Behavioral optimal insurance

The present work studies the optimal insurance policy offered by an insurer adopting a proportional premium principle to an insured whose decision-making behavior is modeled by Kahneman and Tversky’s Cumulative Prospect Theory with convex probability distortions. We show that, under a fixed premium rate, the optimal insurance policy is a generalized insurance layer (that is, either an insurance layer or a stop–loss insurance). This optimal insurance decision problem is resolved by first converting it into three different sub-problems similar to those in Jin and Zhou (2008); however, as we now demand a more regular optimal solution, a completely different approach has been developed to tackle them. When the premium is regarded as a decision variable and there is no risk loading, the optimal indemnity schedule in this form has no deductibles but a cap; further results also suggests that the deductible amount will be reduced if the risk loading is decreased. As a whole, our paper provides a theoretical explanation for the popularity of limited coverage insurance policies in the market as observed by many socio-economists, which serves as a mathematical bridge between behavioral finance and actuarial science.     

Behavioral optimal insurance

The present work studies the optimal insurance policy offered by an insurer adopting a proportional premium principle to an insured whose decision-making behavior is modeled by Kahneman and Tversky’s Cumulative Prospect Theory with convex probability distortions. We show that, under a fixed premium rate, the optimal insurance policy is a generalized insurance layer (that is, either an insurance layer or a stop–loss insurance). This optimal insurance decision problem is resolved by first converting it into three different sub-problems similar to those in Jin and Zhou (2008); however, as we now demand a more regular optimal solution, a completely different approach has been developed to tackle them. When the premium is regarded as a decision variable and there is no risk loading, the optimal indemnity schedule in this form has no deductibles but a cap; further results also suggests that the deductible amount will be reduced if the risk loading is decreased. As a whole, our paper provides a theoretical explanation for the popularity of limited coverage insurance policies in the market as observed by many socio-economists, which serves as a mathematical bridge between behavioral finance and actuarial science.     

Optimal insurance design in the presence of exclusion clauses

The present work studies the design of an optimal insurance policy from the perspective of an insured, where the insurable loss is mutually exclusive from another loss that is denied in the insurance coverage. To reduce ex post moral hazard, we assume that both the insured and the insurer would pay more for a larger realization of the insurable loss. When the insurance premium principle preserves the convex order, we show that any admissible insurance contract is suboptimal to a two-layer insurance policy under the criterion of minimizing the insured’s total risk exposure quantified by value at risk, tail value at risk or an expectile. The form of optimal insurance can be further simplified to be one-layer by imposing an additional weak condition on the premium principle. Finally, we use Wang’s premium principle and the expected value premium principle to illustrate the applicability of our results, and find that optimal insurance solutions are affected not only by the size of the excluded loss but also by the risk measure chosen to quantify the insured’s risk exposure.     

人寿保险中的最优缴费模型

精算数学中 ,将自然保费制转化为现今的均衡保费制 ,精算师并未考虑投保人的最优缴费策略 .本文采用最优化方法对定期寿险保单的缴费方式进行了分析 .得出 ,当精算师计算保费的利息与“银行储蓄利率”相等时 ,均衡收缴保费是保险人的最优策略 ,否则应分别采用递增或递减缴费策略 .     

风险资产的最优保险

本文采用期望方差方法，引入无风险投资；建立多元风险模型，从投保人角度讨论了最优保险决策，分析了投资风险，无风险投资收益和保费政策等因素对最优决策的影响，为现代企业采取综合措施降低风险提供了理论依据．     

Risky asset allocation and consumption rule in the presence of background risk and insurance markets

This study examines joint decisions regarding risky asset allocation and consumption rate for a representative agent in the presence of background risk and insurance markets. Contrary to the conclusion of the “mutual fund separation theorem”, we show that the optimal risky asset mix will reflect an agent’s risk attitude as long as background risk is not independent of investment risk. This result can, however, be used to solve the “riskyasset allocation puzzle”. We also unveil that optimal insurance to shift background risk is determined through establishing a hedging portfolio against investment risk and is an arrangement maintaining the balance between growth and volatility of expected consumption. Because the optimal insurance we obtain generally leads to a smoother consumption path, it may plausibly explain the “equity premium puzzle” in the financial literature.     

两阶段免费增值商业模式中的定价优化与时序研究

免费增值商业模式在信息产品和服务当中被广泛采用。针对企业首先推出免费产品再推出付费产品以充分利用两种产品推出的时间差来提升消费者学习效应、降低消费者使用成本的情形,本文首先建立两阶段模型,求解给定系统参数情况下的付费版产品最优定价问题并给出解析解,然后通过与企业应用单阶段免费增值模式时的利润进行比较,解析地得到企业选择两阶段模式可获得较高利润的条件,最后在数值计算基础上讨论了学习效应强度对企业利润的影响,和优化学习效应强度以拓展两阶段模式适用范围的问题。本文的研究成果为拟采用免费增值商业模式的企业提供了关于产品最优定价和模式选择的决策支持。     

新疆财产保险发展与经济增长关系的实证分析

运用VAR模型,采取实证分析的方法,选取样本区间为1985～2015年的新疆财产保险保费收入和新疆GDP的自然对数,通过单位根检验,协整检验和脉冲响应函数等研究了新疆财产保险的发展现状及其与经济的相互影响作用.研究发现近几年新疆财产保险发展迅速,保险机构数量和保费收入增加很快.结果表明:保险发展和经济发展具有相互促进、相互影响的作用,但经济发展对保险发展作用更显著,两者存在单项因果关系,即表明新疆经济发展推动了新疆财产保险的事业发展.     

Simulation of a health insurance market with adverse selection

A health insurance market is examined in which individuals with a history of high utilization of health care services tend to select fee-for-service (FFS) insurance when offered a choice between FFS and health maintenance organizations (HMOs). In addition, HMOs are assumed to practice community rating of employee groups. Based on these observations and health plan enrollment and premium data from Minneapolis-St. Paul, a deterministic simulation model is constructed to predict equilibrium market shares and premiums for HMO and FFS insurers within a firm. Despite the fact that favorable selection enhances their ability to compete with FFS insurers, the model predicts that HMOs maximize profits at less than 100% market share, and at a lower share than they could conceivably capture. That is, HMOs would not find it to their advantage to drive FFS insurers from the market even if they could. In all cases, however, the profit-maximizing HMO premium is greater than the experience-rated premium and, thus, the average health insurance premium per employee in firms offering both HMOs and FFS insurance is predicted to be greater than in firms offering one experience-rated plan. The model may be used to simulate the effects of varying the employer's method of contributing to health insurance premiums. Several contribution methods are compared. Employers who offer FFS and HMO insurance and pay the full cost of the lowest-cost plan are predicted to have lower average total premiums (employer plus employee contributions) than employers who pay any level percent of the cost of each plan.     

A mathematical programming approach to optimise insurance premium pricing within a data mining framework

In this paper we provide evidence of the benefits of an approach which combines data mining and mathematical programming to determining the premium to charge automobile insurance policy holders in order to arrive at an optimal portfolio. An non-linear integer programming formulation is proposed to determine optimal premiums based on the insurer's need to find a balance between profitability and market share. The non-linear integer programming approach to solving this problem is used within a data mining framework which consists of three components: classifying policy holders into homogenous risk groups and predicting the claim cost of each group using k-means clustering; determining the price sensitivity (propensity to pay) of each group using neural networks; and combining the results of the first two components to determine the optimal premium to charge. We have earlier presented the results of the first two components. In this paper we present the results of the third component. Using our approach, we have been able to increase revenue without affecting termination rates and market share.     

���ϱ���׼���������ٱ��չ�˾ΥԼ���յ������ٱ������

Based on the default risk effect of reinsurance company for reinsurer, this paper studies the optimal reinsurance strategy by VaR optimality criterion. In a reinsurance contract, reinsurance company will charge the number of premium to undertake part of the insurer's loss. However, if the reinsurance company's commitment exceeds its solvency, the default risk will occur. In order to avoid the default risk and minimize the total risk of the insurance company, the paper introduces Wang's premium principle to obtain the optimal reinsurance policy under VaR risk measure. Some numerical examples are given to illustrate these results.     

Effects of insurance premium and deductible on production

We consider a risk-averse firm bearing the revenue risk and fuzzy production cost. Using the quadratic utility function the sufficient conditions for a deductible insurance to increase the output are derived and found to be the functions of insurance premium and deductible. We also show that the optimal production for a firm in the fuzzy environment is less than that in the crisp environment.     

指数保费原理下的经验厘定

在经典的信度理论中,信度保费是在净保费原理下得到的. 但是, 保险商业中, 保险公司要求制定的保费必须适用于某合适的保费原理以适应具体的保险商业的需要. 本文建立了指数保费原理下的完全经验厘定模型, 得到了风险保费的信度估计和经验Bayes 信度估计, 并讨论了结构参数的估计及其性质. 最后证明了多合同模型的经验Bayes 信度估计的渐近最优性     

Underwriting strategy in a competitive insurance environment

In recent times the Australian insurance market, particularly the Liability section of it, has been characterized by violent changes in premium rate. For a number of years premium rates declined to a point where the market, on average, was underwriting at a considerable loss. This trend was reversed by a sequence of large increases in premium rates to the point where, on average, substantial profits were probably being made.During these fluctuations in premium rates the various operators in the market appeared to act in a similar manner; generally, these individual operators followed ‘the market’ as its average premium rates declined and then increased. From the viewpoint of rational product pricing, this cyclical behaviour of premium rates is peculiar. It raises questions as to

1. 1.what ‘the market’ was attempting to achieve by such pricing;
2. 2.what individual insurers were attempting to achieve in following the market.

The present paper investigates the appropriate response of an individual insurer to movements in market premium rates. It is assumed that the management objective of this insurer is maximization of expected discounted profit arising between the present and some planning horizon. Price-elasticity of demand for the insurance produce is taken into account.Section 5 provides an explicit formula for the response of optimal pricing policy to changes in market premium rates. Several theorems are developed there indicating the response of this optimal policy to changes in various parameters. The same section provides a verbal interpretation of those theorems.It is found that optimal strategies do not follow what might be thought the obvious rules. In particular, it is not the case that profitability is best served by following the market during a period of premium rate depression. The relation between the market's behaviour and optimal response of an individual insurer is a complex one. It depends upon various factors, including

1. 1.the predicted time which will elapse before a return of market rates to profitability;
2. 2.the price-elasticity of demand for the insurance product under consideration;
3. 3.the rate of return required on the capital supporting the insurance operation.

Each of these features is illustrated in the numerical examples of Section 7. In particular, it is seen that the optimal strategy may well involve underwriting for significant profit margins at times when the average market premium rate is well short of breaking even.On the other hand, conditions can arise in which the optimal premium rating strategy will indicate loss leading in the near future. As a very broad generalization, this may be the case when the current average market rate lies below the break-even rate, but is expected to return to substantial profitability in the very near future. The phrases ‘substantial profitability’ and ‘very near future’ are both operative in this generalization (see Section 7.5).One of the numerical examples demonstrates that optimal strategies will not involve loss leaders, irrespective of the degree of competition from the market, if the demand function for the insurance product assumes certain forms. These particular forms are not unrealistic. It follows that some market research on the shape of the demand function may assist an insurer seeking to determine a suitable underwriting strategy.In fact, some sections toward the end of the paper point out that there are other factors, and particularly taxation considerations (Section 9.1), which need to be considered before an optimal strategy involving loss leading be adopted. Again as a broad generalization, it may be said that these considerations tend to militate against loss leading.In summary then, it appears that the longer term profitability of an insurer will only comparatively rarely be best served by underwriting for deliberate losses.Section 10 gives details of a small survey of Australian underwriters. These underwriters have stated the manner in which they would respond, in terms of pitching their rates, to a particular set of circumstances in a competitive market. These responses are compared with the optimal response.     

Optimal XL-insurance under Wasserstein-type ambiguity

We study the problem of optimal insurance contract design for risk management under a budget constraint. The contract holder takes into consideration that the loss distribution is not entirely known and therefore faces an ambiguity problem. For a given set of models, we formulate a minimax optimization problem of finding an optimal insurance contract that minimizes the distortion risk functional of the retained loss with premium limitation. We demonstrate that under the average value-at-risk measure, the entrance-excess of loss contracts are optimal under ambiguity, and we solve the distributionally robust optimal contract-design problem. It is assumed that the insurance premium is calculated according to a given baseline loss distribution and that the ambiguity set of possible distributions forms a neighborhood of the baseline distribution. To this end, we introduce a contorted Wasserstein distance. This distance is finer in the tails of the distributions compared to the usual Wasserstein distance.     

Determination of the optimal level of risk deduction by an insurance company

We study the dependence of the insurance premium on the limit of liability of the insurance company with respect to individual risk. We determine the conditions under which the relative insurance surcharge will have a minimum. By choosing the optimal limit of liability corresponding to a minimum of insurance surcharge, the insurance company decreases the cost of insurance. Translated fromMetody Matematicheskogo Modelirovaniya, 1998, pp. 151–159.     

Pareto-optimal insurance contracts with premium budget and minimum charge constraints

In view of the fact that minimum charge and premium budget constraints are natural economic considerations in any risk-transfer between the insurance buyer and seller, this paper revisits the optimal insurance contract design problem in terms of Pareto optimality with imposing these practical constraints. Pareto optimal insurance contracts, with indemnity schedule and premium payment, are solved in the cases when the risk preferences of the buyer and seller are given by Value-at-Risk or Tail Value-at-Risk. The effect of our constraints and the relative bargaining powers of the buyer and seller on the Pareto optimal insurance contracts are highlighted. Numerical experiments are employed to further examine these effects for some given risk preferences.     

Vigilant measures of risk and the demand for contingent claims

We examine a class of utility maximization problems with a non-necessarily law-invariant utility, and with a non-necessarily law-invariant risk measure constraint. Under a consistency requirement on the risk measure that we call Vigilance, we show the existence of optimal contingent claims, and we show that such optimal contingent claims exhibit a desired monotonicity property. Vigilance is satisfied by a large class of risk measures, including all distortion risk measures and some classes of robust risk measures. As an illustration, we consider a problem of optimal insurance design where the premium principle satisfies the vigilance property, hence covering a large collection of commonly used premium principles, including premium principles that are not law-invariant. We show the existence of optimal indemnity schedules, and we show that optimal indemnity schedules are nondecreasing functions of the insurable loss.     

A methodology for integrated critical spare parts and insurance management

Critical spare‐parts stock optimization has become a relevant topic for academy and industry. In most articles, the problem has been stated as a trade‐off between economic risks of shortages and financial costs. Risk optimization in this context has been mainly studied from a logistics point of view. The most common decision variables have been stock levels, stock location, and reorder points. In this context, buying insurance to cover shortage cost can be a complementary (or exclusive) measure for risk mitigation. Insurance optimization traditionally has been studied from a microeconomic and financial perspective. The main decision variable has been the indemnity function, and occasionally, the insurance premium. Its use in the context of physical asset management has not been observed to the best of our knowledge. This creates an opportunity to link inventory optimization techniques with insurance optimization for shortage losses. In this work, we present a novel approach to jointly manage the shortage risk of a critical non‐repairable component in a unique critical system. We develop an original model to integrate critical spare‐parts stock optimization with insurance optimization techniques. The result is a decision model to select the optimal stock and insurance policy that maximizes the decision maker's expected utility. This allows for a business‐centered integrated perspective in critical parts decisions. We present a case study representative of the mining industry, illustrating the complementary nature of selecting optimal stock levels and contracting an optimal insurance. Our results show that contracting an insurance can lead to policies preferred by a risk‐averse decision maker. The case study shows that this may even occur lowering stock levels and increasing profits. Copyright © 2015 John Wiley & Sons, Ltd.     

财政补贴政策与长期护理保险市场演化

财政补贴政策是政府矫正市场失灵,驱动长期护理保险市场高质量演化发展的重要手段。本文基于多主体仿真模型,考察不同补贴政策驱动长期护理保险市场演化的过程。研究发现:实行产品创新补贴政策时,可以形成健康有序的长期护理保险市场竞争格局;实行经营性补贴政策时,长期护理保险市场容易演化成垄断市场。保费补贴政策能够扩大需求规模,且差异化的保费补贴政策能够更加有效地激励需求空间的大幅增长。