Integrating Financial Ratios and Data Envelopment Analysis in Business Financial Failure–Using Rough Set, Support Vector Machine and Decision Tree
碩士 === 中國文化大學 === 會計研究所 === 96 === Corporate financial failure prediction is of critical importance for decision making of managers , investors and shareholder. In current financial failure prediction models, various financial ratio are usually selected as prediction variables, which implicated that...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2008
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/95166257951878983681 |
| Summary: | 碩士 === 中國文化大學 === 會計研究所 === 96 === Corporate financial failure prediction is of critical importance for decision making of managers , investors and shareholder. In current financial failure prediction models, various financial ratio are usually selected as prediction variables, which implicated that these financial ratio represent the possible cause of financial failure. They always neglect the management operation efficiency. In this study, we use data envelopment analysis(DEA) are employed as a tool to evaluate the input/output efficiency of each corporation. We compare the accuracy of the same prediction model with and without the variable. Experimental results of three main financial prediction models, Rough Set(RS)、Support Vector Machine(SVM)、Decision Tree(DT), all suggest that the DEA is an effective predictor variable.
|
|---|