Robust neural modeling for the cross-sectional analysis of accounting information |
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| Authors: | Manuel Landajo Javier de Andrés Pedro Lorca |
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| Institution: | 1. Unit of Statistics and Econometrics, Department of Applied Economics, University of Oviedo, Avenida del Cristo s/no, 33006 Oviedo, Spain;2. Department of Business Administration and Accounting, University of Oviedo, 33006 Oviedo, Spain |
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| Abstract: | The performance of robust artificial neural network models in learning bivariate relationships between accounting magnitudes is assessed in this paper. Predictive performances of a number of modeling paradigms (namely, linear models, log-linear structures, classical ratios and artificial neural networks) are compared with regard to the problem of modeling a number of the most outstanding accounting ratio relations. We conduct a large scale analysis, carried out on a representative Spanish data base. |
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| Keywords: | Artificial neural networks Accounting ratios Economic analysis Robust regression Simulation |
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