基于行业特性的多元系统风险因子CreditRisk+模型

本文提出了基于行业特性的多元系统风险因子CreditRisk+模型。假设行业风险因子之间相互独立是原CreditRisk+模型存在的不足,随后试图对其进行修正的单因子模型、复合Gamma CreditRisk+模型和两阶段CreditRisk+模型仍存在问题。本文在引入多元系统风险因子的基础上,将行业风险因子的形参数表示为系统风险因子的线性组合与一反映该行业风险因子内在特性的参数之积,对原CreditRisk+模型行业风险因子相关性进行了拓展,使得拓展后的基于行业特性的多元系统风险因子CreditRisk+模型解决了两阶段CreditRisk+模型忽视行业风险因子自身特性这一缺陷,将系统和行业两重风险因子有机地结合起来;新模型能够将一般情形的行业风险因子协方差矩阵纳入该模型框架内,从而克服了复合Gamma CreditRisk+模型要求行业风险因子之间的协方差必须相等的缺陷。本文证明了原CreditRisk+模型、复合Gamma CreditRisk+模型和两阶段CreditRisk+模型都只是新模型的极端情形,这些情形难以将行业风险因子协方差矩阵很好地纳入模型框架内,从而影响贷款组合非预期损失计算的精度。     

风险规避型供应链的收益共享机制研究

探讨了由风险规避型零售商与风险规避型供应商组成的两级供应链协作激励问题.首先研究了Stackelberg主从对策模型下风险规避型零售商与风险规避型供应商的决策行为,并分析了双方的风险规避系数对双方决策行为的影响.然后,研究了垂直一体化模型下风险规避型供应链的决策行为,同样分析了双方风险规避系数对供应链决策行为的影响程度.最后,提出采用收益共享契约机制来协调该供应链.并通过数值实验进一步分析供应商与零售商的风险规避系数对双方的决策行为及收益共享系数的影响程度.     

基于代价敏感决策树的客户价值细分(英文)

由于错误分类代价差异和不同价值客户数量的不平衡分布,基于总体准确率的数据挖掘方法不能体现由于客户价值不同对分类效果带来的影响.为了解决错误分类不平衡的数据分类问题,利用代价敏感学习技术扩展现有决策树模型,将这一方法应用在客户价值细分,建立基于客户价值的错分代价矩阵,以分类代价最小化作为决策树分支的标准,建立分类的期望损失函数作为分类效果的评价标准,采用中国某银行的信用卡客户数据进行实验.实验结果表明,与传统决策树方法相比,代价敏感决策树对客户价值细分问题有更好的分类效果,可以更精确地控制代价敏感性和不同种分类错误的分布,降低总体的错误分类代价,使模型能更准确反映分类的代价,有效识别客户价值     

基于Stackelberg博弈的风险项目投资水平分析

在风险项目以债权-股权相结合的融资工具的假定上,引入融资合约中常用的"激励因子",分别建立风险投资家和企业家的支付函数,从而构建了斯坦克尔伯格(Stackelberg)博弈模型;然后用逆向归纳法分析Stackelberg模型,讨论了作为领导者的企业家的自有资本和"激励因子"对作为跟随者的风险投资家的总投资水平及资本结构的影响;并在此基础上分析了企业家的均衡投资决策,进而给出了企业家为激励风险投资家而需提供自有资本水平的必要条件,从而解决了企业家对风险投资家的激励问题.通过研究发现:风险投资家的总投资水平由债权"激励因子"和其边际投资机会成本决定,而股权投资水平由其绝对风险厌恶因子、主观收益率的参数以及"激励因子"决定.尽管假定风险投资家较企业家风险厌恶,但是后者可以通过激励前者,使前者对于风险项目前景较后者乐观.     

模糊需求信息条件下风险规避型分销商的库存决策研究

着重研究模糊需求信息条件下风险规避型分销商库存决策问题,利用模糊理论的基本运算规则、扩展原理及Markowitz提出的均值一方差模型建立两类模糊需求信息条件下风险规避型分销商库存决策模型风险规避型分销商在可接受的库存成本基础上追求库存成本方差最小的模型;风险规避型分销商在可接受的库存成本方差基础上追求库存成本最小的模型.并以数值分析的方式来分析模型内在涵义.     

设备维护外包中的风险分析

本文首先分析了设备维护外包对企业的重要性,依据“委托—代理”理论,分析了设备维护外包的风险。通过外包的博弈分析,我们得到了影响代理方违规、委托方监督的影响因素,并提出了降低设备维护外包风险的措施。     

HRM成本陷阱预警模型构建

本文针对企业容易忽视的HRM成本问题，从HRM成本角度分析企业引入科学的HRM系统行为，通过引入成本陷阱概念，确定了陷阱因子Φ和Φ′作为临界值和是否引入HRM系统的判别标准，以此构建了HRM成本陷阱预警模型。论文设计了3种具体算例，说明了模型的应用价值。据此，论文最后提出了HRM质量提升的具体对策。     

资产定价与劳动成本占比

根据经典生产函数可知与劳动要素相关的变化应反映到企业价值层面，那么劳动要素对股票市场具有怎样的影响呢？本文以沪深A股为研究对象，基于劳动成本占比探索劳动要素对股票市场定价的影响。通过模型推理和实证分析相结合的方法证明劳动成本占比与企业风险正相关，劳动成本占比具有放大企业风险的杠杆作用。基于风险与收益相补偿的原理，通过回归分析和投资组合分析发现劳动成本占比具有正的股票收益预测能力；采用买多-卖空组合构建劳动成本占比风险因子，通过Fama-MacBeth回归证明劳动成本占比是影响股票收益的风险因子，并且相对Fama-French的五因子不是冗余因子；在三因子模型和五因子模型基础上包含劳动成本占比风险因子的定价模型对股票横截面收益的解释力更好，模型的定价效率更高。本文不仅丰富了股票收益影响因子和劳动成本经济后果领域的文献，而且对投资者投资决策、企业制定薪酬制度、政府颁布劳动保护相关政策和收入分配改革方面具有参考价值。     

基于状态空间模型的宏观经济因素对股市流动性的建模分析

证券市场的流动性是评估一国证券市场是否健康运转的重要指标。关于流动性的各种学术研究也是金融市场微观结构理论中的热点问题。本文主要考察宏观经济因素对时变的股市流动性的影响，选取度量股票流动性的指标以及宏观经济变量，针对行业分类的面板数据提出三个动态因子模型，并引入跨行业的能够捕捉风险聚集现象的潜在因子进行建模，利用状态空间模型与Kalman滤波进行分析和样本外流动性风险预测。我们提出的新颖的带回归效应的高斯面板数据时间序列模型，结合了用主成分的方法从大量宏观经济协变量中提取出来的因子，用来分析和预测股市的流动性风险，具有较强的信息挖掘作用。在对上证A 股的实证研究中，我们发现动态的潜在因子的引入对于防止流动性估计的偏差是需要的。     

因子模型在风险预算分析中的应用

风险预算在国外正赢得学术界、养老基金和资产管理领域等许多方面的广泛关注,并认为是组合管理的一种创新。国内投资者日益认识到投资组合管理与风险控制的重要意义,并近乎成为他们的第一要务。本文利用因子模型,通过风险预算这一投资管理和风险控制技术与方法,讨论投资组合因子风险分解并进行实证分析。     

考虑故障停机的生产控制与维修计划联合决策模型

通过生产控制与维修计划协同决策,降低生产成本。首先描述生产过程,分析各项费用。其次,建立了考虑生产过程失控、故障率和故障停时间的生产过程控制、生产计划优化和维修管理联合优化决策的模型。通过模型求解,联合制定出生产过程检查策略、生产计划（经济生产批量、生产批次）以及维修计划（PM间隔期）,实现单位时间内总费用最低的目标。再次,案例研究,分析生产过程失控、故障率和故障停机时间对于经济生产批量、生产过程检查策略和生产系统维修计划的影响。该模型从理论上解决了生产过程控制、生产计划优化和维修管理联合优化决策难题,对于指导企业制定生产计划和生产系统的检修计划,进而提高产品质量、降低生产成本、确保准时交货都具有指导意义和实用价值。     

Optimal maintenance intervals for a multi-component system

In the manufacturing industry, preventive maintenance (PM) is carried out to minimise the probability of plant unexpected breakdown. Planned PM is preferred as disruption to operation is then minimised. Suggested PM intervals are normally prepared by the original equipment manufacturers (OEMs), however due to the multifaceted relationship between operating context and production requirement for different plants, it is unlikely that these suggested intervals as prescribed by the OEMs are optimal. Reliability, budget and breakdown outages cost are some of the critical factors that will affect the calculation of optimal maintenance intervals. Maintenance managers are required to determine optimal maintenance intervals with the above different requirements set by management. In this paper three models are proposed to calculate optimal maintenance intervals for multi-component system in a factory subjected to minimum required reliability, maximum allowable budget and minimum total cost. Numerical examples are provided to illustrate the application and usefulness of the proposed models.     

Money and Journal of Organizational Behavior Management Interventions: A Review

Practitioners and business leaders can use monetary data to quantify the financial outcomes of interventions in organizational behavior management (OBM). The primary purpose of this review was to investigate the occurrence and classification of monetary data in the OBM literature. Other purposes were to demonstrate ways in which such data contribute to the measurement of value and to provide recommendations for its reporting and publication. Accordingly, a review was conducted of publications in the Journal of Organizational Behavior Management. Cumulative yearly results showed that cost data were reported more often than cost plus benefit data, and cost plus benefit data were reported more often than benefit data alone. More cost than benefit data were reported, most often with social validity, followed by institutionalization, then maintenance measures. However, more cost plus benefit data were reported than either cost or benefit data with a maintenance measure. It is concluded that reporting cost and benefit data would be beneficial to the field of OBM.     

Optimal Allocation of Effort to Software Maintenance: A Queuing Theory Approach

We develop variations of the M|G|1 queue to model the process of software maintenance within organizations and use these models to compute the optimal allocation of resources to software maintenance. User requests are assumed to arrive following a Poisson process and a binomial distribution is used to model duplication of requests. We obtain expressions for expected queue lengths with an exponential server using an N‐policy for an integer N≥1. We also obtain the optimal batching size and mean service rate by minimizing the total cost consisting of the cost of the server, the cost of waiting, and the fixed cost of maintenance, if applicable.     

A cost model for deferred state life test plans with replacement

This paper presents a cost model for the deferred state life test plan, which is one of the lot-by-lot acceptance sampling plans by attributes. In most sampling plans, the decision to accept or reject a submitted lot depends only on the sampling test results of the lot concerned; other information will not be considered. Deferred state life test plan is a sampling plan which uses information about subsequent lots for making decisions to accept or reject the current lot. The objective of this paper is to evaluate the total test cost of using the deferred state life test plan to see whether the use of this life test plan can reduce the total cost of the sampling test. In order to calculate the expected total test cost of the deferred state life test plan, a cost model is developed for the deferred state life test plan with replacement. Also, a cost comparison is made between a deferred state life test plan and a comparable military standard sampling plan which offers the same level of producer's and consumer's protection. The results show that the deferred state life test plan consistently reduces the overall cost of sampling tests over a variety of test conditions.     

Risk-Based Integrity and Inspection Modeling (RBIIM) of Process Components/System

Process plants deal with hazardous (highly flammable and toxic) chemicals at extreme conditions of temperature and pressure. Proper inspection and maintenance of these facilities is paramount for the maintenance of safe and continuous operation. This article proposes a risk-based methodology for integrity and inspection modeling (RBIIM) to ensure safe and fault-free operation of the facility. This methodology uses a gamma distribution to model the material degradation and a Bayesian updating method to improve the distribution based on actual inspection results. The method deals with the two cases of perfect and imperfect inspections. The measurement error resulting from imperfect inspections is modeled as a zero-mean, normally distributed random process. The risk is calculated using the probability of failure and the consequence is assessed in terms of cost as a function of time. The risk function is used to determine an optimal inspection and replacement interval. The calculated inspection and replacement interval is subsequently used in the design of an integrity inspection plan. Two case studies are presented: the maintenance of an autoclave and the maintenance of a pipeline segment. For the autoclave, the interval between two successive inspections is found to be 19 years. For the pipeline, the next inspection is due after 5 years from now. Measurements taken at inspections are used in estimating a new degradation rate that can then be used to update the failure distribution function.     

引入信息成本的信息结构与股权融资成本

本文放松了Easley和O’Hara信息成本为0的假设,在他们的信息结构模型的理论框架下,构建了一个引入信息成本因素的信息结构模型。从信息结构的四个方面：信息成本、信息风险、信息披露的质量和先验信息质量研究了信息结构与股权融资成本之间的关系,得出了四个推论,从而拓展了信息结构模型。在进一步的实证研究中,选取市场微观结构理论中的逆向选择成本、知情交易概率-PIN分别作为信息成本和信息风险的衡量指标,研究发现：信息成本与股权融资成本之间呈倒‘U’型曲线关系;信息风险越高的股票股权融资成本越高;信息披露质量越高的公司,股权融资成本越低;先验信息质量越高,股权融资成本越低;从而对推论进行了有效验证。本文与Easley和O’Hara最大不同在于引入了信息成本因素,并且用实证方法对推论进行了验证,具有一定的开创性。     

考虑质量相关性需求与完全预防性维修的EPQ决策

在经典EPQ模型基础上，考虑质量相关性需求和周期性完全预防性维修策略，以单位时间利润最大化为目标，构建经济生产批量的决策模型。在企业单位时间利润模型的构建中，结合质量相关性需求以及设备退化这一实际问题，进行动态预防性维修成本、恢复成本、次品修复成本以及产品需求率的构建。考虑目标函数的复杂性，本文采用遗传算法对模型进行数值求解，并通过与不考虑质量相关性需求的EPQ决策的比较分析，验证其合理性。     

不对称信息下创新产品研发外包的甄别契约设计

在创新产品研发过程中,许多企业会将部分研发模块外包,而接包方能力水平和成本信息的不对称,会给发包方带来收益风险。对此采用委托代理理论中的信息甄别模型,将研发的接包方分为高成本系数和低成本系数两类,由创新企业设计包含固定支付和收益共享系数两个参数的外包甄别契约,来推断其真实能力。通过考虑创新研发成功的概率因素和技术成果转化后的市场收益分成,以激励接包方做出最优的努力。研究结果表明：高成本系数接包方的收益共享系数将被向下扭曲,低成本系数接包方既获得了保留效用,还会得到额外的信息租金;契约中两类参数的取值受到不同类型接包方所占比例的影响,随着市场中高成本系数企业数量的增加,发包方的期望收益降低。