基于网络的系统性风险测度方法及其在中国银行业的应用

全球金融危机、英国公投脱欧等事件无不冲击着中国银行业,系统性风险的准确预测再一次成为了关注的焦点.随着互联互通程度的增强,网络效应成为了系统性风险研究所必要考虑的因素.完全从网络内部影响的视角,通过计算资产间相关性系数来构建网络,再考虑网络效应推导资产组合理论从而得出新的风险度量公式.之后,选取了10家银行为研究对象,分析了其在2008年1月至2016年6月的风险变化情况.最后,通过对比得出新构建公式预测风险具有准确度高、参考价值大和及时性强等优点.     

Solving a set of global optimization problems by the parallel technique with uniform convergence

In this paper, we consider solving a set of global optimization problems in parallel. The proposed novel algorithm provides uniform convergence to the set of solutions for all problems treated simultaneously. The current accuracy for each particular solution is estimated by the difference in each coordinate from the point of global decision. The main statement is given in the corresponding theorem. For the sake of illustration some computational results with hundreds of multidimensional global problems are provided.     

Developing a risk-assesment methodology in the U.K.defence industry

As a leading defence equipment company, the Dynamics Divisionof British Aerospace Defence Company (BAeDef(DD)) has experiencedthe worst effects of post-Coldwar defence cuts, a global recession,and a determination by the U.K. Government to achieve greatervalue for money in defence procurement. The major tenet of thisnew approach to defence prwurement was 'eyes on, hands off',promoting a shift of the management of project risks from theMinistry of Defence (MOD) to industry. Initial industry reactionwas sceptical but bxame increasingly compliant as tenderingrequirements included visibility of contractors' risk assessment.This paper describes the risk-assessment methodology createdby BAeDef(DD) to meet these changed conditions. The human and organizational aspects of these developments onrisk have helped create a pro-active risk-management cultureat BAeDef(DD). Continuous assessment of project risks providesthe impetus for wider thinking beyond risk-taking or risk-aversionpreferences, leading to greater realism in planning. Decisionsto implement risk resolution measures require competence incost-benefit analysis. The conditions to foster this new behaviourare better-informed senior management, with the rejection ofbad news eliminated at all levels, and the laying of a pathto becoming a learning company.     

Redistribution of longevity risk: The effect of heterogeneous mortality beliefs

Existing literature regarding the natural hedge potential that arises from combining different longevity-linked liabilities typically does not address the question how changes in the liability mix can be obtained. We consider firms who aim to exploit the benefits of natural hedge potential by redistributing their risks, and characterize the risk redistributions that will arise when the parties bargain for a redistribution of risk that weakly benefits them all. We analyze the effects of heterogeneity in the beliefs regarding the probability distribution of future mortality rates on the properties of these risk redistributions, and provide a numerical illustration for a case where an insurer with a portfolio of term assurance contracts and a pension fund with a portfolio of life annuities redistribute their risks.     

A quadratically convergent primal-dual algorithm with global convergence properties for solving optimization problems with equality constraints

This paper presents a globally convergent multiplier method which utilizes an explicit formula for the multiplier. The algorithm solves finite dimensional optimization problems with equality constraints. A unique feature of the algorithm is that it automatically calculates a value for the penalty coefficient, which, under certain assumptions, leads to global convergence.Research sponsored by the Joint Services Electronics Program, Contract F44620-71-C-0087 and the National Science Foundation, Grant GK-37672.     

Implications of personalization offers on demand and supply network design: A case from the golf club industry

Competitive, open and global markets render the consumer more demanding towards manufacturers’ offers. In the past, firms could be competitive by providing value in quality, price and quick delivery. In the new economy, with the coming of e-business, the personalization of products becomes a key competitive factor. Manufacturers need to develop capabilities to fulfill these personalization needs while still respecting price, quality and service. This is an enormous challenge since there are many possible personalization offers that a firm could propose, up to the extreme of delivering a distinct product to each client. An initial step towards developing the appropriate personalization offers and capabilities is the identification of the potential personalization offers and how they affect the key processes within the demand and supply network. The paper presents a framework comprising of eight personalization options that can be combined to form a complete personalized offer. It then contrasts their impact on the demand and supply network. It exploits the industry of golf irons for illustration purposes.     

The pin redistribution problem in multi-chip modules

We introduce thepin redistribution problem (PRP), which arises from layout design ofmulti-chip modules. The problem is to redistribute the pins uniformly over the MCM substrate using a number of pin redistribution layers.Pin redistribution is very important in MCM design because it has been used to not only provide a minimum spacing between signal wires in dense signal distribution layers, but also provide engineering change capability [3, 4]. Moreover, our experience [10] showed that the capacitive coupling noise between vias (one of the major problems in designing MCMs) induced by many layers (up to 63 layers) can be reduced using the pin redistribution technique.The goal of the problem is to minimize the number of layers required to redistribute the entire set. As a net is undefined, a number of challenging issues arise. Three effective approaches are proposed for solving this problem.This work was supported in part by the National Science Foundation under Grant MIP-8921540.This author was supported in part by a Samsung Electronics Fellowship.A preliminary version of this paper appeared in theProceedings of the Fourth Annual IEEE International ASIC Conference and Exhibit, September 1991, pp. 9-2.1–9-2.4.     

Linear generalized synchronization of continuous-time chaotic systems

This paper develops a general approach for constructing a response system to implement linear generalized synchronization (GS) with the drive continuous-time chaotic system. Some sufficient conditions of global asymptotic linear GS between the drive and response continuous-time chaotic systems are attained from rigorously modern control theory. Finally, we take Chua’s circuit as an example for illustration and verification.     

Global chaos in a periodically forced, linear system with a dead-zone restoring force

The Poincare mapping and the corresponding mapping sections for global motions in a linear system possessing a dead-zone restoring force are introduced through switching planes pertaining to two constraints. The global periodic motions based on the Poincare mapping are determined, and the eigenvalue analysis for the stability and bifurcation of periodic motion is carried out. Global chaos in such a system is investigated numerically from the unstable global periodic motions analytically determined. The bifurcation scenario with varying parameters is presented. The mapping structures of periodic and chaotic motions are discussed. The Poincare mapping sections for global chaos are given for illustration. The grazing phenomenon embedded in chaotic motion is observed in this investigation.     

A note on adapting methods for continuous global optimization to the discrete case

In this note we show that various branch and bound methods for solving continuous global optimization problems can be readily adapted to the discrete case. As an illustration, we present an algorithm for minimizing a concave function over the integers contained in a compact polyhedron. Computational experience with this algorithm is reported.     

Global Optimization Using Diffusion Perturbations with Large Noise Intensity

This work develops an algorithm for global optimization.The algorithm is of gradient ascent typeand uses random perturbations.In contrast to the annealing type procedurcs,the perturbation noise intensityis large.We demonstrate that by properly varying the noise intensity,approximations to the global maximumcan be achieved.We also show that the expected time to reach the domain of attraction of the global maximum,which can be approximated by the solution of a boundary value problem,is finite.Discrete-time algorithmsare proposed;recursive algorithms with occasional perturbations involving large noise intensity are developed.Numerical examples are provided for illustration.     

一类变时滞神经网络的全局指数稳定性

本文研究一类变时滞神经网络平衡点的全局指数稳定性.在不要求激活函数全局Lipschitz条件下,利用Lyapunov函数方法,并结合Young不等式和Halanay时滞微分不等式,得到了系统全局指数稳定的充分条件.文末,一个数值例子用以说明本文结果的有效性.     

Application of homogenization theory related to Stokes flow in porous media

We consider applications, illustration and concrete numerical treatments of some homogenization results on Stokes flow in porous media. In particular, we compute the global permeability tensor corresponding to an unidirectional array of circular fibers for several volume-fractions. A 3-dimensional problem is also considered.     

Quantile regression based on counting process approach under semi-competing risks data

In this paper, we investigate the quantile regression analysis for semi-competing risks data in which a non-terminal event may be dependently censored by a terminal event. The estimation of quantile regression parameters for the non-terminal event is complicated. We cannot make inference on the non-terminal event without extra assumptions. Thus, we handle this problem by assuming that the joint distribution of the terminal event and the non-terminal event follows a parametric copula model with unspecified marginal distributions. We use the stochastic property of the martingale method to estimate the quantile regression parameters under semi-competing risks data. We also prove the large sample properties of the proposed estimator, and introduce a model diagnostic approach to check model adequacy. From simulation results, it shows that the proposed estimator performs well. For illustration, we apply our proposed approach to analyze a real data.     

Optimal dynamic asset allocation of pension fund in mortality and salary risks framework

In this paper, we consider the optimal dynamic asset allocation of pension fund with mortality risk and salary risk. The managers of the pension fund try to find the optimal investment policy (optimal asset allocation) to maximize the expected utility of terminal wealth. The market is a combination of financial market and insurance market. The financial market consists of three assets: cashes with stochastic interest rate, stocks and rolling bonds, while the insurance market consists of mortality risk and salary risk. These two non-hedging risks cause incompleteness of the market. By martingale method and dynamic programming principle we first derive the approximate optimal investment policy to overcome the difficulty, then investigate the efficiency of the approximation. Finally, we solve an optimal assets liabilities management(ALM) problem with mortality risk and salary risk under CRRA utility, and reveal the influence of these two risks on the optimal investment policy by numerical illustration.     

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Berkson测量误差模型在工业、农业、流行病学、经济学 等领域有广泛的应用. 本文考虑了一类多元超结构Berkson测量误差模型, 给出了该模型中参数的相合估计, 推导了估计的渐近分布, 并把该方法应用到一元超结构Berkson测量误差模型中, 最后给出了模拟结果和实例分析来说明本文所提出的估计方法的表现.     

基于灰色神经网络的企业风险特征指标动态预测方法研究

根据企业风险特征指标预测问题的特点,提出将灰色系统GM(1,1)模型与神经网络结合建立一阶灰色神经网络预测模型,以实现系统预测的动态性及提高系统的预测精度.但该模型具有一定的局限性,从模型参数的角度给出了该模型只适用于具有"单调"性数据的证明,进而提出了三阶灰色神经网络预测模型,以适应预测数据"非单调"或摆动的情况.但随着系统建模过程中阶数的增加,预测精度会有所下降,因此应根据数据特点选择预测模型.最后,通过实证分析验证了上述模型及证明结论.     

Resurgence relation and global asymptotic analysis of orthogonal polynomials via the Riemann-Hilbert approach

A global asymptotic analysis of orthogonal polynomials via the Riemann-Hilbert approach is presented,with respect to the polynomial degree.The domains of uniformity are described in certain phase variables.A resurgence relation within the sequence of Riemann-Hilbert problems is observed in the procedure of derivation.Global asymptotic approximations are obtained in terms of the Airy function.The system of Hermite polynomials is used as an illustration.     

An interactive approach for vector optimization problems

This paper deals with an interactive approach for vector optimization problems. The best compromise solutions are obtained using one of the methods which depends on the global preference, namely Geoffrion's method. The stability set of the first kind is analyzed and used to reduce the parametric space of the problem. An example is given for the sake of illustration.     

Subjective Aspects of the Art of Decision Analysis: Exploring the Role of Decision Analysis in Decision Structuring,Decision Support and Policy Dialogue

The paper argues that, until very recently, decision analysts have devoted relatively little attention to the processes of problem formulation and subjective judgement in handling ill-structured strategic decision problems. Therefore, following a brief review of existing varieties of decision analysis, a modified policy dialogue' model of decision analysis is presented which integrates decision analysis with decision aids and decision support technology. This model is developed using as an illustration strategic problems drawn from the insurance industry. The paper concludes with some suggestions for the successful application and implementation of decision analysis.