Master Thesis Online
Predicting companies' ESG rating from their 10-K filings using a text mining approach
Roufosse, Benjamin 
Promotor(s) :
Ittoo, Ashwin
Date of defense : 2-Sep-2024/7-Sep-2024 • Permalink : http://hdl.handle.net/2268.2/21642
s184504_Benjamin_Roufosse_2024.pdfDetails
| Title : | Predicting companies' ESG rating from their 10-K filings using a text mining approach |
| Author : | Roufosse, Benjamin
|
| Date of defense : | 2-Sep-2024/7-Sep-2024 |
| Advisor(s) : | Ittoo, Ashwin
|
| Committee's member(s) : | Chuor, Porchourng
|
| Language : | English |
| Number of pages : | 19814 |
| Discipline(s) : | Business & economic sciences > Quantitative methods in economics & management |
| Institution(s) : | Université de Liège, Liège, Belgique |
| Degree: | Master en ingénieur de gestion, à finalité spécialisée en Supply Chain Management and Business Analytics |
| Faculty: | Master thesis of the HEC-Ecole de gestion de l'Université de Liège |
Abstract
[en] The goal of this thesis is to gain information from the 10-K fillings of listed companies using Text Mining techniques in order to predict their ESG rating.
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The University of Liège does not guarantee the scientific quality of these students' works or the accuracy of all the information they contain.