The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
International Stock Return Predictability: What Is the Role of the United States?
Abstract
We investigate lead‐lag relationships among monthly country stock returns and identify a leading role for the United States: lagged U.S. returns significantly predict returns in numerous non‐U.S. industrialized countries, while lagged non‐U.S. returns display limited predictive ability with respect to U.S. returns. We estimate a news‐diffusion model, and the results indicate that return shocks arising in the United States are only fully reflected in equity prices outside of the United States with a lag, consistent with a gradual information diffusion explanation of the predictive power of lagged U.S. returns.
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Cited by
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Dissecting Characteristics Nonparametrically
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Can ChatGPT forecast stock price movements? Return predictability and large language models
Lopez-Lira, A., & Tang, Y. (2026) · Journal of Financial Economics · doi:10.1016/j.jfineco.2026.104335 · Cited by 425
Bond Risk Premiums with Machine Learning
Bianchi, D., Büchner, M., & Tamoni, A. (2021) · The Review of Financial Studies · doi:10.1093/rfs/hhaa062 · Cited by 409
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Metadata
- Authors
- RAPACH, D. E., STRAUSS, J. K., & ZHOU, G.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2013-07-16
- Volume
- 68
- Issue
- 4
- Pages
- 1633-1662
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2319405822
- Cited by
- 678
- References
- 80
- FWCI
- 63.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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