Optimal reinsurance/investment problems for general insurance models

TL;DR

This paper investigates a complex utility optimization problem for insurance companies, incorporating stochastic models for reserves, investments, reinsurance, and market factors, providing new conditions for solvability.

Contribution

It introduces a novel approach to optimal reinsurance and investment with proportional reinsurance constraints using duality methods and backward stochastic differential equations.

Findings

Derived necessary and sufficient conditions for problem well-posedness.

Extended duality methods to non-Markovian insurance models.

Established solvability criteria for the optimization problem.

Abstract

In this paper the utility optimization problem for a general insurance model is studied. The reserve process of the insurance company is described by a stochastic differential equation driven by a Brownian motion and a Poisson random measure, representing the randomness from the financial market and the insurance claims, respectively. The random safety loading and stochastic interest rates are allowed in the model so that the reserve process is non-Markovian in general. The insurance company can manage the reserves through both portfolios of the investment and a reinsurance policy to optimize a certain utility function, defined in a generic way. The main feature of the problem lies in the intrinsic constraint on the part of reinsurance policy, which is only proportional to the claim-size instead of the current level of reserve, and hence it is quite different from the optimal investment/consumption problem with constraints in finance. Necessary and sufficient conditions for both well posedness and solvability will be given by modifying the ``duality method'' in finance and with the help of the solvability of a special type of backward stochastic differential equations.