Enhancing reinsurance efficiency using index‐based instruments

Abstract

Purpose

Demonstrates the feasibility of, and introduces a practical approach to enhancing, reinsurance efficiency using index‐based instruments.

Design/methodology/approach

First reviews the general mathematical framework of reinsurance optimization. Next, illustrates how index‐based instruments can potentially enhance reinsurance efficiency through a simple yet self‐contained example. The simplicity allows the analytical examination of the cost and benefits of an index‐based contract. Finally, introduces a real‐world model that optimizes index‐based reinsurance instruments using the genetic algorithm.

Findings

Identifies the key factors that determine the efficiency of index‐based reinsurance contracts and demonstrates that, in the property catastrophe reinsurance market, the combined effect of these factors frequently allows the construction of an index‐based hedging program that is more efficient than a traditional excess‐of‐loss reinsurance contract. A robust optimization model based on the genetic algorithm is introduced and shown to be effective in optimizing index‐based reinsurance contracts.

Research limitations/implications

Most financial optimization procedures are subject to parameter risk, which can adversely affect the robustness of their solutions. The reinsurance optimization approach presented in this paper is not completely immune from this problem. It remains a challenging problem for actuarial researchers and practitioners.

Practical implications

The concept and method proposed in this paper can be applied to designing real‐world reinsurance programs.

Originality/value

This paper makes two contributions to the risk finance literature: a systematic approach for evaluating the costs and benefits of index‐based reinsurance instruments, and an innovative and practical model for optimizing reinsurance efficiency.

Citation

Zeng, L. (2005), "Enhancing reinsurance efficiency using index‐based instruments", Journal of Risk Finance, Vol. 6 No. 1, pp. 6-16. https://doi.org/10.1108/15265940510574727