International Journal of Forecasting

1985 - 2026

Current editor(s): R. J. Hyndman

From Elsevier
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Volume 42, issue 3, 2026

The hybrid renewable energy forecasting and trading competition 2024 pp. 709-723

Jethro Browell, Dennis van der Meer, Henrik Kälvegren, Sebastian Haglund, Edoardo Simioni, Ricardo J. Bessa and Yi Wang

The HEFTCom2024 winning model: A stacked CatBoost approach for probabilistic wind and solar power forecasting pp. 724-735

Jon Olauson, Olle Viotti and Jakob Huss

A hybrid strategy for probabilistic forecasting and trading of aggregated wind-solar power: Design and analysis in HEFTCom2024 pp. 736-751

Chuanqing Pu, Feilong Fan, Nengling Tai, Songyuan Liu and Jinming Yu

Beyond news headlines and TF-IDF: Enhancing text-based forecasting models with validated collocations and improved attention pp. 752-773

Gabriel Appau Abeyie

New tests of equal forecast accuracy for factor-augmented regressions with weaker loadings pp. 776-795

Luca Margaritella and Ovidijus Stauskas

Corrected Support Vector Regression for intraday point forecasting of prices in the continuous power market pp. 796-815

Andrzej Puć and Joanna Janczura

Modeling and forecasting intraday spot volatility pp. 816-832

Adam Clements and Daniel P.A. Preve

Jump persistence and temporal aggregation of tail risk pp. 833-852

Chunyang Zhou, Chongfeng Wu and Xiangwei Wan

Bayesian forecasting of zero-inflated time-series of counts pp. 853-871

Tevfik Aktekin, Refik Soyer and Di Zhang

Quantile-based modeling of scale dynamics in financial returns for Value-at-Risk and Expected Shortfall forecasting pp. 872-888

Xiaochun Liu and Richard Luger

International factors and inflation risks pp. 889-908

Ignacio Garrón, Vladimir Rodríguez-Caballero and Esther Ruiz

Assessing the accuracy of probabilistic population forecasts pp. 909-923

Juha Alho and Nico Keilman

Beyond forecast leaderboards: Measuring individual model importance based on contribution to ensemble accuracy pp. 924-936

Minsu Kim, Evan L. Ray and Nicholas G. Reich

Assessing cross-currency predictability in forex markets: Insights from limit order book data pp. 937-953

Yana Petrova, Anders Vilhelmsson and Lars L. Nordén

Candidate vote prediction in open-list systems: Forecasting the results of the 2023 Finnish parliamentary election pp. 954-970

Tapio Vepsäläinen

Integrating nowcasts into an ensemble of data-driven forecasting models for SARI hospitalizations in Germany pp. 971-988

Daniel Wolffram, Johannes Bracher and Melanie Schienle

Forecasting systemic risk measures using a dynamic semiparametric approach based on the Asymmetric Laplace distribution pp. 989-1007

Yaming Yang

Confidence-scaled margin adaptation boosting for interpretable financial distress prediction pp. 1008-1032

Wanan Liu, Xingyu Lan, Meng Xia, Yao Zou, Congyuan Pang and Guangxiao Song

A Bayesian Dirichlet autoregressive conditional heteroskedasticity model for forecasting currency shares pp. 1033-1046

Harrison Katz and Robert E. Weiss

Improving disaggregated short-term food inflation forecasts with webscraped data pp. 1047-1068

Christian Beer, Robert Ferstl and Bernhard Graf

Realized volatility forecasting for new issues and spin-offs using multi-source transfer learning pp. 1069-1103

Andreas Teller, Uta Pigorsch and Christian Pigorsch

Restoring the forecasting power of Google Trends with statistical preprocessing pp. 1104-1122

Candice Djorno, Mauricio Santillana and Shihao Yang

Volume 42, issue 2, 2026

Can we protect time series data while maintaining accurate forecasts? pp. 297-314

Cameron D. Bale, Matthew J. Schneider and Jinwook Lee

Practice makes perfect: Learning effects with household point and density forecasts of inflation pp. 315-329

James Mitchell, Taylor Shiroff and Hana Braitsch

HARd to beat: The overlooked impact of rolling windows in the era of machine learning pp. 330-343

Jonathan Chassot and Francesco Audrino

Using dynamic loss weighting to boost improvements in forecast stability pp. 344-358

Daan Caljon, Jeff Vercauteren, Simon De Vos, Wouter Verbeke and Jente Van Belle

Impact of climate change on mortality: An extrapolation of temperature effects based on time series data in France pp. 359-413

Quentin Guibert, Gaëlle Pincemin and Frédéric Planchet

Forecasting economic time series in the presence of weak factors: Multiple supervised learning-based approach pp. 414-433

Ulrich Hounyo and Zhendong Li

Portfolio return prediction and risk price heterogeneity pp. 434-456

Nick Taylor

Ups and (draw) downs pp. 457-473

Tommaso Proietti

The Bayesian context trees state space model for time series modelling and forecasting pp. 474-491

Ioannis Papageorgiou and Ioannis Kontoyiannis

Bayesian estimation of a multivariate TAR model when the noise process distribution belongs to the class of Gaussian variance mixtures pp. 492-511

L.H. Vanegas, S.A. Calderón V and L.M. Rondón

Overreaction through anchoring pp. 512-526

Constantin Bürgi and Julio L. Ortiz

Macroeconomic forecasting using factor models with martingale difference errors pp. 527-547

L.M. Rolla and A. Giovannelli

Getting back on track: Forecasting after extreme observations pp. 548-569

Pål Boug, Håvard Hungnes and Takamitsu Kurita

Volatility forecasting for low-volatility investing pp. 570-586

Christian Conrad, Onno Kleen and Rasmus Lönn

Whispers in the oil market: Exploring sentiment and uncertainty insights pp. 587-601

Luigi Gifuni

Forecasting electoral violence pp. 602-615

David Randahl, Maxine Leis, Tim Gåsste, Hanne Fjelde, Håvard Hegre, Staffan I. Lindberg and Steven Wilson

Leveraging image-based generative adversarial networks for time series generation pp. 616-639

Justin Hellermann and Stefan Lessmann

Asymmetric models for realized covariances pp. 640-656

Luc Bauwens, Emilija Dzuverovic and Christian Hafner

Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model pp. 657-672

Luca Barbaglia, Lorenzo Frattarolo, Niko Hauzenberger, Dominik Hirschbühl, Florian Huber, Luca Onorante, Michael Pfarrhofer and Luca Tiozzo Pezzoli

Combining predictive distributions for time-to-event outcomes in meteorology pp. 673-690

Céline Cunen, Thea Roksvåg, Claudio Heinrich-Mertsching and Alex Lenkoski

Stochastic modelling of football matches using dynamic regressors pp. 691-707

Luiz Fernando G.N. Maia, Teemu Pennanen, Moacyr A.H.B. da Silva and Rodrigo S. Targino

Volume 42, issue 1, 2026

Editorial and introduction to the special section on the Bernanke’s review of the Bank of England’s forecasting activities pp. 1-2

Pierre Pinson

Reactions to the Bernanke Review from Bank of England watchers pp. 3-12

David Aikman and Richard Barwell

Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24? pp. 13-21

Jennifer Castle, Jurgen A. Doornik and David Hendry

Forecasting for monetary policy pp. 22-33

Laura Coroneo

Forecasting and policy when “we simply do not know” pp. 34-39

Alan Kirman, Angus Armstrong and William Hynes

Beyond the numbers: The role of people and processes in central bank forecasting pp. 40-43

Nikolaos Kourentzes and Robert Fildes

Optimal text-based time-series indices pp. 44-60

David Ardia and Keven Bluteau

When to be discrete: The importance of time formulation in the modeling of extreme events in finance pp. 61-84

Katarzyna Bień-Barkowska and Rodrigo Herrera

Deep switching state space model for nonlinear time series forecasting with regime switching pp. 85-98

Xiuqin Xu, Hanqiu Peng and Ying Chen

Is it possible to predict electoral abstention on the individual level? A preregistered test on forecasting the effects of abolishing compulsory voting in Belgium pp. 99-111

Dieter Stiers and Marc Hooghe

Kairosis: A method for dynamical probability forecast aggregation informed by Bayesian change-point detection pp. 112-125

Zane Hassoun, Niall MacKay and Ben Powell

Combining forecasts under structural breaks using Graphical LASSO pp. 126-137

Tae-Hwy Lee and Ekaterina Seregina

Anticipating humanitarian emergencies with a high risk of conflict-induced displacement pp. 138-157

Nicolas Rost and Michele Ronco

A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures pp. 158-180

Deqing Wang, Zhihao Lu, Zhenhua Liu, Shoucong Xue, Mengxia Guo and Yiwen Hou

Forecasting UK consumer price inflation with RaGNAR: Random generalised network autoregressive processes pp. 181-202

Guy P. Nason and Henry Antonio Palasciano

Citizen forecasting in a mixed electoral system pp. 203-215

Arndt Leininger, Andreas E. Murr, Lukas Stötzer and Mark A. Kayser

Hierarchical neural additive models for interpretable demand forecasts pp. 216-234

Leif Feddersen and Catherine Cleophas

All forecasters are not the same: Systematic patterns in predictive performance pp. 235-258

Robert Rich and Joseph Tracy

VAR Model with Sparse Group LASSO for Multi-population Mortality Forecasting pp. 259-280

Tim J. Boonen and Yuhuai Chen

Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil? pp. 281-295

Amor Aniss Benmoussa, Reinhard Ellwanger and Stephen Snudden