基于长短期记忆神经网络的每日股票价格预测

Daily Stock Price Prediction Based on Long and Short Term Memory Neural Network

股票价格预测一直是人们关注的焦点之一。针对每日股票预测存在的问题,本文提出一种基于长短期记忆神经网络的方法来预测每日股票的最高价与最低价,通过使用Python编程语言构建长短期记忆神经网络模型,并对2000—2020年上海证券、深圳证券的股票数据进行预测。实验结果表明,采用长短期记忆神经网络能够很好地拟合每日股价的波动趋势,具有较高的准确率。

Stock price prediction has always been one of the focuses of people’s attention. Aiming at the problems of daily stock forecasting, this paper proposes a method based on long and short-term memory neural network to predict the highest and lowest price of daily stocks. The long-term and short-term memory neural network model is constructed by using Python programming language.-Forecast the stock data of Shanghai Securities and Shenzhen Securities from 2000 to 2020. The experimental results show that the use of long and short-term memory neural networks can fit the daily stock price fluctuation trend well and has a high accuracy rate.