We set out in this study to review a vast amount of recent literature on machine learning (ML) approaches to predicting financial distress (FD), including supervised, unsupervised and hybrid supervised-unsupervised learning algorithms. Four supervised ML models including the traditional support...

Eine große Herausforderung der multivariablen Analyse mit bilanziellen Kennzahlen besteht in der Identifikation derjenigen Kennzahlen, die zur besten Modellperformance führen und dabei möglichst leicht interpretierbar und intuitiv bleiben. Die Menge der in Frage kommenden Kennzahlen ist in...

We hypothesize and find empirical evidence that two structural constraints of the industry are informative in the corporate failure prediction, industry concentration and dependence on customers and suppliers. Using an extensive database on corporate failures and bankruptcies in U.S. market from...

This paper examines the performance of two commonly applied bankruptcy prediction models, the accounting ratio-based Altman Z-Score model, and the structural Distance to Default model which currently underlies Morningstar's Financial Health Grade for public companies (Morningstar 2008)....

We argue that the true transition-to-default dynamic in banks' credit portfolios can only be fully described with a multiple-spell discrete-time hazard model. This paper develops such a model for default prediction. The model permits the use of all data available to the bank or to the bank...

This paper addresses the theoretical foundations of corporate failure prediction, using the neo-classical theory of capital structure as a starting point. The paper intends to demonstrate the feasibility of such an approach in a simple setting, i.e. by using a simple theoretical model and a...

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...

While there is an increasing interest in crypto-assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we consider a unique data set on 144 exchanges active from the first quarter of 2018 to the first quarter of 2021. We analyze the determinants of the...

The aim of this article is to prove the key role of the structure of the research sample used for accuracy determining on the accuracy of bankruptcy models. The creators of these models report the accuracy usually in the range of 60 to 90%. The authors of this article claim that these values are...

Co-operative movement dawned in India a century ago to eradicate indebtedness and to accelerate agricultural production in India. Co-operatives are eminently suited to achieve social, economic changes in rural India. However, credit risk is acute in co-operative credit system, predominantly...