Physical risk, modelled
How acute and chronic physical climate hazards are mapped to assets, facilities and supply chains — and why a portfolio's geographic footprint is the first thing a model has to get right.
What the journal covers
Editorial scope: climate risk analysis for investment portfolios.
The subjects we take seriously, and the order in which a reader new to this field can approach them. Everything below is free to read; nothing is sold.
Climate risk analysis tries to put a number on how a changing climate — and the policy and technology that respond to it — could move the value of an investment portfolio. Artificial intelligence sits inside that effort, mostly at the messy joins between inconsistent data. This page sets out the scope we write to.
The journal is editorial, not advisory. We do not publish buy or sell recommendations, portfolio ratings, or forecasts for specific securities. What we publish is reasoned explanation of how climate risk is modelled inside portfolios, and where artificial intelligence enters that modelling — for readers who want to understand the method well enough to judge claims made about it.
Topic areas
Four areas the journal returns to.
Transition risk, priced
How carbon prices, technology shifts and policy moves are translated into issuer-level exposure, and where machine learning helps reconcile inconsistent sector and emissions classifications.
Where AI helps — and fails
The honest map: where models add signal (disclosure reconciliation, non-linear exposure) and where they overreach (long-horizon point forecasts dressed up as analysis).
A reading path
How a new reader can work through it.
Read the scenario, not the headline
Start with what a warming pathway actually assumes. The scenario is the input to everything that follows; treating it as a forecast is the first common error.
Follow the exposure down to the issuer
Trace how a global scenario becomes a line on a specific company's balance sheet. This is where most of the modelling work — and most of the AI — actually lives.
Stress the portfolio, then question the weights
Push the issuer-level exposures through the portfolio's weights and ask which holdings are doing the work. The answer is often unintuitive for Taiwan-weighted books.
Ask what the model cannot know
Close by listing the assumptions the result depends on. A climate number without its assumptions listed is not analysis; it is a claim.
Inquiries
If a topic in this scope is missing, or you want us to take a question seriously, send it to the editor.