南非 Twitter 政策的不确定性与股票回报:来自时变格兰杰因果关系的证据

IF 3.4 3区 经济学 Q1 ECONOMICS Journal of Forecasting Pub Date : 2024-05-10 DOI:10.1002/for.3148
Kingstone Nyakurukwa, Yudhvir Seetharam
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引用次数: 0

摘要

本研究采用时变格兰杰因果关系模型,结合推特政策不确定性和南非股票回报率两个代理变量,研究 2017 年至 2023 年期间推特不确定性与南非股票回报率之间的因果关系。研究结果表明,Twitter 市场不确定性和 Twitter 经济不确定性分别在 COVID-19 大流行和俄乌战争爆发前后对 JSE 股票回报率产生了主要影响。研究结果还显示,使用推特的不确定性指数进行样本外预测效果显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Twitter policy uncertainty and stock returns in South Africa: Evidence from time-varying Granger causality

The study uses time-varying Granger causality models that incorporate two proxies for Twitter policy uncertainty and South African returns stock returns to investigate the causal relationship between Twitter uncertainty and South African stock returns for the period between 2017 and 2023. The findings demonstrate that Twitter Market Uncertainty and Twitter Economic Uncertainty mostly lead JSE returns around the start of the COVID-19 pandemic and the Russia-Ukranainan war respectively. The findings also show significant out-of-sample forecasts using uncertainty indexes from Twitter.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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