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Module guide WS 2018-2022

Module MA4610-KP05

Stochastic processes (StoProKP05)

Duration:


1 Semester
Turnus of offer:


normally each year in the winter semester
Credit points:


5
Course of studies, specific field and terms:
  • Master CLS 2023 (compulsory), mathematics, 1st or 3rd semester
  • Master CLS 2016 (compulsory), mathematics, 1st or 3rd semester
Classes and lectures:
  • Stochastic processes (exercise, 1 SWS)
  • Stochastic processes (lecture, 2 SWS)
Workload:
  • 20 Hours exam preparation
  • 85 Hours private studies and exercises
  • 45 Hours in-classroom work
Contents of teaching:
  • Conditional expectation
  • Stochastic processes
  • Filtrations
  • Martingales
  • Brownian motion
Qualification-goals/Competencies:
  • To develop some insight into stochastic processes based on selected classes of processes
  • Training of a stochastic way of thinking
  • Application of basic ideas and concepts of stochastic analysis
Grading through:
  • written exam
Requires:
Responsible for this module:
Teachers:
Literature:
  • L. C. G. Rogers, D. Williams: Diffusions, Markov Processes, and Martingales, Vol. 1, Foundations - 2nd edition, Cambridge University Press, 2000
  • L. C. G. Rogers, D. Williams: Diffusions, Markov Processes, and Martingales, Vol. 2, Ito Calculus - 2nd edition, Cambridge University Press, 2014
  • Ioannis Karatzas, Steven E. Shreve: Brownian Motion and Stochastic Calculus - Springer Verlag, 2nd edition, 1991
Language:
  • English, except in case of only German-speaking participants
Notes:

Admission requirements for taking the module:
- None (The competencies of the modules listed under 'Requires' are needed for this module, but are not a formal prerequisite)

Admission requirements for participation in module examination(s):
- Examination prerequisites can be defined at the beginning of the semester. If preliminary work is defined, it must have been completed and positively evaluated before the first examination.

Module exam(s):
- MA4610-L1: Stochastic processes, written exam, 90 min, 100 % of module grade

Letzte Änderung:
22.2.2022