Ects : 3

Enseignant responsable :

• GAELLE LE FOL

Volume horaire : 24

Description du contenu de l'enseignement :

Introduction : issues and problems of financial econometrics ; Simple and multiple regression models ; Statistical inference and regression quality ; Hypotheses and tests of the hypotheses of the linear regression model ; Applications : linear regression models in finance.

Pré-requis recommandés :

A first cours in programming

Pré-requis obligatoires :

Applied statistics, Financial Mathematics (BSc. in Economics and Management Level)

Coefficient : 0.5 (MI Finance - Formation Initiale) Pas de coefficient, ni de crédit ECTS pour le parcours "Research in Finance"

Compétence à acquérir :

This course is an introduction and/or refresher course in Econometrics that focuses on techniques for estimating regression models, on problems commonly encountered in estimating such models, and on interpreting the estimates. The goal is to provide participants with the basic skills and knowledge necessary to undertake empirical research and to prepare them to more advanced course in Econometrics for Finance. Gretl will be the econometric software used in the course (alternatively, R can be used). If some theoretical aspects will be studied, the focus is more on the acquisition of a scientific empirical approach.

Concretely, this course will allow students to

• keep a critical eye on econometrics results,
• acquire a method to answer economic and financial questions in a quantified manner
• to use this knowledge to carry out basics empirical studies in finance.

Bibliographie, lectures recommandées

Adkins, L., 2018, Using Gretl for Principles of Econometrics, 5th Edition, Version 1.0, http: ; Brooks C., 2019, Introductory Econometrics for Finance, 4th Edition, Cambridge University Press, 724 pages ; Carter Hill R., W. E. Griffiths and G.C. Lim, 2018, Principles of Econometrics, 5th Edition, John Wiley & Sons, 912 pages.