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.     

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.     

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.     

金融中心评价指标体系研究

本文在综述国内外关于金融中心评价指标体系的基础上,分析了影响金融中心形成和运行的因素,依据国际金融中心的形成和运行具有较高相关度的原则,构建了包括经济环境、金融市场、金融机构和金融制度四方面内容的评价指标体系,利用2004年东京、新加坡、香港、北京、上海、广州和深圳七个城市的数据,依据层次聚类分析方法对这些城市所处的层次进行定位:北京、广州和深圳成为一类,为金融中心的初级阶段;上海成为第二类,为国内金融中心阶段;香港和新加坡成为一类,是区域国际金融中心;东京处于最高阶段,是真正的国际金融中心.最后对这些城市的发展前景进行了预测.     

基于MF-DCCA方法的证券市场间交叉相关性研究

运用多重分形去趋势波动交叉相关分析法(MF-DCCA),考量上海证券市场和香港证券市场之间的交叉相关关系。实证表明：上海证券市场和香港证券市场之间存在交叉相关性,且呈现出多重分形特征;当证券市场出现较大的波动时,上海证券市场和香港证券市场的交叉标度指数要大于其平均标度指数,即两个证券市场之间的交叉相关性要大于其自相关性。     

Nonlinear interdependence of the Chinese stock markets

The methodologies and assumptions in financial integration studies are problematic and may lead to spurious empirical results. Using surrogate data analysis and the mutual prediction method of testing for nonlinear interdependence, it is feasible for an analyst, with a scant knowledge of the underlying dynamics of two dynamical systems, to show whether or not the systems are interdependent. This study applies these techniques in testing for nonlinear interdependence of three Chinese stock markets: Shanghai, Shenzhen, and Hong Kong. The empirical results of the present study indicate that the stock market series are nonlinear and that the Chinese stock exchanges are nonlinearly interdependent. Specifically, the evidence indicates that Shanghai and Shenzhen markets are bi-directionally interdependent, while Shanghai and Hong Kong as well as Shenzhen and Hong Kong markets are unidirectionally interdependent, with the direction of interdependence going from the mainland's markets to the Hong Kong market.     

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。     

Do zero-cost portfolios have the ability to predict economic growth? Evidence from Hong Kong, South Korea and Taiwan

In this paper we investigate the relationship between growth in future Gross Domestic Product (GDP) and Industrial Production (IDP) and the performance of SMB (small stocks minus big stocks) and HML (High book-to-market stocks minus low book-to-market stocks) portfolios for equities listed in Hong Kong, South Korea and Taiwan.We find evidence to suggest that: (a) the excess market return is positively related to future GDP or IDP growth in South Korea and Taiwan; (b) contrary to most European markets, Australia, Japan and the US, future economic growth is in general significantly negatively related to SMB in Hong Kong and South Korea; and, (c) a negative relationship between future economic growth and HML for Hong Kong. Our results cast doubt if SMB and HML portfolios are positive risk factors in the Fama and French (Fama, E. F., and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3-56) three-factor asset pricing model for Hong Kong, South Korea and Taiwan.     

中国城市网络结构及空间关联性 ——来自"网络流"数据的分析

基于中国城市之间的关联特征和溢出效应,将人力资本变量纳入引力模型,运用社会网络分析和机器学习方法并依据主要节点城市的有向数据,考量城市网络结构及其关联性.结果显示:新引力模型可有效衡量样本城市的网络关联效应,金融状况、港口距离和高等教育资源丰裕度是决定城市引力流量重要原因,政府干预对城市引力流作用不明显;城市空间分布呈现明显的四级分层特征,但从人力资本对城市引力流影响看,作为中心城市的广州和深圳在网络拓扑中心的稳定性相对较弱.     

基于空间关联性的广深金融服务业集群研究——珠三角经济区域背景下的考察

自2000年以来,以广州、深圳为代表的珠三角各大城市先后出现了不同程度的金融服务业集群,本文利用区位熵、Moran＇s I等指数来考察该区域内各大城市之间的区域外溢性及存在的空间关联,以进一步揭示广州、深圳两大中心城市在金融服务业集群过程中基于空间自相关性的空间依赖和空间异质。结果表明：珠三角9大城市在集群过程中各自与周边地区的关联程度不一,存在着4种不同的情形,而广州、深圳的空间关联性则更多的体现为空间依赖上的异质性。     

The unsung impact of currency risk on the performance of international real property investment

The paper revisits the currency risk debate to ascertain the statistical significance of currency risk on the return of international real property investment, especially in a period of increased exchange rate volatility. After statistical analyses of the returns of a portfolio of office investments in seven Asia Pacific cities over the 1986 to 2007 period, it was found that currency risk had a statistically significant positive impact on the performance of the portfolio of office investments. This is confirmed by the results of stochastic dominance test. If the results of this study are verified by subsequent studies, and the past reliably presages the future, they would imply that investors holding portfolios of real property investments in the sample markets might not need to be unduly concerned with currency risk.     

香港公司如何在内地找到自己的位置?

<正> 罗康瑞:香港公司自中国内地改革开放之初进入内地市场,到现在已有20多年的经验。在企业的运作当中,许多跨国公司通常需要几个月时间才能做出决策,而香港的小投资者却能够科学迅速地决策,从而抢占商机,迅速得到发展。在进行投资时,要尽量了解所投资国家或地区的系统、环境、机制,只有这样才能认清客观情况,利用客观条件,使自己得到顺利发展。在中国的建材、房地产领域,欧洲企业、美国企业都尝试进行投资,但他们没成功。相     

The bivariate GARCH approach to investigating the relation between stock returns,trading volume,and return volatility

We use a bivariate GJR-GARCH model to investigate simultaneously the contemporaneous and causal relations between trading volume and stock returns and the causal relation between trading volume and return volatility in a one-step estimation procedure, which leads to the more efficient estimates and is more consistent with finance theory. We apply our approach to ten Asian stock markets: Hong Kong, Japan, Korea, Singapore, Taiwan, China, Indonesia, Malaysia, the Philippines, and Thailand. Our major findings are as follows. First, the contemporaneous relation between stock returns and trading volume and the causal relation from stock returns and trading volume are significant and robust across all sample stock markets. Second, there is a positive bi-directional causality between stock returns and trading volume in Taiwan and China and that between trading volume and return volatility in Japan, Korea, Singapore, and Taiwan. Third, there exists a positive contemporaneous relation between trading volume and return volatility in Hong Kong, Korea, Singapore, China, Indonesia, and Thailand, but a negative one in Japan and Taiwan. Fourth, we find a significant asymmetric effect on return and volume volatilities in all sample countries and in Korea and Thailand, respectively.     

What Drives Housing Markets: Fundamentals or Bubbles?

This study applies the dynamic Gordon growth model which is in the circumstance of rational bubbles to decompose log price-rent ratio into three parts, i.e., rational bubbles, discounted expected future rent growth rates and discounted expected future returns. The latter two terms represent housing fundamentals. The magnitudes of the components of price-rent ratio’s variance are estimated to distinguish the relative impact of the three parts on housing prices. Using time series data from the housing markets in the four largest cities in China (1991:Q1–2011:Q1 for Shanghai, Guangzhou and Shenzhen; 1993:Q2–2011:Q1 for Beijing), this paper presents a number of empirical findings: (a) the variance of rational bubbles is much larger than the variance of price-rent ratio, and rational bubbles contribute more fluctuations directly to price-rent ratio than the expected returns or the expected rent growth rates do; (b) the covariance between rational bubbles and expected returns or expected rent growth rates is also large; (c) the positive covariance of rational bubbles and expected returns implies that high expected returns coexist with bubbles, which differs from previous findings that lower expected returns drive asset prices; (d) the negative covariance of rational bubbles and expected rent growth rates indicates that the larger the bubbles are, the lower the expected rent growth rates are; (e) the positive covariance of expected returns and expected rent growth rates reveals under-reaction of the housing markets to rents.     

Separating the Age Effect from a Repeat Sales Index: Land and Structure Decomposition

Since real estate is heterogeneous and not all its quality attributes are observable, the repeat sales model pioneered by Bailey et al. (1963) has become one of the standard methods to estimate a constant-quality price index. The model, however, fails to adjust for depreciation, as age and time between sales have an exact linear relationship. This paper proposes a new method to estimate an age-adjusted repeat sales index by decomposing property value into land and structure components. As depreciation is more relevant to the structure than land, the property’s depreciation rate should depend on the relative size of land and structure. The larger the land component, the lower the depreciation rate of the property. This new method is applied to property transactions in Hong Kong and Tokyo. Hong Kong is shown to have a higher depreciation rate based on a fixed structure-to-property value ratio, while the resulting age adjustment is larger in Tokyo because its land value has shrunken over time.     

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.     

Bank lending and property prices in Hong Kong

This paper studies the relationship between residential property prices and bank lending in Hong Kong. This is an interesting topic for three reasons. First, swings in property prices have been extremely large and frequent in Hong Kong. Second, under the currency board regime, monetary policy cannot be used to guard against asset price swings. Third, despite the collapse in property prices since 1998, the banking sector remains sound. While the contemporaneous correlation between lending and property prices is large, our results suggest that the direction of influence goes from property prices to bank credit rather than conversely.     

ROBUSTNESS OF THE HEADQUARTERS‐CITY EFFECT ON STOCK RETURNS

Recent studies report that U.S. firms headquartered near each other experience positive comovement in their stock returns, a finding suggestive of local biases in equity trading activity. We investigate the robustness of these findings and find that including additional pricing factors in models for monthly stock returns materially reduces the magnitude of the headquarters‐city effect in stock returns. Additionally, we find that an implicit null hypothesis of zero local return comovement is inappropriate as there is positive comovement between a stock's return and returns on portfolios of stocks from nonheadquarters cities, on average. Nevertheless, results benchmarked against estimates based on resampling methods indicate a significant and robust headquarters‐city effect in stock returns.     

Interactions among China-Related Stocks

This paper explores the issue of causalities among five different indices of shares issued by Chinese firms, A and B Shares listed in the Shenzhen and Shanghai Stock Exchanges, and H Shares listed in the Stock Exchange of Hong Kong. By measuring cross autocorrelations and conducting Granger causality tests, we found that the causality relationships among the five different indices went through significant changes after early 1996; B Shares became more influential relative to the other shares. B Shares in China have tended to lead H Shares in Hong Kong since 1996. Although A Shares tended to lead B Shares before 1996, such relationships either disappeared or were reversed after 1996.