This paper investigates calculations of robust CVA for OTC derivatives under distributional uncertainty using Wasserstein distance as the ambiguity measure. Wrong way counterparty credit risk  can be characterized (and indeed quantified) via the robust CVA formulation . The simpler dual formulation of the robust CVA optimization is derived . Next, some computational experiments are conducted to measure the additional CVA charge due to distributional uncertainty under a variety of portfolio and market configurations. Finally some suggestions for future work , such as robust FVA, are discussed.
This paper investigates calculations of robust XVA, in particular, credit valuation adjustment (CVA) and funding valuation adjustment (FVA) for over-the-counter derivatives under distributional uncertainty using Wasserstein distance as the ambiguity measure. Wrong way counterparty credit risk and funding risk can be characterized (and indeed quantified) via the robust XVA formulations . The simpler dual formulations are derived using recent infinite dimensional Lagrangian duality results . Next, some computational experiments are conducted to measure the additional XVA charges due to distributional uncertainty under a variety of portfolio and market configurations. Finally some suggestions for future work are discussed.
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CVA for OTC
XVA, in particular, credit valuation adjustment (CVA) and funding valuation adjustment (FVA) for over-the-counter
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and funding risk
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CVA formulation
XVA formulations
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formulation of the robust CVA optimization is derived
formulations are derived using recent infinite dimensional Lagrangian duality results
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CVA charge
XVA charges
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, such as robust FVA,