Affine or polynomial processes are fascinating classes of models due to the so-called affine transform formulae or moment formulae, respectively. We first show through a linearization procedure that generic classes of diffusion models can be obtained as projections of infinite dimensional affine processes (which actually coincide with polynomial processes). Affine and polynomial technology next allows to derive so far unknown formulae for characteristic functions and moments of involved process functionals. Third a dynamic viewpoint on those formulae (combined with machine learning approaches) leads to efficient numerical evaluations.
Link to Zoom meeting: https://univr.zoom.us/j/84072573273
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