A forward intensity model for the prediction of corporate defaults over different future periods is proposed. Maximum pseudo-likelihood analysis is then conducted on a large sample of the US industrial and financial firms spanning the period 1991-2011 on a monthly basis. Several commonly used...

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...

The purpose of this study was to develop a new bankruptcy prediction framework that considers a wider range of factors beyond traditional financial ratios and improve the efficiency and accuracy of bankruptcy prediction models in the Indian ecosystem. The financial statements of three Indian...

In this paper, we evaluate an alternative approach for bankruptcy prediction that measures the financial healthiness of firms that have coupon-paying debts. The approach is based on the framework of Leland and Toft (1996), which is an extension of a widely-used model; the Black-Scholes-Merton...

We use a vector error correction model to study the long-term relationship between aggregate expected default frequency and the macroeconomic development, i.e. CPI, industry production and short-term interest rate. The model is used to forecast the median expected default frequency of the...

This study proposes a simple theoretical framework that allows for assessing financial distress up to five years in advance. We jointly model financial distress by using two of its key driving factors: declining cash-generating ability and insufficient liquidity reserves. The model is based on...