The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy....

Using a local adaptive Forward Intensities Approach (FIA) we investigate multiperiod corporate defaults and other delisting schemes. The proposed approach is fully datadriven and is based on local adaptive estimation and the selection of optimal estimation windows. Time-dependent model...

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 develop distress prediction models for non-financial small and medium sized enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power...

Poor corporate governance can damage the interests of shareholders, and may lead to company collapse. Previous studies in credit risk prediction provide no consensus as to which and how corporate governance variables determine bankruptcy. This paper is the first to apply a discrete time hazard...

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...

This paper investigates the role of industry-specific effects and structural properties of intersectoral customer-supplier relations on the corporate default prediction of individual firms. We focus on a large sample of US exchange-listed companies over the period 1997- 2015 and show that...

A firm's current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in...

A firm's current leverage ratio is one of the core characteristics of credit quality used in statistical default prediction models. Based on the capital structure literature, which shows that leverage is mean-reverting to a target leverage, we forecast future leverage ratios and include them in...