This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three ...This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments （GMM） to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.展开更多
This paper introduces the disposition effect into asset pricing process, and sets dynamic equilibrium model on which we can discuss the pattern of risk assets＇ returns. On base of theory results, we use data of China...This paper introduces the disposition effect into asset pricing process, and sets dynamic equilibrium model on which we can discuss the pattern of risk assets＇ returns. On base of theory results, we use data of China stock market to analyze the influence of disposition effect on stock return. The empirical study result confirms the disposition effect＇s existence in China stock market and it does affect the stock return.展开更多
文摘This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments （GMM） to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.
文摘This paper introduces the disposition effect into asset pricing process, and sets dynamic equilibrium model on which we can discuss the pattern of risk assets＇ returns. On base of theory results, we use data of China stock market to analyze the influence of disposition effect on stock return. The empirical study result confirms the disposition effect＇s existence in China stock market and it does affect the stock return.
