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

22 Pages Posted:

See all articles by Alessandro Gnoatto

Alessandro Gnoatto

University of Verona - Department of Economics

Christoph Reisinger

University of Oxford - Oxford-Man Institute of Quantitative Finance

Athena Picarelli

University of Verona - Department of Economics

Date Written: May 6, 2020

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.

Keywords: CVA, DVA, FVA, ColVA, xVA, EPE, Collateral, xVA hedging, Deep BSDE Solver

JEL Classification: G12, G13, C63

Suggested Citation

Gnoatto, Alessandro and Reisinger, Christoph and Picarelli, Athena, Deep xVA solver - A neural network based counterparty credit risk management framework (May 6, 2020). Available at SSRN: https://ssrn.com/abstract=

Alessandro Gnoatto (Contact Author)

University of Verona - Department of Economics ( email )

Via dell'Artigliere, 8
37129 Verona
Italy

Christoph Reisinger

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Athena Picarelli

University of Verona - Department of Economics ( email )

Via dell'Artigliere, 8
37129 Verona
Italy

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
1
Abstract Views
8
PlumX Metrics