CVA sensitivities, hedging and risk
A probabilistic machine learning approach to CVA calculations is proposed
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Stéphane Crépey, Bouazza Saadeddine, Botao Li and Hoang Nguyen present a framework for computing credit valuation adjustment (CVA) sensitivities, hedging the CVA and assessing CVA risk, using probabilistic machine learning as a refined regression tool applied to simulated data, which can be validated by low-cost companion Monte Carlo procedures. They identify the sensitivities representing the best practical trade-offs in downstream tasks, including CVA hedging and
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