A novel single-loop procedure for time-variant reliability analysis based on Kriging model

This paper proposes a novel single-loop procedure for time-variant reliability analysis based on a Kriging model. A new strategy is presented to decouple the double-loop Kriging model for time-variant reliability analysis, in which the extreme value response in double-loop procedure is replaced by the best value in the current sampled points to avoid the inner optimization loop. Consequently, the extreme value response surface for time-variant reliability analysis can be directly established through a single-loop Kriging surrogate model. To further improve the accuracy of the proposed Kriging model, two methods are provided to adaptively choose a new sample point for updating the model. One method is to apply two commonly used learning functions to select the new sample point that resides as close to the extreme value response surface as possible, and the other is to apply a new learning function to select the new point. Synchronously, the corresponding different stopping criteria are also provided. It is worth nothing that the proposed single-loop Kriging model for time-variant reliability analysis is for a single time-variant performance function. To verify the proposed method, it is applied to four examples, two of which have with random process and others have not. Other popular methods for time-variant reliability analysis including the existing single-loop Kriging model are also used for the comparative analysis and their results testify the effectiveness of the proposed method.     

A Bayesian approach to equity valuation

Quantitative approaches to equity valuation in common use includemethods based upon the dividend discount model, which equatesthe value of an enterprise to the present value of the dividendsthat it pays to its owners, and methods which begin from therelation between the current share price and the expected earningsfor the next 12 months. A short coming of each of these approachesis that they are forced to take near-term earnings and dividendforecasts as their basic data, when in fact the values theyare trying to estimate are dominated by longer-term considerations.As a result, model estimates are often too sensitive to changesin near-term earnings which have little effect on a company'slong-term prospects. In relatively efficient markets, however, the price of a company'sshares at any time reflects information which is not readilyquantifiable and which may represent a longer-term view. Thatinformation can be used to create a stable quantitative valuationmodel in which the information content of near-term changesis balanced against longer-term considerations via a Bayesianupdating procedure. The structure of the Bayesian valuation model is essentiallythat of a truncated dividend discount model, where the fairvalue today is expressed as the present value of a terminaldividend (i.e. the fair value at a future date, discounted tothe present), plus the present value of the interim dividends.In the Bayesian model, the terminal dividend is a variable whoseprobability distribution depends upon the sequence of earningsbetween the valua tion date and the terminal date.     

二维可压缩油水两相渗流动边值问题的特征差分方法

可压缩可混溶油、水两相渗流动边值问题的研究,对重建盆地发育中油气资源运移、聚集的历史和评估油气资源的勘探与开发有重要的价值,其数学模型是一组非线性偶合偏微分方程组的动边值问题．本文对二维有界域的两类边值问题提出一类新的特征差分格式,应用区域变换、时间的变步长、粗细网格配套、变分形式、先验估计的理论和技巧,得到了最佳阶l2误差估计结果．将J．Douglas,Jr．提出的著名方法,成功地拓广到这一新领域,并得到实质性进展．它对这一领域的模型分析,数值方法和软件研制均有重要的价值．     

基于蒙特卡洛-马尔科夫链(MCMC)的ARMA模型选择

AIC与SIC等准则函数方法是ARMA模型选择过程中经常使用的方法。但是,当模型的阶数很高时,无法计算并比较每一个备选模型的准则函数值。本文提出了一个基于蒙特卡洛-马尔科夫链方法的随机模型生成方法,以产生准则函数值最小的备选模型。实际应用表明本文的方法在处理拥有大量备选模型的ARMA模型选择问题时有很好的效果。     

Risk models based on time series for count random variables

In this paper, we generalize the classical discrete time risk model by introducing a dependence relationship in time between the claim frequencies. The models used are the Poisson autoregressive model and the Poisson moving average model. In particular, the aggregate claim amount and related quantities such as the stop-loss premium, value at risk and tail value at risk are discussed within this framework.     

Estimating bank default with generalised extreme value regression models

The paper proposes a novel model for the prediction of bank failures, on the basis of both macroeconomic and bank-specific microeconomic factors. As bank failures are rare, in the paper we apply a regression method for binary data based on extreme value theory, which turns out to be more effective than classical logistic regression models, as it better leverages the information in the tail of the default distribution. The application of this model to the occurrence of bank defaults in a highly bank dependent economy (Italy) shows that, while microeconomic factors as well as regulatory capital are significant to explain proper failures, macroeconomic factors are relevant only when failures are defined not only in terms of actual defaults but also in terms of mergers and acquisitions. In terms of predictive accuracy, the model based on extreme value theory outperforms classical logistic regression models.     

Analytical pricing of defaultable discrete coupon bonds in unified two-factor model of structural and reduced form models

Pricing formulae for defaultable corporate bonds with discrete coupons (under consideration of the government taxes) in the united two-factor model of structural and reduced form models are provided. The aim of this paper is to generalize the two-factor structural model for defaultable corporate discrete coupon bonds (considered in [1]) into the unified model of structural and reduced form models. In our model the bond holders receive the stochastic coupon (which is the discounted value of a predetermined value at the maturity) at predetermined coupon dates and the face value (debt) and the coupon at the maturity as well as the effect of government taxes which are paid on the proceeds of an investment in bonds is considered. The expected default event occurs when the equity value is not sufficient to pay coupon or debt at the coupon dates or maturity and the unexpected default event can occur at the first jump time of a Poisson process with the given default intensity provided by a step function of time variable. We provide the model and pricing formula for equity value and using it calculate expected default barrier. Then we provide pricing model and formula for defaultable corporate bonds with discrete coupons and consider its duration.     

基于初始值和背景值改进的GM(1, 1)模型优化与应用

针对在现实生活中, 经典GM(1,1)模型预测精度不稳定, 且以往的优化方法大部分具有片面性的缺点, 文章对经典GM(1,1)模型背景值与初始值进行改进, 提出了一种组合优化方法:根据动态寻优原则, 将背景值设为变量, 其参数以及时间响应式由MRE取最小值时确定;同时, 采用差分方程取代以x⁽¹⁾(1)为固定点的静态方程。将初始值和背景值看作变量, 以系统地减少模型误差。结合国内石油年消费量数据, 分别应用经典和改进后的GM(1,1)模型进行计算和误差对比, 验证了改进后的模型精度要显著优于经典模型。     

Characterization of the Value Process in Robust Efficient Hedging

This paper examines the value function of a partial hedging problem under model ambiguity. The study is based on a dual representation of the value function obtained by the authors. We formulate a family of control problems, whose value processes are characterized as solutions of a backward stochastic differential equation and give a sufficient condition to identify optimal controls.     

A discrete time optimal control model with uncertainty for dynamic machine allocation problem and its application to manufacturing and construction industries

This paper proposed a discrete time optimal control model in which machine failure time is modeled assuming a Weibull distribution and machine productivity is regarded as a fuzzy variable for dealing with a dynamic machine allocation problem (DMAP) in manufacturing and construction industries. The aim is to maximize total production or construction throughput when uncertainties such as machine breakdowns are taken into account. A failure probability-work time equation is presented to describe the relationship between machine failure probability and mean time to work. To transform the uncertain optimal control model into a deterministic one, the expected value model (EVM) was introduced for forming an equivalent crisp model. The fuzzy variables in the model are also defuzzified by using an expected value operator with an optimistic–pessimistic index. Then a number of lemmas and theorems are presented and proved to formulate the theoretical algorithm so that the crisp model of the DMAP can be solved. Three actual construction and production projects are used as practical application examples. The theoretical algorithm results for the three project examples are compared with a particle swarm optimization approach and a genetic algorithm method, which demonstrates the practicality and efficiency of our optimization method.     

Dantzig-Wolfe Reformulation for the Network Pricing Problem with Connected Toll Arcs

This paper considers a pricing problem on a network with connected toll arcs and proposes a Dantzig-Wolfe reformulation for it. The model is solved with column generation and the gap between the optimal integer value and the linear relaxation optimal value is shown to be at least as good as the one from the mixed-integer formulation proposed in the literature. Numerical results on different sets of instances are reported, showing that in many cases the proposed model performs strictly better.     

Probabilistic analysis of a capactiated vehicle routing problem—I

A fleet of vehicles located at a service center must serve the demands of a set of customers. The amount delivered by each vehicle cannot exceed its capacity and a customer’s demand may not be split over more than one vehicle. In our model, customers locations, as well as their demands are independent identically distributed. Simchi-Levi and Bramel [10] determined the asymptotic value of the optimal solution in this model. We prove here a sharp rate of convergence to the asymptotic value     

跳-扩散过程下具有目标杠杆比率的违约风险模型

本文在研究公司债务违约风险时,假设公司价值的动态变化服从跳-扩散过程;假设公司可以根据公司价值的变化调整其债务水平,因而存在公司的目标杠杆比率,违约边界定义为公司历史价值的对数加权平均;当公司价值下降到违约边界时发生债务违约.数值模拟表明公司债务的信用利差对公司的目标杠杆比率和跳过程的强度具有高度的敏感性.本文的模型解决了在长期和短期信用利差预测时结构化模型和约化模型存在的缺陷.     

基于修正区间模糊Shapley值的“一带一路”PPP项目利益分配模型

多方合作的“一带一路”基础设施PPP项目是互联互通的基石,公平合理地分配项目利益则是保障其顺利实施的关键。为了构建科学的利益分配模型,考虑项目参与方组建的合作联盟预期收益为模糊数且分配时受多种因素影响,本文首先,基于区间模糊Shapley值构建“一带一路”PPP项目利益分配初始模型;然后,识别出利益分配影响因素并量化参与方的投入分担程度,据此修正初始的利益分配模型;最后,结合实际案例,将该模型与现存方法进行对比分析,结果显示本模型的可操作性更强,针对影响因素系数的测算更为精准,整体具有显著优势。     

向量灰色模型的建立及应用

针对传统多变量灰色预测模型(MGM(1,m))有时存在的建模数据失真问题,以系统中关联变量具有趋同性为基础,提出了一种新的模型——向量灰色模型(VGM(1,m))。与MGM(1,m)模型相比,VGM(1,m)结构更简单,模型参数更少,从而有利于参数的估计。将VGM(1,m)、MGM(1,m)、GM(1,1)模型应用于四个实例的分析,结果表明VGM(1,m)消除了MGM(1,m)的建模失真现象,模型的稳定性得到了增强。进一步,与GM(1,1)建模结果相比,VGM(1,m)模型的预测精度更高,即新模型有更好的泛化性。     

Risk management strategies via minimax portfolio optimization

Recent extreme economic developments nearing a worst-case scenario motivate further examination of minimax linear programming approaches for portfolio optimization. Risk measured as the worst-case return is employed and a portfolio from maximizing returns subject to a risk threshold is constructed. Minimax model properties are developed and parametric analysis of the risk threshold connects this model to expected value along a continuum, revealing an efficient frontier segmenting investors by risk preference. Divergence of minimax model results from expected value is quantified and a set of possible prior distributions expressing a degree of Knightian uncertainty corresponding to risk preference determined. The minimax model will maximize return with respect to one of these prior distributions providing valuable insight regarding an investor’s risk attitude and decision behavior. Linear programming models for financial firms to assist individual investors to hedge against losses by buying insurance and a model for designing variable annuities are proposed.     

基于参数设计的信噪比交叉效率评价方法

针对DEA交叉效率评价过程中没有考虑自评与互评效率的作用而主观赋予相同权重导致交叉效率评价值不准确的问题.文章基于参数设计的思想,依据试验设计中可控与不可控因素的作用机理区分自评权重和互评权重对所评价决策单元交叉效率的影响与作用,将其界定为可控与不可控因素的管理学属性,明确不同权重作用机理;引入信噪比作为衡量决策单元交叉效率评价时的性能指标,实施DEA交叉效率评价方法的改进,设计出DEA信噪比交叉效率集结方法,从而实现交叉效率的集结方式由单一考虑交叉效率波动的均值转化为综合考虑交叉效率波动情况(均值与方差),交叉效率评价值用信噪比交叉效率替代交叉效率平均值更具有统计学意义并可从管理学角度解释,评价结果也具有更高的可区分性;最后通过算例分析验证了交叉效率评价理论上的必要性和该方法的合理性与可行性,同时发现了交叉效率评价中存在CCR有效DMU序位超出了有效DMU范围现象,建议应实施同质DMU检验和评价值归一化.文章的研究也为提高DEA交叉效率测算的准确性提供一种新思路.     

基于语言值2元组的多属性决策方法

利用2元组方法建立了一个语言值决策模型和LOW A算子模型,这两个模型具有可操作性强和语义明确等优点,特别是充分利用了语言值所含的信息,提高了决策结果的精度.最后,利用这两个模型给出了基于语言值的多属性群决策方法,同时给出一个应用实例.     

Potential,value, and coalition formation

In this paper, a simple probabilistic model of coalition formation provides a unified interpretation for several extensions of the Shapley value. Weighted Shapley values, semivalues, weak (weighted or not) semivalues, and the Shapley value itself appear as variations of this model. Moreover, some notions that have been introduced in the search of alternatives to Shapley’s seminal characterization, as ‘balanced contributions’ and the ‘potential’ are reinterpreted from this point of view. Natural relationships of these conditions with some mentioned families of ‘values’ are shown. These reinterpretations strongly suggest that these conditions are more naturally interpreted in terms of coalition formation than in terms of the classical notion of ‘value.’