The short of it

By Rob Stambaugh, Jianfeng Yu, Yuehuan Yuan. 2012

1,178 citations recorded by the source corpus.

This study explores the role of investor sentiment in a broad set of anomalies in cross-sectional stock returns. We consider a setting where the presence of market-wide sentiment is combined with the argument that overpricing should be more prevalent than underpricing, due to short-sale impediments. Long-short strategies that exploit the anomalies exhibit proﬁts consistent with this setting. First, each anomaly is stronger—its long-short strategy is more proﬁtable—following high levels of sentiment. Second, the short leg of each strategy is more proﬁtable following high sentiment. Finally, sentiment exhibits no relation to returns on the long legs of the strategies.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/c5dc4ca15b45f64bdfbf5708d5b9e9d639c9a4ac

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Citations in the corpus

Cash Flow Duration and the Term Structure of Equity Returns (2018, positive): “Antoniou et al. (2012b) show that the CAPM holds in times of low investor sentiment while Stambaugh, Yu, and Yuan (2012) study 11 anomalies and demonstrate that they are larger following periods of high investor sentiment.”
Googling Investor Sentiment around the World (2019, neutral): “…Das and Chen (2007), Edmans, Garcia, and Norli (2007), Tetlock (2007), Barber, Odean, and Zhu (2009), Kaplanski and Levy (2010), Hwang (2011), Yu and Yuan (2011), Baker et al. (2012), Stambaugh et al. (2012), (2014), Huang et al. (2015), Da et al. (2015), Sibley et al. (2016), and Soo (2018)).”
Corporate Social Responsibility and Market Efficiency: Evidence from ESG and Misvaluation Measures (2020, background): “This awareness is mirrored in public sentiment which in general has been shown to affect the pricing of securities (Baker and Wurgler, 2006; Stambaugh et al., 2012; Yu and Yuan, 2011).”
Investor sentiment and stock return volatility: Evidence from the Johannesburg Stock Exchange (2019, result): “This is consistent with a study by Stambaugh, Yu, and Yuan (2012) on the US market and Dalika and Seetharam (2015) on the South African market.”
Investor sentiment and the MAX effect (2014, methodology): “Following Baker and Wurgler (2007) and Stambaugh et al. (2012), we define a high (low) sentiment month as one in which the BW index is above (below) the sample median value, and denote these sentiment states by 1 and 0 respectively.2 2 Fig.”
Predicting anomaly performance with politics, the weather, global warming, sunspots, and the stars. (2014, background): “Baker and Wurgler (2006), Lemmon and Portniaguina (2006), and Stambaugh, Yu, and Yuan (2012) find that investor sentiment, as measured by the University of Michigan survey of consumer sentiment, the Conference Board survey of consumer confidence, and the Baker-Wurgler sentiment index, has…”
Ownership Structure , Limits to Arbitrage and Stock Returns: Evidence from Equity Lending Markets (2016, positive): “5Autore et al. (2015) and Blocher et al. (2013) show that hard-to-borrow stocks can become highly overvalued and Stambaugh et al. (2012) and Avramov et al. (2013) find that profits from anomaly-based strategies reside mostly on the short-side of the trade.”
Overnight Returns and Firm-Specific Investor Sentiment (2018, background): “…Mergenthaler (2012), Gao and Suss (2015), Huang, Jiang, Tu, and Zhou (2015), Lee, Shleifer, and Thaler (1991), Lemmon and Portniaguina (2006), Ljungqvist, Nanda, and Singh (2006), Neal and Wheatley (1998), Qui and Welch (2004), Ritter (1991), Stambaugh, Yu, and Yuan (2012), and Yu and Yuan (2011).”
Investor sentiment aligned: : A powerful predictor of stock returns (2015, methodology): “Following Stambaugh, Yu, and Yuan (2012), we classify a month as high (low) sentiment if the sentiment level (SPLS) in the previous month is above (below) its median value for the sample period, and compute the R2high and R 2 low statistics for the high and low sentiment periods, respectively, in a…”
The Long of It: Odds That Investor Sentiment Spuriously Predicts Anomaly Returns (2014, positive): “Out of 200 million simulated regressors, we find none that jointly support the three hypotheses in Stambaugh, Yu, and Yuan (2012) as strongly as investor sentiment.”
Institutional Investors and Stock Return Anomalies (2016, background): “…anomalies considered.1 Notably, in nine out of the twelve anomalies there is greater institutional buying in short-leg stocks than in long-leg stocks – despite the fact that anomaly returns are largely driven by the negative returns of the short-leg portfolios [Stambaugh, Yu, and Yuan (2012)].”
Time-Varying Liquidity and Momentum Profits (2016, background): “The effect of liquidity is robust to, and partially subsumes the recent evidence that momentum payoffs depend on inter-temporal variation in investor sentiment, as documented by Stambaugh, Yu, and Yuan (2012) and Antoniou, Doukas, and Subrahmanyam (2013).”
Investor sentiment in the stock market (2013, positive): “Stambaugh et al. (2012) used a predictive regression to assess the effect of sentiment indicators on anomalies in the subsequent month.”
Public Sentiment and the Price of Corporate Sustainability (2020, positive): “…as a function of public sentiment represents new evidence that not only investor sentiment about the stock market (Baker and Wurgler 2006; Yu and Yuan 2011; Stambaugh, Yu, and Yuan 2012) but also public sentiment about companies’ sustainability activities affects the valuation of a company.”
Can investor sentiment be a momentum time-series predictor? Evidence from China (2017, result): “Lee et al. (1991) contend that investor sentiment is more of a size story: Small firms are influenced more than large firms, which is later confirmed by other studies (Baker & Wurgler 2006, 2007; Baker et al. 2012; Stambaugh et al. 2012).”