{"title":"Based on Panel Logistic model about Early warning of financial distress of listed companies in automobile industry","authors":"Wan Xiaodan","doi":"10.1145/3598438.3598462","DOIUrl":null,"url":null,"abstract":"In recent years, listed companies in general have poor risk management, the proportion of listed companies affected by the Chinese financial crisis is growing, resulting in a large number of bad debts. Thus, it is worthwhile to establish an early warning system for listed companies' financial crisis before it occurs, and to inform managers and investors in advance, so that effective measures can be implemented as soon as possible to eliminate the crisis's hidden dangers. In this paper, 181 ST enterprises from Shanghai and Shenzhen are chosen, and 181 non-ST enterprises from Shanghai and Shenzhen are matched 1:1, and a financial risk early-warning model based on principal component analysis and logistic regression is built. After obtaining 15 financial indicators through DuPont analysis, 8 financial indicators are chosen as early-warning indicators based on their significance, and a model for predicting financial crises is established through logistic regression analysis. According to the results, the logistic prediction model is superior.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"185 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3598438.3598462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, listed companies in general have poor risk management, the proportion of listed companies affected by the Chinese financial crisis is growing, resulting in a large number of bad debts. Thus, it is worthwhile to establish an early warning system for listed companies' financial crisis before it occurs, and to inform managers and investors in advance, so that effective measures can be implemented as soon as possible to eliminate the crisis's hidden dangers. In this paper, 181 ST enterprises from Shanghai and Shenzhen are chosen, and 181 non-ST enterprises from Shanghai and Shenzhen are matched 1:1, and a financial risk early-warning model based on principal component analysis and logistic regression is built. After obtaining 15 financial indicators through DuPont analysis, 8 financial indicators are chosen as early-warning indicators based on their significance, and a model for predicting financial crises is established through logistic regression analysis. According to the results, the logistic prediction model is superior.