Brownian motion and stochastic differential equations
The Brownian motion is a canonical example of a stochastic process which is both a martingale and a Markov process. Using the Brownian motion we develop stochastic integrals as well as stochastic differential equations, which are then used to formulate and study problems of stochastic control and stopping.
The course treats Brownian motion (the Wiener process), Itô integrals, Itô's formula and stochastic differential equations as well as their properties and relations to partial differential equations. The course also covers optimal stopping theory and the theory of optimal stochastic control, as well as applications. In addition, some basic concepts of measure theoretic probability theory is treated.
The course consists of one element.
Teaching Format
Teaching consists of lectures and exercise sessions.
Assessment
Assessment takes place through written examination and hand in problems.
Examiner
A list of examiners can be found on
The schedule will be available no later than one month before the start of the course.
We do not recommend print-outs as changes can occur. At the start of the course,
your department will advise where you can find your schedule during the course.
Note that the course literature can be changed up to two months before the start of the course.
Course reports are displayed for the three most recent course instances.
