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Cited by 268

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

The Impact of Trades on Daily Volatility

Open access
Avramov, Doron, Chordia, Tarun, Goyal, Amit·2006·Review of Financial Studies

Abstract

This article proposes a trading-based explanation for the asymmetric effect in daily volatility of individual stock returns. Previous studies propose two major hypotheses for this phenomenon: leverage effect and time-varying expected returns. However, leverage has no impact on asymmetric volatility at the daily frequency and, moreover, we observe asymmetric volatility for stocks with no leverage. Also, expected returns may vary with the business cycle, that is, at a lower than daily frequency. Trading activity of contrarian and herding investors has a robust effect on the relationship between daily volatility and lagged return. Consistent with the predictions of the rational expectation models, the non-informational liquidity-driven (herding) trades increase volatility following stock price declines, and the informed (contrarian) trades reduce volatility following stock price increases. The results are robust to different measures of volatility and trading activity. (JEL C30, G11, G12)

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Metadata

Authors
Avramov, D., Chordia, T., & Goyal, A.
Venue
Review of Financial Studies
Published
2006
Volume
19
Issue
4
Pages
1241-1277
ISSN
  • 0893-9454 (ISSN-L)
  • 1465-7368
OpenAlex
W3122446295
Cited by
268
References
49
FWCI
15.33
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Impact of Trades on Daily Volatility. https://app.cochat.ai/papers/10.1093/rfs/hhj027
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Avramov, D., Chordia, T., & Goyal, A. (2006). The Impact of Trades on Daily Volatility. Review of Financial Studies. https://doi.org/10.1093/rfs/hhj027

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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.