随机波动HJM框架下信用利差模型及实证研究

将随机波动引入到具有违约风险的HJM模型中,基于无套利条件推导得出随机波动HJM模型框架下信用利差的漂移项限制条件,从而构建了随机波动HJM框架下的信用利差模型,并基于波动率结构的适当设定对模型进行马尔科夫简化,进而利用该模型对中国可违约债券市场信用利差的动态特性进行实证分析。结果发现：短期信用利差的动态特性具有显著的随机波动特征,而随机波动HJM框架下的信用利差模型可以很好地刻画中国可违约债券市场信用利差的动态特性。     

信用违约互换的定价模型及实证研究

本文假设市场风险和信用风险线性相关,在交易双方互不违约的情况下,建立了基于某一个参照信用的标准信用违约互换和远期信用违约互换的简约定价模型.然后以Xerox公司的相关数据为样本,对标准信用违约互换模型进行实证检验.结果表明由模型模拟的价差期限结构图与实际报价的价差期限结构图基本吻合.     

基于信用溢价的融资租赁企业信用风险的测度

依靠KMV模型的理论基础与Merton提出的内生信用溢价公式,在违约距离的基础上衍生出信用溢价;通过承租人企业二级市场股价表现与财务等相关信息得出资产价值波动与违约距离,进而使用信用溢价指标来衡量承租人产生的信用风险,并收集融资租赁行业主要上市公司数据,对模型的有效性进行实证研究。信用溢价指标作为分析企业债信用风险的计量方法,在融资租赁行业信用风险研究中可以起到借鉴作用。     

公司债违约风险补偿研究

文章从公司债利差入手,探讨了公司违约的风险补偿问题.研究认为:(1)公司债利差中的信用溢价部分是由不可预测的跳跃性违约及市场违约传染所致,它具有系统性风险特征,无法分散;(2)用即期利率来测度和估算公司债利差,可以有效地避免用到期收益率计算利差的三个缺陷;(3)在没有公司累计违约率历史数据的条件下,可以用卡尔曼滤波下的拟最大似然法(QML)来估算跳跃性违约风险补偿.     

信用风险管理中损失分布法与价值分布法的模拟比较

文章通过实际模型比较了信用风险的两大类模型:违约模型和盯市模型。信用风险具有广义与侠义之分,狭义的信用风险就指违约风险,即相关金融资产(贷款)发生违约的可能性及违约的可能损失;广义的信用风险在违约风险的基础上应该包括信用变化所带来风险,也就是信用迁移风险。文章通过构建具有蒙特卡洛模拟的信用风险模型,计算这两种风险值,通过比较得出如下结论:并不是广义的信用风险就大,而是与资产组合的信用状况相关,高信用品质的资产信用迁移增加风险,而对低信用品质的资产信用迁移减少风险。     

交易对手违约风险的信用违约互换定价

本文在约化模型的框架内考虑了含交易对于违约风险的信用违约互换的定价。在参照资产违约强度与利率相关、信用保护买卖双方违约强度受到参照资产违约影响的情形下,给出了信用违约互换的定价公式。     

基于中国隐含波动率和方差溢价的实证研究

隐含波动率在资本市场中发挥着重要作用,本文使用二次幂变差方法,首次就我国股市的隐含波动率指数及其方差溢价对股市收益和宏观经济活动的预测能力进行实证分析.研究发现:隐含波动率的增加会加剧市场波动风险;方差的连续部分和跳跃部分对未来的实现方差具有显著的正向影响;相对于周收益,方差溢价和波动率指数对月度收益的预测能力更强;隐含波动率指数和方差溢价目前无法对我国宏观经济活动起到预测作用.研究结论为进一步分析我国证券市场的风险偏好提供了经验证据.     

信用风险的GLMMs建模分析

如何精确计量信用风险一直是理论界和实务部门的难点和热点问题.本文使用广义线性混合模型对信用风险进行建模分析,将影响违约概率的可观测因素和不可观测因素分别用固定效应和随机效应表示,根据需要随机效应可扩展为多个因子.研究表明,模型具有较好的延展性,宏观经济变量作为可观测变量无法全部解释违约率的异质性,随机效应可以更好地捕捉违约率的异质性,行业因素对违约概率的影响比宏观经济变量显著.     

宏观经济总指数的一种新研究方法

本文在深入分析Creditportfolio View模型的原理基础上,在我国历史违约概率有关数据缺乏的情况下,利用模糊数学的非线性隶属函数确定各宏观经济变量的隶属函数,以及判断矩阵分析法来确定各宏观经济变量因素的重要程度,得到宏观经济总指数.粗略得出我国近20年来违约概率的周期性变化特点并进行分析.     

随机波动率下信用风险定价模型的比较分析

文章分析了在Morten模型、跳扩散模型和首次时间通过模型中的随机波动率下可违约债券的定价问题。探讨了随机波动率下可违约债券定价机制,利用特征函数及其逆变换的方法得到了随机波动率下可违约债券的定价公式,并通过数值模拟分析了违约概率和信用价差的期限结构。     

货币政策、时变预期与融资成本

文章在货币当局与市场主体存在不对称信息条件下,探讨了货币当局实施未预期的宽松性政策时,市场主体预期时变性在这一政策行动影响信贷市场融资成本过程中的机制。首先,我们采用外部融资溢价度量融资成本,提出在经济周期的不同阶段,未预期的宽松性政策通过作用于市场主体预期的时变性特征,进而影响外部融资溢价的非线性效应假说,然后,建立包含货币政策变量的马尔科夫区制转换信贷利差模型和市场主体预期形成模型展开检验。研究显示,未预期的宽松性政策会暴露出经济不良的私有信息,从而使市场主体形成悲观的经济前景预期。而且,在经济衰退阶段,政策行动促使市场主体预期恶化的影响效应较小,会较大幅度地降低外部融资溢价;在经济扩张阶段,政策行动促使市场主体预期恶化的影响效应将会越大,进而较小幅度地降低外部融资溢价,这也就意味着,市场主体预期形成方式的时变性,影响到未预期宽松性政策降低信贷市场融资成本的力度。     

A Markov Chain Copula Model for Credit Default Swaps with Bilateral Counterparty Risk

Reduced-form credit risk models are widely used in pricing and hedging credit derivatives. Generating default dependency is the key element in any such model. In this article, we use Markov copulae approach to model the dependence structure of defaults between the three obligors, one is the reference entity, another is the protection seller, the other is the protection buyer(the investor), so we can consider the bilateral counterparty risk of credit default swaps(CDS). In this Markov chain copula model, we obtain the explicit formulas of the CDS premium rates C ₁(T) (with unilateral counterparty risk) and C ₂(T) (with bilateral counterparty risk). And then we perform some numerical experiments to analyze the difference of the fair spreads between the unilateral case and the bilateral case.     

时变三因子模型风险系数的动态研究

由Fama和French提出的三因子模型能够较好地解释股票的收益率风险溢价。文章以状态空间模型为框架,将风险因子系数作为状态变量,市场风险溢价作为观测变量,构建时变三因子模型来应对股票市场价格的时变特征。研究结果显示,利用卡尔曼滤波来估计时变风险因子系数,增强了估计结果的准确性与连贯性;风险因子系数变化规律与中国A股市场政策和环境影响相吻合,消除非理性噪声后的时变三因子模型更具有解释力度。     

Establishing decision tree-based short-term default credit risk assessment models

ABSTRACT

Traditional credit risk assessment models do not consider the time factor; they only think of whether a customer will default, but not the when to default. The result cannot provide a manager to make the profit-maximum decision. Actually, even if a customer defaults, the financial institution still can gain profit in some conditions. Nowadays, most research applied the Cox proportional hazards model into their credit scoring models, predicting the time when a customer is most likely to default, to solve the credit risk assessment problem. However, in order to fully utilize the fully dynamic capability of the Cox proportional hazards model, time-varying macroeconomic variables are required which involve more advanced data collection. Since short-term default cases are the ones that bring a great loss for a financial institution, instead of predicting when a loan will default, a loan manager is more interested in identifying those applications which may default within a short period of time when approving loan applications. This paper proposes a decision tree-based short-term default credit risk assessment model to assess the credit risk. The goal is to use the decision tree to filter the short-term default to produce a highly accurate model that could distinguish default lending. This paper integrates bootstrap aggregating (Bagging) with a synthetic minority over-sampling technique (SMOTE) into the credit risk model to improve the decision tree stability and its performance on unbalanced data. Finally, a real case of small and medium enterprise loan data that has been drawn from a local financial institution located in Taiwan is presented to further illustrate the proposed approach. After comparing the result that was obtained from the proposed approach with the logistic regression and Cox proportional hazards models, it was found that the classifying recall rate and precision rate of the proposed model was obviously superior to the logistic regression and Cox proportional hazards models.     

基于行业冲击因子矩阵的宏观压力测试方法研究

目前,考虑行业违约相关的宏观压力测试方法较少,而两种主流方法风险传导过程都存在明显不足。因此,从理论上提出一个新的压力传导模型,通过冲击因子矩阵使偏离平均值的行业违约率与宏观经济冲击因子联系起来,将违约的顺周期性和行业违约相关性纳入统一框架内;在技术上避免了分行业多元线性回归方程,使分行业压力测试过程简易可行。实证结果表明:该方法能合理刻画宏观经济冲击对各行业违约率的影响,商业银行为提高抵御系统性风险的能力,可降低顺周期性强的行业贷款占比,或者调整贷款行业结构以避免行业集中度过高。     

The pricing of defaultable bonds under a regime-switching jump-diffusion model with stochastic default barrier

In this paper, we investigate the price for the zero-coupon defaultable bond under a structural form credit risk with regime switching. We model the value of a firm and the default threshold by two dependent regime-switching jump-diffusion processes, in which the Markov chain represents the states of an economy. The price is associated with the Laplace transform of the first passage time and the expected discounted ratio of the firm value to the default threshold at default. Closed-form results used for calculating the price are derived when the jump sizes follow a regime-switching double exponential distribution. We present some numerical results for the price of the zero-coupon defaultable bond via Gaver-Stehfest algorithm.     

Macroeconomic Factors Strike Back: A Bayesian Change-Point Model of Time-Varying Risk Exposures and Premia in the U.S. Cross-Section

This article proposes a Bayesian estimation framework for a typical multi-factor model with time-varying risk exposures to macroeconomic risk factors and corresponding premia to price U.S. publicly traded assets. The model assumes that risk exposures and idiosyncratic volatility follow a break-point latent process, allowing for changes at any point on time but not restricting them to change at all points. The empirical application to 40 years of U.S. data and 23 portfolios shows that the approach yields sensible results compared to previous two-step methods based on naive recursive estimation schemes, as well as a set of alternative model restrictions. A variance decomposition test shows that although most of the predictable variation comes from the market risk premium, a number of additional macroeconomic risks, including real output and inflation shocks, are significantly priced in the cross-section. A Bayes factor analysis massively favors the proposed change-point model. Supplementary materials for this article are available online.     

Conditional Euro Area Sovereign Default Risk

We propose an empirical framework to assess the likelihood of joint and conditional sovereign default from observed CDS prices. Our model is based on a dynamic skewed-t distribution that captures all salient features of the data, including skewed and heavy-tailed changes in the price of CDS protection against sovereign default, as well as dynamic volatilities and correlations that ensure that uncertainty and risk dependence can increase in times of stress. We apply the framework to euro area sovereign CDS spreads during the euro area debt crisis. Our results reveal significant time-variation in distress dependence and spill-over effects for sovereign default risk. We investigate market perceptions of joint and conditional sovereign risk around announcements of Eurosystem asset purchases programs, and document a strong impact on joint risk.     

Basket CDS pricing with default intensities using a regime-switching shot-noise model

In this paper, we employ an intensity-based credit risk model with regime-switching to study the valuation of basket CDS in a homogeneous portfolio. We assume that the default intensities are described by some dependent regime-switching shot-noise processes and the individual jumps of the intensity are driven by a common factor. By using the conditional Laplace transform of the regime-switching shot-noise process, we obtain the closed form results for pricing the fair spreads of the basket CDS. We present some numerical examples to illustrate the effect of the model parameters on the fair spreads.     

Sovereign rescheduling probabilities in emerging markets: a comparison with credit rating agencies’ ratings

This study estimates default probabilities of 124 emerging countries from 1981 to 2002 as a function of a set of macroeconomic and political variables. The estimated probabilities are then compared with the default rates implied by sovereign credit ratings of three major international credit rating agencies (CRAs) – Moody's Investor's Service, Standard & Poor's and Fitch Ratings. Sovereign debt default probabilities are used by investors in pricing sovereign bonds and loans as well as in determining country risk exposure. The study finds that CRAs usually underestimate the risk of sovereign debt as the sovereign credit ratings from rating agencies are usually too optimistic.