Earticle

초록

영어

The purpose of this study is to evaluate financial models that can predict corporate bankruptcy with diverse studies on evaluation models. The study uses discriminant analysis, logistic model, decision tree, neural networks as analyses tools with 18 input variables as major financial factors. The study found meaningful variables such as current ratio, return on investment, ordinary income to total assets, total debt turn over rate, interest expenses to sales, net working capital to total assets and it also found that prediction performance of suggested method is a bit low compared to that in literature review. It is because the studies in the past uses the data set on the listed companies or companies audited from outside. And this study uses data on the companies whose credibility is not verified enough. Another finding is that models based on decision tree analysis and discriminant analysis showed the highest performance among many bankruptcy forecasting models.

목차

Abstract
1. 서론
2. 기업부실의 원인과 징후
2.1 기업의 부실화 진행과정
2.2 기업부실의 유형
2.3 기업의 부실징후
2.4 부실징후 발견방법
3. 신용평가 모델
3.1 신용평가의 의의
3.2 신용평가 요소
3.3 부실예측모형의 종류
4. 데이터 수집과 변수선정
4.1 표본기업의 선정
4.2 변수의 선정
4.3 연구방법론 및 자료처리
5. 모델의 기본 테스트
5.1 T-test
5.2 다변량 로지스틱 분석
5.3 단변량모형별 유의성 검정
5.4 상관관계 분석
6. 부실예측모형의 성과 비교
6.1 다변량 로지스틱스 회귀분석
6.2 판별분석
6.3 인공신경망 모형
6.4 의사결정나무
7. 결론 및 시사점
참고문헌

저자

• 오우석 [ Woo-Seok Oh | 서강대학교 경영학과 ]
• 김진화 [ Jin-Hwa Kim | 서강대학교 경영하과 ]

참고문헌