International Journal of Forecasting

1985 - 2025

Current editor(s): R. J. Hyndman

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Volume 39, issue 4, 2023

Harry Markowitz: An appreciation pp. 1496-1501

John Guerard

On the evaluation of hierarchical forecasts pp. 1502-1511

George Athanasopoulos and Nikolaos Kourentzes

Forecast combinations: An over 50-year review pp. 1518-1547

Xiaoqian Wang, Rob Hyndman, Feng Li and Yanfei Kang

Testing big data in a big crisis: Nowcasting under Covid-19 pp. 1548-1563

Luca Barbaglia, Lorenzo Frattarolo, Luca Onorante, Filippo Maria Pericoli, Marco Ratto and Luca Tiozzo Pezzoli

Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk pp. 1564-1572

Romain Pic, Clément Dombry, Philippe Naveau and Maxime Taillardat

Robust regression for electricity demand forecasting against cyberattacks pp. 1573-1592

Daniel VandenHeuvel, Jinran Wu and You-Gan Wang

Tree-based heterogeneous cascade ensemble model for credit scoring pp. 1593-1614

Wanan Liu, Hong Fan and Meng Xia

IMF trade forecasts for crisis countries: Bias, inefficiency, and their origins pp. 1615-1639

Theo Eicher and Reina Kawai

Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value pp. 1640-1654

Dazhi Yang and Jan Kleissl

The impact of macroeconomic scenarios on recurrent delinquency: A stress testing framework of multi-state models for mortgages pp. 1655-1677

Cecilia Bocchio, Jonathan Crook and Galina Andreeva

Forecasting the variability of stock index returns with the multifractal random walk model for realized volatilities pp. 1678-1697

Cristina Sattarhoff and Thomas Lux

Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data pp. 1698-1712

Jin-Yu Fu, Jin-Guan Lin and Hong-Xia Hao

Internal consistency of household inflation expectations: Point forecasts vs. density forecasts pp. 1713-1735

Yongchen Zhao

Real-time density nowcasts of US inflation: A model combination approach pp. 1736-1760

Edward Knotek and Saeed Zaman

Projected Dynamic Conditional Correlations pp. 1761-1776

Jordi Llorens-Terrazas and Christian Brownlees

Early Warning Systems for identifying financial instability pp. 1777-1803

Erindi Allaj and Simona Sanfelici

Stock market volatility predictability in a data-rich world: A new insight pp. 1804-1819

Feng Ma, Jiqian Wang, M.I.M. Wahab and Yuanhui Ma

Macroeconomic forecasting in the euro area using predictive combinations of DSGE models pp. 1820-1838

Jan Čapek, Jesus Crespo Cuaresma, Niko Hauzenberger and Vlastimil Reichel

LASSO principal component averaging: A fully automated approach for point forecast pooling pp. 1839-1852

Bartosz Uniejewski and Katarzyna Maciejowska

Identifying predictors of analyst rating quality: An ensemble feature selection approach pp. 1853-1873

Shuai Jiang, Yanhong Guo, Wenjun Zhou and Xianneng Li

A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks pp. 1874-1894

Yara Kayyali Elalem, Sebastian Maier and Ralf W. Seifert

On the uncertainty of a combined forecast: The critical role of correlation pp. 1895-1908

Jan R. Magnus and Andrey Vasnev

Forecasting GDP growth rates in the United States and Brazil using Google Trends pp. 1909-1924

Evripidis Bantis, Michael Clements and Andrew Urquhart

Dynamic linear models with adaptive discounting pp. 1925-1944

Alisa Yusupova, Nicos G. Pavlidis and Efthymios Pavlidis

Volume 39, issue 3, 2023

Thirty years on: A review of the Lee–Carter method for forecasting mortality pp. 1033-1049

Ugofilippo Basellini, Carlo Giovanni Camarda and Heather Booth

Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods pp. 1065-1077

Claudia Berloco, Raffaele Argiento and Silvia Montagna

Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models pp. 1078-1096

Carol Alexander, Yang Han and Xiaochun Meng

The power of narrative sentiment in economic forecasts pp. 1097-1121

Steven Sharpe, Nitish R. Sinha and Christopher A. Hollrah

Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data pp. 1122-1144

Daniel Borup, David E. Rapach and Erik Christian Schütte

Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks pp. 1145-1162

Oren Barkan, Jonathan Benchimol, Itamar Caspi, Eliya Cohen, Allon Hammer and Noam Koenigstein

Distributed ARIMA models for ultra-long time series pp. 1163-1184

Xiaoqian Wang, Yanfei Kang, Rob Hyndman and Feng Li

Penalized estimation of panel vector autoregressive models: A panel LASSO approach pp. 1185-1204

Annika Camehl

Factor models for large and incomplete data sets with unknown group structure pp. 1205-1220

Maximo Camacho and German Lopez-Buenache

Improving variance forecasts: The role of Realized Variance features pp. 1221-1237

Ioannis Papantonis, Leonidas Rompolis and Elias Tzavalis

A fully Bayesian tracking algorithm for mitigating disparate prediction misclassification pp. 1238-1252

Martin B. Short and George O. Mohler

Forecasting electricity prices using bid data pp. 1253-1271

Aitor Ciarreta, Blanca Martinez and Shahriyar Nasirov

Daily peak electrical load forecasting with a multi-resolution approach pp. 1272-1286

Yvenn Amara-Ouali, Matteo Fasiolo, Yannig Goude and Hui Yan

Bayesian forecast combination using time-varying features pp. 1287-1302

Li Li, Yanfei Kang and Feng Li

fETSmcs: Feature-based ETS model component selection pp. 1303-1317

Lingzhi Qi, Xixi Li, Qiang Wang and Suling Jia

Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility pp. 1318-1332

Yaojie Zhang, Mengxi He, Yudong Wang and Chao Liang

Improving forecast stability using deep learning pp. 1333-1350

Jente Van Belle, Ruben Crevits and Wouter Verbeke

Shrinkage estimator for exponential smoothing models pp. 1351-1365

Kandrika F. Pritularga, Ivan Svetunkov and Nikolaos Kourentzes

Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States pp. 1366-1383

Evan L. Ray, Logan C. Brooks, Jacob Bien, Matthew Biggerstaff, Nikos I. Bosse, Johannes Bracher, Estee Y. Cramer, Sebastian Funk, Aaron Gerding, Michael A. Johansson, Aaron Rumack, Yijin Wang, Martha Zorn, Ryan J. Tibshirani and Nicholas G. Reich

Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model pp. 1384-1412

David Kohns and Arnab Bhattacharjee

Betting on a buzz: Mispricing and inefficiency in online sportsbooks pp. 1413-1423

Philip Ramirez, J Reade and Carl Singleton

LoMEF: A framework to produce local explanations for global model time series forecasts pp. 1424-1447

Dilini Rajapaksha, Christoph Bergmeir and Rob Hyndman

Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions pp. 1448-1459

Maxime Taillardat, Anne-Laure Fougères, Philippe Naveau and Raphaël de Fondeville

Nowcasting GDP with a pool of factor models and a fast estimation algorithm pp. 1460-1476

Sercan Eraslan and Maximilian Schröder

Model combinations through revised base rates pp. 1477-1492

Fotios Petropoulos, Evangelos Spiliotis and Anastasios Panagiotelis

Volume 39, issue 2, 2023

How to “improve” prediction using behavior modification pp. 541-555

Galit Shmueli and Ali Tafti

Forecasting, causality and feedback pp. 558-560

Rob Hyndman

Forecasting electricity prices with expert, linear, and nonlinear models pp. 570-586

Anna Gloria Billé, Angelica Gianfreda, Filippo Del Grosso and Francesco Ravazzolo

Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US pp. 587-605

Felix Haase and Matthias Neuenkirch

Testing the predictive accuracy of COVID-19 forecasts pp. 606-622

Laura Coroneo, Fabrizio Iacone, Alessia Paccagnini and Paulo Santos Monteiro

A Markov chain model for forecasting results of mixed martial arts contests pp. 623-640

Benjamin Holmes, Ian G. McHale and Kamila Żychaluk

An accurate and fully-automated ensemble model for weekly time series forecasting pp. 641-658

Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb and Pablo Montero-Manso

Forecasting crude oil futures market returns: A principal component analysis combination approach pp. 659-673

Yaojie Zhang and Yudong Wang

Bayesian model averaging for mortality forecasting using leave-future-out validation pp. 674-690

Karim Barigou, Pierre-Olivier Goffard, Stéphane Loisel and Yahia Salhi

Beating the market with a bad predictive model pp. 691-719

Ondřej Hubáček and Gustav Šír

Forecasting extreme financial risk: A score-driven approach pp. 720-735

Fernanda Fuentes, Rodrigo Herrera and Adam Clements

Empirically-transformed linear opinion pools pp. 736-753

Anthony Garratt, Timo Henckel and Shaun Vahey

Analysing differences between scenarios pp. 754-771

David Hendry and Felix Pretis

Differing behaviours of forecasters of UK GDP growth pp. 772-790

Nigel Meade and Ciaran Driver

The power of text-based indicators in forecasting Italian economic activity pp. 791-808

Valentina Aprigliano, Simone Emiliozzi, Gabriele Guaitoli, Andrea Luciani, Juri Marcucci and Libero Monteforte

Nowcasting food inflation with a massive amount of online prices pp. 809-826

Paweł Macias, Damian Stelmasiak and Karol Szafranek

Time-varying variance and skewness in realized volatility measures pp. 827-840

Anne Opschoor and Andre Lucas

Targeting predictors in random forest regression pp. 841-868

Daniel Borup, Bent Jesper Christensen, Nicolaj Søndergaard Mühlbach and Mikkel Slot Nielsen

A copula-based time series model for global horizontal irradiation pp. 869-883

Alfred Müller and Matthias Reuber

Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx pp. 884-900

Kin G. Olivares, Cristian Challu, Grzegorz Marcjasz, Rafał Weron and Artur Dubrawski

Real-time inflation forecasting using non-linear dimension reduction techniques pp. 901-921

Niko Hauzenberger, Florian Huber and Karin Klieber

The RWDAR model: A novel state-space approach to forecasting pp. 922-937

Giacomo Sbrana and Andrea Silvestrini

DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations pp. 938-955

Luc Bauwens and Yongdeng Xu

Aggregating qualitative district-level campaign assessments to forecast election results: Evidence from Japan pp. 956-966

Michio Umeda

Physics-informed Gaussian process regression for states estimation and forecasting in power grids pp. 967-980

Alexandre M. Tartakovsky, Tong Ma, David A. Barajas-Solano and Ramakrishna Tipireddy

Calibration of deterministic NWP forecasts and its impact on verification pp. 981-991

Martin János Mayer and Dazhi Yang

Deep learning models for visibility forecasting using climatological data pp. 992-1004

Luz C. Ortega, Luis Daniel Otero, Mitchell Solomon, Carlos E. Otero and Aldo Fabregas

A robust support vector regression model for electric load forecasting pp. 1005-1020

Jian Luo, Tao Hong, Zheming Gao and Shu-Cherng Fang

Volume 39, issue 1, 2023

Forecasting Bitcoin with technical analysis: A not-so-random forest? pp. 1-17

Nikola Gradojevic, Dragan Kukolj, Robert Adcock and Vladimir Djakovic

Too similar to combine? On negative weights in forecast combination pp. 18-38

Peter Radchenko, Andrey Vasnev and Wendun Wang

Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives pp. 39-57

Tommaso Di Fonzo and Daniele Girolimetto

Real estate illiquidity and returns: A time-varying regional perspective pp. 58-72

Michael Ellington, Xi Fu and Yunyi Zhu

Probabilistic population forecasting: Short to very long-term pp. 73-97

Adrian E. Raftery and Hana Ševčíková

Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy pp. 98-109

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

Evaluation of the best M4 competition methods for small area population forecasting pp. 110-122

Tom Wilson, Irina Grossman and Jeromey Temple

Influence of earnings management on forecasting corporate failure pp. 123-143

David Veganzones, Eric Séverin and Souhir Chlibi

Interactive R&D spillovers: An estimation strategy based on forecasting-driven model selection pp. 144-169

Georgios Gioldasis, Antonio Musolesi and Michel Simioni

Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020) pp. 170-177

Andreas Graefe

Technical analysis, spread trading, and data snooping control pp. 178-191

Ioannis Psaradellis, Jason Laws, Athanasios A. Pantelous and Georgios Sermpinis

Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques pp. 192-208

Elisabetta Benevento, Davide Aloini and Nunzia Squicciarini

Data-based priors for vector error correction models pp. 209-227

Jan Prüser

Weekly economic activity: Measurement and informational content pp. 228-243

Philipp Wegmüller, Christian Glocker and Valentino Guggia

Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods pp. 244-265

Fan Lin, Yao Zhang and Jianxue Wang

Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence pp. 266-278

Andres Algaba, Samuel Borms, Kris Boudt and Brecht Verbeken

FRED-SD: A real-time database for state-level data with forecasting applications pp. 279-297

Kathryn O. Bokun, Laura Jackson Young, Kevin Kliesen and Michael Owyang

Nowcasting German GDP: Foreign factors, financial markets, and model averaging pp. 298-313

Paolo Andreini, Thomas Hasenzagl, Lucrezia Reichlin, Charlotte Senftleben-König and Till Strohsal

Forecasting expected shortfall: Should we use a multivariate model for stock market factors? pp. 314-331

Alain-Philippe Fortin, Jean-Guy Simonato and Georges Dionne

Parameter-efficient deep probabilistic forecasting pp. 332-345

Olivier Sprangers, Sebastian Schelter and Maarten de Rijke

Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage pp. 346-363

Deborah Gefang, Gary Koop and Aubrey Poon

Does the Phillips curve help to forecast euro area inflation? pp. 364-390

Marta Banbura and Elena Bobeica

Non-Gaussian models for CoVaR estimation pp. 391-404

Michele Leonardo Bianchi, Giovanni De Luca and Giorgia Rivieccio

Estimation of a dynamic multi-level factor model with possible long-range dependence pp. 405-430

Yunus Emre Ergemen and C. Vladimir Rodríguez-Caballero

The accuracy of IMF crises nowcasts pp. 431-449

Theo Eicher and Yuan Gao Rollinson

Multi-population mortality projection: The augmented common factor model with structural breaks pp. 450-469

Pengjie Wang, Athanasios A. Pantelous and Farshid Vahid

Decomposing the effects of crowd-wisdom aggregators: The bias–information–noise (BIN) model pp. 470-485

Ville A. Satopää, Marat Salikhov, Philip E. Tetlock and Barbara Mellers

Forecasting crude oil market volatility using variable selection and common factor pp. 486-502

Yaojie Zhang, M.I.M. Wahab and Yudong Wang

A mixture model for credit card exposure at default using the GAMLSS framework pp. 503-518

Suttisak Wattanawongwan, Christophe Mues, Ramin Okhrati, Taufiq Choudhry and Mee Chi So

The COVID-19 shock and challenges for inflation modelling pp. 519-539

Elena Bobeica and Benny Hartwig