AAD: Breaking the Primal Barrier

18th September 2019 Editor 0

In this article we present a new approach for automatic adjoint differentiation (AAD) with a special focus on computations where derivatives ∂F(X)/∂X are required for multiple instances of vectors X. In practice, the presented approach […]


Automatic Differentiation for the Greeks

16th April 2017 Editor 0

The sensitivities of the value of an option to the model parameters, a.k.a. “the Greeks,” are crucial to understanding the risk of an option position, as well as tasks such as model calibration. Outside a […]