Overview

Level up your actuarial and analytics toolkit with the most complete, implementation-focused guide to catastrophe portfolios and tail risk. This intensive, 33-chapter blueprint takes you from rigorous theory to exam-style multiple-choice reinforcement and straight into production-ready Python code-chapter by chapter. Who it's for Actuaries, catastrophe modelers, and reinsurance analysts ERM leaders and capital modelers building internal models Data scientists and quantitative researchers entering insurance risk What you'll master Extreme Value Theory end to end: domains of attraction, GEV/POT, tail index estimators, declustering, and nonstationary extremes Spatial/spatiotemporal extremes, conditional extremes, and tail dependence for multi-peril portfolios Full catastrophe model pipeline: hazard → exposure → vulnerability → financial terms → portfolio roll-up Year-event tables, OEP/AEP/CDEP, PML and Tail-VaR, uncertainty bands, and secondary uncertainty Rare-event simulation (importance sampling, subset simulation) for extreme quantiles and exceedance probabilities Reinsurance structuring and optimization; ILS, triggers, and basis risk analytics Climate conditioning, trend-aware EVT, model validation, and governance Build real portfolios, not toy examples Calibrate thresholds, tail indices, and return levels on sparse, messy data Construct EP curves with uncertainty overlays; attribute risk by region/peril/layer Simulate occurrence and aggregate treaties with reinstatements and hours clauses Quantify and manage basis risk for indemnity, parametric, and modeled-loss triggers Stress-test nonstationarity and compound events (e.g., wind-surge-rain) Why this book Dense, practitioner-grade coverage with a direct line to real decisions Designed for on-the-job impact: each topic closes with runnable Python workflows Bridges actuarial rigor and catastrophe engineering, so you can price, allocate capital, and communicate tail risk with confidence Upgrade your models, tighten your capital, and outpace uncertainty. Start building industrial-grade catastrophe analytics today.

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