The fundamental theorem of mutual insurance

The essence of mutual insurance is the notion that re-distributing risk in a pool of risks is more beneficial than taking the risk alone. Interpreting ‘more beneficial’ as an increase in utility and considering sequences of exchangeable risks, we are able to formalize this notion from the policyholder’s perspective and demonstrate its validity for various alternative preference functionals (e.g., expected utility, Choquet expected utility, and distortion risk measures). To obtain this result, we exploit that for a sequence of exchangeable risks the corresponding sequence of arithmetical averages is a reversed martingale.We conclude that pooling risks is fundamental for understanding the mechanisms of insurance because it favourably affects the utility of policyholders, and we refer to this phenomenon as the ‘utility-improving effect of risk pooling’. Moreover, we demonstrate that the utility of the policyholder is (strictly) increasing with the size of the risk pool.     

Redistribution of longevity risk: The effect of heterogeneous mortality beliefs

Existing literature regarding the natural hedge potential that arises from combining different longevity-linked liabilities typically does not address the question how changes in the liability mix can be obtained. We consider firms who aim to exploit the benefits of natural hedge potential by redistributing their risks, and characterize the risk redistributions that will arise when the parties bargain for a redistribution of risk that weakly benefits them all. We analyze the effects of heterogeneity in the beliefs regarding the probability distribution of future mortality rates on the properties of these risk redistributions, and provide a numerical illustration for a case where an insurer with a portfolio of term assurance contracts and a pension fund with a portfolio of life annuities redistribute their risks.     

Characterization of acceptance sets for co-monotone risk measures

We present a geometric characterization of acceptance sets for monotone, co-monotone and convex risk measures on finite state spaces. Geometrically, such acceptance sets can be represented by convex polygons with edges only on certain hyperplanes. We also provide some lower dimensional examples, and study acceptance sets for value at risk and expected shortfall.     

Haezendonck–Goovaerts risk measure with a heavy tailed loss

Recently Haezendonck–Goovaerts (H–G) risk measure has received much attention in (re)insurance and portfolio management. Some nonparametric inferences have been proposed in the literature. When the loss variable does not have enough moments, which depends on the involved Young function, the nonparametric estimator in Ahn and Shyamalkumar (2014) has a nonnormal limit, which challenges interval estimation. Motivated by the fact that many loss variables in insurance and finance could have a heavier tail such as an infinite variance, this paper proposes a new estimator which estimates the tail by extreme value theory and the middle part nonparametrically. It turns out that the proposed new estimator always has a normal limit regardless of the tail heaviness of the loss variable. Hence an interval with asymptotically correct confidence level can be obtained easily either by the normal approximation method via estimating the asymptotic variance or by a bootstrap method. A simulation study and real data analysis confirm the effectiveness of the proposed new inference procedure for estimating the H–G risk measure.     

On the construction of non-affine jump-diffusion models

We describe a method for construction of jump analogues of certain one-dimensional diffusion processes satisfying solvable stochastic differential equations. The method is based on the reduction of the original stochastic differential equations to the ones with linear diffusion coefficients, which are reducible to the associated ordinary differential equations, by using the appropriate integrating factor processes. The analogues are constructed by means of adding the jump components linearly into the reduced stochastic differential equations. We illustrate the method by constructing jump analogues of several diffusion processes and expand the notion of market price of risk to the resulting non-affine jump-diffusion models.     

基于权重比的民航飞行员安全行为指标权重算法

确定飞行员安全行为指标的权重,对发现民航飞行员飞行安全风险的短板,提高民航飞行安全性具有重要意义.基于指标权重比,提出了一种飞行员安全行为指标权重算法.并以此算法分析了职业安全意识、飞行情景意识、特情应变能力以及机组资源管理能力等指标对飞行员安全行为的影响程度,研究可为飞行员安全行为风险管理提供依据,对安全飞行具有积极的指导意义.     

基于时变SJC-Copula对商品期货市场间风险传染的探究

分别选取WIND商品指数和CRB指数作为衡量我国商品期货市场及国际商品期货市场综合价格的指标,利用时变SJC-Copula模型构建两者之间的动态相依结构,通过动态的尾部相关系数来探究我国商品期货市场与国际市场间的尾部相关性.实证结果表明,我国商品期货市场与国际市场间的上尾相关性要强于下尾相关性,即当商品期货价格上涨时,两个市场间更易发生风险传染.     

考虑事故风险损失的爆炸物品经济订货批量模型研究

爆炸物品在储存过程中存在发生爆炸事故,从而给人类和环境带来伤害的可能,因此在对爆炸物品进行采购决策时必需考虑由此带来的风险损失.在给出爆炸物品事故风险损失度量方法的基础上,建立了爆炸物品的经济订货批量模型,证明了模型存在唯一最优解,并给出了模型的求解步骤,为相关企业合理制定采购决策提供了理论依据.数字算例分析了事故概率、赔偿标准、单位库存费、单次采购费对最优批量的影响,比较了考虑事故风险损失与否时的最优批量,结果表明,当事故概率或赔偿标准较高时,两者对应的最优批量差异明显.这也说明,当事故概率或赔偿标准达到一定程度时,考虑事故风险损失是十分必要的.