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Investment Intelligence from Insider Trading
Abstract
Part 1 Insider-trading patterns. Part 2 Does insider trading predict future stock returns?. Part 3 A stock-picking strategy. Part 4 Predicting future market returns. Part 5 Crash of October 1987 and insider trading. Part 6 Dividend yields and insider trading. Part 7 Dividend initiations. Part 8 Earnings announcements. Part 9 Price-earnings ratio. Part 10 Book-to-market ratio. Part 11 Insiders trading in target firms. Part 12 Insider trading in bidder firms. Part 13 Momentum and mean reversion. Part 14 Implementation and conclusions.
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Citations
Cited by
Investor Sentiment and the Cross‐Section of Stock Returns
BAKER, M., & WURGLER, J. (2006) · The Journal of Finance · doi:10.1111/j.1540-6261.2006.00885.x · Cited by 6,049
Corporate Governance and Equity Prices
Gompers, P., Ishii, J., & Metrick, A. (2003) · The Quarterly Journal of Economics · doi:10.1162/00335530360535162 · Cited by 6,120
Investor Sentiment and the Cross-section of Stock Returns
Baker, M. P., & Wurgler, J. A. (2003) · SSRN Electronic Journal · doi:10.2139/ssrn.464843 · Cited by 1,456
Commitment to social good and insider trading
Gao, F., Lisic, L. L., & Zhang, I. X. (2014) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2014.03.001 · Cited by 375
Metadata
- Authors
- Seyhun, H. N.
- Venue
- The MIT Press eBooks
- Publisher
- The MIT Press
- Published
- 1998
- OpenAlex
- W2096552260
- Cited by
- 342
- References
- 0
- FWCI
- 11.20
- Type
- book
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Investment Intelligence from Insider Trading. https://app.cochat.ai/papers/10.7551/mitpress/3951.001.0001
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- Seyhun, H. N. (1998). Investment Intelligence from Insider Trading. The MIT Press eBooks. https://doi.org/10.7551/mitpress/3951.001.0001
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.
