摘要
股票市场瞬息万变,股价反转点对投资者进行投资决策起着至关重要的作用。技术分析能够揭示股价反转的某些特征,但是使用单一技术指标预测股价反转点的召回率和准确率不高。本文提出了一种使用支持向量机(SVM)对技术指标组合进行数据挖掘,从而实现预测股价反转点的方法,实验结果表明该方法较使用单一技术指标进行反转点预测在召回率和准确率方面都有极大的提高。
The stock market changes rapidly.Thus, the stock price reversal points play a vital role in investment decisions.Technical analysis can reveal some features of stock price reversal, but to use a sole technical indicator to predict the reversal points can end with sesults that have very low recall and precision rates.In order to improve recall and precision rates, a novel method of using Support Vector Machines （SVM） is proposed to data mine a combination of technical indicators.The experiment results show that this method has a higher recall and precision rate than the original ones.
出处
《计算机系统应用》
2010年第9期214-218,共5页
Computer Systems & Applications
关键词
支持向量机
股价反转点
股票市场
support vector machines
stock price reversal point
stock market
