Journal of Forecasting
1987 - 2023
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.
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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 K. 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, Oğuzhan Çepni, 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 Caldas 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 P. 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 Lucena 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 Abdulsalam Abidemi Sikiru
- 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
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