Risk aggregation and stochastic dominance for a class of heavy-tailed distributions

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      <subfield code="a">Distributions with infinite mean are ubiquitous in the realm of banking and insurance, and they are particularly useful in modeling catastrophic losses (Ibragimov et al., 2009), operational losses (Moscadelli, 2004), costs of cyber risk events (Eling andWirfs, 2019), and financial returns from technology innovations (Silverberg and Verspagen, 2007); see also Chen andWang (2025) for a list of empirical examples of distributions with infinite mean. This paper focuses on establishing some stochastic dominance relations for infinite-mean models</subfield>
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