Nonparametric Estimation of Optimal Retention for Reinsurance Under Tail Risk Criterion

• Activity Number: 371
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
• Sponsor: IMS
• Author(s): Desale Habtzghi*+ and Dale Borowiak
• Companies: University of Akron and The University of Akron
• Keywords: Optimal retention ; Stop-loss reinsurance ; Value-at risk ; Conditional tail expectation ; Nonparametric

Abstract

Tail risk measures, value-at risk (VaR) and conditional tail expectation (CTE) are applied to stop-loss reinsurance with the premium structure with the goal of searching for optimal retention. Based on these criteria we introduce a nonparametric approach for estimation of optimal retention and corresponding tail risk measures in a stop-loss reinsurance. Our approach can provide good approximation to claim data when the parametric method is inappropriate due restricted assumptions on the distributions. We evaluate the performance of our estimators via simulation studies and an illustration based on lawsuit claims is presented.