{"title":"Twitter-based market uncertainty and global stock volatility predictability","authors":"Yong Ma, Shuaibing Li, Mingtao Zhou","doi":"10.1016/j.najef.2024.102256","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":47831,"journal":{"name":"North American Journal of Economics and Finance","volume":"75 ","pages":"Article 102256"},"PeriodicalIF":3.8000,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"North American Journal of Economics and Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1062940824001815","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
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.
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.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
