B-share premiums. For example, Chan et al. construct

9 measures of information asymmetry based on market microstructure models, and find that they can explain 45% of the variation of A- and B-share prices.

Sun and Tong (2000) argue that from the perspective of foreign investors, the introduction of

Hong Kong H-shares is a substitute for the Mainland China B-shares. They find that when more H-shares are listed in Hong Kong, the B-share discount becomes larger. Mei, Scheinkman, and Xiong (2003) find that the turnover rate of A shares is able to explain 20% of the cross-sectional variation in A-B share premium. Tong and Yu (2008) find that B-share discount is larger for firms with weaker corporate governance.

4. Empirical Analysis

4.1 Data Collection

We obtain listing dates of H-shares from the website of Hong Kong Exchanges (HKEx), and listings dates of A-shares from the websites of Shanghai Stock Exchange and Shenzhen Stock Exchange.

We also obtain the industry classification from the website of The China Securities Regulatory

Commission (CSRC). The list of short selling eligibility is obtained from the HKEx. Data on stock prices, trading volume, bid-ask spread, market capitalization of a firm, book value of a company, number of shares outstanding at daily, weekly and monthly level are obtained from Datastream for H-shares and from Tsinghua Financial Database for A-shares. The stock market indices, including Hang Seng Index,

Shanghai Composite Index, and currency exchange rate between Hong Kong dollar and Chinese RMB are also obtained from Datastream. The constituent stocks of H-share Index are obtained from the website of

Hang Seng Index Services Company Ltd. 1

4.2 Preliminary Analysis

1 Website of Hong Kong Exchange, Shanghai Stock Exchange, Shenzhen Stock Exchange, CSRC, and Hang Send Index Services Ltd. are : http://www.hkex.com, http://www.sse.com.cn, http://www.szse.cn, http://www.csrc.gov.cn, and http://www.hsi.com.hk, respectively.

10 Table 1 reports the listing dates of H-shares on the HKEx, and A-shares on the Shanghai Stock

Exchange and Shenzhen Stock Exchange. Among 53 stocks in the sample, 49 stocks are listed in the

HKEx first and then listed on the Mainland stock exchanges later. For the other 4 stocks, ZTE

Corporation and China Merchants Bank are listed on the China A-share market first, while Industrial and

Commercial Bank of China (ICBC) and China CITIC Bank are listed on the HKEx and the Shanghai

Stock Exchange at the same date. Out of the 53 companies listed on the Mainland, 45 are listed on the

Shanghai Stock Exchange and 8 are listed on the Shenzhen Stock Exchange. The average time gap between the listing date in Hong Kong and Mainland is 1080 calendar days, with the longest one being

Guangshen Railway Company, which is first listed on the HKEx on May 14, 1996 and then listed on the

Shanghai Stock Exchange on December 22, 2006.

[ Table 1 here ]

Table 2 reports the industry classification of sample stocks, including the classification of individual companies in Panel A, and the percentage distribution of sample stocks across the industry in

Panel B. Manufacturing industry comprises 40% of the sample, with the Metal and Non-Metal sub- industry and Machinery, Equipment and Instrument sub-industry accounting for 13% and 15%, respectively. The other major industry includes the Transport and Storage (19% of the sample), Finance and Insurance (15%), and Mining (11%).

[ Table 2 here ]

Table 3 reports the number of companies cross-listed in Hong Kong and Mainland China each year in the sample period. The number of cross-listed companies has increased from 13 in 1996 to 51 in

2007. Table 3 also reports the number of companies eligible for short selling and ineligible for short selling in the H-share market. Since 2001, the percentage of H-shares non-eligible for short-selling is in the range of 30% to 60%. We also compute the A-H share premium, based on the difference of A- and

11 H-share prices divided by the A-share price, all expressed in Hong Kong dollar. The cross-sectional mean of A-H share premium has decreased from 0.77 in 2001 to 0.42 in 2007.

[ Table 3 here ]

Figure 1 plots the time-series variation of cross-sectional means of A-H share premiums, along with Hang Seng Index and Shanghai Composite Index, the benchmark indices for the Hong Kong and the

China A-share market. The time-series trend of A-H share premium can be partitioned to two regimes. In the first regime from 1996 to 2002, the A-H share premiums stayed at a relatively high level, in the neighborhood of above 0.5 for most of the time. In the second regime after 2002, the A-H share premiums have gone down, and were below 0.5 during that period.

[ Figure 1 here ]

Figure 2 graphs the average of A-H share premiums for short-selling eligible and non-eligible H- share stocks. Because there are relatively fewer stocks before 2000 as reported in Table 3, we focus on the period from 2001 to 2007. Except 2001, the A-H share premiums of short-selling eligible H-share stocks are consistently lower than those of non-eligible ones. At a first glance, this appears to be inconsistent with the overvaluation effect of short-sale constraints. However, as we demonstrate in the subsequent regression analysis, this is because we have not controlled for other factors. Once the other control variables are considered, we find a reversal of the pattern during the bearish market.

[ Figure 2 here ]

Table 4 reports the summary statistics of the short-selling eligible and non-eligible H-share companies. In order to be eligible for short-selling, the H-share companies should be constituent stocks of the equity indices, have stock options traded on the HKEx, or meet a certain requirement for market capitalization and turnover ratio. As a result, it is not surprising from Table 4 that the market capitalization of shortable stocks is higher than non-shortable stocks, no matter whether it is in terms of H

12 shares or A shares. The median market capitalization of shortable H shares is 2.9 billion Hong Kong dollar, as compared with 0.28 billion Hong Kong dollars for non-shortable H shares. The market-to-book ratio of shortable H shares is higher than non-shortable H-shares, with the median values at 1.21 and 0.8, respectively. On the other hand, the market-to-book ratios of the corresponding A shares for the shortable and non-shortable H shares are much closer, with the median values at 2.9 and 2.8, respectively.

We construct three liquidity proxies: trading volume, turnover ratio, and Amihud (2002) illiquidity measure (measured as the absolute returns divided by dollar volume). Results on the three proxies are consistent with each others. In general, the liquidity of shortable stocks is higher than those of non-shortable stocks, especially for the H shares. For example, the Amihud illiquidity measures for shortable H shares and non-shortable H shares are 0.060 and 0.941, respectively. The Amihud measures for the corresponding A shares are 0.063 and 0.150, respectively.

Table 4 also reports the volatility of the sample stocks, as measured by the standard deviation of daily returns. The volatility of shortable stocks is similar to those of non-shortable stocks, both for H shares and A shares. For example, the volatility of shortable H shares is 2.87 and the volatility of non- shortable H shares is 2.92.

[ Table 4 here ]

In Table 5, we examine the relation between the short-selling eligibility of the H shares and the representation in constituent stocks of Hang Seng China Enterprises Index as of 2008. Since the constituent stocks will qualify as short-sale designated securities, Table 5 shows that all constituent stocks of Hang Seng China Enterprises Index are eligible for short selling. Among the 22 non-constituent stocks,

13 are permitted for short selling and 9 are not permitted.

[ Table 5 here ]

5. Regression Analysis

5.1 Construction of A-H Share Premiums

13 The main analysis of the paper is to investigate the price effect of short-sale constraints, by comparing the A-H share premium of the H shares eligible for short selling and those ineligible. The A-H premium is defined as

P A − P H Premium = i,t i,t (1) i,t A Pi,t

A H where Pi,t and Pi,t are stock prices of A- and H-shares of the same firm i at month t. It can be shown that the change of premium at month t can be expressed as follows:

∆=premiumit,,,1 premium it − premium it− ⎛⎞HHHH HH Pit,1−−()11++ RET it ,⎛⎞PP P it ,1() RET it , =−⎜⎟11 −−⎜⎟it,1−− = it ,1 − ⎜⎟PAA11++ RET⎜⎟PPAA P AA RET ⎝⎠it,1−−() it ,⎝⎠it,1−− it ,1 it ,1() it , HA PPit,1−−AH it ,1 ≈×+−AH()1 RETit,, RET it − PPit,1−− it ,1 H Pit,1− AH = A ×−()RETit,, RET it Pit,1− =−1premium × RETAH − RET (2) ()it,1− () it , it ,

A H where RETi,t and RETi,t are stock returns of A and H shares. Equation (2) shows that the change of

premium is proportional to(1 − Pr emiumi,t−1 ), as well as the difference of stock returns between A and H shares. Therefore, when we later investigate the effect of short sale constraints on the A-H share

∆premiumi,t premium, we will use either ∆ Pr emiumi,t or as the dependent variable. 1 − premiumi,t−1

5.2 Construction of Explanatory Variables

The following are the variables being used in the regression analysis to explain ∆ Pr emiumi,t or

14 ∆premium i,t : 1 − premiumi,t−1

(a) Shortablei,t – dummy variable for H-share short-selling eligibility. It is equal to 1 for shortable H-shares and 0 otherwise;

(b) MKTH,t and MKTA,t – market returns of the H-share and A-share market, with the market returns constructed based on Hang Seng China Enterprises Index and Shanghai Composite Index;

(c) MKTDummy1 and MKTDummy2 – dummy variable for the market going down at month t. In terms of the market proxy, we have a choice of the H-share and A-share market. Since our hypothesis is on the effect of different short-sale constraints across two groups of H-shares on their A-H share premiums, we choose the H-share market as the market proxy. We construct two variables based on the H-share market returns, which will interact with the dummy variable Shortablei,t in the regression analysis:

Dummy1 ⎧1, if MKTh,t < 0 MKTH ,t = ⎨ ⎩0, otherwise

Dummy2 ⎧− MKT, if MKTh,t < 0 MKTH ,t = ⎨ (3) 0, otherwise ⎩

(d) Other control variables – We also incorporate other control variables in explaining the change of premium, including the market capitalization, trading volume, bid-ask spread, and stock return volatility for both H-shares and A-shares.

5.3 Regression Analysis

We first estimate the following four regression models using change of the premium, with results reported in Table 6. To control for the fixed effects and autocorrelations of the residuals, we follow

Peterson (2008) and adjust the t-value by Rogers standard error clustered at the firm level.

15 Dummy1 ∆premiumi,t = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t (4) Dummy2 ∆premiumi,t = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t (5) Dummy1 ∆premiumi,t = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t (6) Dummy2 ∆premiumi,t = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t + ControlVariables + ε (7) i,t

Holding other things equal, we expect an increase in H-share market return (MKTH,t ) to have a negative effect on the premium (negative β1), and an increase in A-share market return (MKTA,t ) to have a positive effect (positive β2). Since pessimistic investors could short in those H shares eligible for short- selling but cannot do so in those ineligible ones, shortable H shares have a higher premium than the non- shortable ones. Therefore, we expect the coefficient β3 to be positive. We also have the interaction term,

Dummy1 Dummy1 such as MKTH ,t * Shortablei,t or MKTA,t * Shortablei,t , which represents the additional effect of bearish market on the premium of shortable H shares over the non-shortable ones. Since the shortable H shares are subject to more downward price pressure due to short-selling than the non-shortable ones, we expect the coefficient of β4 be positive.

Results are shown in Table 6. We first examine the results in Model 1 and 2. Consistent with our prediction, H-share market return (MKTH,t ) has a negative effect on the premium while the A-share market return (MKTH,t ) has a positive effect on the premium. The dummy variable for short-sale eligibility (Shortablei,t ) does not have a significant effect on the premium, probably because the short- sale eligibility is correlated with stock liquidity. Since the H-share company that is permitted for short- sale is more liquid, it probably commands a higher price so that it partially offsets the lower valuation effect due to short-sale eligibility. As a result, the effect of short-sale eligibility on the premium is not unambiguous. On the other hand, consistent with our prediction, we find that the coefficient associated

16 Dummy1 Dummy1 with the interaction terms, MKTH ,t * Shortablei,t or MKTA,t * Shortablei,t , are statistically positive.

Results based on Model 3 and 4 are similar. The difference of stock market returns in the H- share and A-share market (MKTH,t - MKTA,t ) has a significantly negative impact on the premium. Again, while the coefficient for short-sale eligibility dummy variable is not significant, the coefficient associated

Dummy1 Dummy1 with either MKTH ,t * Shortablei,t or MKTA,t * Shortablei,t is significantly positive.

Overall, results indicate that when the market goes down, short-sale constraints play a role in explaining the change of A-H share premiums. This is because the prices of shortable H shares decrease faster than those of non-shortable H shares. As a consequence, the premium of A-H shares becomes larger for the shortable H shares. For control variables, the A-share market value, trading volume of H-share stocks and H-share return volatility contribute to explain the movements of the premiums.

[ Table 6 here ]

∆premium We also estimate the regression model (4) to (7), using i,t as the dependent 1 − premiumi,t−1 variable. Results, which are reported in Table 7, are generally to those in Table 6. The coefficient of the dummy variable Shortablei,t is not statistically significant in any model. As regards the interaction terms

Dummy1 Dummy1 (e.g. MKTH ,t * Shortablei,t and MKTA,t * Shortablei,t ), they are statistically positive in three out of four models.

[ Table 7 here ]

5.4. VAR Analysis of A-H Share Premiums

Previous studies show that stock prices incorporate information more quickly if short selling is allowed (Chen and Rhee (2007)). In this section, we investigate the lead-lag relation between the A-H share premiums of shortable H-share stocks and non-shortable H-share stocks. We hypothesize that the

A-H share premiums of short-selling eligible stocks lead the premiums of short-selling ineligible stocks,

17 especially in the down market. We perform the following VAR analysis using weekly A-H share premium data:

Non Short Non Short premiumi,t = c0 + λ0 premiumi,t−1 + α 0 premiumi,t−1 + β 0 premiumi,t−1 * MKTt−1 + ε 0 (8)

Short Short Non Short premiumi,t = c1 + λ1 premiumi,t−1 + α1 premiumi,t−1 + β1 premiumi,t−1 * MKTt−1 + ε1 (9)

Short where premiumi,t is the cross-sectional average of A-H share premium on the portfolio of stocks

Non eligible for short selling, premiumi,t is the cross-sectional average of A-H share premium on the

portfolio of stocks not eligible for short selling, and MKTt−1 is a dummy variable for the market direction, with 1 for the down market (negative market return at week t-1) and 0 for the up market (positive market return at week t-1). The market direction is defined based on either the A-share market (Shanghai

Composite Index) or H-share market (Hang Seng China Enterprises Index), and the regression analysis is conducted based on different market proxy for defining MKTt−1 , respectively.

Table 8 reports the results. First, regardless of whether MKTt−1 is defined using the A-share

Short market or H-share market proxy, the lagged premium of shortable stock portfolio ( premiumi,t−1 ) can

Non predict the premium of non-shortable stock portfolio ( premiumi,t ), but lagged premiums of non-

Non shortable stock portfolio ( premiumi,t−1 ) cannot predict the premium of shortable stock portfolio

Short ( premiumi,t ). The results are robust by conducting the VAR analysis from one-week lag to eight-week lag. Second, the interaction of lagged premiums of shortable stocks with the down market dummy is statistically significant in most models, no matter whether we define the dummy variable based on the A- share market or H-share market.

[ Table 8 here ]

5.5. Event Studies of Changes of Short-sale Eligibility in H-shares

18 In this section we investigate the changes of A-H share premiums if the H-shares are added to or deleted from the designated short-selling list on the HKEx. If short-sale constraints will cause overvaluation, we should see that H-share stocks that are deleted from the short-selling list will experience an increase in stock prices and a decrease in the A-H share premium, while the stocks that are added to the short-selling list will experience a decrease in stock prices and an increase in the A-H share premium.

Table 9 reports the analysis of the additions/deletions of H-share stocks to the short-selling list on

A-H share premiums, using various event windows. Contrary to our prediction, we find that on average,

A-H share premium decreases significantly upon the addition of H-shares to short-selling list, at least for the 11-day window (decreasing from 0.556 in the pre-event [-5, -1] to 0.543 in the post-event [0, 5] ) and

21-day window (decreasing from 0.560 in the pre-event [-10, -1] to 0.541 in the post-event [0, 10]), while the premium increase significantly upon the deletion of H-shares from the short-selling list, at least for the

41-day window (increasing from 0.736 in the pre-event [-20, -1] to 0.751 in the post-event [0, 20]). One explanation is that H-share stocks that are deleted from (added to) the short-selling list might be associated with weak (strong) investor sentiment, so that H-share prices move in the direction opposite to our prediction.

On the other hand, we do find over the 121-day window, the premium decreases significantly upon the deletion of H-shares from the short-selling list, decreasing from 0.760 in the pre-event [-60, -1] to 0.730 in the post-event [0, 60]).

[ Table 9 here ]

6. Conclusion

In this paper we investigate the effect of different short-sale constraints of the H-share stocks on the A-H share premiums, using data on H shares from Hong Kong and A shares from Mainland in the

1996 – 2007 sample period. Our results indicate that when the market goes down, short-sale constraints play a role in explaining the change of A-H share premiums. When the market is down, the prices of

19 shortable H-shares decrease faster than those of non-shortable H-shares. As a consequence, the premium of A-H shares becomes larger for the shortable H-shares. We also investigate the lead-lag relation between the A-H share premiums of short-selling eligible stocks and those of ineligible ones. Consistent with the prediction that shortable stocks incorporate information faster, we find that lagged premium of shortable stock portfolio leads the premium of non-shortable stock portfolio, but not vice versa.

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22 Table 1: Listing Dates of Sample Stocks This table reports the listing dates of H-shares in the Hong Kong Exchange, A-shares in the Shanghai Stock Exchange (SH) and Shenzhen Stock Exchange (SZ). The listing dates of H-shares are obtained from Hong Kong Exchange webiste and the listing dates of A-shares are obtained from Shanghai Stock Exchange and Shenzhen Stock Exchange.

H-share A-share Listing H-share listing A-share A-share listing Gap Stock Name Code date Code exchange date (Day)

Tsingtao Brewery 168 19930715 600600 SH 19930827 43 Sinopec Shanghai Petrochem 338 19930726 600688 SH 19931108 105 Beiren Printing Machinery 187 19930806 600860 SH 19940506 273 Guangzhou Shipyard Int'l 317 19930806 600685 SH 19931028 83 Maanshan Iron & Steel 323 19931103 600808 SH 19940106 64 Kunming Machine Tool 300 19931207 600806 SH 19940103 27 Sinopec Yizheng Chemical Fibre 1033 19940329 600871 SH 19950411 378 Tianjin Capital Envir Protection 1065 19940517 600874 SH 19950630 409 Dongfang Electric Corp 1072 19940606 600875 SH 19951010 491 Luoyang Glass 1108 19940708 600876 SH 19951031 480 China Shipping Development 1138 19941111 600026 SH 20020523 2750 Jilin Chemical Industrial * 368 19950523 618 SZ 19961015 511 Northeast Electric Dev 42 19950706 585 SZ 19951213 160 Jingwei Textile Machinery 350 19960202 666 SZ 19961210 312 Nanjing Panda Electric 553 19960502 600775 SH 19961118 200 Guangshen Railway 525 19960514 601333 SH 20061222 3874 Hisense Kelon Electric 921 19960723 921 SZ 19990713 1085 Anhui Expressway 995 19961113 600012 SH 20030107 2246 Shandong Xinhua Pharm 719 19961231 756 SZ 19970806 218 China Eastern Airlines 670 19970205 600115 SH 19971105 273 Shenzhen Expressway 548 19970312 600548 SH 20011225 1749 Datang Int'l Power Generation 991 19970321 601991 SH 20061220 3561 Beijing North Star 588 19970514 601588 SH 20061016 3442 Jiangxi Copper 358 19970612 600362 SH 20020111 1674 Jiangsu Expressway 177 19970627 600377 SH 20010116 1299 Angang Steel 347 19970724 898 SZ 19971225 154 Chinia Southern Airlines 1055 19970731 600029 SH 20030725 2185 Chongqing Iron & Steel 1053 19971017 601005 SH 20070228 3421 Anhui Conch Cement 914 19971021 600585 SH 20020207 1570 Guangzhou Pharm 874 19971030 600332 SH 20010206 1195 Huaneng Power Int'l 902 19980121 600011 SH 20011206 1415 Yanzhou Coal Mining 1171 19980401 600188 SH 19980701 91

23 Huadian Power Int'l 1071 19990630 600027 SH 20050203 2045 Petro China 857 20000407 601857 SH 20071105 2768 China Petro & Chemical 386 20001019 600028 SH 20010808 293 Aluminum Corp of China 2600 20011212 601600 SH 20070430 1965 China Oilfield Services 2883 20021120 601808 SH 20070928 1773 China Life Insurance 2628 20031218 601628 SH 20070109 1118 China Shipping Container Lines 2866 20040616 601866 SH 20071212 1274 Ping An Insurance 2318 20040624 601318 SH 20070301 980 Weichai Power 2338 20041103 338 SZ 20070430 908 ZTE Corp 763 20041209 63 SZ 19971118 -2578 Air China 753 20041215 601111 SH 20060818 611 China Shenhua Energy 1088 20050615 601088 SH 20071009 846 Bank of Communication 3328 20050623 601328 SH 20070515 691 China Cosco 1919 20050630 601919 SH 20070626 726 China Construction Bank 939 20051027 601939 SH 20070925 698 Bank of China 3988 20060601 601988 SH 20060705 34 China Merchants Bank 3968 20060922 600036 SH 20020409 -1627 Ind & Com Bank of China 1398 20061027 601398 SH 20061027 0 China Coal Energy 1898 20061219 601898 SH 20080201 409 China CITIC Bank 998 20070427 601998 SH 20070427 0 China Railway 390 20070712 601390 SH 20071203 144

* Delisted on February 20, 2006

24 Table 2: Industry Classification of Sample Stocks CSRC industry code is defined as Guidelines on Industry Classification of Listed Companies of CSRC (China Securities Regulatory Commission ), which could be access at http://www.csrc.gov.cn/. The classification is based on the operation income of the consolidated financial statement. Each company’s industry code and it's a share code are from Shanghai or Shenzhen Stock Exchange. H share code is from Hong Kong Exchange.

Panel A: By individual stocks A-share Industry Stock Name Code code CSRC Industry name

Tsingtao Brewery 600600 C0 Food and beverage Sinopec Shanghai Petrochem 600688 C4 Petroleum, chemistry, rubber and plastic Beiren Printing Machinery 600860 C7 Machinery, equipment and instrument Guangzhou Shipyard Int'l 600685 C7 Machinery, equipment and instrument Maanshan Iron & Steel 600808 C6 Metal and non-metal Kunming Machine Tool 600806 C7 Machinery, equipment and instrument Sinopec Yizheng Chem Fibre 600871 C4 Petroleum, chemistry, rubber and plastic Tianjin Capital Envir Prot 600874 K Social service Dongfang Electric Corp 600875 C7 Machinery, equipment and instrument Luoyang Glass 600876 C6 Metal and non-metal China Shipping Development 600026 F Transport and storage Jilin Chemical Industrial * 618 C4 Petroleum, chemistry, rubber and plastic Northeast Electric Dev 585 C7 Machinery, equipment and instrument Jingwei Textile Machinery 666 C7 Machinery, equipment and instrument Nanjing Panda Electric 600775 G Information Technology Guangshen Railway 601333 F Transport and storage Hisense Kelon Electric 921 C7 Machinery, equipment and instrument Anhui Expressway 600012 F Transport and storage Shandong Xinhua Pharm 756 C8 Medicine and biological products China Eastern Airlines 600115 F Transport and storage Shenzhen Expressway 600548 F Transport and storage Datang Int'l Power Electric power, gas and water production and Generation 601991 D supply Beijing North Star 601588 J Real estate Jiangxi Copper 600362 C6 Metal and non-metal Jiangsu Expressway 600377 F Transport and storage Angang Steel 898 C6 Metal and non-metal Chinia Southern Airlines 600029 F Transport and storage Chongqing Iron & Steel 601005 C6 Metal and non-metal Anhui Conch Cement 600585 C6 Metal and non-metal Guangzhou Pharm 600332 C8 Medicine and biological products Electric power, gas and water production and Huaneng Power Int'l 600011 D supply

25 Yanzhou Coal Mining 600188 B Mining Electric power, gas and water production and Huadian Power Int'l 600027 D supply Petro China 601857 B Mining China Petro & Chemical 600028 B Mining Aluminum Corp of China 601600 C6 Metal and non-metal China Oilfield Services 601808 B Mining China Life Insurance 601628 I Finance and insurance China Shipping Cont Lines 601866 F Transport and storage Ping An Insurance 601318 I Finance and insurance Weichai Power 338 C7 Machinery, equipment and instrument ZTE Corp 63 G Information Technology Air China 601111 F Transport and storage China Shenhua Energy 601088 B Mining Bank of Communication 601328 I Finance and insurance China Cosco 601919 F Transport and storage China Construction Bank 601939 I Finance and insurance Bank of China 601988 I Finance and insurance China Merchants Bank 600036 I Finance and insurance Ind & Com Bank of China 601398 I Finance and insurance China Coal Energy 601898 B Mining China CITIC Bank 601998 I Finance and insurance China Railway 601390 E Construction

Panel B: By industry

Industry Code Industry Name Percentage B Mining 11% C Manufacturing 40% - C6 - Metal and non-metal 13% - C7 - Machinery, equipment and instrument 15% D Electric power, gas and water production and supply 6% E Construction 2% F Transport and storage 19% G Information Technology 4% I Finance and insurance 15% J Real estate 2% K Social service 2%

26 Table 3: Number of A- and H-share Stocks and A-H Share Premiums This table reports the number of stocks which are listed in both of A-share market and Hong Kong market from 1996 to 2007. We report the number of stocks is eligible (non-eligible) for selling-selling. We also report the mean and median value of A-H share premiums. A-H share premiums are computed as the difference of A- and H-share prices, and then divided by the A-share price, both measured in the Hong Kong dollar. We obtained the A-share prices from Tsinghua Financial Database and H-share prices from Datastream. The Shanghai Composite Index and Hang Seng Index are obtained from Datastream. We obtained the short-selling eligibility of H-shares from the Hong Kong Exchange.

No of A- and H- share stocks A-H share premiums Year Total Non-eligible Eligible Mean Median

1996 13 12 1 0.56 0.59 1997 16 13 15 0.63 0.65 1998 17 2 17 0.80 0.81 1999 18 0 18 0.78 0.82 2000 18 0 18 0.82 0.85 2001 23 13 23 0.77 0.77 2002 26 16 14 0.71 0.73 2003 28 16 16 0.59 0.64 2004 29 13 16 0.48 0.51 2005 30 13 18 0.30 0.29 2006 37 13 26 0.25 0.22 2007 51 15 42 0.42 0.41

27 Table 4: Summary Statistics of A- and H-shares This table presents the summary statistics of dual listing A- and H-shares in the China A-Share market and the Hong Kong H-share market from 1997 to 2007. Market Capitalization is the share price multiplied by the number of ordinary shares outstanding. Market-to-Book Ratio is defined as market capitalization over net tangible assets. Trading volume is the average daily trading volume in million shares. Turnover is defined as the daily trading volume over number of shares outstanding. For the market capitalization and the market-to-book ratio, we first obtained the last observation of each firm in each year then take the average. For the trading volume and turnover, we use the data in the December of each firm in each year, and then take the average. Illiquidity (Amihud, 2002) is defined as

Dim 1 Rimd ILLIQit = ∑ Dim t=1 VOLDimd where Dim is the number of days for which data is available for stock i in month m, Rimd is the return on stock i on day d of month t and VOLDimd is the respective daily volume in dollars. Shortable and non-shortable refer to the information in the last trading of each year. All the data are obtained from Datastream.

Shortable Non-Shortable Mean Median S.D. Min Max Mean Median S.D. Min Max

Market Capitalization (million) H-share (HK$) 28,736 2,944 119,716 20 1,473,959 493 288 639 75 4,028 A-share (RMB) 10,668 1,774 26,742 109 199,132 1,182 565 2,709 129 21,240 Market-to-book Ratio H-share 1.76 1.21 2.05 0.13 19.84 0.97 0.8 0.57 0.32 2.83 A-share 3.96 2.9 3.4 0.94 25.01 3.42 2.82 2.33 0.71 16.56 Trading Volume (million shares) H-share 24 8 64 0 494 14 1 98 0 879 A-share 17 26 45 0 353 12 1 71 0 628 Turnover H-share 0.8 0.63 0.78 0.03 7.27 1.07 0.35 2.83 0.07 24.03 A-share 1.74 1.07 2.16 0.03 20.61 1.72 0.74 2.62 0.16 15.47 Daily Return Std deviation H-share 3.084 2.876 1.326 1.483 8.240 3.042 2.920 0.918 1.846 4.553 A-share 2.007 1.856 0.723 1.382 4.444 1.993 1.887 0.629 0.895 4.177 Amihud Illquidity H-share (%/million HK$) 0.523 0.060 1.369 0.000 8.096 2.298 0.941 2.688 0.001 9.802 A-share (%/million RMB) 0.214 0.053 0.297 0.001 1.232 0.378 0.150 0.442 0.001 1.800

29 Table 5: A-H Dual-Listing and Hang Seng China Enterprises Index Constituent Stocks This table presents whether the A-H dual-listed stocks are included in the Hang Seng China Enterprises Index (H-share Index) on July 23, 2008. In the third column, 1 means it includes in the H-share Index and 0 means not. In the last column, we also report whether the stock is eligible for short selling in the Hong Kong market at the same time. The H-share Index constituent stocks data is obtained from the Hang Seng Index Services Co. Ltd. Website, and the short selling list is obtained from the Hong Kong Exchange.

Stock Name H-share Hang Seng China Eligible for Code Enterprises Index Short Selling

Northeast Electric Dev 42 0 0 Beiren Printing Machinery 187 0 0 Kunming Machine Tool 300 0 0 Jingwei Textile Machinery 350 0 0 Nanjing Panda Electric 553 0 0 Shandong Xinhua Pharm 719 0 0 Hisense Kelon Electric 921 0 0 Tianjin Capital Envir Protection 1065 0 0 Luoyang Glass 1108 0 0 Guangzhou Shipyard Int'l 317 0 1 Shenzhen Expressway 548 0 1 Beijing North Star 588 0 1 China Eastern Airlines 670 0 1 ZTE Corp 763 0 1 Guangzhou Pharm 874 0 1 Anhui Expressway 995 0 1 Sinopec Yizheng Chemical Fibre 1033 0 1 Chongqing Iron & Steel 1053 0 1 Chinia Southern Airlines 1055 0 1 Huadian Power Int'l 1071 0 1 Dongfang Electric Corp 1072 0 1 Weichai Power 2338 0 1 Tsingao Brewery 168 1 1 Jiangsu Expressway 177 1 1 Maanshan Iron & Steel 323 1 1 Sinopec Shanghai Petrochem 338 1 1 Angang Steel 347 1 1 Jiangxi Copper 358 1 1 China Petro & Chemical 386 1 1 China Railway 390 1 1 Guangshen Railway 525 1 1 Air China 753 1 1 Petro China 857 1 1 Huaneng Power Int'l 902 1 1 Anhui Conch Cement 914 1 1 China Construction Bank 939 1 1 Datang Int'l Power Generation 991 1 1 China CITIC Bank 998 1 1 China Shenhua Energy 1088 1 1 China Shipping Development 1138 1 1 Yanzhou Coal Mining 1171 1 1 Ind & Com Bank of China 1398 1 1 China Coal Energy 1898 1 1 China Cosco 1919 1 1 Ping An Insurance 2318 1 1 Aluminum Corp of China 2600 1 1 China Life Insurance 2628 1 1 China Shipping Container Lines 2866 1 1 China Oilfield Services 2883 1 1 Bank of Communication 3328 1 1 China Merchants Bank 3968 1 1 Bank of China 3988 1 1

Total 30 43

31 Table 6: Regression Analysis on Changes of Premiums (I) In this table we report the coefficients of the following regressions: Dummy1 ∆premiumi,t = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t Dummy2 ∆premiumi,t = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t Dummy1 ∆premiumi,t = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t Dummy2 ∆premiumi,t = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t

+ ControlVariables + ε i,t A-H share premiums are computed as the difference of A- and H-share prices, and then divided by the A- share price, both measured in the Hong Kong dollar. ∆premiumit, , MKTH,t, MKTA,t are premium change for stock i from the end of month t-1 to the end of month t, the H share market return for month t, and A share market return month t, respectively.

Dummy1 ⎧ 1, if MKTh,t < 0 MKTH ,t = ⎨ 0, otherwise ⎩

Dummy2 ⎧− MKT, if MKTh,t < 0 MKTH ,t = ⎨ ⎩ 0, otherwise The control variables are: natural logarithm of A and H share market value (A share market value is the market value of all the floating shares), natural logarithm of A and H share trading volume, A and H share return volatility, and A and H share closing bid-ask spread. Market value, trading volume, and closing bid- ask spread are calculated as the average of all the daily observations for each share at each month, then take the natural log for market value and trading volume. Return volatility is the return standard deviation of each share at each month. Market value is in million RMB and HK$, respectively. Trading volume is in thousands of shares. We obtained the A-share prices from Tsinghua Financial Database and H-share prices from Datastream. We obtain the short-selling eligibility of H-shares from the Hong Kong Exchange. The period is from Jan 2002 to Dec 2007. T-value is adjusted by the Rogers standard error clustered by the firm.

Independent Variables Model 1 Model 2 Model 3 Model 4 Intercept -0.022 -0.021 -0.0177 -0.0164 (-1.15) (-1.10) (-0.91) (-0.85)

MKTH,t -0.36*** -0.367*** (-9.71) (-9.64)

MKTA,t 0.263*** 0.263*** (14.21) (14.12)

MKTH,t – MKTA,t -0.279*** -0.280*** (-15.93) (-15.99)

Shortablei,t -0.0056 -0.0034 -0.0076 -0.0048 (-1.13) (-0.71) (-1.58) (-1.01) Dummy1 MKTH,t * Shortablei,t 0.015*** 0.0233*** (3.10) (6.03) Dummy2 MKTH,t * Shortablei,t 0.250*** 0.415*** (2.59) (5.75) Log(H-share market value) -0.0017 -0.0020 -0.00153 -0.0019 (-0.83) (-0.94) (-0.74) (-0.92) Log (A-share market value) 0.0088*** 0.0088*** 0.0087*** 0.0085*** (4.29) (4.24) (4.21) (4.11) Log (H-share trading volume) -0.0046*** -0.0045*** -0.0051*** -0.0049*** (2.71) (-2.62) (-2.99) (-2.86) Log (A-share trading volume) 0.0024 0.0024 0.0022 0.0022 (1.33) (1.32) (1.24) (1.25) H-share volatility -0.360*** -0.386*** -0.348*** -0.391*** (-2.91) (-3.11) (-2.81) (-3.41) A-share volatility 0.0019 0.0019 0.0016 0.0015 (1.16) (1.15) (0.96) (0.93) H-share spread -0.012 -0.0115 -0.023 -0.022 (-0.34) (-0.32) (-0.64) (-0.63) A-share spread -0.0002 -0.0019 0.0019 -0.0006 (-0.01) (-0.08) (0.08) (-0.03) R-square 0.181 0.180 0.178 0.177 Obs 2097 2097 2097 2097

*, **, *** means significantly at 10%, 5%, and 1% level, respectively.

33 Table 7: Regression Analysis on Changes of Premiums (II) In this table we report the coefficients of the following regressions:

∆premiumi,t Dummy1 = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t 1 − premiumi,t−1

+ ControlVariables + ε i,t

∆premiumi,t Dummy2 = α + β1MKTH ,t + β 2 MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t 1 − premiumi,t−1

+ ControlVariables + ε i,t

∆premiumi,t Dummy1 = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t 1 − premiumi,t−1

+ ControlVariables + ε i,t

∆premiumi,t Dummy2 = α + β1 ()MKTH ,t − MKTA,t + β 3 Shortablei,t + β 4 MKTH ,t * Shortablei,t 1 − premiumi,t−1

Dummy1 ⎧ 1, if MKTh,t < 0 MKTH ,t = ⎨ 0, otherwise ⎩

Independent Variables Model 1 Model 2 Model 3 Model 4 Intercept -0.0794** -0.078** -0.069** -0.0658* (-2.34) (-2.29) (-2.04) (-1.94)

MKTH,t -0.667*** -0.702*** (-10.26) (-10.51)

MKTA,t 0.454*** 0.450*** (13.96) (13.76)

MKTH,t – MKTA,t -0.487*** -0.490*** (-15.88) (-15.95)

Shortablei,t -0.0034 0.0009 -0.0080 -0.0025 (-0.39) (0.11) (-0.94) (-0.30) Dummy1 MKTH,t * Shortablei,t 0.022** 0.0396*** (2.55) (5.85) Dummy2 MKTH,t * Shortablei,t 0.259 0.659*** (1.53) (5.21) Log(H-share market value) -0.0013 -0.0016 -0.0009 -0.0015 (-0.36) (-0.45) (-0.25) (-0.41) Log (A-share market value) 0.0138*** 0.0138*** 0.013*** 0.013*** (3.81) (3.81) (3.70) (3.63) Log (H-share trading volume) -0.0152*** -0.0149*** -0.0162*** -0.0158*** (-5.07) (-4.97) (-5.42) (-5.30) Log (A-share trading volume) 0.0114*** 0.0113*** 0.011*** 0.011*** (3.63) (3.59) (3.52) (3.49) H-share volatility -0.774*** -0.804*** -0.748*** -0.815*** (-3.57) (-3.69) (-3.44) (-3.73) A-share volatility -0.0034 -0.0034 -0.0042 -0.0043 (-1.18) (-1.17) (-1.44) (-1.48) H-share spread -0.063 -0.060 -0.086 -0.087 (-1.00) (-0.96) (-1.39) (-1.39) A-share spread 0.052 0.050 0.057 0.053 (1.26) (1.21) (1.38) (1.28) R-square 0.195 0.193 0.191 0.188 Obs 2097 2097 2097 2097

*, **, *** means significantly at 10%, 5%, and 1% level, respectively.

35 Table 8: VAR Analysis in the Weekly Data This table presents the coefficients of the following VAR regression: Non Short Non Short premiumi,t = c0 + λ0 premiumi,t−1 + α 0 premiumi,t−1 + β 0 premiumi,t−1 * MKTt−1 + ε 0 (8) Short Short Non Short premiumi,t = c1 + λ1 premiumi,t−1 + α1 premiumi,t−1 + β1 premiumi,t−1 * MKTt−1 + ε1 (9)

Short where premiumi,t is the cross-sectional average of A-H share premium on the portfolio of stocks Non eligible for short selling, premiumi,t is the cross-sectional average of A-H share premium on the portfolio of stocks not eligible for short selling, with A-H share premium computed as the difference of A- and H-share prices, then divided by the A-share price, both measured in the Hong Kong dollar, and

MKTt−1 is a dummy variable for the market going up or down (1 for down market, 0 for up market). Up (down) market is when the lagged market return is positive (negative), defined either based on the A-share market return (Shanghai Composite Index) or the H-share market return (Hang Seng China Enterprise Index). We obtained the A-share prices from Tsinghua Financial Database and H-share prices from Datastream. We obtain the short-selling eligibility of H-shares from the Hong Kong Exchange.

A-share Market Return for MKTt−1 H-share Market Return for MKTt−1 Non Short Non Short premiumi,t premiumi,t premiumi,t premiumi,t

Panel A: one-week lag Short 0.247*** 1.038*** 0.196*** 0.948*** premiumi,t−1 (3.93) (14.47) (3.14) (13.83) Non 0.809*** -0.074 0.834*** -0.029 premiumi,t−1 (11.25) (-0.90) (11.69) (-0.37) Short -0.016*** -0.024*** 0.021*** 0.042*** premiumi,t−1 * MKTt−1 (-2.71) (-3.42) (3.60) (6.46)

Panel B: two-week lag Short 0.225*** 1.006*** 0.173*** 0.919*** premiumi,t−1 (3.57) (13.95) (2.69) (12.65) Non 0.813*** -0.069 0.825*** -0.048 premiumi,t−1 (11.21) (-0.83) (11.53) (-0.60) Short -0.010 -0.015** 0.019*** 0.032*** premiumi,t−1 * MKTt−1 (-1.61) (-2.13) (3.14) (4.68)

Panel C: four-week lag Short 0.226*** 1.008*** 0.196*** 0.967*** premiumi,t−1 (2.81) (13.98) (3.04) (13.07) Non 0.814*** -0.068 0.824*** -0.052 premiumi,t−1 (11.21) (-0.82) (11.39) (-0.63) Short -0.007 -0.015** 0.013** 0.018** premiumi,t−1 * MKTt−1 (-1.14) (-2.17) (2.04) (2.49)

Panel D: eight-week lag

36 Short 0.225*** 1.003*** 0.201*** 0.969*** premiumi,t−1 (3.56) (13.84) (3.15) (13.35) Non 0.817*** -0.063 0.819*** -0.059 premiumi,t−1 (11.23) (-0.75) (11.37) (-0.72) Short -0.003 -0.012* 0.015** 0.023*** premiumi,t−1 * MKTt−1 (-0.45) (-1.65) (2.37) (3.20)

*, **, *** means significantly at 10%, 5%, and 1% level, respectively.

37 Table 9: Event Study on A-H Share Premiums, A- and H-Share Returns This table presents an event study on the additions/deletions of short-selling eligibility of H-shares on A-H share premiums in various event windows. The sample period is from 1996 to 2007. The sample is same for all event windows, which has data in [-60, 60] event period. A-H share premiums are computed as the difference of A- and H-share prices, and then divided by the A-share price, both measured in the Hong Kong dollar. We obtained the A-share prices from Tsinghua Financial Database and H-share prices from Datastream. We obtain the short-selling eligibility of H-shares from the Hong Kong Exchange.

Pre-event Post-event Difference t-statistics

[-5,-1] [0,5] Addition 0.556 0.543 -0.013** -2.08 Deletion 0.744 0.749 0.005 1.11

[-10,-1] [0,10] Addition 0.560 0.541 -0.019** -3.53 Deletion 0.741 0.751 0.010* 2.14

[-20,-1] [0,20] Addition 0.552 0.541 -0.021 -1.38 Deletion 0.736 0.751 0.014** 2.53

[-30,-1] [0,30] Addition 0.548 0.543 -0.004 -0.36 Deletion 0.740 0.743 0.003 0.37

[-60,-1] [0,60] Addition 0.539 0.529 -0.010 -0.57 Deletion 0.760 0.730 -0.030** -2.63

38 Figure 1: Time-series A-H Share Premiums This figure plots the time series changes of average A-H share premiums from 1996 to 2007. A-H share premiums are computed as the difference of A- and H-share prices, then divided by the A-share price, both measured in the Hong Kong dollar. We also plot the Shanghai Composite Index and Hang Seng Index. We obtained the A-share prices from Tsinghua Financial Database and H-share prices from Datastream. The Shanghai Composite Index and Hang Seng Index are obtained from Datastream.

35000 1

0.9 30000 0.8

25000 0.7

l 0.6 20000 0.5 15000

Index Leve Index 0.4

10000 0.3 premium share A-H 0.2 5000 0.1

0 0 1996-3 1997-7 1998-3 1999-7 2000-3 2001-7 2002-3 2003-7 2004-3 2005-7 2006-3 2007-7 1996-11 1998-11 2000-11 2002-11 2004-11 2006-11

Hang Seng Index Shanghai Composite Index A-H share premium

39 Figure 2: A-H Share Premiums of Short-Selling Eligible and Non-Eligible stocks This figure plots the time series changes of average A-H share premiums of short-selling eligible and non- eligible stocks from 1996 to 2007. A-H share premiums are computed as the difference of A- and H-share prices, and then divided by the H-share price, both measured in the Hong Kong dollar. We obtained the A- share prices from Tsinghua Financial Database and H-share prices from Datastream. We obtain the short- selling eligibility of H-shares from the Hong Kong Exchange. For the year 1999 and 2000, all stocks are eligible for short selling.

0.9

0.8

0.7

0.6

0.5

0.4

A-H share premium share A-H 0.3

0.2

0.1

0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

non-shortable shortable