ALM for insurers with multiple underwriting lines and portfolio constraints: a Lagrangian duality approach

Camilo Castillo, Rafael Serrano

Research output: Contribution to journalArticlepeer-review

Abstract

We investigate how an insurance firm can optimally allocate its assets to back up liabilities from multiple non-life business lines. The insurance risks are modeled by a multidimensional jump-diffusion process that accounts for simultaneous claims in different insurance lines with policy limits. We use Lagrangian convex duality techniques to derive optimal investment-underwriting strategies that maximize the expected utility from dividends and final wealth over a finite horizon. We examine how risk aversion, prudence, portfolio constraints, and multivariate insurance risk affect the firm’s earnings retention. We obtain explicit solutions for optimal strategies under constant relative risk aversion preferences. Finally, we illustrate our results with numerical examples and show the impact of co-integration for asset-liability management with multiple sources of insurance risk.

Original languageEnglish (US)
Article number225
JournalComputational and Applied Mathematics
Volume43
Issue number4
DOIs
StatePublished - Jun 2024

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics

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