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Quantitative Asset and Risk Management

  • Enseignant(s):   E.Jondeau  
  • Titre en français: Gestion des actifs quantitative et management du risque
  • Cours donné en: anglais
  • Crédits ECTS: 6 crédits
  • Horaire: Semestre de printemps 2018-2019, 4.0h. de cours (moyenne hebdomadaire)
  •  séances
  • site web du cours site web du cours
  • Formations concernées:
    Maîtrise universitaire ès Sciences en finance : Entrepreneuriat financier et science des données

    Maîtrise universitaire ès Sciences en finance, Orientation finance d'entreprise

    Maîtrise universitaire ès Sciences en finance, Orientation gestion des actifs et des risques

 

Objectifs

The aim of the course is to address asset and risk management issues using available econometric tools. We will start with the problem of the estimation error in asset management. Given the estimation error surrounding the forecasting of expected returns and the covariance matrix, the mean-variance criterion is also known as an “estimation-error maximizer.” We will study techniques proposed to deal with this issue. Then, we will move to risk management. We will define precisely the risk measures and their practical estimation for the main classes of risk.

There are two main components in this course. On the one hand, there will be some theoretical lectures presenting the main topics and estimation techniques. On the other hand, there will be 2 group projects, which will give the opportunity to work with real-life problems. The projects will involve programming in Matlab, quantitative finance analysis, as well as some personal interpretation. They will be done in groups. The course also includes reading some well-known papers in asset and risk management.

Contenus

We aim at treating the following topics. However, given the available time, not all topics may be covered:

Asset Management

1. General Problem of Asset Management
2. Strategic and Tactical Asset Allocation
3. Estimation Error in Asset Allocation
4. Factor Models and Shrinkage Estimation
5. Bayesian Analysis and Black and Litterman Approach
6. Risk Budgeting and Parametric Weights

Risk Management

7. Basic Concepts of Risk Management
8. Credit Risk Estimating Market Risk
9. Standard Measures of Market Risk
10. Advanced Measures of Market Risk
11. Operational and Liquidity Risks
12. Regulation and Systemic Risk

Références

Brandt M. (2010), Portfolio Choice Problems, in Y. Aït-Sahalia and L.P. Hansen (ed.), Handbook of Financial Econometrics, Vol 1: Tools and Techniques, 269-336.

McNeil A.J., R. Frey, and P. Embrechts (2005), Quantitative Risk Management: Concepts, Techniques, and Tools, Princeton University Press. Advanced textbook for the second part of the course.

Scherer B. (2007), Portfolio Construction and Risk Budgeting, Risk Books. Covers topics in the first part of the course.

Pré-requis

Data Science for Finance

Evaluation

1ère tentative

Examen:
Ecrit 2h00 heures
Documentation:
Non autorisée
Calculatrice:
Autorisée avec restrictions
Evaluation:

Projects: There will be two projects, which will typically consist in the implementation and extension of the techniques studied in the course. The projects will include some empirical work that will be done with Matlab.

Let PRG be the grade for the project. It will be an average of the paper (2/3) and of the presentation (1/3).

Final Examination: The final exam will be a comprehensive 2-hour exam. We call this grade FEG.

The overall grade will be given by the formula:

70%*PRG + 30%*FEG.

Rattrapage

Examen:
Ecrit 2h00 heures
Documentation:
Non autorisée
Calculatrice:
Autorisée avec restrictions
Evaluation:

If you need to retake the exam, the grade will be simply based on the make-up exam, i.e. the grades of the projects no longer count.



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