International Journal of Forecasting

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	623
Adaptively aggregated forecast for exponential family panel model	294
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	256
FFORMPP: Feature-based forecast model performance prediction	192
Systemic bias of IMF reserve and debt forecasts for program countries	187
An overview of the effects of algorithm use on judgmental biases affecting forecasting	165
FRED-SD: A real-time database for state-level data with forecasting applications	142
Survey density forecast comparison in small samples	125
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	123
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	87
Fan charts 2.0: Flexible forecast distributions with expert judgement	86
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis	81
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	80
A survey of models and methods used for forecasting when investing in financial markets	80
The profitability of lead–lag arbitrage at high frequency	77
The decrease in confidence with forecast extremity	67
Short-term forecasting of the coronavirus pandemic	66
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	62
Responses to the discussions and commentaries of the M5 Special Issue	61
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	61
Nonparametric expected shortfall forecasting incorporating weighted quantiles	61
A time-varying skewness model for Growth-at-Risk	60
Multi-population mortality projection: The augmented common factor model with structural breaks	58
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	58
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	57

Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	57
Fundamental determinants of exchange rate expectations	55
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	55
Tree-based heterogeneous cascade ensemble model for credit scoring	53
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	52
Weekly economic activity: Measurement and informational content	49
Too similar to combine? On negative weights in forecast combination	49
Forecasting football results and exploiting betting markets: The case of “both teams to score”	46
Editorial Board	46
Real estate illiquidity and returns: A time-varying regional perspective	46
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	43
The M5 competition: Conclusions	43
Forecasting and policy when “we simply do not know”	42
Forecasting the equity premium with frequency-decomposed technical indicators	41
A robust support vector regression model for electric load forecasting	41
Hierarchical forecasting with a top-down alignment of independent-level forecasts	40
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	40
Forecasting: theory and practice	39
Improving forecast stability using deep learning	39
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	38
Variability of the Lee–Carter model parameters	35
Model combinations through revised base rates	35
Editorial Board	35
Editorial Board	35
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	34
Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24?	33
Exploring the representativeness of the M5 competition data	32
Optimal hierarchical EWMA forecasting	31
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	31
Forecasting presidential elections: Accuracy of ANES voter intentions	31
Post-script—Retail forecasting: Research and practice	31
Sequential optimization three-way decision model with information gain for credit default risk evaluation	31
Combining forecasts under structural breaks using Graphical LASSO	31
Evaluating probabilistic classifiers: The triptych	30
Forecasting Australian fertility by age, region, and birthplace	29
Rejoinder: How to “improve” prediction using behavior modification	29
A disaster response model driven by spatial–temporal forecasts	28
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	27
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	27
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	27
The structural Theta method and its predictive performance in the M4-Competition	27
Whispers in the oil market: Exploring sentiment and uncertainty insights	27
Modeling and forecasting intraday spot volatility	26
Forecasting GDP growth rates in the United States and Brazil using Google Trends	26
Forecasting with trees	26
Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems	26
Forecasting crude oil futures market returns: A principal component analysis combination approach	25
Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	24
Forecasting corporate default risk in China	24
Portfolio return prediction and risk price heterogeneity	24

Network log-ARCH models for forecasting stock market volatility	24
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	24
Retail forecasting: Research and practice	24
Editorial Board	23
A loss discounting framework for model averaging and selection in time series models	23
Targeting predictors in random forest regression	22
Reactions to the Bernanke Review from Bank of England watchers	22
Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	22
Nowcasting U.S. state-level CO2 emissions and energy consumption	22
M6 investment challenge: The role of luck and strategic considerations	21
Forecasting electoral violence	21
A review and comparison of conflict early warning systems	19
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	19
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	19
Combining forecasts for universally optimal performance	19
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	18
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	18
Forecasting stock market return with anomalies: Evidence from China	18
Technical analysis, spread trading, and data snooping control	18
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	18
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	18
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	17
All forecasters are not the same: Systematic patterns in predictive performance	17
M5 accuracy competition: Results, findings, and conclusions	17
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	17
The power of narrative sentiment in economic forecasts	17
On forecast stability	16
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	16
Predicting monthly biofuel production using a hybrid ensemble forecasting methodology	16
Sensitivity and uncertainty in the Lee–Carter mortality model	16
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	16
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	16
Forecast value added in demand planning	16
Demand forecasting under lost sales stock policies	16
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	16
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	16
Jump persistence and temporal aggregation of tail risk	15
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	15
Beyond the numbers: The role of people and processes in central bank forecasting	15
Predicting value at risk for cryptocurrencies with generalized random forests	15
Robust returns ranking prediction and portfolio optimization for M6	15
Guest Editorial: Food and Agriculture Forecasting	15
Editorial Board	15
Accelerating peak dating in a dynamic factor Markov-switching model	15
Properties of the reconciled distributions for Gaussian and count forecasts	14
Guest editorial: Economic forecasting in times of COVID-19	14
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	14
Factor-augmented forecasting in big data	14
Lee–Carter models: The wider context	13
Dynamic linear models with adaptive discounting	13
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	13
The uncertainty track: Machine learning, statistical modeling, synthesis	13
Editorial Board	13
Hierarchical transfer learning with applications to electricity load forecasting	12
Trust the experts? The performance of inflation expectations, 1960–2023	12
HARd to beat: The overlooked impact of rolling windows in the era of machine learning	12
Nowcasting with panels and alternative data: The OECD weekly tracker	12
Betting on a buzz: Mispricing and inefficiency in online sportsbooks	12
Real-time hurricane damage nowcasts	12
Cross-temporal forecast reconciliation at digital platforms with machine learning	12
Relative performance of judgmental methods for forecasting the success of megaprojects	12
Leveraging image-based generative adversarial networks for time series generation	12
Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk	12
The probability conflation: A reply to Tetlock et al.	11
Editorial Board	11
A machine learning-based framework for forecasting sales of new products with short life cycles using deep neural networks	11
Editorial Board	11
Robust recalibration of aggregate probability forecasts using meta-beliefs	11
Deep switching state space model for nonlinear time series forecasting with regime switching	11
The Lee–Carter method and probabilistic population forecasts	11
Improving geopolitical forecasts with 100 brains and one computer	11
Efficiency of poll-based multi-period forecasting systems for German state elections	10
Harry Markowitz: An appreciation	10
Comparing probabilistic forecasts of the daily minimum and maximum temperature	10
Probabilistic population forecasting: Short to very long-term	10
A mixture model for credit card exposure at default using the GAMLSS framework	10
SCORE: A convolutional approach for football event forecasting	10
Forecasting electricity prices using bid data	10
A semi-supervised reject inference framework with hierarchical heterogeneous networks for credit scoring	9
Calibration of deterministic NWP forecasts and its impact on verification	9

Bayesian herd detection for dynamic data	9
Forecasting interest rates with shifting endpoints: The role of the functional demographic age distribution	9
Early Warning Systems for identifying financial instability	9
Improving forecasts for heterogeneous time series by “averaging”, with application to food demand forecasts	9
Forecasting for monetary policy	9
Crude oil price forecasting incorporating news text	8
Hierarchical forecasting at scale	8
The RWDAR model: A novel state-space approach to forecasting	8
Daily news sentiment and monthly surveys: A mixed-frequency dynamic factor model for nowcasting consumer confidence	8
Forecasting adversarial actions using judgment decomposition-recomposition	8
Empirical probabilistic forecasting: An approach solely based on deterministic explanatory variables for the selection of past forecast errors	8
Stochastic modelling of football matches using dynamic regressors	8
Forecast combinations: An over 50-year review	8
A projected nonlinear state-space model for forecasting time series signals	8
Short-term Covid-19 forecast for latecomers	8
Aggregating qualitative district-level campaign assessments to forecast election results: Evidence from Japan	8
Parameter-efficient deep probabilistic forecasting	8
Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx	8
Forecasting, causality and feedback	8
The impact of the COVID-19 pandemic on business expectations	8
Emotions and the status quo: The anti-incumbency bias in political prediction markets	8
Ups and (draw) downs	8
Adaptive forecasting in dynamic markets: An evaluation of AutoTS within the M6 competition	7
Forecast combination-based forecast reconciliation: Insights and extensions	7
On single point forecasts for fat-tailed variables	7
Avoiding overconfidence: Evidence from the M6 financial competition	7
High-frequency monitoring of growth at risk	7
The M5 uncertainty competition: Results, findings and conclusions	7
Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions	7
Asymmetric uncertainty: Nowcasting using skewness in real-time data	7
LoMEF: A framework to produce local explanations for global model time series forecasts	7
Anticipating special events in Emergency Department forecasting	7
Forecasting day-ahead expected shortfall on the EUR/USD exchange rate: The (I)relevance of implied volatility	7
Forecasting crude oil market volatility using variable selection and common factor	7
M5 competition uncertainty: Overdispersion, distributional forecasting, GAMLSS, and beyond	7
A solution for M5 Forecasting - Uncertainty: Hybrid gradient boosting and autoregressive recurrent neural network for quantile estimation	7
The time-varying Multivariate Autoregressive Index model	7
A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices	7
Forecasting mail flow: A hierarchical approach for enhanced societal wellbeing	7
On memory-augmented gated recurrent unit network	6
A copula-based time series model for global horizontal irradiation	6
Evaluation of the best M4 competition methods for small area population forecasting	6
Real-time density nowcasts of US inflation: A model combination approach	6
Do professional forecasters believe in the Phillips curve?	6
Robust regression for electricity demand forecasting against cyberattacks	6
Corrigendum to “The behaviour of betting and currency markets on the night of the EU referendum” [Int. J. Forecast. 35 (1) (2018) 371–389]	6
Out-of-sample predictability in predictive regressions with many predictor candidates	6
Humans vs. large language models: Judgmental forecasting in an era of advanced AI	6
COVID-19: Forecasting confirmed cases and deaths with a simple time series model	6
Data-based priors for vector error correction models	6
Epidemiological versus meteorological forecasts: Best practice for linking models to policymaking	6
Do we want coherent hierarchical forecasts, or minimal MAPEs or MAEs? (We won’t get both!)	6
Improving variance forecasts: The role of Realized Variance features	6
Nowcasting economic activity in European regions using a mixed-frequency dynamic factor model	6
Editorial and introduction to the special section on the Bernanke’s review of the Bank of England’s forecasting activities	6
Predicting/hypothesizing the findings of the M5 competition	5
Service-level anchoring in demand forecasting: The moderating impact of retail promotions and product perishability	5
Conditionally optimal weights and forward-looking approaches to combining forecasts	5
Guest Editorial: Forecasting for Social Good	5
Likelihood-based inference in temporal hierarchies	5
Combining predictive distributions for time-to-event outcomes in meteorology	5
Guiding supervisors in artificial intelligence-enabled forecasting: Understanding the impacts of salience and detail on decision-making	5
On the evaluation of hierarchical forecasts	5
Investigating laypeople’s short- and long-term forecasts of COVID-19 infection cycles	5
Coupling LSTM neural networks and state-space models through analytically tractable inference	5
Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?	5
ABC-based forecasting in misspecified state space models	5
Special section on credit risk modelling—Guest editorial	5
Evaluating quantile forecasts in the M5 uncertainty competition	5
Eliciting expectation uncertainty from private households	5
Daily growth at risk: Financial or real drivers? The answer is not always the same	5
Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts	5
A multi-task encoder-dual-decoder framework for mixed frequency data prediction	5
Back to the present: Learning about the euro area through a now-casting model	5
Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model	5
Book review	5
Real-time inflation forecasting using non-linear dimension reduction techniques	5
Asymmetric models for realized covariances	5
Forecasting realized volatility with spillover effects: Perspectives from graph neural networks	5
Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest	5
Forecasting euro area inflation using a huge panel of survey expectations	4
Quantifying subjective uncertainty in survey expectations	4
DCC- and DECO-HEAVY: Multivariate GARCH models based on realized variances and correlations	4
How to “improve” prediction using behavior modification	4
The kernel trick for nonlinear factor modeling	4
Acknowledgement to reviewers	4
GoodsForecast second-place solution in M5 Uncertainty track: Combining heterogeneous models for a quantile estimation task	4
A theory-based method to evaluate the impact of central bank inflation forecasts on private inflation expectations	4
Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value	4
Thinking outside the container: A sparse partial least squares approach to forecasting trade flows	4
How local is the local inflation factor? Evidence from emerging European countries	4
Bayesian forecast combination using time-varying features	4
Exploring the social influence of the Kaggle virtual community on the M5 competition	4
Editorial Board	4
Carpe diem: Can daily oil prices improve model-based forecasts of the real price of crude oil?	4