有散粒噪声的机制转换的马尔科夫copula模型下的有担保安排的CDS的风险分析

信用估值调整是针对交易对手方可能出现的违约责任而对金融产品价格作出调整的计算,是度量交易对手违约风险的重要方式.在信用估值调整的计算中,违约相关风险模型的建立非常关键.我们在马尔科夫copula模型中引入共同的经济状态变量以及散粒噪声过程,建立了带有散粒噪声的机制转换的马尔科夫copula模型,该模型不仅可以刻画经济环境对违约的影响,而且可以反映在同一种经济环境中信用个体的违约变化.我们研究了此模型的鞅性质,在此模型下,我们进一步研究了有抵押担保的信用违约互换的CVA的刻画,并做了数值计算,分析了模型参数对CVA的影响.     

马氏调制强度的传染模型下CDS的CVA计算

本文考虑了具有马氏调制强度的传染模型下,信用违约互换(CDS)的双边信用估值调整(CVA).在我们考虑的模型中,利率、回收率以及CDS的买方、卖方和参照实体三方的违约强度均受宏观经济环境的影响,该经济状况由一连续时间状态的齐次马氏链所刻画.利用测度变换和累积强度的Laplace变换,我们给出了CDS合同的双边CVA的表达公式,该公式可以表示为线性常微分方程组的基本解的形式.利用所得到的公式,我们数值分析了马氏调制和违约相关性对双边CVA的影响.     

带跳扩散的可提前到期的违约期权研究

用偏微分方程的方法,研究子公司是否违约,对母公司的股票期权的定价的影响问题.在跳扩散的前提假设下,利用结构化方法,考虑当子公司违约时,母公司股票期权的可提前到期性,分时段进行分析,并给出了母公司期权定价的数学模型和解的表达式.     

基于马尔可夫方法的违约传染平均域模型

基于平均域模型,将信用组合分为几个同质的子组合,假设组合中各公司的违约强度不仅取决于宏观经济状况,而且依赖于这些子组合中违约公司的数目,以刻画不同公司间的违约相互作用;并据此建模组合违约过程为连续时间马尔可夫链,借助Kolmogorov微分方程求解信用组合损失分布;最后,通过实例计算分析传染现象对组合损失分布、风险量度的影响.     

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.     

具有违约风险和交易费的房产期权定价

房价涨幅过快过高在中国房产市场已经是一个不容回避的问题.房产期权作为一种平衡买卖双方利益进行风险管理的有效工具应运而生.在Black-Scholes定价模型的基础上,考虑违约风险和交易费用这两个影响房产期权定价的重要因素,采用未定权益思想方法和△-对冲技巧建立了房产期权的定价模型,然后对模型进行求解,获得相应的数学公式,为考虑具有违约风险和交易费用影响下房产期权进行定价.     

模型不确定性及违约风险下的最优投资问题

该文研究了一个同时具有模型不确定性和违约风险的随机最优投资组合问题.假设在金融市场中包含三种资产:银行账户(无风险资产),股票资产及可违约债券.考虑一个保险公司把保费盈余投资在这三种资产上来最大化其效用函数.把模型的不确定性因素考虑进去,此时问题转化为一个在金融市场与保险公司之间的零和微分博弈问题.首先考虑了跳扩散风险模型而后又考虑了扩散逼近模型.在这两个模型中通过动态规划准则导出了Hamilton-JacobiBellman-Isaacs(HJBI)方程,从而求出了最优投资策略,并给出了验证定理.     

LQ理论在参数随机的证券投资组合套期保值中的应用

在连续时间情形、不考虑交易费用、市场无摩擦假设,以及套期保值准则等条件下,考察了参数随机的证券投资组合中加入未定权益类衍生品形成的最优动态投资策略(u*(t)),并给出了该投资组合的最优模型所对应的黎卡提(Riccati)方程的解的存在性证明.     

利用传染模型对含有对手风险的信用证券定价(英文)

本文利用传染模型研究了可违约债券和含有对手风险的信用违约互换的定价。我们在约化模型中引入具有违约相关性的传染模型,该模型假设违约过程的强度依赖于由随机微分方程驱动的随机利率过程和交易对手的违约过程.本文模型可视为Jarrow和Yu(2001)及Hao和Ye(2011)中模型的推广.进一步地,我们利用随机指数的性质导出了可违约债券和含有对手风险的信用违约互换的定价公式并进行了数值分析.     

双指数跳扩散模型信用违约互换短期价格研究

假设参考实体没违约时信用违约互换保护买方连续支付互换价格,导出了信用违约互换价格的表达式;对标的资产价值服从双指数跳扩散模型,得到了条件违约风险率和信用违约互换的短期价格极限.这些结果比纯扩散模型假设更符合实际.     

Evaluation and default time for companies with uncertain cash flows

In this study, we propose a modelling framework for evaluating companies financed by random liabilities, such as insurance companies or commercial banks. In this approach, earnings and costs are driven by double exponential jump–diffusion processes and bankruptcy is declared when the income falls below a default threshold, which is proportional to the charges. A change of numeraire, under the Esscher risk neutral measure, is used to reduce the dimension. A closed form expression for the value of equity is obtained in terms of the expected present value operators, with and without disinvestment delay. In both cases, we determine the default threshold that maximizes the shareholder’s equity. Subsequently, the probabilities of default are obtained by inverting the Laplace transform of the bankruptcy time. In numerical applications of the proposed model, we apply a procedure for calibration based on market and accounting data to explain the behaviour of shares for two real-world examples of insurance companies.     

违约风险的交换期权的定价模型与解法

含交易对手违约风险的交换期权采用混合模型定价,借助公司价值模型中的补偿率,同时采用以强度为基础的违约函数来确定违约的发生.假定违约强度遵从均值回复的重随机Poisson过程：且违约强度过程与标的资产,企业价值都相关.利用等价鞅测度变换方法导出含有违约风险的交换期权的价格闭解.     

基于最优负债系数的上市银行违约概率测算模型与实证

当上市银行的长期负债系数γ的取值不同时,应用KMV模型测算出的银行违约概率大相径庭。根据债券的实际信用利差可以推算出上市银行的违约概率PDi,CS,根据长期负债系数γ可以运用KMV模型确定上市银行的理论违约概率PDi,KMV。本文通过理论违约率与实际违约率的总体差异∑ni=1|PDi,KMV-PDi,cs|最小的思路建立规划模型,确定了KMV模型的最优长期负债γ系数;通过最优长期负债系数γ建立了未发债上市银行的违约率测算模型、并实证测算了我国14家全部上市银行的违约概率。本文的创新与特色一是采用KMV模型计算的银行违约概率PDi,KMV与实际信用利差确定的银行违约概率PDi,CS总体差异∑ni=1|PDi,KMV-PDi,cs|最小的思路建立规划模型,确定了KMV模型中的最优长期负债γ系数;使γ系数的确定符合资本市场利差的实际状况,解决了现有研究中在0和1之间当采用不同的长期负债系数γ、其违约概率的计算结果截然不同的问题。二是实证研究表明,当长期负债系数γ=0.7654时,应用KMV模型测算出的我国上市银行违约概率与我国债券市场所接受的上市银行违约概率最为接近。三是实证研究表明国有上市银行违约概率最低,区域性的上市银行违约概率较高,其他上市银行的违约概率居中。     

Restructuring risk in credit default swaps: An empirical analysis

This paper estimates the price for restructuring risk in the US corporate bond market during 1999–2005. Comparing quotes from default swap (CDS) contracts with a restructuring event and without, we find that the average premium for restructuring risk represents 6%–8% of the swap rate without restructuring. We show that the restructuring premium depends on firm-specific balance-sheet and macroeconomic variables. And, when default swap rates without a restructuring event increase, the increase in restructuring premia is higher for low-credit-quality firms than for high-credit-quality firms. We propose a reduced-form arbitrage-free model for pricing default swaps that explicitly incorporates the distinction between restructuring and default events. A case study illustrating the model’s implementation is provided.     

基于信用利差与Logistic回归的公司违约概率测算模型与实证研究

用Logistic模型计算公司违约概率在实际应用中存在两个问题:一是在缺乏公司违约记录数据库或违约记录数据库不典型的情况下,无法应用该模型或模型计算结果不准确;二是现有Logistic违约概率模型忽视了不同行业财务指标分布特征的差异性,导致公司违约概率计算结果的准确性降低。针对问题一,本文通过公司债券信用利差计算市场隐含的公司违约概率,在Logistic变换的基础上进一步确定Logistic线性回归的参数,使得公司违约概率的计算结果符合债券市场的实际状况。针对问题二,通过不同行业关键财务指标的单因子方差分析,证实了行业间财务指标的分布特征具有显著性差异,通过拟合优度证实了区分行业建立Logistic违约概率模型可显著提高违约概率测算的准确性。本文Logistic违约概率模型的构建过程如下:通过初选财务指标的相关性分析,删除反映信息重复的财务指标;通过Logistic回归中财务指标系数的显著性检验,删除对违约概率解释能力弱的财务指标;以Logistic回归的拟合优度为标准,选取各样本行业Logistic违约概率模型的关键财务指标,建立了机械设备等5个样本行业的Logistic违约概率模型,为样本内行业公司违约概率的准确测算提供模型与方法。本文的创新与特色:一是在无套利条件下,通过公司债券信用利差计算市场隐含的公司违约概率,并对其进行Logistic变换,作为Logistic线性回归的被解释变量,解决了在缺乏公司违约记录数据情况下Logistic违约概率模型的参数估计问题;二是通过单因子方差分析方法,证实了行业间财务指标的分布特征具有显著性差异,说明应区分行业建立Logistic违约概率模型;三是通过财务指标间的相关分析删除反映信息重复的财务指标,通过财务指标系数的显著性检验删除对公司违约概率解释能力弱的财务指标,保证了Logistic违约概率模型中关键财务指标选取的合理性;四是实证研究结果表明,不同行业的Logistic违约概率模型的关键财务指标不同,同一财务指标的参数也存在显著差异。实证研究结果还表明,区分行业建立Logistic违约概率模型与不区分行业相比,前者可将拟合优度及调整后的拟合优度提高近1倍。本文研究结果对于提高公司违约概率测算的准确性具有重要参考意义,对于商业银行贷款定价、公司债券发行定价、银行信用风险管理具有重要参考意义。     

带有违约风险的可转换债券的简约型定价

本文考虑简约模型下带有违约风险的可转换债券的定价问题.假定市场中可转换债券的违约强度满足Vasicek模型,利用鞅方法获得了该模型下可转换债券的定价公式.此外,我们通过数值分析显示了模型参数变化对可转换债券价值影响的敏感性程度,结果也表明违约风险将降低可转换债券的价值.     

Analytical pricing of defaultable discrete coupon bonds in unified two-factor model of structural and reduced form models

Pricing formulae for defaultable corporate bonds with discrete coupons (under consideration of the government taxes) in the united two-factor model of structural and reduced form models are provided. The aim of this paper is to generalize the two-factor structural model for defaultable corporate discrete coupon bonds (considered in [1]) into the unified model of structural and reduced form models. In our model the bond holders receive the stochastic coupon (which is the discounted value of a predetermined value at the maturity) at predetermined coupon dates and the face value (debt) and the coupon at the maturity as well as the effect of government taxes which are paid on the proceeds of an investment in bonds is considered. The expected default event occurs when the equity value is not sufficient to pay coupon or debt at the coupon dates or maturity and the unexpected default event can occur at the first jump time of a Poisson process with the given default intensity provided by a step function of time variable. We provide the model and pricing formula for equity value and using it calculate expected default barrier. Then we provide pricing model and formula for defaultable corporate bonds with discrete coupons and consider its duration.     

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This paper establish a first passage time model based on the Merton's structural model by using the method of geometric Brownian motion. In this paper, we consider the accounting noise and historical default record and then introduce a new incomplete information hypothesis. Besides, we introduce the stock's liquidity value into the model, and apply its method measurement which based on Merton's structural model to the first passage time model to obtain the endogenous default boundary. Based on the incomplete information, the conditional default probability is derived by using the default boundary. And at the last of this passage, we analysis the effect of the correlation between stock's price and company assets on the default probability.     

Bayesian confidence intervals for probability of default and asset correlation of portfolio credit risk

We derive Bayesian confidence intervals for the probability of default (PD), asset correlation (Rho), and serial dependence (Theta) for low default portfolios (LDPs). The goal is to reduce the probability of underestimating credit risk in LDPs. We adopt a generalized method of moments with continuous updating to estimate prior distributions for PD and Rho from historical default data. The method is based on a Bayesian approach without expert opinions. A Markov chain Monte Carlo technique, namely, the Gibbs sampler, is also applied. The performance of the estimation results for LDPs validated by Monte Carlo simulations. Empirical studies on Standard & Poor’s historical default data are also conducted.     

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.