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...

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....

This study is intended to identify the predictors of financial distress for the Pakistani firms. Variables used are the financial ratios representing profitability, liquidity, leverage, and cash flows, as well as two important market factors which are size and idiosyncratic standard deviation of...

One of the elements of company's evaluation is an analysis of bankruptcy risk metrics. In this study, the accuracy of bankruptcy predictions generated by EBITDA-based and cash flow-based liabilities-coverage ratios is evaluated within a sample of data from the Polish market. The study is based...

One of the elements of company’s evaluation is an analysis of bankruptcy risk metrics. In this study, the accuracy of bankruptcy predictions generated by EBITDA-based and cash flow-based liabilities-coverage ratios is evaluated within a sample of data from the Polish market. The study is based...

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields...

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 study aims to shed light on the debate concerning the choice between discrete-time and continuous-time hazard models in making bankruptcy or any binary prediction using interval censored data. Building on the theoretical suggestions from various disciplines, we empirically compare widely...

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...