Volatility Prediction Research In Chinese Stock Market With Range

Stock market volatility is the most basic characteristics. If the price is constant, there would be Bid-ask spread, and eventually there would be no deal. However as the stock market stability and the validity decide to achieve maximizing the utility to investors, high volatility will set an adverse effect on the health of the operation the stock market. In a large number of domestic volatility studies, we found that numerous studies used the rate of return to measure volatility, but without using the range to measure volatility of the stock market. At the same time, the market volatility forecasting accuracy of existing models is unsatisfactory, and they needs to be improved, especially domestic studies rarely use AV model to measure the market volatility. Some study overseas showed that the AV model to describe the volatility in the use of the existing models is more accurate, and the domestic researches on these aspects are seldom.This paper uses GARCH model and AV model based on the range to measure the prediction of market volatility, and explores the asymmetry in our stock market volatility. Firstly through the statistic analysis of the yields and range, this paper analyzes the characteristics and the status quo of the volatility of the market. Secondly, using GARCH model and AV model respectively based on the return and the range, this paper builds simulation and analysis of China’s Shanghai market volatility forecast and gets the volatility index and the prediction model which is suitable for China’s Shanghai market. Finally, using EGARCH model and AV-α model respectively based on the return and the range, this paper builds simulation and analysis of China’s Shanghai market asymmetric, validates China’s Shanghai market whether there is asymmetrical. And getting the following conclusions:this paper thinks that the Shanghai market share price has the obvious peak thick tail sex, and is biased; it was found that the range to measure the volatility of the Chinese securities market is more accurate than the traditional return index. Meanwhile, in the process of analysis this paper discovered in the volatility of the traditional forecasting GARCH model and no AV model for China securities market volatility of accurate prediction. Through the empirical results of the asymmetry, it also found the range is more accurate than the traditional index yields. And, in the two model, the empirical results found that China’s securities market exists asymmetry, and got negative news (bad news) make more impact to the China securities than positive messages (good news).