Assemble‐to‐Order Inventory Management via Stochastic Programming: Chained BOMs and the M‐System

We study an inventory management mechanism that uses two stochastic programs (SPs), the customary one‐period assemble‐to‐order (ATO) model and its relaxation, to conceive control policies for dynamic ATO systems. We introduce a class of ATO systems, those that possess what we call a “chained BOM.” We prove that having a chained BOM is a sufficient condition for both SPs to be convex in the first‐stage decision variables. We show by examples the necessity of the condition. For ATO systems with a chained BOM, our result implies that the optimal integer solutions of the SPs can be found efficiently, and thus expedites the calculation of control parameters. The M system is a representative chained BOM system with two components and three products. We show that in this special case, the SPs can be solved as a one‐stage optimization problem. The allocation policy can also be reduced to simple, intuitive instructions, of which there are four distinct sets, one for each of four different parameter regions. We highlight the need for component reservation in one of these four regions. Our numerical studies demonstrate that achieving asymptotic optimality represents a significant advantage of the SP‐based approach over alternative approaches. Our numerical comparisons also show that outside of the asymptotic regime, the SP‐based approach has a commanding lead over the alternative policies. Our findings indicate that the SP‐based approach is a promising inventory management strategy that warrants further development for more general systems and practical implementations.     

Revealed Altruism1

This paper develops a nonparametric theory of preferences over one's own and others' monetary payoffs. We introduce “more altruistic than” (MAT), a partial ordering over such preferences, and interpret it with known parametric models. We also introduce and illustrate “more generous than” (MGT), a partial ordering over opportunity sets. Several recent studies focus on two‐player extensive form games of complete information in which the first mover (FM) chooses a more or less generous opportunity set for the second mover (SM). Here reciprocity can be formalized as the assertion that an MGT choice by the FM will elicit MAT preferences in the SM. A further assertion is that the effect on preferences is stronger for acts of commission by FM than for acts of omission. We state and prove propositions on the observable consequences of these assertions. Finally, empirical support for the propositions is found in existing data from investment and dictator games, the carrot and stick game, and the Stackelberg duopoly game and in new data from Stackelberg mini‐games.     

具有隐含期权的商业银行利率风险测量与管理:凸度缺口模型

研究基于凸度缺口模型的具有隐含期权的商业银行利率风险管理问题 .提出隐含期权型金融工具利率风险测量的杂合低偏差序列 Monte Carlo方法 (HPL- MC) ,构建利率风险管理的目标规划模型 .计算实例表明 ,与久期缺口模型相比 ,凸度缺口模型在鲁棒性和减少利率风险方面效果更好     

局部完全对称的亚半正定矩阵的行列式的不等式

本文得到一个局部完全对称的亚半正定矩阵的行列式的不等式，拓广了[2，3]的结果．     

债券久期和凸性的计算方法探讨

通过分析比较债券的麦考利久期和修正久期在概念和计算方法上的差异,指出修正久期才是债券和债券组合风险管理的核心工具,当利率变化幅度较大的情况下,债券的凸性应该被纳入以改善修正久期的业绩。由于附息债券或债券组合均可被分解为一系列零息债券的组合,根据“组合收益率是组合中各成份证券收益率的加权平均”的基本原理,给出了一种基于零息债券修正久期和凸性的附息债券以及债券组合修正久期和凸性的计算方法,并通过实例阐述了债券修正久期和凸性的计算及应用。     

商业银行利率风险管理中久期技术运用初探

我国利率市场化改革已进入实质性阶段,今后商业银行如何管理利率风险,在利率市场波动的冲击保持盈利和安全经营。久期技术是较为良好的动态风险衡量和管理模型,通过结合凸性概念还可推广运用于隐含期权性质的资产及负债的利率风险衡量中去,这可以提高我国商业银行的风险管理水平。     

Geometric programming for optimal allocation of integrated samples in quality control

We apply geometric programming, developed by Duffin, Peterson Zener (1967), to the optimal allocation of stratified samples. As an introduction, we show how geometric programming is used to allocate samples according to Neyman (1934), using the data of Cornell (1947) and following the exposition of Cochran (1953).

Then we use geometric programming to allocate an integrated sample introduced by Schwartz (1978) for more efficient sampling of three U. S. Federal welfare quality control systems, Aid to Families with Dependent Children, Food Stamps and Medicaid.

We develop methods for setting up the allocation problem, interpreting it as a geometric programming primal problem, transforming it to the corresponding dual problem, solving that, and finding the sample sizes required in the allocation problem. We show that the integrated sample saves sampling costs.     

On the choice of optimality criteria in comparing statistical designs

We formulate in a reasonable sense a class of optimality functionals for comparing feasible statistical designs available in a given setup. It is desired that the optimality functionals reflect symmetric measures of the lack of information contained in the designs being compared. In view of this, Kiefer's (1975) universal optimality criterion is seen to rest on stringent conditions, some of which can be relaxed while preserving optimality (in an extended sense) of the so-called balanced designs.     

关于Ekeland变分原理的一点注记

利用局部凸空间中的Ekeland变分原理,给出了局部凸间中的Takahashi定理,即在一个局部凸拓扑空间中,下半连续且下有界函数如果满足Takahashi条件,则这样的函数下确解可达到.