Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 219

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Does Idiosyncratic Volatility Proxy for Risk Exposure?

Open access
Chen, Zhanhui, Petkova, Ralitsa·2012·Review of Financial Studies

Abstract

We decompose aggregate market variance into an average correlation component and an average variance component. First, we show that the average variance component commands a negative price of risk in the cross-section of portfolios sorted by idiosyncratic volatility. The average correlation component is not significantly priced. Second, we show that portfolios with high idiosyncratic volatility relative to the Fama-French model have positive exposures to innovations in average stock variance and therefore lower expected returns. On the other hand, portfolios with low idiosyncratic volatility relative to the Fama-French model have negative exposures to innovations in average stock variance and therefore higher expected returns. This difference in the variance loadings between high and low idiosyncratic risk stocks, combined with the negative premium for average stock variance, completely explains the idiosyncratic volatility puzzle of Ang, et al. (2006, 2009). Idiosyncratic risk appears to be related to expected returns because it is a proxy for exposure to average stock variance. We explore a growth options explanation behind our results. Stocks with high idiosyncratic volatility have higher research and development expenditures than stocks with low idiosyncratic volatility, and therefore are likely to have more growth options. This explains the positive relation between high idiosyncratic volatility portfolios and aggregate market variance.

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 · 10.1093/rfs/hhs084

Cites

1 of 1 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 1 references

Cited by

See all 219

Metadata

Authors
Chen, Z., & Petkova, R.
Venue
Review of Financial Studies
Published
2012-07-31
Volume
25
Issue
9
Pages
2745-2787
ISSN
  • 0893-9454 (ISSN-L)
  • 1465-7368
OpenAlex
W2148124701
Cited by
219
References
1
FWCI
25.47
Type
journal article
Language
en
Open access
green

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: Does Idiosyncratic Volatility Proxy for Risk Exposure? https://app.cochat.ai/papers/10.1093/rfs/hhs084
The paper
Chen, Z., & Petkova, R. (2012). Does Idiosyncratic Volatility Proxy for Risk Exposure? Review of Financial Studies. https://doi.org/10.1093/rfs/hhs084

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.