基于转移概率矩阵的企业债券定价模型

企业债券评估的主要方法为结构化风险模型和密度式风险模型,但中国企业债券市场评级数据少、缺乏历史违约事件,因此可以通过对JLT模型进行改进,以加权平均的方式计算经验转移概率矩阵,然后利用市场上各评级债券的时间序列数据计算风险中性违约概率,并通过市场宏观数据判断经济处于上升期还是衰退期,据此计算条件转移概率矩阵,最后通过债券远期折现的方式构建适合中国市场特色的债券定价模型。实证部分选取了2014年部分新发行债券对模型进行了实证检验,并对国内企业债券定价的现状进行了分析。     

信息不确定、信息不对称与债券信用利差

在将债券市场中的信息不对称区分为一级市场上发债企业与投资者之间的信息不确定与二级市场上投资者之间的信息不对称基础上,本文以中国企业债券为样本,实证检验信息不确定、信息不对称与债券信用利差的关系。检验结果表明,在控制债券以及企业层面相关控制变量情况下,投资者在信息不确定与信息不对称两种情况下能获得显著的风险溢价。在控制了信用等级与事件日时长的情况下,该结果是稳健的。最后,信息不确定与信息不对称能够帮助信用风险结构模型解释债券信用利差。本文的研究结论表明,为了更好保护投资者,监管部门在加强企业债券信息披露监管的同时,也应该强化对投资者信息披露的监管。     

Do Central Bank Liquidity Facilities Affect Interbank Lending Rates?

In response to the global financial crisis that started in August 2007, central banks provided extraordinary amounts of liquidity to the financial system. To investigate the effect of central bank liquidity facilities on term interbank lending rates near the start of the crisis, we estimate a six-factor arbitrage-free model of U.S. Treasury yields, financial corporate bond yields, and term interbank rates. This model can account for fluctuations in the term structure of credit and liquidity spreads observed in the data. A significant shift in model estimates after the announcement of the liquidity facilities suggests that these central bank actions did help lower the liquidity premium in term interbank rates.     

信息挖掘还是噪声交易:债券特质风险如何影响信用利差?

特质风险向债券市场传递风险的方式,直接关系到债券定价逻辑和系统性金融风险防范。本文选取交易所公司债数据,从投资者信息挖掘行为和非理性交易行为出发,研究债券特质风险对信用利差的传导效应与传导机制,并从违约视角探索特质风险产生传导效应的原因,同时分析投资者对不同类型债券所做反应的异质性。研究结论表明:特质风险会通过信息挖掘机制和噪声交易机制影响 信用利差,且以噪声交易机制为主;违约事件引致了更多噪声交易,是特质风险产生传导效应的重要环境因素;发行人的股票上市或国企背景降低了投资者面临的信息不对称程度,并有效抑制了噪声交易机 制的作用,而债券的低评级或短期限特征则会引发投资者的抛售行为,进而放大了噪声交易机制的作用。     

基于SV模型的中国债券信用价差影响因素研究

针对中国债券市场,选取2005年6月—2010年6月的企业债和国债月度交易情况,对静态利率期限结构SV参数模型利用遗传算法求解,拟合较为精确的企业债和国债的即期利率曲线,据此计算出企业债的信用价差。在对中国AAA级企业债按不同的期限进行回归分析后发现,该等级债券的信用价差曲线形态呈下降趋势,原因可能是中国债券信用评级过高、担保机制存在问题等;对不同期限企业债信用价差的宏观经济影响因素大致相同,如居民消费价格指数、国内生产总值的变化率等,而且这些信用价差序列之间存在显著的相关关系。     

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.     

基于马尔可夫转换模型的违约风险溢价预测研究

针对违约风险溢价变化依赖于经济波动状态以及市场、宏观经济变量依赖于经济周期时变因素的阶段,基于马尔可夫转换阶段的具体特征,构建马尔可夫违约风险溢价预测转换模型,并以香港恒生指数信用违约互换波动为例,测算因时变系数波动的指数息差、宏观经济变量等概率,通过实证算例剖析股市、宏观经济变量与违约风险溢价之间的内在联动关系和信用违约风险溢价变化的转换机制,以期实现对违约风险溢价能够进行有效预测,实证仿真结果说明了模型的有效性。     

Variable selection in proportional hazards cure model with time-varying covariates,application to US bank failures*

From a survival analysis perspective, bank failure data are often characterized by small default rates and heavy censoring. This empirical evidence can be explained by the existence of a subpopulation of banks likely immune from bankruptcy. In this regard, we use a mixture cure model to separate the factors with an influence on the susceptibility to default from the ones affecting the survival time of susceptible banks. In this paper, we extend a semi-parametric proportional hazards cure model to time-varying covariates and we propose a variable selection technique based on its penalized likelihood. By means of a simulation study, we show how this technique performs reasonably well. Finally, we illustrate an application to commercial bank failures in the United States over the period 2006–2016.     

经济政策不确定性如何影响金融市场间的流动性协同运动？——基于中国金融周期的视角

金融市场间流动性出现高协同运动是发生危机传染的重要表现之一，因此，针对流动性动态联动效应的研究显得极为重要。本文基于中国金融市场数据测算了2003-2018年间我国股市、债市流动性，并对Colacito等（2011）的混频数据抽样动态条件相关系数模型（DCC-MIDAS）进行了扩展，同时从金融周期视角出发，运用扩展后的模型考察了经济不确定性在不同时间区间内对于流动性波动率和相关性是否存在不同的作用效果。研究结果表明，相较于单因子混频模型，引入经济政策不确定性的多因子混频模型可以更好地捕捉我国股债两市相关性的动态变化；同时，经济政策不确定性的提高会降低股债两市流动性的正相关性，但这一作用效果会在金融周期的拐点处转为加强两者的正相关性。本文不仅为讨论股债两市联动效应提供了流动性的新视角，也为金融市场风险监管提供了重要的参考依据。     

Marginal Means/Rates Models for Multiple Type Recurrent Event Data

Recurrent events are frequently observed in biomedical studies, and often more than one type of event is of interest. Follow-up time may be censored due to loss to follow-up or administrative censoring. We propose a class of semi-parametric marginal means/rates models, with a general relative risk form, for assessing the effect of covariates on the censored event processes of interest. We formulate estimating equations for the model parameters, and examine asymptotic properties of the parameter estimators. Finite sample properties of the regression coefficients are examined through simulations. The proposed methods are applied to a retrospective cohort study of risk factors for preschool asthma.     

The Additive Nonparametric and Semiparametric Aalen Model as the Rate Function for a Counting Process

We use the additive risk model of Aalen (Aalen, 1980) as a model for the rate of a counting process. Rather than specifying the intensity, that is the instantaneous probability of an event conditional on the entire history of the relevant covariates and counting processes, we present a model for the rate function, i.e., the instantaneous probability of an event conditional on only a selected set of covariates. When the rate function for the counting process is of Aalen form we show that the usual Aalen estimator can be used and gives almost unbiased estimates. The usual martingale based variance estimator is incorrect and an alternative estimator should be used. We also consider the semi-parametric version of the Aalen model as a rate model (McKeague and Sasieni, 1994) and show that the standard errors that are computed based on an assumption of intensities are incorrect and give a different estimator. Finally, we introduce and implement a test-statistic for the hypothesis of a time-constant effect in both the non-parametric and semi-parametric model. A small simulation study was performed to evaluate the performance of the new estimator of the standard error.     

违约相关性分析

 企业违约相关性是指具有相关关系的企业之间违约的相互关系，即一个企业违约引起另一个企业违约的可能性。如果两个企业完全不相关，则两个企业的违约就是相互独立的，违约相关性是“零”；当两个企业有关时，意味着双方同时违约的可能性增大；当两个企业完全相关时，其违约相关性趋于“1”。因此，企业违约相关性是[0,1]上的一个区间值，且违约与违约相关性均具有“模糊性”。     

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.     

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.     

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.     

Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models

The prediction of the time of default in a credit risk setting via survival analysis needs to take a high censoring rate into account. This rate is because default does not occur for the majority of debtors. Mixture cure models allow the part of the loan population that is unsusceptible to default to be modeled, distinct from time of default for the susceptible population. In this article, we extend the mixture cure model to include time-varying covariates. We illustrate the method via simulations and by incorporating macro-economic factors as predictors for an actual bank dataset.     

我国保险投资组合的模拟和金融风险测量研究

 本文利用Copula函数的概念研究了保险投资组合多元金融数据的统计模拟。根据我国保险投资的特殊性，我们选用沪深300指数、基金指数、企债指数和国债指数四种风险资产来模拟保险投资组合中的股票、基金、企债和国债收益。基于模拟的结果分别利用传统近似方法（Add-VaR、N-VaR和H-VaR）和Copula方法计算了投资组合的总风险；相对于Copula-VaR方法，Add-VaR显著高估了风险，N-VaR显著低估了风险，H-VaR对于Copula-VaR的近似效果比较好，但其也高估了风险，即H-VaR相对于Copula-VaR是一种比较保守的方法。另外，我们分析了投资组合权重变化和Copula函数的选择对投资组合总风险的影响。     

An additive Cox model for coronary heart disease study

Existing models for coronary heart disease study use a set of common risk factors to predict the survival time of the disease, via the standard Cox regression model. For complex relationships between the survival time and risk factors, the linear regression specification in the existing Cox model is not flexible enough to accounts for such relationships. Also, the risk factors are actually risky only when they fall in some risk ranges. For more flexibility in modelling and characterize the risk factors more accurately, we study a semi-parametric additive Cox model, using basis splines and LASSO technique. The proposed model is evaluated by simulation studies and is used for the analysis of a real data in the Strong Heart Study.     

收益率曲面预测及其在信用债投资组合管理中的应用

收益率曲线是信用债投资者的重要参考。在市场套利活动的作用下,跨期限和信用等级的债券收益率具有很强的内生联系,其变动规律具有整体性和连续性。以往研究将信用债收益率曲线拆分成无风险利率曲线和信用利差两个部分,前者关注期限的影响,后者关注信用等级的影响,但很少同时考虑两者的共同影响。本文在收益率曲线的基础上增加信用等级维度,将AAA+级到AA级收益率曲线视为一个相互关联的整体,定义为信用债的收益率曲面(Yield Surface)。相比收益率曲线,收益率曲面包含了跨等级的系统性预测信息,通过预测收益率曲面能够构建具有较高收益的投资管理策略。本文以中期票据市场为例,采用卷积神经网络模型预测1周后的收益率曲面,在此基础上计算债券的预测理论价格,发现该价格对未来交易价格的预测有显著作用。基于预测价差,本文提出了信用债投资管 理策略,应用该策略的投资组合能够获得显著的正收益。业绩归因分析发现,该策略取得的收益同时来 自投资组合在信用风险和久期风险上的暴露,预测价差可以刻画债券市场的“风险前沿”。本文采用了中债估值价格进行稳健性检验,主要结论均保持一致,具有较强的稳健性。     

银行间债券市场和交易所债券市场动态关系研究——基于DCC-MGARCH模型的分析

运用DCC-MGARCH模型对银行间债券市场与交易所债券市场之间的动态相关系数进行研究,并对两债券市场之间相关系数的动态时变特征进行分析。研究结果表明:银行间债券市场与交易所债券市场相关系数总体为正,波动幅度小,但时变特征不明显;两市场之间的动态相关系数随着时间的推移没有显著的提高,与其他金融市场之间的动态相关性相比,两市场动态相关系数还相对较低;债券市场的分割特征仍然明显,市场融合有很大的提升空间,这表明银行间债券市场与交易所债券市场之间的一体化进程还任重道远,故应逐步完善债券市场体系,取消市场中不合理的准入限制和市场壁垒,制定有利于两市场融合的政策法规,为建立统一互联高效的债券市场奠定良好的市场基础和制度环境。