The Empirical Rearch On Financail Crisis Warning Based On Default Distance

Since 2006 the Financial Circles has a large-scale implementation of Basel II, while the global finance crisis gave birth to Basel III directly. Domestic and global financial institutions are actively pursing the construction of credit risk assessment model. In fact, the early detection of credit customers, credit crisis, for the safe operation of financial institutions has been an important issue. KMV credit monitor model has been proposed as a potential approach to circumvent credit risk of banking customers. This study investigates the function of the KMV as an early warning vehicle in Chinese A market.The period of the sample is from 2007 to 2009, using a matched sample of 1 to 2, a total of 294 companies, of which 98 troubled companies and 196 normal companies. Data were analyzed using three years before the crisis. The empirical analysis proceeds in three stages. First, we use KMV model to estimate the DD (Default Distance) of sample companies, and then incorporate the DD into Logit regression model to establish an early warning system. At last, we use Out-Sample data to verify the effective of the model we constructed.The findings suggest that using Logit Model for early-warning Model has a comparably good discriminative and predictive accuracy. The DD of KMV model is significantly associated with probability of default in both 2nd and 3rd years prior to the financial crises of sample firms. Thus, an incorporation of KMV into the early warning system does not show the desired results, but the model enhances its overall accuracy in 2nd and 3rd years prior to financial crisis.