基于集成深度学习的股票价格预测
Stock Price Prediction Based on Integrated Deep Learning
郭慧婷 1常延贞 1厉亮 1徐永利1
作者信息
摘要
股票市场是国民经济的一个重要组成部分,股票投资是一项高风险但同时高回报的投资方式.为了给股票投资者提供参考,对未来股票价格进行了预测研究.设计了一种基于深度学习的集成预测算法,对未来 5 日的股价进行预测.研究结果显示,基于预测性能的权重分配集成方法相比基本模型平均绝对误差(MAE)降低,在平均绝对误差评价指标上给出了最好的结果.
Abstract
The stock market is an important component of the national economy,and stock investment is a high-risk but high-return investment method.To provide guidance for stock investors,a research is conducted to predict future stock prices.This paper designs an integrated prediction algorithm based on Deep Learning for predicting the stock price over the next 5 days.The research results show that the MAE of the weight allocation integrated method based on prediction performance reduces compared to the basic model and gives the best results on MAE index.
关键词
深度学习/股价预测/集成学习Key words
Deep Learning/stock price prediction/integrated learning引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据