Journal of Forecasting

1987 - 2025

Continuation of Journal of Forecasting.

Current editor(s): Derek W. Bunn

From John Wiley & Sons, Ltd.
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Volume 41, issue 8, 2022

Interest rate uncertainty and the predictability of bank revenues pp. 1559-1569

Oguzhan Cepni, Riza Demirer, Rangan Gupta and Ahmet Sensoy

A Siamese network framework for bank intelligent Q&A prediction pp. 1570-1577

Wei Wei and Yingli Liang

Mixed membership nearest neighbor model with feature difference pp. 1578-1594

Simon K. C. Cheung and Tommy K. Y. Cheung

Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets pp. 1595-1607

Man Wang and Yihan Cheng

A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes pp. 1608-1622

Giuseppe Orlando and Michele Bufalo

High‐frequency data and stock–bond investing pp. 1623-1638

Yu‐Sheng Lai

Predicting earnings management through machine learning ensemble classifiers pp. 1639-1660

Ahmad Hammami and Mohammad Hendijani Zadeh

Cryptocurrencies trading algorithms: A review pp. 1661-1668

Isabela Ruiz Roque da Silva, Eli Hadad Junior and Pedro Paulo Balbi

Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending pp. 1669-1690

Yufei Xia, Xinyi Guo, Yinguo Li, Lingyun He and Xueyuan Chen

Forecasting chlorophyll‐a concentration using empirical wavelet transform and support vector regression pp. 1691-1700

Jin‐Won Yu, Ju‐Song Kim, Yun‐Chol Jong, Xia Li and Gwang‐Il Ryang

Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting pp. 1701-1724

Pedro Henrique Melo Albuquerque, Yaohao Peng and João Pedro Fontoura da Silva

The role of investor sentiment in forecasting housing returns in China: A machine learning approach pp. 1725-1740

Oguzhan Cepni, Rangan Gupta and Yigit Onay

Volume 41, issue 7, 2022

Bayesian quantile forecasting via the realized hysteretic GARCH model pp. 1317-1337

Cathy W. S. Chen, Edward M. H. Lin and Tara F. J. Huang

Are internally consistent forecasts rational? pp. 1338-1355

Jing Tian, Firmin Doko Tchatoka and Thomas Goodwin

Forgetting approaches to improve forecasting pp. 1356-1371

Robert A. Hill and Paulo Rodrigues

Central bank information and private‐sector expectations pp. 1372-1385

Jochen Güntner

Modeling credit risk with a multi‐stage hybrid model: An alternative statistical approach pp. 1386-1415

Mohammad Shamsu Uddin, Guotai Chi, Mazin A. M. Al Janabi, Tabassum Habib and Kunpeng Yuan

Evaluating the predictive power of intraday technical trading in China's crude oil market pp. 1416-1432

Xiaoye Jin

Forecasting international equity market volatility: A new approach pp. 1433-1457

Chao Liang, Yan Li, Feng Ma and Yaojie Zhang

Stochastic configuration network based on improved whale optimization algorithm for nonstationary time series prediction pp. 1458-1482

Zi‐yu Chen, Fei Xiao, Xiao‐kang Wang, Min‐hui Deng, Jian‐qiang Wang and Jun‐Bo Li

Multi‐step air quality index forecasting via data preprocessing, sequence reconstruction, and improved multi‐objective optimization algorithm pp. 1483-1511

Ying Wang, Jianzhou Wang, Hongmin Li, Hufang Yang and Zhiwu Li

A weights direct determination neuronet for time‐series with applications in the industrial indices of the Federal Reserve Bank of St. Louis pp. 1512-1524

Spyridon D. Mourtas

Uncertainty and predictability of real housing returns in the United Kingdom: A regional analysis pp. 1525-1556

Afees Salisu, Rangan Gupta, Ahamuefula Ogbonna and Mark Wohar

Volume 41, issue 6, 2022

Uncertainty and forecastability of regional output growth in the UK: Evidence from machine learning pp. 1049-1064

Mehmet Balcilar, David Gabauer, Rangan Gupta and Christian Pierdzioch

Distributional modeling and forecasting of natural gas prices pp. 1065-1086

Jonathan Berrisch and Florian Ziel

Parallel architecture of CNN‐bidirectional LSTMs for implied volatility forecast pp. 1087-1098

Ji‐Eun Choi and Dong Wan Shin

Forecast evaluation of DSGE models: Linear and nonlinear likelihood pp. 1099-1130

Kuo‐Hsuan Chin

Anticipating financial distress of high‐tech startups in the European Union: A machine learning approach for imbalanced samples pp. 1131-1155

Yang Liu, Qingguo Zeng, Bobo Li, Lili Ma and Joaquín Ordieres‐Meré

A novel robust structural quadratic forecasting model and applications pp. 1156-1180

He Jiang

Nowcasting world GDP growth with high‐frequency data pp. 1181-1200

Caroline Jardet and Baptiste Meunier

Deep learning with regularized robust long‐ and short‐term memory network for probabilistic short‐term load forecasting pp. 1201-1216

He Jiang and Weihua Zheng

Subsampled factor models for asset pricing: The rise of Vasa pp. 1217-1247

Gianluca De Nard, Simon Hediger and Markus Leippold

A comparative study of combining tree‐based feature selection methods and classifiers in personal loan default prediction pp. 1248-1313

Weidong Guo and Zach Zhizhong Zhou

Volume 41, issue 5, 2022

Predicting financial crises with machine learning methods pp. 871-910

Lanbiao Liu, Chen Chen and Bo Wang

Stock market as a nowcasting indicator for real investment pp. 911-919

Stavros Degiannakis

ANN–polynomial–Fourier series modeling and Monte Carlo forecasting of tourism data pp. 920-932

Salim Jibrin Danbatta and Asaf Varol

Volatility forecasting for crude oil based on text information and deep learning PSO‐LSTM model pp. 933-944

Xingrui Jiao, Yuping Song, Yang Kong and Xiaolong Tang

Cryptocurrency exchanges: Predicting which markets will remain active pp. 945-955

George Milunovich and Seung Ah Lee

Corporate failure prediction using threshold‐based models pp. 956-979

David Veganzones

Forecasting stock return volatility: The role of shrinkage approaches in a data‐rich environment pp. 980-996

Zhifeng Dai, Tingyu Li and Mi Yang

The influence of policy uncertainty on exchange rate forecasting pp. 997-1016

Lee Smales

A model sufficiency test using permutation entropy pp. 1017-1036

Xin Huang, Han Lin Shang and David Pitt

Limited memory predictors based on polynomial approximation of periodic exponentials pp. 1037-1045

Nikolai Dokuchaev

Volume 41, issue 4, 2022

Multiperiod default probability forecasting pp. 677-696

Oliver Blümke

A new hedging hypothesis regarding prediction interval formation in stock price forecasting pp. 697-717

Dan Zhu, Qingwei Wang and John Goddard

Mixed data sampling regression: Parameter selection of smoothed least squares estimator pp. 718-751

Selma Toker, Nimet Özbay and Kristofer Månsson

Recession forecasting with high‐dimensional data pp. 752-764

Lauri Nevasalmi

Uncertainty and the predictability of stock returns pp. 765-792

Wensheng Cai, Zhiyuan Pan and Yudong Wang

Dendritic neuron model neural network trained by modified particle swarm optimization for time‐series forecasting pp. 793-809

Ayse Yilmaz and Ufuk Yolcu

Uncertainty and disagreement of inflation expectations: Evidence from household‐level qualitative survey responses pp. 810-828

Yongchen Zhao

Evaluating heterogeneous forecasts for vintages of macroeconomic variables pp. 829-839

Philip Hans Franses and Max Welz

Do sentiment indices always improve the prediction accuracy of exchange rates? pp. 840-852

Takumi Ito and Fumiko Takeda

Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models pp. 853-868

Xinjie Lu, Feng Ma, Jiqian Wang and Jing Liu

Volume 41, issue 3, 2022

Forecasting expected shortfall and value at risk with a joint elicitable mixed data sampling model pp. 407-421

Qifa Xu, Lu Chen, Cuixia Jiang and Yezheng Liu

Measuring multi‐volatility states of financial markets based on multifractal clustering model pp. 422-434

Xun Huang and Huiyue Tang

The mutual predictability of Bitcoin and web search dynamics pp. 435-454

Bernd Süssmuth

Random forest versus logit models: Which offers better early warning of fiscal stress? pp. 455-490

Barbara Jarmulska

Assessing the usefulness of survey‐based data in forecasting firms' capital formation: Evidence from Italy pp. 491-513

Claire Giordano, Marco Marinucci and Andrea Silvestrini

The global latent factor and international index futures returns predictability pp. 514-538

Shu‐Lien Chang, Hsiu‐Chuan Lee and Donald Lien

A novel deep learning model based on convolutional neural networks for employee churn prediction pp. 539-550

Ebru Pekel Ozmen and Tuncay Ozcan

Forecasting unemployment in the euro area with machine learning pp. 551-566

Periklis Gogas, Theophilos Papadimitriou and Emmanouil Sofianos

Firm dynamics and bankruptcy processes: A new theoretical model pp. 567-591

Şaban Çelik, Bora Aktan and Bruce Burton

Fundamental index aligned and excess market return predictability pp. 592-614

Samuel YM Ze‐To

Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine pp. 615-632

Wen Zhang and Zhibin Wu

Forecasting Bitcoin volatility: A new insight from the threshold regression model pp. 633-652

Yaojie Zhang, Mengxi He, Danyan Wen and Yudong Wang

A dynamic scenario‐driven technique for stock price prediction and trading pp. 653-674

Yash Thesia, Vidhey Oza and Priyank Thakkar

Volume 41, issue 2, 2022

Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years pp. 213-229

G. Kontogeorgos and Kyriacos Lambrias

Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach pp. 230-251

Danyan Wen, Mengxi He, Yaojie Zhang and Yudong Wang

Investigating the predictive ability of ONS big data‐based indicators pp. 252-258

George Kapetanios and Fotis Papailias

Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models pp. 259-278

Yingying Xu and Donald Lien

Bootstrap VAR forecasts: The effect of model uncertainties pp. 279-293

Diego Fresoli

Spatial beta‐convergence forecasting models: Evidence from municipal homicide rates in Colombia pp. 294-302

Felipe Santos‐Marquez

Forecasting realized volatility of international REITs: The role of realized skewness and realized kurtosis pp. 303-315

Matteo Bonato, Oguzhan Cepni, Rangan Gupta and Christian Pierdzioch

Time‐varying trend models for forecasting inflation in Australia pp. 316-330

Na Guo, Bo Zhang and Jamie Cross

Competition can help predict sales pp. 331-344

Sima M. Fortsch, Jeong Hoon Choi and Elena A. Khapalova

Multistage optimization filter for trend‐based short‐term forecasting pp. 345-360

Usman Zafar, Neil Kellard and Dmitri Vinogradov

What matters when developing oil price volatility forecasting frameworks? pp. 361-382

Panagiotis Delis, Stavros Degiannakis and George Filis

Forecasting the volatility of agricultural commodity futures: The role of co‐volatility and oil volatility pp. 383-404

Hardik A. Marfatia, Qiang Ji and Jiawen Luo

Volume 41, issue 1, 2022

Singular spectrum analysis for value at risk in stochastic volatility models pp. 3-16

Josu Arteche and Javier García‐Enríquez

Step‐ahead spot price densities using daily synchronously reported prices and wind forecasts pp. 17-42

Per B. Solibakke

A state‐dependent linear recurrent formula with application to time series with structural breaks pp. 43-63

Donya Rahmani and Damien Fay

A novel hybrid fine particulate matter (PM2.5) forecasting and its further application system: Case studies in China pp. 64-85

Pei Du, Jianzhou Wang, Wendong Yang and Tong Niu

Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility pp. 86-99

Adam Clements, Yin Liao and Yusui Tang

Forecasting carbon price using a multi‐objective least squares support vector machine with mixture kernels pp. 100-117

Bangzhu Zhu, Shunxin Ye, Ping Wang, Julien Chevallier and Yi-Ming Wei

A new Markov regime‐switching count time series approach for forecasting initial public offering volumes and detecting issue cycles pp. 118-133

Xinyu Wang and Cathy Ning

Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions pp. 134-157

Afees Salisu, Rangan Gupta, Elie Bouri and Qiang Ji

Optimal forecast error as an unbiased estimator of abnormal return: A proposition pp. 158-166

Onur Enginar and Kazim Baris Atici

Modeling interval trendlines: Symbolic singular spectrum analysis for interval time series pp. 167-180

Miguel de Carvalho and Gabriel Martos

A Bayesian time‐varying autoregressive model for improved short‐term and long‐term prediction pp. 181-200

Christoph Berninger, Almond Stöcker and David Rügamer

Comparison of prospective Hawkes and recursive point process models for Ebola in DRC pp. 201-210

Sarita D. Lee, Andy A. Shen, Junhyung Park, Ryan J. Harrigan, Nicole A. Hoff, Anne W. Rimoin and Frederic Paik Schoenberg