20248 - ASSET MANAGEMENT
CLMG - M - IM - MM - AFC - CLAPI - CLEFIN-FINANCE - CLELI - ACME - DES-ESS - EMIT
Course taught in English
Go to class group/s: 31
This course aims at analyzing recent theoretical and empirical developments in portfolio management, outlining topics which are relevant for students wishing to work in the asset management industry. The first part of the course deals with portfolio construction and management, outlining advanced asset allocation models, the role of alternative asset classes and portfolio insurance models. The second part of the course deals with performance evaluation and risk management issues.
The course includes four IT sessions on practical applications of the models taught in class and two sessions with industry practitioners.
Advances in strategic asset allocation techniques: resampling and the Black-Litterman approach
The role of alternative asset classes: hedge funds, commodities and private equity for institutional and private clients
International diversification, carry trades and forex hedging;
Portfolio insurance models
Stock selection models in long-only and long-short environments
Portfolio performance evaluation and style analysis
Risk management of asset management portfolios
Private and institutional customer management and behavioural biases
Students who attend the course are evaluated by means of two groupworks, each worth 25% of the final grade, and a final written test worth 50% of the final grade..The two groupworks are only valid for attending students and in connection with the written tests of the January-February session.
Non attending students take a written test worth 100% of the final grade.
There is no book for this course. Teaching material is based on slides and a number of journal articles.
Even if there is no formal requirements for this course you should be familiar with the basic concepts of theoretical finance as, for example, utility theory, standard portfolio theory and CAPM. Students are expected to understand the fundamentals of statistics and multiple regression analysis. We will also take for granted the knowledge of basic calculus and matrix algebra.