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修正的灰预测模型在股价预测中的应用

发表时间:2009-01-15  浏览量:1999  下载量:892
全部作者: 孙鑫
作者单位: 天津工业大学理学院
摘 要: 随着中国证券市场的发展完善和国际化进程的推进,股票市场在经济生活中承担了投资与融资的重要作用。而在当今金融市场的动荡时期,怎样合理地预测股市涨跌行情的变化趋势,以给投资者有效的投资意见,已成为当务之急。为研究股价走势,文章根据灰色系统理论建立了带有残差修正的GM(1,1)模型,利用中国石油的历史股价进行实证分析,求出了具体的GM(1,1)预测模型及预测股价,再由预测结果算出参数a,u的值,得到具体的残差GM(1,1)模型。利用方程对所得预测结果进行残差修正,进而得到了更加精确的股票预测价格。最后,对中国石油未来五天的股价进行预测,确立较佳的买入(卖出)时机。结果表明:残差GM(1,1)模型对于股价的短期预测效果较好,而在中长期预测方面效果极差。同时发现,GM(1,1)预测模型本身是减函数,使得预测出的股价呈现下降趋势。
关 键 词: 应用数学;GM(1,1)模型;股票价格;预测;修正模型
Title: The application of corrected grey model in stock pricing prediction
Author: SUN Xin
Organization: College of Science, Tianjin Polytechnic University
Abstract: With the development and improvement of China’s securities market and the process of internationalization, the stock market plays an important role in the economic life of the investment and financing. In current financial market turmoil period, a reasonable forecasting about the trend of stock prices and giving the investors an effective advice have become a top priority. To study the trend of stock prices, this paper builds the GM(1,1) model with residual amendment according to the gray system theory, and then takes use of the historical stock prices of Petro China to complete empirical analysis, and obtains a specific GM(1,1) model and the forecasted price. Meanwhile, it calculates the value of parameter a,u by the forecasted prices respectively, and gets the specific residual GM(1,1) model, and makes a residual amendment on the previous forecasted stock prices to obtain more accurate ones. Finally, it forecasts the stock prices of Petro China for next five days and finds a better buying (or selling) opportunity. The results show that the residual GM(1,1) model forecasts better in the short term, but does a very poor forecasting in the medium and long term. At the same time, it is found that the GM(1,1) model itself is a decreasing function, so the prediction of the stock prices usually shows a downward trend.
Key words: applied mathematics; GM(1,1) model; stock pricing; prediction; corrected model
发表期数: 2009年1月第1期
引用格式: 孙鑫. 修正的灰预测模型在股价预测中的应用[J]. 中国科技论文在线精品论文,2009,2(1):94-99.
 
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