The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Momentum Strategies
Abstract
We examine whether the predictability of future returns from past returns is due to the market's underreaction to information, in particular to past earnings news. Past return and past earnings surprise each predict large drifts in future returns after controlling for the other. Market risk, size, and book–to–market effects do not explain the drifts. There is little evidence of subsequent reversals in the returns of stocks with high price and earnings momentum. Security analysts' earnings forecasts also respond sluggishly to past news, especially in the case of stocks with the worst past performance. The results suggest a market that responds only gradually to new information.
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“Third, in line with the observations of Chan, Jegadeesh, and Lakonishok (1996), investors might need more time to process newly released information fully.”
From ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy? (2025) · cites this paper as Chan, Jegadeesh, and Lakonishok (1996)
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Citations
Cites
Common risk factors in the returns on stocks and bonds
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Cited by
Sorted by citations
Can ChatGPT forecast stock price movements? Return predictability and large language models
Lopez-Lira, A., & Tang, Y. (2026) · Journal of Financial Economics · doi:10.1016/j.jfineco.2026.104335 · Cited by 425
The Cross-section of Expected Stock Returns
Lewellen, J. (2015) · Critical Finance Review · doi:10.1561/104.00000024 · Cited by 407
ChatGPT and Deepseek: Can They Predict the Stock Market and Macroeconomy?
Chen, J., Tang, G., Zhou, G., & Zhu, W. (2025) · arXiv · doi:10.48550/arxiv.2502.10008 · Cited by 6
Metadata
- Authors
- CHAN, L. K. C., JEGADEESH, N., & LAKONISHOK, J.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 1996-12
- Volume
- 51
- Issue
- 5
- Pages
- 1681-1713
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W4246390368
- Cited by
- 1,279
- References
- 2
- Citations by year
- 2026: 31 · 2025: 55 · 2024: 48 · 2023: 63 · 2022: 63 · 2021: 65 · 2020: 63 · 2019: 51 · 2018: 79 · 2017: 57 · 2016: 60 · 2015: 70 · 2014: 56 · 2013: 57 · 2012: 61
- FWCI
- 15.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Finance (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Keywords
- momentum strategies, price momentum, earnings surprises, return predictability, market underreaction, earnings news, analyst earnings forecasts, market efficiency
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- The paper
- CHAN, L. K. C., JEGADEESH, N., & LAKONISHOK, J. (1996). Momentum Strategies. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.1996.tb05222.x
