Multivariate Granger causality between financial markets: Evidence from US, Europe, Asia and Emerging market
Samuel Tabot Enow ORCID ↗
International Journal of Business Ecosystem & Strategy · 2025 · Vol. 7 / Issue 2 · 270-275
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Abstract
Financial markets are a system of complex price dynamics that are often influenced by various nonlinear factors. Traditional linear models often do not capture the inherent nonlinearities that exist between them. The aim of this study was to examine the interconnectedness of global financial markets using a multivariate Granger causality framework, focusing the United States, Europe, Asia, and emerging markets. Daily closing share prices spanning 13 years were utilised (January 2010 to December 2023) to analyze the shock transmission dynamics. The findings revealed unidirectional causality from the U.S. to European, Japanese, and Emerging markets, underscoring its dominant role in global financial networks. Conversely, European and Asian markets exhibit no reverse causality on the United States, highlighting asymmetrical interdependence. Notably, China’s Shanghai Composite Granger-causes Emerging market returns, reflecting its rising influence. These insights challenge conventional models that underestimate multilateral linkages, demonstrating that financial integration has intensified bidirectional interactions between Emerging markets and developed markets. By implication, investors should reassess exposure to dominant markets like the U.S. and China’s growing sway over Emerging economies while policymakers should prioritize cross-border spillover monitoring and systemic risk frameworks to address asymmetrical dependencies. Also, institutions must adopt nonlinear models to better capture shock transmission and evolving interdependencies, enhancing resilience against contagion.
Keywords: {'name': 'Multivariate Granger Causality; Stationary Test; Financial Market Linkages; Global Financial Markets'}
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Samuel Tabot Enow
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DOI: 10.1093/jjfinec/nbab023
DOI: 10.3390/en17020378
Arezki, R., Fan, R. Y., & Nguyen, H. (2020). Emerging markets and the global financial cycle. Journal of International Money and Finance, 104, 102132.
DOI: 10.1111/j.1540-6261.2006.00885.x
Barunik, J., & Kocenda, E. (2019). Financial contagion and network analysis. Journal of Financial Stability, 42, 1-12.
DOI: 10.1111/jofi.12203
DOI: 10.1016/j.jfineco.2011.12.010
Chen, X., Li, Z., & Wang, Y. (2023). Spillover effects and risk transmission in global financial markets. Finance Research Letters, 56, 103412.
DOI: 10.1016/j.jimonfin.2020.102251
DOI: 10.1016/j.ijforecast.2011.02.006
DOI: 10.2298/PAN1403275K
DOI: 10.1002/jae.1173
DOI: 10.32479/ijefi.13752
DOI: 10.32479/ijefi.13996
Forbes, K., & Rigobon, R. (2021). Contagion in financial markets: A twenty-year perspective. Review of Financial Studies, 34(2), 512-540.
DOI: 10.1093/oxrep/grad002
DOI: 10.1142/S0219091506000732
DOI: 10.2307/1912791
DOI: 10.1016/j.jfs.2023.101103
Huang, J., Chen, L., & Zhou, P. (2023). Financial integration and shock transmission among global markets. Economic Modelling, 117, 105942.
DOI: 10.30574/ijsra.2024.13.1.2047
Li, M., & Sun, W. (2023). The role of emerging markets in global financial stability. Journal of Economic Dynamics and Control, 150, 104179.
DOI: 10.19030/jber.v1i4.3001
DOI: 10.1111/ecoj.12268
DOI: 10.3386/w21162
Sen Liew, V. K. (2004). Which lag selection criteria should we employ? Economics Bulletin, 3(33), 1-9.
DOI: 10.1016/j.heliyon.2024.e34038
DOI: 10.70906/20231702001014
Wang, Q., & Zhang, Y. (2022). The impact of US monetary policy on global financial markets. Journal of International Economics, 134, 103564.
Zhang, H., & Li, X. (2023). Sentiment-driven spillovers in financial markets: A natural language processing framework for real-time risk assessment. Quantitative Finance, 23(7), 1023–1045.
DOI: 10.1016/j.econmod.2022.106101
Zhang, T., & Liu, K. (2023). Network analysis of global financial contagion. Journal of Financial Markets, 58, 101236.