Stochastic Processes

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Stochastic Processes

Semester
WiSe 2025 / 26

Lecturer
Richard Höfer

Type of course (Veranstaltungsart)
Vorlesung

German title
Stochastische Prozesse

Contents
Stochastic processes are the fundamental objects for time dependent phenomena that involve randomness. Applications range from physics, biology, and chemistry over information theory, machine learning, to finance. We study stochastic processes both in discrete and continuous time. The content of the course includes conditional expectations, Markov chains and processes, martingals, recurrence and transience, Poisson processes, random walks, Brownian motion. There will be a course Stochastic Analysis in summmer 2026 where we develop the theory of stochastic integration and stochastic differential equations.

Literature
Kersting, Walkobinger: Stochastische Prozesse
Klenke: Wahrscheinlichkeitstheorie.
Durrett: Probability: Theory and examples
Breiman: Probability.
Norris: Markov chains.

Recommended previous knowledge
Lineare Algebra, Analysis, Introduction to probability theory. Knowledge in Functionalanalysis, partial differential equations or optimization is helpful but not required

Time/Date
Mon 10-12, Thu 8-10; Exercise: Wed 12-14

Location
Mon: M 103, Thu: M 102; Exercise PHY 5.0.20

Course homepage
https://elearning.uni-regensburg.de/course/view.php?id=71686
(Disclaimer: Dieser Link wurde automatisch erzeugt und ist evtl. extern)

Registration

Registration for course work/examination/ECTS: FlexNow

Course work (Studienleistungen)

Successful participation in the exercise classes: 50% of the exercises

Examination (Prüfungsleistungen)

Oral exam: Duration: 30 minutes, Date: by arrangement , re-exam: Date: by arrangement

Modules
BV, MV, MAngAn

ECTS
9