基于因子分析和Logistic模型的大数据产业企业财务预警分析

X. Luana, Hongmei Zhang
{"title":"基于因子分析和Logistic模型的大数据产业企业财务预警分析","authors":"X. Luana, Hongmei Zhang","doi":"10.2991/dramclr-19.2019.36","DOIUrl":null,"url":null,"abstract":"On the basis of systematic research on financial early-warning research at home and abroad, this paper selects Chinese big data listed companies as research samples, constructs financial early-warning model of electronic information listed companies with Logistic regression method comprehensively, and analyzes its discriminating effect. The results show that it is an effective method to construct a financial early-warning model by using logistics regression method to help listed companies prevent financial risks. Keywords—financial early-warning model, financial risk, Logistic regression analysis 摘要—在对国内外财务预警研究进行系统研究 的基础上,选取我国大数据上市企业公司作为研究 样本,综合运用 Logistic 回归法构建电子信息上 市公司财务预警模型,并分析其判别效果。研究结 果表明,通过运用 logistic 回归法构建财务预警 模型来帮助上市公司防范财务风险是一种行之有效","PeriodicalId":142201,"journal":{"name":"Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Financial Early-Warning Analysis of Big Data Industry Enterprises Based on Factor Analysis and Logistic Model\",\"authors\":\"X. Luana, Hongmei Zhang\",\"doi\":\"10.2991/dramclr-19.2019.36\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"On the basis of systematic research on financial early-warning research at home and abroad, this paper selects Chinese big data listed companies as research samples, constructs financial early-warning model of electronic information listed companies with Logistic regression method comprehensively, and analyzes its discriminating effect. The results show that it is an effective method to construct a financial early-warning model by using logistics regression method to help listed companies prevent financial risks. Keywords—financial early-warning model, financial risk, Logistic regression analysis 摘要—在对国内外财务预警研究进行系统研究 的基础上,选取我国大数据上市企业公司作为研究 样本,综合运用 Logistic 回归法构建电子信息上 市公司财务预警模型,并分析其判别效果。研究结 果表明,通过运用 logistic 回归法构建财务预警 模型来帮助上市公司防范财务风险是一种行之有效\",\"PeriodicalId\":142201,\"journal\":{\"name\":\"Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/dramclr-19.2019.36\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/dramclr-19.2019.36","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

On the basis of systematic research on financial early-warning research at home and abroad, this paper selects Chinese big data listed companies as research samples, constructs financial early-warning model of electronic information listed companies with Logistic regression method comprehensively, and analyzes its discriminating effect. The results show that it is an effective method to construct a financial early-warning model by using logistics regression method to help listed companies prevent financial risks. Keywords—financial early-warning model, financial risk, Logistic regression analysis 摘要—在对国内外财务预警研究进行系统研究 的基础上,选取我国大数据上市企业公司作为研究 样本,综合运用 Logistic 回归法构建电子信息上 市公司财务预警模型,并分析其判别效果。研究结 果表明,通过运用 logistic 回归法构建财务预警 模型来帮助上市公司防范财务风险是一种行之有效
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Financial Early-Warning Analysis of Big Data Industry Enterprises Based on Factor Analysis and Logistic Model
On the basis of systematic research on financial early-warning research at home and abroad, this paper selects Chinese big data listed companies as research samples, constructs financial early-warning model of electronic information listed companies with Logistic regression method comprehensively, and analyzes its discriminating effect. The results show that it is an effective method to construct a financial early-warning model by using logistics regression method to help listed companies prevent financial risks. Keywords—financial early-warning model, financial risk, Logistic regression analysis 摘要—在对国内外财务预警研究进行系统研究 的基础上,选取我国大数据上市企业公司作为研究 样本,综合运用 Logistic 回归法构建电子信息上 市公司财务预警模型,并分析其判别效果。研究结 果表明,通过运用 logistic 回归法构建财务预警 模型来帮助上市公司防范财务风险是一种行之有效
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Characteristics of Climate Change in Latest 60 Years and Extreme Severe Weather in latest 10 Years in Qinhuangdao Improvement measures of questionnaire design for risk communication in Internet of intelligences Using Game Theory Approach for Assessment of Risk and Police Patrols Scheduling Research on Risk Sharing of Creative Industrial Park by Recycling Old Industrial Buildings Research on Financial Early Warning of Big Data Enterprises Based on Logistic Regression and BP Neural Network
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1