Artikel

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

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.

Language
Spanisch

Bibliographic citation
Journal: Estudios de Economía ; ISSN: 0718-5286 ; Volume: 41 ; Year: 2014 ; Issue: 2 ; Pages: 187-217 ; Santiago de Chile: Universidad de Chile, Departamento de Economía

Classification
Wirtschaft
Bankruptcy; Liquidation
Neural Networks and Related Topics
Data Collection and Data Estimation Methodology; Computer Programs: Other
Subject
financial failure
financial difficulties
forecast insolvency
audit report

Event
Geistige Schöpfung
(who)
Rodríguez, Manuel
Piñeiro, Carlos
de Llano Monelos, Pablo
Event
Veröffentlichung
(who)
Universidad de Chile, Departamento de Economía
(where)
Santiago de Chile
(when)
2014

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Rodríguez, Manuel
  • Piñeiro, Carlos
  • de Llano Monelos, Pablo
  • Universidad de Chile, Departamento de Economía

Time of origin

  • 2014

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