The ability to predict bank failure has become much more important since the mortgage foreclosure crisis began in 2007. The model proposed in this study uses proxies for the regulatory standards embodied in the so-called CAMELS rating system, as well as several local or national economic...

In this paper, we compare the performance of two non-parametric methods of classification, Regression Trees (CART) and the newly Multivariate Adaptive Regression Splines (MARS) models, in forecasting bankruptcy. Models are implemented on a large universe of US banks over a complete market cycle...

In credit default prediction models, the need to deal with time-varying covariates often arises. For instance, in the context of corporate default prediction a typical approach is to estimate a hazard model by regressing the hazard rate on time-varying covariates like balance sheet or stock...

We argue that the Merton (1974) model's relatively high ability to forecast bankruptcy stems from its ability to capture either the chance of net worth dropping below an externally-imposed threshold or of an economic insolvency. Using unique bankruptcy data from fifteen countries, our evidence...

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...

The aim of the study is to establish insolvency forecast model with the usage of different statistical methods and compare their efficiency. Besides this the relation and direction between indebtedness and financial distress is also part of the examination. With different approaches we nearly...

The risk associated with lending to small businesses has become more important since regulations started obliging banks to use separate procedures in assessing SMEs' credit worthiness. However, current accounting-based models for SMEs do not account for the impact of market information on...

We develop a model to predict bankruptcies, exploiting that negative book equity is a strong indicator of financial distress. Accordingly, our key predictor of bankruptcy is the probability that future losses will deplete a firm's book equity. To calculate this probability, we use earnings...

Previous studies targeting accuracy improvement of default models mainly focused on the choice of the explanatory variables and the statistical approach. We alter the focus to the choice of the dependent variable. We particularly explore whether the common practice (in literature) of using...