Template-Type: ReDIF-Article 1.0
Author-Name: Lu Wang
Title: Financial distress prediction for listed enterprises using Fuzzy C-Means
Abstract: Enterprise financial distress prediction model is an important tool for enterprise risk management. Fuzzy C-Means (FCM) model is more suitable for the classification calculation in reality because of introducing the fuzzy membership. This article adopts the FCM model to predict financial distress. In the experiment, 90 distressed enterprises and 90 normal enterprises were selected as samples, which are all from the same time and the same industry in Chinese Shenzhen and Shanghai Stock Exchange, and 12 financial indicators of these enterprises as a sample dataset. After the data are pre-processed, we identified 11 financial indicators with a significant difference to make the financial distress prediction. Last, it can be concluded based on the FCM results that the performance is better in the case of distressed enterprises.
Keywords: financial distress prediction, financial indicator, fuzzy C-Means
Journal: Littera Scripta
Volume: 12
Issue: 1
Year: 2019
Month: August
DOI: 10.36708/LS.2019.I01.002
File-URL: https://littera-scripta.com/articles/financial-distress-prediction-for-listed-enterprises-using-fuzzy-c-means-c015ed07
File-Format: text/html
Handle: RePEc:rsg:littra:2019-002