工业工程2011，Vol.14Issue(6)：133-137,5.
基于小波多尺度分析的股票价格组合预测方法
Combined Prediction Method of Stock Price Based on Wavelet Multi-Scale Analysis
摘要
Abstract
Stock price is affected by a large number of factors and is a typical non-stationary time series. In order to predict the stock price more accurately, a combined prediction method is proposed by combining the wavelet analysis, remanet GM (1,1) model, and autoregressive (AR) model. By using the wavelet decomposing algorithm, the stock price is approximately decomposed into a number of signals of different scales. Then, these signals are reconstructed to form a number of low and high frequency time serials called the tendency part and random part of the stock price data. These serials are used for stock price prediction by using remanet GM (1,1) and AR models, respectively, with respect to their different features. The predicted results of all serials are combined into the final prediction price. As shown in the experimental result obtained from an example, by the proposed method, the prediction accuracy is higher than that obtained by the traditional ones.关键词
小波分析/灰色残差模型/自回归模型/预测Key words
wavelet analysis/ remanet GM (1,1) model/ autoregressive (AR) model/ prediction分类
管理科学引用本文复制引用
肖燕君,张华,任若恩..基于小波多尺度分析的股票价格组合预测方法[J].工业工程,2011,14(6):133-137,5.基金项目
国家自然科学基金创新研究群体科学基金资助项目(70821061) （70821061）
国家自然科学基金青年资助项目(70901003) （70901003）
