An International Comparative Analysis Of The Correlation Of Stock Index Returns Based On Quantile Regression

In order to study the autocorrelation features of stock yield sequence,we select the representative index in Shanghai,Shenzhen and the G7 group's stock market as the research objects, based on the quantile regression idea and the BIC criteria,established nine quantile autoregression models for analyse.At the same time,we add a new variable trading volume in the above-mentioned models,and taking the logarithm.Regression results show that the lag period returns and trading volume is not always a significant influence on current yield.The regression coefficients changed in different quantile,there are both positive and negative values,it explained that in different quantiles on the lag period returns and trading volume is difference to the influence degree of the current earnings.In a significant interval,the lag period returns and trading volume on the current yield both have positive effects and negative effects.In the G7,the lag period yields regression coefficients with the increase of the quantile showed a trend of decline,on the contrary,the volume regression coefficients with the increase of the quantile showed a trend of growth.But in Shanghai and Shenzhen stock morkets,the effect of lag returns and trading volume on the current yield have no rules to follow.The regression results also show that,for the fat-tailed financial data,quantile regression can better describe the distribution of the local characteristics than ordinary least-squares regression.