K 线能量计算的股市生命期态势预测方法

摘要

股市中 K 线特征是股价涨跌的因果信息，基于支持向量机（SVM）的股价预测模型没有考虑 K 线特征知识，对于股价态势难以有效预测。提出基于 K 线能量计算的股市生命期支持向量机态势预测算法（LPF-SVM），首先，提取典型 K 线特征，通过引入特征的孕育成熟度和爆发力定义，给出 K 线特征支持向量机算法（KLF-SVM）；进而，在 KLF-SVM算法基础上定义特征的能量计算模型给出一种 K 线能量计算的 SVM股价预测算法。为了有效地预测态势，引入股价波动的生命期概念，通过 K 线组合特征判定股价所处的生命期的阶段，进而结合生命期阶段之间的时序影响关系给出一种基于生命期的股价态势预测算法。在上证和深证数据集上的实验结果表明，LPF-SVM算法对于股价上升波段和下跌波段的股价预测取得了很好的效果。%In the stock market,K line feature is the causal information for the rise and fall of stock price.Stock price predic-tion model of support vector machine (SVM),which does not consider K line features,can not predict the stock trend effec-tively.Based on K line energy calculation,this paper put forward a lifetime support vector machine (LPF-SVM)algorithm, forecasting stock market situation.First,it extracted the typical K line,with the introduction of maturity and explosive force definition,obtained the K line feature of support vector machine algorithm (KLF-SVM).Then on the basis of KLF-SVM,it defined typical energy calculation model,gave a kind of SVM prediction algorithm for K line energy calculation.In order to predict the situation effectively,it introduced the lifetime concept of stock price volatility.The stage of lifetime of the stock price could be judged through the K line combination features,and then combing with the timing effect relationship of life stage,it gave a stock price trend prediction algorithm based on lifetime.The experimental results on the Shanghai and Shenz-hen data set show that,the LPF-SVMalgorithm can predict the rising and falling band of stock price effectively.