위험관리에서의 베이지안 이론을 활용한 Value at Risk 사후검증

• 영문명: Back-testing Value at Risk(VaR) Models in Risk Management under a Bayesian Perspective
• 발행기관: 한국산업경영시스템학회
• 저자명: 이유나 김성도 윤덕균
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2008년 춘계학술대회 논문집, 76~83쪽, 전체 8쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2008.05.30

영문 초록

When comparing the traditional financial risk measurements, Value at Risk(VaR) has its benefits for providing a single number that summarizes the overall market risk of the portfolio. Considering the fact that VaR measurement is standardized as a tool for international market risk measurement, back-testing the accuracy and performance of the VaR models plays a crucial role. In this sense, this paper proposes a way to validate the accuracy of the VaR models. Firstly, Bayes factor is used to assess statistical accuracy of the models. For the next step, loss function is applied to measure the differences between the realized and expected losses. Through the procedure, back-testing VaR models considering both frequency and magnitude of violations and comparing between the models can be achieved.

목차

1. 서론

2. 이론적 배경

3. 연구 방법

4. 실증 연구

5. 결론

키워드

Value-at-Risk back-testing model assessment Bayes factor