BIN ZOU (邹斌)
Assistant Professor (Full CV)
Contact Information
Phone: | (860) 486-3921 |
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E-mail: | bin.zou@uconn.edu |
Address: | 341 Mansfield Road U1009 University of Connecticut Storrs, CT 06269-1069 |
More: | Office: Monteith 428 |
News
- 5th PKU-NUS Annual International Conference on Quantitative Finance and EconomicsThe 5th PKU-NUS Annual International Conference on Quantitative Finance and Economics will be held virtually on May 22-23, 2021. This is a FREE online event! Please see attached program file for full details.
Upcoming Events
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Nov
11
Actuarial Science Seminar, Axiomatic characterizations of some simple risk-sharing rules, Emil Valdez (UConn) 11:00am
Actuarial Science Seminar, Axiomatic characterizations of some simple risk-sharing rules, Emil Valdez (UConn)
Monday, November 11th, 2024
11:00 AM - 12:00 PM
Monteith Building
Abstract: In this paper, we present axiomatic characterizations of some simple risk-sharing (RS) rules, such as the uniform, the mean-proportional and the covariance-based linear RS rules. These characterizations make it easier to understand the underlying principles behind how risks are distributed under these simple rules. Such principles typically include maintaining some degree of anonymity regarding participants’ data and incident-specific data, adopting non-punitive processes and ensuring the equitability of risk sharing. By formalizing key concepts of reshuffling property, source-anonymous contributions and aggregated contributions, along with their generalizations, we develop a comprehensive framework that expresses these principles clearly and defines the relevant rules. To illustrate, we demonstrate that the uniform RS rule, a simple mechanism in which risks are shared equally, is the only RS rule that satisfies both the reshuffling property and source-anonymous contributions. These straightforward axiomatic characterizations serve as a foundation for exploring similar principles in two other broader classes of risk-sharing rules for which we baptize the $q$-proportional RS rules and the $(q_1,q_2)$-based linear RS rules. Furthermore, this framework allows us to introduce novel particular RS rules, such as the scenario-based RS rules. This is joint work with Jan Dhaene and Rodrigue Kazzi, both from KU Leuven.
Speaker’s bio: Emil is a Fellow of the Society of Actuaries and holds a Ph.D. from the University of Wisconsin in Madison. He joined the University of Connecticut in 2007 but had a brief stint (2013-2015) as professor and director of the actuarial science program at Michigan State University. His prime research of interest is actuarial science that cover topics in copula models, dependencies, post-retirement asset management, and some related to risk measures and capital allocation. In recent years, his research work has evolved around the applications of data science and statistical modeling to actuarial and insurance problems. The quality of his research has been recognized through awards that include the E. A. Lew Award, the Halmstad Memorial Prize, the Hachemeister Prize, and most recently, the Robert I. Mehr award. See https://emiliano-valdez.scholar.uconn.edu/ for more details
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