International Journal of Forecasting

1985 - 2025

Current editor(s): R. J. Hyndman

From Elsevier
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Volume 40, issue 4, 2024

Forecasting day-ahead expected shortfall on the EUR/USD exchange rate: The (I)relevance of implied volatility pp. 1275-1301

Štefan Lyócsa, Tomáš Plíhal and Tomáš Výrost

Nowcasting with panels and alternative data: The OECD weekly tracker pp. 1302-1335

Nicolas Woloszko

Thinking outside the container: A sparse partial least squares approach to forecasting trade flows pp. 1336-1358

Vincent Stamer

Generalized Poisson difference autoregressive processes pp. 1359-1390

Giulia Carallo, Roberto Casarin and Christian P. Robert

An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors pp. 1391-1409

Yang Liu and Norman R. Swanson

Forecasting emergency department occupancy with advanced machine learning models and multivariable input pp. 1410-1420

Jalmari Tuominen, Eetu Pulkkinen, Jaakko Peltonen, Juho Kanniainen, Niku Oksala, Ari Palomäki and Antti Roine

A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market pp. 1421-1437

Cameron Cornell, Nam Trong Dinh and S. Ali Pourmousavi

Properties of the reconciled distributions for Gaussian and count forecasts pp. 1438-1448

Lorenzo Zambon, Arianna Agosto, Paolo Giudici and Giorgio Corani

CRPS-based online learning for nonlinear probabilistic forecast combination pp. 1449-1466

Dennis van der Meer, Pierre Pinson, Simon Camal and Georges Kariniotakis

Forecasting seasonal demand for retail: A Fourier time-varying grey model pp. 1467-1485

Lili Ye, Naiming Xie, John E. Boylan and Zhongju Shang

Survey density forecast comparison in small samples pp. 1486-1504

Laura Coroneo, Fabrizio Iacone and Fabio Profumo

Instance-based meta-learning for conditionally dependent univariate multi-step forecasting pp. 1507-1520

Vitor Cerqueira, Luis Torgo and Gianluca Bontempi

Forecasting UK inflation bottom up pp. 1521-1538

Andreas Joseph, Galina Potjagailo, Chiranjit Chakraborty and George Kapetanios

Network log-ARCH models for forecasting stock market volatility pp. 1539-1555

Raffaele Mattera and Philipp Otto

A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times pp. 1556-1567

Harrison Katz, Kai Thomas Brusch and Robert E. Weiss

Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices pp. 1568-1586

Jonathan Berrisch and Florian Ziel

The short-term predictability of returns in order book markets: A deep learning perspective pp. 1587-1621

Lorenzo Lucchese, Mikko S. Pakkanen and Almut Veraart

Improving forecasts for heterogeneous time series by “averaging”, with application to food demand forecasts pp. 1622-1645

Lukas Neubauer and Peter Filzmoser

Dynamic prediction of the National Hockey League draft with rank-ordered logit models pp. 1646-1659

Brendan Kumagai, Ryker Moreau, Kimberly Kroetch and Tim B. Swartz

Factor-augmented forecasting in big data pp. 1660-1688

Juhee Bae

Hierarchical forecasting at scale pp. 1689-1700

Olivier Sprangers, Wander Wadman, Sebastian Schelter and Maarten de Rijke

Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts pp. 1701-1720

Helga Kristin Olafsdottir, Holger Rootzén and David Bolin

A loss discounting framework for model averaging and selection in time series models pp. 1721-1733

Dawid Bernaciak and Jim E. Griffin

Conditionally optimal weights and forward-looking approaches to combining forecasts pp. 1734-1751

Christopher Gibbs and Andrey Vasnev

Volume 40, issue 3, 2024

Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties pp. 859-868

Alex T. Mallen, Henning Lange and J. Nathan Kutz

A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices pp. 869-880

Giovanni Campisi, Silvia Muzzioli and Bernard De Baets

A False Discovery Rate approach to optimal volatility forecasting model selection pp. 881-902

Arman Hassanniakalager, Paul L. Baker and Emmanouil Platanakis

Should I open to forecast? Implications from a multi-country unobserved components model with sparse factor stochastic volatility pp. 903-917

Ping Wu

Comparing forecasting performance with panel data pp. 918-941

Ritong Qu, Allan Timmermann and Yinchu Zhu

A multi-task encoder-dual-decoder framework for mixed frequency data prediction pp. 942-957

Jiahe Lin and George Michailidis

Improving geopolitical forecasts with 100 brains and one computer pp. 958-970

Hilla Shinitzky, Yhonatan Shemesh, David Leiser and Michael Gilead

Network time series forecasting using spectral graph wavelet transform pp. 971-984

Kyusoon Kim and Hee-Seok Oh

Systemic bias of IMF reserve and debt forecasts for program countries pp. 985-1001

Theo S. Eicher and Reina Kawai

The profitability of lead–lag arbitrage at high frequency pp. 1002-1021

Cédric Poutré, Georges Dionne and Gabriel Yergeau

Forecasting crude oil market volatility: A comprehensive look at uncertainty variables pp. 1022-1041

Danyan Wen, Mengxi He, Yudong Wang and Yaojie Zhang

Forecasting euro area inflation using a huge panel of survey expectations pp. 1042-1054

Florian Huber, Luca Onorante and Michael Pfarrhofer

Demand forecasting under lost sales stock policies pp. 1055-1068

Juan R. Trapero, Enrique Holgado de Frutos and Diego J. Pedregal

A theory-based method to evaluate the impact of central bank inflation forecasts on private inflation expectations pp. 1069-1084

Luciano Vereda, João Savignon and Tarciso Gouveia da Silva

Improving models and forecasts after equilibrium-mean shifts pp. 1085-1100

Jennifer Castle, Jurgen Doornik and David Hendry

Evaluating probabilistic classifiers: The triptych pp. 1101-1122

Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan and Peter Vogel

DeepTVAR: Deep learning for a time-varying VAR model with extension to integrated VAR pp. 1123-1133

Xixi Li and Jingsong Yuan

Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues pp. 1134-1151

Daniele Girolimetto, George Athanasopoulos, Tommaso Di Fonzo and Rob Hyndman

Rating players by Laplace’s approximation and dynamic modeling pp. 1152-1165

Hsuan-Fu Hua, Ching-Ju Chang, Tse-Ching Lin and Ruby Chiu-Hsing Weng

Out-of-sample predictability in predictive regressions with many predictor candidates pp. 1166-1178

Jesus Gonzalo and Jean-Yves Pitarakis

Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach pp. 1179-1188

Weidong Lin and Abderrahim Taamouti

Short-term stock price trend prediction with imaging high frequency limit order book data pp. 1189-1205

Wuyi Ye, Jinting Yang and Pengzhan Chen

Reservoir computing for macroeconomic forecasting with mixed-frequency data pp. 1206-1237

Giovanni Ballarin, Petros Dellaportas, Lyudmila Grigoryeva, Marcel Hirt, Sophie van Huellen and Juan-Pablo Ortega

Do professional forecasters believe in the Phillips curve? pp. 1238-1254

Michael Clements

Forecasting day-ahead electricity prices with spatial dependence pp. 1255-1270

Yifan Yang, Guo, Ju’e, Yi Li and Jiandong Zhou

Volume 40, issue 2, 2024

Forecast reconciliation: A review pp. 430-456

George Athanasopoulos, Rob Hyndman, Nikolaos Kourentzes and Anastasios Panagiotelis

Probabilistic reconciliation of count time series pp. 457-469

Giorgio Corani, Dario Azzimonti and Nicolò Rubattu

Probabilistic hierarchical forecasting with deep Poisson mixtures pp. 470-489

Kin G. Olivares, O. Nganba Meetei, Ruijun Ma, Rohan Reddy, Mengfei Cao and Lee Dicker

Forecast combination-based forecast reconciliation: Insights and extensions pp. 490-514

Tommaso Di Fonzo and Daniele Girolimetto

Likelihood-based inference in temporal hierarchies pp. 515-531

Jan Kloppenborg Møller, Peter Nystrup and Henrik Madsen

Forecasting Australian fertility by age, region, and birthplace pp. 532-548

Yang Yang, Han Lin Shang and James Raymer

Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement pp. 549-563

Han Li and Hua Chen

Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates pp. 564-580

Doruk Cengiz and Hasan Tekgüç

Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions pp. 581-596

Paul Ghelasi and Florian Ziel

Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions pp. 597-615

Mahdi Abolghasemi, Garth Tarr and Christoph Bergmeir

Optimal hierarchical EWMA forecasting pp. 616-625

Giacomo Sbrana and Matteo Pelagatti

Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates pp. 626-640

Gary Koop, Stuart McIntyre, James Mitchell and Aubrey Poon

Hierarchical transfer learning with applications to electricity load forecasting pp. 641-660

Anestis Antoniadis, Solenne Gaucher and Yannig Goude

Back to the present: Learning about the euro area through a now-casting model pp. 661-686

Danilo Cascaldi-Garcia, Thiago R.T. Ferreira, Domenico Giannone and Michele Modugno

On the role of fundamentals, private signals, and beauty contests to predict exchange rates pp. 687-705

Giuseppe Pignataro, Davide Raggi and Francesca Pancotto

Personalized choice model for forecasting demand under pricing scenarios with observational data—The case of attended home delivery pp. 706-720

Özden Gür Ali and Pedro Amorim

Generalized βARMA model for double bounded time series forecasting pp. 721-734

Vinícius T. Scher, Francisco Cribari-Neto and Fábio M. Bayer

Improving inflation forecasts using robust measures pp. 735-745

Randal Verbrugge and Saeed Zaman

Words or numbers? Macroeconomic nowcasting with textual and macroeconomic data pp. 746-761

Tingguo Zheng, Xinyue Fan, Wei Jin and Kuangnan Fang

Daily growth at risk: Financial or real drivers? The answer is not always the same pp. 762-776

Helena Chuliá, Ignacio Garrón and Jorge Uribe

Financial-cycle ratios and medium-term predictions of GDP: Evidence from the United States pp. 777-795

Graziano Moramarco

Quantifying subjective uncertainty in survey expectations pp. 796-810

Fabian Krüger and Lora Pavlova

Bayesian forecasting in economics and finance: A modern review pp. 811-839

Gael M. Martin, David T. Frazier, Worapree Maneesoonthorn, Rubén Loaiza-Maya, Florian Huber, Gary Koop, John Maheu, Didier Nibbering and Anastasios Panagiotelis

(Structural) VAR models with ignored changes in mean and volatility pp. 840-854

Matei Demetrescu and Nazarii Salish

Volume 40, issue 1, 2024

Forecasting the equity premium with frequency-decomposed technical indicators pp. 6-28

Tobias Stein

Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks pp. 29-43

Mawuli Segnon, Rangan Gupta and Bernd Wilfling

Bars, lines and points: The effect of graph format on judgmental forecasting pp. 44-61

Stian Reimers and Nigel Harvey

Forecasting in factor augmented regressions under structural change pp. 62-76

Daniele Massacci and George Kapetanios

Wind energy forecasting with missing values within a fully conditional specification framework pp. 77-95

Honglin Wen, Pierre Pinson, Jie Gu and Zhijian Jin

A review and comparison of conflict early warning systems pp. 96-112

Espen Geelmuyden Rød, Tim Gåsste and Håvard Hegre

Eliciting expectation uncertainty from private households pp. 113-123

Jonas Dovern

Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling pp. 124-141

Seungwoo Kang and Hee-Seok Oh

A market for trading forecasts: A wagering mechanism pp. 142-159

Aitazaz Ali Raja, Pierre Pinson, Jalal Kazempour and Sergio Grammatico

How local is the local inflation factor? Evidence from emerging European countries pp. 160-183

Oguzhan Cepni and Michael Clements

Empirical probabilistic forecasting: An approach solely based on deterministic explanatory variables for the selection of past forecast errors pp. 184-201

Eduardo E. Romanus, Eugênio Silva and Ronaldo R. Goldschmidt

Equal predictive ability tests based on panel data with applications to OECD and IMF forecasts pp. 202-228

Oguzhan Akgun, Alain Pirotte, Giovanni Urga and Zhenlin Yang

A time-varying skewness model for Growth-at-Risk pp. 229-246

Martin Iseringhausen

Demand forecasting for fashion products: A systematic review pp. 247-267

Kritika Swaminathan and Rakesh Venkitasubramony

Are consensus FX forecasts valuable for investors? pp. 268-284

Marek Kwas, Joscha Beckmann and Michał Rubaszek

Bayesian herd detection for dynamic data pp. 285-301

Jussi Keppo and Ville A. Satopää

Forecasting football match results using a player rating based model pp. 302-312

Benjamin Holmes and Ian G. McHale

Accelerating peak dating in a dynamic factor Markov-switching model pp. 313-323

Bram van Os and Dick van Dijk

2T-POT Hawkes model for left- and right-tail conditional quantile forecasts of financial log returns: Out-of-sample comparison of conditional EVT models pp. 324-347

Matthew F. Tomlinson, David Greenwood and Marcin Mucha-Kruczyński

A novel deep ensemble model for imbalanced credit scoring in internet finance pp. 348-372

Jin Xiao, Yu Zhong, Yanlin Jia, Yadong Wang, Ruoyi Li, Xiaoyi Jiang and Shouyang Wang

Conflict forecasting using remote sensing data: An application to the Syrian civil war pp. 373-391

Daniel Racek, Paul W. Thurner, Brittany I. Davidson, Xiao Xiang Zhu and Göran Kauermann

Outlier-robust methods for forecasting realized covariance matrices pp. 392-408

Dan Li, Christopher Drovandi and Adam Clements

Predicting recessions using VIX–yield curve cycles pp. 409-422

Anne Lundgaard Hansen