Prediction of Shanghai Stock Exchange Index Based on CNN and LSTM Fusion Model
Based on the external and embedded fusion models of CNN and LSTM,some of the structures in the embedded models are adjusted and improved according to the characteristics of the SSE index,and provide a sufficient theoretical basis for the selection of step parameters.The comparison experimental results of multiple groups of models show that the constructed fusion model can grasp the structural characteristics and time-series nature of the data more accurately,and automatically explore the correlation relationships within the data to achieve accurate prediction in the SSE index,which provides some reference for the model selection in financial research.
Deep learningRecurrent neural networkConvolution neural networkFusion modelIndex forecast
NETL
NSTL
万方数据
