← 論文一覧に戻る

Energy Market and Carbon Emission Spillovers in Critical Minerals Investment: A Dynamic Connectedness Approach

重要鉱物投資におけるエネルギー市場と炭素排出のスピルオーバー:動的連接性アプローチ (AI 翻訳)

Haibo Wang, L. Sua, Jaime Ortiz, Jun Huang, B. Alidaee

2026-07-29#エネルギー転換Origin: Global経営インパクト: 資金調達対象セクター: mining
原典: https://www.semanticscholar.org/paper/77e03c1ef50fc71d7eec67b3bd54dacc87406cb0

🤖 gxceed AI 要約

日本語

2013~2023年の日次データを用いて、重要鉱物ETF、エネルギー市場、炭素排出先物などの金融リスク連関をTVP-VARモデルで分析。高ESGスコアのポートフォリオがショックを増幅する一方、WTI原油と炭素排出先物は正味のショック受信者、コバルトとアルミのETFは正味の発信者であることを示した。COVID-19後の構造変化も明らかになり、投資家のヘッジ戦略に実践的示唆を与える。

English

Using daily data from 2013 to 2023, this study employs a TVP-VAR model to examine volatility spillovers among critical mineral ETFs, energy markets, carbon emission futures, and global infrastructure. High-ESG-score portfolios significantly contribute to shock transmission, while WTI oil and carbon futures are net receivers, and cobalt and aluminum ETFs are net givers. The COVID-19 pandemic caused structural shifts in these roles, offering practical insights for investor hedging.

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

重要鉱物(レアメタル等)は日本のエネルギー移行とサプライチェーン安全保障に直結する。本分析は、ESGスコアと金融リスクの連関を実証し、日本の投資家や企業が重要鉱物関連資産のリスクを評価する際の示唆を提供する。また、SSBJ開示を含むESG情報の資本市場への影響を考える材料となる。

In the global GX context

As critical minerals are central to global energy transitions and supply-chain security, this paper provides cross-market insights on how carbon prices and energy volatility interact with mineral ETFs. Linking ESG scores to shock transmission roles informs investor risk management and contributes to the growing literature on climate-related financial risks, relevant to TCFD/ISSB-aligned disclosures.

👥 読者別の含意

🔬研究者:Provides empirical evidence on directional volatility spillovers in critical mineral markets, particularly the role of ESG scores in shock transmission.

🏢実務担当者:Useful for refining hedging strategies and portfolio allocation in critical minerals and energy-related assets, especially during structural breaks.

🏛政策担当者:Highlights how ESG-labeled investment products can propagate systemic risk, informing macroprudential monitoring of energy transition markets.

📄 Abstract(原文)

Design/methodology/approach A time-varying parameter vector autoregression (TVP-VAR) model is employed to quantify dynamic connectedness and directional volatility spillovers using daily data from May 1, 2013, to May 2, 2023. The study isolates the impact of extreme events by splitting the data into pre- and post-COVID-19 samples based on the February 2020 stock market crash. Purpose This paper examines the daily financial risk spillovers associated with investing in critical minerals. It examines the dynamic interconnectedness between seven critical mineral Exchange-Traded Fund (ETF) portfolios and key economic-wide variables, including the energy market, carbon emissions, market sentiment, and global infrastructure. Findings Portfolios with high Environmental, Social, and Governance (ESG) scores significantly contribute to shock spillovers. Net directional connectedness analysis reveals that West Texas Intermediate (WTI) crude oil and carbon emission futures consistently act as"net receivers,"absorbing volatility from the system. Conversely, Cobalt and Aluminum ETFs primarily act as"net givers,"transmitting volatility. The pandemic caused significant structural shifts in these transmission roles. Practical implications The identification of specific net givers and receivers provides actionable insights for investors, facilitating better hedging strategies against time-varying structural breaks and broader economic shocks. Originality This study uniquely utilizes financial ETF data rather than physical mineral prices to capture accessible investment risks. It is among the first to link ESG scores to the directional role (giver vs. receiver) of critical mineral assets within a broader macro-financial network.

🔗 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。