Commissioned by the Cambridge Institute of Sustainability Leadership (CISL) Investment Leaders Group (ILG), this ground-breaking report looks at the economic and financial impacts of climate risk modelled over the next five years in order to identify opportunity for reducing climate-related investment risks through portfolio construction and diversification across different asset classes, regions, and portfolios.
Overview
The most significant physical impacts of climate change will probably be seen in the second half of this century. But financial markets could be affected much sooner. This is driven by the projections of likely future impacts, changing regulations, and shifting market sentiments.
This study employs a unique approach to address these short-term implications of the longer-term climate challenge, in relation to climate risk. The complex analysis presented here is the result of a collaborative effort between research entities within the University of Cambridge. These are the Centre for Risk Studies, the Centre for Climate Mitigation Research (4CMR) and Cambridge Judge Business School.
This study quantifies the potential financial impacts of a shift in market sentiment driven by significant changes in investor and consumer beliefs about the future effects of climate change, modelling the impact of three market sentiment scenarios on four portfolios with different asset allocations.
Scenarios in this report
The scenarios reflect differing beliefs about the likelihood of government action to limit warming to 2°C, the actual emission levels anticipated, as well as physical climate change impacts, the probable stringency of regulation and levels of investment, including the types of technology liked to be developed.
These scenarios, aptly named:
- Two Degrees
- No Mitigation
- Baseline
These scenarios were developed according to well-recognised risk modelling techniques. They draw on the latest IPCC climate change projections and employ analysis of historical market shocks that offer meaningful parallels to interpret and model parameters within a climate risk framework.