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?
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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Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
Risk, Return, and Equilibrium: Empirical Tests
Fama, E. F., & MacBeth, J. D. (1973) · Journal of Political Economy · doi:10.1086/260061 · Cited by 14,258
Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
JEGADEESH, N., & TITMAN, S. (1993) · The Journal of Finance · doi:10.1111/j.1540-6261.1993.tb04702.x · Cited by 11,584
Continuous Auctions and Insider Trading
Kyle, A. S. (1985) · Econometrica · doi:10.2307/1913210 · Cited by 9,580
Does the Stock Market Overreact?
De BONDT, W. F. M., & THALER, R. (1985) · The Journal of Finance · doi:10.1111/j.1540-6261.1985.tb05004.x · Cited by 7,578
Multifactor Explanations of Asset Pricing Anomalies
FAMA, E. F., & FRENCH, K. R. (1996) · The Journal of Finance · doi:10.1111/j.1540-6261.1996.tb05202.x · Cited by 6,700
Liquidity Risk and Expected Stock Returns
Pástor, Ľ., & Stambaugh, R. F. (2003) · Journal of Political Economy · doi:10.1086/374184 · Cited by 5,339
Shleifer, A., & Vishny, R. W. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03807.x · Cited by 5,291
Inferring Trade Direction from Intraday Data
LEE, C. M. C., & READY, M. J. (1991) · The Journal of Finance · doi:10.1111/j.1540-6261.1991.tb02683.x · Cited by 3,147
Evidence of Predictable Behavior of Security Returns
JEGADEESH, N. (1990) · The Journal of Finance · doi:10.1111/j.1540-6261.1990.tb05110.x · Cited by 2,694
Cited by
Luck versus Skill in the Cross‐Section of Mutual Fund Returns
FAMA, E. F., & FRENCH, K. R. (2010) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01598.x · Cited by 1,754
Does Academic Research Destroy Stock Return Predictability?
MCLEAN, R. D., & PONTIFF, J. (2016) · The Journal of Finance · doi:10.1111/jofi.12365 · Cited by 1,566
Cooper, M. J., Gutierrez, R. C., & Hameed, A. (2004) · The Journal of Finance · doi:10.1111/j.1540-6261.2004.00665.x · Cited by 992
A Taxonomy of Anomalies and Their Trading Costs
Novy-Marx, R., & Velikov, M. (2016) · Review of Financial Studies · doi:10.1093/rfs/hhv063 · Cited by 658
Menkhoff, L., Sarno, L., Schmeling, M., & Schrimpf, A. (2012) · Journal of Financial Economics · doi:10.1016/j.jfineco.2012.06.009 · Cited by 518
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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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.