Determinación del riesgo de fracaso financiero mediante la utilización de modelos paramétricos, de inteligencia artificial, y de información de auditoría

  1. Manuel Rodríguez López
  2. Carlos Piñeiro Sánchez
  3. Pablo de Llano Monelos
Revista:
Estudios de economía

ISSN: 0304-2758 0718-5286

Ano de publicación: 2014

Volume: 41

Número: 2

Páxinas: 187-217

Tipo: Artigo

DOI: 10.4067/S0718-52862014000200002 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Outras publicacións en: Estudios de economía

Obxectivos de Desenvolvemento Sustentable

Resumo

This paper offers an exhaustive analysis of the effectiveness of several models and methodologies that are commonly used to forecast financial failure: Linear, MDA, Logit, and artificial neural network. Our main aim is to evaluate their relative strengths and weaknesses, in terms of technical reliability and error cost; to do so, models are estimated and validated, and then used to perform an artificial simulation to evaluate which of them causes the lower cost of errors. Reliability is examined in four forecast horizons, to collect evidences about temporal (in) stability. We also check the relative advantages of financial ratios-based models, versus audit-based forecast models. Our results suggest that all models attain a high performance rate; however, artificial neural networks' forecasts seem to be more stable, both in temporal and cross-sectional perspectives.

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