IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v39y2023i4p1518-1547.html

Forecast combinations: An over 50-year review

Citations

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


Cited by:

  1. Stratigakos, Akylas & Pineda, Salvador & Morales, Juan Miguel, 2025. "Decision-focused linear pooling for probabilistic forecast combination," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1112-1125.
  2. Jinjun Liu & Ming-Yen Cheng, 2026. "Forecasting the U.S. Treasury Yield Curve: A Distributionally Robust Machine Learning Approach," Papers 2601.04608, arXiv.org.
  3. Marco Zanotti, 2025. "On the stability of global forecasting models," Working Papers 553, University of Milano-Bicocca, Department of Economics.
  4. Taylor, James W., 2026. "Probabilistic forecast aggregation with statistical depth," European Journal of Operational Research, Elsevier, vol. 328(2), pages 460-476.
  5. Kozyrev, Boris, 2024. "Forecast combination and interpretability using random subspace," IWH Discussion Papers 21/2024, Halle Institute for Economic Research (IWH).
  6. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
  7. Lin, Tzu-Chi & Liu, Chu-An, 2025. "Model averaging prediction for possibly nonstationary autoregressions," Journal of Econometrics, Elsevier, vol. 249(PB).
  8. Giovanni Ballarin & Lyudmila Grigoryeva & Yui Ching Li, 2025. "From Many Models, One: Macroeconomic Forecasting with Reservoir Ensembles," Papers 2512.13642, arXiv.org, revised Jan 2026.
  9. Wu, Haoran & Gao, Zhiwei & Nie, Boyang & Zhao, Binru, 2025. "Can machines learn Chinese mutual funds?," Pacific-Basin Finance Journal, Elsevier, vol. 94(C).
  10. Lachana, Ioanna & Schröder, David, 2025. "Investor sentiment and stock returns: Wisdom of crowds or power of words? Evidence from Seeking Alpha and Wall Street Journal," Journal of Financial Markets, Elsevier, vol. 74(C).
  11. Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025. "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, vol. 251(C).
  12. V. Candila & O. Cepni & G. M. Gallo & R. Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the volatility of US state-level equity returns: Evidence from a GARCH-MIDAS approach with Shrinkage and Cluster Analysis," Working Paper CRENoS 202414, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
  13. Foucault, Thierry & Gambacorta, Leonardo & Jiang, Wei & Vives, Xavier, 2025. "Barcelona 7: Artificial Intelligence in Finance," HEC Research Papers Series 1599, HEC Paris.
  14. Thompson, Ryan & Qian, Yilin & Vasnev, Andrey L., 2024. "Flexible global forecast combinations," Omega, Elsevier, vol. 126(C).
  15. Li, Bowen & Ampah, Jeffrey Dankwa & Li, Tiantian & Zhang, Xing & Liu, Haifeng & Feng, Hongqing & Yue, Zongyu & Hussain Ratlamwala, Tahir Abdul & Yao, Mingfa, 2025. "Enhancing renewable energy load forecasting through deep data analysis and feature extraction techniques," Energy, Elsevier, vol. 340(C).
  16. Vasiliki Skintzi & Stavroula P. Fameliti, 2025. "Combining realized volatility estimators based on economic performance," Journal of Asset Management, Palgrave Macmillan, vol. 26(7), pages 819-846, December.
  17. Cao, Chaojin & He, Yaoyao & Zhou, Yue & Wang, Shuo, 2025. "An online probabilistic combination framework for power load forecasting under concept-drifting scenarios," Applied Energy, Elsevier, vol. 399(C).
  18. Jeff Tayman & David A. Swanson, 2025. "A Simplified Version of the Hamilton–Perry Method for Forecasting Population by Age Group and Gender," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 44(3), pages 1-33, June.
  19. Han Su & Xiaojia Guo & Xiaoke Zhang, 2026. "Regularized Ensemble Forecasting for Learning Weights from Historical and Current Forecasts," Papers 2602.11379, arXiv.org.
  20. Koo, Moon Su & Lee, Yun Shin & Seifert, Matthias, 2025. "Investigating laypeople’s short- and long-term forecasts of COVID-19 infection cycles," International Journal of Forecasting, Elsevier, vol. 41(2), pages 452-465.
  21. James W. Taylor & Chao Wang, 2025. "Combining a Large Pool of Forecasts of Value-at-Risk and Expected Shortfall," Papers 2508.16919, arXiv.org, revised May 2026.
  22. Faria, Gonçalo & Verona, Fabio, 2024. "Enhancing forecast accuracy through frequencydomain combination: Applications to financial and economic indicators," Bank of Finland Research Discussion Papers 14/2024, Bank of Finland.
  23. Marco Zanotti, 2025. "The cost of ensembling: is it always worth combining?," Working Papers 554, University of Milano-Bicocca, Department of Economics.
  24. Ekaterina Astafyeva & Marina Turuntseva, 2024. "Forecast evaluation improving using the simplest methods of individual forecasts’ combination," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 74, pages 78-103.
  25. Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
  26. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
  27. Daniil Koloskov & Marina Turuntseva, 2025. "The oil and coke prices forecast evaluation using the different forecasting scheme," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 80, pages 5-25.
  28. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
  29. Dengao Li & Qi Liu & Ding Feng & Zhichao Chen, 2024. "A Medium- and Long-Term Residential Load Forecasting Method Based on Discrete Cosine Transform-FEDformer," Energies, MDPI, vol. 17(15), pages 1-14, July.
  30. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
  31. Wang, Shengjie & Kang, Yanfei & Petropoulos, Fotios, 2024. "Combining probabilistic forecasts of intermittent demand," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1038-1048.
  32. Gabe J. Bondt, 2025. "Future real GDP: real interest rate and inflation matter," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 49(3), pages 661-681, September.
  33. Yu, Dalei & Tang, Nian-Sheng & Shi, Yang, 2025. "Adaptively aggregated forecast for exponential family panel model," International Journal of Forecasting, Elsevier, vol. 41(2), pages 733-747.
  34. Brusaferri, Alessandro & Ballarino, Andrea & Grossi, Luigi & Laurini, Fabrizio, 2025. "On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices," Applied Energy, Elsevier, vol. 398(C).
  35. Kohút, Roman & Klaučo, Martin & Kvasnica, Michal, 2025. "Unified carbon emissions and market prices forecasts of the power grid," Applied Energy, Elsevier, vol. 377(PC).
  36. Nathan Canen & Kyungchul Song, 2025. "Simple Inference on a Simplex-Valued Weight," Papers 2501.15692, arXiv.org, revised Jan 2026.
  37. Zhang, Bohan & Panagiotelis, Anastasios & Li, Han, 2025. "Constructing hierarchical time series through clustering: Is there an optimal way for forecasting?," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1022-1036.
  38. Zhu, Ziyang & Zheng, Yuhao & Wang, Xinyi & Huang, Dasen & Feng, Lingbing, 2025. "Forecasting China's precious metal futures volatility: GBRT models and time-model dimension combination of Tree SHAP," International Review of Financial Analysis, Elsevier, vol. 104(PA).
  39. Bernaciak, Dawid & Griffin, Jim E., 2024. "A loss discounting framework for model averaging and selection in time series models," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1721-1733.
  40. Sonnleitner, Benedikt & Kourentzes, Nikolaos & Ehrig, Claudia & Pflaum, Alexander, 2025. "Forecasting for optimization in road freight transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 204(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.