摘要
基于市场信息的MertonDD模型已成为企业财务困境预测研究的主流方法之一。作为MertonDD模型的重要改进，Bharath＆Shumway（2008）的naiveDD已被国际学者普遍采用，但国内学者却比较青睐于KMV模型。通过我国A股市场2014年被ST的上市公司连续3年的数据分析，我们实证研究了naiveDD模型对中国上市公司财务困境预测的适用性，结果发现：（1）计算相对简单的nagveDD能显著地识别出ST与非ST公司；（2）naiveDD与Z-Score都是预测企业财务困境的重要因子，二者间有着不稳定的一致性；（3）联合利用这二者的信息能显著地提高预测效果。此外，还发现naiveDD竟与资产波动性呈同向变动关系，这违背了其理论预期。
The marked-based Merton DD model has become one of the main methods of financial distress prediction. As an important improvement of the Merton DD model, the naive DD model ofBharath ＆ Shumway （2008） has been widely used abroad. However, our researchers are more favorable of the KMV model. By analyzing three consecutive years of data about the ST companies in our A-share market in 2014, we tested the applicability of the naive DD in our country and concluded that the simply calculated naive DD can significantly identify the ST and non-ST companies. Besides, it is an important predictor of financial distress as well as the Z-Score. Apart from that, there is an instable consistency between the naive DD and the Z-Score, and the joint of them can significantly improve the prediction performance. In addition, we also found a positive correlation between the naive DD and the asset volatility, which is contrary to the theoretical expectations.
