The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Mental Accounting, Loss Aversion, and Individual Stock Returns
Abstract
We study equilibrium firm‐level stock returns in two economies: one in which investors are loss averse over the fluctuations of their stock portfolio, and another in which they are loss averse over the fluctuations of individual stocks that they own. Both approaches can shed light on empirical phenomena, but we find the second approach to be more successful: In that economy, the typical individual stock return has a high mean and excess volatility, and there is a large value premium in the cross section which can, to some extent, be captured by a commonly used multifactor model.
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Cites
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Cited by
The Cross‐Section of Volatility and Expected Returns
ANG, A., HODRICK, R. J., XING, Y., & ZHANG, X. (2006) · The Journal of Finance · doi:10.1111/j.1540-6261.2006.00836.x · Cited by 4,508
Limited attention, information disclosure, and financial reporting
Hirshleifer, D., & Teoh, S. H. (2003) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2003.10.002 · Cited by 2,324
Chapter 18 A survey of behavioral finance
Barberis, N., & Thaler, R. (2003) · Handbook of the Economics of Finance · doi:10.1016/s1574-0102(03)01027-6 · Cited by 1,441
Self-citationGoyal, A., & Santa‐Clara, P. (2003) · The Journal of Finance · doi:10.1111/1540-6261.00555 · Cited by 1,161
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
Metadata
- Authors
- Barberis, N., & Huang, M.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2001-08
- Volume
- 56
- Issue
- 4
- Pages
- 1247-1292
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2136408930
- Cited by
- 979
- References
- 42
- FWCI
- 26.61
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
