Evolution and management of price risk in the carbon market: The role of hedging
炭素市場における価格リスクの進化と管理：ヘッジの役割 (AI 翻訳)
Jialan Wang, J. Chavas, Jian Li, Tao Xiong
🤖 gxceed AI 要約
日本語
本論文は、EU ETSにおける価格変動性の上昇とヘッジ需要の減少という乖離を背景に、炭素先物のヘッジ有効性を分析。分位点ベクトル自己回帰モデルとコピュラを用いてテールリスクを評価し、従来の最小分散法よりも優れたヘッジ手法を提案。
English
This paper investigates the evolving price risk in the EU ETS and the effectiveness of carbon futures as hedging instruments. Using a quantile vector autoregression and copula approach, it finds significant tail risk and proposes a novel Minimum Cost-of-Risk hedging method that outperforms traditional approaches.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
EU ETSのフェーズ遷移に伴う価格リスクの実証分析は、日本の排出量取引制度設計やカーボンプライシング導入検討において示唆に富む。特に、テールリスク管理の重要性を指摘している点が参考になる。
In the global GX context
This paper provides rigorous empirical evidence on carbon price risk and hedging effectiveness in the world's largest carbon market (EU ETS). Its findings on tail risk and the proposed hedging method are relevant for global carbon market participants and policymakers designing risk management frameworks.
👥 読者別の含意
🔬研究者:Offers a novel quantile-based hedging method and empirical evidence on tail risk dynamics in carbon markets.
🏢実務担当者:Provides insights into managing carbon price risk using futures, with a practical alternative to traditional variance-minimization hedging.
🏛政策担当者:Highlights the importance of addressing tail risk in carbon market design and the role of derivatives for market stability.
📄 Abstract（原文）
This paper is motivated by the observed discrepancy between rising price volatility and declining hedging demand in the European Union Emission Trading System (EU ETS). To investigate whether the effectiveness of carbon futures as hedging instruments persists under varying scenarios, this paper evaluates the evolving price risk in the EU carbon market and examines the role of hedging in managing the risk. It investigates tail risk (corresponding to adverse market shocks occurring under rare events) and its temporal evolution over successive phases of EU carbon policy. Price risk is assessed empirically based on a quantile vector autoregression model of marginal price distributions along with a copula evaluation of the joint distribution of futures price and spot price. Applied to EU Allowance market over the period of 2008–2023, we find that: (1) the price distributions of both spot and futures market exhibit heavy‐tailed and leptokurtosis properties, thereby highlighting the significance of tail risk under changing policy schemes, such as the four phases of the EU ETS and shifting emission and energy policies; (2) decomposing the cost of risk across quantiles, we show that the risk located at the lower tail of the price distributions plays a dominant role; (3) we propose a novel Minimum Cost‐of‐Risk method based on the quantile vector autoregression, which more effectively evaluates the overall hedging performance in terms of cost of risk reduction compared to the traditional Minimum−Variance method.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/ajae.70038first seen 2026-05-15 17:17:38
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