Skip to main content

CVA sensitivities, hedging and risk

A probabilistic machine learning approach to CVA calculations is proposed

 CLICK HERE TO DOWNLOAD PDF

Stéphane Crépey, Bouazza Saadeddine, Botao Li and Hoang Nguyen present a framework for computing credit valuation adjustment (CVA) sensitivities, hedging the CVA and assessing CVA risk, using probabilistic machine learning as a refined regression tool applied to simulated data, which can be validated by low-cost companion Monte Carlo procedures. They identify the

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 copy this content. Please contact info@risk.net to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Risk.net? View our subscription options

Want to know what’s included in our free membership? Click here

Show password
Hide password

Most read articles loading...