26 Pages Posted: 1 Jun 2010
Date Written: May 30, 2010
This paper demonstrates how the adjoint PDE method can be used to compute Greeks in Markov-functional models. This is an accurate and efficient way to compute Greeks, where most of the model sensitivities can be computed in approximately the same time as a single sensitivity using finite difference. We demonstrate the speed and accuracy of the method using a Markov-functional interest rate model, also demonstrating how the model Greeks can be converted into market Greeks.
Keywords: Adjoint PDE Greeks, delta, vega, skew, adjoint method, PDE, Markov-functional model, market Greeks, cancellable inverse floater, Bermudan swaption
JEL Classification: G13
Suggested Citation: Suggested Citation
Denson, Nick and Joshi, Mark S., Fast Greeks for Markov-Functional Models Using Adjoint Pde Methods (May 30, 2010). Available at SSRN: https://ssrn.com/abstract=1618026 or http://dx.doi.org/10.2139/ssrn.1618026