Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression

Wenpei Yang

doi:10.47297/wspdecWSP2515-797317.20250906

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Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression

9卷第6期

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Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression
Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression
School of Economics and Management, China University of Geosciences (Wuhan), Wuhan, Hubei, 430074, China
2025年9卷第6期页码：87-94
纸质出版日期：2025-06-30
DOI：10.47297/wspdecWSP2515-797317.20250906
Accepted：

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(2025). Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression. 发展经济学, 9(6), 87-94.

Yang Wenpei.Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression[J].Development Economics of China,2025,09(06):87-94.
(2025). Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression. 发展经济学, 9(6), 87-94. DOI： 10.47297/wspdecWSP2515-797317.20250906.

Yang Wenpei.Research on Risk Spillover Effects of A-Share Sector Indices Based on EVT-GARCH-Quantile Regression[J].Development Economics of China,2025,09(06):87-94. DOI： 10.47297/wspdecWSP2515-797317.20250906.

摘要

Abstract

This study investigates the risk spillover effects among A-share sector indices by constructing an integrated EVT-GARCH-quantile regression framework. Using daily data from five major sector indices (including CSI 300

Financials

Technology

etc.) between January 2020 and June 2024

we employ the EVT-POT model to characterize tail distributions

the DCC-GARCH model to capture dynamic volatility correlations

and quantile regression to quantify spillover intensities under extreme risks. Key findings include: (1) The CSI 300 exerts significantly stronger risk spillovers on Financials and Technology sectors than on Consumer Staples and Healthcare

with Financials' %CoVaR reaching 39.62% at the 5% quantile; (2) Under extreme risk scenarios

spillover effects intensify by 30%-50% compared to normal conditions

confirming nonlinear tail risk transmission. The study provides theoretical foundations for regulators to establish sector-specific risk early-warning mechanisms and for investors to optimize cross-sector asset allocation during market turmoil.

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references

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