Abstract
How does the market react when more or fewer investors are allowed to trade certain stocks? Stock Connect, a cross-border investment channel between mainland China and Hong Kong, provides a natural testing ground. Investors are allowed to trade a list of qualified stocks from the stock market on the other side, and when a stock is removed from the list, investors can only sell but cannot buy that stock. We find that the inclusion of stocks is correlated with abnormal returns, implying downward-sloping demand curves for stocks. The effect weakens over time and disappears in about 40 trading days. There are no abnormal returns when stocks are removed from the list. On the other hand, when investors can only sell some stocks, they have a significantly higher propensity to sell. Their trading style becomes more contrarian for such stocks, and they tend to trade in small amounts. After 6 months, their investment behavior returns to that before the removal.
Similar content being viewed by others
Notes
Stock supply in these studies is not restricted to increase in a short period of time. For example, the secondary distributions used in Scholes (1972) were initiated by shareholders, while the change of regulation used in Jain et al. (2019) allowed blockholders to reduce their shareholding in three years.
There are studies in behavioural finance that suggest sell-only restrictions matter. For example, neural evidence on regret in investment provided by Frydman et al. (2014) and Frydman and Camerer (2016) imply that not being able to buy will induce anticipated regret, changing the deposition effect of such stocks. Since we do not have investor-level transaction data, we are not able to explore in this direction.
In turn, they are part of a large literature on the co-movement between stock markets in China and Hong Kong, such as Kim and Shin (2000).
The numbers come from The Stock Connect Fact Sheet (November 17, 2014–October 31, 2019) issued by Hong Kong Exchanges and Clearing Limited.
Moreover, the foreign shareholding of a stock listed in Chinese stock markets is subject to a limit of 30%. Excess shares are subject to forced sale. This poses an additional uncertainty for foreign investors to trade securities in Northbound trading and thus makes corresponding abnormal returns less clear evidences on the slope of demand curves.
In particular, under the Shanghai-Hong Kong Connect, eligible securities include all the constituent stocks of the Hang Seng Composite LargeCap Index and Hang Seng Composite MidCap Index, and all H-shares that are not included as constituent stocks of the relevant indexes but which have corresponding shares in the form of A-shares listed on SSE (with certain exceptions). The Shenzhen-Hong Kong Connect has nearly the same arrangement, with additional eligible stocks from constituent stocks of the Hang Seng Composite SmallCap Index which have a market capitalization of not less than HK$5 billion (which is roughly US$0.5 billion).
The Shanghai Stock Exchange usually announces changes after the market close on Friday while the Shenzhen Stock Exchange usually announces before the market open on Monday.
In particular, each day’s sell ratio is generated by subtracting the average sell ratio of sell-only stocks with past returns in the winner and loser quartile from the average sell ratio of other stocks with past returns in the winner and loser quartile.
Other control variables are not included in the estimations as it would greatly reduce the number of stock-removal observations from 102 to 48. In regressions with the other control variables, the estimated abnormal returns for pooled and fixed effect models are −0.186 and −0.025, respectively. Both estimated results are statistically insignificant due to the limited number of observations.
Using the whole pre-sell-only period does not affect the comparison for liquidity and market capitalization. However, mainland investors; the holding of the sell-only stocks will be underestimated as pre-sell-only period has a greater weight on the initial inclusion period when the holding is small. We, therefore, prefer using a shorter pre-sell-only period for comparison.
The 100 stocks with the largest market capitalization are grouped as large market capitalization stocks while others are classified as small market capitalization stocks. Liquidity is measured as the average ratio of trading value to market capitalization.
References
Afego, P. N. (2017). Effects of changes in stock index compositions: A literature survey. International Review of Financial Analysis, 52, 228–239.
Ahern, K. R. (2014). Do common stocks have perfect substitutes? product market competition and the elasticity of demand for stocks. Review of Economics and Statistics, 96(4), 756–766.
Bai, Y., & Chow, D. Y. P. (2017). Shanghai-hong kong stock connect: An analysis of Chinese partial stock market liberalization impact on the local and foreign markets. Journal of International Financial Markets, Institutions and Money, 50, 182–203.
Biktimirov, E. N., Cowan, A. R., & Jordan, B. D. (2004). Do demand curves for small stocks slope down? Journal of Financial Research, 27(2), 161–178.
Burdekin, R. C., & Siklos, P. L. (2018). Quantifying the impact of the November 2014 Shanghai-Hong Kong stock connect. International Review of Economics and Finance, 57, 156–163.
Chen, H., Noronha, G., & Singal, V. (2004). The price response to s &p 500 index additions and deletions: Evidence of asymmetry and a new explanation. The Journal of Finance, 59(4), 1901–1930.
Choe, H., Kho, B.-C., & Stulz, R. M. (1999). Do foreign investors destabilize stock markets? the Korean experience in 1997. Journal of Financial Economics, 54(2), 227–264.
Dahlquist, M., & Robertsson, G. (2004). A note on foreigners’ trading and price effects across firms. Journal of Banking and Finance, 28(3), 615–632.
Denis, D. K., McConnell, J. J., Ovtchinnikov, A. V., & Yu, Y. (2003). S &p 500 index additions and earnings expectations. The Journal of Finance, 58(5), 1821–1840.
Duffie, D. (2010). Presidential address: Asset price dynamics with slow-moving capital. The Journal of Finance, 65(4), 1237–1267.
Fan, Q., & Wang, T. (2017). The impact of Shanghai-Hong Kong stock connect policy on ah share price premium. Finance Research Letters, 21, 222–227.
Frydman, C., Barberis, N., Camerer, C., Bossaerts, P., & Rangel, A. (2014). Using neural data to test a theory of investor behavior: An application to realization utility. The Journal of Finance, 69(2), 907–946.
Frydman, C., & Camerer, C. (2016). Neural evidence of regret and its implications for investor behavior. The Review of Financial Studies, 29(11), 3108–3139.
Greenwood, R. (2005). Short-and long-term demand curves for stocks: Theory and evidence on the dynamics of arbitrage. Journal of Financial Economics, 75(3), 607–649.
Grinblatt, M., & Keloharju, M. (2000). The investment behavior and performance of various investor types: A study of Finland’s unique data set. Journal of Financial Economics, 55(1), 43–67.
Grinblatt, M., Titman, S. & Wermers, R. ( 1995) . Momentum investment strategies, portfolio performance, and herding: A study of mutual fund behavior, The American Economic Review 1088–1105.
Huo, R., & Ahmed, A. D. (2017). Return and volatility spillovers effects: Evaluating the impact of Shanghai-Hong Kong stock connect. Economic Modelling, 61, 260–272.
Jain, A., Tantri, P., & Thirumalai, R. S. (2019). Demand curves for stocks do not slope down: Evidence using an exogenous supply shock. Journal of Banking and Finance, 104, 19–30.
Kaul, A., Mehrotra, V., & Morck, R. (2000). Demand curves for stocks do slope down: New evidence from an index weights adjustment. The Journal of Finance, 55(2), 893–912.
Kim, Y., & Shin, J. (2000). Interactions among China-related stocks. Asia-Pacific Financial Markets, 7(1), 97–115.
Li, Q., Liu, X., Chen, J., & Wang, H. (2022). Does stock market liberalization reduce stock price synchronicity?-evidence from the Shanghai-Hong Kong stock connect. International Review of Economics and Finance, 77, 25–38.
Li, S., & Chen, Q.-A. (2021). Do the Shanghai-Hong Kong & Shenzhen-Hong Kong stock connect programs enhance co-movement between the mainland Chinese, Hong Kong, and US stock markets? International Journal of Finance and Economics, 26(2), 2871–2890.
Liu, C., Wang, S., & Wei, K. J. (2021). Demand shock, speculative beta, and asset prices: Evidence from the Shanghai-Hong Kong stock connect program. Journal of Banking and Finance, 126, 106102.
Liu, S. (2000). Changes in the nikkei 500: New evidence for downward sloping demand curves for stocks. International Review of Finance, 1(4), 245–267.
Ma, R., Deng, C., Cai, H., & Zhai, P. (2019). Does Shanghai-Hong Kong stock connect drive market comovement between Shanghai and Hong Kong: A new evidence. The North American Journal of Economics and Finance, 50, 100980.
Merton, R. C. (1987) . A simple model of capital market equilibrium with incomplete information.
Neumann, R., & Voetmann, T. (2003). Demand curves for European stocks slope down too. Review of Finance, 7(3), 437–457.
Ng, L., & Wu, F. (2007). The trading behavior of institutions and individuals in Chinese equity markets. Journal of Banking and Finance, 31(9), 2695–2710.
Pan, J., & Chi, J. (2021). How does the Shanghai-Hong Kong stock connect policy impact the ah share premium? Emerging Markets Finance and Trade, 57(7), 1912–1928.
Peng, X. (2015) . Corporate governance of chinese privately owned enterprises listed in hong kong: an empirical study of three levels of agency problems. HKU Theses Online.
Petajisto, A. (2009). Why do demand curves for stocks slope down? Journal of Financial and Quantitative Analysis, 44(5), 1013–1044.
Scholes, M. S. (1972). The market for securities: Substitution versus price pressure and the effects of information on share prices. The Journal of Business, 45(2), 179–211.
Schultz, P. (2008). Downward-sloping demand curves, the supply of shares, and the collapse of internet stock prices. The Journal of Finance, 63(1), 351–378.
Sha, Y., Zhang, P., Wang, Y., & Xu, Y. (2022). Capital market opening and green innovation-evidence from Shanghai-Hong Kong stock connect and the Shenzhen-Hong Kong stock connect. Energy Economics, 111, 106048.
Shleifer, A. (1986). Do demand curves for stocks slope down? The Journal of Finance, 41(3), 579–590.
Shleifer, A., & Vishny, R. W. (1997). The limits of arbitrage. The Journal of finance, 52(1), 35–55.
Wang, Q., & Chong, T.T.-L. (2018). Co-integrated or not? after the Shanghai-Hong Kong and Shenzhen-Hong Kong stock connection schemes. Economics Letters, 163, 167–171.
Wang, S. (2021). How does stock market liberalization influence corporate innovation? Evidence from stock connect scheme in China. Emerging Markets Review, 47, 100762.
Wurgler, J., & Zhuravskaya, E. (2002). Does arbitrage flatten demand curves for stocks? The Journal of Business, 75(4), 583–608.
Xiong, L., Deng, H., & Xiao, L. (2021). Does stock market liberalization mitigate litigation risk? Evidence from stock connect in China. Economic Modelling, 102, 105581.
Xu, K., Zheng, X., Pan, D., Xing, L., & Zhang, X. (2020). Stock market openness and market quality: Evidence from the Shanghai-Hong Kong stock connect program. Journal of Financial Research, 43(2), 373–406.
Yang, L., Wang, B., & Luo, D. (2022). Corporate social responsibility in market liberalization: Evidence from Shanghai-Hong Kong stock connect. Journal of International Financial Markets Institutions and Money, 77, 101519.
Yang, X., Lu, C. & Yang, Z. (2022) . Capital-market liberalization and controlling shareholders’ tunneling-experimental research in the context of “mainland China-Hong Kong stock connect”. Applied Economics 1–16.
Zhang, W., Li, H. & Cao, S. (2021) . Does the Shanghai-Hong Kong stock connect policy reduce China’s ah share price premium? Applied Economics Letters 1–6.
Zhao, Y., Xiang, C., & Cai, W. (2021). Stock market liberalization and institutional herding: Evidence from the Shanghai-Hong Kong and Shenzhen-Hong Kong stock connects. Pacific-Basin Finance Journal, 69, 101643.
Acknowledgments
The authors would like to thank Ka Yan Wong for data collection, Connie Tang for research assistance, and Ka Wai Wan and an anonymous referee for useful comments.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Wong, K.M., Tsang, K.P. Inclusions and Exclusions of Stocks in Cross-Border Investments: The Case of Stock Connect. Asia-Pac Financ Markets 30, 701–727 (2023). https://doi.org/10.1007/s10690-022-09395-3
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10690-022-09395-3