This page is about the intersection of finance and machine learning in the context of climate change. For an overview of global financial system as a whole, please see the Wikipedia page on this topic.
Climate change poses a substantial financial risks to global assets measured in the trillions of dollars, and it is hard to forecast where, how, or when climate change will impact the stock price of a given company, or even the debt of an entire nation. ML can help climate finance in several ways, either by designing portfolios and in timing investments for positive reinforcement of climate-positive investment or by helping forecast prices in carbon markets, identifying climate risks and investment opportunities, and quantifying the monetary impact of climate change on supply and demand by using data-based approaches.
Machine Learning Application Areas[edit | edit source]
- Climate Investment: involves investing money in companies with low carbon footprint or those that actively address the climate crisis, both for reasons of societal benefit and because these are widely expected to be good investments in the long term.
- Climate Analytics: aims to quantify the expected financial impacts of climate change, thereby incentivizing investors and companies to act.
Background Readings[edit | edit source]
- Finance and climate: The transition to a low-carbon and climate-resilient economy from a financial sector perspective (2016): sketches out its relevance of climate change for the financial sector, covering topics from low-carbon investments to bridging the manageable financing gap. Available here.
- A climate stress-test of the financial system. (2017): a birds-eye view of the potential impacts of climate change on the stock market that looks at how climate policy risk might propagate through the financial system. Available here.
- Climate change challenges for central banks and financial regulators (2018) : this article presents the key controversies and discusses potential research and policy avenues for the future.
Online Courses and Course Materials[edit | edit source]
- Climate Finance: Innovative Approaches in Supporting Climate Action: this online course, created by the World Bank Group, summarizes the tested knowledge and practices in climate finance from different development partners.
- Climate Change: Financial Risks and Opportunities: this course, curated by the Imperial College London, does a deep dive on the risks and opportunities that climate change presents to financial markets,
- Introduction to Sustainable Finance: a high-level interactive and practice-oriented course that covers the basics of Sustainable Finance, hosted on the UN Climate Change E-Learn platform.
Community[edit | edit source]
Major societies and organizations[edit | edit source]
- Task Force on Climate-related Financial Disclosures: an organization created to increase transparency with regards to climate change reporting, making markets more efficient, and economies more stable and resilient.
- Climate Policy Initiative: an analysis and advisory organization with deep expertise in finance and policy.
- OECD Center on Green Finance and Investment: the mission of the Center is to "help catalyse and support the transition to a green, low-emissions and climate-resilient economy through the development of effective policies, institutions and instruments for green finance and investment".
Libraries and Tools[edit | edit source]
- ClimateScope: a country-by-country assessment that provides an interactive report and index indicating suitability for climate-related investment.
- Renewable Energy (RE) Data Explorer: a platform created to inform vital renewable energy investment and deployment decisions.
Data[edit | edit source]
Datasets are fairly limited in terms of data quantity (i.e. no single dataset would be enough to implement an ML system), but merging different sources of data together can yield interesting insights. Some promising data sources include:
- United Nations Framework Convention on Climate Change (UNFCCC) Climate Finance Data Portal: this website aims to assemble data on the implementation of adaptation and mitigation projects and other activities under the United Nations Framework Convention on Climate Change.
- OECD Development finance data: includes high level overviews on developmental statistics, as well as country and sector specific data. Y
- Global Financial Development Database: an extensive dataset of financial system characteristics for 214 economies.
- Inter-American Development Bank Climate Finance 2017 Dataset: the IDB publishes its reported climate finance on a project-level, disaggregated basis for all public sector activity, and on an aggregated basis for all private sector activity.
- Electronic Data Gathering, Analysis and Retrieval (EDGAR): the electronic filing system created by the Securities and Exchange Commission for corporate filings, which can be queried by company, by year and by sector in PDF format.
References[edit | edit source]
- "Finance and climate: The transition to a low-carbon and climate-resilient economy from a financial sector perspective". OECD Journal: Financial Market Trends. doi:10.1787/19952872.
- Battiston, Stefano; Mandel, Antoine; Monasterolo, Irene; Schütze, Franziska; Visentin, Gabriele (2017-04). "A climate stress-test of the financial system". Nature Climate Change. 7 (4): 283–288. doi:10.1038/nclimate3255. ISSN 1758-678X. Check date values in:
- Campiglio, Emanuele; Dafermos, Yannis; Monnin, Pierre; Ryan-Collins, Josh; Schotten, Guido; Tanaka, Misa (2018-06). "Climate change challenges for central banks and financial regulators". Nature Climate Change. 8 (6): 462–468. doi:10.1038/s41558-018-0175-0. ISSN 1758-678X. Check date values in: