南京师范大学学报（工程技术版）2023，Vol.23Issue(4)：19-28,10.DOI:10.3969/j.issn.1672-1292.2023.04.003
基于神经网络预测模型的最佳交易策略探究
Research on the Optimal Trading Strategy Based on Neural Network Prediction Model
摘要
Abstract
Based on the long short-term memory neural network(LSTM)model,the rise and fall in the future price of investment products in financial transactions are predicted,and the best strategies for long and short trading methods are analyzed considering the transaction cost.Through experiments,it is concluded that the trading model can make a greater profit when the prediction accuracy is close to 50%or greater than 50%,and the maximum profit can be obtained when the test set is 25%,and the order of return of the four varieties is Bitcoin,crude oil,US dollar index,and gold.Changing the relative commission has a certain impact on the bias of portfolio transactions,and the return changes in a gradient style.The model is simplified on a daily basis and cannot be used for single-day high-frequency trading analysis.关键词
期货交易/LSTM模型/单类交易/组合交易Key words
futures trading/LSTM model/single class trading/portfolio trading分类
管理科学引用本文复制引用
董涵,陈佳丽,王浩然,叶晓辉..基于神经网络预测模型的最佳交易策略探究[J].南京师范大学学报（工程技术版）,2023,23(4):19-28,10.基金项目
福建省中青年教师教育科研项目(JAT210609)、厦门大学嘉庚学院校级科研孵化项目(PY2023L01). （JAT210609）
