Levy process

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Lévy process, named after the French mathematician Paul Lévy, is a càdlàg stochastic process with independent, stationary increments: it represents the motion of a point whose successive displacements are random and independent, and statistically identical over different time intervals of the same length. A Lévy process may thus be viewed as the continuous-time analog of a random walk.

The most well known examples of Lévy processes are Brownian motion and the Poisson process. Aside from Brownian motion with drift, all other proper Lévy processes have discontinuous paths.

Formalization

A stochastic process $X_t$ is said to be a Lévy process if it satisfies the following properties:

  • ${\displaystyle X_{0}=0}$, almost surely
  • Independence of increments: For any ${\displaystyle 0\leq t_{1}<t_{2}<\cdots <t_{n}<\infty }$, ${\displaystyle X_{t_{2}}-X_{t_{1}},X_{t_{3}}-X_{t_{2}},\dots ,X_{t_{n}}-X_{t_{n-1}}}$ are independent
  • Stationary increments: For any ${\displaystyle s<t}$, ${\displaystyle X_{t}-X_{s}}$, is equal in distribution to ${\displaystyle X_{t-s}}.
  • Continuity in probability: For any ${\displaystyle \epsilon >0} and ${\displaystyle t\geq 0}$ it holds that ${\displaystyle \lim _{h\rightarrow 0}P(X_{t+h}-X_{t}>\epsilon )=0}$

If ${\displaystyle X}$ is a Lévy process then one may construct a version of ${\displaystyle X}$ such that ${\displaystyle t\mapsto X_{t}}$ is almost surely right continuous with left limits.

See also

Wiener process

Papers

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