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Cited by 567

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Are Momentum Profits Robust to Trading Costs?

Korajczyk, Robert A., Sadka, Ronnie·2004·The Journal of Finance

Abstract

We test whether momentum strategies remain profitable after considering market frictions induced by trading. Intraday data are used to estimate alternative measures of proportional and non‐proportional (price impact) trading costs. The price impact models imply that abnormal returns to portfolio strategies decline with portfolio size. We calculate break‐even fund sizes that lead to zero abnormal returns. In addition to equal‐ and value‐weighted momentum strategies, we derive a liquidity‐weighted strategy designed to reduce the cost of trades. Equal‐weighted strategies perform the best before trading costs and the worst after trading costs. Liquidity‐weighted and hybrid liquidity/value‐weighted strategies have the largest break‐even fund sizes: $5 billion or more (relative to December 1999 market capitalization) may be invested in these momentum strategies before the apparent profit opportunities vanish.

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Crossref · 10.1111/j.1540-6261.2004.00656.x

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Metadata

Authors
Korajczyk, R. A., & Sadka, R.
Venue
The Journal of Finance
Publisher
Wiley
Published
2004-06
Volume
59
Issue
3
Pages
1039-1082
ISSN
  • 0022-1082 (ISSN-L)
  • 1540-6261
OpenAlex
W3123921709
Cited by
567
References
43
FWCI
41.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Are Momentum Profits Robust to Trading Costs? https://app.cochat.ai/papers/10.1111/j.1540-6261.2004.00656.x
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Korajczyk, R. A., & Sadka, R. (2004). Are Momentum Profits Robust to Trading Costs? The Journal of Finance. https://doi.org/10.1111/j.1540-6261.2004.00656.x

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.