信用风险计量技术及其应用于我国商业银行的思考

信用风险是我国商业银行目前所面临的主要风险。文章首先定义了信用风险计量的基本概念 ,接着从分析信用风险计量的原理模型入手 ,指出了目前国际上流行的信用风险计量模型并不适用于我国 ,最后对我国商业银行开发信用风险计量模型提出了几点思考。     

现代信用风险量化模型及对我国商业银行信用风险管理的借鉴

文章通过分析目前国际上正式对外公布、有影响力的主要信用风险量化模型,结合我国信用风险管理的现状,揭示了现代信用风险量化模型对我国商业银行信用风险管理具有的借鉴意义。     

基于BP算法的神经网络信用风险度量实证研究

理论与实际相结合,应用神经网络技术,构建了一个基于BP神经网络技术的信用风险评价模型,对我国传统的信用风险分析方法进行改进,克服了以往我国信用风险度量中存在主观随意性的特点,为我国信用风险度量模型的建设拓宽了思路,丰富了我国信用风险体系建设中的度量方法。     

我国上市公司信用风险度量——基于KMV模型

美国次贷危机的爆发,加深了人们对信用风险度量重要性的认识,KMV模型是当今世界最流行的信用风险度量模型之一。文章运用KMV模型,比较各组样本违约距离的差异性,得出了如下的结论:总体上看,ST股票的信用风险要大于非ST股票,*ST股票的信用风险要大于ST股票,而对于不同主体信用等级的股票,随着信用等级的逐步降低,信用风险也随之加大。从而证明了KMV模型在我国具有良好的适用性。     

现代信用风险度量模型综述

新的巴塞尔协议允许十国集团的国家银行可以采用内部模型来度量信用风险。文章介绍了目前世界各国金融机构普遍采用的四种信用风险度量模型,对其进行了比较分析,并对各种信用风险模型在中国的应用提出了自己的建议。     

神经网络模型在不良资产证券化资产池信用风险分析中的应用

不良资产证券化资产池信用风险的研究在我国尚属空白。文章立足我国不良资产信用数据严重不足的现状,尝试使用改进的BP神经网络模型测算单笔不良资产的信用风险,并通过整合信用风险附加模型,量化资产池的信用风险。以某不良资产证券化案例为样本进行的实证分析结果表明,改进的BP神经网络模型为测算不良资产证券化资产池信用风险提供了一条可行之路。     

上市公司信用评级与股票收益率关系实证分析

本文以三因素模型为基础,将信用风险纳入股票定价模型并构建了四因子定价模型,对国内部分上市公司的信用评级与股票收益率之间的关系进行了分析。研究发现,在考察期的部分时间区间,信用风险低的上市公司在未来得到的收益反而比信用风险高的上市公司高,股票收益率与信用风险呈反向变动。     

现代信用风险度量模型比较分析

金融危机的爆发以及<巴塞尔新资本协议>的正式实施,为银行业进行信用风险管理提出新的挑战.本文对国际上信用风险管理实践中应用最为广泛的现代信用风险度量模型进行了分析比较,提出我国商业银行应用信用风险模型中的问题,并给出相关建议.     

国外主要信用风险度量方法评介

信用风险是金融风险中最为重要的风险之一,随着金融业的迅猛发展和金融创新的进程不断加快,金融领域面临着更大的挑战,因此,对信用风险的评价与管理越来越重要,文章回顾了信用风险度量方法的历史沿革,并着重介绍几种国际上主要的信用风险度量方法,如Z评分模型、莫顿模型、KMV的信用监测模型、J·P·摩根的信用度量制模型、麦肯锡的信用组合观点、死亡率模型和信用风险附加法等,以期使读者对其有更加清晰和全面的认识。     

我国上市公司信用风险预警研究

本文以我国上市公司作为研究样本,构建基于组合预测模型的我国商业银行信用风险管理预警系统。在结合目前国内外各商业银行信用风险预警指标体系的基础上,筛选构建较为合理并适合我国国情的信用风险预警指标体系;进而选择传统数理统计模型Logistic回归模型和人工智能模型RBF神经网络模型建立组合预测预警模型,以求能够组合不同单一模型的优点,解决信用风险预警模型的准确性和稳定性兼顾的问题,仿真结果表明:组合预测模型解决了单一模型应用中精确性和第二类问题处理能力不能同时兼得的问题,达到了预期的效果。     

巴塞尔新资本协议与信用风险模型的监管审查研究

巴塞尔新资本协议鼓励银行采用内部评级法评估信用风险以提取资本准备,但内部评级法必须满足监管审查的要求。基于新资本协议的这一要求,从监管机构的角度出发,建立信用风险模型监管审查框架,讨论了银行建立内部信用风险模型时,为确保其合理性需要满足的条件与要求,从而为我国的监管机构提供参考借鉴。     

Bank Credit Risk Management and Migration Analysis; Conditioning Transition Matrices on the Stage of the Business Cycle

Credit risk has been one of the most active areas of recent financial research. It is driven by advances in portfolio risk measurement and management techniques, growth in credit derivatives trading, the Basel II implementation, and regulatory concerns stemming from the commercial credit crunch that initially took place in 2001 and 2002 in the USA. Within this broader literature, a growing body of research analyzes the meaning, role, and influence of credit ratings that quantify credit risk. This paper examines the two-way links between credit risk measurement and the macroeconomic conditions, interpreted through phases of business cycles. We propose a methodology applied on bank internal rating data, which estimates ratings migration probabilities while integrating the state of the economy. We first discuss the issue of whether credit risk is low or high in different economic scenarios. In order to evaluate this prospect, we examine each year in four quarters that represent different scenarios throughout the year. We then review how macroeconomic considerations are incorporated into credit risk models and the risk measurement approach that underlies Basel II and Basel III.     

中国信用风险预警模型及实证研究——基于企业关联关系和信贷行为的视角

文章从分析当前次贷危机的根源出发,在综述现有信用风险计量预警模型的基础上,针对其在我国的适应及局限性问题,根据风险相关性原理和多米诺骨牌理论,提出从企业关联关系(Correlation)和信贷行为(Behavior)角度建立一种全新的信用风险预警模型(简称C&B模型),并应用国内某商业银行的数据进行实证研究.结果表明,在我国商业银行中应用C&B模型,思路可行,数据易得,预警有效.     

信用风险模型的新发展与商业银行风险管理

信用风险是商业银行面临的主要风险之一,其直接影响商业银行持续经营的能力。《新巴塞尔资本协议》鼓励商业银行在进行信用风险管理时更多地使用内部模型,这意味着建立有效的信用风险模型应成为商业银行的重要任务。中国银行业要健康、稳定地发展,需要借鉴西方信用风险模型,对风险进行科学管理。     

Credit risk – Return puzzle: Evidence from India

Although asset pricing theories predict a positive relation between risk and returns, empirical findings on credit risk-return relationship are mixed. And, observed negative relation between the two in this regard is referred to as credit risk-return puzzle. Using credit rating as a measure of credit risk, we have investigated into the existence of this puzzle in India during July 2011 to March 2019. We have used information for the companies listed on the National Stock Exchange for this purpose. Our results validate the presence of this puzzle in the Indian stock market. Moreover, credit risk is observed to be a systematic risk, which has not been captured in the traditional asset pricing models. We have also observed partial evidence favoring both behavioural and rational pricing explanations—the two widely acknowledged explanations in the literature behind this puzzle. On our further query in this connection, we have not seen any significant change in the puzzle due to the recent enactment of the Insolvency and Bankruptcy Code.     

信用等级转移分析

在我国现阶段 ,商业银行开展的业务主要是贷款业务。信用等级是识别、度量和控制贷款的信用风险的重要参数。本文通过对度量信用等级变化的转移矩阵的介绍 ,结合贷款五级分类方法 ,说明转移矩阵在商业银行贷款风险管理的作用 ,并指出我国现阶段建立转移矩阵贷款数据库对管理贷款风险的重要性和迫切性。     

Parametric versus nonparametric methods in risk scoring: an application to microcredit

The importance of credit access to improve economic opportunities in developing markets is well established in the literature. However, there exists a strong need to mitigate adverse selection problems in microlending. A risk scoring model that more accurately predicts the likelihood of repayment of potential borrowers can help address this market imperfection and to benefit both lenders and borrowers. This paper compares the performance of nonparametric versus semiparametric and traditional parametric risk scoring models based on default probabilities. We show the advantages of relying on less structured, data-driven methods for risk scoring using both simulated data and data from credit loans granted to small and microenterprises in rural Peru. The estimation results indicate that nonparametric methods lead to a better evaluation of credit worthiness and can help prevent including potential “bad” borrowers and excluding “good” borrowers from sensitive microcredit markets.     

A Structural Analysis of Credit Risk With Risky Collateral: A Methodology for Haircut Determination

Although many credit risk pricing models exist in the academic literature, very little attention has been paid to the impact of risky collateral on credit risk. It is nonetheless well known that practitioners often mitigate credit risk with collateral, using so–called haircuts for collateral level determination. The presence of collateral has a complex effect that can not be analysed simply with existing models. We analyse the value of credit risk when there is collateral in a range of different situations, including dual–default in a simple setting, stochastic collateral, stochastic bond collateral with stochastic interest rates, continuous and discrete marking–to–market and margin calls. The models confirm many practical intuitions, such as the impact on the haircut level required of the risks of the collateral asset and of the underlying asset to the forward as well as the impact of their correlation. Moreover, the model supports the intuition that the frequency of marking–to–market and collateral are substitutes. The models also stress the possibly unexpected magnitude of these factors. More importantly, they give actual solutions to determining the value of the credit risk depending on the haircut chosen and the frequency of marking–to–markets, results not presented before in the literature. The models are also a good basis to understand the portfolio effect of collateral management. Finally, they illustrate how differences in prices may arise from pure differences of credit risk management, as illustrated here in the case of futures and forwards.
(J.E.L.: G13).     

基于博弈理论的企业商业信用风险研究

信用风险已成为企业经营管理中重要的一部分,直接影响企业持续经营的能力。如何防范信用风险的发生已成为企业极为迫切的需求。从交易的角度对信用风险的产生进行表述,然后进一步采用博弈论模型对其原因进行剖析,从而得出信息不对称和失信惩罚机制不完善是信用风险产生的主要原因,并针对其原因提出对策。通过研究,以期对企业在信用风险的管理和防范上起到一定的指导作用。     

VMI模式下仓单质信的企业资信评级体系建立探讨

仓单质信能够有效控制VMI运作中的信用风险,但随着实践深入,仓单质信的风险逐渐显露。基于客户资信风险、仓单风险、银行风险都与信用有着密切的联系,提出建立仓单质信的供应链企业资信评级体系。研究表明:通过构造指标要素,分析评级指数设定、信用等级平均累计违约率统计以及评级结果的准确性,可以实现信贷决策的科学化、精细化发展。