In view of the failure of high profile companies like Circuit City and Linens n Things, Financial distress or bankruptcy prediction has generated much interest recently. This research develops and tests a model for the prediction of bankruptcy of retail firms. We use accounting variables such as...

This study develops a corporate bankruptcy classification model from a sample of 258 bankrupt and non-bankrupt companies, covering the period 1986-2008. Instead of depending on traditional ratios, it uses a simple exponential function-based algorithm to improve the stability of financial data....

This paper investigates how the process of going bankrupt can be recognized much earlier by enterprises than by traditional forecasting models. The presented studies focus on the assessment of credit risk classes and on determination of the differences in risk class migrations between...

The scientific community has demonstrated that for the bankruptcy prediction, different techniques have different advantages on different data sets and different feature selection approaches. This subject has attracted a lot of research interests as it is one of the major preoccupation of...

Bankruptcy filings are as high today as ever, calling into question the efficacy of existing bankruptcy prediction models. This paper tries to provide an alternative for bankruptcy prediction by integrated Multi Layered Perceptron with Imperialist Competitive Algorithm (MLP-ICA) and Kohonen self...

This paper is the first to compare the ability of the two structural credit risk models of Merton (1974) and Leland (1994a, b) to predict bankruptcy. We investigate different implementations of the Merton and Leland models on the whole CRSP/Compustat universe of firms from 1980 to 2015. Although...

Using a large panel of US banks over the period 2008-2013, this paper proposes an early warning framework to identify bank heading to bankruptcy. We conduct a comparative analysis based on both Canonical Discriminant Analysis and Logit models to examine and to determine the most accurate one....

This paper shows the evolution of financial distress prediction models of the past four decades. Special attention is paid to linear discriminant analyses, logistic regression analyses and neural networks. Based on accounting data of 50 UK industrial firms, prediction models are estimated using...

Previous research claims that industry-relative financial ratios are more stable than unadjusted ratios. Yet, most bankruptcy studies continue to use unadjusted financial ratios to develop bankruptcy-prediction models. In re-examining whether industry-relative ratios are actually more stable, we...

A financial market can be expressed in a network structure where the stocks resides as nodes and the links account for returns correlation. Centrality measure in the financial network structure captures firms' embeddedness and connectivity in the capital market structure. This paper investigates...