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1. 1. Calibrating the Hull-White model using Adjoint Algorithmic Differentiation

   University essay from KTH/Matematisk statistik

   Author : Simon Carmelid; [2017]
   Keywords : ;

   Abstract : This thesis includes a brief introduction to Adjoint Algorithmic Differentiation (AAD), accompanied by numerical examples, step-by-step explanations and runtime comparisons to a finite difference method. In order to show the applicability of AAD in a stochastic setting, it is also applied in the calculation of the arbitrage free price and partial derivatives of a European call option, where the underlying stock has Geometric Brownian motion dynamics. READ MORE