Veranstaltung
Literaturseminar - Return Predictability in Equity and Option Markets with Machine Learning and Big Data [WS222500029]
Dozent/en
Einrichtung
- Institut für Finanzwirtschaft, Banken und Versicherungen
Bestandteil von
- Teilleistung Seminar Betriebswirtschaftslehre A (Master) | Wirtschaftsingenieurwesen (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre B (Master) | Wirtschaftsingenieurwesen (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre A (Master) | Technische Volkswirtschaftslehre (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre B (Master) | Technische Volkswirtschaftslehre (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre A (Master) | Wirtschaftsinformatik (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre A (Master) | Informationswirtschaft (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre A (Master) | Wirtschaftsmathematik (M.Sc.)
- Teilleistung Seminar Betriebswirtschaftslehre B (Master) | Wirtschaftsmathematik (M.Sc.)
Veranstaltungstermine
- 26.10.2022 11:30 - 13:00 - Room: 20.30 Seminarraum -1.009 (UG)
- 02.11.2022 11:30 - 13:00 - Room: 20.30 Seminarraum -1.009 (UG)
- 09.11.2022 11:30 - 13:00 - Room: 20.30 Seminarraum -1.009 (UG)
- 16.11.2022 11:30 - 13:00 - Room: 20.30 Seminarraum -1.009 (UG)
- 23.11.2022 11:30 - 13:00 - Room: 20.30 Seminarraum -1.009 (UG)
Anmerkung
The aim of this seminar is to master real-world challenges of computational risk and asset management. The CRAM team offers a wide range of topics across different asset classes and different stages of the investment process.
Students will work on a quantitative problem related to risk and asset management. This seminar is ideally suited for students who want to deepen and apply their statistics / programming skills and knowledge about financial markets. Industry-relevant problems will be solved with financial data and modern statistical tools in close collaboration with a supervisor. Topics which students solved in the past include the option-based pricing of dividends during the Euro crisis, the estimation of risk neutral moments with high-frequent data and the application of a particle filter to estimate stochastic volatility. The current topics will be presented during the first meeting.