Forecasting and Pricing in the Carbon Credits Market

Abstract

The European Union Emissions Trading System has emerged as a cornerstone of climate policy, with carbon allowance prices exhibiting complex dynamics influenced by policy reforms, market shocks, and structural transitions. This study examines European Union Allowances (EUA) spot-price dynamics through four canonical processes and their regime-switching hidden Markov model (HMM) extensions, estimated using rolling windows to capture time-varying parameters. Our framework integrates in-sample fitting, multi-horizon forecasting, density calibration, and hedging performance evaluation, revealing that regime switching systematically enhances model flexibility and accuracy, particularly for jump-diffusion specifications. By incorporating maturity-matched risk-free rates and statistical tests, we demonstrate that regime-switching models better capture state-dependent behaviors and provide more reliable derivatives pricing and risk management insights. These findings offer practical value for market participants and policymakers in navigating carbon market risks and designing effective hedging strategies.