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Präsenz/Online gemischt
Event
Essentials for Dynamic Financial Machine Learning [SS242600004]
Type
lecture/exercise (VÜ)Präsenz/Online gemischt
Term
SS 2024SWS
Language
EnglischAppointments
27Links
ILIASLecturers
Organisation
- Institut für Finanzwirtschaft, Banken und Versicherungen
Part of
- Brick Modeling the Dynamics of Financial Markets | Industrial Engineering and Management (M.Sc.)
- Brick Modeling the Dynamics of Financial Markets | Economics Engineering (M.Sc.)
- Brick Modeling the Dynamics of Financial Markets | Digital Economics (M.Sc.)
- Brick Modeling the Dynamics of Financial Markets | Information Systems (M.Sc.)
- Brick Modeling the Dynamics of Financial Markets | Economathematics (M.Sc.)
Appointments
- 17.04.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 19.04.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 24.04.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 26.04.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 03.05.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 08.05.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 10.05.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 15.05.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 17.05.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 29.05.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 31.05.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 05.06.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 07.06.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 12.06.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 14.06.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 19.06.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 21.06.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 26.06.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 28.06.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 03.07.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 05.07.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 10.07.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 12.07.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 17.07.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 19.07.2024 15:45 - 17:15 - Room: 05.20 1C-01
- 24.07.2024 09:45 - 11:15 - Room: 11.40 Raum 221
- 26.07.2024 15:45 - 17:15 - Room: 05.20 1C-01
Note
This course teaches students to work with financial data. Students learn algorithms that are used to learn key quantities of dynamic capital markets, such as time-varying risk premia, volatility and unobserved state variables. The course covers the following concepts:
* Multivariate time series modeling
* Dynamic volatility modeling
* Handling big financial data
* Estimating risk premia
* Kalman Filtering
Lectures develop all material on the whiteboard. Tutoriums solve and discuss python solutions to selected problems.