Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle

By Rob Stambaugh, Jianfeng Yu, Yu Yuan. 2014

833 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/18bac40b8e2a47c1a6ddde9de0ecf9e311f5a410

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Citations in the corpus

Charles A. Dice Center for Research in Financial Economics The Implied Cost of Capital: A New Approach (2010, neutral): “…(Avramov, Chordia, Jostova, and Philipov, 2013), high short-sale constraints (Boehme, Danielsen, Kumar, and Sorescu, 2009; George and Hwang, 2011; Stambaugh, Yu, and Yuan, 2015), high leverage (Johnson, 2004), low institutional ownership (Nagel, 2005), low book-to-market equity (Barinov, 2013),…”
The Long of It: Odds That Investor Sentiment Spuriously Predicts Anomaly Returns (2014, neutral): “…of sentiment measures to predict returns include Brown and Cliff (2004, 2005), Lemmon and Portniaguina (2006), Baker and Wurgler (2007, 2012), Livnat and Petrovic (2008), Baker, Wurgler, and Yuan (2012), Antoniou, Doukas, and Subrahmanyam (2013), Stambaugh, Yu, and Yuan (2013), and Yu (2013).”
Short- and Long-Horizon Behavioral Factors (2019, neutral): “(2015), and Stambaugh and Yuan (2017) models achieve realized monthly Sharpe ratios of 0.”
Psychology-based Models of Asset Prices and Trading Volume (2018, background): “Stambaugh et al. (2015) combine two of the points noted above – that idiosyncratic volatility is a limit to arbitrage and that shorting is riskier than going long – to come up with an explanation for a puzzling fact from Section 2.2, namely that stocks with high idiosyncratic volatility have a…”
Roughing up Beta: Continuous vs. Discontinuous Betas, and the Cross-Section of Expected Stock Returns (2014, neutral): “For a recent discussion of the idiosyncratic volatility puzzle see also Stambaugh, Yu, and Yuan (2015). simultaneously controlling for multiple explanatory variables.”
A diagnostic criterion for approximate factor structure (2016, background): “02) ﬁnd only two latent factors. As observed in GOS, measures of limits-to-arbitrage and missing factor impact (not reported here) like those in Pontiff (2006), Ang et al. (2009), Lam and Wei (2011), Stambaugh et al. (2015) decrease with the 24 number of observable factors. Concerning the additional”