基于轻量化机器学习法的陕西电气制造上市公司综合评价  

Comprehensive Evaluation of Shaanxi Electrical Manufacturing Listed Companies Based on Lightweight Machine Learning Approach

作　　者：赵耀 Zhao Yao(Xingzhi College of Xi'an University of Finance and Economics,Xi'an Shaanxi 710018,China)

机构地区：[1]西安财经大学行知学院,陕西西安710018

出　　处：《现代工业经济和信息化》2024年第9期204-206,共3页Modern Industrial Economy and Informationization

基　　金：陕西省教育厅科学研究规划项目资助(23JK0450);西安财经大学行知学院财政与经济发展研究中心2024年度校内培育课题“基于机器学习的陕西省电气制造业上市企业盈利能力综合评价”。

摘　　要：分析了各种评价方法的优缺点,其次进行因子选择,并通过主成分分析法筛选因子,从而对数据进行降维,最后设置电气行业大盘对比结果为因变量,通过随机森林的方法计算出各因子的基尼系数,作为影响度的代理指标,并对此提出相应意见。研究结果表明:资产规模、营业利润等规模指标相较于周转率、流动比率等效率指标在盈利方面更加显著,表明电气制造业应当更优先于走高集成、高规模型路线。The advantages and disadvantages of various evaluation methods are analysed,followed by factor selection and screening of factors through principal component analysis so as to downsize the data,and finally setting the results of the comparison of the general market of the electrical industry as the dependent variable,calculating the Gini coefficients of the factors through the method of Random Forest as a proxy for the degree of influence,and making corresponding comments in this regard.The results of the study show that scale indicators such as asset size and operating profit are more significant in terms of profitability compared to efficiency indicators such as turnover ratio and current ratio,indicating that the electrical manufacturing industry should be more prioritised to take the route of high integration and high scale.

关 键 词：企业评价 上市公司 主成分分析法 陕西省电气制造业 

分 类 号：F832.51[经济管理—金融学] F425F272.5