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An Explicit Scheme for Pathwise XVA Computations

Risk Management 2024-01-25 v1 Numerical Analysis Numerical Analysis Computational Finance Machine Learning

Abstract

Motivated by the equations of cross valuation adjustments (XVAs) in the realistic case where capital is deemed fungible as a source of funding for variation margin, we introduce a simulation/regression scheme for a class of anticipated BSDEs, where the coefficient entails a conditional expected shortfall of the martingale part of the solution. The scheme is explicit in time and uses neural network least-squares and quantile regressions for the embedded conditional expectations and expected shortfall computations. An a posteriori Monte Carlo validation procedure allows assessing the regression error of the scheme at each time step. The superiority of this scheme with respect to Picard iterations is illustrated in a high-dimensional and hybrid market/default risks XVA use-case.

Keywords

Cite

@article{arxiv.2401.13314,
  title  = {An Explicit Scheme for Pathwise XVA Computations},
  author = {Lokman Abbas-Turki and Stéphane Crépey and Botao Li and Bouazza Saadeddine},
  journal= {arXiv preprint arXiv:2401.13314},
  year   = {2024}
}
R2 v1 2026-06-28T14:25:36.797Z