An Empirical Study On Listed Companies’ Financial Distress Warning Model Taking Into Account Distance To Default

Large scale, good performance, strong financing capability and other characteristicsmake listed companies become the most core business organization in economy market.The quality of listed companies’ financial situation affects the development of the stockmarket directly. However, the factors which make companies have financial difficulties arein large numbers and complicated. Scholars have always been trying to find the mostcritical variables to establish a financial distress prediction model. By this model, we canobjectively evaluate listed company’s financial position and predict whether thesecompanies have financial difficulties. Regulatory agencies can monitor the abnormalfinance companies accurately, while securities companies can identify quality customerseffectively, and stock investors can adjust the investment strategies promptly.Based on previous studies, this paper aims at researching a Financial Distress Warningmodel which is applicable to China’s listed companies. By using data from non-financiallisted companies which have completed share segregation reform, this paper studiessample companies’ financial indicators and non-financial indicators. Taking2011as thebase year of the financial distress event, study the data of3years before2011, which from2008to2010. Firstly, use descriptive statistics to research15financial indicators fromnormal companies and ST companies to filter indicators which include more corporatefinancial distress information. Secondly, use empirical research methods to distinguish theadvantages and disadvantages of the fisher model and Logistic models, which are widelyrecognized by academics. Thirdly, on the basis of the KMV model, set the optimal defaultpoint which has the best ability to distinguish sample companies. Finally, introduce theoptimal distance to default (DD) to Logistic model, and discuss whether the predictionaccuracy of Logistic model is improved after introducing DD.Conclusions are as follows:(1) Logistic model performs better at accuracy offinancial distress prediction than fisher model;(2) optimal default point is equal toshort-term debt plus long-term debt;(3) the financial distress prediction accuracy of DD’sLogistic model is higher than original model;(4) the prediction accuracy is significantlyimproved with the approaching of financial distress.