Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 192

The DOI matches its Crossref record.

Anomalies: Seasonal Movements in Security Prices II: Weekend, Holiday, Turn of the Month, and Intraday Effects

Thaler, Richard·1987·Journal of Economic Perspectives

Abstract

This feature will report successful searches for disconfirming evidence--economic anomalies. As suggested by Thomas Kuhn, an economic anomaly is a result inconsistent with the economics paradigm. Economics is distinguished from other social sciences by the belief that most (all?) behavior can be explained by assuming that agents have stable, well-defined preferences and make rational choices consistent with those preferences in markets that (eventually) clear. An empirical result is anomalous if it is difficult to “rationalize,” or if implausible assumptions are necessary to explain it within the paradigm. In the previous issue, I reviewed the peculiar behavior of security prices in January. Stock prices tend to rise in January, particularly the prices of small firms and firms whose stock price has declined substantially over the past few years. Also, risky stocks earn most of their risk premiums in January. This issue will conclude our survey of seasonal anomalies in security prices with a review of four additional effects: the behavior of prices over weekends, before holidays, at the turn of each month, and within the day.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1257/jep.1.2.169

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cited by

See all 192

Metadata

Authors
Thaler, R.
Venue
Journal of Economic Perspectives
Published
1987-11-01
Volume
1
Issue
2
Pages
169-177
ISSN
0895-3309 (ISSN-L)
OpenAlex
W2024254877
Cited by
192
References
0
FWCI
6.54
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: Anomalies: Seasonal Movements in Security Prices II: Weekend, Holiday, Turn of the Month, and Intraday Effects. https://app.cochat.ai/papers/10.1257/jep.1.2.169
The paper
Thaler, R. (1987). Anomalies: Seasonal Movements in Security Prices II: Weekend, Holiday, Turn of the Month, and Intraday Effects. Journal of Economic Perspectives. https://doi.org/10.1257/jep.1.2.169

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.