Dynamic correlation and risk resonance among industries of Chinese stock market: New evidence from time–frequency domain and complex network perspectives

Chen Tao, Guang-Yan Zhong and Jiang-Cheng Li

Physica A: Statistical Mechanics and its Applications, 2023, vol. 614, issue C

Abstract: To sustain market stability, it is crucial to research the impact of risk resonance across industries. In this paper, we demonstrate the dynamic risk resonance between various sectors in the Chinese market. To do so, by using a recently developed method that divides spillover measures based on variance decompositions into their components at different frequency ranges, a set of frequency spillover matrices is obtained to show the overall risk resonance within sectors. Second, we use a complex network to investigate the risk contagion path among different industries. The research results show that: (1) the risk resonance effect varies significantly over time; (2) during our sample period, the transportation and utilities industries are net transmitters; (3) the risk resonance mechanism is frequency dependent. Spillovers generated at low-frequency, extreme occurrences have a long-lasting effect on the industry’s risk resonance; and (4) extreme events such as the financial crisis and the COVID-19 will enhance the risk resonance effect. The results of our research can provide a reference for market participants to formulate corresponding regulatory and investment strategies.

Keywords: Econophysics; Risk resonance; Time-frequency domains; Complex network; Connectedness (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:614:y:2023:i:c:s0378437123001139

DOI: 10.1016/j.physa.2023.128558

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