Integrated Structural Approach to Counterparty Credit Risk with Dependent Jumps

Ballotta, Laura; Fusai, Gianluca; Marazzina, Daniele

doi:10.2139/ssrn.2706416

Cited by 4 publications

(4 citation statements)

References 47 publications

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“…In the sequel we restrict ourselves to stochastic intensity models, which is the most popular dynamic setup for CVA purposes (see for instance [14], [16], [23], [26]). 2 This first class of models is mathematically sound in the sense that it can be arbitrage-free if handled properly. However, as pointed in [26], dealing with this additional stochastic process may be computationally intensive.…”

Section: Two Approaches For One Problemmentioning

confidence: 99%

“…This method is very popular in credit risk in general, except for pricing purposes as it is know to underestimate short-term default (see e.g. [2,14,15] and references therein for CVA pricing methods using structural credit models). The second dynamic setup (reduced-form model ) consists in modeling the default likelihood via a stochastic intensity process.…”

Section: Two Approaches For One Problemmentioning

confidence: 99%

“…is the EPE under WWR : it is the deterministic profile to be integrated with respect to the survival probability curve G to get the CVA (up to the constant 1 − R) including WWR, just like the EPE in the no-WWR case eq (2). Moreover, from the calibration equation ( 3),…”

Section: Cva In the Cox Process Setupmentioning

confidence: 99%

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Disentangling Wrong-Way Risk: Pricing CVA via Change of Measures and Drift Adjustment

Brigo

Vrins²

2016

SSRN Journal

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A key driver of Credit Value Adjustment (CVA) is the possible dependency between exposure and counterparty credit risk, known as Wrong-Way Risk (WWR). At this time, addressing WWR in a both sound and tractable way remains challenging: arbitrage-free setups have been proposed by academic research through dynamic models but are computationally intensive and hard to use in practice. Tractable alternatives based on resampling techniques have been proposed by the industry, but they lack mathematical foundations. This probably explains why WWR is not explicitly handled in the Basel III regulatory framework in spite of its acknowledged importance. The purpose of this paper is to propose a new method consisting of an appealing compromise: we start from a stochastic intensity approach and end up with a pricing problem where WWR does not enter the picture explicitly. This result is achieved thanks to a set of changes of measure: the WWR effect is now embedded in the drift of the exposure, and this adjustment can be approximated by a deterministic function without affecting the level of accuracy typically required for CVA figures. The performances of our approach are illustrated through an extensive comparison of Expected Positive Exposure (EPE) profiles and CVA figures produced either by (i) the standard method relying on a full bivariate Monte Carlo framework and (ii) our drift-adjustment approximation. Given the uncertainty inherent to CVA, the proposed method is believed to provide a promising way to handle WWR in a sound and tractable way.

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Section: Two Approaches For One Problemmentioning

confidence: 99%

Section: Two Approaches For One Problemmentioning

confidence: 99%

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Disentangling Wrong-Way Risk: Pricing CVA via Change of Measures and Drift Adjustment

Brigo

Vrins²

2016

SSRN Journal

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“…For instance, Feldhütter and Lando [26] proposed a model with six independent factors to calibrate Treasury bonds, corporate bonds, and swap rates using both cross-sectional and time-series properties of the observed yields. This independence assumption may be restrictive (see [27]), although the advantage is that pricing formulas have explicit solutions, and the model is more parsimonious with fewer FIGURE 3 | Calibration of the 2-factor default intensity process δ t on the Italy bond yields from January 02, 2008 to December 31, 2014. We report the observed spreads between bond and risk-free rates and the estimated ones for all maturities investigated.…”

Section: A Multi-factor Reduced-form Modelmentioning

confidence: 99%

Disentangling the Information Content of Government Bonds and Credit Default Swaps: An Empirical Analysis on Sovereigns and Banks

Bianchi

Rocco

2016

Front. Appl. Math. Stat.

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We propose a multi-factor Gaussian model to analyze the dynamics of sovereign bond yields, as well as sovereign and banks CDS quotes. This paper has three objectives (all of them with relevant implications from a supervisory perspective): (1) disentangling the credit risk component of sovereign bonds from the interest rate component; (2) exploring the sovereign CDS-bond basis, i.e., the difference between sovereign CDS quotes and the corresponding bond yields; (3) inferring from CDS quotes the idiosyncratic component of a bank credit risk and analyzing its relation with sovereign risk. We cast the model in a state-space form with linear measurement function. To calibrate the model we consider a maximum likelihood estimation together with a Kalman filter method in which both the gradient vector and the Hessian matrix to be used in the optimization can be computed in closed form.

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Evaluation of counterparty risk for derivatives with early-exercise features

Breton

Marzouk²

2018

Journal of Economic Dynamics and Control

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Integrated Structural Approach to Counterparty Credit Risk with Dependent Jumps

Cited by 4 publications

References 47 publications

Disentangling Wrong-Way Risk: Pricing CVA via Change of Measures and Drift Adjustment

Disentangling Wrong-Way Risk: Pricing CVA via Change of Measures and Drift Adjustment

Disentangling the Information Content of Government Bonds and Credit Default Swaps: An Empirical Analysis on Sovereigns and Banks

Evaluation of counterparty risk for derivatives with early-exercise features

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