报告题目：Modeling Correlated Defaults with Multi-Name Distance to Defaults
报告人：Prof. Cheng-Der Fuh (Fanhai International School of Finance, Fudan University)
报告摘要：This paper studies correlated default structure in a structure form model. Through the developed renewal theory, we show that even under a simple one-factor model, the proposed structure form model can produce a sophisticated correlated default dynamic which will be affected when a firm defaults. This creates different effects of how a firm impacts other firms' default structure; some of them exist before any default, and some come into present only when a default is triggered. We further propose several multi-name distance-to-default to capture these different effects, which would be beneficial in quantifying correlated defaults. By such, we provide an alternative quantitative way in studying the relationship between defaults of multiple corporations. Numerical and empirical studies are given to illustrate the proposed model. This is a joint with Professor Kao, Chu-Lan.
报告人简介：Cheng-Der Fuh received his B.S. in Mathematics from National Central University, Taiwan in 1980, and his Ph.D. in Statistics and Mathematics (Double majors) from Iowa State University, Iowa, USA in 1989. After graduation, he joined the Institute of Statistical Science, Academia Sinica in Taiwan, where he was an associate research fellow from 1989 to 2000, a research fellow from 2000 to 2006. He was a chair professor at National Central University, Taiwan from 2006 to 2018. Currently, he is a professor at Fanhai International School of Finance (FISF), Fudan University, Shanghai, China, where he has worked since 2018. Dr. Fuh is an Elected fellow of the International Statistical Institute. He received the outstanding research award twice from the Ministry of Science and Technology, Taiwan. He is the author of a book and over 100 papers. His research interests are generally in the areas of credit risk, quantitative finance, econometrics, big data in financial markets, statistics, applied probability, and signal processing.