Implementing the Rearrangement Algorithm: An Example from Computational Risk Management
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2020
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Abstract
After a brief overview of aspects of computational risk management, the implementation of the rearrangement algorithm in R is considered as an example from computational risk management practice. This algorithm is used to compute the largest quantile (worst value-at-risk) of the sum of the components of a random vector with specified marginal distributions. It is demonstrated how a basic implementation of the rearrangement algorithm can gradually be improved to provide a fast and reliable computational solution to the problem of computing worst value-at-risk. Besides a running example, an example based on real-life data is considered. Bootstrap confidence intervals for the worst value-at-risk as well as a basic worst value-at-risk allocation principle are introduced. The paper concludes with selected lessons learned from this experience.
| Reference Key |
hofert2020risksimplementing
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| Authors | Marius Hofert;Hofert, Marius; |
| Journal | risks |
| Year | 2020 |
| DOI |
10.3390/risks8020047
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