基于投资的再保险定价公式

从系统的观点出发,把保险公司的赔付情况与投资收益相结合,对比例再保险和超额损失再保险,建立了在投资背景下它们应满足的线性正倒向随机微分方程.根据一类特殊线性倒向随机微分方程的显式解,给出了基于投资的再保险定价公式,为保险公司厘订再保险保费提供了新的方法.     

最优再保险及投资组合策略问题

为规避风险的巨大波动,保险公司会将承保的理赔进行分保,即再保险.假定再保险公司采用方差保费准则从保险公司收取保费.应用扩散逼近模型,刻画了保险公司有再保险控制下的资本盈余.另外,保险公司的盈余允许投资到利率、股票等金融市场.通过控制再保险及投资组合策略,研究了最小破产概率.应用动态规划方法(Hamilton-Jacobi-Bellman方程),对最小破产概率、最优再保险及投资组合策略给出了明晰解答,并给出了数值直观分析.     

基于时滞效应的随机微分投资与比例再保险博弈

金融市场不断发展,激烈的市场竞争使得相对绩效比较在保险机构的业绩评估中占据越来越重要的地位。考虑历史业绩对公司决策的影响,引入时滞效应,研究时滞效应对具有竞争关系公司之间最优投资策略和最优再保险策略的影响。运用随机最优控制和微分博弈理论,针对Cramér-Lundberg模型,得到了均衡投资和再保险策略,给出了值函数的显式解;然后进一步针对近似扩散过程,求得指数效用下均衡投资策略和比例再保险策略的显式表达。通过数值算例,分析了最优均衡策略随模型各重要参数的动态变化。结论显示:保险公司在决策时是否将时滞信息纳入考虑之中将大大影响其投资和再保险行为。保险公司考虑较早时间财富值越多,其投资再保险行为就表现得越趋向于保守和谨慎;与之相反,如果保险公司对行业间的竞争越看重,其投资再保险策略就越倾向于冒险和激进。     

保险公司的最优投资与一般再保险策略

本文研究了在股票价格服从几何布朗运动的假设下,原保公司考虑再保险时的最优投资问题.运用动态规划和鞅方法,得到了一般最优控制问题所满足的HJB方程以及该方程的识别定理,并分别对比例再保险和超额再保险做了详细分析.     

最优再保险及投资组合策略问题北大核心

为规避风险的巨大波动,保险公司会将承保的理赔进行分保,即再保险.假定再保险公司采用方差保费准则从保险公司收取保费.应用扩散逼近模型,刻画了保险公司有再保险控制下的资本盈余.另外,保险公司的盈余允许投资到利率、股票等金融市场.通过控制再保险及投资组合策略,研究了最小破产概率.应用动态规划方法(Hamilton-Jacobi-Bellman方程),对最小破产概率、最优再保险及投资组合策略给出了明晰解答,并给出了数值直观分析.     

投资影响下的再保险策略

本文研究了投资影响下的再保险策略,利用有关的线性正倒向随机微分方程,获得投资影响下再保险的自留比例或自留额的计算式子.     

保险与再保险及市场对冲稳健均衡策略

假设保险公司的资本盈余过程服从复合Poisson风险跳过程,保险公司通过向再保险公司购买比例再保险来分散保险风险,保险公司和再保险公司均基于方差原则收取保险费率.两个公司都可以投资于金融市场,其中风险资产的价格过程服从几何布朗运动.假设保险公司和再保险公司都是模糊厌恶的且具有指数效用函数,基于保险公司与再保险公司加权终期财富效用最大化目标,利用动态规划原理,得到了两公司的稳健均衡比例再保险和投资组合策略的解析表达式.分析了均衡条件下的风险投资,再保险价格与保险公司自保险比例受不同参变量影响的变化特征.     

跳-扩散风险模型的最优投资和再保险策略

本文对跳-扩散风险模型,在赔付进行比例再保险,以及盈余投资于无风险资产和风险资产的条件下,研究使得最终财富的指数期望效用最大的最优投资和比例再保险策略.得到最优投资策略和最优再保险策略,以及最大指数期望效用函数的显式表达式,发现最优策略和值函数都受到无风险利率的影响.最后通过数值计算,得到最优投资和比例再保险策略,以及值函数与模型各个参数之间的关系.     

基于股票价格随机脉冲模型的保险人再保险和投资的最优动态组合选择

本文假设保险人可以进行再保险,并且允许其在金融市场中将资产投资于风险资产和无风险资产,其中风险资产价格采用随机脉冲模型来刻画.当目标是最大化在某一确定终止时刻所拥有财富的二次效用函数期望时,分别得到了超额损失再保险和比例再保险情况下保险人的再保险和投资最优动态选择的显式解和闭解.利用得到的显式解,考虑了金融风险和保险风险之间相关性对最优动态选择的影响,做了相关数值计算.     

扩散风险模型下再保险和投资对红利的影响

对扩散风险模型,研究了比例再保险和投资对红利的影响．在常数边界分红策略下,得到了使得期望贴现红利最大的最优比例再保险和投资策略的显示表达式,并得到最大期望贴现红利的显示表达式．最后,通过数值计算得到了再保险和投资对期望红利的影响,以及最优投资策略与各参数之间的关系．     

Optimality of excess-loss reinsurance under a mean–variance criterion

In this paper, we study an insurer’s reinsurance–investment problem under a mean–variance criterion. We show that excess-loss is the unique equilibrium reinsurance strategy under a spectrally negative Lévy insurance model when the reinsurance premium is computed according to the expected value premium principle. Furthermore, we obtain the explicit equilibrium reinsurance–investment strategy by solving the extended Hamilton–Jacobi–Bellman equation.     

Time-consistent reinsurance and investment strategies for mean–variance insurer under partial information

In this paper, based on equilibrium control law proposed by Björk and Murgoci (2010), we study an optimal investment and reinsurance problem under partial information for insurer with mean–variance utility, where insurer’s risk aversion varies over time. Instead of treating this time-inconsistent problem as pre-committed, we aim to find time-consistent equilibrium strategy within a game theoretic framework. In particular, proportional reinsurance, acquiring new business, investing in financial market are available in the market. The surplus process of insurer is depicted by classical Lundberg model, and the financial market consists of one risk free asset and one risky asset with unobservable Markov-modulated regime switching drift process. By using reduction technique and solving a generalized extended HJB equation, we derive closed-form time-consistent investment–reinsurance strategy and corresponding value function. Moreover, we compare results under partial information with optimal investment–reinsurance strategy when Markov chain is observable. Finally, some numerical illustrations and sensitivity analysis are provided.     

Optimal Investment-Reinsurance Strategy with Exchange Rate Risk under Variance Premium Principl

It is assumed that both an insurance company and a reinsurance company adopt the variance premium principle to collect premiums. Specifically, an insurance company is allowed to investment not only in a domestic risk-free asset and a risky asset, but also in a foreign risky asset. Firstly, we use a geometry Brownian motion to model the exchange rate risk, and assume that the insurance company could control the insurance risk by transferring the insurance business into the reinsurance company. Secondly, the stochastic dynamic programming principle is used to study the optimal investment and reinsurance problems in two situations. The first is a diffusion approximation risk model and the second is a classical risk model. The optimal investment and reinsurance strategies are obtained under these two situations. We also show that the exchange rate risk has a great impact on the insurance company's investment strategies, but has no effect on the reinsurance strategies. Finally, a sensitivity analysis of some parameters is provided.     

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??It is assumed that both an insurance company and a reinsurance company adopt the variance premium principle to collect premiums. Specifically, an insurance company is allowed to investment not only in a domestic risk-free asset and a risky asset, but also in a foreign risky asset. Firstly, we use a geometry Brownian motion to model the exchange rate risk, and assume that the insurance company could control the insurance risk by transferring the insurance business into the reinsurance company. Secondly, the stochastic dynamic programming principle is used to study the optimal investment and reinsurance problems in two situations. The first is a diffusion approximation risk model and the second is a classical risk model. The optimal investment and reinsurance strategies are obtained under these two situations. We also show that the exchange rate risk has a great impact on the insurance company's investment strategies, but has no effect on the reinsurance strategies. Finally, a sensitivity analysis of some parameters is provided.     

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??Under inflation influence, this paper investigate a stochastic differential game with reinsurance and investment. Insurance company chose a strategy to minimizing the variance of the final wealth, and the financial markets as a game ``virtual hand' chosen a probability measure represents the economic ``environment' to maximize the variance of the final wealth. Through this double game between the insurance companies and the financial markets, get optimal portfolio strategies. When investing, we consider inflation, the method of dealing with inflation is: Firstly, the inflation is converted to the risky assets, and then constructs the wealth process. Through change the original based on the mean-variance criteria stochastic differential game into unrestricted cases, then application linear-quadratic control theory obtain optimal reinsurance strategy and investment strategy and optimal market strategy as well as the closed form expression of efficient frontier are obtained; finally get reinsurance strategy and optimal investment strategy and optimal market strategy as well as the closed form expression of efficient frontier for the original stochastic differential game.     

Optimal investment–reinsurance strategies with state dependent risk aversion and VaR constraints in correlated markets

In this paper, we investigate the optimal time-consistent investment–reinsurance strategies for an insurer with state dependent risk aversion and Value-at-Risk (VaR) constraints. The insurer can purchase proportional reinsurance to reduce its insurance risks and invest its wealth in a financial market consisting of one risk-free asset and one risky asset, whose price process follows a geometric Brownian motion. The surplus process of the insurer is approximated by a Brownian motion with drift. The two Brownian motions in the insurer’s surplus process and the risky asset’s price process are correlated, which describe the correlation or dependence between the insurance market and the financial market. We introduce the VaR control levels for the insurer to control its loss in investment–reinsurance strategies, which also represent the requirement of regulators on the insurer’s investment behavior. Under the mean–variance criterion, we formulate the optimal investment–reinsurance problem within a game theoretic framework. By using the technique of stochastic control theory and solving the corresponding extended Hamilton–Jacobi–Bellman (HJB) system of equations, we derive the closed-form expressions of the optimal investment–reinsurance strategies. In addition, we illustrate the optimal investment–reinsurance strategies by numerical examples and discuss the impact of the risk aversion, the correlation between the insurance market and the financial market, and the VaR control levels on the optimal strategies.