earticle

논문검색

텍스트마이닝 방법론을 활용한 기업 부도 예측 연구

원문정보

The Prediction of Corporate Bankruptcy Using Text-mining Methodology

최정원, 한호선, 이미영, 안준모

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Traditional corporate bankruptcy prediction methodology basically relies on financial accounting data to objectively reflect the status of companies. However, since financial accounting data is difficult to immediately reflect changes in the status of companies, real-time financial data such as stock and bond prices are also used in order to make up for the shortcomings. In this study, we use news text information which is a typical real-time information to study the corporate bankruptcy prediction models. In the past, news text information was difficult to use in quantitative analysis but not any more due to the recent advances of information processing technology and text-mining techniques. For bankruptcy prediction using news information, we collect news text for six months before the bankruptcy events of companies actually occur and study the possibility of bankruptcy prediction based on the data by utilizing text-mining techniques. Results indicate that we can not get such a high level of predictability as that of existing corporate bankruptcy prediction models, but that there exists a high potential of this approach enough to increase the predictability of bankruptcy models. Further research on bankruptcy prediction model using news text information will be promising.

목차

Ⅰ. 서론
 Ⅱ. 연구방법론
 Ⅲ. 실증분석
 Ⅳ. 결론 및 제언
 참고문헌
 Abstract

저자정보

  • 최정원 Jung-won Choi. 딜로이트안진, 건국대학교 경영학과 박사과정
  • 한호선 Ho-sun Han. 유세스파트너스, 건국대학교 경영정보학과 박사과정
  • 이미영 Mi-young Lee. 건국대학교 경영정보학과 교수
  • 안준모 Jun-mo Ahn. 건국대학교 경영정보학과 교수

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 기관로그인 시 무료 이용이 가능합니다.

      • 6,700원

      0개의 논문이 장바구니에 담겼습니다.