Three-State Financial Distress Prediction Based on Support Vector Machine | SpringerLink
Skip to main content

Three-State Financial Distress Prediction Based on Support Vector Machine

  • Conference paper
Advances in Neural Networks – ISNN 2009 (ISNN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Included in the following conference series:

Abstract

This paper examines the three-state financial distress prediction using support vector machine (SVM) and compares the classification results with the one using multinominal logit analysis(MLA).The results show that SVM provides better three-state classification than MLA. The model using SVM has better generalization than the model using MLA.

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

Access this chapter

Subscribe and save

Springer+ Basic
¥17,985 /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
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 17159
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 21449
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

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. Altman, E.I., Hotchkiss, E.: Corporate Financial Distress and Bankruptcy. John Wiley & Sons Inc., New York (2005)

    Book  Google Scholar 

  2. Beaver, W.H.: Financial Ratios as Predictors of Failure, Empirical Research in Accounting: Selected Studies. Journal of Accounting Research 4(suppl.1), 79–111 (1966)

    Google Scholar 

  3. Altman, E.I.: Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance 9, 589–690 (1968)

    Article  Google Scholar 

  4. Ohlson, J.: Financial Ratio and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research 18, 109–131 (1980)

    Article  Google Scholar 

  5. Odom, M., Sharda, R.A.: Neural Networks Model for Bankruptcy Prediction. In: IEEE International Conference on Neural Network, vol. 2, pp. 163–168. IEEE Press, New York (1990)

    Google Scholar 

  6. Lau, H.: A Five State Financial Distress Prediction Model. Journal of Accounting Research 25, 127–138 (1987)

    Article  Google Scholar 

  7. Ward, T.J.: An Empirical Study of the Incremental Predictive Ability of Beaver’s Naive Operating Flow Measure Using Four-State Ordinal Models of Financial Distress. Journal of Business Finance and Accounting 7, 547–561 (1994)

    Article  Google Scholar 

  8. Wu, S.N., Lu, X.Y.: The Financial Distress Prediction Research of Chinese Listed Corporations. Economic Research Journal 6, 46–55 (2001)

    Google Scholar 

  9. Yang, S., Huang, L.: Firms Warning Model Based on BP Neural Networks. Systems Engineering Theory and Practice 1, 12–18 (2005)

    Google Scholar 

  10. Vapnik, V.N.: Statistical Learning Theory. Electric Industrial Publishing House, Beijing (2004)

    MATH  Google Scholar 

  11. Hearst, M.A., Dumais, S.T., Osman, E., Platt, J., Schölkopf, B.: Support Vector Machines. IEEE Intelligent Systems 13(4), 18–28 (1998)

    Article  Google Scholar 

  12. Hsu, C.W., Lin, C.J.: A Comparison of Methods for Multi-class Support Vector Machines, Technical report, National Taiwan University, Taiwan (2001)

    Google Scholar 

  13. Hensher, D.A., Rose, D., Greene, W.: Applied Choice Analysis: A Primer. Cambridge University Press, Cambridge (2005)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yao, H. (2009). Three-State Financial Distress Prediction Based on Support Vector Machine. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_47

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01510-6_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics