Conditional tail risk measures for the skewed generalised hyperbolic family

This paper deals with the estimation of loss severity distributions arising from historical data on univariate and multivariate losses. We present an innovative theoretical framework where a closed-form expression for the tail conditional expectation (TCE) is derived for the skewed generalised hyperbolic (GH) family of distributions. The skewed GH family is especially suitable for equity losses because it allows to capture the asymmetry in the distribution of losses that tends to have a heavy right tail. As opposed to the widely used Value-at-Risk, TCE is a coherent risk measure, which takes into account the expected loss in the tail of the distribution. Our theoretical TCE results are verified for different distributions from the skewed GH family including its special cases: Student-t, variance gamma, normal inverse gaussian and hyperbolic distributions. The GH family and its special cases turn out to provide excellent fit to univariate and multivariate data on equity losses. The TCE risk measure computed for the skewed family of GH distributions provides a conservative estimator of risk, addressing the main challenge faced by financial companies on how to reliably quantify the risk arising from the loss distribution. We extend our analysis to the multivariate framework when modelling portfolios of losses, allowing the multivariate GH distribution to capture the combination of correlated risks and demonstrate how the TCE of the portfolio can be decomposed into individual components, representing individual risks in the aggregate (portfolio) loss.     

Asset pricing for an affine jump‐diffusion model using an FD method of lines on nonuniform meshes

We present a novel numerical scheme for the valuation of options under a well‐known jump‐diffusion model. European option pricing for such a case satisfies a 1 + 2 partial integro‐differential equation (PIDE) including a double integral term, which is nonlocal. The proposed approach relies on nonuniform meshes with a focus on the discontinuous and degenerate areas of the model and applying quadratically convergent finite difference (FD) discretizations via the method of lines (MOL). A condition for observing the time stability of the fully discretized problem is given. Also, we report results of numerical experiments.     

A hybrid descent method for solving a convex constrained optimization problem with applications

The purpose of this paper is to introduce a hybrid descent algorithm for finding a common point in fixed‐point sets of quasi‐nonexpansive mappings and solution sets of variational inequality problems. In the framework of Hilbert spaces, the strong convergence of the hybrid descent algorithm is established. Numerical experiments for the bandwidth allocation, which demonstrate the effectiveness, performance, and convergence of the proposed algorithm, are provided.     

Balanced allocation on graphs: A random walk approach

We propose algorithms for allocating n sequential balls into n bins that are interconnected as a d‐regular n‐vertex graph G, where d ≥ 3 can be any integer. In general, the algorithms proceeds in n succeeding rounds. Let ? > 0 be an integer, which is given as an input to the algorithms. In each round, ball 1 ≤ t ≤ n picks a node of G uniformly at random and performs a nonbacktracking random walk of length ? from the chosen node and simultaneously collects the load information of a subset of the visited nodes. It then allocates itself to one of them with the minimum load (ties are broken uniformly at random). For graphs with sufficiently large girths, we obtain upper and lower bounds for the maximum number of balls at any bin after allocating all n balls in terms of ?, with high probability.     

考虑边流量有限的网络路径博弈问题研究

考虑每条边有流量约束的网络路径博弈问题, 根据收益函数单调递增的特点分析其内在零和性质, 并建模为存在公共边的路径博弈模型。在寻找均衡解的过程中, 首先考虑非合作的情形, 在局中人风险中性的假设下, 给出了求Nash均衡流量分配的标号法并证明该均衡分配的唯一性。接着进一步考虑局中人合作的可能性, 给出模型求得所有局中人的整体最大收益, 并基于纳什谈判模型给出目标函数为凸函数的数学模型确定唯一收益分配方案。事实上, 该方案是对剩余价值的平均分配。最后给出一个算例, 验证本文理论和方法的可行性。关键词:流量约束; 均衡流量; 网络路径博弈; 收益分配     

考虑联盟结构的联合采购合作剩余分配博弈分析

联合采购合作剩余分配本质是在最大联盟剩余值与最小期望分配值之间的谈判协商过程。当前联合采购合作剩余分配研究主要基于参与企业地位无差别假设,忽略了联盟结构对剩余分配具有明显影响。基于联盟形成的层次结构,研究论证了采购企业通过组建小联盟形式参与更大联盟的联合采购,可提升其在分配谈判中的话语权。通过算例分析表明,考虑联盟结构的联合采购合作剩余分配相对于不考虑联盟结构得到的分配方案更具公平性和合理性。     

航空公司中的飞行员配置研究

随着新航线的开辟和新飞机的投入使用,航空公司的任务量急剧增长,飞行员需求的估计和机组的合理配置变得日益重要。本文基于实际工作需求,提出一类用于评估飞行员数量,并进行机组均衡配置的整数规划模型,为航空公司进行飞行员的数量评估和任务分配提供决策支持。本文在以下两个方面做出改进:1)加入国际长途航线,研究国内短途航线和国际长途航线混合搭配情况下飞行员的配置问题;2)鉴于大型整数规划求解的复杂性,通过评估航空公司所需要的飞行员数量的下界,为决策人员制定中长期规划提供依据。本文通过启发式算法进行飞行员的配置,计算结果接近理论问题的下界,证明了算法的有效性。     

Four-dimensional scheduling for uplink dynamic bandwidth allocation in OFDM-PON

Orthogonal frequency division multiplexing passive optical network (OFDM-PON) has been considered a promising access solution to meet the variable bandwidth demand. In this paper, a novel scheduling for dynamic bandwidth allocation (DBA) at medium access control (MAC) layer is proposed for uplink transmission of OFDM-PON. In order to utilize the bandwidth efficiently, scheduling in four dimensions is adopted in the proposed DBA algorithm. Four dimensions stand for frequency domains, time domains, modulation formats and power allocations. The algorithm is quite flexible. Simulation results and analysis show that the proposed algorithm can efficiently utilize the OFDM bandwidth and make the system highly energy-efficient.     

Decision support system for mass dispensing of medications for infectious disease outbreaks and bioterrorist attacks

A simulation and decision support system, RealOpt^©, for planning large-scale emergency dispensing clinics to respond to biological threats and infectious disease outbreaks is described. The system allows public health administrators to investigate clinic design and staffing scenarios quickly. RealOpt^© incorporates efficient optimization technology seamlessly interfaced with a simulation module. The system's correctness and computational advantage are validated via comparisons against simulation runs of the same model developed on a commercial system. Simulation studies to explore facility layout and staffing scenarios for smallpox vaccination and for an actual anthrax-treatment dispensing exercise and post event analysis are presented. The system produces results consistent with the model built on the commercial system, but requires only a fraction of the computational time. Each smallpox scenario runs within 1 CPU minute on RealOpt^©, versus run times of over 5–10 h on the commercial system. The system's fast computational time enables its use in large-scale studies, in particular an anthrax response planning exercise involving a county with 864,000 households. The computational effort required for this exercise was roughly 30 min for all scenarios considered, demonstrating that RealOpt^© offers a very promising avenue for pursuing a comprehensive investigation involving a more diverse set of scenarios, and justifying work towards development of a robust system that can be widely deployed for use by state, local, and tribal health practitioners. Using our staff allocation and assignments for the Anthrax field exercise, DeKalb county achieved the highest throughput among all counties that simultaneously conducted the same scale of Anthrax exercise at various locations, with labor usage at or below the other counties. Indeed, DeKalb exceeded the targeted number of households, and it processed 50% more individuals compared to the second place county. None of the other counties achieved the targeted number of households. The external evaluators commented that DeKalb produced the most efficient floor plan (with no path crossing), the most cost-effective dispensing (lowest labor/throughput value), and the smoothest operations (shortest average wait time, average queue length, equalized utilization rate). The study proves that even without historical data, using our system one can plan ahead and be able to wisely estimate the required labor resources. The exercise also revealed many areas that need attention during the operations planning and design of dispensing centers. The type of disaster being confronted (e.g., biological attack, infectious disease outbreak, or a natural disaster) also dictates different design considerations with respect to the dispensing clinic, facility locations, dispensing and backup strategies, and level of security protection. Depending on the situation, backup plans will be different, and the level of security and military personnel, as well as the number of healthcare workers required, will vary. In summary, the study shows that a real-time decision support system is viable through careful design of a stand-alone simulator coupled with powerful tailor-designed optimization solvers. The flexibility of performing empirical tests quickly means the system is amenable for use in training and preparation, and for strategic planning before and during an emergency situation. The system facilitates analysis of “what-if'' scenarios, and serves as an invaluable tool for operational planning and dynamic on-the-fly reconfigurations of large-scale emergency dispensing clinics. It also allows for “virtual field exercises” to be performed on the decision support system, offering insight into operations flow and bottlenecks when mass dispensing is required for a region with a large population. The system, designed in modular form with a flexible implementation, enables future expansion and modification regarding emergency center design with respect to treatment for different biological threats or disease outbreaks. Working with emergency response departments, further fine-tuning and development of the system will be made to address different biological attacks and infectious disease outbreaks, and to ensure its practicality and usability.     

关于无风险资产不存在时资产组合选择的研究

以往关于资产组合选择的研究大多假设市场上存在无风险资产,但无风险资产实际上是不存在的.当不存在无风险资产时,假设投资者的效用定义在消费上,消费一直是投资者财富的一个固定比例,投资者的最优资产组合由两部分组成:短视的资产组合和对冲组合.假设只有股票和债券两种风险资产,当股票和债券的风险具有负的相关性时,投资者现在会消费更多,同时也会在股票上投资更多;两者正相关时,投资者无法降低风险,会减持股票并降低当前消费;两者不相关时,投资者持有的股票权重和存在无风险资产时一样.最后,还推导出了多种资产情况下最优消费和资产组合的解析表达式.