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The Twitter myth revisited: Intraday investor sentiment, Twitter activity and individual-level stock return volatility
被引:80
作者:
Behrendt, Simon
[1
]
Schmidt, Alexander
[2
]
机构:
[1] Zeppelin Univ, Dept Empir Finance & Econometr, Friedrichshafen, Germany
[2] Univ Hohenheim, Dept Econometr & Stat, D-70593 Stuttgart, Germany
关键词:
Return volatility;
Investor sentiment;
Twitter;
Intraday;
Forecasting;
SOCIAL MEDIA;
MARKETS;
NOISE;
MODEL;
PATTERNS;
TRADES;
NEWS;
D O I:
10.1016/j.jbankfin.2018.09.016
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
Taking an intraday perspective, we study the dynamics of individual-level stock return volatility, measured by absolute 5-minute returns, and Twitter sentiment and activity. After accounting for the intraday periodicity in absolute returns, we discover some statistically significant co-movements of intraday volatility and information from stock-related Tweets for all constituents of the Dow Jones Industrial Average. However, economically, the effects are of negligible magnitude and out-of-sample forecast performance is not improved when including Twitter sentiment and activity as exogenous variables. From a practical point of view, we find that high-frequency Twitter information is not particularly useful for highly active investors with access to such data for intraday volatility assessment and forecasting when considering individual-level stocks. (C) 2018 Elsevier B.V. All rights reserved.
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页码:355 / 367
页数:13
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