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 39, issue 8, 2020

Modeling of frequency containment reserve prices with econometrics and artificial intelligence pp. 1179-1197

Emil Kraft, Dogan Keles and Wolf Fichtner

Predictive models for influence of primary delays using high‐speed train operation records pp. 1198-1212

Zhongcan Li, Ping Huang, Chao Wen, Yixiong Tang and Xi Jiang

Analysis of the relationship between LSTM network traffic flow prediction performance and statistical characteristics of standard and nonstandard data pp. 1213-1228

Erdem Doğan

Stock index prediction based on wavelet transform and FCD‐MLGRU pp. 1229-1237

Xiaojun Li and Pan Tang

Financial distress prediction model: The effects of corporate governance indicators pp. 1238-1252

Chih‐Chun Chen, Chun‐Da Chen and Donald Lien

Is implied volatility more informative for forecasting realized volatility: An international perspective pp. 1253-1276

Chao Liang, Yu Wei and Yaojie Zhang

Cryptocurrency volatility forecasting: A Markov regime‐switching MIDAS approach pp. 1277-1290

Feng Ma, Chao Liang, Yuanhui Ma and M.I.M. Wahab

A large Bayesian VAR with a block‐specific shrinkage: A forecasting application for Italian industrial production pp. 1291-1304

Valentina Aprigliano

Predictive modeling of consumer color preference: Using retail data and merchandise images pp. 1305-1323

Songtao Li, Ruoran Chen, Lijian Yang, Dinglong Huang and Simin Huang

A hybrid model considering cointegration for interval‐valued pork price forecasting in China pp. 1324-1341

Dabin Zhang, Qian Li, Amin Mugera and Liwen Ling

Volume 39, issue 7, 2020

Professional forecasters' expectations, consistency, and international spillovers pp. 1001-1024

Joscha Beckmann and Robert Czudaj

A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility pp. 1025-1034

Yafeng Shi, Tingting Ying, Yanlong Shi and Chunrong Ai

Moving average threshold heterogeneous autoregressive (MAT‐HAR) models pp. 1035-1042

Kaiji Motegi, Xiaojing Cai, Shigeyuki Hamori and Haifeng Xu

Forecasting models in the manufacturing processes and operations management: Systematic literature review pp. 1043-1056

Icaro Romolo Sousa Agostino, Wesley Vieira da Silva, Claudimar Pereira da Veiga and Adriano Mendonça Souza

Using the yield curve to forecast economic growth pp. 1057-1080

Parley Ruogu Yang

On the forecasting of high‐frequency financial time series based on ARIMA model improved by deep learning pp. 1081-1097

Zhenwei Li, Jing Han and Yuping Song

Forecasting Australia's real house price index: A comparison of time series and machine learning methods pp. 1098-1118

George Milunovich

A detailed look at crude oil price volatility prediction using macroeconomic variables pp. 1119-1141

Nima Nonejad

Sparse Bayesian vector autoregressions in huge dimensions pp. 1142-1165

Gregor Kastner and Florian Huber

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR pp. 1166-1178

Zhenni Jin, Kun Guo, Yi Sun, Lin Lai and Zhewen Liao

Volume 39, issue 6, 2020

Cholesky–ANN models for predicting multivariate realized volatility pp. 865-876

Andrea Bucci

Optimal forecast combination based on ensemble empirical mode decomposition for agricultural commodity futures prices pp. 877-886

Yongmei Fang, Bo Guan, Shangjuan Wu and Saeed Heravi

Do credit booms predict US recessions? pp. 887-910

Marius M. Mihai

A multi‐country dynamic factor model with stochastic volatility for euro area business cycle analysis pp. 911-926

Florian Huber, Michael Pfarrhofer and Philipp Piribauer

Correcting the January optimism effect pp. 927-933

Philip Hans Franses

Efficient selection of hyperparameters in large Bayesian VARs using automatic differentiation pp. 934-943

Joshua Chan, Liana Jacobi and Dan Zhu

Assessment of agricultural energy consumption of Turkey by MLR and Bayesian optimized SVR and GPR models pp. 944-956

Zeynep Ceylan

The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles pp. 957-965

Elie Bouri, Riza Demirer, Rangan Gupta and Xiaojin Sun

Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages pp. 966-985

Oguzhan Cepni, Rangan Gupta, I. Ethem Güney and M. Yilmaz

A deep residual compensation extreme learning machine and applications pp. 986-999

Yinghao Chen, Xiaoliang Xie, Tianle Zhang, Jiaxian Bai and Muzhou Hou

Volume 39, issue 5, 2020

Forecasting with unbalanced panel data pp. 709-724

Badi Baltagi and Long Liu

Shift‐contagion in energy markets and global crisis pp. 725-736

Mehdi Mili, Jean‐Michel Sahut and Frédéric Teulon

A generalized regression model based on hybrid empirical mode decomposition and support vector regression with back‐propagation neural network for mid‐short‐term load forecasting pp. 737-756

Guo‐Feng Fan, Yan‐Hui Guo, Jia‐Mei Zheng and Wei‐Chiang Hong

Timescale classification in wind forecasting: A review of the state‐of‐the‐art pp. 757-768

Jannik Schütz Roungkvist and Peter Enevoldsen

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods pp. 769-787

Xiaobo Tang, Shixuan Li, Mingliang Tan and Wenxuan Shi

Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms pp. 788-796

David Gabauer

Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects pp. 797-810

Lu Wang, Feng Ma and Guoshan Liu

On long memory origins and forecast horizons pp. 811-826

J. Eduardo Vera‐Valdés

Identifying US business cycle regimes using dynamic factors and neural network models pp. 827-840

Barış Soybilgen

Model averaging estimation for conditional volatility models with an application to stock market volatility forecast pp. 841-863

Qingfeng Liu, Qingsong Yao and Guoqing Zhao

Volume 39, issue 4, 2020

Forecasting interest rates through Vasicek and CIR models: A partitioning approach pp. 569-579

Giuseppe Orlando, Rosa Maria Mininni and Michele Bufalo

Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation pp. 580-598

Constandina Koki, Loukia Meligkotsidou and Ioannis Vrontos

On the predictability of crude oil market: A hybrid multiscale wavelet approach pp. 599-614

Stelios Bekiros, Jose Arreola Hernandez, Gazi Uddin and Ahmed Taneem Muzaffar

Spatial dependence model with feature difference pp. 615-627

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

Combining multivariate volatility forecasts using weighted losses pp. 628-641

Adam Clements and Mark Bernard Doolan

Short‐run wavelet‐based covariance regimes for applied portfolio management pp. 642-660

Theo Berger and Ramazan Gencay

Diagnosis of diabetes mellitus using artificial neural network and classification and regression tree optimized with genetic algorithm pp. 661-670

Ebru Pekel Özmen and Tuncay Özcan

Can online search data improve the forecast accuracy of pork price in China? pp. 671-686

Liwen Ling, Dabin Zhang, Shanying Chen and Amin W. Mugera

Evaluation of the going‐concern status for companies: An ensemble framework‐based model pp. 687-706

Yu‐Feng Hsu and Wei‐Po Lee

Volume 39, issue 3, 2020

The wavelet scaling approach to forecasting: Verification on a large set of Noisy data pp. 353-367

Joanna Bruzda

Do monetary policy transparency and central bank communication reduce interest rate disagreement? pp. 368-393

Ruttachai Seelajaroen, Pornanong Budsaratragoon and Boonlert Jitmaneeroj

Short‐term forecasting of the US unemployment rate pp. 394-411

Benedikt Maas

Revealing forecaster's preferences: A Bayesian multivariate loss function approach pp. 412-437

Emmanuel Mamatzakis and Mike Tsionas

State‐space models for predicting IBNR reserve in row‐wise ordered runoff triangles: Calendar year IBNR reserves & tail effects pp. 438-448

Leonardo Costa and Adrian Pizzinga

On the directional predictability of equity premium using machine learning techniques pp. 449-469

Jonathan Iworiso and Spyridon Vrontos

A predictive model of train delays on a railway line pp. 470-488

Chao Wen, Weiwei Mou, Ping Huang and Zhongcan Li

Regression tree model for prediction of demand with heterogeneity and censorship pp. 489-500

Evgeniy M. Ozhegov and Alina Ozhegova

Real time prediction of irregular periodic time series data pp. 501-511

Kaimeng Zhang, Chi Tim Ng and Myung Hwan Na

Forecasting of dependence, market, and investment risks of a global index portfolio pp. 512-532

Jose Arreola Hernandez and Mazin A.M. Al Janabi

The impact of economic growth in mortality modelling for selected OECD countries pp. 533-550

Lydia Dutton, Athanasios A. Pantelous and Malgorzata Seklecka

Gaussian processes for daily demand prediction in tourism planning pp. 551-568

Wai Kit Tsang and Dries F. Benoit

Volume 39, issue 2, 2020

Forecasting air pollution PM2.5 in Beijing using weather data and multiple kernel learning pp. 117-125

Xiang Xu

Modeling and forecasting commodity market volatility with long‐term economic and financial variables pp. 126-142

Duc Khuong Nguyen and Thomas Walther

Volatility forecasts using stochastic volatility models with nonlinear leverage effects pp. 143-154

Kenichiro McAlinn, Asahi Ushio and Teruo Nakatsuma

Volatility forecasting with bivariate multifractal models pp. 155-167

Ruipeng Liu, Riza Demirer, Rangan Gupta and Mark Wohar

Model instability in predictive exchange rate regressions pp. 168-186

Niko Hauzenberger and Florian Huber

A simple parameter‐driven binary time series model pp. 187-199

Yang Lu

Predictive ability and economic gains from volatility forecast combinations pp. 200-219

Stavroula P. Fameliti and Vasiliki Skintzi

Financial market imperfections and profitability: New evidence from a large panel of US SME firms pp. 220-241

Nicholas Apergis

Forecasting of electricity price through a functional prediction of sale and purchase curves pp. 242-259

Ismail Shah and Francesco Lisi

Predicting loan default in peer‐to‐peer lending using narrative data pp. 260-280

Yufei Xia, Lingyun He, Yinguo Li, Nana Liu and Yanlin Ding

Filtering and prediction of noisy and unstable signals: The case of Google Trends data pp. 281-295

Livio Fenga

On the use of power transformations in CAViaR models pp. 296-312

Georgios Tsiotas

Predicting exchange rates in Asia: New insights on the accuracy of survey forecasts pp. 313-333

Frederik Kunze

Evaluation of current research on stock return predictability pp. 334-351

Erhard Reschenhofer, Manveer Kaur Mangat, Christian Zwatz and Sándor Guzmics

Volume 39, issue 1, 2020

Evaluating early warning and coincident indicators of business cycles using smooth trends pp. 1-17

Marcos Bujosa, Antonio García‐Ferrer, Aránzazu de Juan and Antonio Martín‐Arroyo

Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors pp. 18-36

Oguzhan Cepni, I. Ethem Guney and Norman Swanson

Forecasting inflation using univariate continuous‐time stochastic models pp. 37-46

Kevin Fergusson

A likelihood ratio and Markov chain‐based method to evaluate density forecasting pp. 47-55

Yushu Li and Jonas Andersson

A novel forecasting model for the Baltic dry index utilizing optimal squeezing pp. 56-68

Spyros Makridakis, Andreas Merikas, Anna Merika, Mike Tsionas and Marwan Izzeldin

A new approach to forecasting intermittent demand based on the mixed zero‐truncated Poisson model pp. 69-83

Aiping Jiang, Kwok Leung Tam, Xiaoyun Guo and Yufeng Zhang

The dynamic effect of macroeconomic news on the euro/US dollar exchange rate pp. 84-103

Walid Ben Omrane, Robert Welch and Xinyao Zhou

Using social media mining technology to improve stock price forecast accuracy pp. 104-116

Jia‐Yen Huang and Jin‐Hao Liu