Sectoral uncertainty spillovers in emerging markets: A quantile time–frequency connectedness approach
Dang T.H.N. Balli F. Balli H.O. Gabauer D. Nguyen T.T.H.
June 2024Elsevier Inc.
International Review of Economics and Finance
2024#93121 - 139 pp.
This study investigates the sectoral expected uncertainty connectedness in emerging markets across different frequencies and quantiles using the novel quantile time–frequency connectedness approach of Chatziantoniou et al. (2022a). The employed dataset spans from January 1st, 2003 to October 4th, 2022, encompassing 10 key sectors. The findings reveal a robust and notable interconnection among these sectors, with a substantial total connectedness index of 91.01%. We also note that the largest proportion of the sectoral total connectedness is associated with long-term spillovers. Consumer Cyclicals emerges as the primary source of net risk transmission. Conversely, the Communications & Networking and Healthcare appear to be the greatest net receivers of shocks at the median level. Furthermore, we find that the degree of interconnectedness substantially varies over time, frequency, and quantile, and by economic events. In addition, we find suggestive evidence of asymmetric sectoral uncertainty connectedness effects as the uncertainty spillovers are higher during turbulent market conditions than normal market conditions. A positive relationship between uncertainty measures and sectoral connectedness is also observed during periods of smooth and normal market conditions. Besides, we also conduct different portfolio analyses illustrating the importance of risk diversification to reduce investment uncertainty. This has important implications for international investors and policymakers in forming optimal investment portfolios reducing adverse risk spillovers.
Emerging markets , Expected uncertainty transmission , Portfolio analysis , Quantile time–frequency connectedness , Sectoral spillover
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School of Economics and Finance, Massey University, Auckland, New Zealand
Academy of Data Science in Finance, Vienna, Austria
Institute of Corporate Finance, Johannes Kepler University, Linz, Austria
Higher School of Economics and Business, Al-Farabi Kazakh National University, Almaty, Kazakhstan
School of Economics and Finance
Academy of Data Science in Finance
Institute of Corporate Finance
Higher School of Economics and Business
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