How are shorts informed

By Joseph E. Engelberg, Adam V. Reed, Matthew C. Ringgenberg. 2012

440 citations recorded by the source corpus.

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Citations in the corpus

Textual Sentiment in Finance: A Survey of Methods and Models (2014, methodology): “Engelberg (2008), Tetlock et al. (2008), Sinha (2010), and Engelberg et al. (2012) employ much wider news sources, and they all research firm-specific news.”
Short interest and stock price crash risk (2015, neutral): “6 See also Dechow et al. (2001), Christophe et al. (2004, 2010), Engelberg et al. (2012).”
Rumor Has It: Sensationalism in Financial Media (2015, background): “Engelberg, Reed, and Ringgenberg (2012) show that short sellers are better able to process publicly available information.”
Competition of the Informed: Does the Presence of Short Sellers Affect Insider Selling? (2015, methodology): “…that short sellers possess superior information: they are able to identify overvalued stocks (e.g., Desai et al., 2002; Cohen, et al., 2007; Boehmer et al., 2008; Diether et al., 2009; Boehmer, et al., 2010) or are particularly good at processing information (e.g., Engelberg et al., 2012).”
Short Interest and Aggregate Stock Returns (2016, background): “…traders who earn excess returns in compensation for processing firm-specific information (Boehmer, Jones, and Zhang, 2008; Karpoff and Lou, 2010; Engelberg, Reed, and Ringgenberg, 2012; Akbas, Boehmer, Erturk, and Sorescu, 2013).3 In our setting, we find that short sellers are also able to…”
In Short Supply: Short Sellers and Stock Returns (2015, positive): “…studies that examine short-selling at the individual stock level have consistently demonstrated that, as a group, short-sellers are sophisticated investors with superior information processing capabilities (e.g., Dechow et al. 2001; Desai et al. 2002; Drake et al. 2011; and Engelberg et al. 2012).”
Natural Language Processing in Accounting, Auditing and Finance: A Synthesis of the Literature with a Roadmap for Future Research (2016, background): “%) were associated with studies employing sentiment analysis (Sinha, 2010; Bollen et al., 2011a; Engelberg et al., 2012; Smales, 2014).”
Price Discovery without Trading: Evidence from Limit Orders (2019, background): “However, if HFTs’ algorithms better interpret public signals (like the short sellers on news days in Engelberg, Reed, and Ringgenberg (2012)) then it is more difficult to characterize HFTs as purely incorporating public information.”
Are Institutions Informed About News (2015, neutral): “Engelberg, Reed, and Ringgenberg (2012) combine data on short selling with news releases to show that short sellers' trading advantage comes largely from their ability to analyze publicly available information and not from being able to anticipate information before it becomes public.”
Intraday online investor sentiment and return patterns in the U.S. stock market (2017, methodology): “Whereas dictionary-based methods that use the HarvardIV dictionary or the Loughran and McDonald (2011) dictionary (LM hereafter) are widely used in the literature to measure sentiment in articles published in traditional media (Tetlock, 2007; Tetlock et al., 2008; Engelberg et al., 2012; Dougal et a”
Ownership Structure , Limits to Arbitrage and Stock Returns: Evidence from Equity Lending Markets (2016, positive): “This result is mostly concentrated in negative news events, consistent with the relation between informed short selling and future returns found by Boehmer et al. (2008) and Engelberg et al. (2012).”