A Bayesian approach to estimate the marginal loss distributions in operational risk management

DOI10.1016/j.csda.2007.09.025zbMath1452.62788OpenAlexW2038168460MaRDI QIDQ1023645

Luciana Dalla Valle, Paolo Giudici

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.025

zbMATH Keywords

Markov chain Monte Carloexpected shortfallvalue at riskoperational riskloss distribution approachmarginal loss distribution

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15)

Related Items (9)

Bayesian copulae distributions, with application to operational risk management ⋮ Bayesian estimation of truncated data with applications to operational risk measurement ⋮ Modeling the yearly value-at-risk for operational risk in Chinese commercial banks ⋮ A threshold based approach to merge data in financial risk management ⋮ Asymptotic results for over-dispersed operational risk by using the asymptotic expansion method ⋮ Analysis of an aggregate loss model in a Markov renewal regime ⋮ A Bayesian h‐index: How to measure research impact ⋮ Editorial: Special issue on statistical and computational methods in finance ⋮ Clustering heteroskedastic time series by model-based procedures

Uses Software

• R

Cites Work

• Econometric specification of stochastic discount factor models
• Statistical decision theory and Bayesian analysis. 2nd ed
• Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms
• Convergence control methods for Markov chain Monte Carlo algorithms
• Functional correlation approach to operational risk in banking organizations
• Coherent Measures of Risk
• Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
• Sampling-Based Approaches to Calculating Marginal Densities
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• COMPARATIVE ANALYSES OF EXPECTED SHORTFALL AND VALUE-AT-RISK(Special Issue on Theory, Methodology and Applications in Financial Engneering)
• Equation of State Calculations by Fast Computing Machines
• Monte Carlo sampling methods using Markov chains and their applications
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