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This entry is from Winter semester 2018/19 and might be obsolete. You can find a current equivalent here.
Stochastical Analysis
(dt. Stochastische Analysis)
Level, degree of commitment | Specialization module, compulsory elective module |
Forms of teaching and learning, workload |
Lecture (4 SWS), recitation class (2 SWS), 270 hours (90 h attendance, 180 h private study) |
Credit points, formal requirements |
9 CP Course requirement(s): Written or oral examination Examination type: Successful completion of at least 50 percent of the points from the weekly exercises. |
Language, Grading |
German,The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Business Mathematics. |
Duration, frequency |
One semester, Regularly alternating with other specialization modules |
Person in charge of the module's outline | Prof. Dr. Markus Bibinger |
Contents
We introduce stochastic integration and applications. Different topics cover, for instance, stochastic differential equations, jump processes and applications in financial mathematics.
Qualification Goals
The students shall
- gain insight into the research field of stochastic analysis,
- learn basic structures and techniques of stochastic analysis,
- get to know selected applications of stochastic analysis,
- practice mathematical methods (developing mathematical intuition and its formal justification, training of the ability to abstract, proof methods),
- practice oral communication skills in the recitation classes by practicing free speech in front of an audience.
Prerequisites
Translation is missing. Here is the German original:
Keine. Empfohlen werden die Kompetenzen, die in den Basismodulen und im Vertiefungsmodul Wahrscheinlichkeitstheorie vermittelt werden.
Applicability
Module imported from M.Sc. Business Mathematics.
It can be attended at FB12 in study program(s)
- B.Sc. Mathematics
- B.Sc. Business Mathematics
- M.Sc. Data Science
- M.Sc. Computer Science
- M.Sc. Mathematics
- M.Sc. Business Mathematics
- LAaG Mathematics
When studying M.Sc. Computer Science, this module can be attended in the study area Minor subject Mathematics.
Recommended Reading
- Oksendal, B., „Stochastic Differential Equations: An Introduction with Applications“. Springer-Verlag Berlin 1998
- Karatzas, I., Shreve, S., „Brownian Motion and Stochastic Calculus“. Springer-Verlag Berlin 1991
- Protter, P., „Stochastic Integration and Differential Equations: A New Approach“. Springer-Verlag Berlin 2003
- Revuz, D., Yor, M., „Continuous Martingales and Brownian Motion“. Springer 2005
Please note:
This page describes a module according to the latest valid module guide in Winter semester 2018/19. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:
- Winter 2016/17
- Summer 2018
- Winter 2018/19
- Winter 2019/20
- Winter 2020/21
- Summer 2021
- Winter 2021/22
- Winter 2022/23
- Winter 2023/24
The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.
The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.