Seminar

Abstract

One of the largest stock markets in the world is opening up to foreign investors. Chinese officials have taken significant steps to make China’s mainland equity market, represented by A-shares, much more accessible. As a result, major index providers such as MSCI and FTSE are incorporating them into their passive indices, and global institutional investors are adding them to their portfolios.

With China A-share market becoming more integrated with the international market such Hong Kong and global institutional investors adding them into their portfolios, it is essential to build a comprehensive understanding of the specific features of this market. The dual-listed A- and H- shares represent a good sample for these studies as they have separated the micro-level company specific risks as these shares are issued by the same company and their shareholders are entitled with exactly same rights. There are already a number of research pieces which discuss pricing relationships between A- and H-shares. These researches cover a range of topics including the cause(s) of any pricing differential, the dynamics of the A/H premium and information asymmetries between the A/H markets. However, the risk relationship between A- and H-shares are lightly touched in the academia world.

Therefore, we are motivated to conduct an in-depth research that looks at the risk features of China A-share market through a close study of the relationship of volatility features between dual-listed A- and H-shares. We try to understand the risk features of Chinese equities from statistical and econometric perspectives by modeling the characteristics of volatility of both China domestic and offshore equities. We use the daily data of dual-listed A- and H-shares over the period from 17 November 2014 to 30 June 2019 post the launch of the Stock Connect Program, in the backdrop of China A-share globalization. By introducing both symmetric and asymmetric models of the generalized autoregressive conditional heteroscedastic (GARCH) family, we use the daily data to estimate the parameters of each model. According to the empirical results presented in this chapter, we conclude that these two models can capture most characteristics of the volatility of Chinese equities and both are adequate to model the exchange rate volatility series.