Portfolio Management [ELFIM400]

Learning outcomes

At the end of this course, the student should be able to:

- select and rely on appropriate theoretical tools to :

(i) analyse and predict stock returns,

(ii) build a portfolio of stocks from observed individual return series according to standard approaches (Markowitz, Risk budgeting),

- use R software to:

(i) build up portfolio from observed data on stock returns,

(ii) analyse financial returns based on statistical metrics (e.g. mean, variance, covariances/correlation) and via the estimation of benchmark models by means of appropriate econometric techniques (e.g. beta computation via CAPM estimations of on real data, etc.)

Objectives

The objective of the course is threefold:

1. equip students with a theoretical knowledge on modern portfolio theory, that is the traditional approach from Markowitz (still widely used in practice) to be completed with more recent "Risk budgeting" approach that aims to become the new standard, as well as asset pricing models (e.g. Constant Expected Return (CER), single index (SI), CAPM, multi-factor models [Fama-French-Carhart], APT),
2. sensitize students to investment sustainability and the relevance of taking into account environmental, societal as well as governance criteria when building up and managing stock portfolios
3. initiate students to the practice of R software to collect data, estimate asset pricing models as well as simulate stock portfolios

Content

The course will be articulated over the following topics:

1. Measuring and analysing stock returns
2. Modern portfolio theory: H.Markowitz' approach
3. Standard asset princng models: CER/SI/CAPM/Multi-factor models/APT
4. Risk budgeting
5. [If enough time] C-CAPM

In parallel, lab sessions in R will be scheduled:

1. Introduction to programming and data analysis in R
2. Portfolio analysis in R
3. Estimation of standard asset pricing models in R
4. [If enough time] GMM estimation of C-CAPM