Kolmogorov continuity theorem

{{Short description|Mathematical theorem}}

In mathematics, the Kolmogorov continuity theorem is a theorem that guarantees that a stochastic process that satisfies certain constraints on the moments of its increments will be continuous (or, more precisely, have a "continuous version"). It is credited to the Soviet mathematician Andrey Nikolaevich Kolmogorov.

Statement

Let (S,d) be some complete separable metric space, and let X\colon [0, + \infty) \times \Omega \to S be a stochastic process. Suppose that for all times T > 0, there exist positive constants \alpha, \beta, K such that

:\mathbb{E} [d(X_t, X_s)^\alpha] \leq K | t - s |^{1 + \beta}

for all 0 \leq s, t \leq T. Then there exists a modification \tilde{X} of X that is a continuous process, i.e. a process \tilde{X}\colon [0, + \infty) \times \Omega \to S such that

  • \tilde{X} is sample-continuous;
  • for every time t \geq 0, \mathbb{P} (X_t = \tilde{X}_t) = 1.

Furthermore, the paths of \tilde{X} are locally \gamma-Hölder-continuous for every 0<\gamma<\tfrac\beta\alpha.

Example

In the case of Brownian motion on \mathbb{R}^n, the choice of constants \alpha = 4, \beta = 1, K = n (n + 2) will work in the Kolmogorov continuity theorem. Moreover, for any positive integer m, the constants \alpha = 2m, \beta = m-1 will work, for some positive value of K that depends on n and m.

See also

References

  • {{cite book | author= Daniel W. Stroock, S. R. Srinivasa Varadhan | authorlink=Daniel W. Stroock, S. R. Srinivasa Varadhan | title=Multidimensional Diffusion Processes | publisher=Springer, Berlin | year=1997 | isbn=978-3-662-22201-0}} p. 51

Category:Theorems about stochastic processes