Research on Financial Risk Early Warning of Listed Companies on the Science and Technology Innovation Board Based on the Life Cycle Perspective

DOI

10.2991/assehr.k.210407.129How to use a DOI?

Keywords

Financial early warning, Logistic regression analysis, Financial risk management, Listed company on science and technology innovation board

Abstract

This paper selects the 2017 to 2019 science and technology innovation board listed companies and ST companies as samples, from finance, corporate governance and life cycle three categories to construct and optimize the financial risk early warning index system. Factor analysis method and binary logistic regression method are used to construct the financial early warning models of listed companies in the science and technology innovation board in the growth and maturity periods, and then tested. It is found that the accuracy of the early-warning model in the growth stage can reach 90%, and the accuracy of the early-warning model in the growth stage can reach 95%.

Copyright

© 2021, 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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TY  - CONF
AU  - Lan Wang
AU  - Yilin Xiong
PY  - 2021
DA  - 2021/04/08
TI  - Research on Financial Risk Early Warning of Listed Companies on the Science and Technology Innovation Board Based on the Life Cycle Perspective
BT  - Proceedings of the 2021 6th International Conference on Social Sciences and Economic Development (ICSSED 2021)
PB  - Atlantis Press
SP  - 680
EP  - 685
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210407.129
DO  - 10.2991/assehr.k.210407.129
ID  - Wang2021
ER  -