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What Drives Firm‐Level Stock Returns?
Open accessAbstract
I use a vector autoregressive model (VAR) to decompose an individual firm's stock return into two components: changes in cash‐flow expectations (i.e., cash‐flow news) and changes in discount rates (i.e., expected‐return news). The VAR yields three main results. First, firm‐level stock returns are mainly driven by cash‐flow news. For a typical stock, the variance of cash‐flow news is more than twice that of expected‐return news. Second, shocks to expected returns and cash flows are positively correlated for a typical small stock. Third, expected‐return‐news series are highly correlated across firms, while cash‐flow news can largely be diversified away in aggregate portfolios.
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Cites
Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
JEGADEESH, N., & TITMAN, S. (1993) · The Journal of Finance · doi:10.1111/j.1540-6261.1993.tb04702.x · Cited by 11,584
Dividend Yields and Expected Stock Returns: Alternative Procedures for Inference and Measurement
Hodrick, R. J. (1992) · Review of Financial Studies · doi:10.1093/rfs/5.3.351 · Cited by 1,523
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Campbell, J. L., Chen, H., Dhaliwal, D. S., Lu, H.-M., & Steele, L. B. (2014) · Review of Accounting Studies · doi:10.1007/s11142-013-9258-3 · Cited by 923
Accounting conservatism and firm investment efficiency
García Lara, J. M., García Osma, B., & Penalva, F. (2016) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2015.07.003 · Cited by 659
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KELLY, B., & PRUITT, S. (2013) · The Journal of Finance · doi:10.1111/jofi.12060 · Cited by 584
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Metadata
- Authors
- Vuolteenaho, T.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2002-02
- Volume
- 57
- Issue
- 1
- Pages
- 233-264
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3124909920
- Cited by
- 987
- References
- 2
- FWCI
- 42.08
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.
