The Combined Analysis And Prediction Of Markov Chain And Time Series Model On Shanghai Stock Index

Markov chain prediction method has been attached importance in China when China's stock markets established. The time series technology is an important tool in study of stock market and it has been taken on it long time. This paper introduces the Markov chain and the traditional time series models, not only their application but also a new model called time series--Markov chain (TSMC) method. Then we apply it on the stock market, and achieve a contentment result. After study, we come to some valuable conclusions.These are the primary contents of this paper:First, we apply Markov chain on the stock index and predict its tendency and gain some right results.Second, we observe the stock yield distribution graph,histogram and some basic statistics data and conclude that the stock returns of our country are non-Gaussian and have volatility clustering phenomenon.Third, traditional time series models are used to analyze China stock market. Models ARMA is fitted stock returns. The study results are fitted together with the owned conclusions.Fourth, we combine the upper two model and apply TSMC method on prediction stock index, and predict the continue five weeks stock yield, and come to a good effect and some valuable conclusions.