Underwriting Cycles in Property-Casualty Insurance: The Impact of Catastrophic Events
نویسندگان
چکیده
This paper challenges the question of existence and predictability underwriting cycles in U.S. property casualty insurance industry. Using an approach frequency domain, we demonstrate a hidden periodic component annual aggregated loss ratios. The data support cycle length 8–9 years. Going beyond previous research studying almost 30 years quarterly data, can improve forecasting performance by (dis)connecting catastrophic events. Superior out-of-sample forecast results from models with intervention variables flagging time point outbreaks is achieved terms mean squared/absolute errors. We evaluate model confidence sets containing most accurate certain level. analysis suggests that reliable forecasts be net irregular major peaks distributions arise natural catastrophes as well unusual “black swan”
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ژورنال
عنوان ژورنال: Risks
سال: 2023
ISSN: ['2227-9091']
DOI: https://doi.org/10.3390/risks11040075