Dynamic Spillovers in Higher Moments and Jumps Across Chinese New Energy and Industry Stock Markets
- 1Business School, Hunan University, Changsha 410082, China
- 2College of Tourism, Hunan Normal University, Changsha 410081, China
- 3School of Mathematics and Statistics, Central South University, Changsha 410083, China
Abstract
Equity-market connectedness can look different depending on whether risk is measured by variance, asymmetry, tail thickness, or jumps. Using 5 min observations for the CSI New Energy Index and ten Shanghai Stock Exchange sector indices from 4 January 2016 to 31 December 2025, we construct 2430 common daily observations of realized volatility, skewness, kurtosis, and jump risk and estimate four TVP-VAR/GFEVD systems. Average total connectedness is 81.2 for volatility, 52.1 for skewness, 41.2 for kurtosis, and 51.1 for jump risk. The new-energy index is a net transmitter in all four full-sample systems, with NET values of 4.7, 4.0, 3.5, and 3.6, respectively, but the dominant transmitter differs by risk dimension: industrials lead volatility and skewness, materials lead kurtosis, and consumer discretionary leads jump risk. Subperiod results show that these roles are not temporally invariant; ZNE becomes a net receiver in several post-2021 risk-measure/period combinations. Alternative lag lengths, forecast horizons, forgetting factors, 15 min aggregation, and an alternative jump-test size leave the broad TVP-VAR conclusions unchanged. The results show that sectoral risk leadership is both dimension-specific and time-varying, with implications for portfolio and sectoral risk monitoring.
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BibTeX
@article{xie2026dynamic,
title = {{Dynamic Spillovers in Higher Moments and Jumps Across Chinese New Energy and Industry Stock Markets}},
author = {Sai Xie and Cai Yang and Hongwei Zhang},
journal = {Mathematics},
year = {2026},
month = sep,
doi = {10.3390/math14193440},
url = {https://www.mdpi.com/2227-7390/14/19/3440},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Dynamic Spillovers in Higher Moments and Jumps Across Chinese New Energy and Industry Stock Markets
AU - Sai Xie
AU - Cai Yang
AU - Hongwei Zhang
PY - 2026
DA - 2026/09/22
JO - Mathematics
DO - 10.3390/math14193440
UR - https://www.mdpi.com/2227-7390/14/19/3440
AB - Equity-market connectedness can look different depending on whether risk is measured by variance, asymmetry, tail thickness, or jumps. Using 5 min observations for the CSI New Energy Index and ten Shanghai Stock Exchange sector indices from 4 January 2016 to 31 December 2025, we construct 2430 common daily observations of realized volatility, skewness, kurtosis, and jump risk and estimate four TVP-VAR/GFEVD systems. Average total connectedness is 81.2 for volatility, 52.1 for skewness, 41.2 for kurtosis, and 51.1 for jump risk. The new-energy index is a net transmitter in all four full-sample systems, with NET values of 4.7, 4.0, 3.5, and 3.6, respectively, but the dominant transmitter differs by risk dimension: industrials lead volatility and skewness, materials lead kurtosis, and consumer discretionary leads jump risk. Subperiod results show that these roles are not temporally invariant; ZNE becomes a net receiver in several post-2021 risk-measure/period combinations. Alternative lag lengths, forecast horizons, forgetting factors, 15 min aggregation, and an alternative jump-test size leave the broad TVP-VAR conclusions unchanged. The results show that sectoral risk leadership is both dimension-specific and time-varying, with implications for portfolio and sectoral risk monitoring.
SN - 2227-7390
ER -