A comparison of dynamic hazard models and static models for predicting the special treatment of stocks in China with comprehensive variables

The stock exchanges in China give a stock special treatment in order to indicate its risk warning if the corresponding listed company cannot meet some requirements on financial performance. To correctly predict the special treatment of stocks is very important for the investors. The performance of the prediction models is mainly affected by the selection of explanatory variables and modelling methods. This paper makes a comparison between the multi-period hazard models and five widely used single-period static models by investigating a comprehensive category of variables including accounting variables, market variables, characteristic variables and macroeconomic variables. The empirical result shows that the performance of the models is sensitive to the choice of explanatory variables but the performance between the multi-period hazard models and the single-period static models has no significant difference.