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基于小波、转移熵和网络分析的投资者情绪传导多尺度特征

Multi-Scale Characteristics of Investor Sentiment Transmission Based on Wavelet, Transfer Entropy and Network Analysis.

作者信息

Han Muye, Zhou Jinsheng

机构信息

School of Economics and Management, China University of Geosciences, Beijing 100083, China.

出版信息

Entropy (Basel). 2022 Dec 6;24(12):1786. doi: 10.3390/e24121786.

Abstract

Investor sentiment transmission is significantly influential over financial markets. Prior studies do not reach a consensus about the multi-scale transmission patterns of investor sentiment. Our study proposed a composite set of methods based on wavelet, transfer entropy, and network analysis to explore the transmission patterns of investor sentiment among firms. By taking 137 new energy vehicle-related listed firms as an example, the results show three key findings: (1) the transmission of investor sentiment presents more active in the short term and takes place in a local range; (2) the transmission of investor sentiment presents patterns of continuity and growth from short term to long term; and (3) the transmission patterns of investor sentiment will have specific evolutions from short term to long term. Suggestions are offered to investors, managers and policymakers to better monitor the financial market using investor sentiment transmission.

摘要

投资者情绪传导对金融市场具有显著影响。先前的研究对于投资者情绪的多尺度传导模式尚未达成共识。我们的研究提出了一套基于小波、转移熵和网络分析的综合方法,以探究企业间投资者情绪的传导模式。以137家新能源汽车相关上市公司为例,结果显示出三个关键发现:(1)投资者情绪的传导在短期内更为活跃,且发生在局部范围内;(2)投资者情绪的传导呈现出从短期到长期的连续性和增长模式;(3)投资者情绪的传导模式从短期到长期会有特定的演变。我们为投资者、管理者和政策制定者提供了建议,以便利用投资者情绪传导更好地监测金融市场。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f863/9778233/ffc08bb8be12/entropy-24-01786-g001.jpg

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