Publication Bias and the Cross-Section of Stock Returns

Citations

Cited by:

1. Chinco, Alex & Neuhierl, Andreas & Weber, Michael, 2021. "Estimating the anomaly base rate," Journal of Financial Economics, Elsevier, vol. 140(1), pages 101-126.
   • Alexander M. Chinco & Andreas Neuhierl & Michael Weber, 2019. "Estimating The Anomaly Base Rate," NBER Working Papers 26493, National Bureau of Economic Research, Inc.
2. Cujean, Julien & Andrei, Daniel & Fournier, Mathieu, 2019. "The Low-Minus-High Portfolio and the Factor Zoo," CEPR Discussion Papers 14153, C.E.P.R. Discussion Papers.
3. Andrew Y. Chen & Chukwuma Dim, 2023. "High-Throughput Asset Pricing," Papers 2311.10685, arXiv.org, revised Jun 2025.
4. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2024. "Evaluating asset pricing anomalies: Evidence from Latin America," Research in International Business and Finance, Elsevier, vol. 70(PB).
5. Andrew Y. Chen & Alejandro Lopez-Lira & Tom Zimmermann, 2022. "Does Peer-Reviewed Research Help Predict Stock Returns?," Papers 2212.10317, arXiv.org, revised Mar 2025.
   • Chen, Andrew Y. & Lopez-Lira, Alejandro & Zimmermann, Tom, 2024. "Does peer-reviewed research help predict stock returns?," CFR Working Papers 24-02, University of Cologne, Centre for Financial Research (CFR).
6. Andrew Y. Chen, 2022. "Most claimed statistical findings in cross-sectional return predictability are likely true," Papers 2206.15365, arXiv.org, revised Jun 2025.
7. Azevedo, Vitor & Müller, Sebastian, 2024. "Analyst recommendations and mispricing across the globe," Journal of Banking & Finance, Elsevier, vol. 169(C).
8. Chen, Hailiang & Hwang, Byoung-Hyoun, 2022. "Listening in on investors’ thoughts and conversations," Journal of Financial Economics, Elsevier, vol. 145(2), pages 426-444.
9. Andrew C. Chang & Trace J. Levinson, 2020. "Raiders of the Lost High-Frequency Forecasts: New Data and Evidence on the Efficiency of the Fed's Forecasting," Finance and Economics Discussion Series 2020-090, Board of Governors of the Federal Reserve System (U.S.).
10. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    • Yukun Liu & Aleh Tsyvinski, 2019. "Risks and Returns of Cryptocurrency," 2019 Meeting Papers 160, Society for Economic Dynamics.
11. Shynkevich, Andrei, 2025. "Wine market efficiency: Is glass half full or half empty?," International Review of Economics & Finance, Elsevier, vol. 98(C).
12. Han, Yufeng & Lu, Yueliang (Jacques) & Xu, Weike & Zhou, Guofu, 2024. "Mispricing and Anomalies: An Exogenous Shock to Short Selling from JGTRRA," Journal of Empirical Finance, Elsevier, vol. 78(C).
13. Andrew Y. Chen, 2021. "The Limits of p‐Hacking: Some Thought Experiments," Journal of Finance, American Finance Association, vol. 76(5), pages 2447-2480, October.
14. Andrew Y. Chen & Tom Zimmermann, 2022. "Open Source Cross-Sectional Asset Pricing," Critical Finance Review, now publishers, vol. 11(2), pages 207-264, May.
    • Chen, Andrew Y. & Zimmermann, Tom, 2020. "Open source cross-sectional asset pricing," CFR Working Papers 20-04, University of Cologne, Centre for Financial Research (CFR).
    • Andrew Y. Chen & Tom Zimmermann, 2021. "Open Source Cross-Sectional Asset Pricing," Finance and Economics Discussion Series 2021-037, Board of Governors of the Federal Reserve System (U.S.).
15. Andrew Y. Chen, 2019. "The Limits of p-Hacking : A Thought Experiment," Finance and Economics Discussion Series 2019-016, Board of Governors of the Federal Reserve System (U.S.).
16. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
17. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
18. Jiří Witzany, 2021. "A Bayesian Approach to Measurement of Backtest Overfitting," Risks, MDPI, vol. 9(1), pages 1-22, January.
19. Jacobs, Heiko & Müller, Sebastian, 2020. "Anomalies across the globe: Once public, no longer existent?," Journal of Financial Economics, Elsevier, vol. 135(1), pages 213-230.
20. Andrew Y. Chen & Tom Zimmermann, 2022. "Publication Bias in Asset Pricing Research," Papers 2209.13623, arXiv.org, revised Sep 2023.
21. Vincent, Kendro & Hsu, Yu-Chin & Lin, Hsiou-Wei, 2021. "Investment styles and the multiple testing of cross-sectional stock return predictability," Journal of Financial Markets, Elsevier, vol. 56(C).
22. Alexandre Ripamonti & Raphael Videira & Denis Ichimura, 2020. "Asymmetric information and daily stock prices in Brazil," Estudios Gerenciales, Universidad Icesi, vol. 36(157), pages 465-472.
23. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2019. "Common Risk Factors in Cryptocurrency," NBER Working Papers 25882, National Bureau of Economic Research, Inc.
24. Xiong, Ruoxuan & Pelger, Markus, 2023. "Large dimensional latent factor modeling with missing observations and applications to causal inference," Journal of Econometrics, Elsevier, vol. 233(1), pages 271-301.
    • Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
25. Andrew Y. Chen & Mihail Velikov, 2020. "Zeroing in on the Expected Returns of Anomalies," Finance and Economics Discussion Series 2020-039, Board of Governors of the Federal Reserve System (U.S.).
26. Cakici, Nusret & Zaremba, Adam & Bianchi, Robert J. & Pham, Nga, 2021. "False discoveries in the anomaly research: New insights from the Stock Exchange of Melbourne (1927–1987)," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).