Evaluating the Evaluators: Should Investors Trust Corporate Governance Metrics Ratings?

Companies are under increasing pressure to have their corporate governance rated by an independent corporate governance metrics firm, such as Institutional Shareholder Services (ISS) or Governance Metrics International (GMI). These rating firms claim to be able to determine how effective and responsive a company’s board is. Institutional investors have begun using these board governance ratings when deciding which firms to include in their stock portfolios. This paper considers whether investors, many of whom claim to be socially responsible, should be relying upon board governance metrics. We find that these metrics are not good indicators of either the quality of a firm’s earnings or of its ethics.     

Coordinating contracts for a financially constrained supply chain

We consider a financially constrained supply chain in which a supplier (leader) sells products to a retailer (follower) who has no access to bank financing due to her low credit rating. However, the supplier can borrow from a bank and offer trade credit to the retailer to alleviate her financial constraint. Failure to pay off a bank loan or trade credit incurs a variable default cost. We analyze the centralized version of the supply chain to obtain new coordination requirements. We then examine whether revenue-sharing, buyback, and all-unit quantity discount contracts can coordinate our supply chain. We show that the all-unit quantity discount contract fails to coordinate. However, the revenue-sharing and buyback contracts can coordinate the supply chain, but only when the supply chain has a sufficient total working capital. Moreover, they cannot allocate profit flexibly unless the supplier has a large enough working capital. Finally, we design a generalized revenue-sharing contract that coordinates the supply chain with flexible profit allocation, and also show by numerical examples its superiority over the revenue-sharing and buyback contracts.     

Estimation of Deprivation Level Functions using a Numerical Rating Scale

Evaluating and quantifying human suffering in humanitarian operations offers an innovative and potentially powerful way to assess the performance of humanitarian logistics (HL) and help build optimization models. Previous studies have suggested deprivation cost as a metric and have estimated deprivation cost functions for water using willingness‐to‐pay. Our study proposes deprivation levels, defined as the degree of human suffering caused by lack of access to a good or service, and estimates deprivation level functions using a numerical rating scale. Analyzing data collected from respondents with and without disaster experience, we find that individuals in the latter category estimate deprivation differently from the beneficiaries of disaster relief. Our study demonstrates that deprivation levels can be expressed as logistic growth functions with a typical S‐shape, and that these can be integrated into HL optimization models to better account for human suffering.     

遗传算法优化神经网络及信用评价研究

研究关于公司神经网络信用评估问题的现状,提出遗传算法辅助网络训练策略(优化后的网络称为进化网络),克服传统网络建模中产生的局部极小缺陷。建立了适合于我国商业企业的信用评分指标体系;然后依据该指标体系建立了基于进化神经网络的信用评估模型;最后,利用样本公司实际指标数据对该模型的评分效果进行了比较研究。     

上市公司信用风险度量模型的实证比较研究

本文首次运用Merton模型和Leland-Toft模型对我国上市公司的信用风险进行了比较实证研究。研究结果表明,Merton模型对上市公司信用风险的预期违约率的计算明显太低。但是,违约距离的计算在一定程度上可以反映出不同公司信用风险存在的差异。而使用Leland-Toft模型计算信用风险的预期违约率较Merton模型有更高的敏感性、有效性。依据大公国际资信评级体系评级的结果,将A股50指数上市公司的信用评级等级,对比Leland-Toft模型计算的预期违约率,不同等级的上市公司,其预期违约率有明显的不同,说明其模型的预测是有效的。并且,也反映出近期预期违约率低而远期则较高的规律性。但是,计算的预期违约率还是偏低,说明Leland-Toft模型在用于目前的上市公司信用风险分析时,尚需调整有关的参数。     

供应链中信用交易的演化博弈分析

本文运用演化博弈理论研究了供应链中信用交易的演化过程,建立了供应商和零售商信用交易的演化博弈模型。分析了两类个体在守信与失信两种策略下的行为特征,根据复制者动态方程得到了两者的行为演化规律和政府失信惩罚机制下的行为演化和演化稳定策略,给出了从根本上消灭失信动机的惩罚区间,分析了政府失信惩罚机制的有效性,探寻国内信用制度建设的发展路径。最后,通过数值分析证明了结论的正确性。     

风险相关性下的信用风险、市场风险和操作风险集成度量

商业银行各种风险之间相关性的存在,对其整体风险的度量产生重要影响。本文针对商业银行的信用风险、市场风险和操作风险这三类主要风险,在考虑相关性基础上给出了风险集成过程,通过copula函数和蒙特卡洛模拟方法计算了商业银行的整体风险,同时研究了风险分散化效应和在不同copula函数下整体风险的变化情况。最后以主流文献中的数据做了实证分析,结果显示本文提出方法能够很好的描述风险损失之间的相关性,同时在能够抵御相同风险的情况下考虑相关性下的在险值与简单相加得到的在险值相比要小,这能为银行业提高资金利用率提供了一定的理论和方法依据。     

Optimizing the Collections Process in Consumer Credit

This paper builds a dynamic programming model to optimize the collections process in consumer credit. It determines which collections actions should be undertaken and how long they should be performed, including theoretical results about the form of the optimal policy under certain conditions. Finally, a case study is described based on data from the collections department of a European bank.     

企业信用内生网络模型及其演化研究

本文考虑上游企业和下游企业两个部门,通过构建企业内生网络模型研究企业间信用关联内在形成机制及其演化特征。通过对内生网络模型仿真研究,结果表明本文构建的模型重现了现实企业系统存在的一些特征：企业信用网络度分布服从幂律分布,该网络具有无标度特征;较长的合并周期则能更好地反映企业间信用关系,且随着合并周期变大,网络密度也显著增大;企业资产规模分布具有幂律尾部特征,企业资产增长率随时间演化逐渐呈收敛状,且其概率分布近似于正态分布。     

中国企业部门信用风险溢价期限结构与宏观经济因子

近年来，中国企业部门债务风险不断暴露，其是否会引发系统性信用危机正成为焦点。本文着眼于中国企业部门信用风险累积与暴露背后的宏观经济现实，在简约模型中引入结构向量自回归模型（SVAR），将经济冲击区分为总供给冲击、总需求冲击和货币政策冲击，以此研究各宏观经济因子对中国企业部门信用风险溢价期限结构的影响特征，从而揭示中国企业部门信用风险定价的宏观经济机理。本文发现，正向的总供给冲击和货币政策冲击有助于降低中国企业部门信用风险溢价，但正向的总需求冲击则会推高中国企业部门信用风险溢价，自2011年以来持续处于高位水平的信用风险溢价的主要根源正是4万亿经济刺激计划所带来的扩张性总需求，因此欲从根本上降低中国企业部门信用风险水平，应紧缩社会总需求，并通过制度改革和结构调整，改善社会总供给。