We study the local (in time) expansion of a continuous-time process and its conditional moments, including the process' characteristic function. The expansions are conducted by using the properties of the (time-extended) Ito signature, a tractable basis composed of iterated integrals of the driving deterministic and stochastic signals: time, multiple correlated Brownian motions and multiple correlated compound Poisson processes. We show that these properties are conducive to automated expansions to any order with explicit coefficients and, therefore, to stochastic representations in which asymptotics can be conducted for a shrinking time (t to 0), as in the extant continuous-time econometrics literature, but, also, for a fixed time (such that t smaller than 1) with a diverging expansion order. The latter design opens up novel opportunities for identifying deep characteristics of the assumed process.