VaR at Its Extremes: Impossibilities and Conditions for One-Sided Random Variables

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1. Verfasser: Mohammed, Nawaf
Format: Preprint
Veröffentlicht: 2025
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author Mohammed, Nawaf
author_facet Mohammed, Nawaf
contents We investigate the extremal aggregation behavior of Value-at-Risk (VaR) -- that is, its additivity properties across all probability levels -- for sums of one-sided random variables. For risks supported on \([0,\infty)\), we show that VaR sub-additivity is impossible except in the degenerate case of exact additivity, which holds only under co-monotonicity. To characterize when VaR is instead fully super-additive, we introduce two structural conditions: negative simplex dependence (NSD) for the joint distribution and simplex dominance (SD) for a margin-dependent functional. Together, these conditions provide a unified and easily verifiable framework that accommodates non-identical margins, heavy-tailed laws, and a wide spectrum of negative dependence structures. All results extend to random variables with arbitrary finite lower or upper endpoints, yielding sharp constraints on when strict sub- or super-additivity can occur.
format Preprint
id arxiv_https___arxiv_org_abs_2512_07787
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle VaR at Its Extremes: Impossibilities and Conditions for One-Sided Random Variables
Mohammed, Nawaf
Risk Management
Probability
We investigate the extremal aggregation behavior of Value-at-Risk (VaR) -- that is, its additivity properties across all probability levels -- for sums of one-sided random variables. For risks supported on \([0,\infty)\), we show that VaR sub-additivity is impossible except in the degenerate case of exact additivity, which holds only under co-monotonicity. To characterize when VaR is instead fully super-additive, we introduce two structural conditions: negative simplex dependence (NSD) for the joint distribution and simplex dominance (SD) for a margin-dependent functional. Together, these conditions provide a unified and easily verifiable framework that accommodates non-identical margins, heavy-tailed laws, and a wide spectrum of negative dependence structures. All results extend to random variables with arbitrary finite lower or upper endpoints, yielding sharp constraints on when strict sub- or super-additivity can occur.
title VaR at Its Extremes: Impossibilities and Conditions for One-Sided Random Variables
topic Risk Management
Probability
url https://arxiv.org/abs/2512.07787