Firm Bankruptcy Prediction Using Multiple Criteria Linear Programming Data Mining Approach

Wikil Kwak ； Yong Shi ； John J. Cheh

《Advances in Investment Analysis and Portfolio Management》 2期 (2006/11) Pp. 27-49

https://doi.org/10.6291/AIAPM.2006.02.03

並列摘要

Data mining applications are growing rapidly in today's dynamic business environment as one of a manager's most useful decision making tools. Many applications have been used in accounting areas where accountants deal with large amounts of computerized operational and financial databases. There are higher potential payoffs for data mining applications in these areas. The purpose of this research is to propose a multiple criteria linear programming (MCLP) approach to data mining for bankruptcy prediction. A MCLP data mining approach has recently been applied to credit card portfolio management. This approach has proven to be robust and powerful even for a large sample size using a huge financial database. The results of the MCLP approach in a bankruptcy prediction study are promising as this approach performs better than traditional multiple discriminant analysis or logit analysis using financial data. Similar approaches can be applied to other accounting areas such as fraud detection, forecasting stock performance, detection of tax evasion, and an audit-planning tool for financially distressed firms.

並列關鍵字

bankruptcy ； data mining ； multiple criteria linear programming

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