Explanation

Understanding-oriented material: the why and how it works behind OasisLMF.

These pages are co-located with the code they describe so that a change in behaviour and its explanation travel together in the same pull request. This is the core of the documentation strategy — see DOCS_STRATEGY.md.

Financial Module

The conceptual model and the Python/NumPy implementation of the Financial Module (oasislmf/pytools/fm):

Financial Module

• Financial Module
• Financial Module — architecture

Ground-up loss modelling

How ground-up losses are simulated by the Monte-Carlo engine (oasislmf/pytools/gulmc): the modelling methodology, sampling, correlation, disaggregation, and coverage dependency.

Ground-up loss

• Modelling methodology
• Sampling Methodology
• Correlation
• Disaggregation
• Coverage dependency (gulmc)

Adjustments & methodology

Adjustments applied around the core loss calculation — vulnerability and damage adjustments, post-loss amplification, pre-analysis exposure adjustments, and currency conversion:

Adjustments & methodology

• Vulnerability Adjustments
• Absolute Damage
• Post Loss Amplification
• Pre Analysis Adjustments
• Currency Conversion

Models

What an Oasis model is made of — its components and structure:

Models

• Oasis Models

Keys & lookup

How exposure is matched to model data (areaperil and vulnerability IDs) via the keys / lookup service (oasislmf/lookup):

Keys & lookup

• Keys Service
• Geocoding

The corresponding API reference for these subsystems is generated directly from the source in Reference, so explanation and reference sit side by side.