The application of Genetic Algorithm and Data Envelopment Analysis to bankruptcy prediction: A comparative study
Journal Title: Journal of Science and today’s world - Year 2014, Vol 3, Issue 1
Abstract
The high social costs associated with bankruptcy have spurred searches for better theoretical understanding and prediction capability. Using an additive super-efficiency data envelopment analysis (DEA) model and genetic algorithm (GA), this paper develops a new assessment index based on two frontiers for predicting corporate failure and success. The proposed approach is applied 70 bankrupt and 70 healthy matching firms in Tehran Stock Exchange. This sample represents the largest firms that went bankrupt over the period 2004–2010 and represents a full spectrum of industries. Our findings demonstrate that the DEA and GA models is relatively weak in predicting corporate failures compared to healthy firm predictions, and the assessment index improves this weakness by giving the decision maker various options to achieve different precision levels of bankrupt, non-bankrupt, and total predictions.
Authors and Affiliations
Ahmad Abdollahi
Keywords
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