Does uncertainty matter for US financial market volatility spillovers? Empirical evidence from a nonlinear Granger causality network

ABSTRACT

We investigate the role of uncertainty in US financial market volatility spillovers by using a directional financial network determined by the nonlinear Granger causality test. We find that uncertainty is an essential volatility transmission channel for financial market volatility spillovers. Financial uncertainty is the most central node in the financial market network. A subsample analysis, excluding the pandemic period, confirms the robustness of our results.

KEYWORDS:

• Uncertainty
• volatility spillovers
• financial market network
• nonlinear Granger causality

JEL CLASSIFICATION:

• E44
• G15

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Benhmad (2012) tests the nonlinear Granger causality based on the Taylor approximation and the artificial neural network. Because we mainly focus on the pairwise Granger causalities between 7 variables, 21 test iterations are needed. Therefore, we directly use the approach of Diks and Panchenko (2006) due to the fact that it requires less complex computations.

² The pairwise nonlinear Granger causality test results that determine the adjacent matrix in Table 2 are reported in Appendix 1 due to space limits.

³ Wavelet-based nonlinear Granger causality tests, performed as a research extension, are shown in Appendix 2.

Additional information

Funding

This paper is financially supported by the Fundamental Research Funds of Shandong University, China, the Young Scholar Future Project of Shandong University, China, the Natural Science Foundation of Shandong Province, China, and the National Natural Science Foundation of China [No. 71871234].