{"title":"Research on the Analysis and Application of Financial Risk Early Warning Model","authors":"Di Lu, Guanhua Wang","doi":"10.1145/3357292.3357301","DOIUrl":null,"url":null,"abstract":"This study takes China's 43 agricultural listed companies in 2016 as a sample, which shows that the financial early warning model of China's agricultural listed companies constructed based on factor analysis method has really good predicting effect, and the system indicates that the forecast accuracies are 88.37%, 93.02%, 79.07% and 93.02% from 2013 to 2016, respectively. Also, this result demonstrates that most of the listed agricultural companies are in a state of warning and their development is not optimistic. This study has theoretical and practical significance for the analysis of the construction of financial early warning model for agricultural listed companies, which expands the theoretical boundary of this area.","PeriodicalId":115864,"journal":{"name":"Proceedings of the 2nd International Conference on Information Management and Management Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Conference on Information Management and Management Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3357292.3357301","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
This study takes China's 43 agricultural listed companies in 2016 as a sample, which shows that the financial early warning model of China's agricultural listed companies constructed based on factor analysis method has really good predicting effect, and the system indicates that the forecast accuracies are 88.37%, 93.02%, 79.07% and 93.02% from 2013 to 2016, respectively. Also, this result demonstrates that most of the listed agricultural companies are in a state of warning and their development is not optimistic. This study has theoretical and practical significance for the analysis of the construction of financial early warning model for agricultural listed companies, which expands the theoretical boundary of this area.