INTRODUCTION A L'ECONOMETRIE DE LA FINANCE

Professeur

GAELLE LE FOL -Professor in Finance, Head of the Master 203, Université Paris - Dauphine

Les objectifs du cours

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 the advanced course in Econometrics of Financial Markets. If Gretl will be the econometric software used in the course, it is possible to use R.

Plan du cours

• How to build an econometric model and how to use it?
• The (simple and multiple) linear regression model
• Inference, hypothesis testing and prediction
• Specification and diagnostic testing (heteroskedasticity, autocorrelation, model specification)
• Selection criteria
• Alternative to OLS (2SLS, ML, GLS, Quantile regression)

Bibliographie

Adkins L. C., Using gretl for Principles of Econometrics, Version 1.041, August 2018, Free copy

Brooks C., Introductory Econometrics for Finance, Second Edition, Cambridge University Press, 2014

Gelman A., J. Hill and A. Vehtari, 2021, Regression and Other Stories, 1st Edition, Cambridge University Press, 2021

Gujarati D., Basic Econometrics, McGraw Hill Higher Education; 5th Revised edition edition, 2009

Hill C., W. Griffiths and G. Lim, Principles of Econometrics, Wiley, 5th Edition, 2018

Le Fol G., A (very) short introduction to Gretl using scripts, Mimeo, 2022.

Examen

1 final exam

Prerequisits: 

• in mathematics: "Mathematics for Economics and Business", Iran J., 9th Edition, 2018, Pearson.
• in statistic: "Statistics for Business and Economics", Newbold P., W. Carlson, B.Thorne, 8th Edition, 2013, Pearson Education.
• in programming: Gretl turorial for beginners (using scripts) or Very short introduction to R