Multi-factor Stock Selecting Model Based on Residual Net and LSTM Deep Learning Algorithm

机译：基于残差网络和LSTM深度学习算法的多因素选股模型

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

This paper builds a multi-factor stock selection model based on optimized deep learning algorithms, using SFS, GA and XGBoost for factor combination and feature selection. Besides, applying Multi-LR to integrate Residual Net and LSTM to predict the stock's weekly change, which better simulates the randomness, information asymmetry and timing of financial markets. The quantitative models in this paper have excellent prediction accuracy, return and stability.

机译：本文基于优化的深度学习算法，使用SFS，GA和XGBoost进行因子组合和特征选择，建立了一个多因子选股模型。此外，应用Multi-LR将Residual Net和LSTM集成在一起，以预测股票的每周变化，从而更好地模拟金融市场的随机性，信息不对称性和时机。本文的定量模型具有出色的预测准确性，收益率和稳定性。

著录项

来源
《IEEE International Conference on Advances in Electrical Engineering and Computer Applications》|2020年|1049-1053|共5页
会议地点
作者
Muhao Chen; Weixia Guo;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类
关键词
Machine learning; Data models; Security; Prediction algorithms; Predictive models; Investment; Feature extraction;

机译：机器学习;数据模型;安全性;预测算法;预测模型;投资;特征提取;

相似文献

外文文献
中文文献
专利

1. Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling [J] . Li Wei, Becker Denis Mike Energy . 2021,第Pta1期

机译：基于LSTM的深度学习方法的混合模型及特征选择算法应用了一天的电力价格预测
2. Integrated Long-Term Stock Selection Models Based on Feature Selection and Machine Learning Algorithms for China Stock Market [J] . Yuan Xianghui, Yuan Jin, Jiang Tianzhao, Quality Control, Transactions . 2020,第期

机译：基于特色选择与机器学习算法的综合长期股票选择模型中国股市
3. Overview of Machine Learning for Stock Selection Based on Multi-Factor Models [J] . Haoxuan Li, Xueyan Zhang, Ziyan Li, E3S Web of Conferences . 2020,第10期

机译：基于多因素模型的股票选择机器学习概述
4. Deep Stock Ranker: A LSTM Neural Network Model for Stock Selection [C] . Xiaolin Zhang, Ying Tan International conference on swarm intelligence;International conderence on data mining and big data . 2018

机译：深度股票排名：用于股票选择的LSTM神经网络模型
5. Design and Simulation Analysis of Deep Learning Based Approaches and Multi-Attribute Algorithms for Warehouse Task Selection [D] . Sankaran, Prashant. 2020

机译：基于深度学习方法和多属性算法的仓库任务选择的设计与仿真分析
6. The use of machine translation algorithm based on residual and LSTM neural network in translation teaching [O] . Beibei Ren 2020

机译：基于残差和LSTM神经网络的机器翻译算法在翻译教学中的使用
7. Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches † [O] . Salah Bouktif, Ali Fiaz, Ali Ouni, 2018

机译：采用特征选择和遗传算法电负荷预测的最佳深度学习LSTM模型：与机器学习方法的比较†

Multi-factor Stock Selecting Model Based on Residual Net and LSTM Deep Learning Algorithm

摘要

著录项

相似文献

相关主题

期刊订阅