filmov
tv
A Bespoke, probabilistic approach to climate scenario analysis
![preview_player](https://i.ytimg.com/vi/FoS2ftxPng8/sddefault.jpg)
Показать описание
Presented by Jeremy Lawson, Chief Economist and Head of the abrdn Research Institute
Co-authored with Anna Moss, Alexandre Popa, Eva Cairns and Craig Mackenzie
Moderated by Mar Reguant, Northwestern University, Barcelona School of Economics and CEPR
We develop a new approach to designing climate scenarios and assessing the impact of physical and transition climate risks on companies and markets that is better tailored for financial and investment decision making. Our main innovations are that we: (i) allow for more plausible policy variation across sectors and regions to construct ‘bespoke’ scenarios that are more realistic than typical ‘off-the-shelf’ reference scenarios, (ii) develop a baseline scenario benchmarked against what is priced into the market to better identify potential asset price misalignments, (iii) assign probabilities to scenarios and aggregate them to analyse how the long-term fair valuation of asset prices relates to a probability-weighted mean outcome.
Co-authored with Anna Moss, Alexandre Popa, Eva Cairns and Craig Mackenzie
Moderated by Mar Reguant, Northwestern University, Barcelona School of Economics and CEPR
We develop a new approach to designing climate scenarios and assessing the impact of physical and transition climate risks on companies and markets that is better tailored for financial and investment decision making. Our main innovations are that we: (i) allow for more plausible policy variation across sectors and regions to construct ‘bespoke’ scenarios that are more realistic than typical ‘off-the-shelf’ reference scenarios, (ii) develop a baseline scenario benchmarked against what is priced into the market to better identify potential asset price misalignments, (iii) assign probabilities to scenarios and aggregate them to analyse how the long-term fair valuation of asset prices relates to a probability-weighted mean outcome.