Deep xVA solver -- A neural network based counterparty credit risk management framework

Alessandro Gnoatto, Athena Picarelli and Christoph Reisinger

Papers from arXiv.org

Abstract: In this paper, we present a novel computational framework for portfolio-wide risk management problems, where the presence of a potentially large number of risk factors makes traditional numerical techniques ineffective. The new method utilises a coupled system of BSDEs for the valuation adjustments (xVA) and solves these by a recursive application of a neural network based BSDE solver. This not only makes the computation of xVA for high-dimensional problems feasible, but also produces hedge ratios and dynamic risk measures for xVA, and allows simulations of the collateral account.

Date: 2020-05, Revised 2022-12
New Economics Papers: this item is included in nep-big, nep-cmp, nep-gen and nep-rmg
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