2 résultats pour « Catastrophic Events. »
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The insurance sector faces pressure from rising catastrophic risks, leading to higher premiums and policy non-renewals. This paper proposes an arbitrage-free method for pricing catastrophe reinsurance using the compound dynamic contagion process and Esscher transform. The findings help insurers assess liabilities amid emerging risks like climate change, cyberattacks, and pandemics.
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This research develops a mathematical model using Extreme Value Theory and Risk Measures to estimate and forecast major fire insurance claims, enhancing insurers' understanding of potential risks. Utilizing a three-parameter Generalized Pareto Distribution in the Extreme Value Theory framework, the study effectively models large losses, aiding in risk management and pricing strategies for insurance firms.
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