Understanding Carbon Trade Dynamics: A European Union Emissions Trading System Perspective

ArXiv ID: 2510.22341 “View on arXiv”

Authors: Avirup Chakraborty

Abstract

The European Union Emissions Trading System (EU ETS), the worlds largest cap-and-trade carbon market, is central to EU climate policy. This study analyzes its efficiency, price behavior, and market structure from 2010 to 2020. Using an AR-GARCH framework, we find pronounced price clustering and short-term return predictability, with 60.05 percent directional accuracy and a 70.78 percent hit rate within forecast intervals. Network analysis of inter-country transactions shows a concentrated structure dominated by a few registries that control most high-value flows. Country-specific log-log regressions of price on traded quantity reveal heterogeneous and sometimes positive elasticities exceeding unity, implying that trading volumes often rise with prices. These results point to persistent inefficiencies in the EU ETS, including partial predictability, asymmetric market power, and unconventional price-volume relationships, suggesting that while the system contributes to decarbonization, its trading dynamics and price formation remain imperfect.

Keywords:

Complexity vs Empirical Score

  • Math Complexity: 5.0/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Street Traders
  • Why: The paper employs established econometric models like AR-GARCH and log-log regressions, which are moderately advanced but not novel or overly dense, while it relies heavily on a real-world, decade-long transaction dataset from the EU ETS for backtesting and implementation-focused results.
  flowchart TD
    A["Research Goal<br>Assess EU ETS efficiency<br>and price dynamics 2010-2020"] --> B["Methodology<br>AR-GARCH & Network Analysis"]
    B --> C["Data Inputs<br>EU ETS Registry Transactions<br>2010-2020"]
    C --> D["Computational Processes<br>Price clustering, forecast<br>inter-country network flows<br>log-log regression"]
    D --> E["Key Findings<br>Pronounced clustering<br>60.05% directional accuracy<br>Concentrated network structure<br>Unconventional price-volume elasticity"]