The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
On the Predictability of Stock Returns: An Asset‐Allocation Perspective
Abstract
Sample evidence about the predictability of monthly stock returns is considered from the perspective of a risk‐averse Bayesian investor who must allocate funds between stocks and cash. The investor uses the sample evidence to update prior beliefs about the parameters in a regression of stock returns on a set of predictive variables. The regression relation can seem weak when described by usual statistical measures, but the current values of the predictive variables can exert a substantial influence on the investor's portfolio decision, even when the investor's prior beliefs are weighted against predictability.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Cited by
Investing for the Long Run when Returns Are Predictable
Barberis, N. (2000) · The Journal of Finance · doi:10.1111/0022-1082.00205 · Cited by 1,372
The Dog That Did Not Bark: A Defense of Return Predictability
Cochrane, J. H. (2008) · Review of Financial Studies · doi:10.1093/rfs/hhm046 · Cited by 1,227
Investor Sentiment Aligned: A Powerful Predictor of Stock Returns
Huang, D., Jiang, F., Tu, J., & Zhou, G. (2015) · Review of Financial Studies · doi:10.1093/rfs/hhu080 · Cited by 1,123
Forecasting the equity risk premium: the role of technical indicators
Neely, C. J., Rapach, D. E., Tu, J., & Zhou, G. (2014) · Management Science · doi:10.1287/mnsc.2013.1838 · Cited by 1,003
Optimal Portfolio Choice with Parameter Uncertainty
Kan, R., & Zhou, G. (2007) · Journal of Financial and Quantitative Analysis · doi:10.1017/s0022109000004129 · Cited by 699
Metadata
- Authors
- KANDEL, S., & STAMBAUGH, R. F.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 1996-06
- Volume
- 51
- Issue
- 2
- Pages
- 385-424
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W3123320210
- Cited by
- 673
- References
- 1
- FWCI
- 18.63
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: On the Predictability of Stock Returns: An Asset‐Allocation Perspective. https://app.cochat.ai/papers/10.1111/j.1540-6261.1996.tb02689.x
- The paper
- KANDEL, S., & STAMBAUGH, R. F. (1996). On the Predictability of Stock Returns: An Asset‐Allocation Perspective. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.1996.tb02689.x
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.
