Early Warning Research On Zombie Enterprises Listed In China's Manufacturing And Mining Industries

Zombie Firms has distorted the normal order of market competition,wasted our social resources,meanw hile easily to causing systemic economic risk.Thus,research on early-warning system of Zombie Firms is of great significance to promote the quality of economic growth in the 'New Normal'.This paper use the individual share of excess capacity battered sectors in stock markets of Shanghai and Shenzhen as the research object.Building early warning system based on carefully designed identification method and financial ratio in consolidated annual report through significance test,factor analysis,cleaning,normalization and other preprocessing methods.Then make empirical research using Binary Logistic Regression Model and BP Neural Network Model.Finally,provi ding reasoned model explanation and related policy suggestions for both firms themselves and supervision department.The results showed that the established model could obtain stable recognition result.Because of the development and evolution of enterprise business benefit are processes of gradual accumulation.Compared with traditional linear and structured method represented by Logistic regression,BP Neural Network could make better feedback,whose result has remarkably positive meaning and important value.Profitability and the capability of producing cash flows play key roles in the early warning of zombie Firms.Specifically,Earnings per share and Return on total assets,Net profit(Year-on-year growth rate)and Net cash flow from operating activities(Year-on-year growth rate)are the critical factors that determine w hether a Firms is judged to be a Zombie Firms.