  We prove a universal approximation theorem that allows to approximate continuous functionals of c\`adl\`ag (rough) paths uniformly in time and on compact sets of paths via linear functionals of their time-extended signature. Our main motivation to treat this question comes from signature-based models for finance that allow for the inclusion of jumps. Indeed, as an important application, we define a new class of universal signature models based on an augmented L\'evy process, which we call L\'evy-type signature models. They extend continuous signature models for asset prices as proposed e.g. by Arribas et al.(2020) in several directions, while still preserving universality and tractability properties. To analyze this, we first show that the signature process of a generic multivariate L\'evy process is a polynomial process on the extended tensor algebra and then use this for pricing and hedging approaches within L\'evy-type signature models. 
Universal approximation theorems for continuous functions of c\`adl\`ag   paths and L\'evy-type signature models