Events Calendar
DSAS Department Meeting
April 25, 2019

PhD Thesis Proposal - Public Lecture -Wenjun Jiang

Wednesday, February 7, 2018
12:00 pm
Middlesex College (MC)
Room: 108

Title: Some recent developments on Pareto-optimal reinsurance

Abstract:  The design of optimal reinsurance has been extensively studied in the actuarial literature. Different results are obtained from the insurer's point of view. However, it is understandable that a reinsurance contract which is attractive to one party may not be acceptable by the other party. We treat insurance-reinsurance problem as a two-person bargaining problem, and explore the solution by bridging game theory and actuarial theory. Many existing classical solutions for cooperative games, such as Nash equilibrium, Kalai-Smorodinsky solutions, are all located on the Pareto efficient frontier. Therefore, we study the Pareto-optimal reinsurance in our projects.

In the first project, we extended the geometric approach which is first applied by Cheung (2010) to study the Pareto-optimal reinsurance when both the insurer and the reinsurer adopt Value-at-Risk as their risk measures. The functional form and the parameter values of optimal reinsurance treaties can be determined efficiently under this setting.

In the second project, we extend our analysis from Value-at-Risk to a bigger family of risk measure -- distortion risk measure. To make it more realistic, we assume both participants can impose their own risk tolerance levels. Some popular methods, like generalized Neyman-Pearson, Lagrange multiplier and optimal control method, can be used in deriving the closed-form of the optimal reinsurance ceded functions.
Currently, we are trying to explore the Pareto-optimal reinsurance in the context of expected utility, but under heterogeneous beliefs. The index-based reinsurance is also under study. Practically, we will simulate the earthquake loss frequency and severity from models developed using state-of-art civil engineering models. Then we will apply our theoretical results to the simulated loss data and obtain the optimal reinsurance contracts.

Supervisors: Jiandong Ren & Hanping Hong

Erin Woolnough
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