catastrophe-modelling

Loss modelling framework.

A repository for modelling and analysing multi-degree-of-freedom systems for response characterisation of global building classes

File validation and data sampling toolkit for the Simplitium Open Exposure Data (OED) (re)insurance exposure data format

A Python command-line utility for Linux that computes the economic loss for hurricanes in Florida and in the Gulf states

Pricing and trigger-design engine for rainfall-index parametric crop insurance. Gamma/Weibull index fitting, Monte Carlo pricing with risk loadings, 40-year backtest, and quantified basis-risk analysis showing 33% of genuine loss years go uncompensated.

Location-level Florida hurricane catastrophe model in Python: HURDAT2-calibrated hazard + physical wind field (Holland, Vickery-Wadhera, Kaplan-DeMaria), synthetic exposure, HAZUS-anchored vulnerability, OED/YLT/ELT formats, XoL reinsurance with reinstatements, gross/net AEP/OEP curves & PMLs, historical backtesting (Andrew, Ian).

Monte Carlo simulation modelling flood-related financial losses in South Africa using probabilistic risk analysis.

Final Project for Leiden University Media Technology MSc. involving an advanced processing sketch that simulates the effect of catastrophe types on Faraday Wave pattern morphology during audiovisual playback. All code by Trent Eriksen and inspired by research from Amber van der Tuin

Eradicate all the silliness this year has given us ⚡

Scenario earthquake damage and risk for Germany: GEM building exposure disaggregated to a 1 km grid, OpenQuake hazard library, interactive map dashboard

Compatibility-first R pipeline for cross-country earthquake damage modelling. Harmonises asset-level building-damage data from Nepal (2015 Gorkha), Türkiye (2023) and Japan (2024 Noto), benchmarks within-country models, runs Nepal–Türkiye transfer, and isolates compatibility vs. classifier effects via simulation.

Monte Carlo catastrophe risk model using NOAA HURDAT2 Atlantic hurricane data to estimate Expected Annual Loss (EAL), exceedance probabilities, and tail risk.

This repo serves as a guide for understanding what extreme value theory is, using the genextreme package.

Climate-conditioned tropical cyclone risk model for coastal Odisha, covering hazard, exposure, vulnerability, loss, climate sensitivity and CAT XL pricing.

R package: design parametric windstorm covers for UK regions and measure their basis risk, using public data (ERA5, LitPop)