计算机与数字工程2024，Vol.52Issue(2)：337-342,6.DOI:10.3969/j.issn.1672-9722.2024.02.007
基于LSTM的多指标股票预测
Multi-index Stock Forecast Based on LSTM
齐太威 1于文年2
作者信息
- 1. 武汉邮电科学研究院 武汉 430074||南京烽火天地通信科技有限公司 南京 210019
- 2. 南京烽火天地通信科技有限公司 南京 210019
- 折叠
摘要
Abstract
In this Research,ten representative technical indexes are generated by processing Ping An Bank stock data,and the values of technical indexes are preprocessed as the input of multiple linear regression based on machine learning,BP neural net-work and LSTM neural network respectively,training through the models to predict the rise and fall of the stock,and then compare the performance of the three models in the prediction accuracy and the calculation of annualized rate of return,it is confirmed that the LSTM neural network model has the best effect on the prediction of the nonlinear stock trend.Then a trading timing strategy based on LSTM pattern classification is designed to obtain a higher annual rate of return,and it's a more viable strategy,Finally,it is feasible to use the LSTM model to carry out quantitative trading.关键词
多元线性回归/BP神经网络/长短期记忆网络/行为金融学/量化投资Key words
multiple linear regression/BP neural network/long short-term memory neural networks/behavioral finance/quantitative investment分类
数理科学引用本文复制引用
齐太威,于文年..基于LSTM的多指标股票预测[J].计算机与数字工程,2024,52(2):337-342,6.
