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

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

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 net...

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Main Authors: Jing Zhang, Ya-ming Zhuang
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2021/6645151
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spelling doaj-d2ce44e00cb549ac913fb860ff0fec902021-02-15T12:52:51ZengHindawi-WileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66451516645151Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian NetworkJing Zhang0Ya-ming Zhuang1School of Economics and Management, Southeast University, Nanjing, Jiangsu, ChinaSchool of Economics and Management, Southeast University, Nanjing, Jiangsu, ChinaThis 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.http://dx.doi.org/10.1155/2021/6645151
collection DOAJ
language English
format Article
sources DOAJ
author Jing Zhang
Ya-ming Zhuang
spellingShingle Jing Zhang
Ya-ming Zhuang
Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
Complexity
author_facet Jing Zhang
Ya-ming Zhuang
author_sort Jing Zhang
title Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
title_short Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
title_full Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
title_fullStr Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
title_full_unstemmed Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network
title_sort cross-market infection research on stock herding behavior based on dgc-msv models and bayesian network
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2021-01-01
description 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.
url http://dx.doi.org/10.1155/2021/6645151
work_keys_str_mv AT jingzhang crossmarketinfectionresearchonstockherdingbehaviorbasedondgcmsvmodelsandbayesiannetwork
AT yamingzhuang crossmarketinfectionresearchonstockherdingbehaviorbasedondgcmsvmodelsandbayesiannetwork
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