Operational Risk Management Based on Bayesian MCMC

被引：1
|
作者：
Zou, Qingzhong [1 ]
Li, Jinlin [1 ]
Ran, Lun [1 ]
机构：
[1] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
来源：
IACSIT-SC 2009: INTERNATIONAL ASSOCIATION OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY - SPRING CONFERENCE | 2009年
关键词：
operational risk; loss distribution approach; beyesian; markov chain monte carlo; GB2; distribution;
D O I：
10.1109/IACSIT-SC.2009.40
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The aim of this paper is to introduce a new framework for operational risk management, based on Bayesian Markov chain Monte Carlo (MCMC). Under the LDA approach, non-conjugate distribution is used to fit the frequency and severity. One of the problems relative to the non-conjugate distribution is difficult to estimate the parameter. Then the Bayesian MCMC approach is brought forward. The Bayesian is implemented to obtain the posterior of non-conjugate distribution, the MCMC algorithm is employed to estimate the posterior parameters. The Bayesian MCMC framework is strongly recommended in the operational risk management as it incorporate internal and external loss data observations in combination with expert opinion. A numerical example is constructed to illustrate the performance of the framework advocated by this paper.
引用
收藏
页码：236 / 239
页数：4
相关论文
共 50 条
  • [1] Study on operational risk management in commercial banks based on Bayesian networks
    Li, Bo
    Xu, Cong-wei
    Quan, Cong-na
    [J]. PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON RISK AND RELIABILITY MANAGEMENT, VOLS I AND II, 2008, : 110 - 113
  • [2] Bayesian Copulae Distributions, with Application to Operational Risk Management
    Luciana Dalla Valle
    [J]. Methodology and Computing in Applied Probability, 2009, 11 : 95 - 115
  • [3] Bayesian Copulae Distributions, with Application to Operational Risk Management
    Dalla Valle, Luciana
    [J]. METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 2009, 11 (01) : 95 - 115
  • [4] Erratum to: Bayesian Copulae Distributions, with Application to Operational Risk Management
    Luciana Dalla Valle
    [J]. Methodology and Computing in Applied Probability, 2012, 14 : 1121 - 1121
  • [5] Bayesian network based dynamic operational risk assessment
    Barua, Shubharthi
    Gao, Xiaodan
    Pasman, Hans
    Mannan, M. Sam
    [J]. JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES, 2016, 41 : 399 - 410
  • [6] Bayesian operational risk models
    Figini, Silvia
    Gao, Lijun
    Giudici, Paolo
    [J]. JOURNAL OF OPERATIONAL RISK, 2015, 10 (02): : 45 - 60
  • [7] A Bayesian approach to estimate the marginal loss distributions in operational risk management
    Valle, L. Dalla
    Giudici, P.
    [J]. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2008, 52 (06) : 3107 - 3127
  • [8] Bayesian Copulae Distributions, with Application to Operational Risk Management—Some Comments
    Philipp Arbenz
    [J]. Methodology and Computing in Applied Probability, 2013, 15 : 105 - 108
  • [9] Bayesian analysis of panel data based on mcmc
    Zhang, Xia-Tao
    [J]. PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 1167 - 1171
  • [10] Operational Risk Control of Commercial Banks based on Bayesian Network
    Hao, Xiaoling
    [J]. PROCEEDINGS OF THE 2013 THE INTERNATIONAL CONFERENCE ON EDUCATION TECHNOLOGY AND INFORMATION SYSTEM (ICETIS 2013), 2013, 65 : 913 - 918
12345