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Trigueiros, D. & Sam, C. (2018). Discovering the optimal set of ratios to use in accounting-based models. International Journal of Society Systems Science. 10 (2), 110-131
D. M. Trigueiros and C. Sam, "Discovering the optimal set of ratios to use in accounting-based models", in Int. Journal of Society Systems Science, vol. 10, no. 2, pp. 110-131, 2018
@article{trigueiros2018_1732211456525, author = "Trigueiros, D. and Sam, C.", title = "Discovering the optimal set of ratios to use in accounting-based models", journal = "International Journal of Society Systems Science", year = "2018", volume = "10", number = "2", doi = "10.1504/IJSSS.2018.10013669", pages = "110-131", url = "http://www.inderscience.com/jhome.php?jcode=ijsss" }
TY - JOUR TI - Discovering the optimal set of ratios to use in accounting-based models T2 - International Journal of Society Systems Science VL - 10 IS - 2 AU - Trigueiros, D. AU - Sam, C. PY - 2018 SP - 110-131 SN - 1756-2511 DO - 10.1504/IJSSS.2018.10013669 UR - http://www.inderscience.com/jhome.php?jcode=ijsss AB - Ratios are the prime tool of financial analysis. In predictive modelling tasks, however, the use of ratios raises difficulties, the most obvious being that, in a multivariate setting, there is no guarantee that the collection of ratios eventually selected as predictors will be optimal in any sense. Using, as starting-point, a formal characterisation of cross-sectional accounting numbers, the paper shows how the multilayer perceptron can be trained to create internal representations which are an optimal set of ratios for a given modelling task. Experiments suggest that, when such ratios are utilised as predictors in well-known modelling tasks, performance improves on that reported by the extant literature. ER -