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.
引用
收藏
页码:355 / 367
页数:13
相关论文
共 35 条
  • [31] GOOD VOLATILITY, BAD VOLATILITY: SIGNED JUMPS AND THE PERSISTENCE OF VOLATILITY
    Patton, Andrew J.
    Sheppard, Kevin
    [J]. REVIEW OF ECONOMICS AND STATISTICS, 2015, 97 (03) : 683 - 697
  • [32] The limits of arbitrage
    Shleifer, A
    Vishny, RW
    [J]. JOURNAL OF FINANCE, 1997, 52 (01) : 35 - 55
  • [33] Tweets and Trades: the Information Content of Stock Microblogs
    Sprenger, Timm O.
    Tumasjan, Andranik
    Sandner, Philipp G.
    Welpe, Isabell M.
    [J]. EUROPEAN FINANCIAL MANAGEMENT, 2014, 20 (05) : 926 - 957
  • [34] News or Noise? Using Twitter to Identify and Understand Company-specific News Flow
    Sprenger, Timm O.
    Sandner, Philipp G.
    Tumasjan, Andranik
    Welpe, Isabell M.
    [J]. JOURNAL OF BUSINESS FINANCE & ACCOUNTING, 2014, 41 (7-8) : 791 - 830
  • [35] Twitter financial community sentiment and its predictive relationship to stock market movement
    Yang, Steve Y.
    Mo, Sheung Yin Kevin
    Liu, Anqi
    [J]. QUANTITATIVE FINANCE, 2015, 15 (10) : 1637 - 1656