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Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network

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  • Jing Zhang
  • Ya-ming Zhuang
  • M. Irfan Uddin

Abstract

This paper is concerned with the multivariate stochastic volatility modeling of the stock market. We investigate a DGC-t-MSV model to find the historical volatility spillovers between nine markets, including S&P, Nasdaq, SSE, SZSE, HSI, FTSE, CAC, DAX, and Nikkei indices. We use the Bayesian network to analyze the spreading of herd behavior between nine markets. The main results are as follows: (1) the DGC-t-MSV model we considered is a useful way to estimate the parameter and fit the data well in the stock market; (2) our computational analysis shows that the S&P and Nasdaq have higher volatility spillovers to the Shanghai and Shenzhen stock markets; (3) the results also show that there is a strong correlation between stock markets in the same region.

Suggested Citation

  • Jing Zhang & Ya-ming Zhuang & M. Irfan Uddin, 2021. "Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network," Complexity, Hindawi, vol. 2021, pages 1-8, January.
    • Handle: RePEc:hin:complx:6645151
    DOI: 10.1155/2021/6645151
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    Cited by:

    1. Hatoum, Khalil & Moussu, Christophe & Gillet, Roland, 2022. "CEO overconfidence: Towards a new measure," International Review of Financial Analysis, Elsevier, vol. 84(C).

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