The role of non-financial features related to corporate governance in business crisis prediction

Fengyi Lin, Deron Liang, Wing Sang Chu

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Recent outbreak of corporate financial crises worldwide has brought attention to the need for a new international financial architecture which rests on crisis prediction and crisis management. It is therefore both desirable and vital to explore new predictive techniques for providing early warnings aganist bankruptcy. Financial data have been widely used by researchers to predict financial distress or business crisis, but few studies exploit the use of non-financial indicators related to corporate governance to construct business crisis prediction model. This article introduces into the field of business crisis prediction model based on a combination of both financial and corporate governance related non-financial data. The experiment results show that the combined use of both financial and non-financial features with SVM model leads to a more accurate prediction of financial distress.

Original languageEnglish
Pages (from-to)504-513
Number of pages10
JournalJournal of Marine Science and Technology (Taiwan)
Volume18
Issue number4
StatePublished - Aug 2010

Keywords

  • Corporate governance
  • Financial prediction
  • Support vector machines

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