Reinsurance and Alternative Capital - Structures, Pricing, and ILS With Python

The complete actuarial toolkit for modern reinsurance and alternative capital-rigorous, practical, and code-first.

This hands-on, densely engineered resource takes you from first principles to production-grade pricing for treaties, retro, and ILS. Built for working actuaries, underwriters, catastrophe modelers, risk managers, and ILS investors, it turns complex structures into clear, executable frameworks you can run and audit.

Structure you can rely on:

33 tightly written chapters
Each chapter: core theory → exam-style multiple-choice questions → fully runnable Python code demonstrations
Consistent actuarial framing: expected loss, tail metrics (TVaR), capital consumption, cost of capital, and model risk

What you’ll be able to do:

Price proportional and non-proportional treaties, including aggregate covers and reinstatements
Convert catastrophe model output into AAL, OEP/AEP curves, TVaR, and technical rates
Build a defensible view-of-risk by blending models and accounting for climate nonstationarity
Design and price ILWs, cat options, parametric triggers, and modeled/indemnity/industry cat bonds
Structure and evaluate sidecars and fully collateralized reinsurance, including trapped collateral economics
Quantify counterparty credit risk, collateral sufficiency, and wrong-way risk
Apply EVT and copulas for tail modeling, Panjer/FFT and Monte Carlo for aggregates, and portfolio optimization with capital allocation

Inside the code:

Fully commented Python demos for treaty rating, reinstatements, aggregate stop-loss, ILW and parametric triggers, cat bond expected loss/multiples, sidecar cashflows, basis risk simulation, EVT/copula fitting, Panjer/FFT, and portfolio capital allocation
Built on the standard scientific stack (NumPy, pandas, SciPy, statsmodels, and efficient simulation techniques) to go from indication to production-quality prototypes

Who it’s for:

Pricing and capital actuaries, catastrophe modelers, and risk managers
Reinsurance underwriters and brokers seeking quantitative, defensible indications
ILS portfolio managers and analysts optimizing spreads, liquidity, and correlation
Advanced students and faculty adopting a code-first actuarial curriculum

Level up your reinsurance and ILS decisions with a resource that doesn’t just explain- it computes. Add this to your desk and your toolkit now.