灰色—马尔可夫链模型在股市预测中的应用

Based on gray prediction model and Markov chain prediction theory, gray prediction model is combined with Markov chain-state transition and the theory of gray-Markov chain prediction model is expounded and applied to the prediction of stock market. Using GM(1,1) model to predict has good accuracy and regularity, but to the stock market with large random fluctuation, its accuracy is lower. Markov model can overcome this defection, so combining GM(1,1) with Markov chain model to predict stock market can improve the precision of prediction. Based on the indexes ended in the twenty months in Shenzhen Stock Exchange , the range of the index in the end of next four months was predicted, and example is given to prove its reliability in the application in the prediction of stock market.