含马氏链的股票指数模糊随机预测模型

A new stock index fuzzy stochastic prediction model developed by introducing a Markov chain

为了获得更加准确和更加值得信赖的股票指数预测结果,依据股票指数的模糊随机预测模型,通过引入马尔可夫链的概念和股票指数上涨或下跌的转移概率,改进了股票指数的模糊随机预测模型中的预测参数.在以2009年全年的每日60 min沪深300指数为样本的实证研究中,采用了原模糊随机预测模型和改进了预测参数后的模糊随机预测模型分别进行预测,改进后的模型预测出的结果比原模型预测的结果更加接近沪深300指数的真实走势.研究结果表明:通过引入马尔可夫链和转移概率对预测参数进行的改进,提高了模糊随机预测模型对股票指数的预测精度.

With the aim of acquiring more accurate and reliable stock index forecasting results,this paper introduced the concept of a Markov chain and the transition probability on rise or fall of stock index into the fuzzy stochastic predicted model to improve the predicted parameters.In the practical study by applying the 2009 full-year HS300 stock index（60 minutes in every day） as specimen,the original fuzzy stochastic predicted model and the fuzzy stochastic predicted model with improved predicted parameters were used.This empirical study shows that the predicted results of the improved model are closer to real HS300 stock indexes than the original model.The study shows that this method,which introduces the Markov chain and transition probability into the predicted model,makes the predicted parameters of the fuzzy stochastic predicted model more effective than before.