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The Cross-section of Expected Stock Returns

Citations

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Cited by:

  1. Ian W. R. Martin & Christian Wagner, 2019. "What Is the Expected Return on a Stock?," Journal of Finance, American Finance Association, vol. 74(4), pages 1887-1929, August.
  2. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
  3. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
  4. Dittmar, Robert F. & Lundblad, Christian T., 2017. "Firm characteristics, consumption risk, and firm-level risk exposures," Journal of Financial Economics, Elsevier, vol. 125(2), pages 326-343.
  5. Christian Fieberg & Lars Hornuf & Gerrit Liedtke & Thorsten Poddig, 2020. "Are Characteristics Covariances? A Comment on Instrumented Principal Component Analysis," CESifo Working Paper Series 8377, CESifo.
  6. Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
  7. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
  8. Lin, Yu En & Chu, Chien Chi & Omura, Akihiro & Li, Bin & Roca, Eduardo, 2020. "Arbitrage risk and the cross-section of stock returns: Evidence from China," Emerging Markets Review, Elsevier, vol. 43(C).
  9. Ahmad Fraz & Arshad Hassan, 2017. "Stock Price Synchronicity and Information Environment," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(4), pages 213-232, December.
  10. Sakkas, Athanasios & Tessaromatis, Nikolaos, 2020. "Factor based commodity investing," Journal of Banking & Finance, Elsevier, vol. 115(C).
  11. Huang, Dashan & Li, Jiangyuan & Wang, Liyao & Zhou, Guofu, 2020. "Time series momentum: Is it there?," Journal of Financial Economics, Elsevier, vol. 135(3), pages 774-794.
  12. Kewei Hou & Haitao Mo & Chen Xue & Lu Zhang, 2019. "Security Analysis: An Investment Perspective," NBER Working Papers 26060, National Bureau of Economic Research, Inc.
  13. 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.
  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. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
  16. Ding, Yi & Li, Yingying & Liu, Guoli & Zheng, Xinghua, 2024. "Stock co-jump networks," Journal of Econometrics, Elsevier, vol. 239(2).
  17. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2022. "Dissecting green returns," Journal of Financial Economics, Elsevier, vol. 146(2), pages 403-424.
  18. Gonçalves, Andrei S., 2021. "The short duration premium," Journal of Financial Economics, Elsevier, vol. 141(3), pages 919-945.
  19. Akbas, Ferhat & Boehmer, Ekkehart & Jiang, Chao & Koch, Paul D., 2022. "Overnight returns, daytime reversals, and future stock returns," Journal of Financial Economics, Elsevier, vol. 145(3), pages 850-875.
  20. Edelen, Roger M. & Ince, Ozgur S. & Kadlec, Gregory B., 2016. "Institutional investors and stock return anomalies," Journal of Financial Economics, Elsevier, vol. 119(3), pages 472-488.
  21. Atif Ellahie, 2021. "Earnings beta," Review of Accounting Studies, Springer, vol. 26(1), pages 81-122, March.
  22. 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).
  23. 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.
  24. Luyang Chen & Markus Pelger & Jason Zhu, 2024. "Deep Learning in Asset Pricing," Management Science, INFORMS, vol. 70(2), pages 714-750, February.
  25. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
  26. 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.
  27. Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022. "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, vol. 79(C).
  28. Bajzik, Josef, 2021. "Trading volume and stock returns: A meta-analysis," International Review of Financial Analysis, Elsevier, vol. 78(C).
  29. Philip A. Stork & Milan Vidojevic & Remco C. J. Zwinkels, 2021. "Behavioral heterogeneity in return expectations across equity style portfolios," International Review of Finance, International Review of Finance Ltd., vol. 21(4), pages 1225-1250, December.
  30. Wolfgang Drobetz & Rebekka Haller & Christian Jasperneite & Tizian Otto, 2019. "Predictability and the cross section of expected returns: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 508-533, December.
  31. Hanauer, Matthias X. & Kalsbach, Tobias, 2023. "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 55(C).
  32. Heaney, Richard & Koh, SzeKee & Lan, Yihui, 2016. "Australian firm characteristics and the cross-section variation in equity returns," Pacific-Basin Finance Journal, Elsevier, vol. 37(C), pages 104-115.
  33. Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019. "Characteristics are covariances: A unified model of risk and return," Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
  34. 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).
  35. Victor Duarte & Diogo Duarte & Dejanir H. Silva, 2024. "Machine Learning for Continuous-Time Finance," CESifo Working Paper Series 10909, CESifo.
  36. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
  37. Atif Ellahie & Xiaoxia Peng, 2021. "Management forecasts of volatility," Review of Accounting Studies, Springer, vol. 26(2), pages 620-655, June.
  38. Hanauer, Matthias X. & Lauterbach, Jochim G., 2019. "The cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 38(C), pages 265-286.
  39. 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.
  40. Christopher G. Lamoureux & Huacheng Zhang, 2021. "An Empirical Assessment of Characteristics and Optimal Portfolios," Papers 2104.12975, arXiv.org, revised Feb 2024.
  41. Fletcher, Jonathan, 2018. "Betas V characteristics: Do stock characteristics enhance the investment opportunity set in U.K. stock returns?," The North American Journal of Economics and Finance, Elsevier, vol. 46(C), pages 114-129.
  42. 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.
  43. Alois Weigand, 2019. "Machine learning in empirical asset pricing," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 93-104, March.
  44. David, Joel M. & Schmid, Lukas & Zeke, David, 2022. "Risk-adjusted capital allocation and misallocation," Journal of Financial Economics, Elsevier, vol. 145(3), pages 684-705.
  45. 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).
  46. 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.
  47. Fletcher, Jonathan, 2018. "An empirical examination of the diversification benefits of U.K. international equity closed-end funds," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 23-34.
  48. Jeffrey L. Callen & Matthew R. Lyle, 2020. "The term structure of implied costs of equity capital," Review of Accounting Studies, Springer, vol. 25(1), pages 342-404, March.
  49. Sadok El Ghoul & Omrane Guedhami & Sattar A. Mansi & Oumar Sy, 2023. "Event studies in international finance research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(2), pages 344-364, March.
  50. 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).
  51. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
  52. Yu-Chin Hsu & Hsiou-Wei Lin & Kendro Vincent, 2017. "Do Cross-Sectional Stock Return Predictors Pass the Test without Data-Snooping Bias?," IEAS Working Paper : academic research 17-A003, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  53. Geertsema, Paul & Lu, Helen, 2020. "The correlation structure of anomaly strategies," Journal of Banking & Finance, Elsevier, vol. 119(C).
  54. 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.
  55. Kolari, James W. & Pynnonen, Seppo & Tuncez, Ahmet M., 2021. "Further evidence on long-run abnormal returns after corporate events," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 421-439.
  56. Andrew C. Chang, 2018. "Nothing is Certain Except Death and Taxes : The Lack of Policy Uncertainty from Expiring \"Temporary\" Taxes," Finance and Economics Discussion Series 2018-041, Board of Governors of the Federal Reserve System (U.S.).
  57. Tu, Xueyong & Li, Bin, 2024. "Robust portfolio selection with smart return prediction," Economic Modelling, Elsevier, vol. 135(C).
  58. Tian, Mary, 2018. "Tradability of output, business cycles and asset prices," Journal of Financial Economics, Elsevier, vol. 128(1), pages 86-102.
  59. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J. & Uppal, Raman, 2017. "A Portfolio Perspective on the Multitude of Firm Characteristics," CEPR Discussion Papers 12417, C.E.P.R. Discussion Papers.
  60. Dichtl, Hubert & Drobetz, Wolfgang & Otto, Tizian, 2023. "Forecasting Stock Market Crashes via Machine Learning," Journal of Financial Stability, Elsevier, vol. 65(C).
  61. Penman, Stephen & Zhu, Julie, 2022. "An accounting-based asset pricing model and a fundamental factor," Journal of Accounting and Economics, Elsevier, vol. 73(2).
  62. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
  63. Xiao, Xiang & Hua, Xia & Qin, Kexin, 2024. "A self-attention based cross-sectional return forecasting model with evidence from the Chinese market," Finance Research Letters, Elsevier, vol. 62(PA).
  64. Huber, Daniel & Jacobs, Heiko & Müller, Sebastian & Preissler, Fabian, 2023. "International factor models," Journal of Banking & Finance, Elsevier, vol. 150(C).
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