The Impact Of Overnight Information On The Stock Returns And Volatility Based On SV Model

With the development of economic integration and financial globalization, financial markets around the world contact more and more closely, and the response of global macroeconomic information is becoming more and more consistent. It is also because of the existence of the system of globalization makes any information of financial price volatility to be able to quickly and effectively spread in the global capital markets. Although the degree of market reaction to this kind of information is different, any market could not ignore the existence of the outside information. Europe and the United States and the stock market in mainland China can’t keep the same trading speed because of the jet lag. China stock market as an emerging market, how to reduce the intense price fluctuation in the market has been the regulators, academic researchers and investors’ concerns. As a member in the system of economic globalization, China’s stock markets receive the influence of the main international markets more and more.Based on the background of China’s stock market, the overnight information in stock market returns and volatility is studied. Firstly we compare the two kinds of typical financial model, and select the SV model based on T distribution, and add the lagged income items and overnight information items into the mean equation and volatility equation of the SV model, classifying information overnight and introducing the asymmetric volatility to the volatility equation. Under China’s economy, we select the Shanghai and Shenzhen index as the research data, using MCMC method to estimate the model, and test three hypotheses proposed in this paper according to the estimation results.The conclusions of this paper include:first, the SV model based on the T distribution can better depict the characteristic of financial time series; Second, daytime and overnight gains are two different sources of data, and overnight information has certain prediction ability on the daytime returns and volatility, classifying the overnight information is necessary; Third, without considering the length of the overnight information, different types of overnight information have different ability to predict and classifying overnight information is necessary; Fourth, There exists leverage effect in the stock market, which differs from the daytime information and overnight information. For daytime information, the negative impact would cause greater volatility, and both the positive and the negative impact can be able to increase volatility. For overnight information, as the market and the overnight information differ, the overnight information has different influence on daytime volatility.