Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)

Financial Early-Warning Analysis of Big Data Industry Enterprises Based on Factor Analysis and Logistic Model

Authors
XiaoFei Luana, HongMei Zhang
Corresponding Author
XiaoFei Luana
Available Online November 2019.
DOI
https://doi.org/10.2991/dramclr-19.2019.36How to use a DOI?
Keywords
financial early-warning model, financial risk, Logistic regression analysis
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.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)
Series
Advances in Intelligent Systems Research
Publication Date
November 2019
ISBN
978-94-6252-827-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/dramclr-19.2019.36How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - XiaoFei Luana
AU  - HongMei Zhang
PY  - 2019/11
DA  - 2019/11
TI  - Financial Early-Warning Analysis of Big Data Industry Enterprises Based on Factor Analysis and Logistic Model
BT  - Proceedings of the Fourth Symposium on Disaster Risk Analysis and Management in Chinese Littoral Regions (DRAMCLR 2019)
PB  - Atlantis Press
SP  - 59
EP  - 63
SN  - 1951-6851
UR  - https://doi.org/10.2991/dramclr-19.2019.36
DO  - https://doi.org/10.2991/dramclr-19.2019.36
ID  - Luana2019/11
ER  -