Optimal Reinsurance Strategy Research Articles

Determining the Optimal Investment and Reinsurance Strategy of Insurance Company Based on Stochastic Differential Game

In this paper, we discuss how to determine the optimal investment portfolio and reinsurance strategy of insurance company based on zero-sum stochastic differential game between the market and the insurer. We extend Zhang and Siu (2009)’s model by (1) including a risk-free asset, (2) considering risky assets instead of only one risky asset and (3) discussing the case of power utility function besides exponential utility when the wealth process of an insurance company is a diffusion process. We establish the Hamilton-Jacobi-Bellman-Issacs equations and obtain the optimal solutions of the amount invested in risky assets and retention of reinsurance. Our results show that the optimal solution is positively correlated to time but independent of the wealth of insurer, when the utility function of terminal wealth is exponential. However, the optimal solution is uncorrelated to time and is increasing function of the wealth of the insurer in the case of power utility function. Our results also show that the risk-free interest rate will affect the strategy of investment and reinsurance.

Optimal reinsurance strategy under fixed cost and delay

We consider an optimal reinsurance strategy in which the insurance company (1) monitors the dynamics of its surplus process, (2) optimally chooses a time to begin negotiating with a reinsurer to buy quota-share, or proportional, reinsurance, which introduces an implementation delay (denoted by Δ ≥ 0 ), (3) chooses the optimal proportion at the beginning of the negotiation period, and (4) pays a fixed transaction cost when the contract is signed ( Δ units of time after negotiation begins). This setup leads to a combined problem of optimal stopping and stochastic control. We obtain a solution for the value function and the corresponding optimal strategy, while demonstrating the solution procedure in detail. It turns out that the optimal continuation region is a union of two intervals, a rather rare occurrence in optimal stopping. Numerical examples are given to illustrate our results and we discuss relevant economic insights from this model.

Optimal Dynamic Reinsurance

We consider a classical surplus process where the insurer can choose a different level of reinsurance at the start of each year. We assume the insurer’s objective is to minimise the probability of ruin up to some given time horizon, either in discrete or continuous time. We develop formulae for ruin probabilities under the optimal reinsurance strategy, i.e. the optimal retention each year as the surplus changes and the period until the time horizon shortens. For our compound Poisson process, it is not feasible to evaluate these formulae, and hence determine the optimal strategies, in any but the simplest cases. We show how we can determine the optimal strategies by approximating the (compound Poisson) aggregate claims distributions by translated gamma distributions, and, alternatively, by approximating the compound Poisson process by a translated gamma process.

Optimal Dynamic Reinsurance

We consider a classical surplus process where the insurer can choose a different level of reinsurance at the start of each year. We assume the insurer’s objective is to minimise the probability of ruin up to some given time horizon, either in discrete or continuous time. We develop formulae for ruin probabilities under the optimal reinsurance strategy, i.e. the optimal retention each year as the surplus changes and the period until the time horizon shortens. For our compound Poisson process, it is not feasible to evaluate these formulae, and hence determine the optimal strategies, in any but the simplest cases. We show how we can determine the optimal strategies by approximating the (compound Poisson) aggregate claims distributions by translated gamma distributions, and, alternatively, by approximating the compound Poisson process by a translated gamma process.

Optimal combinational quota‐share and excess‐of‐loss reinsurance policies in a dynamic setting

AbstractIn this paper, we describe a large insurance company's surplus by a Brownian motion with positive drift, which is the approximation of a classical risk process. The problem of minimizing the probability of ruin by controlling the combinational quota‐share and excess‐of‐loss reinsurance strategy is considered. We show that the optimal combinational reinsurance strategy must be the pure excess‐of‐loss reinsurance strategy. Moreover, we give an explicit solution for the optimal reinsurance strategy. Copyright © 2006 John Wiley & Sons, Ltd.

Benchmark and mean-variance problems for insurers

We consider the classical Cramer-Lundberg model with dynamic proportional reinsurance and solve the problem of finding the optimal reinsurance strategy which minimizes the expected quadratic distance of the risk reserve to a given benchmark. This result is extended to a mean-variance problem.

Optimal dynamic reinsurance

We consider a risk process modelled as a compound Poisson process. We find the optimal dynamic reinsurance strategy to minimize infinite time ruin probability in a general setup. A closer look on special types of reinsurance: Proportional, unlimited and limited excess of loss reinsurance shows different features of optimal reinsurance strategies.

An optimality of change loss type strategy

A reinsurance problem is presented as a convex programming problem in Hilbert setup. The explicit form of the solution as well as the optimal reinsurance strategy is obtained.

A dynamic reinsurance theory

In this paper we present a technique that can be used by the insurer, who reinsured part of his risk by means of a proportional stop-loss contract, to evaluate his residual risk position. Part of this technique consists of the calculation of the optimal reinsurance strategy. We also show how this same technique can be used by the reinsurer to evaluate his risk position.