Asymptotic Behaviour of Unexpected Losses and Risk Ratios for Co-Monotonic Alternatives
Max Nendel

TL;DR
This paper analyzes the asymptotic behavior of unexpected losses and risk ratios in large credit and insurance portfolios, establishing convergence properties and potential underestimation risks under diversification.
Contribution
It provides new theoretical results on the asymptotics of unexpected losses and risk ratios for large portfolios using monotone risk measures and Choquet premiums.
Findings
Unexpected losses are of order o(nar{n}_n) for large portfolios.
Convergence of risk measures is equivalent to scalar continuity at zero.
Risk ratios quantify underestimation when comparing diversified portfolios to co-monotonic ones.
Abstract
The aggregation of individual risks in large credit and insurance portfolios is guided by diversification and the law of large numbers, which formalizes the convergence of sample averages to their means. At the same time, regulatory capital requirements and insurance premia are designed to provide a capital buffer or risk margin above the mean. The resulting excess, given by the difference between the nonlinear valuation of the aggregate loss and the corresponding mean, reflects the idea of protection against unexpected losses in the sense of banking and insurance regulation. This paper studies the asymptotic behaviour of this excess for large weighted portfolios. The main result shows that, for monotone cash-additive risk measures on Banach-lattice-valued Orlicz spaces, convergence along weighted averages satisfying a weak law of large numbers together with a uniform integrability…
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