基于改进GA参数优化的SVR股价预测模型

Stock Price Prediction Model Based on SVR with Parameters Optimized by Improved GA

针对股票价格的动态性及非线性等特点,提出了基于改进遗传算法(Genetic Algorithm,GA)优化参数的支持向量回归机(Support Vector Regression,SVR)股价预测模型.首先将选取的股票价格样本进行小波去噪处理,然后将经过改进GA优化参数的SVR模型对去噪后的数据进行预测及评价.结果证明,改进小波-GA-SVR模型具有良好的预测效果,对股票价格的预测研究具有一定的意义.

Aiming to the dynamics and nonlinearities of stock price, a stock price prediction model that based on support vector regression（SVR） with parameters optimized by improved genetic algorithm（GA） was proposed. First, the wavelet was used to de-noise the samples of stock price. Then the SVR model whose parameters were optimized by improved GA was utilized to predict and assess the data de-noised by wavelet. The result demonstrated that the improved wavelet-GA-SVR model has good prediction effect, and it is significant to the study of the prediction of stock price.