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• W2891701924 abstract "This paper applies effective transfer entropy to research the information transfer in the Chinese stock market around its crash in 2015. According to the market states, the entire period is divided into four sub-phases: the tranquil, bull, crash, and post-crash periods. Kernel density estimation is used to calculate the effective transfer entropy. Then, the information transfer network is constructed. Nodes' centralities and the directed maximum spanning trees of the networks are analyzed. The results show that, in the tranquil period, the information transfer is weak in the market. In the bull period, the strength and scope of the information transfer increases. The utility sector outputs a great deal of information and is the hub node for the information flow. In the crash period, the information transfer grows further. The market efficiency in this period is worse than that in the other three sub-periods. The information technology sector is the biggest information source, while the consumer staples sector receives the most information. The interactions of the sectors become more direct. In the post-crash period, information transfer declines but is still stronger than the tranquil time. The financial sector receives the largest amount of information and is the pivot node." @default.
• W2891701924 created "2018-09-27" @default.
• W2891701924 creator A5032962996 @default.
• W2891701924 creator A5080791772 @default.
• W2891701924 date "2018-09-03" @default.
• W2891701924 modified "2023-09-26" @default.
• W2891701924 title "Cross-Sectoral Information Transfer in the Chinese Stock Market around Its Crash in 2015" @default.
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• W2891701924 doi "https://doi.org/10.3390/e20090663" @default.
• W2891701924 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7513187" @default.
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• W2891701924 hasPublicationYear "2018" @default.
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