Empirical Studies Of Financial Distress Prediction Based On Panel Data Of Listed Companies In China

As the development of the stock market in China, Sepecial Treated (ST) Companies have been focused on by scholars recently and they are always considered as financial distressed companys. The financial distressed companies face more risks, which is disadvantageous to their future development. So not only creditors and investor but also supervisors and regulators are concerned about whether the listed company is in abnormal financial situation or not.Summed up the conclusions of former studies, they mainly forecasted the financial situation only based on one year data (the section data namely). That is to say, they don't consider the factor of time continuity and the prediction model only can be used for a short time. Under this circumstance, the applicability of forecasting the financial distress in practice is limited.Therefore, a panel data model will be established in this paper to forecast financial status of the listed company, which considers not only the section imformation but also the time continuity information. The aim of this paper is to prove that the panel data model is more logical than other models.To maintain the same circumstance, five variables that were chosen frequently by former studies will be chosen in this paper. Compared with other models, the panel data model established in this paper has the advantages of higher accuracy, stronger stability and longer predictive time-span.