Based on 5-minute high-frequency trading data, we examine the time-varying causal relationship between herding behavior and multiscale spillovers (return, volatility, skewness, and kurtosis) in the Chinese stock market. We employ the novel time-varying Granger causality test proposed by Shi et al. (2018), which is based on the recursive evolving algorithm developed by Phillips et al. (2015a, 2015b), to identify real-time causal relationships and capture possible changes in the causal direction. Our findings reveal a strong relationship between herding and spillover effects, particularly with odd-moment (return and skewness) spillovers. For most of the study period, a bidirectional causal relationship was found between herding and odd-moment spillovers. These results imply that herding behavior is a key driver of spillover effects, especially return and skewness spillovers, which are primarily transmitted through the information channel. By contrast, volatility and kurtosis spillovers are more strongly driven by real and financial linkages. Furthermore, spillover effects also affect herding behavior, highlighting the intricate feedback loop between investor behavior and risk transmission.

This paper examines the different responses of local and foreign investors to host government risk perceptions in the context of extreme events. We develop COVID-19 attention indices that capture attention related to COVID-19 according to China Central Television (CCTV) news program and further construct the government’s risk perception (GRPC) measure about COVID-19. Given the cross-listed AH-shares in China, we find that GRPC caused the extreme movement of stock markets by applying the multi-quantile VaR Granger causality approach. The results show that the reaction of cross-listed stocks in the A-share market is more inflexible than that in the H-share market during the outbreak period of the pandemic, foreign investors follow GRPC as a weather vane than local investors, and both types of investors are more concerned about the pessimism of GRPC. In the period of epidemic normalization, local and foreign investors prefer the optimistic attitude conveyed by the Chinese government.

The COVID-19 pandemic has inflicted substantial impacts on global financial markets and the economy. This study explores the impact of two pandemic outbreaks in China on its stock market industries. It employs the Conditional Autoregressive Value at Risk (CAViaR) model to compute tail risks across 16 selected industry sectors. Additionally, risk correlation networks are constructed to illustrate the risk correlations among industry sectors during different phases of the two outbreaks. Furthermore, risk contagion networks are built based on the Granger causality test to examine the similarities and differences in the contagion mechanisms between the two outbreaks. The findings of this study show that (i) the two outbreaks of COVID-19 have resulted in tail risks for most industries in the Chinese stock market. (ii) The risk correlation network became more compact because of both outbreaks. The impact of the second outbreak on the network was less severe than that of the first outbreak. (iii) During the first outbreak of COVID-19, the financial industry was the primary source of risk output; during the second outbreak, the concentrated outbreak in Shanghai led the industries closely related to the city's economy and trade to become the most significant risk industries. These findings have practical implications for researchers and decision-makers in terms of risk contagion among stock market industries under major public emergencies.

Using annual time series data (1978-2010), the present paper examines the nexus between financial intermediation development and economic fluctuation in China. The time series properties of the data are analyzed by bounds testing approach, ARDL model and vector error-correction model. The empirical results show that, there is long-term negative equilibrium relationship between financial intermediation development and economic fluctuation margin. However, although the short-term dynamics of volatility in economy growth can make adjustments in light of the long-term equilibrium relationship, it is not enough for economic fluctuation margin to revert to the equilibrium only through the error correction mechanism. Meanwhile, using the Granger causality test based on error correction model, the present paper finds the empirical evidence to support unidirectional Granger causality from financial intermediation development to economic fluctuation margin.

This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen’s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ‘irrational’ and ‘speculative’. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China’s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen’s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ‘irrational’ and ‘speculative’. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China’s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen’s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ‘irrational’ and ‘speculative’. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China’s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

This paper investigates the dynamic and long-run relationships between monetary policy and asset prices in China using monthly data from June 2005 to September 2010. Johansen?s cointegration approach based on vector autoregression (VAR) and Granger causality test are used to identify the long-run relationships and directions of causality between asset prices and monetary variables. Empirical results show that monetary policies have little immediate effect on asset prices, suggesting that Chinese investors may be ?irrational? and ?speculative?. Instead of running away from the market, investors rush to buy houses or shares whenever tightening monetary actions are taken. Such seemingly irrational and speculative behavior can be explained by various social and economic factors, including lack of investment channels, market imperfections, cultural traditions, urbanization and demographic changes. The results have two important policy implications. First, China?s central bank has not used and should not use interest rate alone to maintain macro-economic stability. Second, both monetary and non-monetary policies should be deployed when asset bubbles loom large to avoid devastating consequences when they burst.

The debate among various market partic-ipants on the short-selling of securities continues today. Opponents of short-selling argue that it disrupts orderly mar-kets by causing panic selling, high vola-tility, and market crashes. So this paper investigates what the impact of short sell-ing on the volatility and liquidity of Hong Kong stock market is, and the results in-dicate that short selling volumes do not Granger-cause market volatility, but volatility Granger-cause short selling volumes. Moreover Granger causality tests show that there is a double direc-tional causality relationship between short selling volumes and market liquidity.

In this paper, we pay attention to the relationship between stock index and increments of trading accounts in A, B share market and funds. We show that there exists bilateral relationship between A, B index and their trading accounts increments. However, Granger causality only exists from stock index to increments of funds accounts. Regressions show that the investors’ sentiment will be easily driven by the index in the same direction, which imply momentum strategy in a very short period. In comparison, when using weekly data, only increments of funds accounts Granger cause the stock index. These uncover the differences between fund managers and small investors while investing on stock market. We also analyse the relationship between index volatility and trading accounts volatility.