Algorithmic Differentiation: Adjoint Greeks Made Easy
12 Pages Posted: 4 Apr 2011
Date Written: April 2, 2011
We show how algorithmic differentiation can be used as a design paradigm to implement the adjoint calculation of sensitivities in Monte Carlo in full generality and with minimal analytical effort. With several examples we illustrate the workings of this technique and demonstrate how it can be straightforwardly implemented to reduce the time required for the computation of the risk of any portfolio by orders of magnitude.
Keywords: Algorithmic Differentiation, Monte Carlo Simulations, Derivatives Pricing
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