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 42, issue 8, 2023

Mixed‐frequency predictive regressions with parameter learning pp. 1955-1972

Markus Leippold and Hanlin Yang

Forecasting intraday financial time series with sieve bootstrapping and dynamic updating pp. 1973-1988

Han Lin Shang and Kaiying Ji

Forecasting global solar radiation using a robust regularization approach with mixture kernels pp. 1989-2010

He Jiang

Analyzing and forecasting electricity price using regime‐switching models: The case of New Zealand market pp. 2011-2026

Gaurav Kapoor, Nuttanan Wichitaksorn and Wenjun Zhang

Uncertainty analysis–forecasting system based on decomposition–ensemble framework for PM2.5 concentration forecasting in China pp. 2027-2044

Zongxi Qu, Xiaogang Hao, Fazhen Zhao and Chunhua Niu

Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling pp. 2045-2062

Ali Taiebnia and Shapour Mohammadi

Variable selection for classification and forecasting of the family firm's socioemotional wealth pp. 2063-2078

Susana Álvarez‐Díez, J. Samuel Baixauli‐Soler, María Belda‐Ruiz and Gregorio Sánchez‐Marín

The benefit of the Covid‐19 pandemic on global temperature projections pp. 2079-2098

Pierre Rostan and Alexandra Rostan

Deep learning on mixed frequency data pp. 2099-2120

Qifa Xu, Zezhou Wang, Cuixia Jiang and Yezheng Liu

Daily tourism forecasting through a novel method based on principal component analysis, grey wolf optimizer, and extreme learning machine pp. 2121-2138

Chuan Zhang, Ao‐Yun Hu and Yu‐Xin Tian

Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises pp. 2139-2166

Maziar Sahamkhadam and Andreas Stephan

Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity pp. 2167-2196

Xingyu Dai, Dongna Zhang, Chi Keung Lau and Qunwei Wang

Regularized Poisson regressions predict regional innovation output pp. 2197-2216

Li Xiang, Hu Xuemei and Yang Junwen

Large covariance estimation using a factor model with common and group‐specific factors pp. 2217-2248

Shi Yafeng, Ai Chunrong, Yanlong Shi, Ying Tingting and Xu Qunfang

Optimal out‐of‐sample forecast evaluation under stationarity pp. 2249-2279

Filip Staněk

The battle of the factors: Macroeconomic variables or investor sentiment? pp. 2280-2291

David A. Mascio, Marat Molyboga and Frank J. Fabozzi

Time‐varying partial‐directed coherence approach to forecast global energy prices with stochastic volatility model pp. 2292-2306

Zouhaier Dhifaoui, Sami Ben Jabeur, Rabeh Khalfaoui and Muhammad Ali Nasir

Policy uncertainty and stock market volatility revisited: The predictive role of signal quality pp. 2307-2321

Afees Salisu, Riza Demirer and Rangan Gupta

Forecasting the different influencing factors of household food waste behavior in China under the COVID‐19 pandemic pp. 2322-2340

Xiangdong Shen, Junbin Wang, Li Wang and Chunlan Jiao

Forecasting base metal prices with exchange rate expectations pp. 2341-2362

Pablo Pincheira and Nicolas Hardy

Volume 42, issue 7, 2023

Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model pp. 1539-1559

Bumho Son, Yunyoung Lee, Seongwan Park and Jaewook Lee

Assessing components of uncertainty in demographic forecasts with an application to fiscal sustainability pp. 1560-1568

Juha Alho and Jukka Lassila

Nowcasting the state of the Italian economy: The role of financial markets pp. 1569-1593

Donato Ceci and Andrea Silvestrini

Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators pp. 1594-1621

Tianlun Fei, Xiaoquan Liu and Conghua Wen

Forecasting stock volatility with a large set of predictors: A new forecast combination method pp. 1622-1647

Xue Gong, Weiguo Zhang, Yuan Zhao and Xin Ye

Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach pp. 1648-1663

Giuseppe Storti and Chao Wang

Forecasting nonperforming loans using machine learning pp. 1664-1689

Mohammad Abdullah, Mohammad Ashraful Chowdhury, Ajim Uddin and Syed Moudud‐Ul‐Huq

The ENSO cycle and forecastability of global inflation and output growth: Evidence from standard and mixed‐frequency multivariate singular spectrum analyses pp. 1690-1707

Mohammad Reza Yeganegi, Hossein Hassani and Rangan Gupta

A review of artificial intelligence quality in forecasting asset prices pp. 1708-1728

Flavio Barboza, Geraldo Nunes Silva and José Augusto Fiorucci

A hybrid forecasting model based on deep learning feature extraction and statistical arbitrage methods for stock trading strategies pp. 1729-1749

Weiqian Zhang, Songsong Li, Zhichang Guo and Yizhe Yang

Electricity price forecasting using hybrid deep learned networks pp. 1750-1771

Krishna Prakash N. and Jai Govind Singh

Yield spread selection in predicting recession probabilities pp. 1772-1785

Jaehyuk Choi, Desheng Ge, Kyu Ho Kang and Sungbin Sohn

Default return spread: A powerful predictor of crude oil price returns pp. 1786-1804

Qingxiang Han, Mengxi He, Yaojie Zhang and Muhammad Umar

Forecasting the stock risk premium: A new statistical constraint pp. 1805-1822

Xianfeng Hao and Yudong Wang

Effective multi‐step ahead container throughput forecasting under the complex context pp. 1823-1843

Yi Xiao, Minghu Xie, Yi Hu and Ming Yi

On bootstrapping tests of equal forecast accuracy for nested models pp. 1844-1864

Firmin Doko Tchatoka and Qazi Haque

Comprehensive commodity price forecasting framework using text mining methods pp. 1865-1888

Wuyue An, Lin Wang and Dongfeng Zhang

Optimal forecasts in the presence of discrete structural breaks under long memory pp. 1889-1908

Mwasi Paza Mboya and Philipp Sibbertsen

Forecasting realized volatility of Bitcoin: The informative role of price duration pp. 1909-1929

Skander Slim, Ibrahim Tabche, Yosra Koubaa, Mohamed Osman and Andreas Karathanasopoulos

Forecasting nonstationary time series pp. 1930-1949

Lukasz T. Gatarek and Aleksander Welfe

Volume 42, issue 5, 2023

A new model for forecasting VaR and ES using intraday returns aggregation pp. 1039-1054

Shijia Song and Handong Li

Dynamic forecasting for nonstationary high‐frequency financial data with jumps based on series decomposition and reconstruction pp. 1055-1068

Yuping Song, Zhenwei Li, Zhiren Ma and Xiaoyu Sun

Reference class selection in similarity‐based forecasting of corporate sales growth pp. 1069-1085

Etienne Theising, Dominik Wied and Daniel Ziggel

Risk‐neutral moments and return predictability: International evidence pp. 1086-1111

Junyu Zhang, Xinfeng Ruan and Jin E. Zhang

Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach pp. 1112-1137

Jiaming Liu, Chengzhang Li, Peng Ouyang, Jiajia Liu and Chong Wu

A hybrid prediction model with time‐varying gain tracking differentiator in Taylor expansion: Evidence from precious metals pp. 1138-1149

Zhidan Luo, Wei Guo, Qingfu Liu and Yiuman Tse

Early prediction of Ibex 35 movements pp. 1150-1166

I. Marta Miranda García, María‐Jesús Segovia‐Vargas, Usue Mori and José A. Lozano

Multiclass financial distress prediction based on one‐versus‐one decomposition integrated with improved decision‐directed acyclic graph pp. 1167-1186

Jie Sun, Jie Li, Hamido Fujita and Wenguo Ai

Forecasting financial markets with semantic network analysis in the COVID‐19 crisis pp. 1187-1204

Andrea Fronzetti Colladon, Stefano Grassi, Francesco Ravazzolo and Francesco Violante

Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap pp. 1205-1227

Albert Tsui, Junxiang Wu, Zhaoyong Zhang and Zhongxi Zheng

An investigation into the probability that this is the last year of the economic expansion pp. 1228-1244

Manfred Keil, Edward Leamer and Yao Li

A deep learning model for online doctor rating prediction pp. 1245-1260

Anurag Kulshrestha, Venkataraghavan Krishnaswamy and Mayank Sharma

Forecasting air quality index considering socioeconomic indicators and meteorological factors: A data granularity perspective pp. 1261-1274

Chih‐Hsuan Wang and Chia‐Rong Chang

Does herding effect help forecast market volatility?—Evidence from the Chinese stock market pp. 1275-1290

Yide Wang, Chao Yu and Xujie Zhao

Volume 42, issue 4, 2023

An evolutionary cost‐sensitive support vector machine for carbon price trend forecasting pp. 741-755

Bangzhu Zhu, Jingyi Zhang, Chunzhuo Wan, Julien Chevallier and Ping Wang

A dynamic performance evaluation of distress prediction models pp. 756-784

Mohammad Mahdi Mousavi, Jamal Ouenniche and Kaoru Tone

El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach pp. 785-801

Matteo Bonato, Oguzhan Cepni, Rangan Gupta and Christian Pierdzioch

A new recurrent pi‐sigma artificial neural network inspired by exponential smoothing feedback mechanism pp. 802-812

Eren Bas and Erol Eğrioğlu

Extensions of the Lee–Carter model to project the data‐driven rotation of age‐specific mortality decline and forecast coherent mortality rates pp. 813-834

Cuixia Liu and Yanlin Shi

Semiparametric estimation of expected shortfall and its application in finance pp. 835-851

Yan Fang, Jian Li, Yinglin Liu and Yunfan Zhao

Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage pp. 852-871

Mingzhe Wei, Georgios Sermpinis and Charalampos Stasinakis

Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting pp. 872-904

Tong Fang, Deyu Miao, Zhi Su and Libo Yin

Using shapely values to define subgroups of forecasts for combining pp. 905-923

Zhenni Ding, Huayou Chen and Ligang Zhou

A review of scenario planning for emissions in environmental assessments pp. 924-936

Venmathy Samanaseh, Zainura Zainon Noor, Siti Norasyiqin, Che Hafizan, Muhammad Amani Mazlan and Florianna Lendai Michael

Uncertainties and disagreements in expectations of professional forecasters: Evidence from an inflation targeting developing country pp. 937-956

Gabriel Montes and Igor Mendes Marcelino

Electricity demand forecasting and risk management using Gaussian process model with error propagation pp. 957-969

Kuangyu Wen, Wenbin Wu and Ximing Wu

Which factors drive Bitcoin volatility: Macroeconomic, technical, or both? pp. 970-988

Jiqian Wang, Feng Ma, Elie Bouri and Yangli Guo

A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies pp. 989-1007

Carlos Trucíos and James W. Taylor

A retrospective analysis of Journal of Forecasting: From 1982 to 2019 pp. 1008-1035

Dejian Yu, Libo Sheng and Shunshun Shi

Volume 42, issue 3, 2023

Advances in forecasting: An introduction in light of the debate on inflation forecasting pp. 455-463

Anindya Banerjee, Stephen Hall, Georgios Kouretas and George Tavlas

Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data pp. 464-480

Tesi Aliaj, Milos Ciganovic and Massimiliano Tancioni

Forecasting inflation in open economies: What can a NOEM model do? pp. 481-513

Roberto Duncan and Enrique Martínez‐García

Forecasting inflation: The use of dynamic factor analysis and nonlinear combinations pp. 514-529

Stephen Hall, George Tavlas and Yongli Wang

Evaluation and indirect inference estimation of inattentive features in a New Keynesian framework pp. 530-542

Jenyu Chou, Yifei Cao and A. Patrick Minford

Forecasting housing investment pp. 543-565

Carlos Cañizares Martínez, Gabe de Bondt and Arne Gieseck

Assessing the informational content of card transactions for nowcasting retail trade: Evidence for Latvia pp. 566-577

Anete Brinke, Ludmila Fadejeva, Boriss Siliverstovs and Karlis Vilerts

Jump forecasting in foreign exchange markets: A high‐frequency analysis pp. 578-624

Sevcan Uzun, Ahmet Sensoy and Duc Khuong Nguyen

The role of expectations for currency crisis dynamics—The case of the Turkish lira pp. 625-642

Joscha Beckmann and Robert Czudaj

The effects of shocks to interest rate expectations in the euro area: Estimates at the country level pp. 643-656

Martin Mandler and Michael Scharnagl

Forecasting sovereign risk in the Euro area via machine learning pp. 657-684

Guillaume Belly, Lukas Boeckelmann, Carlos Mateo Caicedo Graciano, Alberto Di Iorio, Klodiana Istrefi, Vasileios Siakoulis and Arthur Stalla‐Bourdillon

Worse than you think: Public debt forecast errors in advanced and developing economies pp. 685-714

Julia Estefania‐Flores, Davide Furceri, Siddharth Kothari and Jonathan Ostry

Macro‐financial effects of monetary policy easing pp. 715-738

George Apostolakis, Nikolaos Giannellis and Athanasios Papadopoulos

Volume 42, issue 2, 2023

Robust forecasting in spatial autoregressive model with total variation regularization pp. 195-211

He Jiang

Trading cryptocurrencies using algorithmic average true range systems pp. 212-222

Gil Cohen

Structural and predictive analyses with a mixed copula‐based vector autoregression model pp. 223-239

Woraphon Yamaka, Rangan Gupta, Sukrit Thongkairat and Paravee Maneejuk

Nonlinear inflation forecasting with recurrent neural networks pp. 240-259

Anna Almosova and Niek Andresen

Combined water quality forecasting system based on multiobjective optimization and improved data decomposition integration strategy pp. 260-287

Yuqi Dong, Jianzhou Wang, Xinsong Niu and Bo Zeng

The effect of environment on housing prices: Evidence from the Google Street View pp. 288-311

Guan‐Yuan Wang

Text‐based soybean futures price forecasting: A two‐stage deep learning approach pp. 312-330

Wuyue An, Lin Wang and Yu‐Rong Zeng

Forecasting inflation and output growth with credit‐card‐augmented Divisia monetary aggregates pp. 331-346

William Barnett and Sohee Park

Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations pp. 347-368

Tamas Kiss, Stepan Mazur, Hoang Nguyen and Pär Österholm

Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil pp. 369-401

Carlos Henrique Dias Cordeiro de Castro and Fernando Antonio Aiube

Application of machine learning techniques to predict entrepreneurial firm valuation pp. 402-417

Ruling Zhang, Zengrui Tian, Killian J. McCarthy, Xiao Wang and Kun Zhang

Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs pp. 418-451

Chenghan Hou, Bao Nguyen and Bo Zhang

Volume 42, issue 1, 2023

Geopolitical risk and global financial cycle: Some forecasting experiments pp. 3-16

Afees Salisu, Philip C. Omoke and Sikiru Abdulsalam

Forecasting energy prices: Quantile‐based risk models pp. 17-33

Nicholas Apergis

Estimation of short‐run predictive factor for US growth using state employment data pp. 34-50

Arabinda Basistha

Volatility forecasting for stock market incorporating macroeconomic variables based on GARCH‐MIDAS and deep learning models pp. 51-59

Yuping Song, Xiaolong Tang, Hemin Wang and Zhiren Ma

A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information pp. 60-75

Feng Ma, M. I. M. Wahab, Julien Chevallier and Ziyang Li

Trading volume and realized volatility forecasting: Evidence from the China stock market pp. 76-100

Min Liu, Wei‐Chong Choo, Chi‐Chuan Lee and Chien‐Chiang Lee

Wind power prediction based on wind speed forecast using hidden Markov model pp. 101-123

Khatereh Ghasvarian Jahromi, Davood Gharavian and Hamid Reza Mahdiani

Power grid operation optimization and forecasting using a combined forecasting system pp. 124-153

Lifang Zhang, Jianzhou Wang and Zhenkun Liu

A new PM2.5 concentration forecasting system based on AdaBoost‐ensemble system with deep learning approach pp. 154-175

Zhongfei Li, Kai Gan, Shaolong Sun and Shouyang Wang

A hybrid approach with step‐size aggregation to forecasting hierarchical time series pp. 176-192

Hakeem‐Ur Rehman, Guohua Wan and Raza Rafique