This work analyzes inclusion relationships among distribution classes for infinite-mean random variables and derives necessary and sufficient conditions for stochastic dominance preservation in convex combinations and compound binomial cases.
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The paper establishes coherence, convexity, and time-consistency properties for expected-maximum-deficit risk measures and derives exact analytical solutions for optimal aggregate minimum reserves under fixed and proportional tolerances.
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Further Developments on Stochastic Dominance for Convex Combinations of Infinite-Mean Random Variables
This work analyzes inclusion relationships among distribution classes for infinite-mean random variables and derives necessary and sufficient conditions for stochastic dominance preservation in convex combinations and compound binomial cases.
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On the Expected Maximum Deficit and the Optimal Allocation of Reserves
The paper establishes coherence, convexity, and time-consistency properties for expected-maximum-deficit risk measures and derives exact analytical solutions for optimal aggregate minimum reserves under fixed and proportional tolerances.