Comparison of support vector machine and support vector regression - An application to predict financial distress and bankruptcy

Mu Yen Chen, Chia Chen Chen, Ya Fen Chang

研究成果: Conference contribution

4 引文 斯高帕斯(Scopus)

摘要

Lately, many notorious financial distress and bankruptcy events occurred in the world economic. As we known, bankruptcy of Lehman Brothers Holdings Inc. (LEH) is the largest bankruptcy filing in U.S. history in 2008. These events have serious impacted on the socio-economic and investment in public wealth. Due to solve this dilemma, this research collected 68 listed companies as the raw data from Taiwan Stock Exchange Corporation (TSEC). The support vector machine (SVM) and support vector regression (SVR) techniques were used to implement the financial distress prediction model. Moreover, we adopted a total of 22 ratios which composed of 13 financial ratios and 9 macroeconomic indexes to be the input variables for these models. Finally, the experiments obtained the accuracy rate, Type II error rate and RMSE (root mean squared error) of these classification methods for the financial distress and bankruptcy prediction.

原文English
主出版物標題2010 7th International Conference on Service Systems and Service Management, Proceedings of ICSSSM' 10
頁面923-928
頁數6
DOIs
出版狀態Published - 2010
事件7th International Conference on Service Systems and Service Management, ICSSSM'10 - Tokyo, Japan
持續時間: 2010 6月 282010 6月 30

出版系列

名字2010 7th International Conference on Service Systems and Service Management, Proceedings of ICSSSM' 10

Conference

Conference7th International Conference on Service Systems and Service Management, ICSSSM'10
國家/地區Japan
城市Tokyo
期間10-06-2810-06-30

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 硬體和架構
  • 控制與系統工程

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