Implementing the Rearrangement Algorithm: An Example from Computational Risk Management

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ID: 111212
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 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Marius Hofert;Hofert, Marius;
Journal risks
Year 2020
DOI
10.3390/risks8020047
URL
https://doi.org/10.3390/risks8020047
Keywords
r implementation bootstrap computational risk management rearrangement algorithm worst value-at-risk allocation

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