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Empirical Methods in Finance

  • Teacher(s):   E.Jondeau  
  • Course given in: English
  • ECTS Credits: 6 credits
  • Schedule: Spring Semester 2021-2022, 4.0h. course + 2.0h exercices (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 provide a comprehensive knowledge of the econometric tools that are essential to estimate financial models, for asset pricing, asset management, or risk management. We focus on the empirical techniques used most often in the analysis of financial markets and how they are applied to actual market data. The class will give a solid balance between the necessary academic knowledge and hands-on applications.

Contents

We will address the following topics:

Introduction and Methodology
[1] Characteristics of financial time series
[2] Univariate Time Series Analysis
[3] Multivariate Time Series Analysis
[4] Non-Stationarity and Cointegration

Empirical Finance
[5] Capital Asset Pricing Model
[6] Multi-factor models
[7] Efficient markets hypothesis

Financial Econometrics
[8] Modeling volatility: ARCH models
[9] Modeling volatility: GARCH models and extensions
[10] Modeling non-normality
[11] Extreme value theory
[12] Modeling correlation

References

Jondeau, E., S.-H. Poon, and M. Rockinger (2006), Financial Modeling Under Non-Normality, Springer Finance. It is an advanced text book for both parts of course.

Campbell, J. Y., A. W. Lo, and A. C. MacKinlay (1997), The Econometrics of Financial Markets, Princeton University Press. It covers topics in the first part of the course.

Pre-requisites

Data Science for Finance

Evaluation

First attempt

Exam:
Written 3h00 hours
Documentation:
Not allowed
Calculator:
Allowed
Evaluation:

Projects: Projects typically consist in implementing the techniques studied during the lectures. There will be two projects:

- The first project covers Parts I and II of the course. The main objective is to describe the characteristics of some financial series.

- The second project covers Part III of the course. The objective consists in modelling the dynamics of daily returns and implementing allocation strategies based on these series. There is an oral presentation of the project during the last session of the course, which will count for the grade.

Let PR1 and PR2 be the grade for Project 1 and Project 2.

Final Examination: The final exam will cover the entire course. We call this grade FEG.

The overall grade will be given by the formula

20%*PR1 + 30%*PR2 + 50%*FEG

Retake

Exam:
Written 3 hours
Documentation:
Not allowed
Calculator:
Not allowed
Evaluation:

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



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