报告题目：A review of modeling methods of recovery rate
报 告 人：王增相教授，加拿大阿萨巴斯卡大学管理学院
报告摘要：This workshop talk is a review of modeling methods of recover rate given possible default in bank loans or corporate bonds. Efforts in modeling recovery rate, though has been less studied in comparison with default probability and exposure at default, has increasingly become more intensive because it is found that modeling recovery rate, its density function, recovery dynamics and recovery times, is critical in credit risk analysis. Given the plethora of financial default data, methods for modeling recovery rate have moved from a parametric approach to non-parametric Bayesian and empirical data driven, and furthering with a potential trend of adapting machine learning technology in modeling recovery rate. The purpose of this review is hoped to identify possible new frontiers in modeling methods of recovery rate dynamics.
报告人简介：王增相，现任阿萨巴斯卡大学管理学院副院长，金融学教授，博士生导师。研究兴趣包括期权定价，公司治理，加拿大上市公司股东行为、 CEO和董事薪酬等。 研究成果已发表于《International Review of Financial Analysis》、《Journal of Management》、《Journal of Management and Governance》、《Managerial Finance》、《Canadian Investment Review》、《Distance Education in China》、和《Ivey Business Journal》等学术刊物。 因对股东行为和CEO薪酬的研究成就，曾受Ottawa Citizen报社记者的采访。2016年获得加拿大管理科学协会最佳战略管理论文奖。
报告时间：2022年12月22日 9:00-10:30
报告地点：腾讯会议ID：874 626 676
主办单位：伟德国际1946源自英国
