The Characteristics that Provide Independent Information about Average U.S. Monthly Stock Returns

By Jeremiah Green, John R. M. Hand, Frank Zhang. 2017

480 citations recorded by the source corpus.

Subfields: Accounting, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/b5ac1023a8fdee47fd43f99ccecb18779066ecc1

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Citations in the corpus

Discussion of “disclosure processing costs, investors' information choice, and equity market outcomes: A review” (2020, methodology): “This mechanism builds on the insights of Grossman and Stiglitz (1980).8 We assume that it is commonly known that q ¼ 1 (i.e., it is commonly known that the public signal is payoff relevant).”
Taming the Factor Zoo: A Test of New Factors (2019, unknown): “Green, Hand, and Zhang (2017) test 94 firm characteristics using Fama-Macbeth regressions and find that 8 to 12 characteristics are significant independent determinants of average returns.”
Empirical Asset Pricing via Machine Learning (2018, methodology): “30The 94 predictive characteristics are based on Green et al. (2017), and we adapt the SAS code available from Jeremiah Green’s website and extend the sample period back to 1957.”
Anomalies across the globe: Once public, no longer existent? (2020, unknown): “In Panel D, we only keep anomalies which are also taken into account in at least one of the following meta studies on return predictability: Green et al. (2013), Green et al. (2017), Harvey et al. (2016), Hou et al. (2018), and McLean and Pontiff (2016).”
Shrinking the Cross Section∗ (2017, unknown): “Green et al. (2017) and Harvey et al. (2015) adjust significance thresholds to account for such data mining.”
ESG Rating Disagreement and Stock Returns (2019, result): “Other research also has shown that return predictability fell sharply after 2003 (Green, Hand, and Zhang 2017).”
Forecasting: theory and practice (2020, background): “…of cross-sectional stock returns based on a large number of firm characteristics from the cross-sectional literature (e.g., Harvey et al., 2016; McLean and Pontiff, 2016; Hou et al., 2020), extending the conventional OLS approach of Haugen and Baker (1996), Lewellen (2015), and Green et al. (2017).”
A Transaction-Cost Perspective on the Multitude of Firm Characteristics (2020, unknown): “Indeed, Green, Hand, and Zhang (2017) considers 94 characteristics and finds using Fama-MacBeth regressions that 12 are jointly signifi- 5In addition to the 50 firm-specific characteristics, we consider also beta (i.e., the exposure of each stock to the market-return factor) because of its…”