Prague Economic Papers 2026, 35(3):314-344 | DOI: 10.18267/j.pep.917

US-China Tensions and Financial Spillovers: Uncovering Asymmetric TVP-VAR Transmission

Veysel Karagöl ORCID..., Deniz Sevinç ORCID..., Ayºegül ªahin ORCID...
Veysel Karagöl, Bingöl University, Faculty of Economics and Administrative Sciences, Department of Economics, 12000, Merkez, Bingöl, Türkiye
Deniz Sevinç (Corresponding author), Anadolu University, Faculty of Economics and Administrative Sciences, Department of Business Administration, 26470, Tepebaºi, Eskiºehir, Türkiye
Ayºegül ªahin, Anadolu University, Faculty of Economics and Administrative Sciences, Department of Economics, 26470, Tepebaºi, Eskiºehir, Türkiye

This study investigates the transmission of geopolitical tensions between the United States and China to their stock markets within a dynamic and asymmetric framework. The analysis uses monthly returns of the S&P 500 and the Shanghai Composite Index, along with the log-difference of the US-China Tension Index (UCT), covering the period 1993-2024. An asymmetric TVP-VAR model is applied to capture time-varying and directional spillovers arising from positive and negative tension shocks. At the same time, a quantile-VAR connectedness analysis is employed for robustness. The results reveal pronounced asymmetries in spillover dynamics. Increases in geopolitical tensions lead to stronger and more widespread effects than periods of easing, particularly during crisis episodes, when spillover intensity rises markedly. The findings further show that while UCT shocks significantly impact financial markets, extreme market stress can also trigger feedback effects on geopolitical tension indicators. In addition, the Chinese stock market exhibits higher sensitivity to UCT shocks than the US market, indicating greater exposure to geopolitical risk. Overall, the results underline the persistent impact of geopolitical tensions on stock market dynamics.

Keywords: US-China Tension Index, Financial spillovers, TVP-VAR
JEL classification: C32, F51, G15

Received: December 12, 2025; Revised: March 23, 2026; Accepted: April 21, 2026; Prepublished online: September 8, 2026; Published: September 10, 2026  Show citation

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Karagöl, V., Sevinç, D., & ªahin, A. (2026). US-China Tensions and Financial Spillovers: Uncovering Asymmetric TVP-VAR Transmission. Prague Economic Papers, 35(3), 314-344. doi: 10.18267/j.pep.917
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    References

    1. Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., Oliyide, J. (2022). Crude Oil and Islamic Sectoral Stocks: Asymmetric TVP-VAR Connectedness and Investment Strategies. Resources Policy, 78, 102877. https://doi.org/10.1016/J.RESOURPOL.2022.102877 Go to original source...
    2. AlGhazali, A., Mensi, W., Belghouthi, H. E., Morley, B., Kang, S. (2025). Oil subsidy removal and spillovers between crude oil and stock markets: Empirical study from GCC countries. Journal of Asian Business and Economic Studies, 32(4), 190-203. https://doi.org/10.1108/JABES-03-2025-0105 Go to original source...
    3. Ando, T., Greenwood-Nimmo, M., Shin, Y. (2022). Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks. Management Science, 68(4), 2401-2431. https://doi.org/10.1287/MNSC.2021.3984 Go to original source...
    4. Antonakakis, N., Chatziantoniou, I., Gabauer, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4). https://doi.org/10.3390/jrfm13040084 Go to original source...
    5. Bissoondoyal-Bheenick, E., Do, H., Hu, X., Zhong, A. (2022). Sentiment and Stock Market Connectedness: Evidence from the US-China Trade War. International Review of Financial Analysis, 80, 102031. https://doi.org/10.1016/j.irfa.2022.102031 Go to original source...
    6. Cai, Y., Shen, Y., Uddin, G. S. (2025a). Financial Conditions and Sino-US Tensions: A Granger Causality Analysis of Diverging Financial Condition Indicators. Finance Research Letters, 79, 107199. https://doi.org/10.1016/j.frl.2025.107199 Go to original source...
    7. Cai, Y., Saadaoui, J., Uddin, G. S. (2025b). US Partisan Conflict, Sino-US Political Relations News, and Oil Market Dynamics. Energy Economics, 149, 108820. https://doi.org/10.1016/j.eneco.2025.108820 Go to original source...
    8. Cai, Y. (2025). US-China Tensions, Global Supply Chain Pressures, and the Global Economy. Economics Letters, 250, 112283. https://doi.org/10.1016/J.ECONLET.2025.112283 Go to original source...
    9. Caporin, M., Kuziboev, B., Catik, A. N. (2025). The Time-Varying Impact of US-China Tension on the Oil-gas and Clean Energy Stock Markets. Energy Research Letters, 6(Early View). https://doi.org/10.46557/001c.142276 Go to original source...
    10. Carlomagno, G., Albagli, E. (2022). Trade Wars and Asset Prices. Journal of International Money and Finance, 124, 102631. https://doi.org/10.1016/j.jimonfin.2022.102631 Go to original source...
    11. Chatziantoniou, I., Gabauer, D., Stenfors, A. (2021). Interest Rate Swaps and the Transmission Mechanism of Monetary Policy: A Quantile Connectedness Approach. Economics Letters, 204, 109891. https://doi.org/10.1016/J.ECONLET.2021.109891 Go to original source...
    12. Chen, Y., Pantelous, A. A. (2022). The US-China Trade Conflict Impacts on the Chinese and US stock markets: A Network-Based Approach. Finance Research Letters, 46, 102486. https://doi.org/10.1016/j.frl.2021.102486 Go to original source...
    13. Chengying, H., Rui, C., Ying, L. (2022). US-China Trade War and China's Stock Market: An Event-driven Analysis. Economic research-Ekonomska istra¾ivanja, 35(1), 3277-3290. https://doi.org/10.1080/1331677X.2021.1990781 Go to original source...
    14. Council on Foreign Relations. (2025). U.S.-China Relations. https://www.cfr.org/articles/us-china-relations (accessed: 23.08.2026)
    15. Diebold, F. X., Yilmaz, K. (2012). Better to Give Than to Receive: Predictive Directional Measurement of Volatility Spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/J.IJFORECAST.2011.02.006 Go to original source...
    16. Dixit, A. K., Pindyck, R. S. (1994). Investment under Uncertainty. Princeton University Press. https://press.princeton.edu/books/hardcover/9780691034102/investment-under-uncertainty Go to original source...
    17. Drezner, D. W. (2009). Bad Debts: Assessing China's Financial Influence in Great Power Politics. International Security, 34(2), 7-45. https://www.jstor.org/stable/40389212 Go to original source...
    18. Du, Y., Ju, J., Ramirez, C. D., Yao, X. (2017). Bilateral Trade and Shocks in Political Relations: Evidence from China and Some of Its Major Trading Partners, 1990-2013. Journal of International Economics, 108, 211-225. https://doi.org/10.1016/J.JINTECO.2017.07.002 Go to original source...
    19. Egger, P. H., Zhu, J. (2020). The US-Chinese Trade War: An Event Study of Stock-Market Responses. Economic Policy, 35(103), 519-559. https://doi.org/10.1093/epolic/eiaa016 Go to original source...
    20. Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417. https://doi.org/10.2307/2325486 Go to original source...
    21. Farrell, H., Newman, A. L. (2019). Weaponized Interdependence: How Global Economic Networks Shape State Coercion. International Security, 44(1), 42-79. https://doi.org/10.1162/ISEC_A_00351 Go to original source...
    22. Gries, P. H. (2001). Tears of rage: Chinese Nationalist Reactions to the Belgrade Embassy Bombing. China Journal, 46, 25-43. https://doi.org/10.2307/3182306 Go to original source...
    23. He, F., Lucey, B., Wang, Z. (2021). Trade Policy Uncertainty and Its Impact on the Stock Market-Evidence from China-US Trade Conflict. Finance Research Letters, 40, 101753. https://doi.org/10.1016/j.frl.2020.101753 Go to original source...
    24. Hines, B., Liu, C., Qiu, Y., Westerholm, P. J. (2025). Trading on Tension: Geopolitical Motives and Market Distortions. Available at SSRN: https://ssrn.com/abstract=5311288 or http://dx.doi.org/10.2139/ssrn.5311288 Go to original source...
    25. Inglesi-Lotz, R., Kuziboev, B., Ibadullaev, E., Saidmamatov, O., Çatik, A. N. (2025). Energy Uncertainty and Geopolitical Tensions: Impacts on European CO2 Emissions. Energy, 138592. https://doi.org/10.1016/j.energy.2025.138592 Go to original source...
    26. Kan, S. A. (2000). China: Suspected Acquisition of U.S. Nuclear Weapon Secrets. Library of Congress. Congressional Research Service. https://digital.library.unt.edu/ark:/67531/metacrs1138/
    27. Khan, N., Shah, S. Z. A., Siddiqui, O. (2025a). Fluctuations in Metals and Agricultural Commodity Markets under US-China Trade Tension: Evidence from Quantile-on-Quantile Regression and Wavelet Coherence. The Chinese Economy, 1-21. https://doi.org/10.1080/10971475.2025.2552609 Go to original source...
    28. Khan, N., Siddiqui, O., Yaya, O. S., Vo, X. V. (2025b). Ripple Effects of the US-China Tension on Asian Emerging and Frontier Markets with Portfolio Implications. Studies in Nonlinear Dynamics & Econometrics. https://doi.org/10.1515/snde-2024-0116 Go to original source...
    29. Kim, M. H. (2019). A Real Driver of US-China Trade Conflict: The Sino-US Competition for Global Hegemony and Its Implications for the Future. International Trade, Politics and Development, 3(1), 30-40. https://doi.org/10.1108/ITPD-02-2019-003 Go to original source...
    30. Koop, G., Pesaran, M. H., Potter, S. M. (1996). Impulse Response Analysis in Nonlinear Multivariate Models. Journal of Econometrics, 74(1), 119-147. https://doi.org/10.1016/0304-4076(95)01753-4 Go to original source...
    31. Li, S., Chen, H., Chen, G. (2025). The US-China Tension and Fossil Fuel Energy Price Volatility Relationship. Finance Research Letters, 74, 106707. https://doi.org/10.1016/j.frl.2024.106707 Go to original source...
    32. Li, S., Liu, Y. (2025). Geopolitical Risk and US Stock Market Volatility: Evidence from the US-China Tension Index. Applied Economics Letters, 1-7. https://doi.org/10.1080/13504851.2025.2534501 Go to original source...
    33. Lieberthal, K. G. (2011). The American Pivot to Asia. Brookings. https://www.brookings.edu/articles/the-american-pivot-to-asia/
    34. Liu, T., Woo, W. T. (2018). Understanding the US-China Trade War. China Economic Journal, 11(3), 319-340. https://doi.org/10.1080/17538963.2018.1516256 Go to original source...
    35. Luo, W., Kang, S., Di, Q. (2025). Global Supply Chain Reallocation and Shift under Triple Crises: A U.S.-China Perspective. https://arxiv.org/pdf/2508.06828
    36. Nishimura, Y., Sun, B. (2021). President's Tweets, US-China Economic Conflict and Stock Market Volatility: Evidence from China and G5 Countries. The North American Journal of Economics and Finance, 58, 101506. https://doi.org/10.1016/j.najef.2021.101506 Go to original source...
    37. Oh, M., Kim, D. (2024). Effect of the US-China Trade War on Stock Markets: A Financial Contagion Perspective. Journal of Financial Econometrics, 22(4), 954-1005. https://doi.org/10.1093/jjfinec/nbad016 Go to original source...
    38. Peng, C., Deng, H., Xie, J., Liu, X. (2025). US-China Tension and Stock Market Performance in US and China: New Insights from Time-Varying Quantile Causality Method. Finance Research Letters, 107888. https://doi.org/10.1016/j.frl.2025.107888 Go to original source...
    39. Pesaran, H. H., Shin, Y. (1998). Generalized Impulse Response Analysis in Linear Multivariate Models. Economics Letters, 58(1), 17-29. https://doi.org/10.1016/S0165-1765(97)00214-0 Go to original source...
    40. Rogers, J. H., Sun, B. Sun, T. (2024) U.S.-China Tension, Available at SSRN: https://ssrn.com/abstract=4815838 or http://dx.doi.org/10.2139/ssrn.4815838 Go to original source...
    41. ªeyranlioğlu, O. (2025). The Impact of US-China Tensions on Borsa Istanbul Stock Market: Evidence from ARDL Approach. Politik Ekonomik Kuram, 9(2), 783-804. https://doi.org/10.30586/pek.1589295 Go to original source...
    42. Tillmann, P., Yun, J. (2025). Gains from Gunboats: US Aircraft Carriers and Financial Markets in East Asia. Available at SSRN: https://ssrn.com/abstract=5085402 or http://dx.doi.org/10.2139/ssrn.5085402 Go to original source...
    43. Wahyudi, I., Sani, G. A. (2014). Interdependence between Islamic Capital Market and Money Market: Evidence from Indonesia. Borsa Istanbul Review, 14(1), 32-47. https://doi.org/10.1016/j.bir.2013.11.001World Bank World Integrated Trade Solution (WITS) Database https://wits.worldbank.org/Default.aspx?lang=en (accessed: 12.11.2025) Go to original source...
    44. Wu, B. (2025). Sino-American relations and gold market volatility. Finance Research Letters, 80, 107379. https://doi.org/10.1016/j.frl.2025.107379 Go to original source...
    45. Yeh, C. C., Ou, Y. T., Hsu, T. H., Huang, C. C. (2025). The influence of individual partner auditor quality on stock price synchronicity and crash risk. Journal of Asian Business and Economic Studies, 32(4), 214-226. https://doi.org/10.1108/JABES-05-2024-0245 Go to original source...
    46. Xu, J., Bouri, E., Fang, L., Gupta, R. (2025). US-China Tensions and Stock Market Co-movement Between the US and China: Insights from a DCC-DAGARCH-MIDAS Model. University of Pretoria Department of Economics Working Paper Series (No. 202522). https://ideas.repec.org/p/pre/wpaper/202522.html
    47. Xu, Y., Peng, L., Song, A. (2026). Composite uncertainty indicators and stock market returns: Based on supervised dimension reduction techniques. International Finance, 1-16. https://doi.org/10.1111/infi.70023 Go to original source...

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