Do Carbon Price Forecasts Improve Compliance Procurement? Evidence from European Union Allowances
炭素価格予測はコンプライアンス調達を改善するか？欧州連合排出枠からの証拠 (AI 翻訳)
Muzi Chen, Difang Huang, Shouyang Wang, Xinghan Xia
🤖 gxceed AI 要約
日本語
排出量取引制度の対象企業は、排出枠の評価だけでなく購入時期の決定にも予測を必要とする。本論文は、EUA価格に短期予測可能性が存在し、コンプライアンス調達を改善できるかを検証。2019～2025年の日次データを用い、1～5営業日先の直接予測を生成。全予測期間でRMSE最小の予測を達成し、予測経路を用いた調達最適化により、平均実現コストを均一執行比で8.5～38.5ベーシスポイント低減することを示した。
English
Firms covered by emissions trading systems need forecasts to value allowances and decide when to buy them. This paper tests whether EUA prices have short-horizon predictability that improves compliance procurement. Using daily data from 2019-2025, direct forecasts for 1-5 trading days ahead achieve the lowest RMSE among 14 benchmarks. The forecast path in a constrained procurement optimization lowers average realized costs by 8.5-38.5 basis points relative to uniform execution.
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
日本でもカーボンプライシングの本格導入が議論される中、EU ETSでの調達最適化の実証結果は、今後導入される可能性のある国内排出量取引制度における企業のコンプライアンス戦略に示唆を与える。特に予測を活用した調達コスト削減の定量評価は、実務上有用な知見となる。
In the global GX context
As the EU ETS serves as the global benchmark for emissions trading, this paper provides rigorous evidence that carbon price forecasts can reduce compliance procurement costs. For jurisdictions developing carbon pricing (e.g., US, China, Japan), the findings inform how regulated firms can optimize allowance purchasing under uncertainty, with implications for market design and cost of compliance.
👥 読者別の含意
🔬研究者:Demonstrates that short-horizon carbon price forecasts have economic value beyond random walk, with robust out-of-sample R² up to 15.5% and significant cost savings in procurement optimization.
🏢実務担当者:Provides a practical framework for compliance teams to use daily price forecasts to schedule allowance purchases, reducing average procurement costs by up to 38.5 basis points.
🏛政策担当者:Offers evidence that market participants can actively manage compliance costs through forecasting, suggesting that ETS design should account for dynamic procurement behavior.
📄 Abstract（原文）
Firms covered by emissions trading systems need forecasts not only to value allowances, but also to decide when to buy them. This paper asks whether European Union Allowance (EUA) prices contain short-horizon predictability that survives a forecast-origin information design and improves simulated compliance procurement. Using daily data from 2019 to 2025, we produce direct forecasts for one to five trading days ahead. All predictors are observable at the forecast origin, and calibration and model-selection rules are fixed before the final holdout. The released forecast has the lowest point-estimate RMSE at every horizon among fourteen benchmarks, with the strongest loss-difference evidence at horizons three and four. Relative to a random walk, out-of-sample R^2 rises from 1.2% at one day to 15.5% at five days. We then use the forecast path in a constrained procurement problem with execution costs, market impact, capacity limits, and tail risk; sensitivity exercises add demand uncertainty. For a fixed 100,000-EUA order, optimized schedules lower average realized costs by 8.5 to 38.5 basis points relative to uniform execution across horizons h=2 to h=5. The gains come from reallocating purchases within a fixed window, not from reliable next-day directional timing.
🔗 Provenance — このレコードを発見したソース
- arXiv https://arxiv.org/abs/2607.23426first seen 2026-07-28 04:10:56
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