Pena Centeno, Tonatiuh and Martinez Jaramillo, Serafin and Abudu, Bolanle (2009): Predicción de bancarrota: Una comparación de técnicas estadísticas y de aprendizaje supervisado para computadora.
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We are interested in forecasting bankruptcies in a probabilistic way. Specifcally, we com- pare the classification performance of several statistical and machine-learning techniques, namely discriminant analysis (Altman's Z-score), logistic regression, least-squares support vector machines and different instances of Gaussian processes (GP's) -that is GP's classifiers, Bayesian Fisher discriminant and Warped GP's. Our contribution to the field of computa- tional finance is to introduce GP's as a potentially competitive probabilistic framework for bankruptcy prediction. Data from the repository of information of the US Federal Deposit Insurance Corporation is used to test the predictions.
|Item Type:||MPRA Paper|
|Original Title:||Predicción de bancarrota: Una comparación de técnicas estadísticas y de aprendizaje supervisado para computadora|
|English Title:||Bankruptcy prediction: a comparison of some statistical and machine learning techniques|
|Keywords:||Bankruptcy prediction, Artificial intelligence, Supervised learning, Gaussian processes, Z-score.|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General
C - Mathematical and Quantitative Methods > C4 - Econometric and Statistical Methods: Special Topics > C45 - Neural Networks and Related Topics
C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General
|Depositing User:||Tonatiuh Pena Centeno|
|Date Deposited:||25. Jan 2010 13:51|
|Last Modified:||17. Feb 2014 17:49|
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