Lehrinhalte
definition and existence of stochastic processes in continuous and discrete time
- Brownian motion: definition, existence and important properties
- general theory of Gaussian processes
- Ito integral
- stochastic differential equations

Literature
Klenke: Wahrscheinlichkeitstheorie
Mörters and Peres: Brownian motion
Lifshits: Gaussian random functions
Karatsas and Shreve: Brownian motion and stochastic calculus

Voraussetzungen
recommended: Analysis, Linear Algebra, Probability Theory;
basic familiarity with functional analysis will be of great use.

Online-Angebote
moodle

Semester: WT 2022/23