聚合信用风险模型在我国商业银行应用的方法论探讨

根据《巴塞尔新资本协议》的要求并结合我国的现实情况,本文对聚合信用风险模型在商业银行的应用进行了系统的研究,旨在提供一种计量贷款组合非预期损失的有效方法。本文指出了国外聚合信用风险模型频带划分方法的缺陷,对频带的划分做了创新性的设计,提出了具有可操作性的确定违约概率和违约损失率等参数的方法。同时采用某国有控股商业银行一地级市分行公司贷款数据对文中提出的计量非预期损失方法的科学性进行了论证,指出这一方法应用于我国商业银行可提高经济资本管理的效率。     

我国商业银行信用风险管理问题研究

商业银行的信用风险直接关系到整个银行业的运营安全,关系到整个宏观经济的金融稳定与安全。在我国,商业银行依然面临着巨大的信用风险。对商业银行信用风险管理的研究,有助于提升商业银行信用风险管理水平,降低其风险成本,加强商业银行对未知风险的应对能力。文章在分析我国商业银行信用风险管理问题的基础上,对商业银行信用风险管理提出了相应的解决措施。     

商业银行信用风险度量模型简介及思考

信用风险是现阶段商业银行面临的主要风险,本文在对商业银行信用风险度量代表性模型介绍、比较和分析的基础上,分析了我国商业银行信用风险管理的特点,并提出了加强我国商业银行信用风险度量研究的思考。     

我国商业银行信用风险管理

风险管理是商业银行经营管理的核心问题,而信用风险是商业银行最主要的风险之一。我国商业银行长期处于高风险运行状态,因此,进行信用风险管理研究,提高我国商业银行信用风险管理水平,是我国商业银行要解决的重要课题。本文分析了我国商业银行信用风险管理的必要性,并从我国商业银行的发展现状出发,对我国商业银行信用风险管理进行了系统的探索和研究,同时提出了改善我国商业银行信用风险管理的对策。     

商业银行信用风险管理研究

随着商业银行在日常经营中出现的信用风险不断增多,信用风险管理已经成为商业银行风险管理工作中的重中之重。本文分析了信用风险产生的原因及信用风险管理存在的问题,最终提出完善我国商业银行信用风险管理的对策。     

信用平稳下商业银行信用风险测度模型及应用——基于模糊综合评判法

科学高效的商业银行信用风险测度模型,是实现商业银行信用风险监测目标的重要保障。商业银行信用风险主要来源于贷款企业层面,贷款企业信用质量状况将对应着商业银行信用风险水平。对此,从贷款企业的财务与非财务两个层面设计信用风险的测度指标体系,运用模糊综合评判法构建信用平稳下商业银行信用风险测度模型,并给出信用风险测度模型的应用实例。研究发现,在信用平稳下,依赖于专家评判及打分方式,使得模糊综合评判法对于解决商业银行信用风险测度问题具有很好的操作便利性;也可为我国商业银行体系构建科学高效的信用风险监测机制提供重要的理论指导与决策参考。     

银行信用风险与金融经济周期管理研究

商业银行面临的主要风险就是信用风险,银行的健康发展有赖于信用风险管理关系,目前我国银行信用风险管理体制具有很大缺陷,尤其表现在商业银行。本文通过对商业银行信用风险管理中的问题进行研究,为提高商业银行的抗信用风险能力提供具体建议。     

商业银行信用风险研究综述

本文在理清商业银行信用风险的定义和产生原因的基础上,针对商业银行信用风险进行了研究综述,结合巴塞尔协议系统地归纳了信用风险在不同阶段的评价方法和相关指标,为我国加强商业银行信用风险管控提供依据.     

我国商业银行信用风险的化解之道

一、商业银行信用风险的概念商业银行的信用风险是指借款人(或交易对手)不能按照合约履行其义务的潜在可能性。信用风险可分为以下5类:(一)工商贷款信用风险。工商贷款信用风险是商业银行面临的最主要的信用风险。商业银行在接到贷款申请时,通常根据“5C”法对申请人的还款能力     

商业银行信用管理功能缺位的成因与补救

狭义的商业银行信用管理包括自身信用风险、贷款信用风险和投资信用风险的管理;广义上的商业银行信用管理可以认为是对商业银行面对的所有风险的综合管理,而商业银行面临的更主要是授信业务中的信用风险.     

A mathematical model for multi-name credit based on community flocking

We present a new mathematical model for multi-name credit that employs stochastic flocking. Flocking mechanisms have been used in a variety of models of biological, sociological and physical aggregation phenomena. As a direct application of a flocking mechanism, we introduce a credit risk model based on community flocking for a credit worthiness index. Correlations between different credit worthiness indices are explained in terms of communication rates and coupling strengths from the flocking system. Based on the flocking model, we compute credit curves for individual names and default time distributions. We also apply the proposed model to the pricing of credit derivatives such as credit default swaps and collateralized debt obligations.     

Interaction of market and credit risk

Experience during the financial crisis illustrates that the integrated measurement and management of different forms of risk remains a challenge for industry practitioners, researchers and financial supervisors alike. In the context of related literature, this article summarizes new research on the interaction of market and credit risk and implications for risk management that is presented in this special issue. The research covered highlights in particular the errors that can occur in the aggregation of the two types of risk and the strong relationships between them that suggest caution in the use of pragmatic distinctions between them. The article also touches on some research-based lessons for supervisory policies and suggests some directions for future research.     

Financial statements based bank risk aggregation

One of the major challenges involved in risk aggregation is the lack of risk data. Recently, researchers have found that mapping financial statements into risk types is a satisfactory way to resolve the problem of data shortage and inconsistency. Nevertheless, ignoring off-balance sheet (OBS) items has so far been regarded as the usual practice in risk aggregation, which may lead to deviations in conclusions. Hence, we improve the financial statements based risk aggregation framework by mapping OBS items into risk types. Based on 487 quarterly financial statements from all 16 listed Chinese commercial banks over the period 2007–2014, we empirically study whether the overall impact of OBS activities and the individual impact of each of the OBS risk types on total risk depend on bank size. Moreover, this research divides the sample into two subsets, during and after the subprime crisis, to find out how the subprime crisis affects risks of Chinese banks. Our empirical results show that although OBS credit risk is positively linked to total risk while OBS operational risk is negatively linked to total risk for both large and small banks, the overall impact of OBS activities on total risk depends on bank size. The overall OBS activities are positively related to the large bank’s total risk while they are negatively related to the small bank’s total risk. Besides, we also found that it is the increase of liquidity risk and market risk that leads to the larger total risk of Chinese banks during the subprime crisis.     

信用衍生品在我国商业银行信用风险管理中的应用

我国商业银行针对其面临最重要的风险之一的信用风险采取的信用风险管理方式长期以传统模式为主,这种方式较为被动,缺少积极性及动态有效性。该种方式的缺陷在经济全球化的形势下显得更为严峻,而信用衍生品作为能够有效转移信用风险的创新产品,很有须要将其引进到信用风险管理中。在学习与借鉴前人关于信用衍生品在银行信用风险管理应用的经验上,运用了实证分析方法,对银行信用资产质量与信用衍生品交易量的关系作出了研究,得出了信用衍生品在一定程度上对于降低或转移商业银行信用风险产生了作用,进而保证了信用资产质量的结论,结合了信用衍生品在我国实际的发展现状与条件,提出了该产品在我国商业银行信用风险管理中运用的建议。     

金融信用发展演变研究

由信用风险引发的美国金融危机引起了我们对金融信用的反思。随着金融信用发展,金融信用的内涵和外延在不断变化。本文研究了金融信用的演进历程,根据不同发展时期的特征,将金融信用的发展划分为五个阶段:道德化、法制化、商业化、证券化及风险的市场化阶段。每一发展阶段,金融信用的作用和蕴含的风险是不同的,而目前的金融信用蕴含的信用风险,成为金融危机的重要诱因。     

Basel II: Correlation Related Issues

Basel II aims to aggressively improve on Basel I, and is projected to capitalize on the technological advancements that have permeated the financial industry since Basel I. This paper examines the correlation issues that arise, and provides recommendations on implementation as we move forward. We provide the following results: (1) We demonstrate that fixing asset value correlations by regulators without a specification of business unit granularity and aggregation impacts franchise risk. (2) Loss distributions for credit risk are more sensitive to correlation assumptions that those for market risk; arbitrary, inaccurate correlation specifications can cause large errors in capital requirements. (3) Current regulations do not recognize that credit losses depend on four distinct correlations, not just one. (4) Recovery rates may be determined uniformly across banks. (5) Tail risk comes from LGD correlations and non-Gaussian risks. (6) The 1-year VaR horizon causes distortions especially when regimes and pro-cyclicality are involved. (7) We recommend a quantitative measure for implementing market discipline, the third pillar of the Basel II accord. Therefore, this paper highlights many issues that may be addressed using the tools banks already employ for internal risk management.     

Credit ratings and the cross-section of stock returns

Low credit risk firms realize higher returns than high credit risk firms. This is puzzling because investors seem to pay a premium for bearing credit risk. The credit risk effect manifests itself due to the poor performance of low-rated stocks (which account for 4.2% of total market capitalization) during periods of financial distress. Around rating downgrades, low-rated firms experience considerable negative returns amid strong institutional selling, whereas returns do not differ across credit risk groups in stable or improving credit conditions. The evidence for the credit risk effect points towards mispricing generated by retail investors and sustained by illiquidity and short sell constraints.     

人民币信用风险缓释工具市场应用分析与展望

2010年11月,银行间市场推出人民币信用风险缓释工具,为丰富市场信用风险管理工具、完善市场信用风险分担机制开创新途径。文章基于信用衍生品市场的国际经验,从信用风险缓释工具与经济周期,信用风险缓释工具与信用债券、利率掉期套利等角度,探讨了人民币信用风险缓释工具的市场应用策略,并展望了其市场发展前景。     

信用集中风险研究新进展

历史经验显示,信用集中风险是造成银行危机的一个主要原因,因此,在目前我国信贷快速膨胀、信用集中风险显著加剧的背景下,急需加强对我国商业银行信用集中风险的研究.然而,目前国内研究仍停留于定性分析阶段.鉴于此,本文从信用集中风险的监管要求,信用集中风险测量的理论分析和实证研究三方面对国外信用集中风险及经济资本测度模型的研究进行了述评,以期为提高我国商业银行信用集中风险的测量水平,构建与BasPl Ⅱ一致条件下的经济资本测度模型,从而为提高我国商业银行的信用风险管理能力提供一定的参考.