Based On The Arch Model Of Stock Market Empirical Research

In economic field, the time series models are important methods in describing and forecasting the objective economic process. However, when put them into application, because of the particularity of economic field, we often encounter many difficulties in the time series models analysis by using the traditional frequency statistical method. Therefore, this paper describes a technique, economic analyzes with ARCH time series models, which has proved over the past several years to be an attractive alternative in many situations to the use of traditional econometric models or other time series techniques.The time series technology is an important tool in study of stock market. After study, we come to some valuable conclusions. Time series from stock exchange has the following characteristics. First, it appears to be a random walk but may be not totally random. Second, it is easily and almost costless available. Time series method is a newly-developed quantitative method for yields satisfactory results in the analysis of economic time series in which the involved factors are too many and the relationships between them are too complicated, leading to the application of theory-based quantitative predicting methods unworkable.In this essay, firstly the author introduces the theory of time series models, and then analyzes the predictability of time series from China's stock exchange using the ARCH model and gives evaluation on their performances while at the same time puts forward some conclusions deserving attention from both stock exchange supervising department and stock traders. Secondly, the author examines the assumptions closely on which the above-said methods base and gives a detailed discussion on them, especially using GARCH model to test quantitatively the stability of China's stock exchange, afterwards drawing the conclusion that it is hard to make accurate prediction of price or return rate of China's stocks for none of the assumptions fully holds ground. Thirdly, taking account of the difference between Chinese stock traders as a whole and that of developed countries, the author gives a thorough analysis on the complexity and volatility of its (traders') reaction to information and points out that the intrinsic heterogeneous and volatile reaction to information is an important reason for the almost unpredictability of the price or return rate in China's stock exchange. Given that individual dominated situation in China's stock exchange will last for a long time, it is of great importance to integrate behavioral financial theory into the quantitative research on the time series from China's stock exchange. Finally, the author points out the drawbacks of phenomenon-based predicting and presents an outlook on the direction of the analysis of time series from China's stock exchange in view of the difference between theory-based analysis and phenomenon-based analysis.