Journal of Risk Analysis and Crisis Response

Volume 6, Issue 3, October 2016, Pages 122 - 134

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

Authors
Meiling He, Shutao Qing, Jianming Mo, Xiang Gao
Corresponding Author
Meiling He
Received 26 April 2016, Accepted 2 July 2016, Available Online 3 October 2016.
DOI
10.2991/jrarc.2016.6.3.2How to use a DOI?
Keywords
operational risk; supervising parameters; elasticity theory; operational VaR
Abstract

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.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Risk Analysis and Crisis Response
Volume-Issue
6 - 3
Pages
122 - 134
Publication Date
2016/10/03
ISSN (Online)
2210-8505
ISSN (Print)
2210-8491
DOI
10.2991/jrarc.2016.6.3.2How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Meiling He
AU  - Shutao Qing
AU  - Jianming Mo
AU  - Xiang Gao
PY  - 2016
DA  - 2016/10/03
TI  - Connection Parameters of Heavy-tailed Operational Risk Measurement Model and Management Model
JO  - Journal of Risk Analysis and Crisis Response
SP  - 122
EP  - 134
VL  - 6
IS  - 3
SN  - 2210-8505
UR  - https://doi.org/10.2991/jrarc.2016.6.3.2
DO  - 10.2991/jrarc.2016.6.3.2
ID  - He2016
ER  -