Prediction of corporate failure using past financial data is a well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis , logit, and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which tradit...

Does an entrepreneur-friendly bankruptcy law encourage more entrepreneurship development at a societal level? How does bankruptcy law affect entrepreneurship development around the world? Drawing on a real options perspective, we argue that if bankrupt entrepreneurs are excessively punished for failure, they may pass potentially high-return but inherently high-risk opportunities. Amassing a lon...

The aim of this study is to investigate the effects of corporate governance mechanisms in preventing the bankruptcy of companies listed in Tehran Stock Exchange. For this purpose, corporate governance mechanisms, including institutional ownership, non-executive members of the board, CEO dual responsibility and free float stock are determined as independent variables and Bankruptcy based on the ...

Bankruptcy prediction and credit scoring have long been regarded as critical topics and have been studied extensively in the accounting and finance literature. Artificial intelligence and machine learning techniques have been used to solve these financial decision-making problems. The multilayer perceptron (MLP) network trained by the back-propagation learning algorithm is the mostly used techn...

In the last decade, there was a rapid growth in the availability and use of credit for Brazilian companies. Until recently, the decision to grant credit was based on human trial to evaluate the risk of insolvency. Increased demand from companies for credit has led to the use of more accurate models for bankruptcy prediction. In recent years much progress has occurred in the process of drawing u...

This study proposes an efficient non-parametric classifier for bankruptcy prediction using an adaptive fuzzy k -nearest neighbor (FKNN) method, where the nearest neighbor k and the fuzzy strength parameter m are adaptively specified by the particle swarm optimization (PSO) approach. In addition to performing the parameter optimization for FKNN, PSO is utilized to choose the most discriminative ...

Personal bankruptcy Ž lings have risen from 0.3 percent of households per year in 1984 to around 1.35 percent in 1998 and 1999, transforming bankruptcy from a rare occurrence to a routine event. Lenders lost about $39 billion in 1998 due to personal bankruptcy Ž lings. But economists have little understanding of why households Ž le for bankruptcy or why Ž lings have increased so rapidly. Until ...

Estimation risk occurs when individuals form beliefs about parameters that are unknown. We examine how auditors respond to the estimation risk that arises when they form beliefs about the likelihood of client bankruptcy. We argue that auditors are likely to become more conservative when facing higher estimation risk because they are risk-averse. We find that estimation risk is of first-order im...