解释和预测跨时间和行业的动量表现变化

IF 3.4 3区 经济学 Q1 ECONOMICS
Konstantinos Mamais, Dimitrios Thomakos, Prodromos Vlamis
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引用次数: 0

摘要

在本文中,我们分析了纳斯达克指数及其主要行业组成部分在经济衰退、经济扩张、战争、金融危机和新冠肺炎健康危机等一系列重要经济事件中的走势。我们试图解释动量如何在不同的经济条件下作为一种投资策略,以及理解它如何在样本内工作是否有助于对未来财务业绩的样本外预测。我们方法的新颖之处在于识别和利用动量特征,从而根据我们所处的经济活动时期对行业进行排名。这些排名经过测试,发现对样本内和样本外的财务业绩预测是稳健的,从而使我们推测,人们可以使用过去经济状况的识别来推断未来的投资。我们的研究结果表明,这种建议的方法在实践中非常有效,因此是一种可行的、完全可解释的投资策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Explaining and Predicting Momentum Performance Shifts Across Time and Sectors

Explaining and Predicting Momentum Performance Shifts Across Time and Sectors

In this paper, we analyze the momentum of the NASDAQ and its major sectoral components across an extended period of key economic events, which include recessions, expansions, wars, financial crises, and the Covid-19 health crisis. We seek to explain how momentum works as an investment strategy during different economic conditions and whether understanding how it works in-sample can contribute to the out-of-sample forecasting of future financial performance. The novelty of our approach rests in the identification and exploitation of momentum characteristics that lead to the ranking of sectors depending on the period of economic activity that we are in. These rankings are tested and found to be robust for the in-sample and the out-of-sample forecasting of financial performance, thus leading us to surmise that one can use the identification of past economic conditions to extrapolate for investing accordingly in the future. Our results indicate that this suggested approach works very well in practice and is, thus, a viable and fully interpretable investment strategy.

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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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