The supraview of return predictive signals

By Jeremiah Green, John R. M. Hand, X. F. Zhang. Review of accounting studies, 2013

197 citations recorded by the source corpus.

Subfields: Accounting, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/7796147f1da033b232213ed4c305db9dac660156

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Citations in the corpus

Market maturity and mispricing (2016, unknown): “Third, with respect to the asset pricing model, I use both raw long/short returns [as in, for instance, Griffin, Kelly, and Nardari (2010)] and Fama and French (1993) threefactor adjusted abnormal returns [as in, for instance, Stambaugh, Yu, and Yuan (2012)].”
Nonlinear Shrinkage of the Covariance Matrix for Portfolio Selection: Markowitz Meets Goldilocks (2017, unknown): “McLean and Pontiff (2013) bring the tally up to 82 variables, and Green et al. (2013) to 333 variables.”
Empirical Asset Pricing via Machine Learning (2018, unknown): “(1)Green et al. (2013) count 330 stock-level predictive signals in published or circulated drafts.”
Does Academic Research Destroy Stock Return Predictability (2016, background): “Consistent with Green et al. (2012), the R 2 between anomalies ranges from 6% to 20%, thus there are benefits for sophisticated traders to consider multiple anomalies.”
Factor Models for Portfolio Selection in Large Dimensions: The Good, the Better and the Ugly (2019, unknown): “The literature on Markowitz portfolio selection in large dimensions—that is, when the number of assets is of the same magnitude as the number of observations—has experienced a large expansion over the last decade or so and is still growing; to list only a few examples, see Ledoit and Wolf (2003); Ja”
Tree-Based Conditional Portfolio Sorts: The Relation between Past and Future Stock Returns (2016, unknown): “Subrahmanyam (2010), Goyal (2011), Green et al. (2013) and Harvey et al. (2013) review as many as 330 anomalies that have been found by academic research and call for a synthesis of the existing literature.”
Stock Returns on Customer Satisfaction Do Beat the Market: Gauging the Effect of a Marketing Intangible (2016, background): “Green, Hand, and Zhang (2013) identified more than 300 anomalies and found that they were predominantly orthogonal, a finding also confirmed by McLean and Pontiff (2015).”