Chen Yujia, Liu Jiangdan, Gao Yanzi, He Wei, Li Hongyu, Zhang Guangling, Wei Hongwei
School of Computer Science and Information Engineering, Harbin Normal University, Harbin, China.
School of Economics, Beijing International Studies University, Beijing, China.
Front Psychol. 2023 Feb 9;14:1123578. doi: 10.3389/fpsyg.2023.1123578. eCollection 2023.
Stock market analysis is helpful for investors to make reasonable decisions and maintain market stability, and it usually involves not only quantitative data but also qualitative information, so the analysis method needs to have the ability to deal with both types of information comprehensively. In addition, due to the inherent risk of stock investment, it is necessary to ensure that the analysis results can be traced and interpreted. To solve the above problems, a stock market analysis method based on evidential reasoning (ER) and hierarchical belief rule base (HBRB) is proposed in this paper. First, an evaluation model is constructed based on expert knowledge and ER to evaluate stock market sentiment. Then, a stock market decision model based on HBRB is constructed to support investment decision making, such as buying and selling stocks and holding positions. Finally, the Shanghai Stock Index from 2010 to 2019 is used as an example to verify the applicability and effectiveness of the proposed stock market analysis method for investment decision support. Experimental research demonstrates that the proposed method can help analyze the stock market comprehensively and support investors to make investment decisions effectively.
股票市场分析有助于投资者做出合理决策并维持市场稳定,而且它通常不仅涉及定量数据,还包括定性信息,因此分析方法需要具备全面处理这两类信息的能力。此外,由于股票投资存在固有风险,有必要确保分析结果能够被追溯和解读。为解决上述问题,本文提出一种基于证据推理(ER)和分层置信规则库(HBRB)的股票市场分析方法。首先,基于专家知识和证据推理构建一个评估模型来评估股票市场情绪。然后,构建一个基于分层置信规则库的股票市场决策模型,以支持诸如买卖股票和持仓等投资决策。最后,以2010年至2019年的上证指数为例,验证所提出的股票市场分析方法对投资决策支持的适用性和有效性。实验研究表明,所提出的方法能够帮助全面分析股票市场,并有效支持投资者做出投资决策。