Adjoint algorithmic differentiation (AAD)

Risk optimisation: the noise is the signal

Benedict Burnett, Simon O’Callaghan and Tom Hulme introduce a new method of optimising the accuracy and time taken to calculate risk for an XVA trading book. They show how to make a dynamic choice of the number of paths and time discretisation focusing…

Adjoint credit risk management

Adjoint algorithmic differentiation is one of the principal innovations in risk management in recent times. Luca Capriotti and Jacky Lee show how this technique can be used to compute real-time risk for credit products, even those valued with fast semi…