The Log–Lindley distribution as an alternative to the beta regression model with applications in insurance

In this paper a new probability density function with bounded domain is presented. The new distribution arises from the generalized Lindley distribution proposed by Zakerzadeh and Dolati (2010). This new distribution that depends on two parameters can be considered as an alternative to the classical beta distribution. It presents the advantage of not including any special function in its formulation. After studying its most important properties, some useful results regarding insurance and inventory management applications are obtained. In particular, in insurance, we suggest a special class of distorted premium principles based on this distribution and we compare it with the well-known power dual premium principle. Since the mean of the new distribution can be normalized to give a simple parameter, this new model is appropriate to be used as a regression model when the response is bounded, being therefore an alternative to the beta regression model recently proposed in the statistical literature.     

A participatory multi-criteria approach for power generation and transmission planning

It is well-known that reinsurance can be an effective risk management solution for financial institutions such as the insurance companies. The optimal reinsurance solution depends on a number of factors including the criterion of optimization and the premium principle adopted by the reinsurer. In this paper, we analyze the Value-at-Risk based optimal risk management solution using reinsurance under a class of premium principles that is monotonic and piecewise. The monotonic piecewise premium principles include not only those which preserve stop-loss ordering, but also the piecewise premium principles which are monotonic and constructed by concatenating a series of premium principles. By adopting the monotonic piecewise premium principle, our proposed optimal reinsurance model has a number of advantages. In particular, our model has the flexibility of allowing the reinsurer to use different risk loading factors for a given premium principle or use entirely different premium principles depending on the layers of risk. Our proposed model can also analyze the optimal reinsurance strategy in the context of multiple reinsurers that may use different premium principles (as attributed to the difference in risk attitude and/or imperfect information). Furthermore, by artfully imposing certain constraints on the ceded loss functions, the resulting model can be used to capture the reinsurer’s willingness and/or capacity to accept risk or to control counterparty risk from the perspective of the insurer. Under some technical assumptions, we derive explicitly the optimal form of the reinsurance strategies in all the above cases. In particular, we show that a truncated stop-loss reinsurance treaty or a limited stop-loss reinsurance treaty can be optimal depending on the constraint imposed on the retained and/or ceded loss functions. Some numerical examples are provided to further compare and contrast our proposed models to the existing models.     

Improved bounds on the magnitude of the derivative of rational Bézier curves

In this paper we derive some new derivative bounds of rational Bézier curves according to some existing identities and inequalities. The comparison of the new bounds with some existing ones is also presented.     

Cn-连续的B-型样条曲线及其局部性、插值与逼近

§ 1　IntroductionB-spline curve plays an important role in CAGD.Cn-continuous B-spline curve of de-gree n+ 1 has local support of length n+ 2 [1 ] .In order to modify the shape of a curve insmaller range,the length of its supportshould be as shortas possible.The interpolation ofa set of given data points with the B-spline curve generally needs to solve a system of lin-ear equations or to insert some additional control points[2— 5] .Besides,the global approxi-mation of the control polygon …     

带干扰的两类不同风险模型的比较

本文比较了带干扰的两类不同风险模型.首先研究了在不同保费计算原理下各风险业务的相关性是如何影响保费率计算的,进而通过鞅方法推导出两类模型破产概率的Lundberg指数和Lundberg不等式,最后比较了在不同保费计算原理下两类模型的Lundberg指数的性质.     

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Besides the claims data in the past, certain assumptions about the distribution of claimsare required to derive the credibility premium in the classical theory. In the paper, the credibility premium can be calculated via the maximum entropy method if we know nothing about the distribution of claims. Furthermore, two corollaries are obtained under certain assumptions, that is, new claims have more weight than the old ones and the classical credibility formula is a special case of the credibility premium derived in the present paper. Finally, the simulation study is presented to illustrate that the credibility premium in the present paper is better than other models if the mean square error is taken as the evaluation criterion.     

Teichmüller curves,Galois actions and $ \widehat {GT} $‐relations

Teichmüller curves are geodesic discs in Teichmüller space that project to algebraic curves C in the moduli space M_g. Some Teichmüller curves can be considered as components of Hurwitz spaces. We show that the absolute Galois group G_? acts faithfully on the set of these embedded curves. We also compare the action of G_? on π₁(C) with the one on π₁(M_g) and obtain a relation in the Grothendieck–Teichmüller group, seemingly independent of the known ones. (© 2005 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

C2 Continuous Quartic Hermite Spline Curves with Shape Parameters

In order to relieve the deficiency of the usual cubic Hermite spline curves, the quartic Hermite spline curves with shape parameters is further studied in this work. The interpolation error and estimator of the quartic Hermite spline curves are given. And the characteristics of the quartic Hermite spline curves are discussed. The quartic Hermite spline curves not only have the same interpolation and conti-nuity properties of the usual cubic Hermite spline curves, but also can achieve local or global shape adjustment and C2 continuity by the shape parameters when the interpolation conditions are fixed.     

Optimization incentive and relative riskiness in experimental stag-hunt games

We compare the experimental results of three stag-hunt games. In contrast to Battalio et al. (Econometrica 69:749–764, 2001), our design keeps the riskiness ratio of the two strategies at a constant level as the optimization premium is increased. We define the riskiness ratio as the relative payoff range of the two strategies. We find that decreasing the riskiness ratio while keeping the optimization premium constant decreases sharply the frequency of the payoff-dominant equilibrium strategy. On the other hand an increase of the optimization premium with a constant riskiness ratio has no effect on the choice frequencies. Finally, we confirm the dynamic properties found by Battalio et al. that increasing the optimization premium favours best-response and sensitivity to the history of play.     

相对损失函数下的倍度保费

传统的倍度保费公式利用均方损失函数估计特定保人的风险. 然而, 索取保费与真实保费之间的比例比它们差的绝对值更适合于衡量保费的公平性. 基于这一点, 我们提出了两种计算保费的损失函数: 均方相对损失函数和熵相对损失函数, 并且给出了倍度因子的估计公式及它们的性质.     

An approach to merit rating by means of autoregressive sequences

A posteriori ratemaking is widely applied in the premium calculation of property and casualty products, particularly in third-party automobile insurance, which usually uses a bonus–malus system for premium adjustment. The present paper suggests an alternative to common frameworks that are designed as random walks on graphs of mostly finite states representing premium levels. The proposed premium calculation model is governed by the policyholder’s claim history through a recursive equation. This new autoregressive scheme is structurally different from the ones in use. Relevant metrics that measure the system’s optimality are evaluated, partially in analytical form. Through a comparison with existing models and parameterisation from real-life data, the new model is put into context and its practical relevance is investigated.     

Interpolation Methods for Curve Construction

This paper surveys a wide selection of the interpolation algorithms that are in use in financial markets for construction of curves such as forward curves, basis curves, and most importantly, yield curves. In the case of yield curves the issue of bootstrapping is reviewed and how the interpolation algorithm should be intimately connected to the bootstrap itself is discussed. The criterion for inclusion in this survey is that the method has been implemented by a software vendor (or indeed an inhouse developer) as a viable option for yield curve interpolation. As will be seen, many of these methods suffer from problems: they posit unreasonable expections, or are not even necessarily arbitrage free. Moreover, many methods lead one to derive hedging strategies that are not intuitively reasonable. In the last sections, two new interpolation methods (the monotone convex method and the minimal method) are introduced, which it is believed overcome many of the problems highlighted with the other methods discussed in the earlier sections.     

A family of premium principles based on mixtures of TVaRs

Risk-adjusted distributions are commonly used in actuarial science to define premium principles. In this paper, we claim that an appropriate risk-adjusted distribution, besides satisfying other desirable properties, should be well-behaved under conditioning with respect to the original risk distribution. Based on a sequence of such risk-adjusted distributions, we introduce a family of premium principles that gradually incorporate the degree of risk-aversion of the insurer in the risk loading. Members of this family are particular distortion premium principles that can be represented as mixtures of TVaRs, where the weights in the mixture reflect the attitude toward risk of the insurer. We make a systematic study of this family of premium principles.     

Comparison of non-linear optimization algorithms for yield curve estimation

The yield curve is a very important financial tool used in investment and policy decisions. Its estimation from market data is essentially a non-linear optimization problem. In this paper, we compare a diversity of non-linear optimization algorithms for estimating yield curves based on actual bond market data and conclude that certain classes of algorithms are more effective due to the nature of the problem.     

Towards Bounded Negativity of Self-Intersection on General Blown-up Projective Planes

We address the problem of bounding from below the self-intersection of integral curves on the projective plane blown-up at general points. In particular, by applying classical deformation theory, we obtain the expected bound in the case of either high ramification or low multiplicity.     

Enriched spin curves on stable curves with two components

In [7], Mainò constructed a moduli space for enriched stable curves, by blowing-up the moduli space of Deligne–Mumford stable curves. We introduce enriched spin curves, showing that a parameter space for these objects is obtained by blowing-up the moduli space of spin curves. The author was partially supported by CNPq (Proc.151610/2005-3) and by Faperj (Proc.E-26/152-629/2005).     

六次PH曲线C~1 Hermite插值

本文讨论六次PH(pythagorean hodograph)曲线的Hermite插值问题.六次PH曲线可以分为两种类型,本文使用参数曲线的复数表示形式,分别给出这两类曲线的构造方法.在给定C1连续的Hermite条件下,需要指定一个自由参数以确定插值曲线,本文进一步阐述这个自由参数的几何意义.由于六次PH曲线是非正则曲线,对于第一类曲线,不易控制奇异点在曲线中的位置;而对于第二类曲线,奇异点可以在构造过程中显式地被指定,因此可以有效地避免其在特定曲线段上的出现.     

有理曲线和曲面的分片多项式逼近

本文利用摄动的思想,以摄动有理曲线（曲面）的系数的无穷模作为优化目标,给出了用多项式曲线（曲面）逼近有理曲线（曲面）的一种新方法．同以前的各种方法相比,该方法不仅收敛而且具有更快的收敛速度,并且可以与细分技术相结合,得到有理曲线与曲面的整体光滑、分片多项式的逼近．     

Spreading of epidemics on scale-free networks with nonlinear infectivity

In this paper, we study the spreading of epidemics on scale-free networks with infectivity which is nonlinear in the connectivity of nodes. We will show that the nonlinear infectivity is more appropriate than constant or linear ones, and give the epidemic threshold of the SIS model on a scale-free network with nonlinear infectivity. In addition, we compare the effects of nonlinear infectivity on the epidemic threshold with two other cases on infinite and finite scale-free networks, and find some new results, such as: with unit recovery rate and nonlinear irrational infectivity, the epidemic threshold is always positive; and the epidemic threshold can increase with network size on finite networks, contrary to the findings in all previous work.