多目标条件风险值的一种近似求解方法

本文研究了一种求解多目标条件风险值问题的近似方法,首先引入了多个损失函数在对应的置信水平下关于一个证券组合的α-VaR损失值,以及α-CVaR损失值概念．α-CVaR损失值表明了在给定的证券组合于置信水平对应的最小信用风险值的条件期望损失值,那么求出这样的最小条件期望损失值的模型构成了一个求解α-CVaR损失值的多目标问题,它的解就是最小条件期望损失值的有效证券组合,即Pareto弱有效解．为了求解它的Pareto弱有效解,我们引进了损失函数对应的优化问题(SCVaR),可以通过求解非线性规划问题(SCVaR)的最优解近似地刻画α—CVaR损失值,这样使得求解α-CVaR损失值变得容易．     

一种多目标条件风险值数学模型

研究了一种多目标条件风险值(CVaR)数学模型理论.先定义了一种多目标损失函数下的α-VaR和α-CVaR值,给出了多目标CVaR最优化模型.然后证明了多目标意义下的α-VaR和α-CVaR值的等价定理,并且给出了对于多目标损失函数的条件风险值的一致性度量性质.最后,给出了多目标CVaR模型的近似求解模型.     

多周期多目标条件风险值模型

在商业、工业、电力和房地产等行业中存在许多复杂的多周期风险决策问题,它的数学模型研究对于解决这些问题具有重要的作用.作者建立了一种新的多周期多目标条件风险值(CVaR)数学模型理论和方法.先定义了一种带时间段的多周期多目标损失函数下的α-VaR和α-CVaR值,给出了一类多周期多目标CVaR最优化模型.然后,证明了多目标意义下的对应模型的等价定理,给出了多周期多目标CVaR模型的近似求解等价模型.最后,建立了一种生产企业在供过于求和供不应求两种情形下产生的多周期双目标CVaR模型,针对一个电力生产企业进行的数值实验,表明了模型可以得到在最小供给的用电损失分布下的各周期下的相匹配供电策略,可以帮助供电部门各个时期供电不平衡状况下的风险控制.     

一种多随从双层条件风险值模型的等价性定理

多随从风险决策问题是供应链风险决策中普遍存在的问题,文章研究了风险厌恶下的多随从双层条件风险值模型,引入了多随从上下层决策的VaR损失值(最小风险值)和CVaR损失值(最小风险值对应的条件期望损失值或条件风险价值度量)概念,提出了一种风险厌恶下的多随从双层条件风险值模型,该模型的目标是求上下层的基于权值的多损失CVaR达最小的最优解,文章证明了它可以通过另一个较容易求解的双层规划模型获得最优解的等价性定理.     

多损失条件风险值的多层规划模型

对于多个损失函数,在给定的置信水平下,首先定义了不超过给定损失值的最小风险值(即Va R值)和基于权值的累积期望损失值(即CVa R损失值)概念,然后建立了一个多损失条件风险值的多层规划模型.该模型的目标是求各层多损失CVa R值达最小的最优策略,并证明了它等价于另一个较容易求解的多层规划模型.最后,给出了三级供应链中多产品的定价与订购的条件风险值模型(三层线性规划模型).     

多损失WCVaR模型的等价性定理

研究了多概率分布簇下的多损失下的WCVaR(Multi Worst Conditional Value-at-Risk)模型等价性定理, 根据概率分布簇的VaR测度值, 定义了多损失下的WCVaR风险测度值和对应的多目标优化模型(MWCVaR), 证明了多目标优化模型(MWCVaR)等价另一个多目标优化模型求解. 对于有限分布簇情形, 在一定条件下, 证明了用有限个分布簇就可以近似计算多损失(MWCVaR)优化模型.     

基于凸概度分布簇下WCVaR模型的有限逼近性

如何求解实际问题中Worst条件风险值模型是一个非常困难的问题,研究了凸概率分布簇下的WCVaR(Worst Conditional Value-at-Risk)模型等价性及其在序列分布簇下的有限逼近性,根据概率分布簇的VaR测度值,定义了WCVaR风险测度值和对应的WCVaR模型,证明了WCVaR模型等价一个另一个数学规划问题求解.在一定条件下,证明了在损失有界情形用有限个分布簇就可以足够近似计算WCVaR模型的最优解,因此,对于解决稳健型条件风险值模型具重要的实际价值.     

基于多目标CVaR模型的证券组合投资的风险度量和策略

本文首先定义了多损失函数下的-αVaR,-αCVaR损失值以及-αCVaR损失值的等价函数,给出了多目标CVaR模型.然后,基于多目标CVaR模型,建立了一个多目标证券组合投资优化模型,得出在多置信水平下的证券组合投资比例和CVaR值,据此建立一种证券组合投资的降低风险优化模型.其降低风险策略是在收益率不变的情形下降低风险和总投资比例.数值实验表明,这种策略是可以通过明显地减少总投资比例来达到降低风险的目的.     

概率约束随机规划的一种近似方法及其它的有效解模式

根据最小风险的投资最优问题，我们给出了一个统一的概率约束随机规划模型。随后我们提出了求解这类概率约束随机规划的一种近似算法，并在一定的条件下证明了算法的收敛性。此外，提出了这种具有概率约束多目标随机规划问题的一种有效解模型。     

带权值的模糊多目标线性规划

本文提出了求解一般多目标性规划问题 (MOL P)的带权值的模糊多目标线性规划方法 .证明了在权值都大于零的条件下 ,与 (MOLP)原问题对应的带权值的模糊多目标线性规划问题的最优解为模糊有效解 ,从而为原问题的有效解 ,并作了实例验证 .     

UNIFORM APPROXIMATION OF A MULTIOBJECTIVE OPTIMIZATION SEQUENCE

In this paper the Pareto efficiency of a uniformly convergent multiobjective optimization sequence is studied. We obtain some relation between the Pareto efficient solutions of a given multiobjective optimization problem and those of its uniformly convergent optimization sequence and also some relation between the weak Pareto efficient solutions of the same optimization problem and those of its uniformly convergent optimization sequence. Besides, under a compact convex assumption for constraints set and a certain convex assumption for both objective and constraint functions, we also get some sufficient and necessary conditions that the limit of solutions of a uniformly convergent multiobjective optimization sequence is the solution of a given multiobjective optimization problem.     

On a Transform Method for the Efficient Computation of Conditional V@R (and V@R) with Application to Loss Models with Jumps and Stochastic Volatility

In this paper we consider Fourier transform techniques to efficiently compute the Value-at-Risk and the Conditional Value-at-Risk of an arbitrary loss random variable, characterized by having a computable generalized characteristic function. We exploit the property of these risk measures of being the solution of an elementary optimization problem of convex type in one dimension. An application to univariate loss models driven by Lévy or stochastic volatility risk factors dynamic is finally reported.     

Living on the edge: how risky is it to operate at the limit of the tolerated risk?

This paper studies some of the implicit risks associated with strategies followed by a risk averse investor who maximizes the expected value of his final wealth, subject to a risk tolerance constraint characterized in terms of a convex risk measure such as Conditional Value-at-Risk. Embedded probability measures are uncovered using duality theory; these are used to assess the probability of surpassing a standard Value-at-Risk threshold. Using one of these embedded probabilities, a closed-form measure of the financial cost of hedging the loss exposure associated to the optimal strategies is derived and shown to be, under certain assumptions, a coherent measure of risk.     

多目标规划的圆锥有效解

本文利用有限维向量空间中圆锥的概念,引入了多目标规划问题的一种新的有效解－圆锥有效解,并讨论了这种有效解的性质。同时,讲座了圆锥有效解与Pareto有效解以及绝对最优解之间的关系。最后,通过引进目标总值差异概念,分析了圆锥有效解的主要特点。     

G恰当有效点集和G恰当有效解集的连通性

与多目标规划问题的G恰当有效解相应，引进了集合的G恰当有效点的概念，并互研究了G恰当有效点集和G恰当有效解集的连通性．利用所得的结果，还获得多目标规划问题的Pareto有效解集是连通的一个新的结论。     

Solvency II,regulatory capital,and optimal reinsurance: How good are Conditional Value-at-Risk and spectral risk measures?

We study the problem of optimal reinsurance as a means of risk management in the regulatory framework of Solvency II under Conditional Value-at-Risk and, as its natural extension, spectral risk measures. First, we show that stop-loss reinsurance is optimal under both Conditional Value-at-Risk and spectral risk measures. Spectral risk measures thus constitute a more general class of suitable regulatory risk measures than specific Conditional Value-at-Risk. At the same time, the established type of stop-loss reinsurance can be maintained as the optimal risk management strategy that minimizes regulatory capital. Second, we derive the optimal deductibles for stop-loss reinsurance. We show that under Conditional Value-at-Risk, the optimal deductible tends towards restrictive and counter-intuitive corner solutions or “plunging”, which is a serious objection against its use in regulatory risk management. By means of the broader class of spectral risk measures, we are able to overcome this shortcoming as optimal deductibles are now interior solutions. Especially, the recently discussed power spectral risk measures and the Wang risk measure are shown to avoid any plunging. They yield a one-to-one correspondence between the risk parameter and the optimal deductible and, thus, provide economically plausible risk management strategies.     

多目标最优化G-恰当有效解集的存在性和连通性

本文证明了非空紧凸集上拟凸多目标最优化问题的G-恰当有效解的存在性．在此基础上，得到了向量目标函数既是似凸又是拟凸的多目标最优化问题的G-恰当有效解集是连通的结论．同时，还给出一个关于Pareto有效解集连通性的新结果．     

Credit risk optimization with Conditional Value-at-Risk criterion

This paper examines a new approach for credit risk optimization. The model is based on the Conditional Value-at-Risk (CVaR) risk measure, the expected loss exceeding Value-at-Risk. CVaR is also known as Mean Excess, Mean Shortfall, or Tail VaR. This model can simultaneously adjust all positions in a portfolio of financial instruments in order to minimize CVaR subject to trading and return constraints. The credit risk distribution is generated by Monte Carlo simulations and the optimization problem is solved effectively by linear programming. The algorithm is very efficient; it can handle hundreds of instruments and thousands of scenarios in reasonable computer time. The approach is demonstrated with a portfolio of emerging market bonds. Received: November 1, 1999 / Accepted: October 1, 2000?Published online December 15, 2000