基于信息粒化和支持向量机的股票价格预测

喻胜华; 肖雨峰

基于信息粒化和支持向量机的股票价格预测

引用本文：喻胜华，肖雨峰.基于信息粒化和支持向量机的股票价格预测[J].财经理论与实践,2011,(6):44-47

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作者	单位
喻胜华，肖雨峰	（1．湖南大学经济与贸易学院，湖南长沙410079；2．中南大学数学科学与计算技术学院，湖南长沙410075）

中文摘要:信息粒化是进行海量数据挖掘和模糊信息处理的有效工具。本文提出了一种基于信息粒化和支持向量机的股票价格预测方法。利用长安汽车的股票数据，建立股票开盘价回归预测模型，该模型克服了传统时间序列模型仅局限于线性系统的情况。应用实例表明：该方法能有效地预测股票价格的变化范围。

中文关键词:信息粒化支持向量机股票价格

Forecasting Method of Stock Price based on Information Granulation and Support Vector Machine

Abstract:Information granulation is a powerful tool for massive data mining and fuzzy information processing. In this paper, a new forecasting method of stock price based on information granulation and support vector machine is put forward. Using the stock data of Changan Automobile, a regression prediction model of the opening price is established. This model abstains from the default of traditional time series prediction model that only can be used in linear system. The empirical analysis indicates that the above method can effectively predict the change range of the stock price.

keywords:Information granulation Support vector machine Stock price

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