Grey Markov model based on parameter fits and its application in stock price prediction

For uncertain and fluctuant system, a new kind of method-grey markov model based on parameter fits is put forward. This method synthesizes the advantages of GM forecasting method, which is simple and needs less original data, and of markov method which possesses the characteristics of nonlinear fitting. At last, the presented method is used to build model of the stock price, and the results are much better. The precision of model is up to 99%, and the practical application results show the effectiveness of the proposed approach. It is proved that the method is concise, useful and reliable. So the method can widen range of application of grey model.