Systemic Financial Risk Spillover Between Traditional-Energy and New-Energy Markets: A Quantile Time–Frequency Network with Link Prediction

Energy transition is central to both economic development and climate-change mitigation and has become a shared global challenge. Given the close relationship between conventional energy prices and the development of the new-energy industry, this study investigates systemic risk spillovers among three crude-oil futures, two natural-gas futures, and five Chinese new-energy sector indices. We employ a quantile time-frequency-connectedness framework and an out-of-sample-validated link-prediction model to assess both realized spillovers and potential changes in the network structure. The results reveal that network connectedness is time-varying and asymmetric across quantiles, with short-horizon connectedness accounting for the majority of average system-wide connectedness. Overall connectedness also increases markedly during major crisis episodes. INE crude-oil futures and both natural-gas futures are net receivers of shocks, whereas WTI and Brent crude-oil futures consistently act as net transmitters, with Brent playing the dominant role under extreme market conditions. As the investment horizon lengthens, the solar sector shifts from a net risk receiver to a net risk transmitter. In the predicted network, the solar sector emerges as the market most likely to initiate new short-term spillover links. This finding reflects a prospective, model-implied tendency rather than a causal relationship. These findings offer useful implications for energy market policy, portfolio risk management, and investment decisions involving new-energy companies.

Authors

Institutions

Publication Details

Journal
International Journal of Financial Studies
Published
2026-09-09
DOI
https://doi.org/10.3390/ijfs14090242
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systemic Financial Risk Spillover Between Traditional-Energy and New-Energy Markets: A Quantile Time–Frequency Network with Link Prediction

Di Yuan, Peilin Wang, Sufang Li, Wenxuan Jin
International Journal of Financial Studies
Market Dynamics and Volatility
article

Systemic Financial Risk Spillover Between Traditional-Energy and New-Energy Markets: A Quantile Time–Frequency Network with Link Prediction

Di Yuan, Peilin Wang, Sufang Li, Wenxuan Jin
article en

Abstract

Energy transition is central to both economic development and climate-change mitigation and has become a shared global challenge. Given the close relationship between conventional energy prices and the development of the new-energy industry, this study investigates systemic risk spillovers among three crude-oil futures, two natural-gas futures, and five Chinese new-energy sector indices. We employ a quantile time-frequency-connectedness framework and an out-of-sample-validated link-prediction model to assess both realized spillovers and potential changes in the network structure. The results reveal that network connectedness is time-varying and asymmetric across quantiles, with short-horizon connectedness accounting for the majority of average system-wide connectedness. Overall connectedness also increases markedly during major crisis episodes. INE crude-oil futures and both natural-gas futures are net receivers of shocks, whereas WTI and Brent crude-oil futures consistently act as net transmitters, with Brent playing the dominant role under extreme market conditions. As the investment horizon lengthens, the solar sector shifts from a net risk receiver to a net risk transmitter. In the predicted network, the solar sector emerges as the market most likely to initiate new short-term spillover links. This finding reflects a prospective, model-implied tendency rather than a causal relationship. These findings offer useful implications for energy market policy, portfolio risk management, and investment decisions involving new-energy companies.

International Journal of Financial StudiesVol. 14(9)
Shandong University (CN), Zhongnan University of Economics and Law (CN), Peking University (CN)
Climate action
Openalex Percentile: Top 4%
Market Dynamics and Volatility
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.