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中国の電力スポット・炭素・金融市場間におけるボラティリティリスク波及:BEKK–GARCHと非線形グレンジャー因果性検定による低炭素移行への示唆

Volatility Risk Spillovers Across China’s Electricity Spot, Carbon and Financial Markets: Implications for Low-Carbon Transition with Evidence from BEKK–GARCH and Nonlinear Granger Causality Tests (原題)

Xiang Wu, Weituo Zhu, Zhong Yin

Sustainability📚 査読済 / ジャーナル2026-11-04#炭素価格Origin: CN経営インパクト: 調達リスク対象セクター: power
DOI: 10.3390/su182111231
原典: https://doi.org/10.3390/su182111231

🤖 gxceed AI 要約

日本語

広東省の電力スポット価格・炭素排出枠価格・電力関連株指数の間のボラティリティ波及をVAR(2)-BEKK-GARCH等で分析。電力市場から炭素市場への一方向の波及が頑健に存在し、炭素市場から電力市場へは限定的。両市場のボラティリティは負の共変動を示し、自然なヘッジ関係ではなく緩衝効果の可能性を示唆。金融市場は他2市場と有意な波及がなくリスク隔離が成立。非線形因果性検定では電力市場と電力株指数が炭素価格に対し有意な予測力を持つ。

English

This study analyzes volatility spillovers among Guangdong's electricity spot, carbon allowance, and power-related equity markets using VAR(2)-BEKK-GARCH, news impact surfaces, and nonlinear causality tests. It finds robust unidirectional spillover from electricity to carbon markets, with only marginal reverse shocks, and a negative co-movement suggesting volatility buffering rather than natural hedging. The financial market shows risk isolation, while nonlinear Granger tests reveal electricity and equity prices predict carbon prices.

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

中国の地域炭素市場と電力市場の連動は、日本が進める電力市場改革と炭素価格制度(GXリーグ・排出量取引)設計の参考になる。炭素コストを入札戦略に織り込む発想は日本の発電事業者のリスク管理にも示唆を与える。

In the global GX context

Provides empirical evidence on cross-market risk contagion between carbon and electricity markets, relevant to ISSB/TCFD climate-risk disclosure and transition-finance risk assessment in emerging carbon markets. The nonlinear predictive power of power prices for carbon prices informs systemic-risk monitoring frameworks globally.

👥 読者別の含意

🔬研究者:炭素・電力市場間のボラティリティ波及と非線形因果性の実証手法(BEKK-GARCH、Diks–Panchenko検定)の応用例として有用。

🏢実務担当者:炭素コスト信号を電力入札戦略に組み込み、地域横断リスク監視体制を設計する際の定量的根拠となる。

🏛政策担当者:電力・炭素・金融市場の協調規制とクロスマーケット・リスク伝染防止の政策設計に示唆を与える。

📄 Abstract(原文)

To support coordinated risk management of electricity and carbon markets under the new power system, this paper clarifies the volatility transmission mechanism between Guangdong electricity spot prices and Guangdong carbon allowance prices, and investigates risk spillover effects among the Guangdong electricity spot market, Guangdong carbon market and power-related financial market. The results help identify regional systemic risks in the low-carbon energy transition and provide references for regional energy security and financial stability. This paper adopts the logarithmic return of day-ahead average prices in the Guangdong electricity spot market (RE), the logarithmic return of Guangdong carbon emission allowance prices (RC), and the logarithmic return of the FTSE China A600 Electricity Index (RF). A VAR(2)-BEKK-GARCH(1,1) framework is constructed to analyze risk linkages from mean and volatility dimensions. News impact surfaces, volatility impulse response functions, the Diebold–Yilmaz volatility spillover index and the Diks–Panchenko nonlinear causality test are further applied for comprehensive inference. The results show that the electricity market has significant inherent baseline volatility stemming from real-time supply-demand balance and the non-storability of electricity. Volatility persistence ranks as financial market > carbon market > electricity market. In terms of volatility transmission, there exists robust unidirectional volatility spillover from the electricity market to the carbon market; the carbon market only exerts a marginally significant short-run shock on the electricity market, while the joint test for this direction is insignificant. News impact surfaces and impulse responses reveal a negative co-movement pattern between electricity and carbon volatilities, implying potential volatility buffering effects rather than a straightforward natural hedging relationship. No significant volatility spillover exists between the financial market and the other two markets, meaning risk isolation holds during the sample period. Linear transmission in the mean dimension is weak, while the Diks–Panchenko nonlinear Granger causality test demonstrates that both the electricity market and the power financial index have significant nonlinear predictive power for carbon prices. This study provides empirical evidence for Guangdong power generators to optimize bidding strategies with carbon cost signals and establish a regional joint risk monitoring framework. It offers policy implications for coordinated regulation of the three regional markets and prevention of cross-market risk contagion.

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