南京信息工程大学学报2023，Vol.15Issue(6)：631-642,12.DOI:10.13878/j.cnki.jnuist.20221008002
基于LSTM和灰色模型的股价时间序列预测研究
Stock price time series prediction based on LSTM and grey model
摘要
Abstract
In view of the complicated factors influencing the stock price,we revised the Long Short-Term Memory(LSTM)network,which is commonly used in time series,to predict stock prices under the condition of multivari-able.First,the Variance Inflation Factor(VIF)was used to screen variables,and then the adaptive promotion(Ada-boost)model was combined to check the importance of characteristic variables.Second,the crawler was used to con-duct text analysis of investor sentiment,calculate indicators including sentiment index,and reveal the relationship between them and stock price.Then,prices of three stocks including Gree Electric Appliances,Flyco Electric Appli-ances and Midea Group were predicted by Multilayer Perceptron(MLP)and LSTM,and the appropriate model was selected as the benchmark model.Finally,indicators of sentiment index and investor concern were added to the benchmark model to construct the LSTM-EM model,and the GM(1,1)model was used to correct the residual term after considering investor sentiment.The empirical results show that the proposed model can predict the stock price accurately.关键词
股价预测/综合预测/文本分析/误差修正/长短期记忆网络(LSTM)/灰色模型Key words
stock price forecast/comprehensive prediction/text analysis/error correction/long short-term memory(LSTM)network/grey model分类
经济学引用本文复制引用
韩金磊,熊萍萍,孙继红..基于LSTM和灰色模型的股价时间序列预测研究[J].南京信息工程大学学报,2023,15(6):631-642,12.基金项目
国家社科基金一般项目(23BGL232) （23BGL232）
教育部人文社会科学研究规划项目(22YJA630098) （22YJA630098）
江苏省社会科学项目(22GLB022) （22GLB022）
大学生创新创业训练计划项目(202210300036Z) （202210300036Z）
