讲座主题：Disentangling and Assessing Uncertainties in Multiperiod Corporate Default Risk Predictions

　　报告人： Cheng Yong TANG， Associate Professor, Temple University

　　报告时间： 2017年11月21日(周二)上午10: 00-11:30

　　报告地点： B127

　　主办单位：数理经济与数理金融系， 主持人：刘成

　　摘要：

　　Abstract: Measuring credit risks for individual companies, industrial segments, and market systems is fundamentally and broadly important in economics, finance and beyond. For such a purpose, various quantitative methods have been developed to predictively assess the probabilities of companies going default in future. However, as a more difficult yet crucial problem, evaluating the uncertainties associated with the default predictions remains little explored. In this paper, we develop, for the first time in the scenario of default predictions, a procedure for quantifying the level of associated uncertainties by carefully disentangling multiple contributing sources. Our framework effectively incorporates broad information from historical default data, financial records, and economic environmental conditions by a) characterizing the default mechanism, and b) capturing the future dynamics of various features contributing to the default mechanism. Our development of the framework overcomes major challenges in this tremendously large scale statistical inference problem and makes it practically feasible by using parsimonious models, innovative methods, and modern computational facilities. By appropriately predicting the market-wise total number of defaults and assessing the associated uncertainties, our method can effectively evaluate the aggregated market credit risk level. Upon analyzing a US market data set with our method, we demonstrate that the level of uncertainties associated with default risk assessments is indeed substantial. More importantly and informatively, we also find that the level of uncertainties associated with the default risk predictions is correlated with the level of default risks, indicating potential for benefiting practical applications including improving the accuracy of default risk assessments. This is a joint work with Miao Yuan, Yili Hong, and Jian Yang.

　　简历：

　　Prof. Tang is an Associate Professor of Statistics and the Director of the Graduate Programs in the Department of Statistical Science, Fox School of Business, Temple University. He obtained his Ph.D. in Statistics from the department of Statistics, Iowa State University. His research interests are statistical methods for big and small data analysis. He has published more than 10 articles on top 4 statistics journals (The Annals of Statistics, Journal of the American Statistical Association , Journal of the Royal Statistical Society, Series B., Biometrika). He has also published 2 articles on the top journal of econometrics, Journal of Econometrics.