摘要
模型假设股票价格变化满足齐次马氏性,并具有涨跌两种状态,初始概率的分布是平稳分布,建立了相应的模型,给出了模型中未知参数的极大似然估计,并将模型应用于确定上证综合指数、深证成指及个股的涨跌趋势,得到了令人满意的结果.
We assume that the changing of the stock price down states, initial probability is stationary. Then we build is the homogeneous Markov chain, there are up and mathematical model and give the maximum likehood estimators of the unknown parameter in the model. At last, we apply this model to analyze the index of Shanghai and Shenzhen and changing of one of stocks, obtain satisfactory results.
出处
《昆明理工大学学报（理工版）》
CAS
北大核心
2009年第6期116-118,共3页
Journal of Kunming University of Science and Technology(Natural Science Edition)
基金
教育部"春晖计划"项目(项目编号:Z2006-1-65011)
云南省教育厅项目(项目编号:07Y41143)
关键词
马尔可夫法
初始概率
转移概率
极大似然估计
the Markov forecast model
initial probability
transition probability
maximum likehood estimate
