Tail Dependence in EU Carbon Markets: Graphical Models of Extremes for EUA Futures

Statistics > Applications [Submitted on 16 Jun 2026] Title:Tail Dependence in EU Carbon Markets: Graphical Models of Extremes for EUA Futures View PDF HTML (experimental)Abstract:Understanding how extreme price movements propagate across financial and energy markets is critical for risk management and regulatory design in the EU Emissions Trading System (EU ETS). We apply Hüsler-Reiss graphical models of extremes to a system of 20 daily variables centred on EU allowances futures across Phases 3 and 4 of the EU ETS (2013--2025), with a Gaussian graphical model as the average-dependence baseline. The tail networks are structurally distinct from the average dependence network: substantially denser, organized around different central nodes, and governed by within-sector homophily that binds sector boundaries more tightly than at the average-dependence level. EU allowances futures are peripheral in the standard graphical model but achieve the highest centrality in the tail networks, while equity indices and major FX pairs follow the opposite trajectory. Exponential random graph models confirm equity and FX peripherality in tail networks across all sample periods and identify triadic closure during market downturns as a Phase~3 phenomenon that vanishes in Phase~4. The phase transition restructures the tail network without thinning it: average dependence contracts sharply while tail dependence persists, and crash contagion shifts from clustered to diffuse propagation. These findings have direct implications for hedge construction by compliance entities, stress-test calibration by regulators, and the design of systemic-risk monitoring tools for EU ETS markets. Submission history From: Manuele Leonelli [view email][v1] Tue, 16 Jun 2026 09:36:55 UTC (4,657 KB) References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.