Logit business failure prediction in V4 countries

Dating Business Cycle in Oil Exporting Countries

In this paper, we empirically investigate the relationship between oil price changes and output in a group of oil exporting countries. The dynamics of business cycles in Libya, Saudi Arabia, Nigeria, Kuwait, Venezuela and Qatar are modeled by alternative regime switching models. We show that the extension of uni-variate Markov Switching model in order to include oil revenue improves dating busi...

Business failure prediction using rough sets

A large number of methods like discriminant analysis, logit analysis, recursive partitioning algorithm, etc., have been used in the past for the prediction of business failure. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt ®rms, they su€er from some limitations, often due to the unrealistic assumption of statistical hypoth...

A Hybrid Business Success Versus Failure Classification Prediction Model: A Case of Iranian Accelerated Start-ups

The purpose of this study is to reduce the uncertainty of early stage startups success prediction and filling the gap of previous studies in the field, by identifying and evaluating the success variables and developing a novel business success failure (S/F) data mining classification prediction model for Iranian start-ups. For this purpose, the paper is seeking to extend Bill Gross and Robert L...

Leading Indicators of the Business Cycle: Dynamic Logit Models for Oecd Countries and Russia

Failure prediction in the Russian bank sector with logit and trait recognition models

The Russian banking sector experienced considerable turmoil in the late 1990s, especially around the Russian banking crisis in 1998. The question is what types of banks are vulnerable to shocks and whether or not bank-specific characteristics can be used to predict vulnerability to failures. In this study we employ a parametric logit model and a nonparametric trait recognition approach to predi...