The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects
Abstract
This paper provides empirical support for the notion that Autoregressive Conditional Heteroskedasticity (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, ARCH effects tend to disappear when volume is included in the variance equation.
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
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Cited by
Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility
ANDERSEN, T. G. (1996) · The Journal of Finance · doi:10.1111/j.1540-6261.1996.tb05206.x · Cited by 1,020
Dynamic Volume-Return Relation of Individual Stocks
Llorente, G., Michaely, R., Saar, G., & Wang, J. (2002) · Review of Financial Studies · doi:10.1093/rfs/15.4.1005 · Cited by 689
Modeling and predicting the CBOE market volatility index
Fernandes, M., Medeiros, M. C., & Scharth, M. (2014) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2013.11.004 · Cited by 278
(2016) · PubMed · Cited by 91
Metadata
- Authors
- LAMOUREUX, C. G., & LASTRAPES, W. D.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 1990-03
- Volume
- 45
- Issue
- 1
- Pages
- 221-229
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2110348891
- Cited by
- 1,113
- References
- 1
- FWCI
- 28.10
- 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: Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects. https://app.cochat.ai/papers/10.1111/j.1540-6261.1990.tb05088.x
- The paper
- LAMOUREUX, C. G., & LASTRAPES, W. D. (1990). Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.1990.tb05088.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.
