Deep xVA solver -- a neural network based counterparty credit risk management framework
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 utilizes a coupled system of BSDEs for the valuation adjustments...
| Huvudupphovsmän: | , , |
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| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
Society for Industrial and Applied Mathematics
2023
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| Sammanfattning: | 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 utilizes 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. |
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