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Content
January 2025, Volume 44, Issue 1
- 3-40 New forecasting methods for an old problem: Predicting 147 years of systemic financial crises
by Emile du Plessis & Ulrich Fritsche - 41-58 Short‐term multivariate airworthiness forecasting based on decomposition and deep prediction models
by Ali Tatli & Tansu Filik & Erdogan Bocu & Hikmet Tahir Karakoc - 59-78 Macroeconomic real‐time forecasts of univariate models with flexible error structures
by Kelly Trinh & Bo Zhang & Chenghan Hou - 79-92 Research on occupant injury severity prediction of autonomous vehicles based on transfer learning
by Na Yang & Dongwei Liu & Qi Liu & Zhiwei Li & Tao Liu & Jianfeng Wang & Ze Xu - 93-111 A hybrid interval‐valued time series prediction model incorporating intuitionistic fuzzy cognitive map and fuzzy neural network
by Jiajia Zhang & Zhifu Tao & Jinpei Liu & Xi Liu & Huayou Chen - 112-135 A new probability forecasting model for cotton yarn futures price volatility with explainable AI and big data
by Huosong Xia & Xiaoyu Hou & Justin Zuopeng Zhang & Mohammad Zoynul Abedin - 136-152 Forecasting Markov switching vector autoregressions: Evidence from simulation and application
by Maddalena Cavicchioli - 153-172 Long‐term forecasting of maritime economics index using time‐series decomposition and two‐stage attention
by Dohee Kim & Eunju Lee & Imam Mustafa Kamal & Hyerim Bae - 173-199 Toward a smart forecasting model in supply chain management: A case study of coffee in Vietnam
by Thi Thuy Hanh Nguyen & Abdelghani Bekrar & Thi Muoi Le & Mourad Abed & Anirut Kantasa‐ard - 200-215 Forecasting USD/RMB exchange rate using the ICEEMDAN‐CNN‐LSTM model
by Yun Zhou & Xuxu Zhu - 216-241 Forecasting house price index with social media sentiment: A decomposition–ensemble approach
by Jin Shao & Lean Yu & Jingke Hong & Xianzhu Wang - 242-252 A multi‐objective optimization metaheuristic hybrid technique for forecasting the electricity consumption of the UAE: A grey wolf approach
by Andreas Karathanasopoulos & Chia Chun Lo & Mitra Sovan & Mohamed Osman & Hans‐Jörg von Mettenheim & Slim Skander
November 2024, Volume 43, Issue 7
- 2401-2433 Multivariable forecasting approach of high‐speed railway passenger demand based on residual term of Baidu search index and error correction
by Hongtao Li & Xiaoxuan Li & Shaolong Sun & Zhipeng Huang & Xiaoyan Jia - 2434-2447 Prediction of wind energy with the use of tensor‐train based higher order dynamic mode decomposition
by Keren Li & Sergey Utyuzhnikov - 2448-2477 Credit card loss forecasting: Some lessons from COVID
by Partha Sengupta & Christopher H. Wheeler - 2478-2494 A novel semisupervised learning method with textual information for financial distress prediction
by Yue Qiu & Jiabei He & Zhensong Chen & Yinhong Yao & Yi Qu - 2495-2521 Forecasting Chinese crude oil futures volatility: New evidence based on dual feature processing of large‐scale variables
by Gaoxiu Qiao & Yijun Pan & Chao Liang & Lu Wang & Jinghui Wang - 2522-2539 Data patterns that reliably precede US recessions
by Edward E. Leamer - 2540-2571 Forecasting corporate financial performance with deep learning and interpretable ALE method: Evidence from China
by Longyue Liang & Bo Liu & Zhi Su & Xuanye Cai - 2572-2587 Are professional forecasters inattentive to public discussions about inflation? The case of Argentina
by J. Daniel Aromí & Martín Llada - 2588-2606 Takeover in Europe: Target characteristics and acquisition likelihood
by Hicham Meghouar - 2607-2634 A multistage forecasting model for green bond cost optimization with dynamic corporate risk constraints
by Zinan Hu & Ruicheng Yang & Sumuya Borjigin - 2635-2658 A study and development of high‐order fuzzy time series forecasting methods for air quality index forecasting
by Sushree Subhaprada Pradhan & Sibarama Panigrahi - 2659-2674 Time‐varying risk preference and equity risk premium forecasting: The role of the disposition effect
by Kenan Qiao & Haibin Xie - 2675-2684 Twitter policy uncertainty and stock returns in South Africa: Evidence from time‐varying Granger causality
by Kingstone Nyakurukwa & Yudhvir Seetharam - 2685-2704 A deep learning‐based multivariate decomposition and ensemble framework for container throughput forecasting
by Anurag Kulshrestha & Abhishek Yadav & Himanshu Sharma & Shikha Suman - 2705-2730 Forecasting stock returns with industry volatility concentration
by Yaojie Zhang & Mengxi He & Zhikai Zhang - 2731-2748 Forecasting tail risk of skewed financial returns having exponential‐polynomial tails
by Albert Antwi & Emmanuel N. Gyamfi & Anokye M. Adam - 2749-2765 Volatility forecasting incorporating intraday positive and negative jumps based on deep learning model
by Yilun Zhang & Yuping Song & Ying Peng & Hanchao Wang - 2766-2791 Traffic flow prediction: A 3D adaptive multi‐module joint modeling approach integrating spatial‐temporal patterns to capture global features
by Zain Ul Abideen & Xiaodong Sun & Chao Sun - 2792-2808 Portfolio management based on a reinforcement learning framework
by Wu Junfeng & Li Yaoming & Tan Wenqing & Chen Yun - 2809-2821 Seeing is believing: Forecasting crude oil price trend from the perspective of images
by Xiaohang Ren & Wenting Jiang & Qiang Ji & Pengxiang Zhai - 2822-2847 Regime‐dependent commodity price dynamics: A predictive analysis
by Jesus Crespo Cuaresma & Ines Fortin & Jaroslava Hlouskova & Michael Obersteiner - 2848-2859 Forecasting the direction of the Fed's monetary policy decisions using random forest
by Jungyeon Yoon & Juanjuan Fan - 2860-2885 Measuring persistent global economic factors with output, commodity price, and commodity currency data
by Arabinda Basistha & Richard Startz - 2886-2903 Splitting long‐term and short‐term financial ratios for improved financial distress prediction: Evidence from Taiwanese public companies
by Asyrofa Rahmi & Chia‐chi Lu & Deron Liang & Ayu Nur Fadilah - 2904-2916 Forecasting Bitcoin returns: Econometric time series analysis vs. machine learning
by Theo Berger & Jana Koubová - 2917-2934 Structured multifractal scaling of the principal cryptocurrencies: Examination using a self‐explainable machine learning
by Foued Saâdaoui & Hana Rabbouch
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
August 2024, Volume 43, Issue 5
- 1131-1152 Gated recurrent unit network: A promising approach to corporate default prediction
by Michał Thor & Łukasz Postek - 1153-1172 Density forecast combinations: The real‐time dimension
by Peter McAdam & Anders Warne - 1173-1198 Embedding the weather prediction errors (WPE) into the photovoltaic (PV) forecasting method using deep learning
by Adela Bâra & Simona‐Vasilica Oprea - 1199-1211 Stock movement prediction: A multi‐input LSTM approach
by Pan Tang & Cheng Tang & Keren Wang - 1212-1234 Macroeconomic conditions and bank failure
by Qiongbing Wu & Rebel A. Cole - 1235-1262 Early warning system for currency crises using long short‐term memory and gated recurrent unit neural networks
by Sylvain Barthélémy & Virginie Gautier & Fabien Rondeau - 1263-1277 Two‐stage credit risk prediction framework based on three‐way decisions with automatic threshold learning
by Yusheng Li & Mengyi Sha - 1278-1293 Hybrid convolutional long short‐term memory models for sales forecasting in retail
by Thais de Castro Moraes & Xue‐Ming Yuan & Ek Peng Chew - 1294-1307 A deep learning hierarchical approach to road traffic forecasting
by Redouane Benabdallah Benarmas & Kadda Beghdad Bey - 1308-1320 Measuring the advantages of contemporaneous aggregation in forecasting
by Zeda Li & William W. S. Wei - 1321-1337 Space, mortality, and economic growth
by Kyran Cupido & Petar Jevtić & Tim J. Boonen - 1338-1355 Forecasting multi‐frequency intraday exchange rates using deep learning models
by Muhammad Arslan & Ahmed Imran Hunjra & Wajid Shakeel Ahmed & Younes Ben Zaied - 1356-1373 Forecasting the high‐frequency volatility based on the LSTM‐HIT model
by Guangying Liu & Ziyan Zhuang & Min Wang - 1374-1398 Incorporating media news to predict financial distress: Case study on Chinese listed companies
by Lifang Zhang & Mohammad Zoynul Abedin & Zhenkun Liu - 1399-1421 Conservatism and information rigidity of the European Bank for Reconstruction and Development's growth forecast: Quarter‐century assessment
by Yoichi Tsuchiya - 1422-1446 Forecasting realized volatility of crude oil futures prices based on machine learning
by Jiawen Luo & Tony Klein & Thomas Walther & Qiang Ji - 1447-1464 International evidence of the forecasting ability of option‐implied distributions
by Pedro Serrano & Antoni Vaello‐Sebastià & M. Magdalena Vich Llompart - 1465-1491 Probabilistic electricity price forecasting based on penalized temporal fusion transformer
by He Jiang & Sheng Pan & Yao Dong & Jianzhou Wang - 1492-1512 Tail risk forecasting with semiparametric regression models by incorporating overnight information
by Cathy W. S. Chen & Takaaki Koike & Wei‐Hsuan Shau - 1513-1529 Tail risk forecasting and its application to margin requirements in the commodity futures market
by Yun Feng & Weijie Hou & Yuping Song - 1530-1558 Robust approach to earnings forecast: A comparison
by Xiaojian Yu & Xiaoqian Zhang & Donald Lien - 1559-1574 Applying k‐nearest neighbors to time series forecasting: Two new approaches
by Samya Tajmouati & Bouazza E. L. Wahbi & Adel Bedoui & Abdallah Abarda & Mohamed Dakkon - 1575-1594 Interpretable corn future price forecasting with multivariate time series
by Binrong Wu & Zhongrui Wang & Lin Wang - 1595-1606 Forecasting stock market returns with a lottery index: Evidence from China
by Yaojie Zhang & Qingxiang Han & Mengxi He - 1607-1614 Do search queries predict violence against women? A forecasting model based on Google Trends
by Nicolás Gonzálvez‐Gallego & María Concepción Pérez‐Cárceles & Laura Nieto‐Torrejón - 1615-1624 A forecasting model for oil prices using a large set of economic indicators
by Jihad El Hokayem & Ibrahim Jamali & Ale Hejase - 1625-1660 Credit risk prediction based on causal machine learning: Bayesian network learning, default inference, and interpretation
by Jiaming Liu & Xuemei Zhang & Haitao Xiong - 1661-1681 Improving demand forecasting for customers with missing downstream data in intermittent demand supply chains with supervised multivariate clustering
by Corey Ducharme & Bruno Agard & Martin Trépanier - 1682-1705 A novel hybrid forecasting model with feature selection and deep learning for wind speed research
by Xuejun Chen & Ying Wang & Haitao Zhang & Jianzhou Wang - 1706-1730 Volatility forecasting for stock market incorporating media reports, investors' sentiment, and attention based on MTGNN model
by Bolin Lei & Yuping Song
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
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