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Cited by 1,123

The DOI matches its Crossref record; 135 of the 135 references it cites were found in a registry or an index.

Investor Sentiment Aligned: A Powerful Predictor of Stock Returns

Open access
Huang, Dashan, Jiang, Fuwei, Tu, Jun, Zhou, Guofu·2015·Review of Financial Studies

Abstract

We propose a new investor sentiment index that is aligned with the purpose of predicting the aggregate stock market. By eliminating a common noise component in sentiment proxies, the new index has much greater predictive power than existing sentiment indices both in- and out-of-sample, and the predictability becomes both statistically and economically significant. In addition, it outperforms well recognized macroeconomic variables and can also predict cross-sectional stock returns sorted by industry, size, value, and momentum. The driving force of the predictive power appears stemming from investors’ biased belief about future cash flows.

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Crossref · 10.1093/rfs/hhu080

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Metadata

Authors
Huang, D., Jiang, F., Tu, J., & Zhou, G.
Venue
Review of Financial Studies
Published
2014-10-31
Volume
28
Issue
3
Pages
791-837
ISSN
  • 0893-9454 (ISSN-L)
  • 1465-7368
OpenAlex
W2101620928
Cited by
1,123
References
135
FWCI
58.67
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. https://app.cochat.ai/papers/10.1093/rfs/hhu080
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Huang, D., Jiang, F., Tu, J., & Zhou, G. (2015). Investor Sentiment Aligned: A Powerful Predictor of Stock Returns. Review of Financial Studies. https://doi.org/10.1093/rfs/hhu080

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.