Stock returns and investor sentiment: textual analysis and social media
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Stock returns and investor sentiment: textual analysis and social media Zachary McGurk1 · Adam Nowak2 · Joshua C. Hall2
© Academy of Economics and Finance 2019
Abstract The behavioral finance literature has found that investor sentiment has predictive ability for equity returns. This differs from standard finance theory, which provides no role for investor sentiment. We examine the relationship between investor sentiment and stock returns by employing textual analysis on social media posts. We find that our investor sentiment measure has a positive and significant effect on abnormal stock returns. These findings are consistent across a number of different models and specifications, providing further evidence against non-behavioral theories. Keywords Investor sentiment · Supervised learning · Stock returns · Social media · Sufficient reduction · Predictive regression JEL Classification G12 · G13 · G14
1 Introduction As described in Malkiel and Fama (1970), the Efficient Market Hypothesis (EMH) predicts asset prices fully reflect all available information. Rational investors in response choose asset portfolios which diversify away idiosyncratic risk. As such
Joshua C. Hall
[email protected] Zachary McGurk [email protected] Adam Nowak [email protected] 1
Department of Economics & Finance, Canisus College, Buffalo, NY, USA
2
John Chambers College of Business and Economics, West Virginia University, Morgantown, WV 26506, USA
Journal of Economics and Finance
asset prices are only a function of market fundamentals. When asset prices are mispriced through the actions of irrational investors, rational investors are able to use arbitrage to correct asset prices. In contrast to the EMH, behavioral finance theory suggests that the feelings of irrational investors (Investor Sentiment) drive a portion of asset prices. Due to the specific characteristics of some assets (small, hard to value, limited information, etc.), arbitrage by rational investors becomes costly and asset prices are perpetually mispriced.1 Recent empirical studies have found Investor Sentiment to be related to stock returns.2 While the empirical finance literature has found Investor Sentiment to be a valid predictor of the cross section and time series of stock returns, studies differ how the Investor Sentiment measure is estimated. As noted by Baker and Wurgler (2006, 2007) Investor Sentiment is difficult to directly measure. As a result, the literature has relied on proxies developed from market/investor surveys, data mining methods, and textual analysis from annual reports, commercial media, and social media. Due to data limitations, the market/investor survey and data mining methods literature focus on the impact of investor sentiment on returns over monthly or larger time horizons. While most of these studies show a relationship between asset returns and investor sentiment, these studies may not capture the full impact of investor sentiment. If asset markets are partially efficient (i.e. investor sentiment does not determine a
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