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
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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
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Contents of teaching: | - Conditional expectation
- Stochastic processes
- Filtrations
- Martingales
- Brownian motion
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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
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Grading through: |
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
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Language: - English, except in case of only German-speaking participants
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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 |
für die Ukraine