Dynamic Linkages Between the Greater China Economic Area Stock Markets—Mainland China,Hong Kong,and Taiwan

This research examines the linkages among three Greater China Economic Area (GCEA) stock markets, including Mainland China, Hong Kong, and Taiwan, and two developed markets, Japan and the United States. We find that: (1) a random walk model is outpredicted by an autoregressive GARCH model and an ARIMA model in all three GCEA markets; (2) the three GCEA markets are not cointegrated with either U.S. or Japan but there exists weak nonlinear relationships between these markets; and (3) result from the innovation accounting analysis reveals that the U.S. market has larger influence on the GCEA markets than the Japanese market. Additionally, Hong Kong is the most influential among the three GCEA markets.JEL Classification: G10, G14, G15Opinions and results presented in this paper are those of the authors and are not intended to represent the views, policies, or interests of Fannie Mae. This paper is not the result of Fannie Mae related research and does not use or cite Fannie Mae data sources.     

Volatility spillovers between the Chinese and world equity markets

We propose measures of the directional volatility spillovers between the Chinese and world equity markets based on Diebold and Yilmaz's (2011b) forecast-error variance decompositions in a generalized vector autoregressive framework. It was found that the US market had dominant volatility impacts on other markets during the subprime mortgage crisis. The other markets were also very volatile, and driven by bad news, their massive volatilities were transmitted back to the US market. The volatility of the Chinese market has had a significantly positive impact on other markets since 2005. The volatility interactions among the markets of China, Hong Kong, and Taiwan were more prominent than those among the Chinese, Western, and other Asian markets were. The major correction of the Chinese stock market between February and July 2007 significantly contributed to the volatility surges of other markets. Owing to the restrictions on foreign investment, the Chinese stock market was not considerably affected in terms of market volatility during the subprime mortgage crisis.     

Are stock and real estate markets integrated? An empirical study of six Asian economies

Rising asset prices spurred by Asia's emerging economy have drawn much attention recently. This study examines one source of growth patterns in asset prices by analyzing the integration relationship between stock markets and real estate markets in Asia. Six economies are selected for empirical analysis: China, Hong Kong, Japan, Singapore, South Korea, and Taiwan. Results show that stock markets are integrated with real estate markets in Japan, and partially integrated with real estate markets in China, Hong Kong, and Taiwan. This implies that these two investment vehicles are substitutable in China, Hong Kong, Japan, and Taiwan, and provide diversification potential for investment portfolios in South Korea and Singapore. Examining the timing of market changes, we found the real estate market leading the stock market in some countries, and the stock market leading the real estate market in others. We conclude that stock and real estate markets show a variety of inter-relationships depending on economic and political policy environments.     

香港股市与内地股市的联动性研究

本文分3个阶段考察了香港回归以来,香港股市和内地股市之间的联动关系及其变化。协整分析表明,香港股市和内地股市之间存在长期的均衡关系,这种均衡关系在内地资本市场实行股权分置改革后更趋于稳定。Granger因果检验表明,香港回归以来香港股市和内地股市之间的引导关系在经历B股开放和股权分置改革后发生了变化。脉冲响应函数分析从动态的角度进一步验证了香港股市和内地股市之间的引导关系及其变化,并深入分析了单个变量的波动或冲击对其自身及另一变量的影响程度。     

上海和香港两地股市联动性研究--基于GARCH模型的分析

本文基于经济基础假说和市场传染假说两大基础理论,将股票收益率分解为开盘收益率和收盘收益率,运用GARCH．M模型研究了上海股市和香港股市之间的联动关系。结果显示,两大股市存在相互影响的联动关系,但是上海对香港股市的影响要强于香港对上海股市的影响,反映出两地之间的紧密经济关系及大陆对香港地区经济影响日益增强的现实。     

Dynamic Modeling of Tail Risk: Applications to China, Hong Kong and Other Asian Markets

In this paper, we study the extreme dependence between the markets in Hong Kong, Shanghai, Shenzhen, Taiwan and Singapore. The tail dependence coefficient (TDC), which measures how likely financial returns move together in extreme market conditions, is modeled dynamically using the Multivariate Generalized Autoregressive Conditional Heteroscedasticity model with the time-varying correlation matrix of Tse and Tsui (Journal of Business & Economic Statistics, 20(3):351–363, 2002). The time paths of the TDC indicate that Hong Kong stocks had the highest extreme dependence during the Asian financial crisis and their TDCs have followed an increasing trend since 2006. The results in this paper also show that the TDC pattern of Singapore with the other markets is very similar to the TDC pattern of Hong Kong with the other markets. An increasing trend in the extreme dependence between Shanghai A Share Index and Shanghai B Share Index and between the Hang Seng Index and the Hong Kong China Enterprise Index is observed from 2002 to 2007. A substantial rise in the TDC between Shenzhen A Share Index and Shenzhen B Share Index was recorded after the China market reforms in 2005. Our TDC modeling with Asian market data provides evidence that Asian markets are becoming integrated and their extreme co-movements during financial turmoil are becoming stronger.     

The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas

This study employs the dynamic copula method and extreme value theory to investigate the dependence structure between pairs of greater China economic area (GCEA) stock markets consisting of Shanghai (SHSE), Shenzhen (SZSE), Hong Kong (HKSE), and Taiwan (TWSE) stock exchanges from July 2000 to June 2017. We also examine the impact of financial crisis on the dependence structure by considering the global financial crisis and the Chinese stock market crash (2015–2016). Many studies have shown that the benefits of portfolio diversification across the stock markets in the same region could be diminishing. However, it is interesting to see that the diversification benefits appear to be viable for investing in some GCEA pairs of stock markets (SHSE–TWSE and SZSE–HKSE).     

Time variation paths of international transmission of stock volatility — US vs. Hong Kong and South Korea

This study examines continuous time variation paths of sensitivities of the Hong Kong and South Korea stock markets to the US stock market and bond market (proxied by long-term interest rates) by using the Flexible Least Squares (FLS) estimation technique. The FLS findings suggest that changes in both the US stock market and US long-term interest rates may simultaneously have significant effects on the Hong Kong stock market in some time periods. In other periods, neither may have significant effects on the Hong Kong stock market. The results also indicate that the South Korea stock market is overall insensitive to changes in the US capital markets. However, it becomes more sensitive in the 1990s. Some macroeconomic variables may explain changes in the sensitivities of the Hong Kong and South Korea stock markets to changes in the US capital markets.     

How cross-listings from an emerging economy affect the host market?

We study the impact of mainland Chinese listings in Hong Kong on the quality and development of the Hong Kong equity market. At the macro-level, we find that the increasing presence of mainland Chinese stocks in Hong Kong increases the size, trading volume, and its link with the China and world markets but reduces the overall volatility of the Hong Kong stock market. At the firm level, the increase affects the market quality, resulting in lower turnover rate, higher Amihud illiquidity ratio, and higher spread for non-mainland Chinese firms. Furthermore, such an increase in presence causes Hong Kong stocks to move in a more synchronized way and reduces these firms investment sensitivity to stock price movement, implying deterioration in the information environment. As a whole, the increasing presence of Chinese companies in Hong Kong brings benefits to the Hong Kong market, yet not without cost.     

Determinants of returns and volatility of Chinese ADRs at NYSE

This paper examines the determinants of returns and of volatility of the Chinese ADRs as listed at NYSE. Using an autoregressive conditional heteroskedasticity (ARCH) model and data from 16 April 1998 through 30 September 2004, we find that Hong Kong stock market (underlying market), US stock market (host market), and local (Shanghai A and B) markets all are important determinants of returns of the Chinese ADRs. However, the underlying Hong Kong market has the most significant impact on mean returns of the ADRs. In terms of the determinants of the conditional volatility of the ADRs returns, only shocks to the underlying markets are significant. These results are consistent with [Kim, M., Szakmary, A.C., Mathur, I., 2000. Price transmission dynamics between ADRs and their underlying foreign securities. Journal of Banking and Finance 24, 1359–1382] who find that the most influential factor in pricing the ADRs in Japan, UK, Sweden, The Netherlands and Australia is their underlying shares. Implications of the results for investors are discussed.     

Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying

In this study, we analyze the properties of Bitcoin as a diversifier asset and hedge asset against the movement of international market stock indices: S&P500 (US), STOXX50 (EU), NIKKEI (Japan), CSI300 (Shanghai), and HSI (Hong Kong). For this, we use several copula models: Gaussian, Student-t, Clayton, Gumbel, and Frank. The analysis period runs from August 18, 2011 to June 31, 2019. We found that the Gaussian and Student-t copulas are best at fitting the structure dependence between markets. Also, these copulas suggest that under normal market conditions, Bitcoin might act as a hedge asset against the stock price movements of all international markets analyzed. However, the dependence on the Shanghai and Hong Kong markets was somewhat higher. Also, under extreme market conditions, the role of Bitcoin might change from hedge to diversifier. In a time-varying copula analysis, given by the Student-t copula, we found that even under normal market conditions, for some markets, the role of Bitcoin as a hedge asset might fail on a high number of days.     

Investor legal protection and earnings management: A study of Chinese H-shares and Hong Kong shares

Under the unique “one country, two systems” arrangement, the more stringent investor protection rules in Hong Kong are not enforceable in firms that are incorporated in China but listed on the Hong Kong stock exchange (H-shares). As such, H-shares and other local Hong Kong firms are subject to different investor protection regimes in the same stock market. We find that H-shares are associated with higher earnings management than local Hong Kong firms after controlling for disparity in economic development, types of controlling shareholders and other factors. More importantly, this relationship is weaker after China implemented the Securities Law in 1999. The results are robust after considering the dual-listing status of H-shares and board characteristics. These results provide direct evidence showing the effect of investor legal protection on financial reporting quality.     

香港居民投资大陆市场的产品方案研究

扩展香港居民投资大陆市场的渠道是深化深港金融合作的重要内容。由于我国目前实行资本项目管制,香港居民不能直接投资大陆市场。目前,香港发行的A股ETF基金是香港居民投资大陆市场的主要渠道。本文考察了香港发行的A股ETF产品的发展现状、产品设计原理以及QFII制度对香港居民投资大陆产品发展的影响。在目前的QFII制度背景下,本文提出了人民币定价的A股ETF、香港和大陆基金互换、QHII制度等一系列循序渐进的产品和方案。     

Causality and cointegration of stock markets among the United States,Japan and the South China Growth Triangle

This paper explores the causality and cointegration relationships among the stock markets of the United States, Japan and the South China Growth Triangle (SCGT) region. Applying the recently advanced unit root and cointegration techniques that allow for structural breaks over the sample period (October 2, 1992 to June 30, 1997), we find that there exists no cointegration among these markets except for that between Shanghai and Shenzhen. By invoking the Granger causality test and considering the non-synchronous trading problem, we will show that stock price changes in the US have more impact on SCGT markets than do those of Japan. More specifically, price changes in the US can be used to predict those of the Hong Kong and Taiwan markets on next day. Similarly, price changes on the Hong Kong stock market lead the Taiwan market by 1 day. Furthermore, the stock returns of the US and Hong Kong markets are found to be contemporaneous. Finally, there is a significant feedback relationship between the Shanghai and the Shenzhen Stock Exchanges.     

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.     

Information Flows across Markets: Evidence from China–Backed Stocks Dual–Listed in Hong Kong and New York

Using a bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model, we examine patterns of information flows for China–backed stocks that are cross–listed on exchanges in Hong Kong and New York. Results analyzing the dual–listed stocks indicate significant mutual feedback of information between domestic (Hong Kong) and offshore (New York) markets in terms of pricing and volatility. Stocks listed on the domestic market appear to play a more significant role of information transmission in the pricing process, whereas stocks listed on the offshore market play a bigger role in volatility spillover.     

Choice of foreign listing location: Experience of Chinese firms

At the end of October 2003, there were 237 Chinese firms' listings on various stock exchanges outside of Mainland China. Beyond geographical proximity and other obvious explanations of why Chinese firms prefer listing in Hong Kong more than in the United States, we identify two additional benefits of a Hong Kong listing. We find that Chinese firms listed in Hong Kong have a better information environment than those listed solely in the United States. We also find that the Hong Kong-listed firms are less financially constrained, which may be due to their ability to access the Hong Kong capital market for external financing. The results of our study show that different stock markets offer different benefits as a listing venue and the benefits of foreign listing may depend on the choice of listing location.     

首次公开募股(IPO)市场表现及破发影响——基于港市中资股的经验证据

以在港上市中资股2013—2019年的数据为研究样本,首先,基于典型事件分析中资股在境外资本市场的整体表现;然后,采用多元回归模型实证检验破发、市场状况及投资者态度等因素对中资股市场表现的影响。研究结果表明：相较于恒生指数,港市中资股IPO上市后两年内的整体市场表现处于劣势;IPO破发不利于后期市场的表现,破发股的整体市场表现差于非破发股;投资者行为是市场表现的重要影响因素之一,投资者意见分歧会对中资股的市场表现产生正向影响;新股上市前的市场环境越好,中资股IPO上市后的市场表现会越好。     

Long-run equilibrium, short-term adjustment, and spillover effects across Chinese segmented stock markets and the Hong Kong stock market

This paper adopts a novel FIVECM-BEKK GARCH approach to examine the bilateral relationships among the A-share and B-share stock markets in China and the Hong Kong stock market. The evidence shows that these stock markets are fractionally cointegrated. Analyses of the spillover effects across these markets indicate that the A-share markets are most influential. The relaxation of government restrictions on the purchase of B shares by domestic residents accelerates the market integration process of A-share markets with the B-share and Hong Kong markets. The effects of the Asian crisis on the stock-return dynamic correlations vary across these markets.     

新闻驱动的量化投资

本文讨论了在香港股市中利用新闻软信息进行量化处理并进行统计套利的量化投资策略,提出了测量新闻消息作者情绪的统计学指数,以及测量新闻消息与证券的相关的统计学指数,以及新闻消息对相关证券影响方向（正、负面或者中性）的指数。本文证明在香港股票市场上存在着利用这些指数进行统计套利的机会。