债务抵押债券定价中的违约相依性研究

如何衡量违约风险乃至违约相依性是债务抵押债券定价的主要问题.运用PairCopula刻划信用资产组合违约时刻的相依结构,通过Pair Copula分解得到资产组合违约时刻的联合密度,利用Monte Carlo模拟估算CDO各系列的公平价差,进而分析各系列公平价差对回收率的敏感性.实证研究结果表明,Pair Copula能有效捕捉信用资产组合的违约相依性,各系列公平价差随着回收率的增加而减小.     

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。     

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.     

Copula理论在信用风险研究中的应用

信用风险研究足近些年来金融数学中的一个崭新的研究方向.本文主要研究了组合信用风险中的常用方法:违约相关性的Copula方法.本文建立了Copula方法与违约相关性研究中的结构化方法和约化方法的联系.此外对于单个公司的生存概率的研究,本文给出了不同于Lando (1998)的求解和证明方法,而这种方法不需要在现在就知道将...     

考虑动态相依性的可靠性系统随机Copula模型及其参数估计

动态变化是现代复杂工程系统的典型特征,动态相依系统可靠性理论能更好地揭示系统在工作阶段复杂的状态的性能,动态相依系统成为可靠性研究领域的热点和难点。本文基于随机Copula模型研究了可靠性系统在动态相依下的可靠性,介绍了随机Copula模型,基于极大似然理论的参数估计方法,给出了基于随机Copula模型的串联与并联系统在动态相依下的可靠度计算方法,并对独立系统、静态相依系统及动态相依系统的可靠度进行了比较分析,最后给出了数值算例。仿真算例的结果,验证了本文方法的可行性和有效性。     

时变多元NBS Copula模型与美国股指期货市场可视化相依性分析

基于多元NBS(Normal Birnbaum-Saunders)分布构造了一种新的多元偏斜厚尾Copula,即多元NBS Copula,并进一步采用DCC(Dynamic Conditional Correlation)模型构造了时变NBS Copula模型。以美国道琼斯30指数期货、标准普尔500指数期货和纳斯达克100指数期货为例，可视化分析了收益率序列之间的各种相依特征，比较了DCC-NBS Copula模型与其他一些Copula模型在相依结构拟合上的效果差异。实证结果表明：美国三大股指期货之间的相依结构具有正相依性、厚尾相依性、非对称相依性和时变相依性，其中，NAGARCH模型可以较好地描述收益率序列的动态特征，椭圆Copula优于阿基米德Copula,非对称椭圆Copula优于对称椭圆Copula,厚尾椭圆Copula优于正态Copula,时变椭圆Copula优于静态椭圆Copula。综合来看，DCC-NBSCopula模型是所有模型中对相依结构的拟合效果最优的。     

房地产产业链相依结构演化及其危机传染效应研究

以钢铁、有色金属、家用电器、房地产、建筑材料、建筑装饰、银行、非银金融和机械设备九大申万一级行业指数所代表的房地产产业链为研究对象,通过采用R-Vine Copula方法来刻画房地产产业链上行业间相依结构及其在2008年金融危机冲击下的结构演化特征.研究结果表明:房地产产业链上各行业间普遍存在对称、厚尾的相依结构,行业间相依性水平较高;机械设备业在整个房地产产业链上起到了枢纽中心的连接作用;金融危机的发生增强了房地产产业链的总体相依性水平,危机传染效应显著;与CVine Copula和D-Vine Copula方法相比,R-Vine Copula更适合来刻画我国房地产产业链的相依结构特征.     

基于时变Copula模型的 基金收益率相依关系的应用研究

基于时变Copula模型,获得预测方差,确定单个基金收益率序列的边缘分布.利用常见的静态Copula和时变Copula模型对基金收益率序列间两两相依关系进行建模并进行对比分析.应用研究表明,基于MCMC方法的时变Copula模型能更有效地度量基金收益率序列的风险.     

基于藤Copula的多资产交换期权模拟定价

传统的多维Copula是用单个参数来度量多变量之间的相依关系,这限制了该类Copula在描述多变量之间相依结构.为了解决这一问题,提出了一种使用藤构造三维Copula的算法,用蒙特卡罗方法分别模拟传统的单参数三维Copula和藤构造的三维Copula,并给三资产的交换期权定价,发现藤构造的Copula在定价上与单参数多维Copula存在明显的差别,使用藤构造的Copula在描述相依结构时有较大弹性.     

金融风险中违约传染效应的研究

市场中的金融资产作为一个整体,往往具有相当复杂的相依风险。本文对信用风险违约的相依性进行研究,提出一种传染效应下违约预报模型,运用加权平均的极大似然方法获得违约强度的估计。并通过对2004年至2008年美国银行业、汽车业和房地产业的数据进行实证分析,得出三大行业间存在着明显的违约风险传染的结论。     

Tail behaviour of credit loss distributions for general latent factor models

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of credit losses. To capture the co‐movements in defaults over time, we assume that defaults are triggered by a general, possibly non‐linear, factor model involving both systematic and idiosyncratic risk factors. The model encompasses default mechanisms in popular models of portfolio credit risk, such as CreditMetrics and CreditRisk⁺. We show how the tail characteristics of portfolio credit losses depend directly upon the factor model's functional form and the tail properties of the model's risk factors. In many cases the credit loss distribution has a polynomial (rather than exponential) tail. This feature is robust to changes in tail characteristics of the underlying risk factors. Finally, we show that the interaction between portfolio quality and credit loss tail behavior is strikingly different between the CreditMetrics and CreditRisk⁺ approach to modeling portfolio credit risk.     

Modelling Specific Interest Rate Risk with Estimation of Missing Data

For the treatment of specific interest rate risk, a risk model is suggested, quantifying and combining both market and credit risk components consistently. The market risk model is based on credit spreads derived from traded bond prices. Though traded bond prices reveal a maximum amount of issuer specific information, illiquidity problems do not allow for classical parameter estimation in this context. To overcome this difficulty an efficient multiple imputation method is proposed that also quantifies the amount of risk associated with missing data. The credit risk component is based on event risk caused by correlated rating migrations of individual bonds using a Copula function approach.     

信用风险相关性度量的MRS Copula模型构建及实证研究

在构建行业信用风险指数的基础上,将马尔科夫机制转换引入到信用风险相关性的度量中,建立了信用风险相关性度量的MRS Copula模型。以1990-2012年电力、煤气及水的生产和供应业,批发、零售、贸易业,石油、化学、塑胶、塑料业和信息技术业为样本的实证研究表明,行业信用风险相关性表现出较为明显的机制转换特征和非对称效应,在高风险状态,信用风险相关系数达到了0.7以上,而在低风险状态,信用风险相关系数在0.2以下.同时,信用风险"一损俱损"的特征比较明显,行业信用风险的下尾相关系数较为显著,而上尾相关系数则并不显著.商业银行可据此调整信贷资产结构,防范信用风险传染,以及优化信贷组合管理.     

A Reduced Model with Thinning-Dependence Structure

The class of reduced form models is a very important class of credit risk models, and the modelling of the default dependence structure is essential in the reduced form models. This paper models dependent defaults under a thinning-dependent structure in the reduced form framework. In our tractable model, the joint survival probability for correlated defaults can be derived, and hence the CDS premium rates (with or without counterparty risk) are given in closed form. The numerical result shows that the thinning-dependent structure is effective to model the default dependence.     

基于Copula的供应链金融质物组合价格风险测度研究

本文选取白银、铝和铜三种供应链金融质物作为研究对象,在分析三种质物收益率统计特征的基础上,引入Copula模型刻画供应链金融业务中质物收益率的“尖峰厚尾”特征以及质物收益率之间的非线性相关结构;采用Monte Carlo模拟方法测度考虑到极端情况下的质物组合价格风险值CVaR;利用时间平方根法则测度长周期视角下质物组合的价格风险。将CVaR与VaR测度结果进行对比,比较分析短期价格风险与长期价格风险,将Copula模型与传统风险测度方法下计算出的风险值进行对比,以期选取最优测度供应链金融质物组合长期价格风险模型。研究结果表明:从单一质物价格波动特征来看,三种单一质物的收益率均存在非正态分布和“尖峰厚尾”特征,具有一般金融资产收益率分布的特点。从模型的有效性来看,第一,CVaR比VaR能够更好地、全面地测度供应链金融质物组合的价格风险;第二,基于Copula模型的风险测度结果比传统集成风险测度结果的准确性高;第三,平方欧式距离法结果表明在五种Copula模型中,t-Copula是最优刻画供应链金融质物组合收益率间的相依关系的模型。从长短期风险测度结果来看,随着风险期限的增加,质物组合的价格风险值随之增大,以往研究中用短期风险测度往往会低估商业银行所面临的价格风险,不利于商业银行资金信贷的优化配置。得到的结论对我国商业银行开展供应链金融业务防范价格风险提供了量化支持。     

Counterparty risk valuation on credit-linked notes under a Markov Chain framework

A credit-linked note(CLN) is a note paying an enhanced coupon to investors for bearing the credit risk of a reference entity. In this paper, we study the counterparty risk on CLNs under a Markov chain framework, and introduce a Markov copula model to describe joint defaults between the reference entity underlying the CLN and CLN issuer. Assuming that the respective default intensities are directly and inversely proportional to the interest rate, which follows a CIR process, we obtain the explicit formulae for CLN values through a PDE approach.Finally, credit valuation adjustment(CVA) formula is derived to price counterparty credit risk.     

Credit risk model with contagious default dependencies affected by macro-economic condition

We consider a credit risk model with two industrial sectors, where defaults of corporations would be influenced by two factors. The first factor represents the macro economic condition which would affect the default intensities of the two industrial sectors differently. The second factor reflects the influences of the past defaults of corporations against other active corporations, where such influences would affect the two industrial sectors differently. A two-layer Markov chain model is developed, where the macro economic condition is described as a birth-death process, while another Markov chain represents the stochastic characteristics of defaults with default intensities dependent on the state of the birth-death process and the number of defaults in two sectors. Although the state space of the two-layer Markov chain is huge, the fundamental absorbing process with a reasonable state space size could capture the first passage time structure of the two-layer Markov chain, thereby enabling one to evaluate the joint probability of the number of defaults in two sectors via the uniformization procedure of Keilson. This in turn enables one to value a variety of derivatives defined on the underlying credit portfolios. In this paper, we focus on a financial product called CDO, and a related option.     

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.     

债券违约是否存在区域传染？——基于中国债券市场融资成本视角

2018年以来中国债券市场违约规模攀升,累计违约金额超2900亿元。债券违约后的负面影响受到投资者、发行人乃至监管部门关注。本文以北京、上海、辽宁等八个辖区为例,选取2016~2019年债券违约及债券发行数据,通过构建违约事件对债券发行价格影响因素模型,分析了债券违约的区域传染效应。研究发现:债券违约引发的信用风险存在区域传染性,主要体现为债券发行前若发行人所属辖区存在违约事件将推升债券融资成本;区域内的传染效应与违约时间距离负相关,当时间距离增长时,传染效应变弱,甚至消失;债券违约风险对不同性质企业的传染效应不同,民营企业受影响尤为显著。