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Modelling Multiperiod Carbon Markets Using Singular Forward-Backward SDEs

Jean-François Chassagneux (), Hinesh Chotai () and Dan Crisan ()
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Jean-François Chassagneux: Laboratoire de Probabilités, Statistique et Modélisation, Université Paris Cité, 75013 Paris, France
Hinesh Chotai: Department of Mathematics, Imperial College London, London SW7 2BX, United Kingdom
Dan Crisan: Citigroup, London E14 5LB, United Kingdom

Mathematics of Operations Research, 2023, vol. 48, issue 1, 463-497

Abstract: We introduce a model for the evolution of emissions and the price of emissions allowances in a carbon market, such as the European Union Emissions Trading System (EU ETS). The model accounts for multiple trading periods, or phases, with multiple times at which compliance can occur. At the end of each trading period, the participating firms must surrender allowances for their emissions made during that period, and additional allowances can be used for compliance in the following periods. We show that the multiperiod allowance pricing problem is well-posed for various mechanisms (such as banking, borrowing, and withdrawal of allowances) linking the trading periods. The results are based on the analysis of a forward-backward stochastic differential equation with coupled forward and backward components, a discontinuous terminal condition, and a forward component that is degenerate. We also introduce an infinite-period model for a carbon market with a sequence of compliance times and with no end date. We show that, under appropriate conditions, the value function for the multiperiod pricing problem converges, as the number of periods increases, to a value function for this infinite-period model and that such functions are unique. Finally, we present a numerical example that demonstrates empirically the convergence of the multiperiod pricing problem.

Keywords: primary 60H30; secondary 91G80; forward-backward systems; decoupling field; carbon markets; emission trading systems; market stability reserve; multiple compliance periods (search for similar items in EconPapers)
Date: 2023
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http://dx.doi.org/10.1287/moor.2022.1269 (application/pdf)

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