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

Published: December 8, 2025 | arXiv ID: 2512.07787v1

By: Nawaf Mohammed

Potential Business Impact:

Makes financial risk predictions more accurate.

Business Areas:
A/B Testing Data and Analytics

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.

Page Count
49 pages

Category
Quantitative Finance:
Risk Management