Uncovering Drivers of EU Carbon Futures with Bayesian Networks

TL;DR

This study uses Bayesian networks to analyze how financial, economic, and energy factors influence EU carbon futures prices, revealing energy commodities and market sentiment as key drivers and providing insights for policymakers and investors.

Contribution

It introduces a novel application of Bayesian networks to model dependencies in EU ETS futures prices, incorporating both contemporaneous and lagged effects over multiple trading phases.

Findings

Energy commodities, especially coal and oil, are primary influences on EUA prices.

Market sentiment affects EUA prices indirectly through energy demand.

Oil markets have a modest next-day predictive influence on EUA futures.

Abstract

The European Union Emissions Trading System (EU ETS) is a key policy tool for reducing greenhouse gas emissions and advancing toward a net-zero economy. Under this scheme, tradeable carbon credits, European Union Allowances (EUAs), are issued to large emitters, who can buy and sell them on regulated markets. We investigate the influence of financial, economic, and energy-related factors on EUA futures prices using discrete and dynamic Bayesian networks to model both contemporaneous and time-lagged dependencies. The analysis is based on daily data spanning the third and fourth ETS trading phases (2013-2025), incorporating a wide range of indicators including energy commodities, equity indices, exchange rates, and bond markets. Results reveal that EUA pricing is most influenced by energy commodities, especially coal and oil futures, and by the performance of the European energy sector. Broader market sentiment, captured through stock indices and volatility measures, affects EUA prices indirectly via changes in energy demand. The dynamic model confirms a modest next-day predictive influence from oil markets, while most other effects remain contemporaneous. These insights offer regulators, institutional investors, and firms subject to ETS compliance a clearer understanding of the interconnected forces shaping the carbon market, supporting more effective hedging, investment strategies, and policy design.