Carbon Finance and Artificial Intelligence

Martin Hellmich and Rüdiger Kiesel

Chapter 5 in Carbon Finance:A Risk Management View, 2021, pp 83-107 from World Scientific Publishing Co. Pte. Ltd.

Abstract: Artificial intelligence (AI) or machine learning (ML) techniques have recently gained attention in asset pricing, hedging, and generally, the valuation of financial assets. ML is a collective term for processes that apply computer algorithms which improve themselves automatically through experience and by the use of data. It is commonly regarded as a part of AI, which is a summary term for all applications in which machines perform human-like intelligent acts, such as learning, assessment, or problem solving. The use of these techniques often creates the opportunity of performing timely, system-spanning evaluations of large and complex data structures, which lead to the identification of previously unknown interrelations. Often, such activities require the extraction of rather elementary pieces of information from high-dimensional and complex data. The process of transforming data from a high-dimensional space into a low-dimensional space, so that the low-dimensional representation retains some meaningful properties of the original data, is referred to as dimensionality reduction…

Keywords: Climate Finance; Carbon Risks; Transition Risks; Emission Certificates; Green Bonds; Carbon Credits; Stress Tests; Machine Learning; Physical Risks; Carbon Markets; Carbon Disclosure; Carbon-Intensity; Commodity Markets; Climate Economics; Climate Risks; Big Data; Emission Certificates; Carbon Investors; Divestment (search for similar items in EconPapers)
JEL-codes: G1 G32 Q5 Q54 (search for similar items in EconPapers)
Date: 2021
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