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Cited by 320

The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.

A tug of war: Overnight versus intraday expected returns

Open access
Lou, Dong, Polk, Christopher, Skouras, Spyros·2019·Journal of Financial Economics

Abstract

We link investor heterogeneity to the persistence of the overnight and intraday components of returns. We document strong overnight and intraday firm-level return continuation along with an offsetting cross-period reversal effect, all of which lasts for years. We look for a similar tug of war in the returns of 14 trading strategies, finding in all cases that profits are either earned entirely overnight (for reversal and a variety of momentum strategies) or entirely intraday, typically with profits of opposite signs across these components. We argue that this tug of war should reduce the effectiveness of clienteles pursuing the strategy. Indeed, the smoothed spread between the overnight and intraday return components of a strategy generally forecasts time variation in that strategy’s close-to-close performance in a manner consistent with that interpretation. Finally, we link cross-sectional and time-series variation in the decomposition of momentum profits to a specific institutional tug of war.

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Crossref · 10.1016/j.jfineco.2019.03.011

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Metadata

Authors
Lou, D., Polk, C., & Skouras, S.
Venue
Journal of Financial Economics
Publisher
Elsevier BV
Published
2019-10
Volume
134
Issue
1
Pages
192-213
ISSN
0304-405X (ISSN-L)
OpenAlex
W2797315895
Cited by
320
References
75
FWCI
30.08
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A tug of war: Overnight versus intraday expected returns. https://app.cochat.ai/papers/10.1016/j.jfineco.2019.03.011
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Lou, D., Polk, C., & Skouras, S. (2019). A tug of war: Overnight versus intraday expected returns. Journal of Financial Economics. https://doi.org/10.1016/j.jfineco.2019.03.011

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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.