基于t-Copula的一篮子信用违约互换定价模型

为了刻画分布函数的厚尾特征和违约的传染性,构建了单因子t-Copula模型,以此研究一篮子信用违约互换(BDS)的定价问题。依据风险中性定价原理和顺序统计量方法,分别得到了第k次违约和n个参照实体中m个受保护的BDS价格的解析式.为了说明定价模型的有效性,用随机模拟方法分析了相应的数值算例.     

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.     

信用违约互换的定价方法

通过对信用违约互换的结构的分析,在Merton的结构化方法框架下,用偏微分方程求出公司的违约概率密度,最后给出信用违约互换的一种定价方法.     

约化模型中含有对手风险的信用违约互换定价

在约化模型中研究了含有对手风险的信用违约互换的定价问题.通过构建信用违约互换买方、卖方和参考资产之间的衰减传染结构,借助于测度变换的方法分别导出了含有单边和双边对手风险的信用违约的定价表达式.     

基于正态逆高斯分布的篮子违约互换定价

主要讨论单因子模型的篮子型信用违约互换定价.目的是寻找一个快捷的方法来处理违约相关问题.采用了正态逆高斯分布对违约时间进行建模,得到了违约时间分布和篮子违约互换定价公式的半分析表达式,进一步地讨论了常数因子荷载扩展到随机因子荷载的情形.最后用数值模拟方法对比了正态分布和正态逆高斯分布两种模型下首次违约互换的价格.     

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本文讨论了信用衍生产品之一的总收益互换的定价问题. 其中涉及到利率风险和违约风险, 本文利用HJM利率模型来刻画利率风险, 并利用强度模型和混合模型对违约风险进行建模. 分别考虑了违约时间与利率无关时总收益互换合约的定价问题, 以及违约时间与利率相关时总收益互换合约的定价问题, 给出了相应的定价模型, 并用蒙特卡罗模拟方法得到定价问题的数值解.     

抵押贷款信用违约互换的定价

在结构化方法框架下,用偏微分方程方法,对抵押贷款的信用违约互换进行定价.给出了形式解,并进行数值计算和参数分析.     

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.     

具有违约观察期公司债券的定价

借助于美国破产保护法第十一章,违约公司获得-个额外的违约观察期过程,通过纳什均衡原理对股东和债权人的利益进行重新分配,利用巴黎型期权的定价思想来刻画具有这种违约观察期过程的股票与公司债券的定价模型,并从股东权益最大化,把股票的定价模型归结为-个自由边界问题,进而通过偏微分方程方法(PDE)推出股票与公司偾券价格的闭合表达式和最佳违约边界解的显式表达式;同时文章还对公司的最优杠杆,清算概率和信用利差进行讨论.     

Empirical analysis of structural change in Credit Default Swap volatility

The purpose of this paper is to study the structural change in Credit Default Swap volatility. We use statistical properties and a network approach to better understand the behavior of CDS volatility. We hypothesize that structural change occurs in CDS index during a financial crisis and it requires subperiod analysis, rather than full period analysis, to investigate properly. Our results show that the probability of large volatility is related to the structure of volatility but it is more significantly related to the size of volatility. Both the memory property and the size of volatility are confirmed to have dependence on the structure of volatility. The linked degree of CDS volatilities is highly related to the probability of large volatility and its predictability, regardless of structural change in volatility. Another interesting result is that the CDS volatility of a country is more related to the behavior of other volatilities, not the geographical location.     

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.     

Credit default swaps and systemic risk

We present a network model for investigating the impact on systemic risk of central clearing of over the counter (OTC) credit default swaps (CDS). We model contingent cash flows resulting from CDS and other OTC derivatives by a multi-layered network with a core-periphery structure, which is flexible enough to reproduce the gross and net exposures as well as the heterogeneity of market shares of participating institutions. We analyze illiquidity cascades resulting from liquidity shocks and show that the contagion of illiquidity takes place along a sub-network constituted by links identified as ’critical receivables’. A key role is played by the long intermediation chains inherent to the structure of the OTC network, which may turn into chains of critical receivables. We calibrate our model to data representing net and gross OTC exposures of large dealer banks and use this model to investigate the impact of central clearing on network stability. We find that, when interest rate swaps are cleared, central clearing of credit default swaps through a well-capitalized CCP can reduce the probability and the magnitude of a systemic illiquidity spiral by reducing the length of the chains of critical receivables within the financial network. These benefits are reduced, however, if some large intermediaries are not included as clearing members.     

Can CDS indexes signal future turmoils in the stock market? A Markov switching perspective

Single-name Credit Default Swaps (CDS) are considered the main providers of direct information related with a reference entity’s creditworthiness and, for this reason, they have often been the core of news on the current financial crisis. The academic research has focused mainly on the capacity of CDS in anticipating agencies’ official rating changes and—in this respect—on their superior signalling power, compared to bond and stock markets. The aim of this work is, instead, to investigate the ability of fluctuations in CDS indexes in anticipating the occurrence of stock market crises. Our goal is to show that CDS indexes may provide investors and institutions with early warning signals of financial distresses in the stock market. We make use of a Markov switching model with states characterized by increasing levels of volatility and compare the times in which the first switch in a high volatility state occurs, respectively, in CDS and stock market index quotes. The data set consists of daily closing quotes for 5 years CDS and stock market index prices, covering the time period from 2004 to 2010. In order to capture possible geographic differences in CDS index capacity of foreseeing stock market distresses, data referring to two different regions, Europe and United States, are analyzed.     

Bayesian corporate bond pricing and credit default swap premium models for deriving default probabilities and recovery rates

This paper develops a Bayesian method by jointly formulating a corporate bond (CB) pricing model and credit default swap (CDS) premium pricing models to estimate the term structure of default probabilities and the recovery rate. These parameters are formulated by incorporating firm characteristics such as industry, credit rating and Balance Sheet/Profit and Loss information. A cross-sectional model valuing all given CB prices and CDS premiums is considered. The quantities derived are regarded as what market participants infer in forming CB prices and CDS premiums. We also develop a statistical significance test procedure without any distributional assumptions for the specified model. An empirical analysis is conducted using Japanese CB and CDS market data.     

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.     

A time series model of CDS sequences in complete genome

A time series model of CDS sequences in complete genome is proposed. A map of DNA sequence to integer sequence is given. The correlation dimensions and Hurst exponents of CDS sequences in complete genome of bacteria are calculated. Using the average of correlation dimensions, some interesting results are obtained.     

Routing-efficient CDS construction in Disk-Containment Graphs

In wireless networks, Connected Dominating Sets (CDSs) are widely used as virtual backbones for communications. On one hand, reducing the backbone size will reduce the maintenance overhead. So how to minimize the CDS size is a critical issue. On the other hand, when evaluating the performance of a wireless network, the hop distance between two communication nodes, which reflect the energy consumption and response delay, is of great importance. Hence how to minimize the routing cost is also a key problem for constructing the network virtual backbone. In this paper, we study the problem of constructing applicable CDS in wireless networks in terms of size and routing cost. We formulate a wireless network as a Disk-Containment Graph (DCG), which is a generalization of the Unit-Disk Graph (UDG), and we develop an efficient algorithm to construct CDS in such kind of graphs. The algorithm contains two parts and is flexible to balance the performance between the two metrics. We also analyze the algorithm theoretically. It is shown that our algorithm has provable performance in minimizing the CDS size and reducing the communication distance for routing.     

Verification and validation of numerical solutions of two-dimensional reactive flow in rocket engine nozzles

Two-dimensional mathematical models for gaseous H₂/O₂ reactive flows are solved for two geometries: a conical and a parabolic one. Five different physical models are studied: two one-species and three multi-species models (frozen, equilibrium and non-equilibrium flows). In the mathematical model, temperature is used as unknown in the energy equation and velocity is obtained for all speed flows. For all analyses, a non-orthogonal finite volume code was implemented, taking into account first (UDS) and second (CDS) order interpolation schemes and co-located grid arrangement. Model predictions of the pressure distribution and Mach number in the nozzle with a conical geometry, calculated using a CDS scheme, were found to agree well with experimental results. For both geometries, numerical results for apparent orders of convergence agreed well with the asymptotic (expected) ones for one-species flows. Some other analyses were provided for mixture of gases flows; in this case, for frozen flow, the apparent order values tend to the asymptotic ones in all cases; for local equilibrium flow, the use of CDS degenerated the apparent order to unity; this fact can be associated to the use of UDS interpolation scheme in the source term of the energy equation. Numerical solutions, including their error estimates, are provided for UDS and CDS schemes. Their analysis shows that global variables of interest (such as thrust and specific impulse) are less affected by the chosen physical model than are local variables of interest (such as the temperature at the symmetry line).     

CDS volatility: the key signal of credit quality

This paper investigates the role of CDS volatility in providing information concerning the credit quality of a company. In Castellano and D’Ecclesia (J. Financ. Decis. Mak. 2:27, 2011) a first analysis of how CDS quotes respond to rating announcements is provided and it showed that market participants do not rely much on Rating Agencies, especially during periods characterized by very high volatility, i.e. during a financial crisis. Here, a more accurate analysis of the CDS’s ability to provide timely information on the creditworthiness of reference entities is performed, estimating the volatility of CDS quotes by using Exponential GARCH(1,1) models. The event study methodology is applied to a sample of CDS quotes for US and European markets, over the period 2004–2009. Results provide an accurate understanding of market behavior in the presence of news released by Rating Agencies. Overall, market participants seem to provide timely reactions around the event date and we show that the key element of signaling is represented by the changing volatility in CDS quotes, before and after the rating event.