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arXiv · 2403.19363

Dynamic Correlation of Market Connectivity, Risk Spillover and Abnormal Volatility in Stock Price

Muzi Chen·Nan Li·Lifen Zheng·Difang Huang·Boyao Wu
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Abstract

The connectivity of stock markets reflects the information efficiency of capital markets and contributes to interior risk contagion and spillover effects. We compare Shanghai Stock Exchange A-shares (SSE A-shares) during tranquil periods, with high leverage periods associated with the 2015 subprime mortgage crisis. We use Pearson correlations of returns, the maximum strongly connected subgraph, and $3\sigma$ principle to iteratively determine the threshold value for building a dynamic correlation network of SSE A-shares. Analyses are carried out based on the networking structure, intra-sector connectivity, and node status, identifying several contributions. First, compared with tranquil periods, the SSE A-shares network experiences a more significant small-world and connective effect during the subprime mortgage crisis and the high leverage period in 2015. Second, the finance, energy and utilities sectors have a stronger intra-industry connectivity than other sectors. Third, HUB nodes drive the growth of the SSE A-shares market during bull periods, while stocks have a think-tail degree distribution in bear periods and show distinct characteristics in terms of market value and finance. Granger linear and non-linear causality networks are also considered for the comparison purpose. Studies on the evolution of inter-cycle connectivity in the SSE A-share market may help investors improve portfolios and develop more robust risk management policies.

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Muzi Chen, Nan Li, Lifen Zheng, Difang Huang, Boyao Wu. 2024-03-28. Dynamic Correlation of Market Connectivity, Risk Spillover and Abnormal Volatility in Stock Price. https://doi.org/10.1016/j.physa.2021.126506

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