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The Characteristics that Provide Independent Information about Average U.S. Monthly Stock Returns

Citations

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Cited by:

  1. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
  2. Chen, Yuanxing & Fang, Kuangnan & Lan, Wei & Tsai, Chih-Ling & Zhang, Qingzhao, 2025. "Community influence analysis in social networks," Computational Statistics & Data Analysis, Elsevier, vol. 202(C).
  3. Rungmaitree, Pattamon & Boateng, Agyenim & Ahiabor, Frederick & Lu, Qinye, 2022. "Political risk, hedge fund strategies, and returns: Evidence from G7 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
  4. Ding, Jing & Jiang, Lei & Liu, Xiaohui & Peng, Liang, 2023. "Nonparametric tests for market timing ability using daily mutual fund returns," Journal of Economic Dynamics and Control, Elsevier, vol. 150(C).
  5. Heping Xiong & Chao Tang & Jianhui Cao & Haitao Zhang, 2025. "A New Four-factor Model for the Chinese Stock Market," Annals of Economics and Finance, Society for AEF, vol. 26(2), pages 853-890, November.
  6. Ding, Yi & Li, Yingying & Liu, Guoli & Zheng, Xinghua, 2024. "Stock co-jump networks," Journal of Econometrics, Elsevier, vol. 239(2).
  7. VICTOR DeMIGUEL & ALBERTO MARTÍN‐UTRERA & RAMAN UPPAL, 2024. "A Multifactor Perspective on Volatility‐Managed Portfolios," Journal of Finance, American Finance Association, vol. 79(6), pages 3859-3891, December.
  8. Huang, Haitao & Jiang, Lei & Leng, Xuan & Peng, Liang, 2023. "Bootstrap analysis of mutual fund performance," Journal of Econometrics, Elsevier, vol. 235(1), pages 239-255.
  9. Hoang, Khoa & Huang, Ronghong & Truong, Helen, 2023. "Resurrecting the market factor: A case of data mining across international markets," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
  10. Sun, Chuanping, 2024. "Factor correlation and the cross section of asset returns: A correlation-robust machine learning approach," Journal of Empirical Finance, Elsevier, vol. 77(C).
  11. Wang, Jianqiu & Wang, Zhuo & Wu, Ke, 2025. "Forecasting stock market return with anomalies: Evidence from China," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1278-1295.
  12. Malakhov, Alexey & Riley, Timothy B. & Yan, Qing, 2024. "Do hedge funds bet against beta?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1507-1525.
  13. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
  14. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  15. Samuel YM Ze‐To, 2022. "Fundamental index aligned and excess market return predictability," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 592-614, April.
  16. Wang, Jianqiu & Wu, Ke & Tong, Guoshi & Chen, Dongxu, 2023. "Nonlinearity in the cross-section of stock returns: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 174-205.
  17. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
  18. Jules H van Binsbergen & Xiao Han & Alejandro Lopez-Lira, 2023. "Man versus Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases," The Review of Financial Studies, Society for Financial Studies, vol. 36(6), pages 2361-2396.
  19. Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
  20. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
  21. 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.
  22. Tobek, Ondrej & Hronec, Martin, 2021. "Does it pay to follow anomalies research? Machine learning approach with international evidence," Journal of Financial Markets, Elsevier, vol. 56(C).
  23. Zhu, Lin & Jiang, Fuwei & Tang, Guohao & Jin, Fujing, 2024. "From macro to micro: Sparse macroeconomic risks and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PB).
  24. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
  25. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
  26. Ma, Tian & Li, Ganghui & Zhang, Huajing, 2024. "Stock return predictability using economic narrative: Evidence from energy sectors," Journal of Commodity Markets, Elsevier, vol. 35(C).
  27. Choy, Siu Kai & Lewis, Craig & Tan, Yongxian, 2023. "Can the changes in fundamentals explain the attenuation of anomalies?," Journal of Financial Economics, Elsevier, vol. 149(2), pages 142-160.
  28. Avramov, D. & Ge, S. & Li, S. & Linton, O. B., 2025. "Dual Industry Effects and Cross-Stock Predictability," Janeway Institute Working Papers 2506, Faculty of Economics, University of Cambridge.
  29. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020. "Dissecting Characteristics Nonparametrically," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
  30. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
  31. Jing Li & Bowei Guo & Xinqi Xie & Kuo-Ping Chang, 2025. "Evaluating Investment Performance: The p-index and Empirical Efficient Frontier," Papers 2510.11074, arXiv.org.
  32. Calice, Giovanni & Lin, Ming-Tsung, 2021. "Exploring risk premium factors for country equity returns," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 294-322.
  33. Ma, Tian & Leong, Wen Jun & Jiang, Fuwei, 2023. "A latent factor model for the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 87(C).
  34. Yang, Huan & Cai, Jun & Huang, Lin & Marcus, Alan J., 2024. "Credit market conditions, expected return proxies, and bank stock returns," Global Finance Journal, Elsevier, vol. 62(C).
  35. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
  36. Cho, Thummim, 2018. "Turning alphas into betas: arbitrage and the cross-section of risk," LSE Research Online Documents on Economics 118915, London School of Economics and Political Science, LSE Library.
  37. Simon, Frederik & Weibels, Sebastian & Zimmermann, Tom, 2025. "Deep parametric portfolio policies," CFR Working Papers 23-01, University of Cologne, Centre for Financial Research (CFR), revised 2025.
  38. Geertsema, Paul & Lu, Helen, 2020. "The correlation structure of anomaly strategies," Journal of Banking & Finance, Elsevier, vol. 119(C).
  39. Lin William Cong & Guanhao Feng & Jingyu He & Xin He, 2022. "Growing the Efficient Frontier on Panel Trees," NBER Working Papers 30805, National Bureau of Economic Research, Inc.
  40. Lars Heinrich & Martin Zurek, 2019. "Alpha forecasting in factor investing: discriminating between the informational content of firm characteristics," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(3), pages 243-275, September.
  41. Bang, Jeongseok & Kang, Yeonchan & Ryu, Doojin, 2024. "Potential pricing factors in the Korean market," Finance Research Letters, Elsevier, vol. 67(PB).
  42. Kaniel, Ron & Lin, Zihan & Pelger, Markus & Van Nieuwerburgh, Stijn, 2023. "Machine-learning the skill of mutual fund managers," Journal of Financial Economics, Elsevier, vol. 150(1), pages 94-138.
  43. Penman, Stephen & Zhu, Julie, 2022. "An accounting-based asset pricing model and a fundamental factor," Journal of Accounting and Economics, Elsevier, vol. 73(2).
  44. Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
  45. Baba-Yara, Fahiz & Boons, Martijn & Tamoni, Andrea, 2024. "Persistent and transitory components of firm characteristics: Implications for asset pricing," Journal of Financial Economics, Elsevier, vol. 154(C).
  46. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
  47. He, Shuoyuan & Narayanamoorthy, Ganapathi (Gans), 2020. "Earnings acceleration and stock returns," Journal of Accounting and Economics, Elsevier, vol. 69(1).
  48. 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).
  49. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
  50. Andrew Y. Chen & Alejandro Lopez-Lira & Tom Zimmermann, 2022. "Does Peer-Reviewed Research Help Predict Stock Returns?," Papers 2212.10317, arXiv.org, revised Dec 2025.
  51. Liao, Cunfei & Ma, Tian, 2024. "From fundamental signals to stock volatility: A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 84(C).
  52. Longyu Chen & Haitao Huang & Lei Jiang & Liang Peng & Zhongling Qin, 2025. "Validating cross-sectional dependence assumptions in a factor model," Empirical Economics, Springer, vol. 68(6), pages 2873-2895, June.
  53. 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.
  54. Constant Aka & Marie‐Hélène Gagnon & Gabriel J. Power, 2025. "Commodity Option Return Predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1544-1578, October.
  55. Zhaobo Zhu & Licheng Sun & Jun Tu, 2021. "Earnings momentum meets short‐term return reversal," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(S1), pages 2379-2405, April.
  56. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
  57. 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.
  58. Vu Le Tran & Guillaume Coqueret, 2023. "ESG news spillovers across the value chain," Post-Print hal-04325746, HAL.
  59. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2429, Faculty of Economics, University of Cambridge.
  60. Claire Y. C. Liang & Rengong Zhang, 2020. "Post-earnings announcement drift and parameter uncertainty: evidence from industry and market news," Review of Quantitative Finance and Accounting, Springer, vol. 55(2), pages 695-738, August.
  61. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
  62. Allaudeen Hameed & Jing Xie & Yuxiang Zhong, 2024. "Preferences for dividends and stock returns around the world," Working Papers 202405, University of Macau, Faculty of Business Administration.
  63. Cici, Gjergji & Zhang, Pei (Alex), 2021. "On the valuation skills of corporate bond mutual funds," CFR Working Papers 21-05, University of Cologne, Centre for Financial Research (CFR).
  64. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
  65. Du, Kai & Huddart, Steven & Jiang, Xin Daniel, 2023. "Lost in standardization: Effects of financial statement database discrepancies on inference," Journal of Accounting and Economics, Elsevier, vol. 76(1).
  66. De Nard, Gianluca & Zhao, Zhao, 2022. "A large-dimensional test for cross-sectional anomalies:Efficient sorting revisited," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 654-676.
  67. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
  68. Kristoffer Pons Bertelsen, 2022. "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers 2022-05, Department of Economics and Business Economics, Aarhus University.
  69. Bank, Matthias & Insam, Franz, 2021. "Corporate aging and changes in the pricing of stock characteristics," Finance Research Letters, Elsevier, vol. 42(C).
  70. He, Jingbin & Ma, Xinru, 2023. "Is corporate social responsibility engagement influenced by nearby firms? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 86(C).
  71. Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.
  72. Han, Yufeng & Huang, Dashan & Huang, Dayong & Zhou, Guofu, 2022. "Expected return, volume, and mispricing," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1295-1315.
  73. Ka Kei Chan & Ming‐Tsung Lin & Qinye Lu, 2024. "Corporate credit default swap systematic factors," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1224-1256, July.
  74. 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).
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  76. Anja Vinzelberg & Benjamin R. Auer, 2022. "Unprofitability of food market investments," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2887-2910, October.
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  78. Chulwoo Han, 2022. "Bimodal Characteristic Returns and Predictability Enhancement via Machine Learning," Management Science, INFORMS, vol. 68(10), pages 7701-7741, October.
  79. Souza, Thiago de Oliveira, 2018. "Size-related premiums," Discussion Papers on Economics 3/2018, University of Southern Denmark, Department of Economics.
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  128. Steven Y. K. Wong & Jennifer S. K. Chan & Lamiae Azizi & Richard Y. D. Xu, 2022. "Time‐varying neural network for stock return prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(1), pages 3-18, January.
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  131. Christopher G. Lamoureux & Huacheng Zhang, 2021. "An Empirical Assessment of Characteristics and Optimal Portfolios," Papers 2104.12975, arXiv.org, revised Feb 2024.
  132. Konan Chan & Mei‐Xuan Li & Chu‐Bin Lin & Yanzhi Wang, 2022. "Organization capital effect in stock returns—The role of R&D," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(7-8), pages 1237-1263, July.
  133. Martin Zurek & Lars Heinrich, 2021. "Bottom-up versus top-down factor investing: an alpha forecasting perspective," Journal of Asset Management, Palgrave Macmillan, vol. 22(1), pages 11-29, February.
  134. Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024. "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, vol. 239(2).
  135. Shimon Kogan & Vitaly Meursault, 2021. "Corporate Disclosure: Facts or Opinions?," Working Papers 21-40, Federal Reserve Bank of Philadelphia.
  136. Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factors’ CPDAG Roots and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_18, University of São Paulo (FEA-USP).
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