CVA and IM: welcome to the machine

Henry-Labordere proposes a neural networks-based technique to price counterparty risk and initial margin


Building heavily on recent work, Pierre Henry-Labordère introduces a primal-dual method for solving backward stochastic differential equations based on the use of neural networks, stochastic gradient descent and a dual formulation of stochastic control problems. The algorithm is illustrated using two examples relevant to mathematical finance: the pricing of counterparty risk and the computation of initial margin

Solving numerically high-dimensional, non-linear

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 or view our subscription options here:

You are currently unable to copy this content. Please contact 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 View our subscription options

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here