Copula方法与相依违约研究

目前信用风险研究的重点已经从单笔债务的违约概率研究转移到多笔债务的相依违约(Dependent Defaults)研究。Copula方法是研究相依违约的重要方法。这种方法是最近几年才被应用到信用领域研究中的一种新方法。本结合代表性献对Copula方法在相依违约研究中的应用进行了探讨。探讨的内容包括Copula方法被应用于相依违约研究的原因、该方法对于相依违约建模理论的改进以及在实证应用中使用Copula方法应该注意的问题。     

基于Copula的债务抵押债券定价

债务抵押债券在美国次债危机中扮演了非常重要的角色,对其正确定价引起学术界的普遍关注。本文利用KMV模型估算出各债务人的违约概率,并用三种Copula函数分别估算出债务人之间的违约相关系数,模拟出各债务人的违约时点,在此基础上对债务抵押债券各系列进行定价,研究结果发现Student-t Copula计算出的公平溢酬大致上高于Gaussion Copula和Clayton Copula,并且CDO的存续期越长,挽回率越低,各系列投资者要求的公平溢酬就越高。     

有传染违约相关情形下信用违约互换的估价

在回收率非零的情况下,研究了信用违约互换的参照资产和保护卖方有传染违约相关时信用违约互换的定价问题.相关传染违约结构由双方相关的违约强度描述,即一方的违约会导致另一方的违约强度的增加.利用参照资产与保护卖方违约停时的联合概率分布,得到了信用违约互换价格的精确表达式,并且分析了清算期和回收率对清算风险价格和替换成本的影响.数值化的结果说明,在信用违约互换的定价中,不仅不能忽视参照资产对保护卖方违约的影响,还不能忽视清算期和回收率对信用违约互换价格的影响.如果在定价信用违约互换时不考虑回收率,即假定回收率为零时,会严重高估信用违约互换的价格.     

信息披露扭曲下企业债券违约风险量化研究

信息披露的真实性会直接影响到投资者对企业债券违约风险自々判断。利用信息噪声的偏倚性捕获财务报告信息中对资产价值的故意扭曲,推导了信息偏误下资产价值的条件分布、违约概率和信用价差的解析表达式.数值分析表明当资产价值遭到不同方向的扭曲时,信息噪声与违约概率会表现出不同的变动关系。实证检验表明该模型可以较为准确的刻画财务信息扭曲造成的债券违约风险和信用价差的变化规律。该模型为理解债券违约风险和财务报告信息扭曲之间的关系提供了新的启发,可以帮助债券投资者在信息披露问题比较严重的市场环境中评估违约风险。     

多参数Archimedean Copula模型下的CDO定价

利用高维Archimedean Copula模型对合成CDO进行定价,在传统简单Archimedean Copula的基础上,基于三种不同的方式,引入多个参数,从而解决作为市场基准的Gaussian Copula模型下存在相关性微笑的问题.对于特殊的大样本同质资产组合,违约损失分布可以直接从违约概率得到.而对于一般性的资产组合,可以得到损失的特征函数,从而通过快速Fourier变换,计算出违约的分布.最后,给出了数值计算结果.     

基于Copula函数的组合资产条件相依性模型研究

条件概率分布常用来研究马尔科夫序列相依模型的构建,组合资产的相依结构受多方面的影响,资产之间的相互影响与时间上的记忆效应是组合资产两类主要的相依关系.结合条件概率的理论建立基于Copula函数相依关系模型,研究组合资产之间同期相依关系及时间上的短期相依关系,提出了模型参数的三阶段极大似然估计方法.     

随机挽回率下第n次违约互换的蒙特卡罗模拟定价

考虑到挽回率是违约互换定价的重要因素,同时获得准确的挽回率也是极其困难的,于是假设挽回率是随机的,并与对应资产违约时间呈Copula类相依结构.在该假设条件下提出一种对第n次违约互换定价的模拟算法.通过实证模拟发现,恒定挽回率,独立随机挽回率和Copula结构的挽回率对应的定价结果相差较大.     

组合类信用互换BDS的定价研究

由于组合类信用违约互换(BDS)的定价复杂性,目前没有统一的定价模型。基于风险中性定价原则,给出了mBDS公平保费的一个定价公式。应用Clayton Copula函数的来描述违约损失尾部相关的下尾特征,利用Kenclall秩相关系数τ来测度违约时间之间的非线性相关关系。在MC数值计算方面,应用重要性抽样技术来计算或有赔付的期望值E(Z_(pro)~(m))和定期支付的保费E(Z_(pre)~(m)),并进行了比较静态分析。另外数值分析结果表明,Copula函数的选择对估值具有显著影响,表明在衍生品的定价研究中要重视模型风险问题。     

国际碳排放权市场动态相依性分析及风险测度:基于Copula-GARCH模型

选取2009年3月13日-2010年8月4日的CER和EUA交易价格数据,借用CopulaGARCH模型,文章对欧洲气候交易所EUA和CER现货市场与期货市场之间的动态相依性进行了分析。分别选取Student-t DCC、Student-t TVC、Gaussian DCC、G3,ussian TVC和SJCPatton五种动态Copula函数来捕捉市场之间的动态相依性结构,研究表明Student-t DCC动态Copula函数能够更好地描述EUA和CER现货市场与期货市场之间的动态相依性。此外,EUA和CER各市场之间存在较强的对称尾部相依性,而非对称尾部相依性的证据尚不十分充足.进一步地,文章基于动态相依性分析运用Monte Carlo方法模拟国际碳排放权市场投资组合的风险VaR。     

信用组合风险度量研究

我国商业银行在信用组合风险管理方面还比较薄弱，虽然国外已有一些较为成熟的信用组合风险管理模型，但是很难在中国直接应用。另一方面，早期的信用组合风险往往只是单独考虑个别资产的风险，没有考虑资产之间的违约相关性，造成风险度量的偏差。本文在考虑了违约相关性的基础上，基于Logit回归分析，利用微模拟的方法，提出了一个符合中国商业银行资产特点的信用组合风险度量模型。     

On the simulation of portfolios of interest rate and credit risk sensitive securities

We discuss extensions of reduced-form and structural models for pricing credit risky securities to portfolio simulation and valuation. Stochasticity in interest rates and credit spreads is captured via reduced-form models and is incorporated with a default and migration model based on the structural credit risk modelling approach. Calculated prices are consistent with observed prices and the term structure of default-free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds and the sensitivity of future portfolio valuation with respect to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) study of the structure of credit risk by investigating the impact of disparate risk factors on portfolio risk, and (iii) tracking of corporate bond indices via simulation and optimisation models. In particular, we study the effect of uncertainty in credit spreads and interest rates on the overall risk of a credit portfolio, a topic that has been recently discussed by Kiesel et al. [The structure of credit risk: spread volatility and ratings transitions. Technical report, Bank of England, ISSN 1268-5562, 2001], but has been otherwise mostly neglected. We find that spread risk and interest rate risk are important factors that do not diversify away in a large portfolio context, especially when high-quality instruments are considered.     

基于双因子CIR强度式定价的信用债券投资组合优化

信用风险和利率风险是相互关联影响的。资产组合优化不能将这两种风险单独考虑或简单的相加,应该进行整体的风险控制,不然会造成投资风险的低估。本文的主要工作:一是在强度式定价模型的框架下,分别利用CIR随机利率模型刻画利率风险因素“无风险利率”和信用风险因素“违约强度”的随机动态变化,衡量在两类风险共同影响下信用债券的市场价值,从而构建CRRA型投资效用函数。以CRRA型投资效用函数最大化作为目标函数,同时控制利率和信用两类风险。弥补了现有研究中仅单独考虑信用风险或利率风险、无法对两种风险进行整体控制的弊端。二是将无风险利率作为影响违约强度的一个因子,利用“无风险利率因子”和“纯信用因子”的双因子CIR模型拟合违约强度,考虑了市场利率变化对于债券违约强度的影响,反映两种风险的相关性。使得投资组合模型中既同时考虑了信用风险和利率风险、又考虑了两种风险的交互影响。避免在优化资产组合时忽略两种风险间相关性、可能造成风险低估的问题。     

藤Copula模型与多资产投资组合VaR预测

投资组合风险管理往往涉及多个资产,在传统的二元Copula函数面临"维度诅咒"问题及多元Copula函数刻画多变量联合分布时其精确性和灵活性存在各种局限性的情况下,引入藤Copula刻画多个资产收益的联合分布,基于不同的Pair-Copula类别构建藤Copula,运用蒙特卡罗模拟方法计算多资产投资组合的VaR,通过Kupiec和Christoffersen返回检验方法测试藤Copula模型的VaR预测效果,并与传统方差-协方差风险管理方法做比较。实证分析表明,传统的方差-协方差风险管理方法和基于正态Pair-Copula作为藤Copula构建模块的方法不能通过多资产投资组合的VaR预测返回检验;而基于student-t Copula、Clayton Copula具有尾部分布特征的Copula作为构建模块的藤Copula模型能够有效地用于多资产投资组合VaR预测,从而更好的用于指导实践。     

违约强度由Lévy从属过程驱动的约化信用风险模型及信用违约互换的定价

本文引入一个约化信用风险模型,其中违约强度定义为从属过程,即非负增Lévy过程.用概率方法得到了违约时间分布的解析表达式.利用该解析表达式,给出了该信用风险模型下的信用违约互换(Credit Default Swaps)的闭形式的定价公式.     

Pricing credit default swaps with a random recovery rate by a double inverse Fourier transform

We evaluate the par spread for a single-name credit default swap with a random recovery rate. It is carried out under the framework of a structural default model in which the asset-value process is of infinite activity but finite variation. The recovery rate is assumed to depend on the undershoot of the asset value below the default threshold when default occurs. The key part is to evaluate a generalized expected discounted penalty function, which is a special case of the so-called Gerber–Shiu function in actuarial ruin theory. We first obtain its double Laplace transform in time and in spatial variable, and then implement a numerical Fourier inversion integration. Numerical experiments show that our algorithm gives accurate results within reasonable time and different shapes of spread curve can be obtained.     

A reduced-form model with default intensities containing contagion and regime-switching Vasicek processes

The contagion credit risk model is used to describe the contagion effect among different financial institutions. Under such a model, the default intensities are driven not only by the common risk factors, but also by the defaults of other considered firms. In this paper, we consider a two-dimensional credit risk model with contagion and regime-switching. We assume that the default intensity of one firm will jump when the other firm defaults and that the intensity is controlled by a Vasicek model with the coefficients allowed to switch in different regimes before the default of other firm. By changing measure, we derive the marginal distributions and the joint distribution for default times. We obtain some closed form results for pricing the fair spreads of the first and the second to default credit default swaps (CDSs). Numerical results are presented to show the impacts of the model parameters on the fair spreads.     

Unilateral counterparty risk valuation of CDS using a regime-switching intensity model

We consider the unilateral credit valuation adjustment (CVA) of a credit default swap (CDS) under a contagion model with regime-switching interacting intensities. The model assumes that the interest rate, the recovery, and the default intensities of the protection seller and the reference entity are all influenced by macro-economy described by a homogeneous Markov chain. By using the idea of “change of measure” and some formulas for the Laplace transforms of the integrated intensity processes, we derive the semi-analytical formulas for the joint distribution of the default times and the unilateral CVA of a CDS.     

A contagion model with Markov regime-switching intensities

We consider a two-dimensional reduced form contagion model with regime-switching interacting default intensities. The model assumes the intensities of the default times are driven by macro-economy described by a homogeneous Markov chain as well as the other default. By using the idea of ＇change of measure＇ and some closed-form formulas for the Laplace transforms of the integrated intensity processes, we derive the two-dimensional conditional and unconditional joint distributions of the default times. Based on these results, we give the explicit formulas for the fair spreads of the first-to-default and second-to-default credit default swaps （CDSs） on two underlyings.