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Performing Bayesian Risk Aggregation using Discrete Approximation Algorithms with Graph Factorization
[article]
2015
arXiv
pre-print
Risk aggregation is a popular method used to estimate the sum of a collection of financial assets or events, where each asset or event is modelled as a random variable. Applications, in the financial services industry, include insurance, operational risk, stress testing, and sensitivity analysis, but the problem is widely encountered in many other application domains. This thesis has contributed two algorithms to perform Bayesian risk aggregation when model exhibit hybrid dependency and high
arXiv:1506.01056v1
fatcat:foskcu5b7vgmzfkkkhr2ubehxi