Automatic Adjoint Differentiation for special functions involving expectations

José Brito, Andrei Goloubentsev, Evgeny Goncharov

We explain how to compute gradients of functions of the form $G=\frac{1}{2}{\sum }_{i=1}^m(E{y}_i-C_i{)}^2$, which often appear in the calibration of stochastic models, using Aut…