The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Global, local, and contagious investor sentiment
Open accessAbstract
We construct investor sentiment indices for six major stock markets and decompose them into one global and six local indices. In a validation test, we find that relative sentiment is correlated with the relative prices of dual-listed companies. Global sentiment is a contrarian predictor of country-level returns. Both global and local sentiment are contrarian predictors of the time-series of cross-sectional returns within markets: When sentiment is high, future returns are low on relatively difficult to arbitrage and difficult to value stocks. Private capital flows appear to be one mechanism by which sentiment spreads across markets and forms global sentiment.
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Cites
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Cited by
Investor Sentiment Aligned: A Powerful Predictor of Stock Returns
Huang, D., Jiang, F., Tu, J., & Zhou, G. (2015) · Review of Financial Studies · doi:10.1093/rfs/hhu080 · Cited by 1,123
Forecasting the equity risk premium: the role of technical indicators
Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014) · Management Science · doi:10.1287/mnsc.2013.1838 · Cited by 1,003
Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle
STAMBAUGH, R. F., YU, J., & YUAN, Y. (2015) · The Journal of Finance · doi:10.1111/jofi.12286 · Cited by 940
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Self-citationRisk Everywhere: Modeling and Managing Volatility
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Metadata
- Authors
- Baker, M., Wurgler, J., & Yuan, Y.
- Venue
- Journal of Financial Economics
- Publisher
- Elsevier BV
- Published
- 2012-05
- Volume
- 104
- Issue
- 2
- Pages
- 272-287
- ISSN
- 0304-405X (ISSN-L)
- OpenAlex
- W3123834602
- Cited by
- 1,018
- References
- 60
- FWCI
- 69.42
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.