Fast correlation Greeks by adjoint algorithmic differentiation
Adjoint methods have recently been proposed as an efficient way to calculate risk through Monte Carlo simulation. Luca Capriotti and Mike Giles extend these ideas and show how adjoint algorithmic differentiation allows for fast calculation of price sensitivities in full generality. They illustrate the method for the calculation of correlation risk and test it numerically for portfolio default options
One of the consequences of the recent crisis of the financial markets is a renewed emphasis on rigorous risk management practices. To quantify the financial exposure of financial firms, and to ensure efficient capital allocation and more effective hedging practices, regulators and senior management alike are insisting more and more on a thorough monitoring of risk. Among all businesses, those dealing with complex, over-the-counter derivatives are the ones receiving the most attention.
PLEASE
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-digital.com/terms-and-conditions/subscriptions/
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-digital.com/terms-and-conditions/subscriptions/
If you would like to purchase additional rights please email info@risk.net
More on Risk management
Op risk data: UBS takes a giant Greensill pill
Also: Nasdaq insider trading rap; Trafigura travesty; further Citi fat-finger fail. Data by ORX News
Can Citi’s XVA desk help solve risk data failings?
Resolution plan reviews exposed material limitations in banks’ ability to unwind derivatives
Ace high or busted flush? Digital Asset and the big bet on DLT
Blockchain pioneer’s bumpy journey raises questions over future of distributed ledger technology in finance
Bridging the gap risk reloaded: modelling wrong-way risk and leverage
A model extends the counterparty risk calculation to include nonlinear and complex portfolios
Ice postpones migration to VAR in bid to improve offsets
Clearing house will move on freight products before energy, as users fret over margin spikes
How a ‘sushi circle’ approach can improve credit risk management
AI can help banks shift from manual corporate loan reviews to continuous, digitised risk monitoring
AI could cut time for money laundering checks by 99%
Leading crypto exchange rolling out large language model for enhanced due diligence checks
Counterparty risk model links defaults to portfolio values
Fed’s Michael Pykhtin proposes using copula models to capture effects of margin calls on default risk