Expectiles as basis risk-optimal payment schemes in parametric insurance

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<title>Expectiles as basis risk-optimal payment schemes in parametric insurance</title>
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<abstract displayLabel="Summary">The paper develops an analytical framework to minimize basis risk in parametric insurance by asymmetrically penalizing deviations between actual losses and payouts. Using the concept of expectiles, the authors derive optimal payment schemes for both pure parametric and parametric index insurance. The results establish that optimal compensations correspond to conditional expectiles of the insured's true loss, depending on the relative weight assigned to undercompensation versus overcompensation. The study links expectiles to coherent risk measures and stochastic orderings and proposes regression-based methods for practical implementation. Applications to agricultural insurance and cyber risk illustrate the relevance of the approach</abstract>
<note type="statement of responsibility">Markus Johannes Maier and Matthias Scherer</note>
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<text>21/12/2026 Volumen 22 Número 2 - 2026 , 34 p.</text>
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