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Forecasting stock returns: A predictor-constrained approach

Citations

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Cited by:

  1. Giovannelli, Alessandro & Massacci, Daniele & Soccorsi, Stefano, 2021. "Forecasting stock returns with large dimensional factor models," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 252-269.
  2. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
  3. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
  4. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
  5. Yong Qu & Ying Yuan, 2025. "Predicting Equity Premium: A New Momentum Indicator Selection Strategy With Machine Learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 424-435, March.
  6. Zhang, Yue-Jun & Li, Zhao-Chen, 2021. "Forecasting the stock returns of Chinese oil companies: Can investor attention help?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 531-555.
  7. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
  8. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Long, Jian-You & Zhou, Yang, 2023. "Forecasting stock market volatility under parameter and model uncertainty," Research in International Business and Finance, Elsevier, vol. 66(C).
  9. Nonejad, Nima, 2021. "Predicting equity premium using dynamic model averaging. Does the state–space representation matter?," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  10. Yuan, Ying & Qu, Yong & Qiao, Sijia, 2025. "Equity premium prediction: A constraint-based predictor decomposition approach," Global Finance Journal, Elsevier, vol. 68(C).
  11. Wang, Yudong & Pan, Zhiyuan & Wu, Chongfeng & Wu, Wenfeng, 2020. "Industry equi-correlation: A powerful predictor of stock returns," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 1-24.
  12. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
  13. Zhang, Yaojie & He, Mengxi & Wang, Yudong & Liang, Chao, 2023. "Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1318-1332.
  14. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2018. "Forecasting the prices of crude oil using the predictor, economic and combined constraints," Economic Modelling, Elsevier, vol. 75(C), pages 237-245.
  15. Zhang, Yaojie & Zhao, Xinyi & Zhang, Zhikai, 2025. "Financial regulatory policy uncertainty: An informative predictor for financial industry stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 75(PB).
  16. Yuan, Ying & Qu, Yong & Wang, Tianyang, 2025. "Predicting risk premiums: A constraint-based model," Journal of Empirical Finance, Elsevier, vol. 83(C).
  17. Nonejad, Nima, 2022. "Forecasting crude oil price volatility out-of-sample using news-based geopolitical risk index: What forms of nonlinearity help improve forecast accuracy the most?," Finance Research Letters, Elsevier, vol. 46(PA).
  18. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
  19. Ilias Aarab, 2025. "Switching between states and the COVID-19 turbulence," Papers 2512.20477, arXiv.org.
  20. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2022. "Geopolitical risk trends and crude oil price predictability," Energy, Elsevier, vol. 258(C).
  21. Jonathan A. Batten & Harald Kinateder & Niklas Wagner, 2022. "Beating the Average: Equity Premium Variations, Uncertainty, and Liquidity," Abacus, Accounting Foundation, University of Sydney, vol. 58(3), pages 567-588, September.
  22. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
  23. Yuan Zhao & Xue Gong & Weiguo Zhang & Weijun Xu, 2025. "Stock return forecasting based on the proxy variables of category factors," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-48, December.
  24. Zhikai Zhang & Yaojie Zhang & Yudong Wang, 2024. "Forecasting the equity premium using weighted regressions: Does the jump variation help?," Empirical Economics, Springer, vol. 66(5), pages 2049-2082, May.
  25. Navratil, Robert & Taylor, Stephen & Vecer, Jan, 2021. "On equity market inefficiency during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 77(C).
  26. Nonejad, Nima, 2022. "Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
  27. Dai, Zhifeng & Kang, Jie & Wen, Fenghua, 2021. "Predicting stock returns: A risk measurement perspective," International Review of Financial Analysis, Elsevier, vol. 74(C).
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