Universal approximation on non-geometric rough paths and applications to financial derivatives pricing
Fabian A. Harang, Fred Espen Benth, Fride Straum
TL;DR
The paper addresses pricing of complex, path-dependent financial derivatives by extending universal signature-based approximation to non-geometric rough paths, thereby incorporating Itô (Itô) integration into a rough-path framework. It introduces a polynomial-enriched feature class over signatures and, under a separability hypothesis, proves a generalized universal approximation with explicit error bounds, applicable even when time-extended, non-geometric rough paths are used. The approach yields practical representations of payoff functionals as polynomials in a finite set of signature coordinates and enables pricing through low-dimensional correlators, with concrete illustrations for Asian, spread, and quanto-style derivatives and energy-market applications. This framework promises computational efficiency and theoretical robustness for Itô-driven derivatives pricing in finance, linking rough-path theory with practical, model-free pricing techniques.
Abstract
We present a novel perspective on the universal approximation theorem for rough path functionals, introducing a polynomial-based approximation class. We extend universal approximation to non-geometric rough paths within the tensor algebra. This development addresses critical needs in finance, where no-arbitrage conditions necessitate Itô integration. Furthermore, our findings motivate a hypothesis for payoff functionals in financial markets, allowing straightforward analysis of signature payoffs proposed in \cite{arribas2018derivativespricingusingsignature}.
