Insurance Mathematics & Economics最新文献

Mack's distribution-free chain ladder reserving model belongs to the most popular approaches in non-life insurance mathematics. Proposed to determine the first two moments of the reserve, it does not allow to identify the whole distribution of the reserve. For this purpose, Mack's model is usually equipped with a tailor-made bootstrap procedure. Although widely used in practice to estimate the reserve risk, no theoretical bootstrap consistency results exist that justify this approach.

To fill this gap in the literature, we adopt the framework proposed by Steinmetz and Jentsch (2022) to derive asymptotic theory in Mack's model. By splitting the reserve into two parts corresponding to process and estimation uncertainty, this enables - for the first time - a rigorous investigation also of the validity of the Mack bootstrap. We prove that the (conditional) distribution of the asymptotically dominating process uncertainty part is correctly mimicked by Mack's bootstrap if the parametric family of distributions of the individual development factors is correctly specified. Otherwise, this is not the case. In contrast, the (conditional) distribution of the estimation uncertainty part is generally not correctly captured by Mack's bootstrap. To tackle this, we propose an alternative Mack-type bootstrap, which is designed to capture also the distribution of the estimation uncertainty part.

We illustrate our findings by simulations and show that the newly proposed alternative Mack bootstrap performs superior to the Mack bootstrap.

We consider a state-dependent utility model with a binary loss distribution, wherein moral hazard occurs in loss reduction. The findings are as follows: First, partial insurance is optimal under state-dependent utility. Second, the optimal insurance coverage and effort level are affected by the relative sizes of the marginal utilities in the loss and no-loss states. (i) If the marginal utilities are equal between the two states, the optimal coverage and effort are identical to those in the state-independent case. (ii) If the marginal utility in the loss state is greater (less) than that in the no-loss state, the optimal coverage and effort cannot simultaneously be less (greater) than those in the state-independent case. Both coverage and effort can be greater (less) than those in the state-independent case when state dependency is sufficiently large. The compensating variation decreases (increases) as state dependency increases if state dependency is sufficiently large. Although the effect of state dependency on the sensitivity of effort with respect to coverage is unclear, sensitivity decreases (increases) when the loss distribution function is convex in effort.

In this paper, we examine how a monopolistic reinsurer designs a Bowley reinsurance contract, under the assumption that the reinsurer will default on payment if the compensated loss exceeds the sum of the initial capital and the premium charged from the contract. The problem is divided into two subproblems faced by the insurer and the reinsurer in turn. The optimal reinsurance contract is analyzed when both the insurer and the reinsurer minimize their retained risks, as quantified by the VaR measure, and the optimal ceded loss function and the optimal pricing function are provided. Explicit expressions are then derived when the reinsurer adopts either VaR- or TVaR-based regulation capital and charges premiums by the expected-value premium principle. Numerical examples using exponential and Pareto distributions are provided to illustrate the sensitivity effect generated by the confidence levels of the VaR for both parties, as well as those for the initial capitals on the set of Bowley reinsurance contracts.

This article proposes a framework for determining credibility premiums for multiple coverages in a compound risk model with Tweedie distribution. The framework builds upon previous results on credibility premium and provides an explicit multivariate credibility premium formula that is applicable to the Tweedie family assuming that the unobserved heterogeneity for the multiple coverage have the common correlation. The practical applicability of the proposed framework is evaluated through simulation and empirical analysis using the LGPIF dataset, which includes claims and policy characteristics data for various types of coverages observed over time. The findings suggest that the proposed framework can be useful in ratemaking practice by incorporating a non-trivial dependence structure among the multiple types of claims.

For a given risk, the well-known classical definition of Value-at-Risk (VaR) does not take into account possible interactions with other observable risks. For this reason, conditional VaRs that capture contagion effects and tail dependence among risks, such as the Co-Value-at-Risk (CoVaR), have been defined and studied in recent literature. In this paper we study conditions that guarantee, in the bivariate setting, the ordering between VaR and CoVaR, allowing to understand which, among the two measures, is more or less conservative than the other. By doing this, we introduce the notion of Probability Equivalent Level of CoVaR-VaR (PELCoV), which is the VaR value of the observable variable for which VaR and CoVaR coincide, and we study some of its properties such as uniqueness and boundedness. In particular, we show that its properties are entirely explained by the copula that describes the dependence between risks, and we provide a list of copulas for which PELCoV is explicitly available, and for which it is or not bounded. A practical applicative example is also presented.

We study the design of an optimal insurance contract in which the insured maximizes her expected utility and the insurer limits the variance of his risk exposure while maintaining the principle of indemnity and charging the premium according to the expected value principle. We derive the optimal policy semi-analytically, which is coinsurance above a deductible when the variance bound is binding. This policy automatically satisfies the incentive-compatible condition, which is crucial to rule out ex post moral hazard. We also find that the deductible is absent if and only if the contract pricing is actuarially fair. Focusing on the actuarially fair case, we carry out comparative statics on the effects of the insured's initial wealth and the variance bound on insurance demand. Our results indicate that the expected coverage is always larger for a wealthier insured, implying that the underlying insurance is a normal good, which supports certain recent empirical findings. Moreover, as the variance constraint tightens, the prudent insured cedes less losses, while the insurer is exposed to less tail risk.

How to detect different tail behaviors of two risk random variables with the same mean is an important task. In this paper, motivated by Burzoni et al. (2022), a class of convex risk measures, referred to as adjusted higher-order Expected Shortfall (ES), is introduced and studied. The adjusted risk measure quantifies risk as the minimum amount of capital that has to be raised and injected into a financial position to ensure that its higher-order ES does not exceed a pre-specified threshold for every probability level. This new risk measure is intimately linked to dual higher-order increasing convex order by choosing the risk threshold to be the higher-order ES of a special benchmark random loss. The dual representation for (adjusted) higher-order Expected Shortfall is also given.

This paper evaluates socioeconomic basis risk in longevity hedging. Using data for a full population stratified into socioeconomic groups, we explore the benefits and costs of two alternative hedging strategies, with and without basis risk, in the capital market. The benefit of the longevity hedge is represented by the risk reduction in the variability of a life annuity, whereas the cost is the notional amount of hedging contracts times the actuarial risk premium. We find that hedging is more cost-effective for the annuity provider when basis risk is eliminated. Moreover, it allows for a higher degree of hedge effectiveness at a cost that is equivalent to a hedge where basis risk is present. Finally, the yearly expenses related to hedging longevity risk require, at most, an extra added rate of return of no more than 0.16%.

In many developed countries, population aging raises a number of issues related to the organization and financing of long-term care. While the determinants of the overall burden and cost of care are well understood, the organization of institutionalized long-term care must meet the needs of the elderly. One way to optimize management is to use information on health problems to assess the infrastructure needed, the qualifications of staff, and the allocation of new entrants. In this research, we determine the typical health profiles of institutionalized elderly using novel longitudinal data from nursing homes in the canton of Geneva, Switzerland. Our data contain comprehensive information on health factors such as impairments of psychological and sensory functions, levels of limitations, and pathologies for 21 549 individuals covering the period from 1996 to 2018. First, we perform a spectral clustering algorithm and determine the profiles of the institutionalized individuals. Then, we use multinomial logistic regression to study the effects of the factors that determine these health profiles. Our main findings include eight typical health profiles: the largest group consists of the most “healthy” individuals, who, on average, require the least amount of help with their daily needs and who stay in the institution the longest. We show that, in contrast to age at admission and gender, the limitations and the set of pathologies are relevant factors in determining the profile. Our study sheds light on the typical structures of elderly' health profiles, which can be used by institutions to organize their resources and by insurance companies to derive profile-based products that provide additional insurance coverage in case of special needs.

Variability measures are important tools in the construction of premium principles and risk aversions. In this paper, we propose a family of such measures based on a distorted weighted cumulative residual entropy, which follows by a sensitivity analysis of distortion risk measures. For this family, we obtain properties, connections with other measures, a covariance representation, and some useful interpretations. Furthermore, we explore an application on premium principles based on beta generated distributions, and we give an empirical estimation. We also provide bounds and numerical illustrations.