Nr. | LV-Typ(en) | LV-Titel | |
5771 | PI | Asset/Risk Management I
Anmeldung über LPIS vom 02.02.2024 14:00 bis 18.02.2024 23:59 Abmeldung über LPIS vom 02.02.2024 14:00 bis 23.04.2024 23:59 |
LV-Leiter/in | Univ.Prof. Dr. Otto Randl, Patrick Weiß, Ph.D. |
Planpunkte Master | Asset/Risk Management I |
Semesterstunden | 2 |
Unterrichtssprache | Englisch |
Termine | ||||
Fr, | 26.04.2024 | 14:00-17:30 Uhr | TC.2.01 (Lageplan) | |
Fr, | 03.05.2024 | 14:00-17:30 Uhr | TC.2.02 (Lageplan) | |
Fr, | 17.05.2024 | 14:00-17:30 Uhr | TC.2.02 (Lageplan) | |
Mi, | 22.05.2024 | 18:00-19:00 Uhr | DCP | TC.-1.61 (Lageplan) |
Fr, | 24.05.2024 | 14:00-17:30 Uhr | TC.2.02 (Lageplan) | |
Fr, | 31.05.2024 | 14:00-17:30 Uhr | TC.2.02 (Lageplan) | |
Fr, | 07.06.2024 | 14:00-17:30 Uhr | TC.2.02 (Lageplan) | |
Fr, | 21.06.2024 | 14:00-16:00 Uhr | DCP | TC.-1.61 (Lageplan) |
Mi, | 26.06.2024 | 15:00-17:30 Uhr | Online-Einheit | |
Do, | 27.06.2024 | 15:00-17:30 Uhr | Online-Einheit | |
Termindownload (ical) | Termine abonnieren |
Weitere Informationen | https://learn.wu.ac.at/vvz/24s/5771 |
Kontakt: | ||
otto.randl@wu.ac.at | ||
Inhalte der LV: | ||
The courses Asset/Risk Management I and II deal with modern investment theory and its application to portfolio and risk management.
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Lernergebnisse (Learning Outcomes): | ||
Students who have successfully completed this course will have acquired the following skills:
In addition, students will have learned to
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Regelung zur Anwesenheit: | ||
Full attendance is compulsory. This means that students have to attend at least 80% of all lectures. |
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Lehr-/Lerndesign: | ||
The course will consist of a mix of regular lectures, class room discussions, and analyes of assignments. The lectures will be largely based on the instructor's lecture notes. A textbook is suggested for background reading and to help students refresh basic investments knowledge which is a prerequisite. Additional readings are assigned before classes. There will be assignments to practice the concepts developed during the lectures. These will involve quantitative analyses using R, to be solved in small groups. Students will present and discuss solutions in class. |
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Leistung(en) für eine Beurteilung: | ||
Components:
Grading:
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