On the Hull-White model with volatility smile for Valuation Adjustments
针对现有估值调整模型无法捕捉市场隐含偏斜和微笑的问题，提出一种结合多个Hull-White动力学的随机微分方程模型，实现半解析校准并展示其对利率衍生品敞口和估值调整的显著影响。
Affine Diffusion (AD) dynamics are frequently used for Valuation Adjustments (xVA) calculations due to their analytic tractability. However, these models cannot capture the market-implied skew and smile, which are relevant when computing xVA metrics. Hence, additional degrees of freedom are required to capture these market features. In this paper, we address this through an SDE with state-dependent coefficients. The SDE is consistent with the convex combination of a finite number of different AD dynamics. We combine Hull-White one-factor models where one model parameter is varied. We use the Randomized AD (RAnD) technique to parameterize the combination of dynamics. We refer to our SDE with state-dependent coefficients and the RAnD parametrization of the original models as the rHW model. The rHW model allows for efficient semi-analytic calibration to European swaptions through the analytic tractability of the Hull-White dynamics. We use a regression-based Monte-Carlo simulation to calculate exposures. In this setting, we demonstrate the significant effect of skew and smile on (potential future) exposures and xVAs of linear and early-exercise interest rate derivatives.