Kolmogorov continuity theorem
From Wikipedia, the free encyclopedia
In mathematics, the Kolmogorov continuity theorem is a theorem that guarantees that a stochastic process that satisfies certain constrains 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.
[edit] Statement of the theorem
Let
be a stochastic process, and suppose that for all times T > 0, there exist constants α,β,D > 0 such that
for all
. Then there exists a continuous version of X, i.e. a process
such that
is sample continuous;- for every time
,
.
[edit] Example
In the case of Brownian motion on
, the choice of constants α = 4, β = 1, D = n(n + 2) will work in the Kolmogorov continuity theorem.
[edit] References
- Øksendal, Bernt K. (2003). Stochastic Differential Equations: An Introduction with Applications. Springer, Berlin. ISBN 3-540-04758-1. Theorem 2.2.3
![\mathbb{E} \left[ | X_{t} - X_{s} |^{\alpha} \right] \leq D | t - s |^{1 + \beta}](../../../../math/a/2/3/a23084e1b8181d6e87c5fc68388c598d.png)

