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. 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.
  2. Wu, Haoran & Gao, Zhiwei & Nie, Boyang & Zhao, Binru, 2025. "Can machines learn Chinese mutual funds?," Pacific-Basin Finance Journal, Elsevier, vol. 94(C).
  3. 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).
  4. Chen, Yi-Ting & Liu, Chu-An & Su, Jiun-Hua, 2025. "Bregman model averaging for forecast combination," Journal of Econometrics, Elsevier, vol. 251(C).
  5. Pedersen, Michael, 2025. "Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence," International Journal of Forecasting, Elsevier, vol. 41(2), pages 475-486.
  6. V. Candila & O. Cepni & G. 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.
  7. Foucault, Thierry & Gambacorta, Leonardo & Jiang, Wei & Vives, Xavier, 2025. "Barcelona 7: Artificial Intelligence in Finance," HEC Research Papers Series 1599, HEC Paris.
  8. Thompson, Ryan & Qian, Yilin & Vasnev, Andrey L., 2024. "Flexible global forecast combinations," Omega, Elsevier, vol. 126(C).
  9. 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.
  10. Philippe Goulet Coulombe & Maximilian Goebel & Karin Klieber, 2024. "Dual Interpretation of Machine Learning Forecasts," Papers 2412.13076, arXiv.org.
  11. Nathan Canen & Kyungchul Song, 2025. "Simple Inference on a Simplex-Valued Weight," Papers 2501.15692, arXiv.org, revised Jan 2026.
  12. 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).
  13. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
  14. Jinjun Liu & Ming-Yen Cheng, 2026. "Forecasting the U.S. Treasury Yield Curve: A Distributionally Robust Machine Learning Approach for Interest Rate Risk Management," Papers 2601.04608, arXiv.org, revised Jun 2026.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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).
  21. 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.
  22. 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.
  23. Marco Zanotti, 2025. "On the stability of global forecasting models," Working Papers 553, University of Milano-Bicocca, Department of Economics.
  24. Coqueret, Guillaume & Pérignon, Christophe, 2025. "Persistent Anomalies and Nonstandard Errors," HEC Research Papers Series 1578, HEC Paris.
  25. Han Su & Xiaojia Guo & Xiaoke Zhang, 2026. "Regularized Ensemble Forecasting for Learning Weights from Historical and Current Forecasts," Papers 2602.11379, arXiv.org.
  26. Taylor, James W., 2026. "Probabilistic forecast aggregation with statistical depth," European Journal of Operational Research, Elsevier, vol. 328(2), pages 460-476.
  27. Kozyrev, Boris, 2024. "Forecast combination and interpretability using random subspace," IWH Discussion Papers 21/2024, Halle Institute for Economic Research (IWH).
  28. 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.
  29. 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.
  30. 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.
  31. 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).
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. Marco Zanotti, 2025. "The cost of ensembling: is it always worth combining?," Working Papers 554, University of Milano-Bicocca, Department of Economics.
  37. 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).
  38. 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).
  39. 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.
  40. Lin, Tzu-Chi & Liu, Chu-An, 2025. "Model averaging prediction for possibly nonstationary autoregressions," Journal of Econometrics, Elsevier, vol. 249(PB).
  41. Kohút, Roman & Klaučo, Martin & Kvasnica, Michal, 2025. "Unified carbon emissions and market prices forecasts of the power grid," Applied Energy, Elsevier, vol. 377(PC).
  42. Zhang, Hanyuan & Liu, Ying & Liu, Xinyang & Liu, Anyu & Lin, Vera Shanshan, 2026. "Forecasting Chinese outbound tourism recovery: A Triple-layer forecast combination framework," Annals of Tourism Research, Elsevier, vol. 116(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.