基于 Twitter 的市场不确定性和全球股票波动可预测性

IF 3.8 3区 经济学 Q1 BUSINESS, FINANCE
Yong Ma, Shuaibing Li, Mingtao Zhou
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引用次数: 0

摘要

本研究将基于 Twitter 的市场不确定性(TMU)纳入二十个国际股票市场每日波动率的预测框架。研究显示,无论从样本内还是样本外的角度来看,TMU 对股票波动性都有很强的预测能力。有趣的是,尽管 Twitter 在中国并不普及,但全球金融市场的相互联系使其能够间接影响中国股市的波动性。研究还强调,在动荡时期(如 COVID-19 疫情),TMU 在预测股市波动性方面发挥着特别重要的作用。此外,将 TMU 纳入波动率预测框架可提高经济价值。这些研究结果对于政策制定者制定有效的市场稳定政策和投资者加强投资组合管理至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Twitter-based market uncertainty and global stock volatility predictability

This study integrates Twitter-based market uncertainty (TMU) into the predictive framework of daily volatility in twenty international equity markets. The study reveals that TMU has a strong predictive ability for stock volatility from both in- and out-of-sample perspectives. Interestingly, despite Twitter being inaccessible in China, the interconnectedness of global financial markets allows it to indirectly impact China’s stock market volatility. The research also highlights that TMU plays a particularly significant role in forecasting stock market volatility during turbulent periods, such as the COVID-19 epidemic. Furthermore, integrating TMU into the volatility prediction framework leads to an improvement in economic value. These findings are essential for policymakers to develop effective market-stabilizing policies and for investors to enhance the management of their investment portfolios.

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来源期刊
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
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