Speaker:

Dr. Yimin YANG, Senior Director, Protiviti Inc.
 

Abstract:

This paper establishes a new theory for creditworthiness and credit rating. It provides a unified framework for analyzing both the real-world credit ratings (such as agency ratings or bank ratings) and theoretical approaches (such as first-hitting defaults or Distance-to-Default model). The paper offers solutions to many common rating problems (such as time consistent or rating mapping). Using agency ratings as examples, it establishes credit ratings that are consistent across time and fully convertible between different rating systems. It also explains connections between creditworthiness, credit rating and regulatory requirements. When applied to first-hitting default model, it reveals deep connections between credit rating, asset volatility and market price of risk
 

Biography:

Dr. Yimin Yang has over 20 years of experience in financial risk management, including building and heading risk analytics for PNC Financial Services Group and SunTrust Banks. His risk management expertise covers credit risk, investment risk and Anti-money laundering areas. Currently he is the first Senior Director partner at Protiviti Inc., the 6th largest risk management consulting firm in USA, inheriting former Arthur Andersen Consulting. He is responsible for risk management, AI/Machine Learning, and capital management. Dr. Yang holds a Bachelor’s degree from Peking University, a Master degree from Chinese and Academy of Sciences, a Master degree in computer networking from Carnegie Mellon University and a Math Ph.D. from University of Chicago. Prior to his financial industry career, he was a tenure-track assistant professor at University of Minnesota-Morris.
 

Co-organizers:

Center for Investing of Department of Finance
Crypto-Fintech Lab of Department of Mathematics
7月19日
2:00pm - 3:30pm
地点
Room 3003, LSK Building, HKUST
讲者/表演者
主办单位
Department of Finance
联系方法
mikiyeung@ust.hk
付款详情
对象
UG Students, PG Students, Alumni, Faculty and Staff
语言
英语
其他活动
11月22日
研讨会, 演讲, 讲座
IAS / School of Science Joint Lecture - Leveraging Protein Dynamics Memory with Machine Learning to Advance Drug Design: From Antibiotics to Targeted Protein Degradation
Abstract Protein dynamics are fundamental to protein function and encode complex biomolecular mechanisms. Although Markov state models have made it possible to capture long-timescale protein co...
11月8日
研讨会, 演讲, 讲座
IAS / School of Science Joint Lecture - Some Theorems in the Representation Theory of Classical Lie Groups
Abstract After introducing some basic notions in the representation theory of classical Lie groups, the speaker will explain three results in this theory: the multiplicity one theorem for classical...