多次元不確実性を伴う炭素・エネルギー金融ネットワークにおける動的リスク波及の数理的特性評価：一般化予測誤差分散分解によるTVP-VAR-DYコネクテッドネス・アプローチ
Mathematical Characterization of Dynamic Risk Spillovers in Carbon-Energy Financial Networks with Multi-Dimensional Uncertainty: A TVP-VAR-DY Connectedness Approach via Generalized Forecast-Error Variance Decomposition (原題)
Wenxin Zhang, Rufei Zhang, 倩 朱
🤖 gxceed AI 要約
日本語
本論文はTVP-VAR-DYコネクテッドネス手法を用い、EUA炭素先物・化石燃料先物・クリーンエネルギー株指数からなる10次元システムのリスク波及ネットワークを2011〜2025年の月次データで分析する。気候政策不確実性（CPU）が最大のリスク伝播源であり、地政学リスク（GPR）が続き、経済政策不確実性（EPU）は間接的影響に留まる。炭素市場は上流の不確実性を吸収しエネルギー各部門へ波及させる「橋渡し」機能を担い、気候ガバナンス改善とともに純受信者から中立的主体へと進化する。政策ショックは持続的、突発的緊急事態は短命かつ大規模な波及を生む。
English
Using a TVP-VAR-DY connectedness framework on a 10-dimensional carbon-energy financial system (EUA futures, fossil fuel futures, clean energy equity indices) over 2011–2025, the paper shows climate policy uncertainty is the dominant risk transmitter, followed by geopolitical risk, while economic policy uncertainty transmits weakly and indirectly. Carbon markets act as an intermediary bridge, absorbing upstream uncertainty and propagating volatility to energy subsectors, gradually shifting from net receiver to neutral participant. Policy-driven shocks produce stable persistent spillovers, whereas sudden emergencies cause large but short-lived effects.
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
炭素価格がエネルギー市場全体へ波及する経路を定量化した点は、日本企業がEU-ETSやGX-ETS、炭素税の価格変動リスクを財務・調達戦略に織り込む際の参考になる。SSBJ開示における気候関連リスク（移行リスク）の定量評価や、炭素価格シナリオ分析の高度化に資する。
In the global GX context
The paper quantifies how carbon price shocks propagate across energy markets, directly informing transition-risk assessment under TCFD/ISSB and carbon-price scenario analysis. Its finding that climate policy uncertainty is the dominant transmitter strengthens the case for treating policy risk as a first-order financial risk in climate disclosure and cross-market supervision.
👥 読者別の含意
🔬研究者:炭素・エネルギー市場間の動的リスク波及と不確実性要因の異質性を定量化する実証枠組みを提供する。
🏢実務担当者:炭素価格・気候政策不確実性をエネルギー調達コストや移行リスクのシナリオ分析に組み込む根拠となる。
🏛政策担当者:気候政策の不確実性が市場ボラティリティを主導するため、政策の予見可能性向上が市場安定と移行促進に重要と示唆。
📄 Abstract（原文）
This paper employs the established time-varying parameter vector autoregressive connectedness framework (TVP-VAR-DY) based on generalized forecast error variance decomposition (GFEVD) to characterize the nonlinear, time-dependent risk spillover network linking carbon and multi-sector energy financial assets. Our core empirical contribution is to integrate three distinct categories of uncertainty risks with a 10-dimensional carbon-energy financial system in a unified analytical framework. We construct a 10-dimensional stochastic financial system comprising EUA carbon futures, fossil energy commodity futures (crude oil, natural gas, coal), and clean energy equity indices (wind, solar, hydropower). By utilizing monthly logarithmic return stationary time series spanning 2011–2025, we perform numerical estimations of static connectedness matrices, dynamic total spillover indices, directional pairwise spillover networks, and net risk transmission metrics under three distinct multidimensional uncertainty risk factors: geopolitical risk (GPR), economic policy uncertainty (EPU), and climate policy uncertainty (CPU). The empirical results show three key findings. First, spillover effects of multidimensional uncertainty risks exhibit heterogeneous patterns: climate policy uncertainty acts as the primary risk transmitter, followed by geopolitical risk, while economic policy uncertainty exerts weaker and mostly indirect transmission. External uncertainties (climate policy and geopolitical risks) are associated with spillover effects between carbon and energy markets far more strongly than endogenous uncertainties, and extreme events coincide with structural surges in total spillover magnitude. Second, carbon markets function as an intermediary bridge in risk transmission: they absorb upstream uncertainty spillovers and propagate volatility to all energy subsectors, gradually evolving from net risk receivers to neutral market participants alongside improved climate governance frameworks. Third, different shock types generate distinct spillover patterns: sudden emergencies are linked to rapid, large-magnitude yet short-lived spillovers, whereas policy-driven shocks exert stable, persistent impacts; policy factors play a pivotal guiding role in market volatility and the energy transition. This study integrates three categories of uncertainty into a unified analytical framework, clarifies differentiated risk response logics across energy segments via quantitative network analysis, and provides empirical evidence and quantitative references for global climate governance and cross-market risk supervision.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/math14203783first seen 2026-10-21 04:45:37
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