Quantifying Systemic Risk : conditional Interval Risk Measures and Their Applications

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<title>Quantifying Systemic Risk : conditional Interval Risk Measures and Their Applications</title>
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<namePart>Li, Junxue</namePart>
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<namePart>Zhang, Yi</namePart>
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<abstract displayLabel="Summary">This paper introduces two systemic risk measuresCoIVaR and CoIESthat extend traditional conditional risk metrics by conditioning on quantile intervals to better capture uncertainty and contagion effects. A comprehensive theoretical framework is developed, including key properties and risk contribution measures, along with comparison results based on stochastic orders and dependence structures. Numerical experiments and stock market applications demonstrate that these interval-based measures provide robust and practical tools for assessing systemic risk in interconnected financial systems</abstract>
<note type="statement of responsibility">Limin Wen, Junxue Li and Yi Zhang</note>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>19/01/2026 Volume 56 Issue 1 - January 2026 , p. 181 - 205</text>
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