The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Value Spread
Abstract
We decompose the cross‐sectional variance of firms' book‐to‐market ratios using both a long U.S. panel and a shorter international panel. In contrast to typical aggregate time‐series results, transitory cross‐sectional variation in expected 15‐year stock returns causes only a relatively small fraction (20 to 25 percent) of the total cross‐sectional variance. The remaining dispersion can be explained by expected 15‐year profitability and persistence of valuation levels. Furthermore, this fraction appears stable across time and across types of stocks. We also show that the expected return on value‐minus‐growth strategies is atypically high at times when their spread in book‐to‐market ratios is wide.
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Citations
Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
Cited by
From efficient markets theory to behavioral finance
Shiller, R. J. (2003) · Journal of Economic Perspectives · doi:10.1257/089533003321164967 · Cited by 1,835
A Global Version of Samuelson's Dictum
Xiao, Y., Yan, H., & Zhang, J. (2022) · American Economic Review: Insights · doi:10.1257/aeri.20210186 · Cited by 8
Metadata
- Authors
- Cohen, R. B., Polk, C., & Vuolteenaho, T.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2003-03-21
- Volume
- 58
- Issue
- 2
- Pages
- 609-641
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3125275455
- Cited by
- 463
- References
- 1
- FWCI
- 25.95
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cohen, R. B., Polk, C., & Vuolteenaho, T. (2003). The Value Spread. The Journal of Finance. https://doi.org/10.1111/1540-6261.00539
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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.
