Master 2 - MBFA / MBFI (2021-today)
Python 2.0 et introduction à l'apprentissage statistique / Python 2.0 and introduction to statistical learning
(Cours Magistraux / Lectures)
This lesson extends kearnings on python and basic notions and models of statistical learning.
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Master 2 - MBFA / MBFI
Microéconométrie / Microeconometrics (2023-today)
(Cours Magistraux / Lectures)
Shared lesson in which students are introduced to some panel data techniques under python and SAS. I manage the python part of the course: introduction to logit model, multinomial logit, qualitative variables and rare event treatment.
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Master 1 - MBFA / MBFI
Économétrie en finance / Econometrics in finance (2021-today)
(Cours Magistraux / Lectures)
This lesson deals with econometrics, finance and the informatic language python. The purpose of this lecture is to (re)introduce econometric modelling basis: from Ordinary Least Sqaure in simple linear regression to a first overview of time series analysis. Financial examples are given and applications are run using python.
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Master 1 - MBFA / MBFI
Introduction à python / Introduction to python (2021-today)
(Cours Magistraux / Lectures)
This lesson consists in an important introduction to informatic language allowing for econometric applications. The two first thirds are dedicated to the learning of programming basis. Last third consists in an introduction to the basic tools for data analysis and applied econometrics using R and Python. This lecture complements "Econometrics in finance".
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Master 1 - Economie Appliquée / Applied Economics
Statistiques : simulations / Statistics: simulations (2025-today)
(Cours Magistraux / Lectures)
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Licence 2
Statistiques / Statistics (2021-2025)
Probabilité / Probability (2021-2022)
(Cours Magistraux-Travaux Dirigés / Lectures-Tutorials)
Statistics: a first approach of linear regression using knowledge of algebra, probability and analysis.
Probability: introduction to random variable (discrete and continue) and cenrtal limit theorem.
Course materials (all in Jupyter Notebook, databases in .xlsx, .csv, .txt) are available here.
Master 2 - Gestion Des Actifs / Asset Management
Exploitation des données massives en finance / Big data exploitation in finance
(Cours Magistraux / Lectures)
Introduction to the use and challenges around big data. First part of the lesson deals with the definition of big data, technical issues associated with massive datasets and web-scrapping. Second part of the lesson presents some machine learning techniques suitable for big data analysis. Two examples of robot-advisors are introduced using random forest classification and artificial neural network regression.
Due to the sanitary conditions, the last session took place online : the video is available on YouTube.
Master 1 - Économie Appliquée & MBFA / Applied Economics & MBFI
Économétrie sous R et Python / Econometrics under R and Python
(Cours Magistraux - Travaux Dirigés / Lectures - Tutorials)
This lesson consists in an important introduction to informatic language allowing for econometric applications. The two first thirds are dedicated to the learning of programming basis. Last third consists in an introduction to the basic tools for data analysis and applied econometrics using R and Python. For consistency matters, this course was only given under Python in 2019 and 2020.
Due to the sanitary conditions, all sessions took place online and are available on the YouTube channel EconomiX601.
Master 1 - Économie Appliquée & MBFA / Applied Economics & MBFI
Atelier d'économétrie / Econometrics workshop
(Cours Magistraux - Travaux Dirigés / Lectures - Tutorials)
Econometrics workshop is consecutive to the "Econometrics under R and Python" lesson: more specification tests and procedures, sophisticated models and issued associated with data treatment are addressed. A focus is made on how to conduct an econometric analysis (from economic theory to the model implementation and interpretation of results). Evaluation takes the form of a dissertation.
Due to the sanitary conditions, all sessions took place online and are available on the YouTube channel EconomiX601.
Master 1 - Économie Appliquée & MBFA / Applied Economics & MBFI
Économétrie des séries temporelles / Time series econometrics
(Travaux Dirigés / Tutorials)
Econometrics reminder (OLS, relaxation of standard OLS assumptions) and introduction to time series analysis (stationnarity and cointegration).
Licence 3 - Économie & Gestion / Economics & Management
Pratique de l'économétrie / Applied econometrics
(Cours Magistraux - Travaux Dirigés / Lectures - Tutorials)
Introduction to Python and the use of this language for econometrics purposes. A large part of this lesson is common to "Econometrics under R and Python".
Due to the sanitary conditions, all sessions took place online and are available on the YouTube channel EconomiX601.
Licence 1 - Économie & Gestion / Economics & Management
Macroéconomie A / Macroeconomics A
(Travaux Dirigés / Tutorials)
Introduction to the main macroeconomic aggregates and standard growth and consumption models.