Dynamic correlation of market connectivity, risk spillover and abnormal volatility in stock price

被引:27
|
作者
Chen, Muzi [1 ]
Li, Nan [2 ]
Zheng, Lifen [1 ]
Huang, Difang [3 ]
Wu, Boyao [4 ]
机构
[1] Cent Univ Finance & Econ, Sch Management Sci & Engn, Beijing 102206, Peoples R China
[2] Shandong Normal Univ, Business Sch, Jinan 250014, Shandong, Peoples R China
[3] Monash Univ, Dept Econometr & Business Stat, Melbourne, Vic 3145, Australia
[4] Univ Int Business & Econ, Sch Banking & Finance, Beijing 100029, Peoples R China
基金
中国国家自然科学基金;
关键词
Stock network; Industry board; HUB node; Scale-free; Connectivity; NETWORK ANALYSIS; SYSTEMIC RISK; CAUSALITY; RETURNS; CRISIS; EVENT;
D O I
10.1016/j.physa.2021.126506
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
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. (C) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页数:18
相关论文
共 50 条
  • [31] Decomposed oil price shocks and GCC stock market sector returns and volatility
    Al-Fayoumi, Nedal
    Bouri, Elie
    Abuzayed, Bana
    ENERGY ECONOMICS, 2023, 126
  • [32] Sector Volatility Spillover and Economic Policy Uncertainty: Evidence from China's Stock Market
    Su, Xiaqing
    Liu, Zhe
    MATHEMATICS, 2021, 9 (12)
  • [33] Financial turbulence, systemic risk and the predictability of stock market volatility
    Salisu, Afees A.
    Demirer, Riza
    Gupta, Rangan
    GLOBAL FINANCE JOURNAL, 2022, 52
  • [34] Evidence on aggregate volatility risk premium for the French stock market
    Zaghouani Chakroun, Amal
    Mezzez Hmaied, Dorra
    MANAGERIAL FINANCE, 2019, 46 (01) : 72 - 91
  • [35] Geopolitical risk and renewable energy stock markets: An insight from multiscale dynamic risk spillover
    Yang, Kun
    Wei, Yu
    Li, Shouwei
    He, Jianmin
    JOURNAL OF CLEANER PRODUCTION, 2021, 279
  • [36] International stock market volatility: A global tail risk sight
    Lu, Xinjie
    Zeng, Qing
    Zhong, Juandan
    Zhu, Bo
    JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2024, 91
  • [37] Stock Price Crash Risk and the Market for Corporate Control
    Carline, Nicholas F.
    Gao, Yang
    Kuo, Jing-Ming
    BRITISH JOURNAL OF MANAGEMENT, 2024, 35 (04) : 1724 - 1745
  • [38] VOLATILITY SPILLOVER FROM THE GLOBAL OIL PRICE TO ASEAN STOCK MARKETS: A CROSS-QUANTILOGRAM ANALYSIS
    Ngoc, Mien Nguyen Thi
    ASIAN ACADEMY OF MANAGEMENT JOURNAL OF ACCOUNTING AND FINANCE, 2022, 18 (01): : 219 - 233
  • [39] Idiosyncratic volatility and stock price crash risk: Evidence from china
    Cao, Jiahui
    Wen, Fenghua
    Zhang, Yue
    Yin, Zhujia
    Zhang, Yun
    FINANCE RESEARCH LETTERS, 2022, 44
  • [40] Dynamic asymmetric spillovers and volatility interdependence on China's stock market
    Chen, Yufeng
    Li, Wenqi
    Qu, Fang
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 523 : 825 - 838