Journal of Forecasting

1987 - 2024

Continuation of Journal of Forecasting.

Current editor(s): Derek W. Bunn

From John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().

Access Statistics for this journal.
Is something missing from the series or not right? See the RePEc data check for the archive and series.

Volume 43, issue 7, 2024

Multivariable forecasting approach of high‐speed railway passenger demand based on residual term of Baidu search index and error correction pp. 2401-2433

Hongtao Li, Xiaoxuan Li, Shaolong Sun, Zhipeng Huang and Xiaoyan Jia

Prediction of wind energy with the use of tensor‐train based higher order dynamic mode decomposition pp. 2434-2447

Keren Li and Sergey Utyuzhnikov

Credit card loss forecasting: Some lessons from COVID pp. 2448-2477

Partha Sengupta and Christopher H. Wheeler

A novel semisupervised learning method with textual information for financial distress prediction pp. 2478-2494

Yue Qiu, Jiabei He, Zhensong Chen, Yinhong Yao and Yi Qu

Forecasting Chinese crude oil futures volatility: New evidence based on dual feature processing of large‐scale variables pp. 2495-2521

Gaoxiu Qiao, Yijun Pan, Chao Liang, Lu Wang and Jinghui Wang

Data patterns that reliably precede US recessions pp. 2522-2539

Edward E. Leamer

Forecasting corporate financial performance with deep learning and interpretable ALE method: Evidence from China pp. 2540-2571

Longyue Liang, Bo Liu, Zhi Su and Xuanye Cai

Are professional forecasters inattentive to public discussions about inflation? The case of Argentina pp. 2572-2587

J. Daniel Aromí and Martín Llada

Takeover in Europe: Target characteristics and acquisition likelihood pp. 2588-2606

Hicham Meghouar

A multistage forecasting model for green bond cost optimization with dynamic corporate risk constraints pp. 2607-2634

Zinan Hu, Ruicheng Yang and Sumuya Borjigin

A study and development of high‐order fuzzy time series forecasting methods for air quality index forecasting pp. 2635-2658

Sushree Subhaprada Pradhan and Sibarama Panigrahi

Time‐varying risk preference and equity risk premium forecasting: The role of the disposition effect pp. 2659-2674

Kenan Qiao and Haibin Xie

Twitter policy uncertainty and stock returns in South Africa: Evidence from time‐varying Granger causality pp. 2675-2684

Kingstone Nyakurukwa and Yudhvir Seetharam

A deep learning‐based multivariate decomposition and ensemble framework for container throughput forecasting pp. 2685-2704

Anurag Kulshrestha, Abhishek Yadav, Himanshu Sharma and Shikha Suman

Forecasting stock returns with industry volatility concentration pp. 2705-2730

Yaojie Zhang, Mengxi He and Zhikai Zhang

Forecasting tail risk of skewed financial returns having exponential‐polynomial tails pp. 2731-2748

Albert Antwi, Emmanuel N. Gyamfi and Anokye M. Adam

Volatility forecasting incorporating intraday positive and negative jumps based on deep learning model pp. 2749-2765

Yilun Zhang, Yuping Song, Ying Peng and Hanchao Wang

Traffic flow prediction: A 3D adaptive multi‐module joint modeling approach integrating spatial‐temporal patterns to capture global features pp. 2766-2791

Zain Ul Abideen, Xiaodong Sun and Chao Sun

Portfolio management based on a reinforcement learning framework pp. 2792-2808

Wu Junfeng, Li Yaoming, Tan Wenqing and Chen Yun

Seeing is believing: Forecasting crude oil price trend from the perspective of images pp. 2809-2821

Xiaohang Ren, Wenting Jiang, Qiang Ji and Pengxiang Zhai

Regime‐dependent commodity price dynamics: A predictive analysis pp. 2822-2847

Jesus Crespo Cuaresma, Ines Fortin, Jaroslava Hlouskova and Michael Obersteiner

Forecasting the direction of the Fed's monetary policy decisions using random forest pp. 2848-2859

Jungyeon Yoon and Juanjuan Fan

Measuring persistent global economic factors with output, commodity price, and commodity currency data pp. 2860-2885

Arabinda Basistha and Richard Startz

Splitting long‐term and short‐term financial ratios for improved financial distress prediction: Evidence from Taiwanese public companies pp. 2886-2903

Asyrofa Rahmi, Chia‐chi Lu, Deron Liang and Ayu Nur Fadilah

Forecasting Bitcoin returns: Econometric time series analysis vs. machine learning pp. 2904-2916

Theo Berger and Jana Koubová

Structured multifractal scaling of the principal cryptocurrencies: Examination using a self‐explainable machine learning pp. 2917-2934

Foued Saâdaoui and Hana Rabbouch

Volume 43, issue 6, 2024

Forecasting agricultures security indices: Evidence from transformers method pp. 1733-1746

Ammouri Bilel

Liquidity‐adjusted value‐at‐risk using extreme value theory and copula approach pp. 1747-1769

Harish Kamal and Samit Paul

Return predictability via an long short‐term memory‐based cross‐section factor model: Evidence from Chinese stock market pp. 1770-1794

Haixiang Yao, Shenghao Xia and Hao Liu

Forecasting Consumer Price Index with Federal Open Market Committee Sentiment Index pp. 1795-1813

Joshua Eklund and Jong‐Min Kim

Forecasting elections from partial information using a Bayesian model for a multinomial sequence of data pp. 1814-1834

Soudeep Deb, Rishideep Roy and Shubhabrata Das

Correlation‐based tests of predictability pp. 1835-1858

Pablo Pincheira and Nicolás Hardy

Electricity price forecasting using quantile regression averaging with nonconvex regularization pp. 1859-1879

He Jiang, Yao Dong and Jianzhou Wang

Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes pp. 1880-1901

Tomas Pečiulis, Nisar Ahmad, Angeliki N. Menegaki and Aqsa Bibi

Forecasting peak electric load: Robust support vector regression with smooth nonconvex ϵ‐insensitive loss pp. 1902-1917

Rujia Nie, Jinxing Che, Fang Yuan and Weihua Zhao

Forecasting regional industrial production with novel high‐frequency electricity consumption data pp. 1918-1935

Robert Lehmann and Sascha Möhrle

Vine copula‐based scenario tree generation approaches for portfolio optimization pp. 1936-1955

Xiaolei He and Weiguo Zhang

Can intraday data improve the joint estimation and prediction of risk measures? Evidence from a variety of realized measures pp. 1956-1974

Zhimin Wu and Guanghui Cai

Disciplining growth‐at‐risk models with survey of professional forecasters and Bayesian quantile regression pp. 1975-1981

Milan Szabo

Well googled is half done: Multimodal forecasting of new fashion product sales with image‐based google trends pp. 1982-1997

Geri Skenderi, Christian Joppi, Matteo Denitto and Marco Cristani

An ensemble model for stock index prediction based on media attention and emotional causal inference pp. 1998-2020

Juanjuan Wang, Shujie Zhou, Wentong Liu and Lin Jiang

New runs‐based approach to testing value at risk forecasts pp. 2021-2041

Marta Małecka

Text‐based corn futures price forecasting using improved neural basis expansion network pp. 2042-2063

Lin Wang, Wuyue An and Feng‐Ting Li

Explainable machine learning techniques based on attention gate recurrent unit and local interpretable model‐agnostic explanations for multivariate wind speed forecasting pp. 2064-2087

Lu Peng, Sheng‐Xiang Lv and Lin Wang

Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter? pp. 2088-2125

Matteo Bonato, Oguzhan Cepni, Rangan Gupta and Christian Pierdzioch

Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions? pp. 2126-2145

Martin Feldkircher, Luis Gruber, Florian Huber and Gregor Kastner

The effects of governance quality on renewable and nonrenewable energy consumption: An explainable decision frame pp. 2146-2162

Futian Weng, Dongsheng Cheng, Muni Zhuang, Xin Lu and Cai Yang

Predicting tail risks by a Markov switching MGARCH model with varying copula regimes pp. 2163-2186

Markus J. Fülle and Helmut Herwartz

An infinite hidden Markov model with stochastic volatility pp. 2187-2211

Chenxing Li, John Maheu and Qiao Yang

Constructing a high‐frequency World Economic Gauge using a mixed‐frequency dynamic factor model pp. 2212-2227

Chew Lian Chua, Sarantis Tsiaplias and Ruining Zhou

Forecasting carbon emissions using asymmetric grouping pp. 2228-2256

Didier Nibbering and Richard Paap

Performance and reporting predictability of hedge funds pp. 2257-2278

Elisa Becker‐Foss

A systematic vector autoregressive framework for modeling and forecasting mortality pp. 2279-2297

Jackie Li, Jia Liu and Adam Butt

The mean squared prediction error paradox pp. 2298-2321

Pablo Pincheira and Nicolás Hardy

Bayesian Markov switching model for BRICS currencies' exchange rates pp. 2322-2340

Utkarsh Kumar, Wasim Ahmad and Gazi Salah Uddin

Are national or regional surveys useful for nowcasting regional jobseekers? The case of the French region of Pays‐de‐la‐Loire pp. 2341-2357

Clément Cariou, Amélie Charles and Olivier Darné

Forecasting healthcare service volumes with machine learning algorithms pp. 2358-2377

Dong‐Hui Yang, Ke‐Hui Zhu and Ruo‐Nan Wang

Hybrid forecasting of crude oil volatility index: The cross‐market effects of stock market jumps pp. 2378-2398

Gongyue Jiang, Gaoxiu Qiao, Lu Wang and Feng Ma

Volume 43, issue 5, 2024

Gated recurrent unit network: A promising approach to corporate default prediction pp. 1131-1152

Michał Thor and Łukasz Postek

Density forecast combinations: The real‐time dimension pp. 1153-1172

Peter McAdam and Anders Warne

Embedding the weather prediction errors (WPE) into the photovoltaic (PV) forecasting method using deep learning pp. 1173-1198

Adela Bâra and Simona‐Vasilica Oprea

Stock movement prediction: A multi‐input LSTM approach pp. 1199-1211

Pan Tang, Cheng Tang and Keren Wang

Macroeconomic conditions and bank failure pp. 1212-1234

Qiongbing Wu and Rebel A. Cole

Early warning system for currency crises using long short‐term memory and gated recurrent unit neural networks pp. 1235-1262

Sylvain Barthélémy, Virginie Gautier and Fabien Rondeau

Two‐stage credit risk prediction framework based on three‐way decisions with automatic threshold learning pp. 1263-1277

Yusheng Li and Mengyi Sha

Hybrid convolutional long short‐term memory models for sales forecasting in retail pp. 1278-1293

Thais de Castro Moraes, Xue‐Ming Yuan and Ek Peng Chew

A deep learning hierarchical approach to road traffic forecasting pp. 1294-1307

Redouane Benabdallah Benarmas and Kadda Beghdad Bey

Measuring the advantages of contemporaneous aggregation in forecasting pp. 1308-1320

Zeda Li and William W. S. Wei

Space, mortality, and economic growth pp. 1321-1337

Kyran Cupido, Petar Jevtić and Tim J. Boonen

Forecasting multi‐frequency intraday exchange rates using deep learning models pp. 1338-1355

Muhammad Arslan, Ahmed Imran Hunjra, Wajid Shakeel Ahmed and Younes Ben Zaied

Forecasting the high‐frequency volatility based on the LSTM‐HIT model pp. 1356-1373

Guangying Liu, Ziyan Zhuang and Min Wang

Incorporating media news to predict financial distress: Case study on Chinese listed companies pp. 1374-1398

Lifang Zhang, Mohammad Zoynul Abedin and Zhenkun Liu

Conservatism and information rigidity of the European Bank for Reconstruction and Development's growth forecast: Quarter‐century assessment pp. 1399-1421

Yoichi Tsuchiya

Forecasting realized volatility of crude oil futures prices based on machine learning pp. 1422-1446

Jiawen Luo, Tony Klein, Thomas Walther and Qiang Ji

International evidence of the forecasting ability of option‐implied distributions pp. 1447-1464

Pedro Serrano, Antoni Vaello‐Sebastià and M. Magdalena Vich Llompart

Probabilistic electricity price forecasting based on penalized temporal fusion transformer pp. 1465-1491

He Jiang, Sheng Pan, Yao Dong and Jianzhou Wang

Tail risk forecasting with semiparametric regression models by incorporating overnight information pp. 1492-1512

Cathy W. S. Chen, Takaaki Koike and Wei‐Hsuan Shau

Tail risk forecasting and its application to margin requirements in the commodity futures market pp. 1513-1529

Yun Feng, Weijie Hou and Yuping Song

Robust approach to earnings forecast: A comparison pp. 1530-1558

Xiaojian Yu, Xiaoqian Zhang and Donald Lien

Applying k‐nearest neighbors to time series forecasting: Two new approaches pp. 1559-1574

Samya Tajmouati, Bouazza E. L. Wahbi, Adel Bedoui, Abdallah Abarda and Mohamed Dakkon

Interpretable corn future price forecasting with multivariate time series pp. 1575-1594

Binrong Wu, Zhongrui Wang and Lin Wang

Forecasting stock market returns with a lottery index: Evidence from China pp. 1595-1606

Yaojie Zhang, Qingxiang Han and Mengxi He

Do search queries predict violence against women? A forecasting model based on Google Trends pp. 1607-1614

Nicolás Gonzálvez‐Gallego, María Concepción Pérez‐Cárceles and Laura Nieto‐Torrejón

A forecasting model for oil prices using a large set of economic indicators pp. 1615-1624

Jihad El Hokayem, Ibrahim Jamali and Ale Hejase

Credit risk prediction based on causal machine learning: Bayesian network learning, default inference, and interpretation pp. 1625-1660

Jiaming Liu, Xuemei Zhang and Haitao Xiong

Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering pp. 1661-1681

Corey Ducharme, Bruno Agard and Martin Trépanier

A novel hybrid forecasting model with feature selection and deep learning for wind speed research pp. 1682-1705

Xuejun Chen, Ying Wang, Haitao Zhang and Jianzhou Wang

Volatility forecasting for stock market incorporating media reports, investors' sentiment, and attention based on MTGNN model pp. 1706-1730

Bolin Lei and Yuping Song

Volume 43, issue 4, 2024

Forecasting in turbulent times pp. 819-826

Nikolaos Giannellis, Stephen Hall, Georgios Kouretas and George Tavlas

Inflation forecasting with rolling windows: An appraisal pp. 827-851

Stephen Hall, George Tavlas, Yongli Wang and Deborah Gefang

How we missed the inflation surge: An anatomy of post‐2020 inflation forecast errors pp. 852-870

Christoffer Koch and Diaa Noureldin

Post‐COVID inflation dynamics: Higher for longer pp. 871-893

Randal Verbrugge and Saeed Zaman

Using deep (machine) learning to forecast US inflation in the COVID‐19 era pp. 894-902

David Stoneman and John Duca

Trust and monetary policy pp. 903-931

Paul De Grauwe and Yuemei Ji

An evaluation of the inflation forecasting performance of the European Central Bank, the Federal Reserve, and the Bank of England pp. 932-947

Eleni Argiri, Stephen Hall, Angeliki Momtsia, Daphne Marina Papadopoulou, Ifigeneia Skotida, George Tavlas and Yongli Wang

Combine to compete: Improving fiscal forecast accuracy over time pp. 948-982

Laura Carabotta and Peter Claeys

Forecasting exchange rates: An iterated combination constrained predictor approach pp. 983-1017

Antonios K. Alexandridis, Ekaterini Panopoulou and Ioannis Souropanis

The term structure of interest rates and economic activity: Evidence from the COVID‐19 pandemic pp. 1018-1041

Evangelos Salachas, Georgios Kouretas and Nikiforos T. Laopodis

Forecasting GDP growth: The economic impact of COVID‐19 pandemic pp. 1042-1086

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

Forecasting food price inflation during global crises pp. 1087-1113

Patricia Toledo and Roberto Duncan

Modeling the effects of Brexit on the British economy pp. 1114-1126

A. Patrick Minford and Zheyi Zhu

Volume 43, issue 3, 2024

A comparison of Range Value at Risk (RVaR) forecasting models pp. 509-543

Fernanda Maria Müller, Thalles Weber Gössling, Samuel Solgon Santos and Marcelo Brutti Righi

Volatility forecasting for stock market index based on complex network and hybrid deep learning model pp. 544-566

Yuping Song, Bolin Lei, Xiaolong Tang and Chen Li

Out‐of‐sample volatility prediction: Rolling window, expanding window, or both? pp. 567-582

Yuqing Feng, Yaojie Zhang and Yudong Wang

A Markov chain model of crop conditions and intrayear crop yield forecasting pp. 583-592

Jeffrey Stokes

Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system pp. 593-614

Yinghua Song, Minzhe Jiang, Shixuan Li and Shengzhe Zhao

EWT‐SMOTE to improve default prediction performance in imbalanced data: Analysis of Chinese data pp. 615-643

Ying Zhou, Xia Lin, Guotai Chi, Peng Jin and Mengtong Li

RMB exchange rate forecasting using machine learning methods: Can multimodel select powerful predictors? pp. 644-660

Xing Yu, Yanyan Li and Xinxin Wang

Forecasting air passenger travel: A case study of Norwegian aviation industry pp. 661-672

Angesh Anupam and Isah A. Lawal

Downturns and changes in the yield slope pp. 673-701

Mirko Abbritti, Juan Equiza, Antonio Moreno and Tommaso Trani

Forecasting CPI with multisource data: The value of media and internet information pp. 702-753

Tingguo Zheng, Xinyue Fan, Wei Jin and Kuangnan Fang

Empirical prediction intervals for additive Holt–Winters methods under misspecification pp. 754-770

Boning Yang, Xinyi Tang and Chun Yip Yau

Forecasts with Bayesian vector autoregressions under real time conditions pp. 771-801

Michael Pfarrhofer

Forecasting the containerized freight index with AIS data: A novel information combination method based on gray incidence analysis pp. 802-815

Yanhui Chen, Ailing Feng, Shun Chen and Jackson Jinhong Mi

Volume 43, issue 2, 2024

Big data financial transactions and GDP nowcasting: The case of Turkey pp. 227-248

Ali B. Barlas, Seda Guler Mert, Berk Orkun Isa, Alvaro Ortiz, Tomasa Rodrigo, Baris Soybilgen and Ege Yazgan

Interval time series forecasting: A systematic literature review pp. 249-285

Piao Wang, Shahid Hussain Gurmani, Zhifu Tao, Jinpei Liu and Huayou Chen

Credit scoring prediction leveraging interpretable ensemble learning pp. 286-308

Yang Liu, Fei Huang, Lili Ma, Qingguo Zeng and Jiale Shi

Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint pp. 309-325

Qianjie Geng, Xianfeng Hao and Yudong Wang

Determinants of disagreement: Learning from inflation expectations survey of households pp. 326-343

Gaurav Kumar Singh and Tathagata Bandyopadhyay

Prediction of daily tourism volume based on maximum correlation minimum redundancy feature selection and long short‐term memory network pp. 344-365

Ming Yin, Feiya Lu, Xingxuan Zhuo, Wangzi Yao, Jialong Liu and Jijiao Jiang

A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price pp. 366-390

Rui Luo, Jinpei Liu, Piao Wang, Zhifu Tao and Huayou Chen

A classification application for using learning methods in bank costumer's portfolio churn pp. 391-401

Murat Simsek and Iclal Cetin Tas

Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments pp. 402-414

Trung H. Le

Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment pp. 415-428

T. Jayasankar, R. Kiruba Buri and P. Maheswaravenkatesh

Enhancing credit risk prediction based on ensemble tree‐based feature transformation and logistic regression pp. 429-455

Jiaming Liu, Jiajia Liu, Chong Wu and Shouyang Wang

Business applications and state‐level stock market realized volatility: A forecasting experiment pp. 456-472

Matteo Bonato, Oguzhan Cepni, Rangan Gupta and Christian Pierdzioch

Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs pp. 473-489

Wanhai You, Yuming Huang and Chien‐Chiang Lee

The optimal interval combination prediction model based on vectorial angle cosine and a new aggregation operator for social security level prediction pp. 490-505

Kexin Peng, Chao Kang, Xiwen Ru and Ligang Zhou