Prédiction de faillite: Application de deux modèles de prédiction de faillite sur des entreprises belges
Promotor(s) : Van Caillie, Didier
Date of defense : 6-Sep-2016/12-Sep-2016 • Permalink :
|Title :||Prédiction de faillite: Application de deux modèles de prédiction de faillite sur des entreprises belges|
|Translated title :||[fr] Prédiction de faillite: Application de deux modèles de prédiction de faillite sur des entreprises belges|
|Author :||Chekroun, Iliass|
|Date of defense :||6-Sep-2016/12-Sep-2016|
|Advisor(s) :||Van Caillie, Didier|
|Committee's member(s) :||Sougné, Danielle
|Discipline(s) :||Business & economic sciences > General management & organizational theory|
|Institution(s) :||Université de Liège, Liège, Belgique|
|Degree:||Master en ingénieur de gestion, à finalité spécialisée en Performance Management and Control|
|Faculty:||Master thesis of the HEC-Ecole de gestion de l'Université de Liège|
[en] The major objective of this thesis is to provide useful and practical information that could be used by economic actors. The main goal is to assess whether two theoretical models could be used in order to predict bankruptcy. We have divided this work into two distinct parts.
In the first part of this work, we will focus more on the theoretical aspects. Firstly, we will define a few key concepts that will be extensively used throughout our thesis. Secondly, we will summarize the main researches that have been done regarding this field of study. Finally, we will develop two bankruptcy prediction models (Model Beaver (1966) and the model of Van Caillie (2005)), which will be implemented into the second half of the work.
In the second part of the thesis, we will move on to its practical side. We will select a hundred companies (fifty that went bankrupt and fifty that didn’t go bankrupt) on which we will apply both models. On this basis, we will evaluate the relative effectiveness of those and try to determine which model is the most predictive and what are the main reasons that lead to bankruptcy.
Cite this master thesis
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