Return spread and liquidity: Evidence from Hong Kong ADRs

Fifteen Chinese H-shares listed on the Stock Exchange of Hong Kong are cross listed as ADRs on the NYSE. We empirically determine the role of security specific liquidity associated with those ADRs and their underlying H-shares on return spreads, differences between the returns on ADRs and their corresponding H-shares after controlling for ADRs and H-shares excess market returns and their respective price inverses denoting conditional betas. We use three proxies for liquidity, trading volume, turnover, and illiquidity (Amihud, 2002) and find that only trading volume and turnover are consistent determinants of return spread for the majority of Chinese ADRs with primary listing in Hong Kong Stock Exchange (SEHK). We use a switching regression model and find that the model parameter estimates are not stationary and change, often drastically between pre and post 2000 and 2003. Further tests using Bai Perron indicate return spreads data as non-stationary with multiple regime changes during the sample period. Further the causes of non-stationarity seem to be largely security specific and not driven by broad market swings in either market.     

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.     

Day and night returns of Chinese ADRs

Are the returns of Chinese American Depositary Receipts (ADR) more affected by the US market or their underlying home market? We separate Chinese ADR daily returns into day and night returns to investigate the different market effects on ADR pricing. We compare “homeless” ADRs to home-based or cross-listed ADRs to see if they are affected differently by market factors. We find the night returns of Chinese ADRs are significantly affected by their home market (either the Hong Kong market or mainland China market) daily returns and the US market night returns. The US day returns appear to be the most significant pricing factor for the day returns of Chinese ADRs. The homeless ADRs are more affected by the US market and less affected by their home market compared to the cross-listed ADRs.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

A behavioural explanation to the asymmetric volatility phenomenon: Evidence from market volatility index

This study examines how the behavioural explanations, in particular loss aversion, can be used to explain the asymmetric volatility phenomenon by investigating the relationship between stock market returns and changes in investor perceptions of risk measured by the volatility index. We study the behaviour of India volatility index vis‐à‐vis Hong Kong, Australia and UK volatility index, and provide a comprehensive comparative analysis. Using Bai‐Perron test, we identify structural breaks and volatility regimes in the time series of volatility index, and investigate the volatility index‐return relation during high, medium and low volatility periods. Regardless of volatility regimes, we find that volatility index moves in opposite direction in response to stock index returns, and contemporaneous return is the most dominating across the four markets. The negative relation is strongest for UK followed by Australia, Hong Kong and India. Second, volatility index reacts significantly different to positive and negative returns; negative return has higher impact on changes in volatility index than positive return across the markets over full‐sample and sub‐sample periods. The asymmetric effect is stronger in low volatility regime than in high and medium volatility periods for all the markets except UK. The strength of asymmetric effect is strongest for Hong Kong and weakest for India. Finally, negative returns have exponentially increasing effect and positive returns have exponentially decreasing effect on the changes in volatility index.     

Linkages between Indian and US financial markets: impact of global financial crisis and Eurozone debt crisis

This paper examines inter-linkages between Indian and US equity, foreign exchange and money markets using the vector autoregressive-multivariate GARCH-BEKK framework. We investigate the impact of global financial crisis (GFC) and Eurozone debt crisis (EZDC) on the conditional volatility and conditional correlation estimates derived from the multivariate GARCH model for Indian and US financial markets. Our results indicate that there is significant bidirectional causality-in-mean between the Indian stock market returns and the Rs./USD market returns, and significant unidirectional causality-in-mean from the US stock market returns to the Indian stock market returns. As regards volatility spillovers, we find that volatility in the Indian stock market rises in response to domestic as well as US financial market shocks but Indian financial market shocks do not impact the US markets. Further, impact of the recent crisis episodes on the covariance matrix is found to be significant. We find that volatility in the Indian and US financial markets significantly amplified during GFC. The conditional correlations across asset markets were significantly accentuated in the wake of the two crisis episodes. The impact of GFC on cross-market conditional correlations is higher for majority of the asset market pairs in comparison to the EZDC.     

MEAN AND VOLATILITY SPILLOVERS ACROSS MAJOR NATIONAL STOCK MARKETS: FURTHER EMPIRICAL EVIDENCE

This paper provides additional insight into the nature and degree of interdependence of stock markets of the United States, Japan, the United Kingdom, Canada, and Germany, and it reports the extent to which volatility in these markets influences expected returns. The analysis uses the multivariate GARCH-M model. Although they are considered weak, statistically significant mean spillovers radiate from stock markets of the U.S. to the U.K., Canada, and Germany, and then from the stock markets of Japan to Germany. No relation is found between conditional market volatility and expected returns. Strong time-varying conditional volatility exists in the return series of all markets. The own-volatility spillovers in the U.K. and Canadian markets are insignificant, supporting the view that conditional volatility of returns in these markets is “imported” from abroad, specifically from the U.S. Significant volatility spillovers radiate from the U.S. stock market to all four stock markets, from the U.K. stock market to the Canadian stock market, and from the German stock market to the Japanese stock market. The results are robust and no changes occur in the correlation structure of returns over time.     

The Political Economy of Volatility Dynamics in the Hong Kong Stock Market

Despite its obvious importance, little empirical research has examined the impact of political risk on stock market volatility. This paper uses data on the Hong Kong stock market over a long sample period to investigate whether political risk has induced regime shifts in stock market volatility. Regime shifts are modelled via a Markov switching EGARCH model that allows for regime-dependent volatility asymmetry. We find strong evidence of regime shifts in conditional volatility as well as significant volatility asymmetry in high volatility periods. Major political uncertainties were reflected in a switch to the high-volatility regime. However, contrary to popular perceptions, we find no evidence that the Hong Kong stock market has become persistently more volatile since the start of Sino-British political negotiations in 1982.     

Disruption and stock markets: Evidence from Hong Kong

We examine the impact of disruption on stock markets using the 2019 Hong Kong protests for identification. We find that greater protest intensity corresponds to higher bid–ask spreads, lower trading volume, and greater return volatility for dual-listed Chinese firms’ Hong Kong (H) shares but not their home (A) shares. We also document negative abnormal returns only for these firms’ H-shares around major protest events, which shortly after exhibit reversal. Next, we validate our main findings by documenting similar results using Hong Kong-listed firms only. Overall, we provide new evidence highlighting the impact of protest-induced disruption on financial markets.     

Lost in translation: Delayed ex-dividend price adjustments of Hong Kong ADRs

Previous research documents that Hong Kong stocks have a full ex-dividend price adjustment consistent with dividends and capital gains being tax free. We examine ex-dividend price behavior of Hong Kong ADRs to assess the impact of differing tax environments in US and Hong Kong. These ADRs typically go ex-dividend before their underlying stock. They experience significant abnormal returns of 1.16% on their ex-day; the average ex-day price drop is only 30% of the dividend. However, ADR prices drop when the underlying stock goes ex-dividend subsequently. The cumulative ADR price drop is equal to the dividend. Thus, the ADR ex-dividend adjustment resembles that of the underlying stock, consistent with home country tax laws governing ADR price behavior. Neither liquidity nor transaction costs can explain the anomalous delayed ex-dividend adjustment of ADRs.     

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.     

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.     

The Effect of US Stock Market Uncertainty on Emerging Market Returns

We investigate the effects of US stock market uncertainty (VIX) on the stock returns in Latin America and aggregate emerging markets before, during, and after the financial crisis. We find that increases in VIX lead to significant immediate and delayed declines in emerging market returns in all periods. However, changes in VIX explained a greater percentage of changes in emerging market returns during the financial crisis than in other periods. The higher US stock market uncertainty exerts a much stronger depressing effect on emerging market returns than their own-lagged and regional returns. Our risk transmission model suggests that a heightened US stock market uncertainty lowers emerging market returns by both reducing the mean returns and raising the variance of returns. The VIX fears raise the volatility of emerging market returns through generalized autoregressive conditional heteroskedasticity (GARCH)-type volatility transmission processes.     

The Dynamics of Financial Market Integration Between Chinese A- and H-Shares

This study examines the dynamics and underlying determinants of integration based on cross-listed Chinese A-shares and Hong Kong H-shares from January 1996 to December 2016. We focus mainly on three liberalization reforms: the qualified foreign institutional investors (QFII) policy, the qualified domestic institutional investors (QDII) policy, and the Shanghai-Hong Kong Stock Connect program. Our results show that the QDII policy has significantly increased the integration between the Mainland China and Hong Kong stock markets, although the extent to which any stock has been affected is partly dependent upon certain firm-specific characteristics, including liquidity, market value, and volatility. However, we do not document the similar effect of the QFII policy and the Shanghai-Hong Kong Stock Connect program on the integration dynamics.     

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.     

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.     

Common stochastic trends and volatility in Asian-Pacific equity markets

This paper uses Johansen's cointegration test and a modified cointegration test with generalized autoregressive conditional heteroskedasticity (GARCH) effects to examine linkages between the U.S. and five Asian-Pacific stock markets (Australia, Hong Kong, Japan, Malaysia, and Singapore) during the period from 1988 to 1994. The modified cointegration test with GARCH effects is used to assess whether these stock price series share common time-varying volatility. The results indicate that the six stock markets are highly integrated through the second moments of stock returns but not the first moments.     

Granger-causality in quantiles between financial markets: Using copula approach

This paper considers the Granger-causality in conditional quantile and examines the potential of improving conditional quantile forecasting by accounting for such a causal relationship between financial markets. We consider Granger-causality in distributions by testing whether the copula function of a pair of two financial markets is the independent copula. Among returns on stock markets in the US, Japan and U.K., we find significant Granger-causality in distribution. For a pair of the financial markets where the dependent (conditional) copula is found, we invert the conditional copula to obtain the conditional quantiles. Dependence between returns of two financial markets is modeled using a parametric copula. Different copula functions are compared to test for Granger-causality in distribution and in quantiles. We find significant Granger-causality in the different quantiles of the conditional distributions between foreign stock markets and the US stock market. Granger-causality from foreign stock markets to the US stock market is more significant from UK than from Japan, while causality from the US stock market to UK and Japan stock markets is almost equally significant.     

Common Volatility: An Empirical Investigation of Closed-End Country Funds

The study of international integration of equity markets has received a great deal of interest. This paper investigates whether returns of forty-one closed-end country funds share a common volatility process with three comparable return series: the underlying net asset value (NAV), U.S. stock market returns, and foreign stock market returns. Country funds are a natural setting to test for international market integration, as they are traded in the U.S. market, whereas their underlying assets are traded in foreign stock markets. Our results indicate that only a few emerging markets' country funds share common volatility processes with their comparable asset returns. This, in turn, suggests weak linkages through the second moment of related assets.     

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.