Risk Optimisation: Finding the Signal in the Noise

10 Pages Posted: 26 May 2016 Last revised: 28 May 2016

See all articles by Benedict Burnett

Benedict Burnett

Barclays Investment Bank

Simon C O'Callaghan

Barclays Investment Bank

Tom Hulme

Barclays Investment Bank

Date Written: May 26, 2016

Abstract

We introduce a new method of optimising the accuracy and time taken to calculate risk for a complex trading book, focusing on the use case of XVA. We dynamically choose the number of paths and time discretisation to target computational effort on calculations that give the most information in explaining the PnL of the book. The approach is applicable to both fast, accurate intraday pricing calculations as well as large batch runs. The results are demonstrated by application to a large XVA book, which demonstrates speed-ups comparable to those available via adjoint algorithmic differentiation, for a fraction of the implementation cost.

Keywords: XVA, AAD, CVA, FVA, KVA, Monte Carlo Simulations, Optimisation, Entropy

JEL Classification: C15, C61, C63, G13

Suggested Citation

Burnett, Benedict and O'Callaghan, Simon C and Hulme, Tom, Risk Optimisation: Finding the Signal in the Noise (May 26, 2016). Available at SSRN: https://ssrn.com/abstract=2784702 or http://dx.doi.org/10.2139/ssrn.2784702

Benedict Burnett (Contact Author)

Barclays Investment Bank ( email )

5 The North Colonnade
London, Canary Wharf E14 4BB
United Kingdom

Simon C O'Callaghan

Barclays Investment Bank ( email )

5 North Colonnade
London, E14 4BB
United Kingdom

Tom Hulme

Barclays Investment Bank ( email )

5 The North Colonnade
London, E14 4BB
United Kingdom

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