高频金融时序的密度函数肥尾度量

本文在分析高频金融时序的基本特征的基础上,应用极值理论和相关性质估计和检验了肥尾指数。     

一类相依索赔离散风险模型研究

研究了一类相依索赔的离散风险模型,得到了利率为0时模型的最终破产概率所满足的积分方程,以及破产持续n期的概率所满足的表达式.进而,得到了利率不为0时该模型的最终破产概率所满足的积分方程,并利用鞅论技巧导出了最终破产概率的一个Lundberg型上界,最后运用Matlab软件随机模拟破产概率并与Lundberg型上界作比较.     

A new approach for solving linear bilevel problems using genetic algorithms

Bilevel programming involves two optimization problems where the constraint region of the first level problem is implicitly determined by another optimization problem. This paper develops a genetic algorithm for the linear bilevel problem in which both objective functions are linear and the common constraint region is a polyhedron. Taking into account the existence of an extreme point of the polyhedron which solves the problem, the algorithm aims to combine classical extreme point enumeration techniques with genetic search methods by associating chromosomes with extreme points of the polyhedron. The numerical results show the efficiency of the proposed algorithm. In addition, this genetic algorithm can also be used for solving quasiconcave bilevel problems provided that the second level objective function is linear.     

Extreme value analysis of empirical frame coefficients and implications for denoising by soft-thresholding

Denoising by frame thresholding is one of the most basic and efficient methods for recovering a discrete signal or image from data that are corrupted by additive Gaussian white noise. The basic idea is to select a frame of analyzing elements that separates the data in few large coefficients due to the signal and many small coefficients mainly due to the noise ${ϵ}_n$. Removing all data coefficients being in magnitude below a certain threshold yields a reconstruction of the original signal. In order to properly balance the amount of noise to be removed and the relevant signal features to be kept, a precise understanding of the statistical properties of thresholding is important. For that purpose we derive the asymptotic distribution of ${\max }_{\omega \in {\Omega }_n}|〈{\varphi }_{\omega }^n,{ϵ}_n〉|$ for a wide class of redundant frames $({\varphi }_{\omega }^n:\omega \in {\Omega }_n)$. Based on our theoretical results we give a rationale for universal extreme value thresholding techniques yielding asymptotically sharp confidence regions and smoothness estimates corresponding to prescribed significance levels. The results cover many frames used in imaging and signal recovery applications, such as redundant wavelet systems, curvelet frames, or unions of bases. We show that ‘generically’ a standard Gumbel law results as it is known from the case of orthonormal wavelet bases. However, for specific highly redundant frames other limiting laws may occur. We indeed verify that the translation invariant wavelet transform shows a different asymptotic behaviour.     

Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem

We consider the problem of restoring services provided by infrastructure systems after an extreme event disrupts them. This research proposes a novel integrated network design and scheduling problem that models these restoration efforts. In this problem, work groups must be allocated to build nodes and arcs into a network in order to maximize the cumulative weighted flow in the network over a horizon. We develop a novel heuristic dispatching rule that selects the next set of tasks to be processed by the work groups. We further propose families of valid inequalities for an integer programming formulation of the problem, one of which specifically links the network design and scheduling decisions. Our methods are tested on realistic data sets representing the infrastructure systems of New Hanover County, North Carolina in the United States and lower Manhattan in New York City. These results indicate that our methods can be used in both real-time restoration activities and long-term scenario planning activities. Our models are also applied to explore the effects on the restoration activities of aligning them with the goals of an emergency manager and to benchmark existing restoration procedures.     

Graphs and Hermitian matrices: Exact interlacing

We prove conditions for equality between the extreme eigenvalues of a matrix and its quotient. In particular, we give a lower bound on the largest singular value of a matrix and generalize a result of Finck and Grohmann about the largest eigenvalue of a graph.     

基于指数回归模型的极值指数估计的门限选择

在本文中,我们基于指数回归模型,在渐近最小均方误差的准则下,给出了矩估计的门限值和样本点分割的选取原理和方法。利用MC方法,对Burr(1,1,1)、Burr(1,0.5,2)、Fréchet(1)、Fréchet(2)、学生-t4、学生-t6等几种常见的极值分布进行模拟,得到了理想的结果。并运用S&P500指数和Danish火灾数据进行了实证分析。     

一类相依索赔风险模型的破产概率问题研究

考虑一种相依索赔风险模型,其中每次索赔发生时根据索赔额的大小可随机产生一延迟的副索赔.采用L ap lace变换方法,给出了索赔额服从轻尾分布时的最终破产概率,并研究了重尾分布时最终破产概率的极限上下界.     

A representation of bivariate extreme value distributions via norms on \mathbb{R}^{2}

It is known that a bivariate extreme value distribution (EVD) with reverse exponential margins can be represented as , , where is a suitable norm on . We prove in this paper the converse implication, i.e., given an arbitrary norm on , , , defines an EVD with reverse exponential margins, if and only if the norm satisfies for the condition . This result is extended to bivariate EVDs with arbitrary margins as well as to extreme value copulas. By identifying an EVD , , with the unit ball corresponding to the generating norm , we obtain a characterization of the class of EVDs in terms of compact and convex subsets of .     

保费率-巨灾索赔相依的风险模型的破产概率

进一步推广Sparre Andersen风险模型,考虑有意外巨额赔付情况下得到保险公司的破产概率,并得到尾等价式,此结果反映了特殊的巨额索赔对破产的影响程度.另外,当有巨灾索赔发生的时候,模型会对保险费率做出相应的调整.