gxceed
← 論文一覧に戻る

International Oil Price Volatility and the Dynamic Responses of Carbon Emissions Trading Market: Focusing on KAU Price Returns and Trading Volume

国際原油価格の変動と炭素排出権取引市場の動的応答:KAU価格リターンと取引量に焦点を当てて (AI 翻訳)

Youngshin Kim

Global Convergence Research Academy📚 査読済 / ジャーナル2026-06-30#炭素価格対象セクター: cross_sector
DOI: 10.57199/jgcr.2026.5.2.509
原典: https://doi.org/10.57199/jgcr.2026.5.2.509

🤖 gxceed AI 要約

日本語

本研究は国際原油価格の変動が韓国の炭素排出権取引市場(KAU)に与える影響を分析。EGARCHモデルによる原油価格変動性とARDLモデルを用いて、KAU価格リターンと取引量の動的応答を検証。結果、原油価格変動の直接効果は限定的で、KAU市場は内部価格調整と制度変更に強く影響されることを示した。

English

This study examines the impact of international oil price volatility on Korea's carbon emissions trading market (KAU). Using EGARCH-based oil volatility and ARDL models, it finds that oil price volatility has a limited direct effect on KAU price returns and trading volume, which are instead explained by internal price persistence and institutional phase changes.

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

韓国ETS(KAU)の制度変更が市場に与える影響を実証的に示しており、日本の炭素価格制度(GX-ETSなど)の設計や運用に示唆を与える。国際エネルギー市場のショックに対する国内炭素市場の反応の非対称性を明らかにした点は、日本企業のカーボンプライシングリスク管理に有用。

In the global GX context

This paper provides empirical evidence on how institutional phase transitions in a cap-and-trade system (Korean ETS) shape market dynamics, relevant for global carbon market design. It highlights that internal rules and persistence outweigh external energy shocks, informing policymakers and practitioners about carbon price formation under structural breaks.

👥 読者別の含意

🔬研究者:Useful for empirical carbon market research, particularly on the role of institutional phase transitions and internal dynamics.

🏢実務担当者:Limited direct application, but may help in understanding carbon price volatility in policy-dependent markets for risk assessment.

🏛政策担当者:Demonstrates that carbon market stability hinges on internal mechanisms rather than external energy shocks, informing ETS reform and phase design.

📄 Abstract(原文)

This study investigates the effects of international oil price volatility on the Korea‘s carbon emissions trading market, focusing on the dynamic responses of KAU price returns and trading volume. Using daily data from January 2015 to May 2026, this study employs the EGARCH conditional volatility estimated from Dubai crude oil returns as a proxy for international oil market uncertainty. The dependent variables are KAU price returns and the logarithm of KAU trading volume, while the exchange rate return and KOSPI return are included as control variables. In addition, phase dummies and their interaction terms with oil price volatility are incorporated to account for institutional changes in the Korean Emissions Trading System. An autoregressive distributed lag model is also estimated to examine the dynamic adjustment process of the KAU market. The empirical results show that international oil price volatility has a statistically significant negative effect on KAU price returns in some baseline models. However, this direct effect does not remain robust in the ARDL specifications. By contrast, KAU price returns are significantly explained by their own lagged terms, indicating the coexistence of short-term persistence and subsequent adjustment effects. In the trading volume analysis, the direct effect of international oil price volatility is not clearly confirmed, whereas lagged trading volume shows strong positive significance. In addition, phase dummies are significant in some models, suggesting that KAU trading activity may respond more sensitively to internal trading persistence and institutional changes than to international oil price volatility. These findings imply that the Korean carbon emissions trading market does not respond immediately and consistently to international energy market shocks, but is instead strongly influenced by internal price-adjustment dynamics and institutional factors.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。