Universität Wien

390040 SE PhD-AW: Advanced Stochastic Modelling (2022S)

3.00 ECTS (2.00 SWS), SPL 39 - Doktoratsstudium Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

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).

Details

max. 24 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Seminar: 12:15-13:45

  • Tuesday 08.03. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 15.03. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 22.03. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 29.03. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 05.04. 11:30 - 14:45 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
  • Tuesday 26.04. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 03.05. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 10.05. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 17.05. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 24.05. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 31.05. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 14.06. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 21.06. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02
  • Tuesday 28.06. 11:30 - 14:45 PC-Seminarraum 3, Kolingasse 14-16, OG02

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, detection of statistical arbitrages, calibration, hedging, 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 research articles will be announced on Moodle.

Association in the course directory

Last modified: Th 10.03.2022 14:49