Machine learning with Belief Rule-Based Expert Systems to predict stock price movements
作者：
Highlights：
• Used Belief Rule-Based Expert System to predict the stock price movement.
• Each expert system has a knowledge-base that is created from the training samples.
• Assigns a degree of belief in accordance with the probability of price movement.
• Performance increases when parameters are optimized using the fmincon function.
• Produces promising performance compared to other deep learning approaches.
摘要
•Used Belief Rule-Based Expert System to predict the stock price movement.•Each expert system has a knowledge-base that is created from the training samples.•Assigns a degree of belief in accordance with the probability of price movement.•Performance increases when parameters are optimized using the fmincon function.•Produces promising performance compared to other deep learning approaches.
论文关键词：Stock prediction,Bollinger band,Belief rule,Expert system,Machine learning,Time series analysis
论文评审过程：Received 25 October 2021, Revised 23 April 2022, Accepted 29 May 2022, Available online 4 June 2022, Version of Record 27 June 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.117706
