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250152 PS Stochastic Analysis (2021W)
Continuous assessment of course work
Labels
MIXED
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 13.09.2021 00:00 to Mo 27.09.2021 23:59
- Deregistration possible until Su 31.10.2021 23:59
Details
max. 25 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Thursday
07.10.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
14.10.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
21.10.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
28.10.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
04.11.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
11.11.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
18.11.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
25.11.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
02.12.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
09.12.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
16.12.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
13.01.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
20.01.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Thursday
27.01.
13:15 - 14:00
Seminarraum 11 Oskar-Morgenstern-Platz 1 2.Stock
Information
Aims, contents and method of the course
This course aims at rigorously developing Ito's theory of stochastic calculus and presenting some of its fundamental applications.Some of the keywords are: Gaussian processes, Brownian motion, conditional expectation, martingales, stopping times, optional stopping, local martingales, stochastic integral, Ito's lemma.We will first construct Brownian motion and derive its basic properties. Then, we will develop a formal theory of continuous martingales and local martingales, on which we will build the stochastic integral.Towards the end of the course we will use the constructed theory of stochastic calculus to derive some deep results on the nature of Brownian motion (like for example conformal invariance of two-dimensional Brownian motion).Familiarity with Advanced Probability will be assumed. However, we will recall the notion of conditional expectation. Elements of complex analysis will be used towards the end of the course.
Assessment and permitted materials
Homework and blackboard presentations
Minimum requirements and assessment criteria
Examination topics
Reading list
Association in the course directory
MSTV
Last modified: We 29.09.2021 11:51