A genetic programming model for bankruptcy prediction: Empirical evidence from Iran
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- @Article{Etemadi20093199,
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title = "A genetic programming model for bankruptcy prediction:
Empirical evidence from Iran",
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author = "Hossein Etemadi and Ali Asghar Anvary Rostamy and
Hassan Farajzadeh Dehkordi",
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journal = "Expert Systems with Applications",
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volume = "36",
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number = "2, Part 2",
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pages = "3199--3207",
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year = "2009",
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ISSN = "0957-4174",
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DOI = "DOI:10.1016/j.eswa.2008.01.012",
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URL = "http://www.sciencedirect.com/science/article/B6V03-4RSRDDN-4/2/acecffea7c551388162fae4dfbe2a6e2",
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keywords = "genetic algorithms, genetic programming, Bankruptcy
prediction, Financial ratios, Multiple discriminant
analysis, Iranian companies",
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abstract = "Prediction of corporate bankruptcy is a phenomenon of
increasing interest to investors/creditors, borrowing
firms, and governments alike. Timely identification of
firms' impending failure is indeed desirable. By this
time, several methods have been used for predicting
bankruptcy but some of them suffer from underlying
shortcomings. In recent years, Genetic Programming (GP)
has reached great attention in academic and empirical
fields for efficient solving high complex problems. GP
is a technique for programming computers by means of
natural selection. It is a variant of the genetic
algorithm, which is based on the concept of adaptive
survival in natural organisms. In this study, we
investigated application of GP for bankruptcy
prediction modeling. GP was applied to classify 144
bankrupt and non-bankrupt Iranian firms listed in
Tehran stock exchange (TSE). Then a multiple
discriminant analysis (MDA) was used to benchmarking GP
model. Genetic model achieved 94percent and 90percent
accuracy rates in training and holdout samples,
respectively; while MDA model achieved only 77percent
and 73percent accuracy rates in training and holdout
samples, respectively. McNemar test showed that GP
approach outperforms MDA to the problem of corporate
bankruptcy prediction.",
- }
Genetic Programming entries for
Hossein Etemadi
Ali Asghar Anvary Rostamy
Hassan Farajzadeh Dehkordi
Citations