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September 2024, Volume 43, Issue 6
- 1733-1746 Forecasting agricultures security indices: Evidence from transformers method
by Ammouri Bilel - 1747-1769 Liquidity‐adjusted value‐at‐risk using extreme value theory and copula approach
by Harish Kamal & Samit Paul - 1770-1794 Return predictability via an long short‐term memory‐based cross‐section factor model: Evidence from Chinese stock market
by Haixiang Yao & Shenghao Xia & Hao Liu - 1795-1813 Forecasting Consumer Price Index with Federal Open Market Committee Sentiment Index
by Joshua Eklund & Jong‐Min Kim - 1814-1834 Forecasting elections from partial information using a Bayesian model for a multinomial sequence of data
by Soudeep Deb & Rishideep Roy & Shubhabrata Das - 1835-1858 Correlation‐based tests of predictability
by Pablo Pincheira Brown & Nicolás Hardy - 1859-1879 Electricity price forecasting using quantile regression averaging with nonconvex regularization
by He Jiang & Yao Dong & Jianzhou Wang - 1880-1901 Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes
by Tomas Pečiulis & Nisar Ahmad & Angeliki N. Menegaki & Aqsa Bibi - 1902-1917 Forecasting peak electric load: Robust support vector regression with smooth nonconvex ϵ‐insensitive loss
by Rujia Nie & Jinxing Che & Fang Yuan & Weihua Zhao - 1918-1935 Forecasting regional industrial production with novel high‐frequency electricity consumption data
by Robert Lehmann & Sascha Möhrle - 1936-1955 Vine copula‐based scenario tree generation approaches for portfolio optimization
by Xiaolei He & Weiguo Zhang - 1956-1974 Can intraday data improve the joint estimation and prediction of risk measures? Evidence from a variety of realized measures
by Zhimin Wu & Guanghui Cai - 1975-1981 Disciplining growth‐at‐risk models with survey of professional forecasters and Bayesian quantile regression
by Milan Szabo - 1982-1997 Well googled is half done: Multimodal forecasting of new fashion product sales with image‐based google trends
by Geri Skenderi & Christian Joppi & Matteo Denitto & Marco Cristani - 1998-2020 An ensemble model for stock index prediction based on media attention and emotional causal inference
by Juanjuan Wang & Shujie Zhou & Wentong Liu & Lin Jiang - 2021-2041 New runs‐based approach to testing value at risk forecasts
by Marta Małecka - 2042-2063 Text‐based corn futures price forecasting using improved neural basis expansion network
by Lin Wang & Wuyue An & Feng‐Ting Li - 2064-2087 Explainable machine learning techniques based on attention gate recurrent unit and local interpretable model‐agnostic explanations for multivariate wind speed forecasting
by Lu Peng & Sheng‐Xiang Lv & Lin Wang - 2088-2125 Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?
by Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch - 2126-2145 Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian vector autoregressions?
by Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner - 2146-2162 The effects of governance quality on renewable and nonrenewable energy consumption: An explainable decision frame
by Futian Weng & Dongsheng Cheng & Muni Zhuang & Xin Lu & Cai Yang - 2163-2186 Predicting tail risks by a Markov switching MGARCH model with varying copula regimes
by Markus J. Fülle & Helmut Herwartz - 2187-2211 An infinite hidden Markov model with stochastic volatility
by Chenxing Li & John M. Maheu & Qiao Yang - 2212-2227 Constructing a high‐frequency World Economic Gauge using a mixed‐frequency dynamic factor model
by Chew Lian Chua & Sarantis Tsiaplias & Ruining Zhou - 2228-2256 Forecasting carbon emissions using asymmetric grouping
by Didier Nibbering & Richard Paap - 2257-2278 Performance and reporting predictability of hedge funds
by Elisa Becker‐Foss - 2279-2297 A systematic vector autoregressive framework for modeling and forecasting mortality
by Jackie Li & Jia Liu & Adam Butt - 2298-2321 The mean squared prediction error paradox
by Pablo Pincheira Brown & Nicolás Hardy - 2322-2340 Bayesian Markov switching model for BRICS currencies' exchange rates
by Utkarsh Kumar & Wasim Ahmad & Gazi Salah Uddin - 2341-2357 Are national or regional surveys useful for nowcasting regional jobseekers? The case of the French region of Pays‐de‐la‐Loire
by Clément Cariou & Amélie Charles & Olivier Darné - 2358-2377 Forecasting healthcare service volumes with machine learning algorithms
by Dong‐Hui Yang & Ke‐Hui Zhu & Ruo‐Nan Wang - 2378-2398 Hybrid forecasting of crude oil volatility index: The cross‐market effects of stock market jumps
by Gongyue Jiang & Gaoxiu Qiao & Lu Wang & Feng Ma
July 2024, Volume 43, Issue 4
- 819-826 Forecasting in turbulent times
by Nikolaos Giannellis & Stephen G. Hall & Georgios P. Kouretas & George S. Tavlas - 827-851 Inflation forecasting with rolling windows: An appraisal
by Stephen G. Hall & George S. Tavlas & Yongli Wang & Deborah Gefang - 852-870 How we missed the inflation surge: An anatomy of post‐2020 inflation forecast errors
by Christoffer Koch & Diaa Noureldin - 871-893 Post‐COVID inflation dynamics: Higher for longer
by Randal Verbrugge & Saeed Zaman - 894-902 Using deep (machine) learning to forecast US inflation in the COVID‐19 era
by David Stoneman & John V. Duca - 903-931 Trust and monetary policy
by Paul De Grauwe & Yuemei Ji - 932-947 An evaluation of the inflation forecasting performance of the European Central Bank, the Federal Reserve, and the Bank of England
by Eleni Argiri & Stephen G. Hall & Angeliki Momtsia & Daphne Marina Papadopoulou & Ifigeneia Skotida & George S. Tavlas & Yongli Wang - 948-982 Combine to compete: Improving fiscal forecast accuracy over time
by Laura Carabotta & Peter Claeys - 983-1017 Forecasting exchange rates: An iterated combination constrained predictor approach
by Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis - 1018-1041 The term structure of interest rates and economic activity: Evidence from the COVID‐19 pandemic
by Evangelos Salachas & Georgios P. Kouretas & Nikiforos T. Laopodis - 1042-1086 Forecasting GDP growth: The economic impact of COVID‐19 pandemic
by Ioannis D. Vrontos & John Galakis & Ekaterini Panopoulou & Spyridon D. Vrontos - 1087-1113 Forecasting food price inflation during global crises
by Patricia Toledo & Roberto Duncan - 1114-1126 Modeling the effects of Brexit on the British economy
by Patrick Minford & Zheyi Zhu
April 2024, Volume 43, Issue 3
- 509-543 A comparison of Range Value at Risk (RVaR) forecasting models
by Fernanda Maria Müller & Thalles Weber Gössling & Samuel Solgon Santos & Marcelo Brutti Righi - 544-566 Volatility forecasting for stock market index based on complex network and hybrid deep learning model
by Yuping Song & Bolin Lei & Xiaolong Tang & Chen Li - 567-582 Out‐of‐sample volatility prediction: Rolling window, expanding window, or both?
by Yuqing Feng & Yaojie Zhang & Yudong Wang - 583-592 A Markov chain model of crop conditions and intrayear crop yield forecasting
by J. R. Stokes - 593-614 Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system
by Yinghua Song & Minzhe Jiang & Shixuan Li & Shengzhe Zhao - 615-643 EWT‐SMOTE to improve default prediction performance in imbalanced data: Analysis of Chinese data
by Ying Zhou & Xia Lin & Guotai Chi & Peng Jin & Mengtong Li - 644-660 RMB exchange rate forecasting using machine learning methods: Can multimodel select powerful predictors?
by Xing Yu & Yanyan Li & Xinxin Wang - 661-672 Forecasting air passenger travel: A case study of Norwegian aviation industry
by Angesh Anupam & Isah A. Lawal - 673-701 Downturns and changes in the yield slope
by Mirko Abbritti & Juan Equiza & Antonio Moreno & Tommaso Trani - 702-753 Forecasting CPI with multisource data: The value of media and internet information
by Tingguo Zheng & Xinyue Fan & Wei Jin & Kuangnan Fang - 754-770 Empirical prediction intervals for additive Holt–Winters methods under misspecification
by Boning Yang & Xinyi Tang & Chun Yip Yau - 771-801 Forecasts with Bayesian vector autoregressions under real time conditions
by Michael Pfarrhofer - 802-815 Forecasting the containerized freight index with AIS data: A novel information combination method based on gray incidence analysis
by Yanhui Chen & Ailing Feng & Shun Chen & Jackson Jinhong Mi
March 2024, Volume 43, Issue 2
- 227-248 Big data financial transactions and GDP nowcasting: The case of Turkey
by Ali B. Barlas & Seda Guler Mert & Berk Orkun Isa & Alvaro Ortiz & Tomasa Rodrigo & Baris Soybilgen & Ege Yazgan - 249-285 Interval time series forecasting: A systematic literature review
by Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen - 286-308 Credit scoring prediction leveraging interpretable ensemble learning
by Yang Liu & Fei Huang & Lili Ma & Qingguo Zeng & Jiale Shi - 309-325 Forecasting the volatility of crude oil futures: A time‐dependent weighted least squares with regularization constraint
by Qianjie Geng & Xianfeng Hao & Yudong Wang - 326-343 Determinants of disagreement: Learning from inflation expectations survey of households
by Gaurav Kumar Singh & Tathagata Bandyopadhyay - 344-365 Prediction of daily tourism volume based on maximum correlation minimum redundancy feature selection and long short‐term memory network
by Ming Yin & Feiya Lu & Xingxuan Zhuo & Wangzi Yao & Jialong Liu & Jijiao Jiang - 366-390 A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price
by Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen - 391-401 A classification application for using learning methods in bank costumer's portfolio churn
by Murat Simsek & Iclal Cetin Tas - 402-414 Forecasting VaR and ES in emerging markets: The role of time‐varying higher moments
by Trung H. Le - 415-428 Intrusion detection system using metaheuristic fireworks optimization based feature selection with deep learning on Internet of Things environment
by T. Jayasankar & R. Kiruba Buri & P. Maheswaravenkatesh - 429-455 Enhancing credit risk prediction based on ensemble tree‐based feature transformation and logistic regression
by Jiaming Liu & Jiajia Liu & Chong Wu & Shouyang Wang - 456-472 Business applications and state‐level stock market realized volatility: A forecasting experiment
by Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch - 473-489 Forecasting tourist flows in the COVID‐19 era using nonparametric mixed‐frequency VARs
by Wanhai You & Yuming Huang & Chien‐Chiang Lee - 490-505 The optimal interval combination prediction model based on vectorial angle cosine and a new aggregation operator for social security level prediction
by Kexin Peng & Chao Kang & Xiwen Ru & Ligang Zhou
December 2023, Volume 42, Issue 8
- 1955-1972 Mixed‐frequency predictive regressions with parameter learning
by Markus Leippold & Hanlin Yang - 1973-1988 Forecasting intraday financial time series with sieve bootstrapping and dynamic updating
by Han Lin Shang & Kaiying Ji - 1989-2010 Forecasting global solar radiation using a robust regularization approach with mixture kernels
by He Jiang - 2011-2026 Analyzing and forecasting electricity price using regime‐switching models: The case of New Zealand market
by Gaurav Kapoor & Nuttanan Wichitaksorn & Wenjun Zhang - 2027-2044 Uncertainty analysis–forecasting system based on decomposition–ensemble framework for PM2.5 concentration forecasting in China
by Zongxi Qu & Xiaogang Hao & Fazhen Zhao & Chunhua Niu - 2045-2062 Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling
by Ali Taiebnia & Shapour Mohammadi - 2063-2078 Variable selection for classification and forecasting of the family firm's socioemotional wealth
by Susana Álvarez‐Díez & J. Samuel Baixauli‐Soler & María Belda‐Ruiz & Gregorio Sánchez‐Marín - 2079-2098 The benefit of the Covid‐19 pandemic on global temperature projections
by Pierre Rostan & Alexandra Rostan - 2099-2120 Deep learning on mixed frequency data
by Qifa Xu & Zezhou Wang & Cuixia Jiang & Yezheng Liu - 2121-2138 Daily tourism forecasting through a novel method based on principal component analysis, grey wolf optimizer, and extreme learning machine
by Chuan Zhang & Ao‐Yun Hu & Yu‐Xin Tian - 2139-2166 Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises
by Maziar Sahamkhadam & Andreas Stephan - 2167-2196 Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity
by Xingyu Dai & Dongna Zhang & Chi Keung Marco Lau & Qunwei Wang - 2197-2216 Regularized Poisson regressions predict regional innovation output
by Li Xiang & Hu Xuemei & Yang Junwen - 2217-2248 Large covariance estimation using a factor model with common and group‐specific factors
by Shi Yafeng & Ai Chunrong & Yanlong Shi & Ying Tingting & Xu Qunfang - 2249-2279 Optimal out‐of‐sample forecast evaluation under stationarity
by Filip Staněk - 2280-2291 The battle of the factors: Macroeconomic variables or investor sentiment?
by David A. Mascio & Marat Molyboga & Frank J. Fabozzi - 2292-2306 Time‐varying partial‐directed coherence approach to forecast global energy prices with stochastic volatility model
by Zouhaier Dhifaoui & Sami Ben Jabeur & Rabeh Khalfaoui & Muhammad Ali Nasir - 2307-2321 Policy uncertainty and stock market volatility revisited: The predictive role of signal quality
by Afees A. Salisu & Riza Demirer & Rangan Gupta - 2322-2340 Forecasting the different influencing factors of household food waste behavior in China under the COVID‐19 pandemic
by Xiangdong Shen & Junbin Wang & Li Wang & Chunlan Jiao - 2341-2362 Forecasting base metal prices with exchange rate expectations
by Pablo Pincheira Brown & Nicolás Hardy
November 2023, Volume 42, Issue 7
- 1539-1559 Forecasting global stock market volatility: The impact of volatility spillover index in spatial‐temporal graph‐based model
by Bumho Son & Yunyoung Lee & Seongwan Park & Jaewook Lee - 1560-1568 Assessing components of uncertainty in demographic forecasts with an application to fiscal sustainability
by Juha Alho & Jukka Lassila - 1569-1593 Nowcasting the state of the Italian economy: The role of financial markets
by Donato Ceci & Andrea Silvestrini - 1594-1621 Forecasting stock return volatility: Realized volatility‐type or duration‐based estimators
by Tianlun Fei & Xiaoquan Liu & Conghua Wen - 1622-1647 Forecasting stock volatility with a large set of predictors: A new forecast combination method
by Xue Gong & Weiguo Zhang & Yuan Zhao & Xin Ye - 1648-1663 Modeling uncertainty in financial tail risk: A forecast combination and weighted quantile approach
by Giuseppe Storti & Chao Wang - 1664-1689 Forecasting nonperforming loans using machine learning
by Mohammad Abdullah & Mohammad Ashraful Ferdous Chowdhury & Ajim Uddin & Syed Moudud‐Ul‐Huq - 1690-1707 The ENSO cycle and forecastability of global inflation and output growth: Evidence from standard and mixed‐frequency multivariate singular spectrum analyses
by Mohammad Reza Yeganegi & Hossein Hassani & Rangan Gupta - 1708-1728 A review of artificial intelligence quality in forecasting asset prices
by Flavio Barboza & Geraldo Nunes Silva & José Augusto Fiorucci - 1729-1749 A hybrid forecasting model based on deep learning feature extraction and statistical arbitrage methods for stock trading strategies
by Weiqian Zhang & Songsong Li & Zhichang Guo & Yizhe Yang - 1750-1771 Electricity price forecasting using hybrid deep learned networks
by Krishna Prakash N. & Jai Govind Singh - 1772-1785 Yield spread selection in predicting recession probabilities
by Jaehyuk Choi & Desheng Ge & Kyu Ho Kang & Sungbin Sohn - 1786-1804 Default return spread: A powerful predictor of crude oil price returns
by Qingxiang Han & Mengxi He & Yaojie Zhang & Muhammad Umar - 1805-1822 Forecasting the stock risk premium: A new statistical constraint
by Xianfeng Hao & Yudong Wang - 1823-1843 Effective multi‐step ahead container throughput forecasting under the complex context
by Yi Xiao & Minghu Xie & Yi Hu & Ming Yi - 1844-1864 On bootstrapping tests of equal forecast accuracy for nested models
by Firmin Doko Tchatoka & Qazi Haque - 1865-1888 Comprehensive commodity price forecasting framework using text mining methods
by Wuyue An & Lin Wang & Dongfeng Zhang - 1889-1908 Optimal forecasts in the presence of discrete structural breaks under long memory
by Mwasi Paza Mboya & Philipp Sibbertsen - 1909-1929 Forecasting realized volatility of Bitcoin: The informative role of price duration
by Skander Slim & Ibrahim Tabche & Yosra Koubaa & Mohamed Osman & Andreas Karathanasopoulos - 1930-1949 Forecasting nonstationary time series
by Lukasz T. Gatarek & Aleksander Welfe
August 2023, Volume 42, Issue 5
- 1039-1054 A new model for forecasting VaR and ES using intraday returns aggregation
by Shijia Song & Handong Li - 1055-1068 Dynamic forecasting for nonstationary high‐frequency financial data with jumps based on series decomposition and reconstruction
by Yuping Song & Zhenwei Li & Zhiren Ma & Xiaoyu Sun - 1069-1085 Reference class selection in similarity‐based forecasting of corporate sales growth
by Etienne Theising & Dominik Wied & Daniel Ziggel - 1086-1111 Risk‐neutral moments and return predictability: International evidence
by Junyu Zhang & Xinfeng Ruan & Jin E. Zhang - 1112-1137 Interpreting the prediction results of the tree‐based gradient boosting models for financial distress prediction with an explainable machine learning approach
by Jiaming Liu & Chengzhang Li & Peng Ouyang & Jiajia Liu & Chong Wu - 1138-1149 A hybrid prediction model with time‐varying gain tracking differentiator in Taylor expansion: Evidence from precious metals
by Zhidan Luo & Wei Guo & Qingfu Liu & Yiuman Tse - 1150-1166 Early prediction of Ibex 35 movements
by I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano - 1167-1186 Multiclass financial distress prediction based on one‐versus‐one decomposition integrated with improved decision‐directed acyclic graph
by Jie Sun & Jie Li & Hamido Fujita & Wenguo Ai - 1187-1204 Forecasting financial markets with semantic network analysis in the COVID‐19 crisis
by Andrea Fronzetti Colladon & Stefano Grassi & Francesco Ravazzolo & Francesco Violante - 1205-1227 Forecasting term structure of the Japanese bond yields in the presence of a liquidity trap
by Albert K. Tsui & Junxiang Wu & Zhaoyong Zhang & Zhongxi Zheng - 1228-1244 An investigation into the probability that this is the last year of the economic expansion
by Manfred Keil & Edward Leamer & Yao Li - 1245-1260 A deep learning model for online doctor rating prediction
by Anurag Kulshrestha & Venkataraghavan Krishnaswamy & Mayank Sharma - 1261-1274 Forecasting air quality index considering socioeconomic indicators and meteorological factors: A data granularity perspective
by Chih‐Hsuan Wang & Chia‐Rong Chang - 1275-1290 Does herding effect help forecast market volatility?—Evidence from the Chinese stock market
by Yide Wang & Chao Yu & Xujie Zhao
July 2023, Volume 42, Issue 4
- 741-755 An evolutionary cost‐sensitive support vector machine for carbon price trend forecasting
by Bangzhu Zhu & Jingyi Zhang & Chunzhuo Wan & Julien Chevallier & Ping Wang - 756-784 A dynamic performance evaluation of distress prediction models
by Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone - 785-801 El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach
by Matteo Bonato & Oğuzhan Çepni & Rangan Gupta & Christian Pierdzioch - 802-812 A new recurrent pi‐sigma artificial neural network inspired by exponential smoothing feedback mechanism
by Eren Bas & Erol Eğrioğlu - 813-834 Extensions of the Lee–Carter model to project the data‐driven rotation of age‐specific mortality decline and forecast coherent mortality rates
by Cuixia Liu & Yanlin Shi - 835-851 Semiparametric estimation of expected shortfall and its application in finance
by Yan Fang & Jian Li & Yinglin Liu & Yunfan Zhao - 852-871 Forecasting and trading Bitcoin with machine learning techniques and a hybrid volatility/sentiment leverage
by Mingzhe Wei & Georgios Sermpinis & Charalampos Stasinakis - 872-904 Uncertainty‐driven oil volatility risk premium and international stock market volatility forecasting
by Tong Fang & Deyu Miao & Zhi Su & Libo Yin - 905-923 Using shapely values to define subgroups of forecasts for combining
by Zhenni Ding & Huayou Chen & Ligang Zhou - 924-936 A review of scenario planning for emissions in environmental assessments
by Venmathy Samanaseh & Zainura Zainon Noor & Siti Norasyiqin & Che Hafizan & Muhammad Amani Mazlan & Florianna Lendai Michael - 937-956 Uncertainties and disagreements in expectations of professional forecasters: Evidence from an inflation targeting developing country
by Gabriel Caldas Montes & Igor Mendes Marcelino - 957-969 Electricity demand forecasting and risk management using Gaussian process model with error propagation
by Kuangyu Wen & Wenbin Wu & Ximing Wu - 970-988 Which factors drive Bitcoin volatility: Macroeconomic, technical, or both?
by Jiqian Wang & Feng Ma & Elie Bouri & Yangli Guo - 989-1007 A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies
by Carlos Trucíos & James W. Taylor - 1008-1035 A retrospective analysis of Journal of Forecasting: From 1982 to 2019
by Dejian Yu & Libo Sheng & Shunshun Shi
April 2023, Volume 42, Issue 3
- 455-463 Advances in forecasting: An introduction in light of the debate on inflation forecasting
by Anindya Banerjee & Stephen G. Hall & Georgios P. Kouretas & George S. Tavlas - 464-480 Nowcasting inflation with Lasso‐regularized vector autoregressions and mixed frequency data
by Tesi Aliaj & Milos Ciganovic & Massimiliano Tancioni - 481-513 Forecasting inflation in open economies: What can a NOEM model do?
by Roberto Duncan & Enrique Martínez‐García - 514-529 Forecasting inflation: The use of dynamic factor analysis and nonlinear combinations
by Stephen G. Hall & George S. Tavlas & Yongli Wang - 530-542 Evaluation and indirect inference estimation of inattentive features in a New Keynesian framework
by Jenyu Chou & Yifei Cao & Patrick Minford - 543-565 Forecasting housing investment
by Carlos Cañizares Martínez & Gabe J. de Bondt & Arne Gieseck - 566-577 Assessing the informational content of card transactions for nowcasting retail trade: Evidence for Latvia
by Anete Brinke & Ludmila Fadejeva & Boriss Siliverstovs & Kārlis Vilerts - 578-624 Jump forecasting in foreign exchange markets: A high‐frequency analysis
by Sevcan Uzun & Ahmet Sensoy & Duc Khuong Nguyen - 625-642 The role of expectations for currency crisis dynamics—The case of the Turkish lira
by Joscha Beckmann & Robert L. Czudaj - 643-656 The effects of shocks to interest rate expectations in the euro area: Estimates at the country level
by Martin Mandler & Michael Scharnagl - 657-684 Forecasting sovereign risk in the Euro area via machine learning
by Guillaume Belly & Lukas Boeckelmann & Carlos Mateo Caicedo Graciano & Alberto Di Iorio & Klodiana Istrefi & Vasileios Siakoulis & Arthur Stalla‐Bourdillon - 685-714 Worse than you think: Public debt forecast errors in advanced and developing economies
by Julia Estefania‐Flores & Davide Furceri & Siddharth Kothari & Jonathan D. Ostry - 715-738 Macro‐financial effects of monetary policy easing
by George N. Apostolakis & Nikolaos Giannellis & Athanasios P. Papadopoulos
March 2023, Volume 42, Issue 2
- 195-211 Robust forecasting in spatial autoregressive model with total variation regularization
by He Jiang - 212-222 Trading cryptocurrencies using algorithmic average true range systems
by Gil Cohen - 223-239 Structural and predictive analyses with a mixed copula‐based vector autoregression model
by Woraphon Yamaka & Rangan Gupta & Sukrit Thongkairat & Paravee Maneejuk - 240-259 Nonlinear inflation forecasting with recurrent neural networks
by Anna Almosova & Niek Andresen - 260-287 Combined water quality forecasting system based on multiobjective optimization and improved data decomposition integration strategy
by Yuqi Dong & Jianzhou Wang & Xinsong Niu & Bo Zeng - 288-311 The effect of environment on housing prices: Evidence from the Google Street View
by Guan‐Yuan Wang - 312-330 Text‐based soybean futures price forecasting: A two‐stage deep learning approach
by Wuyue An & Lin Wang & Yu‐Rong Zeng - 331-346 Forecasting inflation and output growth with credit‐card‐augmented Divisia monetary aggregates
by William A. Barnett & Sohee Park - 347-368 Modeling the relation between the US real economy and the corporate bond‐yield spread in Bayesian VARs with non‐Gaussian innovations
by Tamás Kiss & Stepan Mazur & Hoang Nguyen & Pär Österholm - 369-401 Forecasting inflation time series using score‐driven dynamic models and combination methods: The case of Brazil
by Carlos Henrique Dias Cordeiro de Castro & Fernando Antonio Lucena Aiube - 402-417 Application of machine learning techniques to predict entrepreneurial firm valuation
by Ruling Zhang & Zengrui Tian & Killian J. McCarthy & Xiao Wang & Kun Zhang - 418-451 Real‐time forecasting of the Australian macroeconomy using flexible Bayesian VARs
by Chenghan Hou & Bao Nguyen & Bo Zhang
January 2023, Volume 42, Issue 1
- 3-16 Geopolitical risk and global financial cycle: Some forecasting experiments
by Afees A. Salisu & Philip C. Omoke & Abdulsalam Abidemi Sikiru - 17-33 Forecasting energy prices: Quantile‐based risk models
by Nicholas Apergis - 34-50 Estimation of short‐run predictive factor for US growth using state employment data
by Arabinda Basistha - 51-59 Volatility forecasting for stock market incorporating macroeconomic variables based on GARCH‐MIDAS and deep learning models
by Yuping Song & Xiaolong Tang & Hemin Wang & Zhiren Ma - 60-75 A tug of war of forecasting the US stock market volatility: Oil futures overnight versus intraday information
by Feng Ma & M. I. M. Wahab & Julien Chevallier & Ziyang Li - 76-100 Trading volume and realized volatility forecasting: Evidence from the China stock market
by Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee - 101-123 Wind power prediction based on wind speed forecast using hidden Markov model
by Khatereh Ghasvarian Jahromi & Davood Gharavian & Hamid Reza Mahdiani - 124-153 Power grid operation optimization and forecasting using a combined forecasting system
by Lifang Zhang & Jianzhou Wang & Zhenkun Liu - 154-175 A new PM2.5 concentration forecasting system based on AdaBoost‐ensemble system with deep learning approach
by Zhongfei Li & Kai Gan & Shaolong Sun & Shouyang Wang - 176-192 A hybrid approach with step‐size aggregation to forecasting hierarchical time series
by Hakeem‐Ur Rehman & Guohua Wan & Raza Rafique
December 2022, Volume 41, Issue 8
- 1559-1569 Interest rate uncertainty and the predictability of bank revenues
by Oguzhan Cepni & Riza Demirer & Rangan Gupta & Ahmet Sensoy - 1570-1577 A Siamese network framework for bank intelligent Q&A prediction
by Wei Wei & Yingli Liang - 1578-1594 Mixed membership nearest neighbor model with feature difference
by Simon K. C. Cheung & Tommy K. Y. Cheung - 1595-1607 Forecasting value at risk and expected shortfall using high‐frequency data of domestic and international stock markets
by Man Wang & Yihan Cheng - 1608-1622 A generalized two‐factor square‐root framework for modeling occurrences of natural catastrophes
by Giuseppe Orlando & Michele Bufalo - 1623-1638 High‐frequency data and stock–bond investing
by Yu‐Sheng Lai - 1639-1660 Predicting earnings management through machine learning ensemble classifiers
by Ahmad Hammami & Mohammad Hendijani Zadeh - 1661-1668 Cryptocurrencies trading algorithms: A review
by Isabela Ruiz Roque da Silva & Eli Hadad Junior & Pedro Paulo Balbi - 1669-1690 Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending
by Yufei Xia & Xinyi Guo & Yinguo Li & Lingyun He & Xueyuan Chen - 1691-1700 Forecasting chlorophyll‐a concentration using empirical wavelet transform and support vector regression
by Jin‐Won Yu & Ju‐Song Kim & Yun‐Chol Jong & Xia Li & Gwang‐Il Ryang - 1701-1724 Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting
by Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva - 1725-1740 The role of investor sentiment in forecasting housing returns in China: A machine learning approach
by Oguzhan Cepni & Rangan Gupta & Yigit Onay
November 2022, Volume 41, Issue 7
- 1317-1337 Bayesian quantile forecasting via the realized hysteretic GARCH model
by Cathy W. S. Chen & Edward M. H. Lin & Tara F. J. Huang - 1338-1355 Are internally consistent forecasts rational?
by Jing Tian & Firmin Doko Tchatoka & Thomas Goodwin - 1356-1371 Forgetting approaches to improve forecasting
by Robert A. Hill & Paulo M. M. Rodrigues - 1372-1385 Central bank information and private‐sector expectations
by Jochen Güntner - 1386-1415 Modeling credit risk with a multi‐stage hybrid model: An alternative statistical approach
by Mohammad Shamsu Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib & Kunpeng Yuan - 1416-1432 Evaluating the predictive power of intraday technical trading in China's crude oil market
by Xiaoye Jin - 1433-1457 Forecasting international equity market volatility: A new approach
by Chao Liang & Yan Li & Feng Ma & Yaojie Zhang - 1458-1482 Stochastic configuration network based on improved whale optimization algorithm for nonstationary time series prediction
by Zi‐yu Chen & Fei Xiao & Xiao‐kang Wang & Min‐hui Deng & Jian‐qiang Wang & Jun‐Bo Li - 1483-1511 Multi‐step air quality index forecasting via data preprocessing, sequence reconstruction, and improved multi‐objective optimization algorithm
by Ying Wang & Jianzhou Wang & Hongmin Li & Hufang Yang & Zhiwu Li - 1512-1524 A weights direct determination neuronet for time‐series with applications in the industrial indices of the Federal Reserve Bank of St. Louis
by Spyridon D. Mourtas - 1525-1556 Uncertainty and predictability of real housing returns in the United Kingdom: A regional analysis
by Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna & Mark E. Wohar