The time-varying nature of social media sentiments in modeling stock returns
The time-varying nature of social media sentiments in modeling stock returns
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DOI：
10.1016/j.dss.2017.06.001
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发表时间：
2017-09
期刊：
影响因子：
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通讯作者：
C. Ho;P. Damien;B. Gu;Prabhudev Konana
中科院分区：
文献类型：
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作者：
C. Ho;P. Damien;B. Gu;Prabhudev Konana
本文的主要目标是回答以下问题：社交媒体情绪与股票回报之间的关系是否随时间变化？为了提供令人满意的响应，引入了一种新颖的方法——贝叶斯动态线性模型和看似不相关的回归的共生。两组道琼斯工业平均指数股票数据以及来自雅虎的相应社交媒体数据金融股留言板被用来进行全面的实证研究。一些主要调查结果如下： (a) 对上述问题的答复是肯定的； (b) 仅包含社交媒体情绪和市场回报的模型的表现至少与包含 Fama-French 和 Momentum 因子的模型一样好； (c) 两个数据集中，股票之间存在显着相关性，范围为 -0.8 到 0.6。
The broad aim of this paper is to answer the following query: is the relationship between social media sentiments and stock returns time-varying? To provide a satisfactory response, a novel methodology—a symbiosis of Bayesian Dynamic Linear Models and Seemingly Unrelated Regressions —is introduced. Two sets of Dow Jones Industrial Average stock data and corresponding social media data from Yahoo! Finance stock message boards are used in a comprehensive empirical study. Some key findings are: (a) Affirmative response to the above question; (b) Models with only social media sentiments and market returns perform at least as well as models that include Fama-French and Momentum factors; (c) There are significant correlations between stocks, ranging from −0.8 to 0.6 in both data sets.