International Journal of Forecasting

Article	Citations
Temporal Fusion Transformers for interpretable multi-horizon time series forecasting	701
Recurrent Neural Networks for Time Series Forecasting: Current status and future directions	549
Forecasting: theory and practice	354
Forecasting for COVID-19 has failed	213
M5 accuracy competition: Results, findings, and conclusions	145
Kaggle forecasting competitions: An overlooked learning opportunity	140
Machine learning model for Bitcoin exchange rate prediction using economic and technology determinants	118
Retail forecasting: Research and practice	114
The impact of the COVID-19 pandemic on business expectations	108
A novel text-based framework for forecasting agricultural futures using massive online news headlines	86
Principles and algorithms for forecasting groups of time series: Locality and globality	86
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx	67
Forecast combinations: An over 50-year review	63
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	56
Forecast reconciliation: A geometric view with new insights on bias correction	52
The M5 competition: Background, organization, and implementation	51
Forecasting crude oil market volatility using variable selection and common factor	50
Nowcasting GDP using machine-learning algorithms: A real-time assessment	49
Forecasting with trees	48
Forecasting recovery rates on non-performing loans with machine learning	45
COVID-19: Forecasting confirmed cases and deaths with a simple time series model	45
Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods	44
The power of text-based indicators in forecasting Italian economic activity	44
Measuring the Connectedness of the Global Economy	43
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	40

Forecasting realized volatility of agricultural commodity futures with infinite Hidden Markov HAR models	40
Stock market volatility forecasting: Do we need high-frequency data?	39
Crude oil price forecasting incorporating news text	39
Targeting predictors in random forest regression	39
Forecasting sales using online review and search engine data: A method based on PCA–DSFOA–BPNN	38
Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	38
Preventing rather than punishing: An early warning model of malfeasance in public procurement	38
Big data from dynamic pricing: A smart approach to tourism demand forecasting	38
The M5 uncertainty competition: Results, findings and conclusions	35
Forecasting macroeconomic risks	35
Artificial bee colony-based combination approach to forecasting agricultural commodity prices	35
High-frequency monitoring of growth at risk	34
Forecasting cryptocurrency volatility	33
Forecasting crude oil futures market returns: A principal component analysis combination approach	33
Investigating the accuracy of cross-learning time series forecasting methods	33
Forecasting realized volatility of agricultural commodities	32
The COVID-19 shock and challenges for inflation modelling	31
Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States	30
Global economic policy uncertainty aligned: An informative predictor for crude oil market volatility	29
Multivariate volatility forecasts for stock market indices	29
A comparison of monthly global indicators for forecasting growth	28
A robust support vector regression model for electric load forecasting	28
Minnesota-type adaptive hierarchical priors for large Bayesian VARs	27
Comparing the accuracy of several network-based COVID-19 prediction algorithms	27
Short-term forecasting of the coronavirus pandemic	26
On single point forecasts for fat-tailed variables	26
Modeling and predicting U.S. recessions using machine learning techniques	26
Nowcasting unemployment insurance claims in the time of COVID-19	25
Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals	25
Forecasting Bitcoin with technical analysis: A not-so-random forest?	25
Prediction of the Indian summer monsoon using a stacked autoencoder and ensemble regression model	25
Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction	25
Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?	25
Conformal prediction interval estimation and applications to day-ahead and intraday power markets	24
Forecasting crude oil prices with DSGE models	24
Probabilistic population forecasting: Short to very long-term	24
Forecasting high resolution electricity demand data with additive models including smooth and jagged components	23
Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach	23
Calibration of deterministic NWP forecasts and its impact on verification	23
Forecasting in humanitarian operations: Literature review and research needs	23
Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches	23
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	22
Forecasting unemployment insurance claims in realtime with Google Trends	22
Distributed ARIMA models for ultra-long time series	22
The recurrence of financial distress: A survival analysis	22
Bagging weak predictors	22
Assessing and predicting small industrial enterprises’ credit ratings: A fuzzy decision-making approach	22
The effect of spatiotemporal resolution on predictive policing model performance	20
Classification-based model selection in retail demand forecasting	20
Stability in the inefficient use of forecasting systems: A case study in a supply chain company	20

A critical overview of privacy-preserving approaches for collaborative forecasting	19
Deep learning models for visibility forecasting using climatological data	19
Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks	19
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	19
Spatial dependence in microfinance credit default	19
Realized volatility forecasting: Robustness to measurement errors	18
Nowcasting food inflation with a massive amount of online prices	17
Expert forecasting with and without uncertainty quantification and weighting: What do the data say?	17
Online distributed learning in wind power forecasting	17
Factor extraction using Kalman filter and smoothing: This is not just another survey	17
Mixed random forest, cointegration, and forecasting gasoline prices	17
Bayesian median autoregression for robust time series forecasting	17
Forecasting European carbon returns using dimension reduction techniques: Commodity versus financial fundamentals	16
Forecasting electricity prices with expert, linear, and nonlinear models	16
Spatio-temporal probabilistic forecasting of wind power for multiple farms: A copula-based hybrid model	16
Thirty years on: A review of the Lee–Carter method for forecasting mortality	16
Stock market volatility predictability in a data-rich world: A new insight	15
Robust recurrent network model for intermittent time-series forecasting	15
Sequential optimization three-way decision model with information gain for credit default risk evaluation	15
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	15
Informational efficiency and behaviour within in-play prediction markets	15
Evaluating quantile-bounded and expectile-bounded interval forecasts	15
FFORMPP: Feature-based forecast model performance prediction	15
Modelling non-stationary ‘Big Data’	14
Variational Bayes approximation of factor stochastic volatility models	14
Probabilistic access forecasting for improved offshore operations	14
Cyberattack-resilient load forecasting with adaptive robust regression	13
U-Convolutional model for spatio-temporal wind speed forecasting	13
Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence	13
What do forecasting rationales reveal about thinking patterns of top geopolitical forecasters?	13
Analytic moments for GJR-GARCH (1, 1) processes	13
Optimal model averaging forecasting in high-dimensional survival analysis	13
A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants	13
Demand forecasting for fashion products: A systematic review	12
Data snooping in equity premium prediction	12
Exploring the representativeness of the M5 competition data	12
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	12
Non-Gaussian models for CoVaR estimation	12
Dimensionality reduction in forecasting with temporal hierarchies	12
Artificial intelligence-based predictions of movie audiences on opening Saturday	12
Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value	12
Forecasting corporate default risk in China	12
Influence of earnings management on forecasting corporate failure	12
Combining forecasts for universally optimal performance	12
Hierarchical forecasting with a top-down alignment of independent-level forecasts	11
Simple averaging of direct and recursive forecasts via partial pooling using machine learning	11
Cross-temporal forecast reconciliation: Optimal combination method and heuristic alternatives	11
Optimal and robust combination of forecasts via constrained optimization and shrinkage	11
Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy	11
Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model	10
Bayesian VAR forecasts, survey information, and structural change in the euro area	10
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	10
Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	10
Anticipating special events in Emergency Department forecasting	10
Real-time inflation forecasting using non-linear dimension reduction techniques	10
Nowcasting GDP and its components in a data-rich environment: The merits of the indirect approach	10
Online hierarchical forecasting for power consumption data	10
Macroeconomic data transformations matter	10
Testing big data in a big crisis: Nowcasting under Covid-19	10
Does judgment improve macroeconomic density forecasts?	10
Sparse structures with LASSO through principal components: Forecasting GDP components in the short-run	10
Weekly economic activity: Measurement and informational content	10
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	10
Daily peak electrical load forecasting with a multi-resolution approach	9
Dynamic functional time-series forecasts of foreign exchange implied volatility surfaces	9
Does the Phillips curve help to forecast euro area inflation?	9
Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities	9
Optimal probabilistic forecasts: When do they work?	9
Nonparametric expected shortfall forecasting incorporating weighted quantiles	9
The power of narrative sentiment in economic forecasts	9
Bayesian forecast combination using time-varying features	9
Interpretable sports team rating models based on the gradient descent algorithm	9
On using predictive-ability tests in the selection of time-series prediction models: A Monte Carlo evaluation	9
Forecasting mortality with a hyperbolic spatial temporal VAR model	9
Applicability of the M5 to Forecasting at Walmart	8
Boosting nonlinear predictability of macroeconomic time series	8
Killing off cohorts: Forecasting mortality of non-extinct cohorts with the penalized composite link model	8
Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective	8
A DCC-type approach for realized covariance modeling with score-driven dynamics	8
Too similar to combine? On negative weights in forecast combination	8

Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting	8
A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks	8
Boosting tax revenues with mixed-frequency data in the aftermath of COVID-19: The case of New York	8
Nowcasting German GDP: Foreign factors, financial markets, and model averaging	8
LoMEF: A framework to produce local explanations for global model time series forecasts	8
Keeping track of global trade in real time	8
Forecasting the volatility of asset returns: The informational gains from option prices	8
A Markov chain model for forecasting results of mixed martial arts contests	8
Granger causality detection in high-dimensional systems using feedforward neural networks	7
Volatility forecasting in European government bond markets	7
Forecasting seasonal demand for retail: A Fourier time-varying grey model	7
Rounding behaviour of professional macro-forecasters	7
Tree-based heterogeneous cascade ensemble model for credit scoring	7
Measuring and forecasting retail trade in real time using card transactional data	7
Shrinkage estimator for exponential smoothing models	7
Forecasting extreme financial risk: A score-driven approach	7
Discrete Gompertz equation and model selection between Gompertz and logistic models	7
Improving the wisdom of crowds with analysis of variance of predictions of related outcomes	7
A data-driven approach to forecasting ground-level ozone concentration	7
Decomposing the effects of crowd-wisdom aggregators: The bias–information–noise (BIN) model	7
Intermittency and obsolescence: A Croston method with linear decay	7
Forecasting GDP growth rates in the United States and Brazil using Google Trends	7
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	7
Dynamic factor models with clustered loadings: Forecasting education flows using unemployment data	7
Machine learning for satisficing operational decision making: A case study in blood supply chain	7
Words or numbers? Macroeconomic nowcasting with textual and macroeconomic data	6
Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach	6
Bayesian forecasting in economics and finance: A modern review	6
Network log-ARCH models for forecasting stock market volatility	6
Robust regression for electricity demand forecasting against cyberattacks	6
Guest editorial: Economic forecasting in times of COVID-19	6
A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market	6
Forecasting electricity prices using bid data	6
Do survey joiners and leavers differ from regular participants? The US SPF GDP growth and inflation forecasts	6
Penalized estimation of panel vector autoregressive models: A panel LASSO approach	6
Do we want coherent hierarchical forecasts, or minimal MAPEs or MAEs? (We won’t get both!)	6
The kernel trick for nonlinear factor modeling	6
Bayesian model averaging for mortality forecasting using leave-future-out validation	6
Post-script—Retail forecasting: Research and practice	6
Forecast reconciliation: A review	5
30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial	5
Predicting/hypothesizing the findings of the M5 competition	5
On the evaluation of hierarchical forecasts	5
Forecasting in GARCH models with polynomially modified innovations	5
A new approach to estimating earnings forecasting models: Robust regression MM-estimation	5
Short-term Covid-19 forecast for latecomers	5
Parameter-efficient deep probabilistic forecasting	5
Pandemics and forecasting: The way forward through the Taleb-Ioannidis debate	5
Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions	5
A disaster response model driven by spatial–temporal forecasts	5
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	5
Real-time density nowcasts of US inflation: A model combination approach	5
Forecast combination-based forecast reconciliation: Insights and extensions	5
Transfer learning for hierarchical forecasting: Reducing computational efforts of M5 winning methods	5
FRED-SD: A real-time database for state-level data with forecasting applications	5
Testing the predictive accuracy of COVID-19 forecasts	5
A dynamic conditional approach to forecasting portfolio weights	5
Commentary on the M5 forecasting competition	5
Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting	5
Spatiotemporal wind forecasting by learning a hierarchically sparse inverse covariance matrix using wind directions	5
Forecast encompassing tests for the expected shortfall	5
M5 competition uncertainty: Overdispersion, distributional forecasting, GAMLSS, and beyond	5
A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls	5
A flexible framework for intervention analysis applied to credit-card usage during the coronavirus pandemic	5
Macroeconomic forecasting in the euro area using predictive combinations of DSGE models	5
A mixture model for credit card exposure at default using the GAMLSS framework	4
Improving inflation forecasts using robust measures	4
Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest	4
A copula-based time series model for global horizontal irradiation	4
Semiparametric time series models driven by latent factor	4
A market for trading forecasts: A wagering mechanism	4
Quantifying subjective uncertainty in survey expectations	4
Generalized βARMA model for double bounded time series forecasting	4
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	4
Penalized maximum likelihood estimation of logit-based early warning systems	4
Relative performance of judgmental methods for forecasting the success of megaprojects	4
Are professional forecasters overconfident?	4
Data-based priors for vector error correction models	4
Forecasting for social good	4
Conflict forecasting using remote sensing data: An application to the Syrian civil war	4
A new method to assess the degree of information rigidity using fixed-event forecasts	4
How to “improve” prediction using behavior modification	4
Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems	4
Modeling high-dimensional unit-root time series	4
Deep learning for modeling the collection rate for third-party buyers	4
Evaluation of the best M4 competition methods for small area population forecasting	4
Sparse estimation of dynamic principal components for forecasting high-dimensional time series	4
Wind energy forecasting with missing values within a fully conditional specification framework	4
Exploring the social influence of the Kaggle virtual community on the M5 competition	4
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	3
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	3
A review and comparison of conflict early warning systems	3
Spurious relationships in high-dimensional systems with strong or mild persistence	3
Regional heterogeneity and U.S. presidential elections: Real-time 2020 forecasts and evaluation	3
DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations	3