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Green investment and asset stranding under transition scenario uncertainty

Maria Flora

CREST, CNRS, Institut Polytechnique de Paris; CNRS (Centre National de la Recherche Scientifique)

Peter Tankov

ENSAE, Institut Polytechnique de Paris; Scientific Director of the Green and Sustainable Finance (GSF) research program at ILB 

Date Written: January 11, 2022

Abstract

We develop a real-options approach to evaluate energy assets and potential investment projects under transition scenario uncertainty. Dynamic scenario uncertainty is modelled by assuming that the economic agent acquires the information about the scenario progressively by observing a signal. The problem of valuing an investment is formulated as an American option pricing problem, where the optimal exercise time corresponds to the time of entering into a potential investment project or the time of selling a potentially stranded asset. To illustrate our approach, we apply representative scenarios from integrated assessment models to the examples of a coal-fired power plant without Carbon Capture and Storage (CCS) and potential investment into a biomass power plant with CCS.

 

Keywords: Transition risk, scenario uncertainty, Bayesian learning, stranded asset, real options

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