A real-time stock price prediction system using LSTM neural network and text miner

摘要

LSTM (long short-term memory networks) neural network is used to train stock prices using historical data, predict stock prices with the learned neural network, and analyze real-time stock news through text miners to add weights to the predicted stock prices. , It relates to a real-time stock price prediction system using an LSTM neural network and a text miner, comprising: a neural network module including an LSTM neural network; a neural network learning unit for learning the LSTM neural network using past stock price data; a text miner for extracting mood data that numerically indicates whether news data is good news or bad news by text mining; and a stock price prediction unit that inputs stock price data up to the day into the LSTM neural network to obtain output predicted stock price data, and calculates final predicted stock price data by weighting the obtained predicted stock price data with the mood data. set up With the system as described above, by predicting stock prices through LSTM neural network and weighting them with analysis results of real-time news through text miners, it is possible to predict stock prices more accurately by reflecting both the time-series prediction and the changing news environment at the same time. can