2021
DOI: 10.1017/s0022109021000090
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Investor Attention and Stock Returns

Abstract: We propose an investor attention index based on proxies in the literature and find that it predicts the stock market risk premium significantly, both in sample and out of sample, whereas every proxy individually has little predictive power. The index is extracted using partial least squares, but the results are similar by the scaled principal component analysis. Moreover, the index can deliver sizable economic gains for mean-variance investors in asset allocation. The predictive power of the investor attention… Show more

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Cited by 153 publications
(27 citation statements)
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References 71 publications
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“…Specifically, the results based on the AIC test suggest that the model considering one‐period lagged returns is optimal. This result is consistent with the convention of return forecasting (see, e.g., Chen et al, 2022; Jiang et al, 2019; Neely et al, 2014). Thus, we use one‐period lagged futures returns as a predictor.…”
Section: Resultssupporting
confidence: 90%
See 1 more Smart Citation
“…Specifically, the results based on the AIC test suggest that the model considering one‐period lagged returns is optimal. This result is consistent with the convention of return forecasting (see, e.g., Chen et al, 2022; Jiang et al, 2019; Neely et al, 2014). Thus, we use one‐period lagged futures returns as a predictor.…”
Section: Resultssupporting
confidence: 90%
“…If out‐of‐sample R 2 is greater than 0, then lagged product‐side returns show predictive power. Following the relevant literature (see, e.g., Chen et al, 2022; He & Zhang, 2022; He et al, 2021; Rapach et al, 2013; Zhang et al, 2019, 2022), we use the Clark and West (2007) (CW) statistic to test the statistical significance of out‐of‐sample R 2 . This statistic is a correction of Diebold and Mariano (1995) statistic and is demonstrated to be suitable for nested models.…”
Section: Out‐of‐sample Evidencementioning
confidence: 99%
“…Financial information may “expose” too much of the hardships caused by the epidemic to firms and lead to investor disinvestment and creditor redemptions. In a confusing market, firms may be favored by investors and external stakeholders because the information is “readable” and “reassuring” (Aubert & Grudnitski, 2011; Chen et al, 2022; Daske, 2006). Second, high information asymmetry is the main reason for poor credit access during the epidemic.…”
Section: Literature Review and Hypothesis Developmentmentioning
confidence: 99%
“…14 Alternative sentiment indexes has been developed by Chen, Tang, Yao and Zhou(2020). See Zhou(2018) for a review.…”
Section: D) Lagged Information Variablesmentioning
confidence: 99%