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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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6645151 |
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| _version_ | 1849473568955432960 |
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| author | Jing Zhang Ya-ming Zhuang |
| author_facet | Jing Zhang Ya-ming Zhuang |
| author_sort | Jing Zhang |
| collection | DOAJ |
| 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. |
| format | Article |
| id | doaj-art-d2ce44e00cb549ac913fb860ff0fec90 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-d2ce44e00cb549ac913fb860ff0fec902025-08-20T03:24:06ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66451516645151Cross-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 |
| spellingShingle | Jing Zhang Ya-ming Zhuang Cross-Market Infection Research on Stock Herding Behavior Based on DGC-MSV Models and Bayesian Network Complexity |
| title | 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_short | 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 |
| url | http://dx.doi.org/10.1155/2021/6645151 |
| work_keys_str_mv | AT jingzhang crossmarketinfectionresearchonstockherdingbehaviorbasedondgcmsvmodelsandbayesiannetwork AT yamingzhuang crossmarketinfectionresearchonstockherdingbehaviorbasedondgcmsvmodelsandbayesiannetwork |