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Quantitative Asset and Risk Management

  • Teacher(s):   E.Jondeau  
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Spring Semester 2021-2022, 4.0h. course (weekly average)
  •  sessions
  • site web du cours course website
  • Related programmes:
    Master of Science (MSc) in Finance : Financial Entrepreneurship and Data Science

    Master of Science (MSc) in Finance, Orientation Corporate Finance

    Master of Science (MSc) in Finance, Orientation Asset and Risk Management
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Objectives

The aim of the course is to address asset and risk management issues using available econometric tools. We 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 study techniques proposed to deal with this issue. Then, we move to risk management. We precisely define the risk measures and their practical estimation for the main classes of risk.

We also describe the impact of climate change on both dimension (asset and risk management) of the course. We start with a presentation of the main challenges of climate change for asset and risk management. Then, we discuss how investors can take climate risks into account in their allocation process and in their risk measurement and management.

Contents

We address the following topics:

Part I - Asset Management

[1] General Problem of Asset Management
[2] Estimating the Inputs
[3] Regularization of Covariance Matrix and Adding Constraints
[4] Risk Budgeting and Other Topics
[5] Climate Change and Climate Risks
[6] Portfolio Construction under Climate Risks

Part II - Risk Management

[7] Introduction to Risk Management
[8] Standard Measures of Market Risk
[9] Advanced Measures of Market Risk
[10] Credit Risk
[11] Operational and Liquidity Risks
[12] Systemic Risks

References

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.

Pre-requisites

Data Science for Finance

Evaluation

First attempt

Exam:
Written 2h00 hours
Documentation:
Not allowed
Calculator:
Allowed with restrictions
Evaluation:

Project: There is one project, which typically consists in the implementation and extension of the techniques studied in the course. It covers the two dimensions of asset and risk management. The project includes some empirical work that is done with Matlab or Python.

Let PRG be the grade for the project. There could be some differentiation between the group members based on the presentation.

Final Examination: The final exam is a comprehensive 2-hour exam on MoodleExam. We call this grade FEG.

The overall grade is given by the formula

60%*PRG + 40%*FEG

Retake

Exam:
Written 2h00 hours
Documentation:
Not allowed
Calculator:
Allowed with restrictions
Evaluation:

If you need to retake the exam, the grade is simply based on the make-up exam, i.e., the grade of the project no longer counts.



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