Tail risk spillover asymmetry across global financial markets: a quantile connectedness approach

Cross-market tail risk spillovers threaten global financial stability, yet most studies examine risk contagion within individual asset classes or a limited set of markets. This study investigates tail risk spillover effects across five major financial market categories—equities, bonds, commodities, foreign exchange (FX), and money markets (short-term interbank interest rates)—in 12 economies from 2 January 2008 to 31 December 2024. Principal Component Analysis is first applied to reduce high-dimensional market data into representative factors, which are then modeled using Quantile Vector Autoregression to estimate spillover intensity at different conditional quantiles ( τ = 0.05 , 0.50 , 0.95 ) . The results reveal a clear asymmetry: under normal conditions ( τ = 0.50 ) , cross-market spillovers remain weak (total connectedness index around 16%), whereas under extreme downside conditions ( τ = 0.05 ) , spillover intensity rises sharply (total connectedness index exceeding 87%). Bootstrap inference shows that the money market’s net absorber position under extreme downside conditions and the commodity market’s net transmitter position under extreme upside conditions are the only market-level net positions statistically distinguishable from zero, whereas the difference between the two tail connectedness levels is not. In contrast, during extreme upside conditions ( τ = 0.95 ) , the commodity market emerges as the dominant net transmitter of risk to other markets. These findings demonstrate that tail risk contagion across global financial markets is both state-dependent and asymmetric, with implications for the design of differentiated cross-market risk monitoring frameworks.

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Publication Details

Journal
Frontiers in Physics
Published
2026-11-11
DOI
https://doi.org/10.3389/fphy.2026.1876146
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Tail risk spillover asymmetry across global financial markets: a quantile connectedness approach

Bin Li, Hongyi Yu
Frontiers in Physics
Financial Risk and Volatility Modeling
article

Tail risk spillover asymmetry across global financial markets: a quantile connectedness approach

Bin Li, Hongyi Yu
article en

Abstract

Cross-market tail risk spillovers threaten global financial stability, yet most studies examine risk contagion within individual asset classes or a limited set of markets. This study investigates tail risk spillover effects across five major financial market categories—equities, bonds, commodities, foreign exchange (FX), and money markets (short-term interbank interest rates)—in 12 economies from 2 January 2008 to 31 December 2024. Principal Component Analysis is first applied to reduce high-dimensional market data into representative factors, which are then modeled using Quantile Vector Autoregression to estimate spillover intensity at different conditional quantiles ( τ = 0.05 , 0.50 , 0.95 ) . The results reveal a clear asymmetry: under normal conditions ( τ = 0.50 ) , cross-market spillovers remain weak (total connectedness index around 16%), whereas under extreme downside conditions ( τ = 0.05 ) , spillover intensity rises sharply (total connectedness index exceeding 87%). Bootstrap inference shows that the money market’s net absorber position under extreme downside conditions and the commodity market’s net transmitter position under extreme upside conditions are the only market-level net positions statistically distinguishable from zero, whereas the difference between the two tail connectedness levels is not. In contrast, during extreme upside conditions ( τ = 0.95 ) , the commodity market emerges as the dominant net transmitter of risk to other markets. These findings demonstrate that tail risk contagion across global financial markets is both state-dependent and asymmetric, with implications for the design of differentiated cross-market risk monitoring frameworks.

Frontiers in PhysicsVol. 14
Chinese Academy of Sciences (CN), Nanjing University of Science and Technology (CN), Shenzhen Institutes of Advanced Technology (CN)
Financial Risk and Volatility Modeling
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Tail risk spillover asymmetry across global financial markets: a quantile connectedness approach — Bin Li, Hongyi Yu · Frontiers in Physics (2026) | TGRS Research Map | TGRS