Research on tail risk measurement and risk spillover effects in financial markets

Against the backdrop of deepening global economic integration, capital flows between different markets have accelerated, intensifying the cross-market transmission of financial risks. Starting from the complex linkage mechanisms between financial market risks and macroeconomic conditions, this paper incorporates economic agents' risk perceptions into a unified analytical framework. Using monthly data from January 2007 to December 2024 on indicators related to financial institutions, stocks, currencies, bonds, foreign exchange, and the real estate market, we apply a Quantile XGBoost+SHAP model to characterize tail risk factors across China's financial submarkets. We further employ a QVAR-DY model to analyze, from a static perspective, the spillover effects among different dimensions at various quantiles, and to trace the time-varying characteristics and evolutionary paths of risk transmission from a dynamic perspective. The study provides an in-depth analysis of the dynamic linkage between financial risks and macroeconomic conditions. The findings reveal that: (1) Economic agents risk perception exhibits significant synergistic and threshold effects on macroeconomic performance; (2) Static analysis indicates heterogeneity in the main sources of risk spillovers across different quantiles, with the most pronounced effects observed in lower-tail risk spillovers; (3) Dynamic analysis shows that upper-tail risk spillovers spike sharply in response to extreme events over the short term, whereas lower-tail risk spillovers reflect a more passive market response to long-term adverse factors and exhibit a gradual release pattern under negative conditions. Moreover, risk clustering patterns vary across different states.

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Publication Details

Journal
Journal of Applied Economics and Policy Studies
Published
2025-08-04
DOI
https://doi.org/10.54254/2977-5701/2025.25621
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Research on tail risk measurement and risk spillover effects in financial markets

Chenggong Lv, Miao Li
Journal of Applied Economics and Policy Studies
Financial Risk and Volatility Modeling
article

Research on tail risk measurement and risk spillover effects in financial markets

Chenggong Lv, Miao Li
article en

Abstract

Against the backdrop of deepening global economic integration, capital flows between different markets have accelerated, intensifying the cross-market transmission of financial risks. Starting from the complex linkage mechanisms between financial market risks and macroeconomic conditions, this paper incorporates economic agents' risk perceptions into a unified analytical framework. Using monthly data from January 2007 to December 2024 on indicators related to financial institutions, stocks, currencies, bonds, foreign exchange, and the real estate market, we apply a Quantile XGBoost+SHAP model to characterize tail risk factors across China's financial submarkets. We further employ a QVAR-DY model to analyze, from a static perspective, the spillover effects among different dimensions at various quantiles, and to trace the time-varying characteristics and evolutionary paths of risk transmission from a dynamic perspective. The study provides an in-depth analysis of the dynamic linkage between financial risks and macroeconomic conditions. The findings reveal that: (1) Economic agents risk perception exhibits significant synergistic and threshold effects on macroeconomic performance; (2) Static analysis indicates heterogeneity in the main sources of risk spillovers across different quantiles, with the most pronounced effects observed in lower-tail risk spillovers; (3) Dynamic analysis shows that upper-tail risk spillovers spike sharply in response to extreme events over the short term, whereas lower-tail risk spillovers reflect a more passive market response to long-term adverse factors and exhibit a gradual release pattern under negative conditions. Moreover, risk clustering patterns vary across different states.

Journal of Applied Economics and Policy StudiesVol. 18(7)
Jiangxi University of Finance and Economics (CN)
Openalex Percentile: Top 75%
Financial Risk and Volatility Modeling
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