A Prediction of Financial Distress for Listed Companies of the New tertiary board Based on Factor Analysis and Logistic Regression

DOI

10.2991/icemse-16.2016.6How to use a DOI?

Keywords

New tertiary board, Factor analysis, Logistic regression, Financial early warning model

Abstract

Under the complex and changeable marketing environment, all walks of life are facing various risks and challenges. The enterprise financial crisis is more likely to happen. The company's financial situation is a standard judgment for investors, creditors and suppliers to make a decision. And it can affect the development of enterprises in the future directly. According to the features of the selected data, we established the binary Logistic regression equation of financial early warning model combined with factor analysis method. This model can analyze the financial status of listed companies in the new tertiary board market. Through the establishment of the model, stakeholders of listed companies may identify the signal of financial crisis and get ready ahead. The government regulators can monitor the quality of listed companies and the risk in the stock market. It also can reduce the volatility of the capital market, promote the benign development of listed companies.

Copyright

© 2016, 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  - Zhuoxi Yu
AU  - Qi Sun
AU  - Milan Parmar
AU  - Tiansong Zhang
PY  - 2016/12
DA  - 2016/12
TI  - A Prediction of Financial Distress for Listed Companies of the New tertiary board Based on Factor Analysis and Logistic Regression
BT  - Proceedings of the 2016 International Conference on Education, Management Science and Economics
PB  - Atlantis Press
SP  - 22
EP  - 26
SN  - 2352-5398
UR  - https://doi.org/10.2991/icemse-16.2016.6
DO  - 10.2991/icemse-16.2016.6
ID  - Yu2016/12
ER  -