Dynamic Connectedness Among Key Financial Markets and the Role of Policy Uncertainty: A Quantile-Based Approach

This paper investigates the return spillover dynamics among carry trade, stock, foreign exchange, and commodity markets to identify their roles as net transmitters or receivers of shocks under varying market conditions. Employing a Quantile Vector Autoregressive (QVAR) framework within the network-connectedness approach, the analysis captures asymmetric and state-dependent relationships across these markets. In addition, the study examines the influence of U.S. monetary and economic policy uncertainties on the total return spillovers among these markets across different market regimes, using the quantile-in-causality technique. The empirical results reveal that market influence shifts with changing conditions, while total interconnectedness intensifies during periods of elevated uncertainty, particularly throughout the bear market with the total connectedness index reaching 69.97%. Moreover, U.S. Monetary Policy Uncertainty (MPU) exerts varying effects on total connectedness depending on the prevailing market regime, with a pronounced effect at 0.50 quantile, representing stable market regime with no effect at extreme market conditions. These findings offer valuable insights for policymakers and investors, especially regarding the timing of asset allocation and investment decisions under different states of market uncertainty.

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Publication Details

Journal
Risks
Published
2025-11-24
DOI
https://doi.org/10.3390/risks13120228
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

Dynamic Connectedness Among Key Financial Markets and the Role of Policy Uncertainty: A Quantile-Based Approach

Lumengo Bonga‐Bonga
Risks
Market Dynamics and Volatility
article

Dynamic Connectedness Among Key Financial Markets and the Role of Policy Uncertainty: A Quantile-Based Approach

Lumengo Bonga‐Bonga
article en

Abstract

This paper investigates the return spillover dynamics among carry trade, stock, foreign exchange, and commodity markets to identify their roles as net transmitters or receivers of shocks under varying market conditions. Employing a Quantile Vector Autoregressive (QVAR) framework within the network-connectedness approach, the analysis captures asymmetric and state-dependent relationships across these markets. In addition, the study examines the influence of U.S. monetary and economic policy uncertainties on the total return spillovers among these markets across different market regimes, using the quantile-in-causality technique. The empirical results reveal that market influence shifts with changing conditions, while total interconnectedness intensifies during periods of elevated uncertainty, particularly throughout the bear market with the total connectedness index reaching 69.97%. Moreover, U.S. Monetary Policy Uncertainty (MPU) exerts varying effects on total connectedness depending on the prevailing market regime, with a pronounced effect at 0.50 quantile, representing stable market regime with no effect at extreme market conditions. These findings offer valuable insights for policymakers and investors, especially regarding the timing of asset allocation and investment decisions under different states of market uncertainty.

RisksVol. 13(12)
University of Johannesburg (ZA)
Openalex Percentile: Top 56%
Market Dynamics and Volatility
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