International Journal of Forecasting

1985 - 2025

Current editor(s): R. J. Hyndman

From Elsevier
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Volume 37, issue 4, 2021

30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial pp. 1333-1337

Alvaro Escribano, Daniel Peña and Esther Ruiz

Macroeconomic data transformations matter pp. 1338-1354

Philippe Goulet Coulombe, Maxime Leroux, Dalibor Stevanovic and Stéphane Surprenant

Variational Bayes approximation of factor stochastic volatility models pp. 1355-1375

David Gunawan, Robert Kohn and David Nott

Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach pp. 1376-1398

Tommaso Proietti, Alessandro Giovannelli, Ottavio Ricchi, Ambra Citton, Christían Tegami and Cristina Tinti

Factor extraction using Kalman filter and smoothing: This is not just another survey pp. 1399-1425

Pilar Poncela, Esther Ruiz and Karen Miranda

Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data pp. 1426-1441

Francisco Blasques, Meindert Heres Hoogerkamp, Siem Jan Koopman and Ilka van de Werve

Mixed random forest, cointegration, and forecasting gasoline prices pp. 1442-1462

Alvaro Escribano and Dandan Wang

Semiparametric time series models driven by latent factor pp. 1463-1479

Gisele de Oliveira Maia, Wagner Barreto-Souza, Fernando de Souza Bastos and Hernando Ombao

Spurious relationships in high-dimensional systems with strong or mild persistence pp. 1480-1497

Jesus Gonzalo and Jean-Yves Pitarakis

Sparse estimation of dynamic principal components for forecasting high-dimensional time series pp. 1498-1508

Daniel Peña, Ezequiel Smucler and Victor J. Yohai

Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach pp. 1509-1519

Francis Diebold, Maximilian Göbel, Philippe Goulet Coulombe, Glenn Rudebusch and Boyuan Zhang

Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting pp. 1520-1534

Carlos Trucíos, João H.G. Mazzeu, Luiz Hotta, Pedro Valls Pereira and Marc Hallin

Modeling high-dimensional unit-root time series pp. 1535-1555

Zhaoxing Gao and Ruey S. Tsay

Modelling non-stationary ‘Big Data’ pp. 1556-1575

Jennifer Castle, Jurgen Doornik and David Hendry

A new method to assess the degree of information rigidity using fixed-event forecasts pp. 1576-1589

Luciano Vereda, João Savignon and Tarciso Gouveia da Silva

Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach pp. 1590-1613

Yufei Xia, Junhao Zhao, Lingyun He, Yinguo Li and Xiaoli Yang

Rounding behaviour of professional macro-forecasters pp. 1614-1631

Michael Clements

Principles and algorithms for forecasting groups of time series: Locality and globality pp. 1632-1653

Pablo Montero-Manso and Rob Hyndman

Forecasting government support in Irish general elections: Opinion polls and structural models pp. 1654-1665

Stephen Quinlan and Michael S. Lewis-Beck

Forecasting multiparty by-elections using Dirichlet regression pp. 1666-1676

Chris Hanretty

Identification of volatility proxies as expectations of squared financial returns pp. 1677-1690

Genaro Sucarrat

Volatility forecasting in European government bond markets pp. 1691-1709

Ali Gencay Ozbekler, Alexandros Kontonikas and Athanasios Triantafyllou

Minimizing post-shock forecasting error through aggregation of outside information pp. 1710-1727

Jilei Lin and Daniel J. Eck

Improving the wisdom of crowds with analysis of variance of predictions of related outcomes pp. 1728-1747

Ville A. Satopää

Temporal Fusion Transformers for interpretable multi-horizon time series forecasting pp. 1748-1764

Bryan Lim, Sercan Ö. Arık, Nicolas Loeff and Tomas Pfister

Volume 37, issue 3, 2021

Big data from dynamic pricing: A smart approach to tourism demand forecasting pp. 1049-1060

Andrea Guizzardi, Flavio Maria Emanuele Pons, Giovanni Angelini and Ercolino Ranieri

Interpretable sports team rating models based on the gradient descent algorithm pp. 1061-1071

Jan Lasek and Marek Gagolewski

Investigating the accuracy of cross-learning time series forecasting methods pp. 1072-1084

Artemios-Anargyros Semenoglou, Evangelos Spiliotis, Spyros Makridakis and Vassilios Assimakopoulos

Forecasting exchange rates with elliptically symmetric principal components pp. 1085-1091

Karo Solat and Kwok Ping Tsang

Stock market volatility forecasting: Do we need high-frequency data? pp. 1092-1110

Štefan Lyócsa, Peter Molnár and Tomáš Výrost

A dynamic conditional approach to forecasting portfolio weights pp. 1111-1126

Fabrizio Cipollini, Giampiero Gallo and Alessandro Palandri

Dimensionality reduction in forecasting with temporal hierarchies pp. 1127-1146

Peter Nystrup, Erik Lindström, Jan K. Møller and Henrik Madsen

Optimal model averaging forecasting in high-dimensional survival analysis pp. 1147-1155

Xiaodong Yan, Hongni Wang, Wei Wang, Jinhan Xie, Yanyan Ren and Xinjun Wang

Penalized maximum likelihood estimation of logit-based early warning systems pp. 1156-1172

Claudia Pigini

Forecasting macroeconomic risks pp. 1173-1191

Patrick A. Adams, Tobias Adrian, Nina Boyarchenko and Domenico Giannone

Discrete Gompertz equation and model selection between Gompertz and logistic models pp. 1192-1211

Daisuke Satoh

Minnesota-type adaptive hierarchical priors for large Bayesian VARs pp. 1212-1226

Joshua Chan

A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls pp. 1227-1234

Mark Levene and Trevor Fenner

Measuring and forecasting retail trade in real time using card transactional data pp. 1235-1246

Juan García López, Matías Pacce, Tomasa Rodrigo, Pep Ruiz de Aguirre and Camilo A. Ulloa

Does judgment improve macroeconomic density forecasts? pp. 1247-1260

Ana Galvão, Anthony Garratt and James Mitchell

Predicting benchmarked US state employment data in real time pp. 1261-1275

Scott Brave, Charles Gascon, William Kluender and Thomas Walstrum

A comparison of monthly global indicators for forecasting growth pp. 1276-1295

Christiane Baumeister and Pierre Guérin

Volume 37, issue 2, 2021

On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation pp. 445-460

Mauro Costantini and Robert Kunst

Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective pp. 461-483

Yezheng Liu, Chang Ye, Jianshan Sun, Yuanchun Jiang and Hai Wang

Multivariate volatility forecasts for stock market indices pp. 484-499

Ines Wilms, Jeroen Rombouts and Christophe Croux

Monitoring recessions: A Bayesian sequential quickest detection method pp. 500-510

Haixi Li, Xuguang Simon Sheng and Jingyun Yang

On the predictability of the distribution of excess returns in currency markets pp. 511-530

Dooyeon Cho

Forecasting crude oil prices with DSGE models pp. 531-546

Michał Rubaszek

Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals pp. 547-568

Erick Meira, Fernando Luiz Cyrino Oliveira and Jooyoung Jeon

A DCC-type approach for realized covariance modeling with score-driven dynamics pp. 569-586

Danilo Vassallo, Giuseppe Buccheri and Fulvio Corsi

Kaggle forecasting competitions: An overlooked learning opportunity pp. 587-603

Casper Solheim Bojer and Jens Peder Meldgaard

Forecast encompassing tests for the expected shortfall pp. 604-621

Timo Dimitriadis and Julie Schnaitmann

Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting pp. 622-633

Anne Opschoor and Andre Lucas

Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts pp. 634-646

Michael Clements

Modeling and predicting U.S. recessions using machine learning techniques pp. 647-671

Spyridon D. Vrontos, John Galakis and Ioannis D. Vrontos

The uncertainty in extreme risk forecasts from covariate-augmented volatility models pp. 675-686

Yannick Hoga

ALICE: Composite leading indicators for euro area inflation cycles pp. 687-707

Gabe de Bondt, Elke Hahn and Zivile Zekaite

Intermittency and obsolescence: A Croston method with linear decay pp. 708-715

S.D. Prestwich, S.A. Tarim and R. Rossi

Are professional forecasters overconfident? pp. 716-732

Eddie Casey

Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions pp. 733-758

Yu-Min Yen and Tso-Jung Yen

Sparse structures with LASSO through principal components: Forecasting GDP components in the short-run pp. 759-776

Saulius Jokubaitis, Dmitrij Celov and Remigijus Leipus

Conformal prediction interval estimation and applications to day-ahead and intraday power markets pp. 777-799

Christopher Kath and Florian Ziel

Evaluating quantile-bounded and expectile-bounded interval forecasts pp. 800-811

James W. Taylor

Spatiotemporal wind forecasting by learning a hierarchically sparse inverse covariance matrix using wind directions pp. 812-824

Yin Liu, Sam Davanloo Tajbakhsh and Antonio J. Conejo

Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches pp. 825-837

Cristiane Melchior, Roselaine Ruviaro Zanini, Renata Rojas Guerra and Dinei A. Rockenbach

Conditional value-at-risk forecasts of an optimal foreign currency portfolio pp. 838-861

Dongwhan Kim and Kyu Ho Kang

Forecasting the volatility of asset returns: The informational gains from option prices pp. 862-880

Vance Martin, Chrismin Tang and Wenying Yao

Nonparametric tests for Optimal Predictive Ability pp. 881-898

Stelios Arvanitis, Thierry Post, Valerio Potì and Selcuk Karabati

Measuring the Connectedness of the Global Economy pp. 899-919

Matthew Greenwood-Nimmo, Viet Hoang Nguyen and Yongcheol Shin

Granger causality detection in high-dimensional systems using feedforward neural networks pp. 920-940

Hector Calvo-Pardo, Tullio Mancini and Jose Olmo

Nowcasting GDP using machine-learning algorithms: A real-time assessment pp. 941-948

Adam Richardson, Thomas van Florenstein Mulder and Tugrul Vehbi

U-Convolutional model for spatio-temporal wind speed forecasting pp. 949-970

Bruno Quaresma Bastos, Fernando Luiz Cyrino Oliveira and Ruy Luiz Milidiú

Bayesian VAR forecasts, survey information, and structural change in the euro area pp. 971-999

Gergely Ganics and Florens Odendahl

Bayesian median autoregression for robust time series forecasting pp. 1000-1010

Zijian Zeng and Meng Li

A new approach to estimating earnings forecasting models: Robust regression MM-estimation pp. 1011-1030

Li Qu

Stability in the inefficient use of forecasting systems: A case study in a supply chain company pp. 1031-1046

Robert Fildes and Paul Goodwin

Volume 37, issue 1, 2021

Probabilistic recalibration of forecasts pp. 1-27

Carlo Graziani, Robert Rosner, Jennifer M. Adams and Reason L. Machete

Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants pp. 28-43

Wei Chen, Huilin Xu, Lifen Jia and Ying Gao

Realized volatility forecasting: Robustness to measurement errors pp. 44-57

Fabrizio Cipollini, Giampiero Gallo and Edoardo Otranto

Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model pp. 58-71

Moumita Saha, Anirban Santara, Pabitra Mitra, Arun Chakraborty and Ravi S. Nanjundiah

Data snooping in equity premium prediction pp. 72-94

Hubert Dichtl, Wolfgang Drobetz, Andreas Neuhierl and Viktoria-Sophie Wendt

Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model pp. 95-104

Silvia Rizzi, Søren Kjærgaard, Marie-Pier Bergeron Boucher, Carlo Giovanni Camarda, Rune Lindahl-Jacobsen and James W. Vaupel

Analytic moments for GJR-GARCH (1, 1) processes pp. 105-124

Carol Alexander, Emese Lazar and Silvia Stanescu

The effect of spatiotemporal resolution on predictive policing model performance pp. 125-133

Anneleen Rummens and Wim Hardyns

Probabilistic access forecasting for improved offshore operations pp. 134-150

Ciaran Gilbert, Jethro Browell and David McMillan

Boosting nonlinear predictability of macroeconomic time series pp. 151-170

Heikki Kauppi and Timo Virtanen

Forecasting high resolution electricity demand data with additive models including smooth and jagged components pp. 171-185

Umberto Amato, Anestis Antoniadis, Italia De Feis, Yannig Goude and Audrey Lagache

Ranking professional forecasters by the predictive power of their narratives pp. 186-204

Krzysztof Rybinski

Online distributed learning in wind power forecasting pp. 205-223

Benedikt Sommer, Pierre Pinson, Jakob W. Messner and David Obst

Keeping track of global trade in real time pp. 224-236

Jaime Martinez-Martin and Elena Rusticelli

Bagging weak predictors pp. 237-254

Eric Hillebrand, Manuel Lukas and Wei Wei

Forecasting mortality with a hyperbolic spatial temporal VAR model pp. 255-273

Lingbing Feng, Yanlin Shi and Le Chang

Artificial intelligence-based predictions of movie audiences on opening Saturday pp. 274-288

Yongdae An, Jinwon An and Sungzoon Cho

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model pp. 289-301

Philippe Mongrain, Richard Nadeau and Bruno Jérôme

Forecasting week-to-week television ratings using reduced-form and structural dynamic models pp. 302-321

Lianlian Song, Yang Shi, Geoffrey Kwok Fai Tso and Hing Po Lo

A critical overview of privacy-preserving approaches for collaborative forecasting pp. 322-342

Carla Gonçalves, Ricardo J. Bessa and Pierre Pinson

Forecast reconciliation: A geometric view with new insights on bias correction pp. 343-359

Anastasios Panagiotelis, George Athanasopoulos, Puwasala Gamakumara and Rob Hyndman

Preventing rather than punishing: An early warning model of malfeasance in public procurement pp. 360-377

Jorge Gallego, Gonzalo Rivero and Juan Martínez

Expert forecasting with and without uncertainty quantification and weighting: What do the data say? pp. 378-387

Roger Cooke, Deniz Marti and Thomas Mazzuchi

Recurrent Neural Networks for Time Series Forecasting: Current status and future directions pp. 388-427

Hansika Hewamalage, Christoph Bergmeir and Kasun Bandara

Forecasting recovery rates on non-performing loans with machine learning pp. 428-444

Anthony Bellotti, Damiano Brigo, Paolo Gambetti and Frédéric Vrins