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X-WR-CALNAME:AKTUARVEREINIGUNG ÖSTERREICHS (AVÖ)
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DTSTART;TZID=Europe/Vienna:20270212T093000
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DTSTAMP:20260910T084841Z
CREATED:20260910T084841Z
LAST-MODIFIED:20260910T084841Z
UID:10000695-1802424600-1802437200@avoe.at
SUMMARY:Tail Risk Measurement: Estimation\, Sensitivity\, Uncertainty
DESCRIPTION:Regulatory frameworks such as Solvency II require non-life insurers to quantify extreme risks — most notably the 99.5% Value-at-Risk over a one-year horizon for the Solvency Capital Requirement (SCR). In practice\, however\, this poses a fundamental challenge: historical loss data contains little to no information about such rare events\, making direct estimation inherently unreliable. \nThis web session addresses exactly this gap. It provides participants with a structured and practical toolkit to estimate high-confidence risk measures from limited data — and\, crucially\, to understand and communicate the uncertainty involved\, enabling more robust risk quantification\, particularly in contexts such as SCR validation and ORSA. \nStarting with classical parametric approaches and kernel density estimation\, the course progresses to Extreme Value Theory (EVT)\, with a focus on the Peaks-over-Threshold (POT) method and the Generalised Pareto Distribution (GPD). Particular attention is given to threshold selection and to Bayesian formulations in which the threshold is treated as an uncertain parameter\, enabling posterior-predictive inference for high quantiles. We also consider flexible bulk-tail mixture models that combine non-parametric bulk estimation with an EVT-based tail component. \nFor each method\, the course takes a structured perspective across four dimensions: \n\nthe point estimator and its finite-sample properties\,\nparameter uncertainty and confidence intervals\,\nsensitivity to modelling assumptions\, and\noverall model uncertainty.\n\nFinally\, we connect tail risk modelling to practical risk steering by linking estimated risk measures to capital allocation via the Euler (gradient) principle\, enabling a decomposition into marginal risk contributions across business units or risk types. \nFor the core methods\, participants apply estimation procedures in hands-on R exercises using real non-life insurance loss data\, developing both technical proficiency and the critical judgement required to interpret results. \nThe course provides a critical overview of methods for estimating tail risk at high confidence levels under real-world data constraints\, examining where and why they differ in their conclusions. \nR exercises on real non-life insurance data illustrate the methods in practice\, with particular attention to the interpretation and limitations of the resulting estimates.
URL:https://avoe.at/event/tail-risk-measurement-estimation-sensitivity-uncertainty/
CATEGORIES:European Actuarial Academy (EAA)
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