Financial Engineering Seminar Series: "Mitigating Extreme Risks through Securitization" - Qihe Tang | Hanlon Financial Systems Center

Financial Engineering Seminar Series: "Mitigating Extreme Risks through Securitization" - Qihe Tang

Financial Engineering Seminar Series: "Mitigating Extreme Risks through Securitization" - Qihe Tang

Event Location: 
Babbio Center 122, Stevens Institute of Technology
Event Time: 
Thursday, March 23, 2017 - 5:00pm to 6:00pm

Qihe Tang

Department of Statistics and Actuarial Science
University of Iowa

"Mitigating Extreme Risks through Securitization" 


Due to great concerns caused by losses from catastrophes, insurers have been seeking solutions to mitigating catastrophe risks. Traditional reinsurance, despite being a commonly used solution, does not have enough capacity to digest the catastrohe risks.  Alternative risk transfer to the capital market through securitization has emerged as another solution. In this talk we discuss securitized (re)insurance products, that is, insurance linked securities (ILSs), such as catastrophe (CAT) bonds and industry loss warranties (ILWs). Our focus is on the pricing of ILSs, as well as possible issues with using them as hedging tools, such as hedging eectiveness and basis risk. We establish a general pricing theory using CAT bonds as an example, and we establish a framework for quantifying the basis risk of hedging using ILWs as an example. In doing so, we propose to use extreme value theory to characterize the catastrophe risks involved. This talk is based on a technical report for the Society of Actuaries (SOA) joint with Jose Blanchet (Columbia University), Henry Lam (University of Michigan), and Zhongyi Yuan (Pennsylvania State University); 


Qihe Tang is Professor of Actuarial Science at the University of Iowa.  He received his Ph.D. in Statistics from the University of Science and Technology of China in June 2001.  He held a postdoctoral research fellow at the University of Amsterdam in May 2002 - June 2004 and a tenure-track assistant professor at Concordia University in July 2004 - December 2005 before he joined the University of Iowa in January 2006.  At the University of Iowa, he was promoted to associate professor in July 2008 and to full professor in July 2012.  In particular, he was conferred the F. Wendell Miller endowed professorship in July 2014 to honor his scholarly work and professional contributions and the great distinction he brings to the University of Iowa. 

His expertise centers on extreme value theory for insurance, finance, and quantitative risk management.  During the past 15 years, he has been working on various topics recently arising from the interdisciplinary area of actuarial science, mathematical finance, and extreme value theory.  These topics include precise large deviations of aggregate losses, interplay of insurance and financial risks, subexponential distributions, extreme dependence, and modeling credit risk.  Research in these areas has also piqued his recent interest in modeling, measuring, and managing catastrophe risks, such as pricing insurance-linked securities and quantifying their basis risk.  He has a particular interest in probabilistic approaches to applied problems in insurance and finance. 

Together with his coauthors he has published nearly 100 papers, most of which appear in top journals in actuarial science and applied probability.  As of today, Google Scholar shows that his works have received 3,664 citations, resulting in an h-index of 35.  His research has been supported by a number of external grants, including one from the NSERC (Natural Sciences and Engineering Research Council of Canada), one from the NSF (National Science Foundation of the US), and four from the SOA (Society of Actuaries).  Currently, he is an associate editor for six academic journals, which are Insurance: Mathematics and Economics, TEST, Applied Stochastic Models in Business and Industry, Statistics & Probability Letters, Risks, and Dependence Modeling.  He has graduated nine doctoral students, most of whom are now university professors.