''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 [https://en.wikipedia.org/wiki/Global_financial_system Wikipedia page] on this topic.''
ThereClimate arechange twoposes maina approachessubstantial tofinancial climaterisks finance: '''climate investment,''' whichto involvesglobal investingassets moneymeasured in companies with low carbon footprint or those that actively address the climate crisis, both for reasonstrillions of societal benefitdollars, and because these areit widelyis expectedhard to beforecast goodwhere, investmentshow, inor thewhen long term, and '''climate analytics,'''change whichwill aims to quantifyimpact the expectedstock financial impactsprice of climatea changegiven company, therebyor incentivizingeven investorsthe anddebt companiesof toan entire actnation. ML can help onclimate bothfinance ofin theseseveral frontsways, on the one handeither by designing portfolios and in timing investments for positive reinforcement of climate-positive investment,and on the other,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 ==
* '''[[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 Investment]]'''
* '''[[Climate Analytics]]:''' aims to quantify the expected financial impacts of climate change, thereby incentivizing investors and companies to act.
* '''[[Climate Analytics]]'''
== Background Readings ==
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