Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 512

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Quality minus junk

Open access
Asness, Clifford S., Frazzini, Andrea, Pedersen, Lasse Heje·2019·Review of Accounting Studies

Abstract

We define quality as characteristics that investors should be willing to pay a higher price for. Theoretically, we provide a tractable valuation model that shows how stock prices should increase in their quality characteristics: profitability, growth, and safety. Empirically, we find that high-quality stocks do have higher prices on average but not by a large margin. Perhaps because of this puzzlingly modest impact of quality on price, high-quality stocks have high risk-adjusted returns. Indeed, a quality-minus-junk (QMJ) factor that goes long high-quality stocks and shorts low-quality stocks earns significant risk-adjusted returns in the United States and across 24 countries. The price of quality varies over time, reaching a low during the internet bubble, and a low price of quality predicts a high future return of QMJ. Analysts’ price targets and earnings forecasts imply systematic quality-related errors in return and earnings expectations.

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 · 10.1007/s11142-018-9470-2

Cites

54 of 54 references verified0 citation errors · 0 not checkable

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

Cites

Show all 54 references

Metadata

Authors
Asness, C. S., Frazzini, A., & Pedersen, L. H.
Venue
Review of Accounting Studies
Published
2018-11-05
Volume
24
Issue
1
Pages
34-112
ISSN
  • 1380-6653 (ISSN-L)
  • 1573-7136
OpenAlex
W3124476761
Cited by
512
References
54
FWCI
60.20
Type
journal article
Language
en
Open access
hybrid

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: Quality minus junk. https://app.cochat.ai/papers/10.1007/s11142-018-9470-2
The paper
Asness, C. S., Frazzini, A., & Pedersen, L. H. (2019). Quality minus junk. Review of Accounting Studies. https://doi.org/10.1007/s11142-018-9470-2

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.