Linear independence properties of the signature components of time-augmented stochastic processes

TL;DR

This paper investigates the linear independence of signature components of time-augmented stochastic processes, revealing new spanning properties and optimal computation strategies, especially for processes solving SDEs with Brownian noise.

Contribution

It generalizes existing results on the spanning properties of signature components, introduces new subfamilies with the same span, and establishes linear independence for solutions to certain SDEs.

Findings

Signature components with words of length N span the same space as those with length ≤ N.

Certain subfamilies of signature components are linearly independent for SDE solutions.

Discretized sample paths retain linear independence with sufficiently small time steps.

Abstract

The addition of the running time as a component of a path before computing its signature is a widespread approach to ensure the one-to-one property between them and leads to universal approximation theorems (Cuchiero, Primavera and Svaluto-Ferro, 2023). However, this also leads to the linear dependence of the components of the terminal value of the signature of the time-augmented path. More precisely, for a given natural number $N$, the signature components associated with words of length $N$ have the same linear span as the signature components associated with words of length not greater than $N$. We generalize this result by exhibiting other subfamilies of signature components with the same spanning properties. In particular we recover the result of Dupire and Tissot-Daguette which states that the spanning of the iterated integrals with the last integrator different from the time variable is the same as the spanning of all iterated integrals. We check that this choice leads to the minimal computation time when the terms of the signature are calculated using Chen's relation in a backward way. The same optimal computation time is symmetrically achieved in a forward way for the iterated integrals with the first integrator different from the time variable. Building on these results, we derive several results regarding the linear independence of the signature components of a time-augmented stochastic process. We show that if the stochastic process we consider is solution to some SDE with additive Brownian noise then any subfamily of components proposed previously is linearly independent. We also prove that the linear independence of these subfamilies of components is still true when we consider the discretization of the sample paths of this stochastic process on a grid with a sufficiently small discretization time step.