Research on Two Stock Price Forecasting Methods Based on Deep Network
Stock is an important investment channel,how to forecast stock price more accurately is a hot research topic.Due to the complex characteristics of stock data,such as non-linearity,non-stationarity and before and after correlation,traditional stock price forecasting methods have reached the performance bottleneck.With the rise of Deep Learning methods,deep neural network forecast models such as LSTM and GRU have received great attention.Based on the historical trading data of Xiamen Port Stock and Shanghai Stock Index,LSTM and GRU models are used to forecast the closing price.The model evaluation is given by 5 indexes of MAE,MSE,RMSE,MAPE and R2.
国家科技期刊平台
NSTL
万方数据
