China's Listed Companies' Financial Crisis Early-warning Model

Corporate financial distress has always been the important subject in the study of corporate finance. Many domestic and foreign scholars have done a great deal of research in this field. From Fitzpartrick's single variable model (1932) to Artificial Neural Network introduced into the financial distress prediction, the scholars have already made very great progress in the research of the financial distress. But there is still insufficient in this field.From four aspects including financial ratios, market yield, ownership structure and corporation governance, I set up one hypothesize and a series propositions. The hypothesize is that before the financial distress the distressed and the non— distressed were very different in the above four aspects. I used the data of publicly listed non-financial companies in China to examine the hypothesis. I adopted MDA and Logistic Regression and set up a series of models, and the empirical result supports the hypothesis ultimately. At the same time, the warning models were valid. At last I set up N-Score combined warning model and it worked rather perfectly.There are three innovations in this paper. First, I redefine the distress as a company's ROE being lower than the interest and discriminate the different situations between the begin of financial distress and the end one. Second I introduced the variables on financial ratios such as the rela-index. The third, I construct N-Score warning combined model in order to combine various warning models' outcome.