Capital account liberalization and dynamic price discovery: evidence from Chinese cross-listed stocks

ABSTRACT

We analyse the effects of a recent financial reform (Shanghai-Hong Kong Stock Connect) that enables cross-market investment between Hong Kong and Shanghai stock exchanges. Using a VECM, we find that the reform announcement considerably narrows the equilibrium level of price disparity and strengthens the price comovement of shares that are cross-listed in both markets. The estimated equilibrium relationship is in support of the relative law of one price. We find that both markets adjust in response to a disequilibrium in price disparity, leading to a sizeable error correction activity. The Shanghai market contributes to approximately two-thirds of the price discovery process. Competition and informativeness of trading affect the relative role of price discovery in each market. Finally, the reform implementation reinforces the long-run cointegration relationship and strengthens the short-run price comovements of cross-listed stocks despite the widening price disparity during the period.

KEYWORDS:

• Capital account liberalization
• cointegration
• VECM
• cross-listing
• Chinese A-H shares

JEL CLASSIFICATION:

• F36
• G18
• C32

Acknowledgement

We would like to thank an anonymous referee for providing comments that substantially improved the article.

Notes

¹ A prevailing empirical approach is to analyse cross-country time-series data using various measures of liberalization as the principal source of policy variation (e.g. Henry 2000; Harrison, Love, and McMillan 2004; Galindo, Schiantarelli, and Weiss 2007). The findings are often sensitive to country coverage, sample periods and indicators of liberalization (Eichengreen 2001).

² For an earlier study that apply a similar model to one firm (IBM), see Harris et al. (1995).

³ The remaining firms were concurrently listed in the Hong Kong and Shenzhen stock exchanges. While these firms are not included in our baseline sample, we will conduct a similar empirical analysis as a natural control group. More details can be found in the section ‘Shenzhen market as a control group and recent developments’.

⁴ Examples of recent studies include Arquette, Brown, and Burdekin (2008), Chang, Luo, and Ren (2013) and Chung, Hui, and Li (2013).

⁵ Otherwise, this may lead to a biased estimate of the error correction process if both H-share and A-share prices adjust in response to a disequilibrium in price disparity. Another advantage of the VECM is that it can perform hypothesis tests on the law of one price. The univariate model restricts the cointegrating coefficient to unity, which assumes the validity of the relative law of one price. Supplemental data on the relationship between our model and Cai, McGuinness, and Zhang (2011) can be assessed in the section ‘Supplemental data’.

⁶ As an illustration, the cointegrating relationship can be written as $log(P_t^H)+\beta log(P_t^A)+c=0$, where $P_t^H$ is the H-share price, $P_t^A$ is the A-share price, $\beta$ is the cointegrating coefficient and c is a constant. The relative law of one price implies that $\beta =-1$.

⁷ The Mainland market has two stock exchanges (Shanghai and Shenzhen). Firms can only list in either the Shanghai or the Shenzhen market. In 2014, 16 firms were concurrently listed in Hong Kong and Shenzhen markets. Therefore, a total of 68 + 16 = 84 firms were cross-listed between Hong Kong and Mainland China. Firms that are concurrently listed in the Shenzhen and Hong Kong stock exchanges are unaffected by the programme and can form a natural control group for analysis. We will discuss this point in further detail in the section ‘Shenzhen market as a control group and recent developments’.

⁸ The daily quotas in the Shanghai and Hong Kong markets are 10.5 and 13 billion yuan, respectively. Investors in Mainland China who are allowed to invest in the Hong Kong market must have at least 500 000 yuan (80 645 USD) in securities or cash.

⁹ Since then, the RQFII programme has been extended to financial institutions in London, Singapore and Paris, to name a few.

¹⁰ In addition, the offshore Renminbi market in Hong Kong expanded further as the daily yuan conversion cap (20 000 yuan) faced by Hong Kong residents was technically removed by the Hong Kong Monetary Authority at the launch of the Shanghai-Hong Kong Stock Connect on 17 November 2014. However, the lifting of the cap is restricted to the offshore RMB market. Transferring of funds to and from mainland China is still subject to the same restriction as before.

¹¹ As of 2015, there are 58 pairs that form the constituents of the Index. The index contains 15 financial stocks, which constitute over half of the weight of the index.

¹² One stock suspended trading for 1 week, while the others suspended trading for at least 3 months in 2014. Except for the stock that suspended trading for 1 week (utilities), the other stocks were ‘small-cap’ stocks.

¹³ An observation is included if the stock is traded in at least one of the markets. In days where the stock is traded in one market only (e.g. public holiday in one market), the missing price in the other market is filled in by interpolation.

¹⁴ We also test for cointegration using the trace statistic method at the 5% significance level. The results are similar and are available upon request.

¹⁵ The protests were a result of dissatisfaction with the decision by the National People’s Congress regarding proposed reforms to the Hong Kong electoral system. The total number of protesters routinely exceeded 100 000, and key areas in central business districts were occupied by protesters and remained closed to traffic for over 70 days. During the month prior to the official implementation of the campaign, the Hang Seng Index dropped by 10%, while the Shanghai Stock Exchange Composite Index (SSE) increased by 6%.

¹⁶ Sample size restrictions preclude us from further classifying the stocks into multiple industries.

¹⁷ The coefficient on BASRelative is positive and statistically significant. Since the dependent variable is the share of price adjustment, the expected sign of the coefficient is ambiguous in this regression.

¹⁸ We also attempt to classify the stocks according to their level of HA premium just prior to reform implementation. However, comparison with Table 4 then becomes difficult, as only one firm belongs to subgroup 3 under this classification.

¹⁹ As discussed earlier, the raw sample contains 68 firms concurrently listed in Hong Kong and Shanghai markets, 7 of which are dropped from the raw sample. We also attempt to extend the empirical analysis to these firms (when trading is not suspended). There is little difference in the result across the sub-periods, as few of these stocks exhibit cointegration.

²⁰ Seven firms have a cointegrating coefficient of lower than –2, 18 firms have a value between 0 and –2, and three firms have a small positive value. The average SE is 0.50, which is considerably larger than firms with cointegrated share prices (0.19).