Asymmetric effects of monetary policy uncertainty on BRICS stock markets, cryptocurrencies, and oil markets: a multiscale perspective based on frequency and quantile frameworks

Amid increasing global financial integration and heightened macroeconomic uncertainty, monetary policy uncertainty (MPU) has emerged as a key driver of cross-market risk transmission. This study investigates the spillover effects of MPU on major global financial markets, including cryptocurrencies, BRICS equity indices, and oil prices, within a unified and distribution-sensitive framework. To capture complex and heterogeneous uncertainty transmission, we employ a time-varying parameter quantile vector autoregression (TVP-QVAR) model with frequency-domain connectedness decomposition, complemented by Quantile-on-Quantile Regression and Cross-Quantile approaches. This integrated framework comprehensively examines dynamic, frequency-specific, and quantile-dependent spillover mechanisms across diverse market states. Results reveal three core findings. First, overall connectedness remains persistently high, signalling strong systemic interdependence, with shocks spreading rapidly across asset classes. Second, spillovers exhibit notable asymmetry: downside tail-risk conditions trigger volatile, abrupt transmission, while upside states sustain persistent long-term spillovers. Third, MPU impacts are nonlinear and state-dependent, intensifying at higher quantiles, with cryptocurrencies and emerging equities showing greater sensitivity. These findings underscore the importance of integrating time variation, frequency decomposition, and distributional heterogeneity into financial interconnectedness modelling.

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Publication Details

Journal
Applied Economics
Published
2026-06-30
DOI
https://doi.org/10.1080/00036846.2026.2696480
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Asymmetric effects of monetary policy uncertainty on BRICS stock markets, cryptocurrencies, and oil markets: a multiscale perspective based on frequency and quantile frameworks

W K Zhang, Panpan Zhang, Tong Xiao, Peishan Tong et al.
Applied Economics
Market Dynamics and Volatility
article

Asymmetric effects of monetary policy uncertainty on BRICS stock markets, cryptocurrencies, and oil markets: a multiscale perspective based on frequency and quantile frameworks

W K Zhang, Panpan Zhang, Tong Xiao, Peishan Tong, Yuan Ma
article en

Abstract

Amid increasing global financial integration and heightened macroeconomic uncertainty, monetary policy uncertainty (MPU) has emerged as a key driver of cross-market risk transmission. This study investigates the spillover effects of MPU on major global financial markets, including cryptocurrencies, BRICS equity indices, and oil prices, within a unified and distribution-sensitive framework. To capture complex and heterogeneous uncertainty transmission, we employ a time-varying parameter quantile vector autoregression (TVP-QVAR) model with frequency-domain connectedness decomposition, complemented by Quantile-on-Quantile Regression and Cross-Quantile approaches. This integrated framework comprehensively examines dynamic, frequency-specific, and quantile-dependent spillover mechanisms across diverse market states. Results reveal three core findings. First, overall connectedness remains persistently high, signalling strong systemic interdependence, with shocks spreading rapidly across asset classes. Second, spillovers exhibit notable asymmetry: downside tail-risk conditions trigger volatile, abrupt transmission, while upside states sustain persistent long-term spillovers. Third, MPU impacts are nonlinear and state-dependent, intensifying at higher quantiles, with cryptocurrencies and emerging equities showing greater sensitivity. These findings underscore the importance of integrating time variation, frequency decomposition, and distributional heterogeneity into financial interconnectedness modelling.

Applied Economics
Shanghai University of Finance and Economics (CN), Rutgers Sexual and Reproductive Health and Rights (NL), Nanyang Institute of Technology (CN), Academy of Social Sciences (GB), University of Hong Kong (HK)
Partnerships for the goals
Openalex Percentile: Top 4%
Market Dynamics and Volatility
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