La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux

Abstract

La prédiction de la faillite des entreprises fait l ' objet de nombreux travaux empiriques , depuis une trentaine d ' années. Elle se fonde sur l ' analyse économique et financière d ' entreprises défaillantes et d ' entreprises non défaillantes , afin de déterminer les variables , principalement comptables , qui distinguent au mieux les deux catégories de firmes. Nous proposons un état des lieux afin de rendre compte de l ' efficacité relative des différentes méthodes de classification utilisées. Dans ce but , nous exposons la démarche commune tout en mettant en évidence les différentes modalités d ' application empirique. Nous présentons le principe des techniques disponibles et une comparaison de leur performance , en mettant l ' accent , de manière non exhaustive , à la fois sur les études fondatrices et sur les études les plus récentes. Mots-clés : prévision , faillite d ' entreprise , analyse financière Abstract A Review of Business Failure Prediction Based on Financial Analysis of the Firm Many studies of business failure prediction have been carried out in the last thirty years or so. Prediction is based on an economic and financial analysis of failing and non-failing firms with the aim of determining the variables , mainly of an accounting nature , that best distinguish the two categories. The purpose of this review is to assess the relative effectiveness of the different classification methods employed. To that end we identify the common elements while highlighting the different ways in which they are applied empirically. We describe the principle of the available techniques and compare their performance , focusing non-exhaustively on both the founding studies and on more recent research .

Financial Distress and Corporate Governance: The Impact of Board Configuration

“…Moreover, following a review of 190 studies related to the development of bankruptcy prediction models, Du Jardin (2009) reports that 93% of them include financial ratios. According to Refait (2004), the accounting measures that have the highest discriminating power in bankruptcy analysis are the profitability and the balance sheet structure. Therefore, we introduced the following accounting ratios in our model: the ROE (Mensah, 1984) and the solvency ratios (Altman, Marco, & Varetto, 1994).…”

A “User Friendly” Bankruptcy Prediction Model Using Neural Networks

“…An important part of the setting of the neural network is related to the selection of discriminant financial ratios. Solvency, liquidity and profitability ratios show very high discriminating power (Refait, 2004) regarding bankruptcy prediction. More precisely, we will use the following ratios that are used in many studies aiming to predict bankruptcy (Akers, et al, 2007) to train our neurons: total equity/total assets for solvency, current ratio for liquidity and EBIT/total assets for profitability ratio.…”

“…Studies regarding bankruptcy prediction generally aim to determine one or several variable(s) that make it possible to discriminate between bankrupt and healthy businesses (Refait, 2004). The pioneers are called Beaver (1966) and Altman (1968) using univariate and linear discriminant analyses, respectively.…”

Analisis Prediksi Kebangkrutan Perusahaan Menggunakan Artificial Neural Network Pada Sektor Pertambangan Batubara

“…Analisis rasio dapat dijadikan alat ukur untuk membantu manajemen dalam mengevaluasi kinerja perusahaan (Yuliastary dan Wirakusuma, 2014). Refait (2004), Brédart (2014) mengatakan bahwa rasio solvabilitas, likuiditas dan profitabilitas menunjukkan diskriminatif yang tinggi mengenai prediksi kebangkrutan.…”