Signature SDEs from an affine and polynomial perspective

Signature stochastic differential equations (SDEs) constitute a large class of stochas- tic processes, here driven by Brownian motions, whose characteristics are entire or real- analytic functions of their own signature, i.e. of iterated integrals of the process with itself, and allow therefore for a generic path dependence. We show that their pro- longation with the corresponding signature is an affine and polynomial process taking values in subsets of group-like elements of the extended tensor algebra. By relying on the duality theory for affine and polynomial processes we obtain explicit formulas in terms of novel and proper notions of converging power series for the Fourier-Laplace transform and the expected value of entire functions of the signature process. The coefficients of these power series are solutions of extended tensor algebra valued Ric- cati and linear ordinary differential equations (ODEs), respectively, whose vector fields can be expressed in terms of the entire characteristics of the corresponding SDEs. In other words, we construct a class of stochastic processes, which is universal within Itˆo processes with path-dependent characteristics and which allows for a relatively explicit characterization of the Fourier-Laplace transform and hence the full law on path space. We also analyze the special case of one-dimensional signature SDEs, which correspond to classical SDEs with real-analytic characteristics. Finally, the practical feasibility of this affine and polynomial approach is illustrated by several numerical examples.