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Applied Extreme Value Theory: Modeling Rare Events in Finance, Climate, and Risk is a practical guide for analysts, scientists, and policymakers who need to understand and manage extreme events. From market crashes and catastrophic floods to major insurance losses, this book turns complex statistical theory into actionable tools.
Covering sixteen chapters, it begins with foundational probability concepts and the Extremal Types Theorem before moving into core techniques such as Block Maxima and Peaks-Over-Threshold modeling, parameter estimation, diagnostics, and multivariate extensions. Applications are explored in finance, climate science, and risk management, including value-at-risk calculations, stress testing, heatwave projections, and reinsurance pricing.
With hands-on implementations in R and Python, detailed case studies, and discussions on non-stationarity and ethical considerations, this book empowers readers to quantify tail risks and make informed, resilient decisions in an uncertain world.
Practical guidance on modeling rare events in finance, climate, and risk management
Step-by-step instructions for Block Maxima and Peaks-Over-Threshold methods
Parameter estimation, diagnostics, and multivariate extensions
Real-world case studies using R and Python
Insights on non-stationarity, ethics, and emerging research frontiers
