The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Interpreting the Value Effect Through the Q-Theory: An Empirical Investigation
Abstract
This article interprets the well-known value effect through the implications of standard Q-theory. An investment growth factor, defined as the difference in returns between low-investment stocks and high-investment stocks, contains information similar to the Fama and French (1993) value factor (HML), and can explain the value effect about as well as HML. In the cross-section, portfolios of firms with low investment growth rates (IGRs) or low investment-to-capital ratios have significantly higher average returns than those with high IGRs or high investment-to-capital ratios. The value effect largely disappears after controlling for investment, and the investment effect is robust against controls for the marginal product of capital. These results are consistent with the predictions of a standard Q-theory model with a stochastic discount factor.
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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
The Cross‐Section of Expected Stock Returns
FAMA, E. F., & FRENCH, K. R. (1992) · The Journal of Finance · doi:10.1111/j.1540-6261.1992.tb04398.x · Cited by 17,261
Risk, Return, and Equilibrium: Empirical Tests
Fama, E. F., & MacBeth, J. D. (1973) · Journal of Political Economy · doi:10.1086/260061 · Cited by 14,258
Large Sample Properties of Generalized Method of Moments Estimators
Hansen, L. P. (1982) · Econometrica · doi:10.2307/1912775 · Cited by 13,467
Multifactor Explanations of Asset Pricing Anomalies
FAMA, E. F., & FRENCH, K. R. (1996) · The Journal of Finance · doi:10.1111/j.1540-6261.1996.tb05202.x · Cited by 6,700
A General Equilibrium Approach To Monetary Theory
Tobin, J. (1969) · Journal of Money, Credit and Banking · doi:10.2307/1991374 · Cited by 5,294
Financing Constraints and Corporate Investment
Fazzari, S., Hubbard, R. G., & Petersen, B. (1987) · National Bureau of Economic Research · doi:10.3386/w2387 · Cited by 4,351
Tobin's Marginal q and Average q: A Neoclassical Interpretation
Hayashi, F. (1982) · Econometrica · doi:10.2307/1912538 · Cited by 2,735
Regression standard errors in clustered samples
Rogers, W. H. (1993) · Stata technical bulletin · Cited by 2,694
A Test of the Efficiency of a Given Portfolio
Gibbons, M. R., Ross, S. A., & Shanken, J. (1989) · Econometrica · doi:10.2307/1913625 · Cited by 2,350
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… and the Cross-Section of Expected Returns
Harvey, C. R., Liu, Y., & Zhu, H. (2016) · Review of Financial Studies · doi:10.1093/rfs/hhv059 · Cited by 2,119
The short of it: Investor sentiment and anomalies
Stambaugh, R. F., Yu, J., & Yuan, Y. (2012) · Journal of Financial Economics · doi:10.1016/j.jfineco.2011.12.001 · Cited by 1,736
Hou, K., Xue, C., & Zhang, L. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhy131 · Cited by 989
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
Stambaugh, R. F., & Yuan, Y. (2017) · The Review of Financial Studies · doi:10.1093/rfs/hhw107 · Cited by 894
Metadata
- Authors
- Xing, Y.
- Venue
- Review of Financial Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-09-28
- Volume
- 21
- Issue
- 4
- Pages
- 1767-1795
- ISSN
- 0893-9454 (ISSN-L)
- 1465-7368
- OpenAlex
- W2019195375
- Cited by
- 393
- References
- 47
- FWCI
- 23.03
- 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).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
