Return Spillovers Among Conventional Energy, New Energy Subsectors, ESG Assets and Gold: A Quantile Time–Frequency Connectedness Network Approach

Geopolitical conflict and the energy transition can alter the dependence between conventional energy, new energy, ESG assets, and gold. This study examines ten Chinese-market exposures using quantile time–frequency connectedness and network analysis. Mean rolling total connectedness is 60.406% at the median, 86.868% in the lower tail, and 86.664% in the upper tail. Wind power and photovoltaics have the largest median outgoing strengths, but directional positions differ across sectors and frequency bands. Short-frequency contributions dominate the baseline estimates; the long-frequency share is larger in the lower tail. Unknown-break tests do not reject constant-mean stability at 5%, and fixed-date confidence intervals include zero; neither result identifies a permanent causal effect of the Russia–Ukraine conflict. A separate portfolio evaluation over 1500 dates shows that minimum-variance allocations reduce realized variance, although weights and performance depend strongly on the gold proxy. Coal/gold-only and positive-NET allocations have different risk–return tradeoffs, and a net-receiver position alone does not establish hedge effectiveness. The findings support monitoring dependence across return states and testing explicit allocation rules, subject to common exposures, preprocessing, and instrument verification.

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Publication Details

Journal
International Journal of Financial Studies
Published
2026-11-03
DOI
https://doi.org/10.3390/ijfs14110301
Primary Topic
Market Dynamics and Volatility
Type
article
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Return Spillovers Among Conventional Energy, New Energy Subsectors, ESG Assets and Gold: A Quantile Time–Frequency Connectedness Network Approach

Yuhan Li, Rong Li
6 links
International Journal of Financial Studies
Market Dynamics and Volatility
article

Return Spillovers Among Conventional Energy, New Energy Subsectors, ESG Assets and Gold: A Quantile Time–Frequency Connectedness Network Approach

Yuhan Li, Rong Li
article en

Abstract

Geopolitical conflict and the energy transition can alter the dependence between conventional energy, new energy, ESG assets, and gold. This study examines ten Chinese-market exposures using quantile time–frequency connectedness and network analysis. Mean rolling total connectedness is 60.406% at the median, 86.868% in the lower tail, and 86.664% in the upper tail. Wind power and photovoltaics have the largest median outgoing strengths, but directional positions differ across sectors and frequency bands. Short-frequency contributions dominate the baseline estimates; the long-frequency share is larger in the lower tail. Unknown-break tests do not reject constant-mean stability at 5%, and fixed-date confidence intervals include zero; neither result identifies a permanent causal effect of the Russia–Ukraine conflict. A separate portfolio evaluation over 1500 dates shows that minimum-variance allocations reduce realized variance, although weights and performance depend strongly on the gold proxy. Coal/gold-only and positive-NET allocations have different risk–return tradeoffs, and a net-receiver position alone does not establish hedge effectiveness. The findings support monitoring dependence across return states and testing explicit allocation rules, subject to common exposures, preprocessing, and instrument verification.

International Journal of Financial StudiesVol. 14(11)
Beijing Union University (CN), Huaihua University (CN), Jishou University (CN)
Affordable and clean energy, Industry, innovation and infrastructure, Climate action
Openalex Percentile: Top 33%
Market Dynamics and Volatility
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