A BSDE-based approach for the optimal reinsurance problem under partial information

We investigate the optimal reinsurance problem under the criterion of maximizing the expected utility of terminal wealth when the insurance company has restricted information on the loss process. We propose a risk model with claim arrival intensity and claim sizes distribution affected by an unobservable environmental stochastic factor. By filtering techniques (with marked point process observations), we reduce the original problem to an equivalent stochastic control problem under full information. Since the classical Hamilton–Jacobi–Bellman approach does not apply, due to the infinite dimensionality of the filter, we choose an alternative approach based on Backward Stochastic Differential Equations (BSDEs). Precisely, we characterize the value process and the optimal reinsurance strategy in terms of the unique solution to a BSDE driven by a marked point process.     

Rotational tools for factor analytic models

Rotational ambiguity is a major problem in the application of factor analysis to a variety of multivariate mixture resolution problems and particularly important in the analysis of environmental data. As part of the development of an implementation of positive matrix factorization for the U.S. Environmental Protection Agency to distribute in support of airborne particle source identification and apportionment, several tools have been developed to control the rotations and explore the extent of rotational solution space. This discussion of the nature of the rotational tools provides an understanding of these rotational tools as well as the basis for their incorporation into other implementations of least‐squares based solutions to the factor analysis problem. Several example algorithms are presented. Copyright © 2008 John Wiley & Sons, Ltd.     

供需模型在众包平台定价中的应用

以众包平台为对象,基于已有数据,考虑供求关系,通过因子分析法对原始数据加以处理,建立任务的定价模型.在实际应用中,可以对分布密集的任务进行打包,并给出针对这种情况的定价模型.结果表明:提出的模型不仅考虑了会员人数与任务数量的关系,还考虑了个人需求的差异,提高了任务的完成度,对众包平台定价的发展与完善有着重要的意义.     

不良贷款约束下我国上市商业银行全要素生产率时序演变及其驱动因素研究——基于非期望产出的Malmquist-luenberger和Tobit模型

基于我国上市商业银行2007~2013年面板数据,构建包括不良贷款约束条件下我国上市商业银行投入产出指标体系,采用基于非期望产出的M-L生产率指数方法对我国上市商业银行全要素生产率跨期动态变化进行实证测度,并应用Tobit回归分析方法对影响我国上市商业银行全要素生产率的因素进行实证分析,实证结果显示:我国上市商业银行全要素生产率平均增长率为2.4%,上市城市商业银行全要素生产率高于股份制上市商业银行,而股份制商业银行高于国有商业银行,其主要来源与规模效率提升;此外,银行规模和存贷比对商业银行技术效率提升产生显著的正向驱动影响;而银行集中度对其产生显著的负向驱动影响;资产收益率和所有权结构对其影响不显著。     

On the Equation n_1n_2= n_3n_4 Restricted to Factor Closed Sets

We study the number of solutions N(B,F) of the diophantine equation n_1n_2 = n_3 n_4,where 1 ≤ n_1 ≤ B,1 ≤ n_3 ≤ B,n_2,n_4 ∈ F and F[1,B] is a factor closed set.We study more particularly the case when F={m = p_1~(ε1)···p_k~(εk),ε_j∈{0,1},1 ≤ j ≤ k},p_1,...,p_k being distinct prime numbers.     

Cycle factors in strongly connected local tournaments

A digraph without loops, multiple arcs and directed cycles of length two is called a local tournament if the set of in-neighbors as well as the set of out-neighbors of every vertex induces a tournament. A digraph is 2-connected if the removal of an arbitrary vertex results in a strongly connected digraph.In 2004 and 2005, Li and Shu investigated the structure of strongly connected, but not 2-connected tournaments. Using their structural results they were able to give sufficient conditions for a strongly connected tournament T to have complementary cycles or a k-cycle factor, i.e. a set of k vertex disjoint cycles that span the vertex set of T.Inspired by the articles of Li and Shu we develop in this paper the structure necessary for a strongly connected local tournament to be not cycle complementary. Using this structure, we are able to generalize and transfer various results of Li and Shu to the class of local tournaments.     

用多元统计方法分析浙江省各地区的经济结构

本文首先利用因子分析方法研究浙江省11个地级市之间的相关性,利用因子得分得到浙江省11个地级市的综合排名。然后又把因子得分作为新变量,用聚类分析法对各地级市进行分类,把浙江省11个地级市分为4类。在统计分析的基础上对浙江省未来发展提出一些有益的建议,供有关部门参考。     

负压爆炸载荷和数据采集间隔对弹性开孔板动应力集中的影响

基于ANSYS 7.0/LS-DYNA程序,对3 m3 m四边简支,厚度0.025 m,中心开有0.3 m0.3 m方孔的弹性板,在正压和负压三角爆炸载荷作用下的应力响应进行了分析,利用能量密度时间分布函数（TDFED）确定了动应力集中因子,并给出其计算步骤。计算结果表明计算总时间和数据采集时间间隔对动应力集中因子影响较大,而负压荷载影响较小。     

Molecular and functional diversity of vascular endothelial growth factors

Summary Members of the vascular endothelial growth factor (VEGF) family are crucial regulators of neovascularization and are classified as cystine knot growth factors that specifically bind cellular receptor tyrosine kinases VEGFR-1, VEGFR-2, and VEGFR-3 with high but variable affinity and selectivity. The VEGF family has recently been expanded and currently comprises seven members: VEGF-A, VEGF-B, placenta growth factor (PlGF), VEGF-C, VEGF-D, viral VEGF (also known as VEGF-E), and snake venom VEGF (also known as VEGF-F). Although all members are structurally homologous, there is molecular diversity among the subtypes, and several isoforms, such as VEGF-A, VEGF-B, and PlGF, are generated by alternative exon splicing. These splicing isoforms exhibit differing properties, particularly in binding to co-receptor neuropilins and heparin. VEGF family proteins play multiple physiological roles, such as angiogenesis and lymphangiogenesis, while exogenous members (viral and snake venom VEGFs) display activities that are unique in physiology and function. This review will highlight the molecular and functional diversity of VEGF family proteins.     

Tracking customer portfolio composition: A factor analysis approach

In this paper, we address the changing composition of a customer portfolio taking into account actions undertaken by the company to adapt its service offer to market conditions and/or technological innovations. We present a specific methodology to identify clusters of customers in different periods and then compare them over time. The classification process takes into account both qualitative and quantitative aspects of the consumption levels of the services or products offered by the company. The possibility of period‐to‐period variation in the customer portfolio and the service or product offer is also considered, in order to achieve a more realistic scenario. The core of the proposed methodology is related to the family of exploratory factorial and cluster techniques. The customers are classified by using a bicriterial clustering methodology based on ‘tandem’ analysis (multiple factor analysis+cluster analysis of the main factors). The bicriterial approach allows for a compromise between customers' consumption levels (a quantitative criterion) and their consumption/non‐consumption pattern (a qualitative criterion). The evolution of the customer portfolio composition is explored through multiple correspondence analysis. This technique allows visual comparison of the position of different clusters against time and the identification of key changes in customer consumption behavior. The methodology is tested on realistic customer portfolio scenarios for a major telecommunication company. We simulate various scenarios to show the strengths of our proposal. Copyright © 2009 John Wiley & Sons, Ltd.