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Open source cross-sectional asset pricing

Citations

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Cited by:

  1. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
  2. Pallavi Basu & Luella Fu & Alessio Saretto & Wenguang Sun, 2021. "Empirical Bayes Control of the False Discovery Exceedance," Working Papers 2115, Federal Reserve Bank of Dallas.
  3. M. Hashem Pesaran & Ron P. Smith, 2023. "The Role of Pricing Errors in Linear Asset Pricing Models with Strong, Semi-Strong, and Latent Factors," CESifo Working Paper Series 10282, CESifo.
  4. Hollstein, Fabian & Prokopczuk, Marcel, 2022. "Testing Factor Models in the Cross-Section," Journal of Banking & Finance, Elsevier, vol. 145(C).
  5. Andrew Y. Chen, 2022. "Most claimed statistical findings in cross-sectional return predictability are likely true," Papers 2206.15365, arXiv.org, revised Sep 2024.
  6. Vitor Azevedo & Christopher Hoegner, 2023. "Enhancing stock market anomalies with machine learning," Review of Quantitative Finance and Accounting, Springer, vol. 60(1), pages 195-230, January.
  7. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
  8. Beckmeyer, Heiner & Wiedemann, Timo, 2022. "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics 264135, Verein für Socialpolitik / German Economic Association.
  9. Antoine Falck & Adam Rej & David Thesmar, 2021. "Why and how systematic strategies decay," Papers 2105.01380, arXiv.org.
  10. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
  11. 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.
  12. Vidal-Llana, Xenxo & Guillén, Montserrat, 2022. "Cross-sectional quantile regression for estimating conditional VaR of returns during periods of high volatility," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  13. Andrew Y. Chen, 2022. "Do t-Statistic Hurdles Need to be Raised?," Papers 2204.10275, arXiv.org, revised Apr 2024.
  14. Evaluator 1, 2024. "Evaluation 1 of "Biodiversity Risk"," The Unjournal Evaluations 2024-151, The Unjournal.
  15. Vitor Azevedo & Georg Sebastian Kaiser & Sebastian Mueller, 2023. "Stock market anomalies and machine learning across the globe," Journal of Asset Management, Palgrave Macmillan, vol. 24(5), pages 419-441, September.
  16. Bui, Dien Giau & Kong, De-Rong & Lin, Chih-Yung & Lin, Tse-Chun, 2023. "Momentum in machine learning: Evidence from the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
  17. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
  18. Kumar, Rajnish & Lawrence, Edward R. & Prakash, Arun & Rodríguez, Iván M., 2023. "Additions to and deletions from the S&P 500 index: A resolution to the asymmetric price response puzzle," Journal of Banking & Finance, Elsevier, vol. 154(C).
  19. Liu, Yangyi & Luo, Ronghua & Zhao, Senyang, 2023. "Improving factor momentum: Statistical significance matters," Economics Letters, Elsevier, vol. 233(C).
  20. Andrew Y. Chen & Tom Zimmermann, 2022. "Publication Bias in Asset Pricing Research," Papers 2209.13623, arXiv.org, revised Sep 2023.
  21. Nusret Cakici & Christian Fieberg & Daniel Metko & Adam Zaremba, 2024. "Do Anomalies Really Predict Market Returns? New Data and New Evidence," Review of Finance, European Finance Association, vol. 28(1), pages 1-44.
  22. Yin Chen & Roni Israelov, 2024. "Income illusions: challenging the high yield stock narrative," Journal of Asset Management, Palgrave Macmillan, vol. 25(2), pages 190-202, March.
  23. Simon, Frederik & Weibels, Sebastian & Zimmermann, Tom, 2023. "Deep parametric portfolio policies," CFR Working Papers 23-01, University of Cologne, Centre for Financial Research (CFR).
  24. Zoran Stoiljkovic, 2023. "Applying Reinforcement Learning to Option Pricing and Hedging," Papers 2310.04336, arXiv.org.
  25. Kim, Junyong, 2024. "Zoom in on momentum," International Review of Financial Analysis, Elsevier, vol. 94(C).
  26. Shi, Huai-Long & Chen, Huayi, 2023. "Revisiting asset co-movement: Does network topology really matter?," Research in International Business and Finance, Elsevier, vol. 66(C).
  27. Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
  28. Azevedo, Vitor, 2023. "Analysts’ underreaction and momentum strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
  29. Jianqing Fan & Weining Wang & Yue Zhao, 2024. "Conditional nonparametric variable screening by neural factor regression," Papers 2408.10825, arXiv.org.
  30. Chen, Zilin & Da, Zhi & Huang, Dashan & Wang, Liyao, 2023. "Presidential economic approval rating and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 147(1), pages 106-131.
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