摘要
用GM(1,1)预测具有良好的精确性和规律性,但对于随机波动性较大的股市行业,它的预测精度比较低,而马尔可夫模型可以克服波动性较大的局限性,弥补灰色模型的不足,因此将两者结合起来对股市进行预测将能提高预测的精度。本文依据上交所20个月末收盘指数预测后四个月的月末收盘指数范围。
Using GM（ 1,1 ）model to predict has great accuracy and regularity.But for the random high waving stock market, The accuracy is low. But Markov model can overcome the defection of high waving and make up the shortage of GM （ 1,1 ） model. 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 Shanghai Stock Exchange, the range of the index in the end of next four months was predicted. Empirical analysis shows that GM - Markov chain model is a feasible tool to predict the stock market.
出处
《价值工程》
2010年第24期255-256,共2页
Value Engineering
关键词
灰色预测模型
马尔可夫模型
月末上证收盘指数
预测
gray prediction
markov model
the index of shanghai stock exchange close in the end of month
predict
