Reinsurance Problem Research Articles

Optimal reinsurance policy under a new distortion risk measure

Distortion risk measures play an essential role in the fields of finance and risk management. In this paper, we present a new distortion risk measure with mixed methods. We then investigate the optimal reinsurance problem under the new risk measure and the closed-form solutions of optimal reinsurance policies are obtained. As special cases of the new distortion risk measure, VaR and GlueVaR are considered in the application of risk management.

Dynamic reinsurance in discrete time minimizing the insurer's cost of capital

In the classical static optimal reinsurance problem, the cost of capital for the insurer's risk exposure determined by a monetary risk measure is minimized over the class of reinsurance treaties represented by increasing Lipschitz retained loss functions. In this paper, we consider a dynamic extension of this reinsurance problem in discrete time which can be viewed as a risk-sensitive Markov Decision Process. The model allows for both insurance claims and premium income to be stochastic and operates with general risk measures and premium principles. We derive the Bellman equation and show the existence of a Markovian optimal reinsurance policy. Under an infinite planning horizon, the model is shown to be contractive and the optimal reinsurance policy to be stationary. The results are illustrated with examples where the optimal policy can be determined explicitly.

Optimal reinsurance under the α-maxmin mean-variance criterion

This paper studies an optimal reinsurance problem under the α-maximin mean-variance criterion proposed in Li et al. (2016). We generalize (Li et al., 2016) by considering a full range of ambiguity preferences and allowing for general form reinsurance contracts. For equilibrium reinsurance strategies, we find that the excess-of-loss form is unique for ambiguity-averse preferences but may not be optimal or unique for ambiguity-loving preferences. An insurer who is more ambiguous to the reference measure retains less risk if she is ambiguity-averse but does not necessarily retain more risk if she is ambiguity-loving and her ambiguity level is high. Our finding suggests that a highly ambiguity-loving preference may only manifest when the ambiguity level is very low, and hence, consistent with empirical studies, demonstrates that decision makers can be ambiguity-loving if they consider themselves more knowledgeable or competent than the other players.

Minimizing spectral risk measures applied to Markov decision processes

We study the minimization of a spectral risk measure of the total discounted cost generated by a Markov Decision Process (MDP) over a finite or infinite planning horizon. The MDP is assumed to have Borel state and action spaces and the cost function may be unbounded above. The optimization problem is split into two minimization problems using an infimum representation for spectral risk measures. We show that the inner minimization problem can be solved as an ordinary MDP on an extended state space and give sufficient conditions under which an optimal policy exists. Regarding the infinite dimensional outer minimization problem, we prove the existence of a solution and derive an algorithm for its numerical approximation. Our results include the findings in Bäuerle and Ott (Math Methods Oper Res 74(3):361–379, 2011) in the special case that the risk measure is Expected Shortfall. As an application, we present a dynamic extension of the classical static optimal reinsurance problem, where an insurance company minimizes its cost of capital.

Optimal Investment and Proportional Reinsurance in a Regime-Switching Market Model under Forward Preferences

In this paper, we study the optimal investment and reinsurance problem of an insurance company whose investment preferences are described via a forward dynamic exponential utility in a regime-switching market model. Financial and actuarial frameworks are dependent since stock prices and insurance claims vary according to a common factor given by a continuous time finite state Markov chain. We construct the value function and we prove that it is a forward dynamic utility. Then, we characterize the optimal investment strategy and the optimal proportional level of reinsurance. We also perform numerical experiments and provide sensitivity analyses with respect to some model parameters.

Equilibrium investment-reinsurance strategy with delay and common shock dependence under Heston's SV model

This paper investigates an investment and reinsurance problem with delay and common shock dependence under the mean-variance utility framework. We first use Heston's SV model to depict the financial market and two-dimensional Poisson process with common shock dependence to characterize the surplus process. We then introduce the past performance and use it to derive the wealth process depicted by the stochastic delay differential equation. Applying the stochastic control theory within the framework of the game theory, and stochastic control theory with delay, we derive an extended Hamilton-Jacobi-Bellman equation with delay. By solving the equation, we obtain the equilibrium strategy and the corresponding equilibrium value function. We also provide a numerical example to analyze the effects of delay parameters and co-shocks parameters on equilibrium strategy and explain why such effects occur.

Distributionally Robust Reinsurance With Value-at-Risk and Conditional Value-at-Risk

A basic assumption of the classic reinsurance model is that the distribution of the loss is precisely known. In practice, only partial information is available for the loss distribution due to the lack of data and estimation error. We study a distributionally robust reinsurance problem by minimizing the maximum Value-at-Risk (or the worst-case VaR) of the total retained loss of the insurer for all loss distributions with known mean and variance. Our model handles typical stop-loss reinsurance contracts. We show that a three-point distribution achieves the worst-case VaR of the total retained loss of the insurer, from which the closed-form solutions of the worst-case distribution and optimal deductible are obtained. Moreover, we show that the worst-case Conditional Value-at-Risk of the total retained loss of the insurer is equal to the worst-case VaR, and thus the optimal deductible is the same in both cases.

Optimal Surplus-Dependent Reinsurance under Regime-Switching in a Brownian Risk Model

In this paper, we consider a company that wishes to determine the optimal reinsurance strategy minimising the total expected discounted amount of capital injections needed to prevent the ruin. The company’s surplus process is assumed to follow a Brownian motion with drift, and the reinsurance price is modelled by a continuous-time Markov chain with two states. The presence of regime-switching substantially complicates the optimal reinsurance problem, as the surplus-independent strategies turn out to be suboptimal. We develop a recursive approach that allows to represent a solution to the corresponding Hamilton–Jacobi–Bellman (HJB) equation and the corresponding reinsurance strategy as the unique limits of the sequence of solutions to ordinary differential equations and their first- and second-order derivatives. Via Ito’s formula, we prove the constructed function to be the value function. Two examples illustrate the recursive procedure along with a numerical approach yielding the direct solution to the HJB equation.

Risk transference constraints in optimal reinsurance

This paper deals with optimal reinsurance problem and involves goals of both insurer and reinsurer. An important novelty may be incorporation of background risk that reinsurer uses in order to diversify (or hedge) risk ceded by insurer. Accordingly, general methods to prevent reinsurer moral hazard must be extended, and a new constraint must be satisfied by selected reinsurance contract, namely, the reinsurer increment of risk must be lower than contract premium. Simultaneously, since contract must be attractive to insurer too, the contract premium must be lower than insurer risk reduction. Integrating both ideas, the contract premium must be higher than reinsurer risk growth and lower than insurer risk mitigation. Bearing in mind both requirements, that is, protection against moral hazard and spread containing contract premium, optimal reinsurance problem is studied under very general conditions about involved risk measures and premium principles, general solutions are provided, and a practical illustrative example is presented.

Optimal Reinsurance and Investment Strategy with Delay in Heston’s SV Model

In this paper, we consider an optimal investment and proportional reinsurance problem with delay, in which the insurer’s surplus process is described by a jump-diffusion model. The insurer can buy proportional reinsurance to transfer part of the insurance claims risk. In addition to reinsurance, she also can invests her surplus in a financial market, which is consisted of a risk-free asset and a risky asset described by Heston’s stochastic volatility (SV) model. Considering the performance-related capital flow, the insurer’s wealth process is modeled by a stochastic differential delay equation. The insurer’s target is to find the optimal investment and proportional reinsurance strategy to maximize the expected exponential utility of combined terminal wealth. We explicitly derive the optimal strategy and the value function. Finally, we provide some numerical examples to illustrate our results.

Optimal Time-Consistent Investment and Reinsurance Strategies with Default Risk and Delay under Heston’s SV Model

Considering the influence of past information on the decision-making of insurers, the correlation between the insurance businesses owned by insurers, and the possible default faced by insurers, we investigate the mean-variance investment and reinsurance problem with the default risk, delay, and common shock dependence. We characterize the insurance market by two-dimensional dependent claims, the financial market by the Heston SV model, and default risk by reduced-form approach and then obtain the evolution equation of the insurer’s wealth. Based on the introduction of time delay, the insurer’s wealth dynamics characterized by a stochastic delay differential equation are obtained. Furthermore, applying stochastic control theory within the game-theoretic framework and stochastic control theory with delay, we derive optimal time-consistent investment and reinsurance strategies, as well as equilibrium value function and equilibrium efficient frontier. Finally, we use a numerical example to analyze the influence of parameters on the time-consistent equilibrium strategies and give an economic explanation.

Mean-variance problem for an insurer with dependent risks and stochastic interest rate in a jump-diffusion market

In this paper, we study an optimal investment and reinsurance problem in which the interest rate is driven by the Vasicek process and two dependent classes of insurance business are correlated through a common shock component. The goal of insurer is to find an optimal investment-reinsurance strategy to minimize the variance of terminal net wealth for a given expected terminal net wealth. By using the linear-quadratic optimal control theory and the corresponding Hamilton-Jacobi-Bellman (HJB) equation, the closed-form expressions for the value function and optimal strategies are obtained under the special case of perfect correlation between the bond and stock processes. We present that the solution of the HJB equation is no longer a classical solution, but a viscosity solution due to the non-negativity constraint of the reinsurance strategy. Furthermore, the efficient strategies and efficient frontier are derived explicitly. Finally, we explore some numerical examples to show the influence of model parameters on the optimal investment and reinsurance strategies.

Optimal Reinsurance Problem under Fixed Cost and Exponential Preferences

We investigate an optimal reinsurance problem for an insurance company taking into account subscription costs: that is, a constant fixed cost is paid when the reinsurance contract is signed. Differently from the classical reinsurance problem, where the insurer has to choose an optimal retention level according to some given criterion, in this paper, the insurer needs to optimally choose both the starting time of the reinsurance contract and the retention level to apply. The criterion is the maximization of the insurer’s expected utility of terminal wealth. This leads to a mixed optimal control/optimal stopping time problem, which is solved by a two-step procedure: first considering the pure-reinsurance stochastic control problem and next discussing a time-inhomogeneous optimal stopping problem with discontinuous reward. Using the classical Cramér–Lundberg approximation risk model, we prove that the optimal strategy is deterministic and depends on the model parameters. In particular, we show that there exists a maximum fixed cost that the insurer is willing to pay for the contract activation. Finally, we provide some economical interpretations and numerical simulations.

Pareto-optimal Reinsurance with Default Risk and Solvency Regulation

This paper studies an optimal reinsurance problem of Pareto-optimality when the contract is subject to default of the reinsurer. We assume that the reinsurer can invest a share of its wealth in a risky asset and default occurs when the reinsurer's end-of-period wealth is insufficient to cover the indemnity. We show that without the solvency regulation, the optimal indemnity function is of excess-of-loss form, regardless of the investment decision. We model solvency regulation as a constraint on the probability of default. Under solvency regulation, by assuming the investment decision remains the same as in the unconstrained solution, the optimal indemnity function is derived element-wisely. Partial results are given when the indemnity function and investment decision are jointly constrained by the solvency regulation. Numerical examples are provided to illustrate the implications of our results and the sensitivity of the solutions to the model parameters.

Time-consistent investment-reinsurance strategy with a defaultable security under ambiguous environment

<p style='text-indent:20px;'>This paper considers an investment and reinsurance problem with a defaultable security for an insurer in an environment with parameter uncertainties. Suppose that the insurer is ambiguous about the insurance claims. Specifically, the insurance claim is exponentially distributed and the rate parameter is uncertain. The insurer is allowed to invest in a financial market consisting of a risk-free bond, a stock whose price process satisfies the Heston's SV model and a defaultable bond. Moreover, the insurer is allowed to purchase proportional reinsurance and aims to maximize the smooth ambiguity utility proposed in Klibanoff et al. [<xref ref-type="bibr" rid="b15">15</xref>]. By applying stochastic control approach, we establish the extended HJB system and derive the time-consistent investment-reinsurance strategy for the post-default case and the pre-default case, respectively. Finally, a sensitivity analysis is provided to illustrate the effects of model parameters on the equilibrium reinsurance-investment strategy under the smooth ambiguity.</p>

Optimal investment and reinsurance to minimize the probability of drawdown with borrowing costs

<p style='text-indent:20px;'>We study the optimal investment and reinsurance problem in a risk model with two dependent classes of insurance businesses, where the two claim number processes are correlated through a common shock component and the borrowing rate is higher than the lending rate. The objective is to minimize the probability of drawdown, namely, the probability that the value of the wealth process reaches some fixed proportion of its maximum value to date. By the method of stochastic control theory and the corresponding Hamilton-Jacobi-Bellman equation, we investigate the optimization problem in two different cases and divide the whole region into four subregions. The explicit expressions for the optimal investment/reinsurance strategies and the minimum probability of drawdown are derived. We find that when wealth is at a relatively low level (below the borrowing level), it is optimal to borrow money to invest in the risky asset; when wealth is at a relatively high level (above the saving level), it is optimal to save more money; while between them, the insurer is willing to invest all the wealth in the risky asset. In the end, some comparisons are presented to show the impact of higher borrowing rate and risky investment on the optimal results.</p>

Optimal investment and reinsurance problem toward joint interests of the insurer and the reinsurer under default risk

In this article, we study the optimal investment and reinsurance problem involving a defaultable security for a group which holds shares of both an insurance company and a reinsurance company. Assuming that the claim process is described by a Brownian motion with drift, and the insurer can purchase proportional reinsurance and invest in a financial market consisting of a risk-free asset, a risky asset and a defaultable bond. Moreover, the reinsurer is allowed to invest in a risk-free asset and a stock. With both the insurer and the reinsurer taken into account, the group aims to maximize the expected exponential utility of the weighted sum of the insurer’s and the reinsurer’s terminal wealth. By using the dynamic programming approach, we study the pre-default case and post-default case, respectively. In both cases, the closed-form expressions for the optimal strategies and the corresponding value functions are derived. Finally, numerical examples are given to illustrate the effects of model parameters on the optimal strategies.

Time-Consistent Investment and Reinsurance Strategies for Mean-Variance Insurers under Stochastic Interest Rate and Stochastic Volatility

This paper studies the time-consistent optimal investment and reinsurance problem for mean-variance insurers when considering both stochastic interest rate and stochastic volatility in the financial market. The insurers are allowed to transfer insurance risk by proportional reinsurance or acquiring new business, and the jump-diffusion process models the surplus process. The financial market consists of a risk-free asset, a bond, and a stock modelled by Heston’s stochastic volatility model. Interest rate in the market is modelled by the Vasicek model. By using extended dynamic programming approach, we explicitly derive equilibrium reinsurance-investment strategies and value functions. In addition, we provide and prove a verification theorem and then prove the solution we get satisfies it. Moreover, sensitive analysis is given to show the impact of several model parameters on equilibrium strategy and the efficient frontier.

Optimal dividends and reinsurance with capital injection under thinning dependence

In this paper, we adopt the variance premium principle to investigate the problem of optimal dividends and reinsurance in a diffusion approximation risk model with thinning-dependence structure. We first study the optimal problem without capital injection. We then consider the incorporation of forced capital injection into the model whenever the reserve level drops below zero. We finally turn to the general problem in which capital injection is allowed but not compulsory. For the three optimal problems, we apply the technique of stochastic control theory to obtain closed-form expressions for the optimal strategies and the corresponding value functions for two classes of insurance business with thinning dependence. Under the assumption of non cheap reinsurance, we obtain results that are quite different from those in the case of cheap reinsurance for both bounded and unbounded dividend rates. Furthermore some numerical examples are presented to show the effect of parameter values on the optimal policies.

Robust optimal investment and reinsurance for an insurer with inside information

This paper studies a robust optimal investment–reinsurance problem for an insurer who possesses inside information on the financial market and the insurance business under model uncertainty. The insurer’s surplus process and the risky asset process in the financial market are assumed to be correlated jump diffusion processes with random coefficients. The inside information is modelled by a general random variable related to the future realizations of the surplus process and the risky asset process. Under the criterion of expected utility maximization, the optimal investment–reinsurance problem with inside information is transformed into an adapted stochastic control problem. By incorporating Knightian uncertainty into the model, we establish an adapted stochastic differential game problem with a nonstandard performance functional, which aims to select the robust optimal investment–reinsurance strategy for the insurer with inside information. The stochastic maximum principles are adopted to derive a characterization of the optimal strategy. Some interesting special cases are discussed and the corresponding optimal strategies are derived.