Implementing the Rearrangement Algorithm: An Example from Computational Risk Management

Marius Hofert
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Marius Hofert: Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada

Risks, 2020, vol. 8, issue 2, 1-28

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.

Keywords: computational risk management; rearrangement algorithm; implementation; R; bootstrap; worst value-at-risk allocation (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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