261-5111-00L Asset Management: Advanced Investments (University of Zurich)
| Semester | Spring Semester 2020 |
| Lecturers | University lecturers |
| Periodicity | yearly recurring course |
| Language of instruction | English |
| Comment | No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: MFOEC207 Mind the enrolment deadlines at UZH: https://www.uzh.ch/cmsssl/en/studies/application/mobilitaet.html |
Courses
| Number | Title | Hours | Lecturers | |
|---|---|---|---|---|
| 261-5111-00 V | Asset Management: Advanced Investments (University of Zurich) **Course at University of Zurich** | 2 hrs | University lecturers |
Catalogue data
| Abstract | Comprehension and application of advanced portfolio theory |
| Objective | Comprehension and application of advanced portfolio theory |
| Content | The theoretical part of the lecture consists of the topics listed below. - Standard Markowitz Model and Extensions MV Optimization, MV with Liabilities and CAPM. - The Crux with MV Resampling, regression, Black-Litterman, Bayesian, shrinkage, constrained and robust optimization. - Downside and Coherent Risk Measures Definition of risk measures, MV optimization under VaR and ES constraints. - Risk Budgeting Equal risk contribution, most diversified portfolio and other concentration indices - Regime Switching and Asset Allocation An introduction to regime switching models and its intuition. - Strategic Asset Allocation Introducing a continuous-time framework, solving the HJB equation and the classical Merton problem. |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 3 credits |
| Examiners | |
| Type | graded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
| Additional information on mode of examination | Registration modalities, date and venue of this performance assessment are specified solely by UZH. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| Data Science Master | Interdisciplinary Electives | W |  |