Website
Module guide

Module MA4610-KP04, MA4610

Stochastic processes and modeling (StochPrzMd)

Duration:


1 Semester
Turnus of offer:


normally each year in the winter semester
Credit points:


4
Course of studies, specific field and terms:
  • Master MES 2020 (optional subject), mathematics / natural sciences, arbitrary semester
  • Master MES 2014 (optional subject), mathematics / natural sciences, 1st or 2nd semester
  • Master Computer Science 2012 (optional subject), advanced curriculum stochastics, 2nd or 3rd semester
Classes and lectures:
  • Stochastic processes and modeling (exercise, 1 SWS)
  • Stochastic processes and modeling (lecture, 2 SWS)
Workload:
  • 20 Hours exam preparation
  • 55 Hours private studies and exercises
  • 45 Hours in-classroom work
Contents of teaching:
  • Conditional expectation
  • Stochastic processes
  • Filtrations
  • Martingales
  • Brownian motion
Qualification-goals/Competencies:
  • Students can name stochastic processes on the basis of selected process classes and explain their properties.
  • They have deepened the stochastic way of thinking and can explain the evidence of the lecture.
  • They can explain and apply basic ideas and concepts of stochastic analysis.
Grading through:
  • written exam
Requires:
Responsible for this module:
Teachers:
Literature:
  • :
  • :
  • Ioannis Karatzas, Steven E. Shreve: Brownian Motion and Stochastic Calculus - Springer Verlag, 2nd edition, 1991
Language:
  • German and English skills required
Notes:

Prerequisites for attending the module:
- None (The competences of the required modules are required for this module, but the modules are not a prerequisite for admission).

Prerequisites for the exam:
- Preliminary examinations can be determined at the beginning of the semester. If preliminary work has been defined, it must have been completed and positively assessed before the initial examination.

Letzte Änderung:
4.12.2019