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

According to Basel III, financial institutions need to charge a Credit Valuation Adjustment (CVA) to account for counterparty default risk. This adjustment is typically driven by a large number of uncertain risk factors, which makes efficient computation of CVA and the corresponding risk measures a complex mathematical and numerical modelling problem. In “Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk” (S. Simaitis 2016), published in Quantitative Finance, Kees de Graaf et al., applied this method to study the complex multi-dimensional problem of the role of fat-tailed distributions of underlying correlated risk factors on default risk. Their studies confirmed that deviations from normality of asset prices significantly impacts exposure dynamics. In particular, for more complex path-dependent derivatives, the risk measures become highly model-dependent. Citation info: S. Simaitis, C.S.L. de Graaf, B.D. Kandhai and N. Hari. 2016. “Smile and default: the role of stochastic volatility and interest rates in counterparty credit risk.” Quantitative Finance...

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

According to Basel III, financial institutions need to charge a Credit Valuation Adjustment (CVA) to account for counterparty default risk. This adjustment is typically driven by a large number of uncertain risk factors, which makes efficient computation of CVA and the corresponding risk measures a complex mathematical and numerical modelling problem. In “Efficient Estimation of Sensitivities for Counterparty Credit Risk with the Finite Difference Monte-Carlo Method” (C.S.L. de Graaf 2016), published in the Journal of Computational Finance, Kees de Graaf, Drona Kandhai and Peter Sloot, introduced a novel and efficient numerical method for the estimation of CVA and its risk measures.  For a wide range of benchmark cases, it is shown that the numerical estimates are highly accurate. Citation info: C.S.L. de Graaf, B.D. Kandhai and P.M.A. Sloot. 2016. “Efficient estimation of sensitivities for counterparty credit risk with the finite difference Monte Carlo method.” Journal of Computational Finance...

Towards the virtual artery: a multiscale model for vascular physiology at the physics–chemistry–biology interface

This discussion paper introduces the concept of the Virtual Artery as a multiscale model for arterial physiology and pathologies at the physics–chemistry–biology (PCB) interface. The cellular level is identified as the mesoscopic level, and we argue that by coupling cell-based models with other relevant models on the macro- and microscale, a versatile model of arterial health and disease can be composed. This  concept of models at the PCB interface could or perhaps should become a powerful paradigm, not only as in our case for studying physiology, but also for many other systems that have such PCB interfaces. DOI:...

Scaling of shear-induced diffusion and clustering in a blood-like suspension

Lampros Mountrakis et. al published a paper in Europhysics Letters where they demonstrate that shear-induced diffusion of red blood cells (in a two-dimensional model system) does not follow the established linear scaling with shear rate for high hematocrits. They hypothesise that collective effects in the suspension are key to understand this phenomenon, and by performing cluster analyses they show the significance of cluster effects on the dynamics of the RBCs.  ...