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.

1. 서론
 2. 이론적 배경
  2.1 Value at Risk (VaR)
  2.2 Back-testing
  2.3 Bayes' theorem
 3. 연구 방법
  3.1 Forecasting VaR
  3.2 Distribution for exception ratio
  3.3 Bayesian hypothesis testing
  3.4 Bayes factor (BF)
 4. 실증 연구
  4.1 Descriptive statistics
  4.2 Results analysis
 5. 결론
 참고문헌

• 이유나(한양대학교)
• 김성도(한양대학교)
• 윤덕균(한양대학교)