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.
Authors
- Bin Li (ORCID: https://orcid.org/0000-0001-5122-5515)
- Hongyi Yu
Institutions
- Chinese Academy of Sciences (CN)
- Nanjing University of Science and Technology (CN)
- Shenzhen Institutes of Advanced Technology (CN)
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
- Field-Weighted Citation Impact
- 0.00