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
  • [41] Reprint of: The capital market consequence of sustained abnormal Audit fees: Evidence from stock price crash risk
    Lee, Sang Mook
    Park, Jong Chool
    Song, Hakjoon
    BRITISH ACCOUNTING REVIEW, 2025, 57 (01):
  • [42] Do world stock markets "jump" together? A measure of high-frequency volatility risk spillover networks
    Zhou, Dong-hai
    Liu, Xiao-xing
    JOURNAL OF INTERNATIONAL FINANCIAL MARKETS INSTITUTIONS & MONEY, 2023, 88
  • [43] Forecasting Volatility with Price Limit Hits-Evidence from Chinese Stock Market
    Chu, Xiaojun
    Qiu, Jianying
    EMERGING MARKETS FINANCE AND TRADE, 2019, 55 (05) : 1034 - 1050
  • [44] The dynamic interaction between volatility and returns in the US stock market using leveraged bootstrap simulations
    Hatemi-J, Abdulnasser
    Irandoust, Manuchehr
    RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2011, 25 (03) : 329 - 334
  • [45] Novel evidence from APEC countries on stock market integration and volatility spillover: A Diebold and Yilmaz approach
    Kakran, Shubham
    Sidhu, Arpit
    Bajaj, Parminder Kaur
    Dagar, Vishal
    COGENT ECONOMICS & FINANCE, 2023, 11 (02):
  • [46] Market integration and volatility spillover across major East Asian stock and Bitcoin markets: an empirical assessment
    Zeng, Hongjun
    Ahmed, Abdullahi D.
    INTERNATIONAL JOURNAL OF MANAGERIAL FINANCE, 2023, 19 (04) : 772 - 802
  • [47] Risk assessment and stock market volatility in the Eurozone: 1986-2014
    Menezes, Rui
    Oliveira, Alvaro
    4TH INTERNATIONAL WORKSHOP ON STATISTICAL PHYSICS AND MATHEMATICS FOR COMPLEX SYSTEMS (SPMCS2014), 2015, 604
  • [48] Oil price risk in the Spanish stock market: An industry perspective
    Moya-Martinez, Pablo
    Ferrer-Lapena, Roman
    Escribano-Sotos, Francisco
    ECONOMIC MODELLING, 2014, 37 : 280 - 290
  • [49] How do exchange rate and oil price volatility shape Pakistan's stock market?
    Khan, Misbah
    Karim, Sitara
    Naz, Farah
    Lucey, Brian M.
    RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2025, 76
  • [50] Multi-scale features of volatility spillover networks: A case study of China's energy stock market
    Liu, Xueyong
    Jiang, Cheng
    CHAOS, 2020, 30 (03)