Optimal multi-period insurance contracts

In multi-period insurance contracts (such as automobile insurance contracts), unlike single-period ones, the premiums that the insured must pay increase whenever he files a claim. Hence, the buyer faces a problem that is absent in one-period models, namely: he must determine for which damages he should file a claim and for which he should not.The optimal claims policy of the buyer is presented for a large class of insurance contracts. It is shown that the buyer will file a claim only if it is larger than some critical value. Based on this it is shown that the buyer prefers a contract that provides full coverage above a deductible for damages that exceed his critical value. In this case the optimal contract is not unique since the buyer is indifferent to the form of the contract for damages below his critical value. It is shown, however, that as in one-period models (Arrow (1963, 1974)) there exists an optimal contract that provides full coverage above a deductible. In multi-period setting, however, the buyer will file a claim only if the damage is sufficiently higher than the deductible.It is also shown that the buyer prefers a strictly positive deductible. Unlike the one-period case (Mossin (1968)), this result holds true even if the premium rates equal the expected payments.     

Explicit solutions of optimal consumption,investment and insurance problems with regime switching

We consider an investor who wants to select his optimal consumption, investment and insurance policies. Motivated by new insurance products, we allow not only the financial market but also the insurable loss to depend on the regime of the economy. The objective of the investor is to maximize his expected total discounted utility of consumption over an infinite time horizon. For the case of hyperbolic absolute risk aversion (HARA) utility functions, we obtain the first explicit solutions for simultaneous optimal consumption, investment, and insurance problems when there is regime switching. We determine that the optimal insurance contract is either no-insurance or deductible insurance, and calculate when it is optimal to buy insurance. The optimal policy depends strongly on the regime of the economy. Through an economic analysis, we calculate the advantage of buying insurance.     

Bounds for the optimal critical claim size of a bonus system

The optimal critical claim size of a bonus system determines whether to file a claim with the insurance company after having an accident. The aim of this paper is to demonstrate, within the framework of a simple model, how bounds for the optimal critical claim size can be constructed when only incomplete information on the claim amount distribution is available.     

Optimal insurance design with a bonus

This paper investigates an insurance design problem, in which a bonus will be given to the insured if no claim has been made during the whole lifetime of the contract, for an expected utility insured. In this problem, the insured has to consider the so-called optimal action rather than the contracted compensation (or indemnity) due to the existence of the bonus. For any pre-agreed bonus, the optimal insurance contract is given explicitly and shown to be either the full coverage contract when the insured pays high enough premium, or a deductible one otherwise. The optimal contract and bonus are also derived explicitly if the insured is allowed to choose both of them. The contract turns out to be of either zero reward or zero deductible. In all cases, the optimal contracts are universal, that is, they do not depend on the specific form of the utility of the insured. A numerical example is also provided to illustrate the main theoretical results of the paper.     

Optimal Claiming on Vehicle Insurance Revisited

Most motorists involved in an accident will claim from their insurance company only if the cost of repair exceeds a certain amount. In this paper, optimal no-claim limits are determined for a common type of insurance policy, and a simple decision rule which might be used by a motorist is shown to have an expected cost very close to the optimal decision rule.     

回购契约下闭环供应链对突发事件的协调应对

在回购契约下,可以实现闭环供应链的协调。然而突发事件发生造成零售商面临的需求分布变化时,闭环供应链的销售活动将受到影响,闭环供应链的协调将被打破;但是闭环供应链的废旧品回收活动却不受突发事件的影响。为此,给出了闭环供应链对突发事件的最优应对策略,并调整了原来的回购契约使其能协调应对突发事件,并且使调整后的回购契约也能实现突发事件前闭环供应链的协调。     

Life insurance in a portfolio context

The ownership of life insurance may be modeled as a portfolio problem in which the return on the life insurance contract is negatively correlated with the return on a claim to future wage income. The mean-variance model developed in the paper uses such a framework to express the optimal amount of insurance in terms of two components: the expected value of the wage claim and the risk/return characteristics of the insurance contract. The model thus offers an appealing way to formulate the life insurance problem in a portfolio context. Implications of the model for the functioning of a life insurance market are examined and the existence of accidental death contracts is explained.     

汽车保险市场的信息不对称:来自商业第三者责任险的证据

本文修正了Richaudeau(1999)提出的保障-风险条件相关模型,考虑到索赔次数中的"零膨胀"现象,采用零膨胀Poisson分布拟合索赔次数,以我国汽车商业第三者责任保险作为研究对象,研究了中国车险市场的信息不对称问题。实证结果表明,在控制公开信息的基础上,我国汽车保险市场仍存在显著的信息不对称问题。但是,保险公司可以通过费率厘定、无赔款优待制度、附加险设计等方法分离不同风险的投保人,减轻信息不对称程度对公司经营的影响。     

Credibility estimators with geometric weights

In the present paper we study credibility estimators with geometric weights in the framework of experience rating in motor insurance. We discuss how to find optimal weights. The estimators are compared with the traditional credibility estimators and shown to be more robust against a certain type of violations against the model assumptions. We also discuss advantages and disadvantages relative to ordinary bonus—malus systems.     

Sarmanov family of multivariate distributions for bivariate dynamic claim counts model

To predict future claims, it is well-known that the most recent claims are more predictive than older ones. However, classic panel data models for claim counts, such as the multivariate negative binomial distribution, do not put any time weight on past claims. More complex models can be used to consider this property, but often need numerical procedures to estimate parameters. When we want to add a dependence between different claim count types, the task would be even more difficult to handle. In this paper, we propose a bivariate dynamic model for claim counts, where past claims experience of a given claim type is used to better predict the other type of claims. This new bivariate dynamic distribution for claim counts is based on random effects that come from the Sarmanov family of multivariate distributions. To obtain a proper dynamic distribution based on this kind of bivariate priors, an approximation of the posterior distribution of the random effects is proposed. The resulting model can be seen as an extension of the dynamic heterogeneity model described in Bolancé et al. (2007). We apply this model to two samples of data from a major Canadian insurance company, where we show that the proposed model is one of the best models to adjust the data. We also show that the proposed model allows more flexibility in computing predictive premiums because closed-form expressions can be easily derived for the predictive distribution, the moments and the predictive moments.     

Optimal dynamic multi-attribute hashing for range queries

This paper examines a partial match retrieval scheme which supports range queries for highly dynamic databases. The scheme relies on order preserving multi-attribute hashing. In general, designing optimal indexes is NP-hard. Greedy algorithms used to determine the optimal indexes for simple partial match queries are not directly applicable because there are a larger number of queries to consider in determining the optimal indexes. In this paper we present heuristic algorithms which provide near-optimal solutions. The optimisation scheme we propose can be used to design other dynamic file structures such as the grid file, BANG file and multilevel grid file to further enhance their retrieval performance taking into consideration the query distribution.     

Optimal Claiming in an Automobile Insurance System with Bonus-Malus Structure

A motorist involved in an accident will have to decide whether to claim from his insurance company or not when he is at fault. An optimal decision rule can only be determined in the light of future developments and future decisions, since the consequences of claiming or not claiming are felt in the subsequent year's premiums. In this paper, optimal no-claim limits are determined for a common Dutch type of insurance policy with bonus-malus structures, using generalized Markovian programming. The computational results are given for various values of the expected number of accidents per year.     

人寿保险合同复效的决策分析

本文提出人寿保险合同复效的决策分析问题,通过建立计算方程分别计算保险合同复效方案和重新购买新保单方案的净保费现值,为投保人选择最佳方案提供一种科学的定量分析方法,本文还借助于计算机定量分析若干因素对方案选择的影响,并讨论利息率的敏感性分析。     

Unit-linked life insurance policies: Optimal hedging in partially observable market models

In this paper we investigate the hedging problem of a unit-linked life insurance contract via the local risk-minimization approach, when the insurer has a restricted information on the market. In particular, we consider an endowment insurance contract, that is a combination of a term insurance policy and a pure endowment, whose final value depends on the trend of a stock market where the premia the policyholder pays are invested. To allow for mutual dependence between the financial and the insurance markets, we use the progressive enlargement of filtration approach. We assume that the stock price process dynamics depends on an exogenous unobservable stochastic factor that also influences the mortality rate of the policyholder. We characterize the optimal hedging strategy in terms of the integrand in the Galtchouk–Kunita–Watanabe decomposition of the insurance claim with respect to the minimal martingale measure and the available information flow. We provide an explicit formula by means of predictable projection of the corresponding hedging strategy under full information with respect to the natural filtration of the risky asset price and the minimal martingale measure. Finally, we discuss applications in a Markovian setting via filtering.     

Impact of taxation on international transfer pricing and offshoring decisions

A multinational company may move production to a foreign country to take advantage of low manufacturing cost, and/or experience tax savings. Transfer prices play an important and strategic role on income shifting by multinational companies. In this paper, we construct a framework for optimal decision making in global supply chains with uncertain and price-dependent demand, propose methods to improve global supply chain parties’ performance, and explore schemes to integrate global supply chains. The optimal pricing and offshoring decisions are investigated for different situations where the low foreign production cost and low foreign tax rate exist or only one of them is available. The case of low foreign tax rate without the advantage of low foreign production cost provides the most interesting findings that partial offshoring dominates when a certain threshold is met. In addition, the double marginalization is examined in decentralized global supply chains similar to the mechanism in newsvendor problems. Due to the existence of the tax jurisdiction, the double marginalization cannot be completely eliminated by coordinating schemes. Finally, the traditional buy back contract is found to be unable to coordinate global supply chains, while a modified sales sharing contract can improve the performance of the global supply chain.     

Short-term booking of air cargo space

This paper proposes a stochastic dynamic programming model for a short-term capacity planning model for air cargo space. Long-term cargo space is usually acquired by freight forwarders or shippers many months ahead on a contract basis, and usually the forecasted demand is unreliable. A re-planning of cargo space is needed when the date draws nearer to the flight departure time. Hence, for a given amount of long-term contract space, the decision for each stage is the quantity of additional space required for the next stage and the decision planning model evaluates the optimal cost policy based on the economic trade-off between the cost of backlogged shipment and the cost of acquiring additional cargo space. Under certain conditions, we show that the return function is convex with respect to the additional space acquired for a given state and the optimal expected cost for the remaining stages is an increasing convex function with respect to the state variables. These two properties can be carried backward recursively and therefore the optimal cost policy can be determined efficiently.     

A continuous time solution for optimal claim limits in vehicle insurance

The traditional method of obtaining optimal claim limits for vehicle insurance is to discretise the state space and use successive approximations. In this paper we show how the stochastic dynamic programming equations reduce to a set of differential equations, in which these are easily solved to provide exact continuous time solutions. The resulting model can be used for evaluating alternative levels of excess.     

Forecast horizons and dynamic facility location planning

We consider a dynamic facility location model in which the objective is to find a planning horizon, *, and a first period decision,X ₁*, such thatX ₁* is a first period decision for at least one optimal policy for all problems with planning horizons equal to or longer than *. In other words, we seek a planning horizon, *, such that conditions after * do not influence the choice of the optimal initial decision,X ₁*. We call * aforecast horizon andX ₁* anoptimal initial decision. For the dynamic uncapacitated fixed charge location problem, we show that simple conditions exist such that the initial decision depends on the length of the planning horizon. Thus, a strictly optimal forecast horizon and initial policy may not exist. We therefore introduce the concepts ofe-optimal forecast horizons and -optimal initial solutions. Our computational experience inicates that such solutions can be found for practical problems. Although computing -optimal forecast horizons and initial decisions can be cumbersome, this approach offers the potential for making significantly better decisions than those generated by other approaches. To illustrate this, we show that the use of the scenario planning approach can lead to the adoption of the worst possible initial decision under conditions of future uncertainty. On the basis of our results, it appears that the forecast horizon approach offers an attractive tool for making dynamic location decisions.     

Operational time and a fundamental problem of insurance in a data-rich environment

A problem of current concern in the assessment of claims experience in non-life insurance is addressed. The problem relates to the interface of two well-defined areas of actuarial activity, namely reserving and rating. A model is proposed that permits the analysis of claim settlement experience in such a way as to allow for variations in settlement rate, proportions of nil claims and variations from year to year in a risk-factorial background. From this, the reserving approach may be developed coherently into the area of risk costing for rating purposes.     

Quantity discounts based on the previous order in a two-period inventory model with demand uncertainty

We examine quantity discount contracts between a manufacturer and a retailer in a stochastic, two-period inventory model. The retailer places an order in each of the two periods to meet stochastic demands. The manufacturer gives the retailer a price discount on purchases in the second period in excess of the first-period order quantity (incremental QDP) or a price discount for all units ordered in the second period if the retailer orders more in the second period than in the first period (all-units QDP). We show that the retailer's optimal ordering decision in the second period depends on the sum of initial inventory and previous order quantity. Our computational study suggests that the QDP contract induces the retailer to buy more in the second period but less in the first period, while the increase of the total order quantity may not be significant; and that it increases the manufacturer's profit only when the wholesale margin is large relative to the retail margin.