基于Copula的供应链金融质物组合价格风险测度研究

本文选取白银、铝和铜三种供应链金融质物作为研究对象,在分析三种质物收益率统计特征的基础上,引入Copula模型刻画供应链金融业务中质物收益率的“尖峰厚尾”特征以及质物收益率之间的非线性相关结构;采用Monte Carlo模拟方法测度考虑到极端情况下的质物组合价格风险值CVaR;利用时间平方根法则测度长周期视角下质物组合的价格风险。将CVaR与VaR测度结果进行对比,比较分析短期价格风险与长期价格风险,将Copula模型与传统风险测度方法下计算出的风险值进行对比,以期选取最优测度供应链金融质物组合长期价格风险模型。研究结果表明:从单一质物价格波动特征来看,三种单一质物的收益率均存在非正态分布和“尖峰厚尾”特征,具有一般金融资产收益率分布的特点。从模型的有效性来看,第一,CVaR比VaR能够更好地、全面地测度供应链金融质物组合的价格风险;第二,基于Copula模型的风险测度结果比传统集成风险测度结果的准确性高;第三,平方欧式距离法结果表明在五种Copula模型中,t-Copula是最优刻画供应链金融质物组合收益率间的相依关系的模型。从长短期风险测度结果来看,随着风险期限的增加,质物组合的价格风险值随之增大,以往研究中用短期风险测度往往会低估商业银行所面临的价格风险,不利于商业银行资金信贷的优化配置。得到的结论对我国商业银行开展供应链金融业务防范价格风险提供了量化支持。     

Mixed integer linear models for the optimization of dynamical transport networks

We introduce a mixed integer linear modeling approach for the optimization of dynamic transport networks based on the piecewise linearization of nonlinear constraints and we show how to apply this method by two examples, transient gas and water supply network optimization. We state the mixed integer linear programs for both cases and provide numerical evidence for their suitability.     

多元弱样条空间和最小确定集

根据研究多元弱样条函数的B—网方法,给出了某些多元弱样条函数空间的最小确定集的构造方法,并从而求出了它们的维数．本文还讨论了对偶基的局部支集性质。     

风险项目的投资期权分析

本文讨论了风险投资家向企业主融资时的投资期权,求出了投资期权的表达式,并对其中的一些参数进行了分析.     

四元数阵重行列式与复阵行列式的关系

指出四元数阵重行列式可用复阵行列式来表示，于是，复阵的伴随矩阵、求逆阵公式、秩的下界等，都可相应地推广到四元数阵．     

供应链系统转变为供需网系统研究

为帮助传统企业顺利转变为供需网企业,提出了供应链系统向供需网系统的转变研究.该研究利用企业节点数据化,通过企业节点的改造及供应链节点与供需网的连接操作达到系统转变的目的.在sc节点数据结构及自身系统功能模块改造的基础上,着重思考了供应链节点连入SDN中的算法思想.通过非线性择优连接方法避免了造成系统易攻击性的枢纽节点的出现.给出了连接算法流程,并以一个示例演示了此连接算法,从中也验证了非线性择优连接的有效性.     

Group activity selection problem with approval preferences

We consider a setting where one has to organize one or several group activities for a set of agents. Each agent will participate in at most one activity, and her preferences over activities depend on the number of participants in the activity. The goal is to assign agents to activities based on their preferences in a way that is socially optimal and/or stable. We put forward a general model for this setting, which is a natural generalization of anonymous hedonic games. We then focus on a special case of our model where agents’ preferences are binary, i.e., each agent classifies all pairs of the form ‘(activity, group size)’ into ones that are acceptable and ones that are not. We formulate several solution concepts for this scenario, and study them from the computational point of view, providing hardness results for the general case as well as efficient algorithms for settings where agents’ preferences satisfy certain natural constraints.     

Programming With Models: Writing Statistical Algorithms for General Model Structures With NIMBLE

We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a particular model and/or nodes, such as creating a Metropolis-Hastings sampler for a particular block of nodes. The second stage allows repeated execution of computations using the results of the first stage. To achieve efficient second-stage computation, NIMBLE compiles models and functions via C++, using the Eigen library for linear algebra, and provides the user with an interface to compiled objects. The NIMBLE language represents a compilable domain-specific language (DSL) embedded within R. This article provides an overview of the design and rationale for NIMBLE along with illustrative examples including importance sampling, Markov chain Monte Carlo (MCMC) and Monte Carlo expectation maximization (MCEM). Supplementary materials for this article are available online.     

含有S,S-二氧-二苯并噻吩和芴酮单元的白光电致发光聚合物的合成与性能

通过Suzuki缩聚反应将发橙红光的2,7-二(2-噻吩基)-9-芴酮(DFT)引入聚芴主链,实现了两元光单分子聚合物白光发射,该聚合物作为发光层的电致发光器件ITO/PEDOT:PSS/PVK/发光层/CsF/Al的最大流明效率为1.0cd/A,色坐标为(0.41,0.36)。再将S,S-二氧-二苯并噻吩(SO)引入聚合物主链中,其电致发光器件的最大流明效率为3.5cd/A,色坐标为(0.34,0.32);此白光器件表现出优异的光谱稳定性。通过将DFT和SO单元引入聚芴主链,可获得有望应用于固态发光与显示的白光电致发光材料。更多还原