Counterparty Risk for Credit Default Swaps: Markov Chain Interacting Intensities Model with Stochastic Intensity

We analyze the counterparty risk for credit default swaps using the Markov chain model of portfolio credit risk of multiple obligors with interacting default intensity processes. The default correlation between the protection seller and underlying entity is modeled by an increment in default intensity upon the occurrence of an external shock event. The arrival of the shock event is a Cox process whose stochastic intensity is assumed to follow an affine diffusion process with jumps. We examine how the correlated default risks between the protection seller and the underlying entity may affect the credit default premium in a credit default swap.     

Counterparty risk and funding: immersion and beyond

In Crépey (Math. Finance 25:23–50, 2015), a basic reduced-form counterparty risk modelling approach was introduced under a standard immersion hypothesis between a reference filtration and the filtration progressively enlarged by the default times of the two parties. This basic setup, with a related continuity assumption on some of the data at the first default time of the two parties, is too restrictive for wrong-way and gap risk applications, such as counterparty risk on credit derivatives. This paper introduces an extension of the basic approach, implements it through marked default times and applies it to counterparty risk on credit derivatives.     

Counterparty Risk and the Pricing of Defaultable Securities

Motivated by recent financial crises in East Asia and the United States where the downfall of a small number of firms had an economy-wide impact, this paper generalizes existing reduced-form models to include default intensities dependent on the default of a counterparty. In this model, firms have correlated defaults due not only to an exposure to common risk factors, but also to firm-specific risks that are termed "counterparty risks." Numerical examples illustrate the effect of counterparty risk on the pricing of defaultable bonds and credit derivatives such as default swaps.     

Neglected Risk in Financial Innovation: Evidence from Structured Product Counterparty Exposure

We investigate the compensation of counterparty exposure in the prices of structured products. Our analysis reveals that product issuers did not compensate retail investors for counterparty exposure before the Lehman default. Post-Lehman, retail prices have no longer neglected this risk. We also measure retail investor attention towards issuer credit risk. For a given level of issuer credit risk, counterparty exposure is compensated more when attention is higher. Furthermore, issuers tend to construct products with larger counterparty exposure. Overall, our results shed light on the conditions under which financial engineering generates neglected risk.     

Credit Contagion from Counterparty Risk

Standard credit risk models cannot explain the observed clustering of default, sometimes described as "credit contagion." This paper provides the first empirical analysis of credit contagion via direct counterparty effects. We find that bankruptcy announcements cause negative abnormal equity returns and increases in CDS spreads for creditors. In addition, creditors with large exposures are more likely to suffer from financial distress later. This suggests that counterparty risk is a potential additional channel of credit contagion. Indeed, the fear of counterparty defaults among financial institutions explains the sudden worsening of the credit crisis after the Lehman bankruptcy in September 2008.     

Bilateral credit valuation adjustment for large credit derivatives portfolios

We obtain an explicit formula for the bilateral counterparty valuation adjustment of a credit default swaps portfolio referencing an asymptotically large number of entities. We perform the analysis under a doubly stochastic intensity framework, allowing default correlation through a common jump process. The key insight behind our approach is an explicit characterization of the portfolio exposure as the weak limit of measure-valued processes associated with survival indicators of portfolio names. We validate our theoretical predictions by means of a numerical analysis, showing that counterparty adjustments are highly sensitive to portfolio credit risk volatility as well as to the intensity of the common jump process.     

The use of credit default swaps by bond mutual funds: Liquidity provision and counterparty risk

Corporate bond mutual funds increased their selling of credit protection in the credit default swaps (CDS) market during the 2007–2008 financial crisis. This trading activity was primarily in multi-name CDS, greater among larger and established funds, and directed toward counterparty dealers in financial distress. Funds that sold credit protection during the crisis experienced greater credit market risk and superior post-crisis performance, consistent with higher expected returns from liquidity provision. Funds using Lehman Brothers as a counterparty experienced abnormal outflows and returns of –2% immediately following Lehman's bankruptcy, suggesting that funds’ opportunistic trading in CDS exposed investors to counterparty risk.     

Contagion models a la carte: which one to choose?

We propose a copula contagion mixture model for correlated default times. The model includes the well-known factor, copula, and contagion models as its special cases. The key advantage of such a model is that we can study the interaction of different models and their pricing impact. Specifically, we model the default times of the underlying names in a reference portfolio to follow contagion intensity processes with exponential decay coupled with a copula dependence structure. We also model the default time of the counterparty and its dependence structure with the reference portfolio. Numerical tests show that correlation and contagion have an enormous joint impact on the rates of CDO tranches and the corresponding credit value adjustments are extremely high to compensate for the wrong-way risk.     

Pricing of swaps with default risk

In this paper, I study the valuation of interest rate and currency swaps with default risk under the contingent claim analysis framework. I demonstrate that the traditional approach of pricing swap contracts as exchanges of loans underestimates the value of such contracts to the counterparty with higher credit rating and exaggerates the credit spread required to guard against default risk. Numerical simulations show that the swap rate is not sensitive to counterparty credit rating: for a ten year interest rate swap, a one hundred basis point increase in counterparty bond yield spread results in only about one basis point increase in the swap rate. (JEL G10, G12, G13)This paper is based on Chapter 2 of my Ph.D. dissertation at Yale University. I would like to thank my dissertation committee, Kenneth French, Roger Ibbotson, and Jonathan Ingersoll, Jr. (chairman), for helpful advice and guidance. I would also like to thank Keny Back, Richard Lindsey, N. R. Prabhala, Ming Huang, Marti Subrahmanyam, three anonymous referees and especially Bob Jarrow, the editor, for helpful comments and suggestions. Any errors that remain are solely mine. This paper won the 1996 Trefftzs Award for best student paper from the Western Finance Association.     

Credit risk modeling strategies: the road to serfdom?

This paper aims at presenting some practical issues in modeling default risk of a single commercial credit counterparty from the perspective of a large retail bank. We define default risk as the probability that a counterparty’s intrinsic credit quality deteriorates within a given time horizon such that contractual agreements cannot be honored. This work gives an insight into using scoring/rating models in a credit environment of a large European bank. Contrary to many banks, we did not define the segments in a first step with a view to developing the rating tools in a second step. Our approach has, to some extent, followed a different path. Iteratively, we both defined the borders for a particular segment and selected an appropriate rating tool. More particularly, customer segmentation has been carried out on the basis of various rating tools’ goodness-of-fit criteria. The topics cover customer segmentation using goodness-of-fit measures, data measurement levels and optimization algorithms, rating tool calibration to the central default tendency and communication to the end user. Copyright © 1999 John Wiley & Sons, Ltd.     

The Credit Risk and Pricing of OTC Options

In the over-the-counter (OTC) markets, the options traded are always subject to credit risk. Therefore the counterparty’s credit risk is a striking factor when pricing options, whereas it is not considered in the classic Black-Scholes models. Based on the first passage time models, this paper develops the credit risk and valuation model for the European options in the OTC markets, incorporating a practical default trigger mechanism. The default probability and the pricing formulae of the OTC options are obtained by using partial differential equation (PDE) techniques, especially Green’s function.     

A framework to measure integrated risk

A framework underlying various models that measure the credit risk of a portfolio is extended in this paper to allow the integration of credit risk with a range of market risks using Monte Carlo simulation. A structural model is proposed that allows interest rates to be stochastic and provides closed-form expressions for the market value of a firm's equity and its probability of default. This model is embedded within the integrated framework and the general approach illustrated by measuring the risk of a foreign exchange forward when there is a significant probability of default by the counterparty. For this example moving from a market risk calculation to an integrated risk calculation reduces the expected future value of the instrument by an amount that could not be calculated using the common pre-settlement exposure technique for estimating the credit risk of a derivative.     

Pricing counterparty default risks: Applications to FRNs and vulnerable options

This paper provides simple closed-form pricing models for floating-rate notes and vulnerable options under the counterparty risk framework of [Jarrow, R., Yu, F., 2001. Counterparty risk and the pricing of default risk. Journal of Finance 56, 1765-1799]. After deriving closed-form pricing models for them, this paper illustrates the impact of the default intensity of counterparty on the prices of floating-rate notes and vulnerable options. Numerical examples show that the default risk of counterparty is an important factor of the value of floating-rate notes and vulnerable options.     

The impact of central clearing on counterparty risk,liquidity, and trading: Evidence from the credit default swap market

This paper examines the impact of central clearing on the credit default swap (CDS) market using a sample of voluntarily cleared single-name contracts. Consistent with central clearing reducing counterparty risk, CDS spreads increase around the commencement of central clearing and are lower than settlement spreads published by the central clearinghouse. Furthermore, the relation between CDS spreads and dealer credit risk weakens after central clearing begins, suggesting a lowering of systemic risk. These findings are robust to controls for frictions in both CDS and bond markets. Finally, matched sample analysis reveals that the increased post-trade transparency following central clearing is associated with an improvement in liquidity and trading activity.     

Pricing Black-Scholes options with correlated credit risk

This paper presents an improved method of pricing vulnerable Black-Scholes options under assumptions which are appropriate in many business situations. An analytic pricing formula is derived which allows not only for correlation between the option's underlying asset and the credit risk of the counterparty, but also for the option writer to have other liabilities. Further, the proportion of nominal claims paid out in default is endogenous to the model and is based on the terminal value of the assets of the counterparty and the amount of other equally ranking claims. Numerical examples compare the results of this model with those of other pricing formulas based on alternative assumptions, and illustrate how the model can be calibrated using market data.     

Counterparty credit risk and the credit default swap market

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers' credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is priced in the CDS market. The magnitude of the effect, however, is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.     

Checking for asymmetric default dependence in a credit card portfolio: A copula approach

Traditional credit risk models adopt the linear correlation as a measure of dependence and assume that credit losses are normally-distributed. However some studies have shown that credit losses are seldom normal and the linear correlation does not give accurate assessment for asymmetric data. Therefore it is possible that many credit models tend to misestimate the probability of joint extreme defaults.This paper employs Copula Theory to model the dependence across default rates in a credit card portfolio of a large UK bank and to estimate the likelihood of joint high default rates. Ten copula families are used as candidates to represent the dependence structure. The empirical analysis shows that, when compared to traditional models, estimations based on asymmetric copulas usually yield results closer to the ratio of simultaneous extreme losses observed in the credit card portfolio.Copulas have been applied to evaluate the dependence among corporate debts but this research is the first paper to give evidence of the outperformance of copula estimations in portfolios of consumer loans. Moreover we test some families of copulas that are not typically considered in credit risk studies and find out that three of them are suitable for representing dependence across credit card defaults.     

Pricing CDS spreads with Credit Valuation Adjustment using a mixture copula

Credit derivatives pricing models before Basel III ignored losses in market value stemming from higher probability of counterparty default. We propose a general credit derivatives pricing model to evaluate a Credit Default Swap (CDS) with counterparty risk, including the Credit Valuation Adjustment (CVA) in order to optimize the economic capital allocation. We work from the model proposed by Luciano (2003, Working Paper, International Center of Economic Research) and the general pricing representation established by Sorensen and Bollier (Financial Analysts Journal 1994;50(3):23–33) to provide a model close to the market practice, easy to implement and fitting with Basel III framework. We approach the dependence between counterparty risk and that of the reference entity with a technical tool: the copula, in particular, the mixture one that combines common “extreme” copulas. We study the CDS's vulnerability in extreme dependence cases. By varying Spearman's rho, the mixture copula covers a broad spectrum of dependence and ensures closed form prices. We end up with an application on real market data.     

A first-passage-time model under regime-switching market environment

In this paper, we suggest a first-passage-time model which can explain default probability and default correlation dynamics under stochastic market environment. We add a Markov regime-switching market condition to the first-passage-time model of Zhou [Zhou, C., 2001. An analysis of default correlations and multiple defaults. Review of Financial Studies 14, 555–576]. Using this model, we try to explain various relationship between default probability, default correlation, and market condition. We also suggest a valuation method for credit default swap (CDS) with (or without) counterparty default risk (CDR) and basket default swap under this model.Our numerical results provide us with several meaningful implications. First, default swap spread is higher in economic recession than in economic expansion across default swap maturity. Second, as the difference of asset return volatility between under bear market and under bull market increases, CDS spread increases regardless of maturity. Third, the bigger the intensity shifting from bull market to bear market, the higher the spread for both CDS without CDR and basket default swap.     

中小企业集合债券总体信用风险度量研究

中小企业集合债券总体信用风险既包括系统风险产生的周期性违约风险,又包括相互关联关系导致的传染性违约风险。首先通过对因素模型的改进构建模型Ⅰ,研究集合债券的周期性违约风险;在此基础上引入违约传染建立模型Ⅱ,分析违约传染对违约概率及违约相关性的影响,研究集合债券的总体信用风险。最后基于模型Ⅱ进行算例研究,得出结论：企业间的相互关联关系降低了其1次违约概率,增加了其多次违约概率即违约相关性。