Hedging Climate Risk
Open accessAbstract
We present a simple dynamic investment strategy that allows long-term passive investors to hedge climate risk without sacrificing financial returns. We illustrate how the tracking error can be virtually eliminated even for a low-carbon index with 50% less carbon footprint than its benchmark. By investing in such a decarbonized index, investors in effect are holding a “free option on carbon.” As long as climate change mitigation actions are pending, the low-carbon index obtains the same return as the benchmark index; but once carbon dioxide emissions are priced, or expected to be priced, the low-carbon index should start to outperform the benchmark.
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Approaches used in climate analytics include NLP for identifying climate risks and investment opportunities in company disclosures, NLP for analyzing media climate coverage to dynamically hedge climate change risk, econometric approaches for arbitrage strategies using carbon risk factor, and ML for forecasting carbon price in emission exchanges.
“Approaches used in this field include: natural language processing techniques for identifying climate risks and investment opportunities in disclosures made by companies [254,442,498,752] as well as for analyzing the evolution of climate coverage in the media to dynamically hedge climate change risk [221]; econometric approaches for developing arbitrage strategies that take advantage of the carbon”
From Tackling climate change with machine learning (2023) · cites this paper as [26]
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- Authors
- Andersson, M., Bolton, P., & Samama, F.
- Affiliations
- Mats Andersson is CEO of AP4, Stockholm.
- National Bureau of Economic Research (US)
- Institut d'Etudes Politiques de Paris (FR)
- Corresponding author
- Bolton, Patrick
- Venue
- Financial Analysts Journal
- Publisher
- Informa UK Limited
- Published
- 2016-05
- Volume
- 72
- Issue
- 3
- Pages
- 13-32
- ISSN
- 0015-198X (ISSN-L)
- 1938-3312
- OpenAlex
- W2337695238
- Cited by
- 434
- References
- 11
- Citations by year
- 2026: 35 · 2025: 72 · 2024: 67 · 2023: 55 · 2022: 53 · 2021: 51 · 2020: 30 · 2019: 33 · 2018: 19 · 2017: 8 · 2016: 11
- FWCI
- 11.59
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Financial Analysts Journal (publishedVersion)
- SSRN Electronic Journal (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Sustainable Finance and Green Bonds
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
- Keywords
- dynamic investment strategies, tracking error, carbon pricing, CO2 emissions, passive investing, climate change mitigation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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