390040 SE PhD-AW: Advanced Stochastic Modelling (2024S)
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 12.02.2024 09:00 to We 21.02.2024 12:00
- Deregistration possible until Th 14.03.2024 23:59
Details
max. 24 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
20.03.
11:30 - 13:00
Digital
Wednesday
24.04.
13:15 - 14:45
Digital
N
Wednesday
22.05.
13:15 - 14:45
Digital
Monday
17.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Tuesday
18.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Tuesday
18.06.
15:00 - 16:30
Seminarraum 19, Kolingasse 14-16, OG02
Wednesday
19.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
20.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Monday
24.06.
13:15 - 14:45
Seminarraum 9, Kolingasse 14-16, OG01
Tuesday
25.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Wednesday
26.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Thursday
27.06.
11:30 - 13:00
Seminarraum 9, Kolingasse 14-16, OG01
Information
Aims, contents and method of the course
The focus of the seminar is on newest developments in the area of data-driven and machine learning approaches to financial problems combined with their mathematical and probabilistic foundations.This includes the analysis of training algorithms, financial time-series predictions, calibration, hedging, risk management, portfolio optimization, and market simulation.An emphasis will lie on machine learning tools tailored to learning of dynamic processes, e.g. neural SDEs and signature based methods. Mathematical tools from rough paths theory as well as (infinite) dimensional stochastic analysis shall be used.
Assessment and permitted materials
Talk on an article in the subject area of the seminar
Minimum requirements and assessment criteria
Assessment of the talk
Examination topics
Content of the paper chosen for the talk
Reading list
The articles will be announced on Moodle.
Association in the course directory
Last modified: Fr 10.05.2024 15:06