IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v31y2015i2p550-560.html

Earnings forecasting in a global stock selection model and efficient portfolio construction and management

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Guerard, John, 2023. "Harry Markowitz: An appreciation," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1496-1501.
  2. Etienne Theising, 2024. "Distributional Reference Class Forecasting of Corporate Sales Growth With Multiple Reference Variables," Papers 2405.03402, arXiv.org.
  3. Beheshti, Bijan, 2015. "A note on the integration of the alpha alignment factor and earnings forecasting models in producing more efficient Markowitz Frontiers," International Journal of Forecasting, Elsevier, vol. 31(2), pages 582-584.
  4. Alejandro Moreno Alonso & Joaquín Ordieres‐Meré, 2026. "Stock Portfolio Management Based on AI Technology," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 458-469, March.
  5. Martin J. Gruber, 2025. "Harry Markowitz and my AFA presidential address," Annals of Operations Research, Springer, vol. 346(1), pages 9-13, March.
  6. Jean-David Fermanian & Benjamin Poignard & Panos Xidonas, 2025. "Model-based vs. agnostic methods for the prediction of time-varying covariance matrices," Annals of Operations Research, Springer, vol. 346(1), pages 511-548, March.
  7. Etienne Theising & Dominik Wied & Daniel Ziggel, 2023. "Reference class selection in similarity‐based forecasting of corporate sales growth," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1069-1085, August.
  8. John Guerard, 2025. "Investments: the (almost) century of Markowitz Harry Markowitz: portfolio selection scholar, simulation creator, and applied investment researcher and consultant extraordinaire," Annals of Operations Research, Springer, vol. 346(1), pages 1-8, March.
  9. Moh’d, Shamis Said & Ozgur, Ceyhun & Mohd, Mohd Yaziz & Khalfan, Mohamed Hafidh, 2021. "The Combined Effects of Managerial and Operational Performance of Various Fundamental Components on Stock Selection," OSF Preprints mqh46, Center for Open Science.
  10. Masoud Rahiminezhad Galankashi & Farimah Mokhatab Rafiei & Maryam Ghezelbash, 2020. "Portfolio selection: a fuzzy-ANP approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-34, December.
  11. John B. Guerard & Dimitrios Thomakos & Foteini Kyriazi & Ganlin Xu & Bijan Beheshti, 2025. "Earnings forecasting and mean–variance efficient portfolios in the United States," Annals of Operations Research, Springer, vol. 346(1), pages 393-414, March.
  12. John B. Guerard & Ganlin Xu & Harry Markowitz, 2021. "A further analysis of robust regression modeling and data mining corrections testing in global stocks," Annals of Operations Research, Springer, vol. 303(1), pages 175-195, August.
  13. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
  14. Xialu Liu & John Guerard & Rong Chen & Ruey Tsay, 2025. "Improving estimation of portfolio risk using new statistical factors," Annals of Operations Research, Springer, vol. 346(1), pages 245-261, March.
  15. Chen, Wei & Zhang, Haoyu & Jia, Lifen, 2022. "A novel two-stage method for well-diversified portfolio construction based on stock return prediction using machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  16. Sébastien Lleo & Leonard C. MacLean, 2025. "Dual dominance: how Harry Markowitz and William Ziemba impacted portfolio management," Annals of Operations Research, Springer, vol. 346(1), pages 181-216, March.
  17. Gillam, Robert A. & Guerard, John B. & Cahan, Rochester, 2015. "News volume information: Beyond earnings forecasting in a global stock selection model," International Journal of Forecasting, Elsevier, vol. 31(2), pages 575-581.
  18. Barret Pengyuan Shao & John B. Guerard & Ganlin Xu, 2025. "Mean-variance and mean-ETL optimizations in portfolio selection: an update," Annals of Operations Research, Springer, vol. 346(1), pages 657-671, March.
  19. Ganggang Guo & Yulei Rao & Feida Zhu & Fang Xu, 2020. "Innovative deep matching algorithm for stock portfolio selection using deep stock profiles," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-31, November.
  20. John B. Guerard, Jr. & Robert A. Gillam & Harry Markowitz & Ganlin Xu & Shijie Deng & Ziwei (Elaine) Wang, 2018. "Data Mining Corrections Testing in Chinese Stocks," Interfaces, INFORMS, vol. 48(2), pages 108-120, April.
  21. Xiaoyu Ji & Hua Ke, 2017. "No-arbitrage theorem for multi-factor uncertain stock model with floating interest rate," Fuzzy Optimization and Decision Making, Springer, vol. 16(2), pages 221-234, June.
  22. Qu, Li, 2021. "A new approach to estimating earnings forecasting models: Robust regression MM-estimation," International Journal of Forecasting, Elsevier, vol. 37(2), pages 1011-1030.
  23. Shao, Barret Pengyuan & Rachev, Svetlozar T. & Mu, Yu, 2015. "Applied mean-ETL optimization in using earnings forecasts," International Journal of Forecasting, Elsevier, vol. 31(2), pages 561-567.
  24. John B. Guerard & Harry Markowitz & Ganlin Xu & Ziwei Wang, 2018. "Global portfolio construction with emphasis on conflicting corporate strategies to maximize stockholder wealth," Annals of Operations Research, Springer, vol. 267(1), pages 203-219, August.
  25. Felix Divo & Eric Endress & Kevin Endler & Kristian Kersting & Devendra Singh Dhami, 2024. "Forecasting Company Fundamentals," Papers 2411.05791, arXiv.org, revised Jun 2025.
  26. Jang Ho Kim & Seyoung Kim & Yongjae Lee & Woo Chang Kim & Frank J. Fabozzi, 2025. "Enhancing mean–variance portfolio optimization through GANs-based anomaly detection," Annals of Operations Research, Springer, vol. 346(1), pages 217-244, March.
  27. Xu, Peng, 2024. "Testing out-of-sample portfolio performance using second-order stochastic dominance constrained optimization approach," International Review of Financial Analysis, Elsevier, vol. 95(PA).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.