Sectoral Corporate Profits and Long-Run Stock Return Volatility in the United States: A GARCH-MIDAS Approach

IF 3.4 3区 经济学 Q1 ECONOMICS
Afees Salisu, Kazeem O. Isah, Ahamuefula Ephraim Ogbonna
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Abstract

This study aims to examine the usefulness of corporate profits in predicting the return volatility of sectoral stocks in the United States. We use a GARCH-MIDAS approach to keep the datasets in their original frequencies. The results show a consistently positive slope coefficient across various sectoral stocks. This implies that higher profits lead to increased trading of stocks and, subsequently, a higher volatility in the long run than usual. Furthermore, the analysis also extends to predictability beyond the in-sample. We find strong evidence that corporate profits can predict the out-of-sample long-run return volatility of sectoral stocks in the United States. These findings are significant for investors and portfolio managers.

Abstract Image

美国部门企业利润与长期股票回报波动:GARCH-MIDAS方法
本研究旨在检验公司利润在预测美国行业股票收益波动方面的有用性。我们使用GARCH-MIDAS方法来保持数据集的原始频率。结果显示,在各个行业股票中,斜率系数始终为正。这意味着更高的利润导致股票交易增加,随后,在长期内的波动性比通常情况下更高。此外,分析还扩展到样本内以外的可预测性。我们发现强有力的证据表明,公司利润可以预测美国行业股票的样本外长期回报波动。这些发现对投资者和投资组合经理来说意义重大。
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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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