The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
On Predicting Stock Returns with Nearly Integrated Explanatory Variables
Abstract
Statistical inference in predictive regressions depends critically on the stochastic properties of the posited explanatory variable, in particular, its order of integration. Confidence intervals computed for the largest autoregressive root of many explanatory variables commonly used in predictive regressions, including the dividend yield, the book‐to‐market ratio, the short‐term rate of interest, and the term and default spreads, confirm uncertainty surrounding these variables' order of integration. We investigate the effects of this uncertainty on inferences drawn in predictive regressions. Once this uncertainty is accounted for, contrary to previous evidence, we find reliable evidence of predictability at shorter rather than at longer horizons.
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
Testing the null hypothesis of stationarity against the alternative of a unit root
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992) · Journal of Econometrics · doi:10.1016/0304-4076(92)90104-y · Cited by 12,633
FAMA, E. F. (1991) · The Journal of Finance · doi:10.1111/j.1540-6261.1991.tb04636.x · Cited by 5,350
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
Predicting excess stock returns out of sample: Can anything beat the historical average?
Campbell, J. Y., & Thompson, S. B. (2008) · Review of Financial Studies · doi:10.1093/rfs/hhm055 · Cited by 2,919
“These problems are exacerbated if researchers are data mining, considering large numbers of variables, and reporting only those results that are apparently statisticallysignificant(Fosteretal.,1997;Fersonetal.,2003).Anactiverecent literature discusses alternative econometric methods for correcting the bias and conduct…”
MethodThe 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
Bond risk, bond return volatility, and the term structure of interest rates
Viceira, L. M. (2012) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2011.02.018 · Cited by 136
Metadata
- Authors
- Torous, W., Valkanov, R., & Yan, S.
- Venue
- The Journal of Business
- Publisher
- University of Chicago Press
- Published
- 2004-10
- Volume
- 77
- Issue
- 4
- Pages
- 937-966
- ISSN
- 0021-9398 (ISSN-L)
- 1537-5374
- OpenAlex
- W1981440879
- Cited by
- 354
- References
- 3
- FWCI
- 46.44
- 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 Predicting Stock Returns with Nearly Integrated Explanatory Variables. https://app.cochat.ai/papers/10.1086/422634
- The paper
- Torous, W., Valkanov, R., & Yan, S. (2004). On Predicting Stock Returns with Nearly Integrated Explanatory Variables. The Journal of Business. https://doi.org/10.1086/422634
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.
