Algorithmic insurable risk portfolios

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      <subfield code="a">This article proposes an algorithmic framework for the management of insurable risk portfolios using constrained optimization techniques, inspired by Markowitz's portfolio theory. The approach makes it possible to determine optimal levels of risk retention and risk transfer by considering measures such as Value at Risk and Expected Shortfall. A methodology based on simulation and multivariate risk measures is developed, applicable to the non-linear risks commonly encountered in insurance. The model is illustrated through a case study of a large organization, showing how the results complement expert decision-making in risk management. In addition, the robustness of the model and its sensitivity to different assumptions are analyzed</subfield>
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      <subfield code="g">16/03/2026 Tomo 30 Número 1 - 2026 , 17 p.</subfield>
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