||This article needs attention from an expert in Statistics. The specific problem is: the article lacks a definition, illustrative examples, but is of importance (Poisson process, Lévy process).. (December 2013)
A jump process is a type of stochastic process that has discrete movements, called jumps, rather than small continuous movements.
A general mathematical framework relating discrete-time processes to continuous time ones is the continuous-time random walk.
In physics, jump processes result in diffusion. On a microscopic level, they are described by jump diffusion models.
In finance, various stochastic models are used to model the price movements of financial instruments; for example the Black–Scholes model for pricing options assumes that the underlying instrument follows a traditional diffusion process, with small, continuous, random movements. John Carrington Cox and Stephen Ross:145-166 proposed that prices actually follow a 'jump process'. The Cox–Ross–Rubinstein binomial options pricing model formalizes this approach. This is a more intuitive view of financial markets, with allowance for larger moves in asset prices caused by sudden world events.
Robert C. Merton extended this approach to a hybrid model known as jump diffusion, which states that the prices have large jumps followed by small continuous movements.