Connection Parameters of Heavy-tailed Operational Risk Measurement Model and Management Model

• Main Authors: Meiling He, Shutao Qing, Jianming Mo, Xiang Gao
• Format: Article
• Language: English
• Published: Atlantis Press 2016-09-01
• Series: Journal of Risk Analysis and Crisis Response (JRACR)
• Subjects: operational risk; supervising parameters; elasticity theory; operational VaR
• Online Access: https://www.atlantis-press.com/article/25863591.pdf

In order to connect the heavy-tailed operational risk measurement model with management model, a model identifying the crucial supervising parameters of operational risk is built after the heavy-tailed operational VaR’s sensitivity is theoretically researched by the elasticity analysis method. Further, the analysis of model application is illustrated with a numerical example. The crucial supervising parameters connect the operational risk measurement model and management model, which make the operational risk management frameworks to be a complete system. And a dynamical supervising system of operational risk is established. This research in theory improves the application of loss distribution approach to the operational risk measurement and management.