Efficient Computation of Exposure Profiles for Counterparty Credit Risk

Graaf, Cornelis S. L. de; Feng, Qibo; Kandhai, Drona; Oosterlee, Cornelis W.

doi:10.2139/ssrn.2395183

Cited by 12 publications

(15 citation statements)

References 11 publications

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“…The valuation of the CCYS is performed by combining Monte Carlo (MC) simulations with analytical pricing. As there is no general analytic price for American or Barrier options under the H2HW dynamics, we apply the Finite Difference Monte Carlo (FDMC) method as described in de Graaf et al (2014). The pseudo-code for the algorithm is as follows:…”

Section: Algorithmmentioning

confidence: 99%

Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk

Simaitis

Graaf

Hari

et al. 2016

Quantitative Finance

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In this research, we investigate the impact of stochastic volatility and interest rates on counterparty credit risk (CCR) for FX derivatives. To achieve this we analyse two real-life cases in which the market conditions are different, namely during the 2008 credit crisis where risks are high and a period after the crisis in 2014, where volatility levels are low. The Heston model is extended by adding two Hull-White components which are calibrated to fit the EURUSD volatility surfaces. We then present future exposure profiles and credit value adjustments (CVAs) for plain vanilla cross-currency swaps (CCYS), barrier and American options and compare the different results when Heston-Hull-WhiteHull-White or Black-Scholes dynamics are assumed. It is observed that the stochastic volatility has a significant impact on all the derivatives. For CCYS, some of the impact can be reduced by allowing for time-dependent variance. We further confirmed that Barrier options exposure and CVA is highly sensitive to volatility dynamics and that American options' risk dynamics are significantly affected by the uncertainty in the interest rates.

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Section: Algorithmmentioning

confidence: 99%

Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk

Simaitis

Graaf

Hari

et al. 2016

Quantitative Finance

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“…This paper extends the FDMC method described in de Graaf et al (2014) and is based on combining the Monte Carlo scenario generation with option valuation by solving a PDE on a grid. For every scenario at every time point, the option prices are obtained by interpolating the scenarios on this option grid.…”

Section: Resultsmentioning

confidence: 99%

“…As presented in de Graaf et al (2014), the FDMC method uses the scenario generation of the Monte Carlo method and the pricing approach of the finite difference method. The market states are simulated by the quadratic exponential (QE) scheme (Andersen 2008).…”

Section: The Fdmc Methodsmentioning

confidence: 99%

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Efficient Estimation of Sensitivities for Counterparty Credit Risk with the Finite Difference Monte-Carlo Method

2014

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According to Basel III, financial institutions have to charge a credit valuation adjustment (CVA) to account for a possible counterparty default. Calculating this measure and its sensitivities is one of the biggest challenges in risk management. Here, we introduce an efficient method for the estimation of CVA and its sensitivities for a portfolio of financial derivatives. We use the finite difference Monte Carlo (FDMC) method to measure exposure profiles and consider the computationally challenging case of foreign exchange barrier options in the context of the Black-Scholes as well as the Heston stochastic volatility model, with and without stochastic domestic interest rate, for a wide range of parameters. In the case of a fixed domestic interest rate, our results show that FDMC is an accurate method compared with the semi-analytic COS method and, advantageously, can compute multiple options on one grid. In the more general case of a stochastic domestic interest rate, we show that we can accurately compute exposures of discontinuous one-touch options by using a linear interpolation

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“…Feng and Oosterlee (2012) [4] studied the exposure profile of European, Bermudan and barrier options under the Heston and Heston HullWhite model. Graaf et al (2014) [5] presented various techniques to approximate exposure for early exercise option within Black-Scholes and Heston framework. Graaf et al (2014) [6] explored the exposure profiles and CVA sensitivities for Barrier option in the context of Black-Scholes and Heston model.…”

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confidence: 99%

CVA under Bates Model with Stochastic Default Intensity

Feng¹

2017

JMF

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Counterparty credit risk has received increasing attention and become a topical issue since 2007 credit crisis, particularly for its impact on the valuation of the OTC derivatives. Credit Value Adjustment (CVA) has become an import field and it is required in Basel III. This paper studies CVA for European options under Bates model with stochastic default intensity. We develop a Monte Carlo and finite difference method framework for assessing exposure profiles and impact of counterparty credit risk in pricing. The exposures are computed by solving a partial integro-differential Equation (PIDE) using implicit-explicit (IMEX) time discretization schemes. CVA in presence of wrong way risk (WWR) is embedded in the correlation between risk factor and default intensity. Meanwhile, the jump-at-default feature of the models offers an effective means to assess WWR. Our results show that both jump and WWR play an important role in evaluating CVA and exposures. The impact is significant and it is crucial for risk management purpose.

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Efficient Computation of Exposure Profiles for Counterparty Credit Risk

Cited by 12 publications

References 11 publications

Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk

Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk

Efficient Estimation of Sensitivities for Counterparty Credit Risk with the Finite Difference Monte-Carlo Method

CVA under Bates Model with Stochastic Default Intensity

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