Journal of Forecasting
1987 - 2025
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 (contentdelivery@wiley.com). Access Statistics for this journal.
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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 E. 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
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