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arxiv: 2407.18583 · v1 · pith:AODFVFN4new · submitted 2024-07-26 · 💱 q-fin.CP

CVA Sensitivities, Hedging and Risk

St\'ephane Cr\'epey (UFR Math\'ematiques UPCit\'e) , Botao Li (LPSM (UMR\_8001)) , Hoang Nguyen (IES , LPSM (UMR\_8001)) , Bouazza Saadeddine This is my paper
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keywords sensitivitieshedgingriskassessingassessmentbenchmarkedbestcarlo
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We present a unified framework for computing CVA sensitivities, hedging the CVA, and assessing CVA risk, using probabilistic machine learning meant as refined regression tools on simulated data, validatable by low-cost companion Monte Carlo procedures. Various notions of sensitivities are introduced and benchmarked numerically. We identify the sensitivities representing the best practical trade-offs in downstream tasks including CVA hedging and risk assessment.

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    Develops basis-expansion reductions for stochastic hedge ratios with residual-minimization and projected-moment (Galerkin/Petrov-Galerkin) coefficient criteria to accelerate pathwise sensitivity-to-hedge conversion in...