Skip to main content
Springer Nature Link
Log in

How to deal with the data in a bankruptcy modelling

  • Conference paper
Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems

  • 678 Accesses

Abstract

This article presents results of a survey that has been led in this year in the University of Szczecin. The aim of the survey was to find a neural model that would be able to predict a bankruptcy of a firm with a high rate of precision. The problem of bankruptcy prediction is broadly discussed in the economic literature and a lot of highly efficient models built via different modelling techniques have been developed in this field so far. The reason why this problem is once more touched in this article is connected with the data involved to the model.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Back B. Laitinen T. Sere K. Wezel M. 1996. ‘Choosing Bankruptcy Predictors Using Discriminant Analysis, Logit Analysis, and Genetic Algorithms’. Technical Raport No 40. Turku Centre for Computer Science.

    Google Scholar 

  2. Demuth H. Beale M. 2000 ‘Neural Network Toolbox User’s Guide’. The Math Works Inc. Natick MA USA.

    Google Scholar 

  3. Piegat A. 1999. ‘Fuzzy Modelling and Control’. Physica-Verlag. New, York.

    Google Scholar 

  4. Poddig T. 1995. ‘Bankruptcy Prediction: A Comparison with Discriminant Analysis’. Neural Networks in the Capital Markets. John Wiley$Sons. Chichester.

    Google Scholar 

  5. Sugeno M. Yasukawa T. A. 1993. ‘A Fuzzy-Logic-Based Approach to Qualitative Modelling’. IEEE Transaction on Fuzyy Systems. vol. 1, no. 1, February.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Uuniversity of Szczecin, Mickiewicza 64, Szczecin

    Rejer Izabela

Authors
  1. Rejer Izabela
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Technical University of Szczecin, Poland

    Jerzy Pejaś  & Andrzej Piegat  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer Science+Business Media, Inc.

About this paper

Cite this paper

Izabela, R. (2005). How to deal with the data in a bankruptcy modelling. In: Pejaś, J., Piegat, A. (eds) Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems. Springer, Boston, MA. https://doi.org/10.1007/0-387-23484-5_31

Download citation

  • DOI: https://doi.org/10.1007/0-387-23484-5_31

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7776-0

  • Online ISBN: 978-0-387-23484-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics