Introduction to Financial Data Science
| Modul number | 5107-221 | ||
| Lecturer | Prof. Dr. Thomas Dimpfl | ||
| Language | English | ||
| Suitability | 4th Semester | ||
Time and place | Thursday, 10 a.m. - 12 p.m., HS 23 (Lecture) Tuesday, 2 p.m. - 4 p.m., HS 7 (Practical Class) | ||
| Exam | Take home assignment (30%) Written exam (70%) | ||
| Credit points | 6 ECTS | ||
| Beginn | Tuesday, April 9, 2024 Please, bring your laptop (fully charged) to the first session. | ||
| ILIAS password | - | ||
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On completion of this module, students demonstrate a knowledge and understanding of the key practical and theoretical components of quantitative financial methods, can apply data science methods to practical problems in finance, can implement a range of applied quantitative techniques using R, and have developed research skills in financial data analysis.
Basic knowledge of statistics is required. Students are expected to have completed the modules 5202-090 (Einführung in die statistische Datenanalyse) and 5202-160 (Stichprobenbasierte Datenanalyse).
Topics covered in the course include
- Returns and their properties
- Risk modelling - the volatility of returns
- Risk management - Value-at-risk and Expected Shortfall
- The Capital Asset Pricing Model
- Markets for cryptocurrencies
- Event study methodology in Finance
- Basics of financial market microstructure
- Return predictability and the efficient market hypothesis