论文标题
Deep XVA求解器 - 基于神经网络的交易对手信用风险管理框架
Deep xVA solver -- A neural network based counterparty credit risk management framework
论文作者
论文摘要
在本文中，我们提出了用于投资组合范围的风险管理问题的新型计算框架，其中潜在的大量风险因素的存在使传统的数值技术无效。该新方法利用BSDE的耦合系统进行估值调整（XVA），并通过基于神经网络的BSDE求解器的递归应用来解决这些调整。这不仅使XVA计算可行的高维问题，而且还会产生XVA的对冲比率和动态风险度量，并允许对附带帐户进行模拟。
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.
