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Block
Computational Risk and Asset Management [T-WIWI-102878]
Type
Examination of another typeCredits
4.5Recurrence
Each winter termVersion
5Responsible
Organisation
- KIT-Fakultät für Wirtschaftswissenschaften
Part of
- Module Data Science for Finance | Industrial Engineering and Management (M.Sc.)
- Module Financial Economics | Industrial Engineering and Management (B.Sc.)
- Module Data Science for Finance | Economics Engineering (M.Sc.)
- Module Financial Economics | Economics Engineering (B.Sc.)
- Module Financial Economics | Digital Economics (B.Sc.)
- Module Data Science for Finance | Information Systems (M.Sc.)
- Module Financial Economics | Information Systems (B.Sc.)
- Module Financial Economics | Information Engineering and Management (B.Sc.)
- Module Data Science for Finance | Information Engineering and Management (M.Sc.)
- Module Data Science for Finance | Economathematics (M.Sc.)
Events
Course Number | Name | SWS | Type |
---|---|---|---|
WS19 2500015 | Computational Risk and Asset Management | 4 | lecture (V) |
WS20 2500015 | Computational Risk and Asset Management | 2 | lecture (V) |
Exams
Course Number | Name | Appointments |
---|---|---|
WS19 7900320 | Computational Risk and Asset Management | |
WS19 7900320 | Computational Risk and Asset Management | |
WS19 7900320 | Computational Risk and Asset Management | |
WS19 7900320 | Computational Risk and Asset Management | 06.02.2020 - 09:45 |
Competence Certificate
The module examination takes the form of an alternative exam assessment.
The alternative exam assessment consists of a Python-based "Takehome Exam". At the end of the third week of January, the student is given a "Takehome Exam" which he processes and sends back independently within 4 hours using Python. Precise instructions will be announced at the beginning of the course. The alternative exam assessment can be repeated a maximum of once. A timely repeat option takes place at the end of the third week in March of the same year. More detailed instructions will be given at the beginning of the course.
Prerequisites
None.
Recommendation
Basic knowledge of capital markt theory.