An empirical study for the detection of corporate financial anomaly using outlier mining techniques

Mei Chih Chen*, Ren Jay Wang, An-Pin Chen

*Corresponding author for this work

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

5 Scopus citations

Abstract

The financial operations of Taiwanese companies are becoming increasingly complex as a greater number of products are introduced into the market as a result of financial deregulation and recent reforms in Taiwan's financial markets. As financial statements are not able to fully reflect the actual state of companies' finances, many crises have occurred. Many investors are suffering from these crises, due to framing effect. This study investigates the outlying behavior of financial activities by using the outlier mining method to build models to predict financial crises. It uses local outlier factor (LOF) values to measure the outlying behavior among peer groups to gauge the financial performance of companies. This study tests its model on Taiwan's publicly-listed IC manufacturers and CDR makers. The result of the empirical study showed that the LOF value indicated the financial anomalies of these companies and confirm that this model can effectively provide advance warning to investors.

Original languageEnglish
Title of host publication2007 International Conference on Convergence Information Technology, ICCIT 2007
Pages612-617
Number of pages6
DOIs
StatePublished - 1 Dec 2007
Event2nd International Conference on Convergent Information Technology, ICCIT 07 - Gyongju, Korea, Republic of
Duration: 21 Nov 200723 Nov 2007

Publication series

Name2007 International Conference on Convergence Information Technology, ICCIT 2007

Conference

Conference2nd International Conference on Convergent Information Technology, ICCIT 07
CountryKorea, Republic of
CityGyongju
Period21/11/0723/11/07

Keywords

  • Financial Anomaly
  • Framing Effect
  • Local Outlier Factor
  • Outlier Mining

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