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Average Returns, B/M, and Share Issues
Open accessAbstract
The book‐to‐market ratio (B/M) is a noisy measure of expected stock returns because it also varies with expected cashflows. Our hypothesis is that the evolution of B/M, in terms of past changes in book equity and price, contains independent information about expected cashflows that can be used to improve estimates of expected returns. The tests support this hypothesis, with results that are largely but not entirely similar for Microcap stocks (below the 20 th NYSE market capitalization percentile) and All but Micro stocks (ABM).
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Citations
Cited by
Size, value, and momentum in international stock returns
Fama, E. F., & French, K. R. (2012) · Journal of Financial Economics · doi:10.1016/j.jfineco.2012.05.011 · Cited by 1,767
Self-citationMaxing out: Stocks as lotteries and the cross-section of expected returns
Bali, T. G., Cakici, N., & Whitelaw, R. F. (2011) · Journal of Financial Economics · doi:10.1016/j.jfineco.2010.08.014 · Cited by 1,624
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
Geographic dispersion and stock returns
García, D., & Norli, Ø. (2012) · Journal of Financial Economics · doi:10.1016/j.jfineco.2012.06.007 · Cited by 543
Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns
Bali, T. G., Cakici, N., & Whitelaw, R. F. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1262416 · Cited by 517
Metadata
- Authors
- FAMA, E. F., & FRENCH, K. R.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2008-11-11
- Volume
- 63
- Issue
- 6
- Pages
- 2971-2995
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3122809341
- Cited by
- 310
- References
- 0
- FWCI
- 28.00
- Type
- journal article
- Language
- en
- Open access
- green
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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.
