基于委托代理理论的信用违约互换最优契约模型分析

本文阐述了信用风险互换及其委托代理关系．分析了信息不对称下引起信用违约互换道德风险问题,运用委托代理理论建立了相应的信用违约互换契约分析模型．对道德风险下的最优信用违约契约性质进行研究．并提出了解决道德风险、优化信用违约互换的激励机制．确保信用违约互换在我国的健康发展。     

浅谈银行信用违约互换的信用风险管理政策披露

信用衍生产品拥有高收益性和难以避免的高风险性。中国的信用衍生产品交易处在起步阶段,银行关于信用衍生产品的信用风险信息披露还存在许多问题,以信用违约互换的信用风险管理政策披露为对象,借鉴美国银行相关信息披露的经验,探讨完善中国信用违约互换的信用风险管理政策披露的建议。     

信用衍生产品与我国商业银行信用风险管理

一、信用风险及信用衍生品的概念信用风险是指交易一方因为另一方违约或不能全部履行合约而遭受损失的可能性。信用风险是我国商业银行面临的最主要风险之一,传统的信用风险管理主要是其缺乏有效的风险对冲管理手段,它主要包括投资分散化、防止授信集中化、对借款人的信用审查以及动态监控、资产证券化和贷款出售等。虽然这些手段随着发展有的已日趋完善但仍存在局限性。1992年,在巴黎举行的ISDA(InternationaI Swaps andDerivatives Association,国际互换与衍生品协会)年会上首次正式提出了一种可以用做分散、转移、对冲信用风险的创新…     

基于供应商管理库存信用风险的供应链违约风险控制

受宏观经济因素的影响,市场风险和违约风险是密切相关的。而VMI作为一种在供应链相邻两级,其成功运作最重要的一个关键点,便是建立信用风险度量,以销售商违约为例,利用信用违约互换模型规避供应链违约风险,供应商和销售商更易达成交易。     

论信用衍生工具及其存在的风险

信用衍生产品是用来交易信用风险的金融工具,在使用信用衍生工具交易信用风险的过程中,信用风险被从标的金融工具中剥离,使信用风险和该金融工具的其他特征分离开来。信用衍生工具作为一种金融合约,提供与信用有关的损失保险,这类合约可以在交易所或场外市场买卖,对于债券发行者、投资者和银行来说,信用衍生工具是贷款出售及资产证券化之后的新的管理信用风险的工具,利用这些衍生工具将贷款及其他资产的信贷风险转移。本文重点分析在使用信用衍生工具过程中的几类风险以其在我国发展的启示。     

信用衍生工具存在的风险及其对我国经济发展的影响

信用衍生产品是用来交易信用风险的金融工具，在使用信用衍生工具交易信用风险的过程中，信用风险被从标的金融工具中剥离，使信用风险和该金融工具的其他特征分离开来。信用衍生工具作为一种金融合约，提供与信用有关的损失保险，这类合约可以在交易所或场外市场买卖，对于债券发行者、投资者和银行来说，信用衍生工具是贷款出售及资产证券化之后的新的管理信用风险的工具，利用这些衍生工具将贷款及其他资产的信贷风险转移。本文重点分析在使用信用衍生工具过程中的几类风险以其在我国发展的启示。     

关于控制银行信用风险的思考

文章分析了银行信用风险与信贷风险之间的关系,认为信贷风险是商业银行信用风险管理的主要对象,将信贷风险分为企业的经营风险和企业赖帐违约的道德风险,并对银行的信贷风险进行了博弈分析。分析说明,银行业面临的信用风险中的信贷风险可以通过控制企业的道德风险、减少经营风险,达到降低信用风险的目的,主要的措施是制定合理的利率水平,加强银行和企业信息交流,消除信息不对称,加大违约惩罚力度。     

信用衍生工具及其在我国的发展

一、信用风险与信用悖论问题信 用风险指的是债权人未能实现债务人还款的预期或未能充分实现的可能性 ,包括因对手违约而导致损失的可能性 ,也包括因交易对手的信用评级或履约能力的变化产生其债务的市场价值变动而导致损失的可能性。信用风险被认为是银行最大的风险 ,以前银行通过提高自身资本金要求、银团贷款、交易对方信用评级、贷款出售等方法规避化解信用风险 ,其缺乏一套通用的信用管理系统 ,对指标的度量无法量化 ,降低了风险管理的有效性。这种风险管理方法带来的后果非常严重 ,银行损失巨大 ,无论是发达国家还是发展中国家 ,银行亏损甚至倒闭 ,银行资本损失更是屡见不鲜。因此 ,银行必须在信用管理上有更好的方法来抵御日益扩大的信用风险。银行对借款人进行的贷款行为主要是在风险与收益之间进行权衡。但是 ,在实践中 ,银行由于对客户信用状况的了解主要来源于长期的业务关系 ,因此 ,银行倾向于将贷款投向并集中于有限的老客户 ,这势必导致银行所面临的信用风险过分集中于某一特定的客户群体 ,一旦违约事件发生 ,银行就可能损失巨大。这一可能的巨大损失是由信用风险特点决定的 (如图 1)。信用风险的概率分布并非服从正态分布。一方面 ,由于银行...     

信用风险管理方式的改革与创新——运用市场方式度量和管理信用风险

党 的十六大报告指出 :“加强金融监管 ,防范和化解金融风险 ,使金融更好地为经济社会发展服务。”可见 ,金融风险的管理已经越来越受到国家的重视。金融风险主要包括汇率风险、利率风险、市场风险、信用风险等。本文拟就构成金融风险之一的信用风险管理展开论述。一、信用风险的概念与产生的原因根据 2 0 0 0年 9月巴塞尔委员会颁布的《信用风险管理原则》的定义 ,信用风险简单地说就是银行的借款人或交易对象不能按事先达成的协议履行其义务的潜在的可能性。其产生的原因从投资组合的角度来看 ,投资者的投资组合不仅会因为交易对手 (包括贷款借用人、债券发行者和其他交易合约的交易对手 )的直接违约发生损失 ,而且 ,交易对手履约可能性的变化也会给组合带来损失。也就是说 ,银行作为投资者 ,其贷款资产的价值与借款人的还款能力和还款可能性建立了联系。一旦一些影响交易对手信用状况的事件发生 ,如政策变动、行政干预、市场变化、经营改变等导致借款人信用等级降低、赢利能力下降 ,则会引起银行资产价值的变化 ,产生风险。银行的信用风险管理贯穿在整个资产组合及单一授信或交易之中并与汇率风险、利率风险、市场风险等一起构成了银行风险管理的重要内容。...     

基于KMV模型的我国上市银行信用风险度量研究

信用风险是商业银行最主要的风险之一,信用风险的产生会增加交易成本、降低投资者投资意愿,从而影响经济的发展。公司通常会采用信用风险度量方法及时预测信用违约情况,以提高公司风控能力,保证信用交易的正常运行。而KMV模型具有良好的风险预测能力,可以为银行违约风险监管提供参考。故选取我国14家上市银行为研究对象,基于2020年样本银行的财务数据及股票数据,运用KMV模型进行信用风险度量,并提出建议与总结,以期完善信用风险度量实证过程,加强上市银行防控风险能力。     

次贷危机后信用违约交换法律规制的新发展

次贷危机后,美国和欧盟相继颁布或修改了相关的法规来加强对信用违约交换的法律监管。这些新法规主要体现在对风险出售者、风险买受者以及债券发行者的监管方面。中国可以借鉴欧美的相关立法经验,建立符合中国实际情况的监管机制。     

An endogenous structural credit risk model incorporating with moral hazard and rollover risk

In this paper, we embed optimal contracting between the manager and equity holders into Leland-Toft endogenous structural credit risk model to study the impact of moral hazard on the firm's credit risk with rollover debts. Our model quantitatively shows that the agency costs induced by the moral hazard can endogenously have significant impacts on credit spreads, besides the costs of rolling over the maturing debts of the firm. It originates from the conflicts that these two costs should be covered by equity holders while both the manager and maturing debt holders are still paid in full. The numerical results show that the credit spread with the agency costs of moral hazard is larger than the one without the agency costs. Thus, the moral hazard could be used to explain “credit spread puzzle” as an endogenous factor. The explicit formulae of the equity value, the debt value, and the endogenous default boundary are also given.     

Bilateral counterparty risk valuation for credit default swap in a contagion model using Markov chain

The computation of the bilateral counterparty valuation adjustment for a credit default swap (CDS) contract is in effect the modeling of the default dependence among the investor, the protection seller, and the reference entity. We present a contagion model, where defaults of three parties are all driven by a common continuous-time Markov chain describing the macroeconomic conditions. We give the explicit formula for the bilateral credit valuation adjustment (CVA) of CDS and examine the effect of the regime switching on the CVA.     

Convergence Clubs: Some Additional Evidence

The paper shows that the joint presence of moral hazard and repudiation risk generates an important interaction effect. In order to provide the proper incentives to borrowers, the optimal financial contract under moral hazard calls for all available resources to be paid to the lender in the event of a poor realization for output. Repudiation risk limits the size of this transfer, as the debtor has the option to default. This upper bound on the resource transfer exacerbates the moral hazard problem, reducing lending and the equilibrium level of investment and output.     

North–South Lending with Moral Hazard and Repudiation Risk

The paper shows that the joint presence of moral hazard and repudiation risk generates an important interaction effect. In order to provide the proper incentives to borrowers, the optimal financial contract under moral hazard calls for all available resources to be paid to the lender in the event of a poor realization for output. Repudiation risk limits the size of this transfer, as the debtor has the option to default. This upper bound on the resource transfer exacerbates the moral hazard problem, reducing lending and the equilibrium level of investment and output.     

Investing against the wind: contagion during the recent financial crisis

This article examines the effect of Warren Buffett’s investment in Goldman Sachs on 24 September 2008, during the subprime mortgage crisis. Although this event is arguably perceived to be the biggest expression of confidence in the financial market during the crisis, by conducting event studies, we do not find the major counterparties of Goldman Sachs displayed positive abnormal returns. Moreover, the abnormal return is not significantly related to the counterparty connection. We have similar findings on these financial institutions’ default probabilities using credit default swap.     

Tail return analysis of Bear Stearns' credit default swaps

We compare several models for Bear Stearns' credit default swap spreads estimated via a Markov chain Monte Carlo algorithm. The Bayes Factor selects a CKLS model with GARCH–EPD errors as the best model. This model best captures the volatility clustering and extreme tail returns of the swaps during the crisis. Prior to November 2007, only four months ahead of Bear Stearns' collapse though, the swap spreads were indistinguishable statistically from the risk-free rate.     

The linkage between life insurer spread behaviour and credit swap transaction: policyholder protection analysis

ABSTRACT

The paper develops a contingent claim model to evaluate the equity of a life insurer when the insurer could act as a protection buyer or a protection seller in a credit swap transaction market. The investment market and the life insurance market faced by the insurer are assumed to be imperfectly competitive in order to capture the insurer’s asset-leading or liability-reducing spread behaviour. This paper complements the insurance literature by analysing how the effects of credit swap transactions on insurer spread behaviour and policyholder protection, and how they might differ across various degrees of capital regulation, premature default risk, and profit-sharing participation. Our findings offer some useful insights for achieving the stability of the insurance system.     

Firm credit risk in normal times and during the crisis: are banks less risky?

Bank solvency was a major issue during the financial crisis of 2007–2009, but bank credit default swap (CDS) spreads were almost always below nonbank CDS spreads. What is the reason for this gap? Are banks perceived to be less risky? This study empirically decomposes CDS premia for 45 major banks and 167 large industrial firms from Europe and the US. It turns out that expected losses are usually somewhat lower for banks than for nonbanks, but expected losses contribute relatively little to the observed CDS premia. CDS spreads for banks and nonbanks differ mainly because market participants require a lower compensation for bearing bank credit risk. The quite persistent difference in the credit risk premia for banks and nonbanks disappears only temporarily during the crisis.