As always, start with George Lowther:

Continuous-time stochastic processes with stationary independent increments are known as

Lévy processes. […]it was seen that processes with independent increments are described by three terms — the covariance structure of the Brownian motion component, a drift term, and a measure describing the rate at which jumps occur. Being a special case of independent increments processes, the situation with Lévy processes is similar.[…]A d-dimensional Lévy process X is a stochastic process taking values in \({\mathbb R}^d\) such that

- independent increments: \(X_t-X_s\) is independent of \(\{X_u\colon u\le s\}\) for any \(s<t.\)
- stationary increments: \(X_{s+t}-X_s\) has the same distribution as \(X_t-X_0\) for any \(s,t>0.\)
- continuity in probability: \(X_s\rightarrow X_t\) in probability as \(s\rightarrow t.\)

## General form

TBC

## Intensity measure

TBC

## Subordinator

See change of time