The study of a financial crisis prediction model based on XBRL

Fengyi Lin, Deron Liang, Shih Jung Chin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 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. Financial data have been widely used by researchers to predict financial crisis, but few studies exploit the use of non-financial indicators in corporate governance to construct financial crisis prediction model. This article introduces a prediction model based on a relatively new machine learning technique, support vector machines (SVM) with XBRL financial reporting. This study indicates that the prediction model considering both financial and non-financial information outperforms those models based on only one type of information. Two well-known prediction models, regression model and genetic algorithm, are compared with SVM. 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
Title of host publicationProc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications
Pages147-153
Number of pages7
DOIs
StatePublished - 2008
Event9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 in conjunction with 2nd International Workshop on Advanced Internet Technology and Applications, AITA 2008 - Phuket, Thailand
Duration: 6 Aug 20088 Aug 2008

Publication series

NameProc. 9th ACIS Int. Conf. Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 and 2nd Int. Workshop on Advanced Internet Technology and Applications

Conference

Conference9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2008 in conjunction with 2nd International Workshop on Advanced Internet Technology and Applications, AITA 2008
Country/TerritoryThailand
CityPhuket
Period6/08/088/08/08

Keywords

  • Corporate governance
  • Financial prediction
  • Non-financial features
  • Predictive process
  • Support vector machines

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