OOIR: Observatory of International Research

Papers

(The TQCC of International Journal of Forecasting is 13. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-06-01 to 2026-06-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	701
Systemic bias of IMF reserve and debt forecasts for program countries	364
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	225
Fan charts 2.0: Flexible forecast distributions with expert judgement	223
FRED-SD: A real-time database for state-level data with forecasting applications	207
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	150
Adaptively aggregated forecast for exponential family panel model	99
FFORMPP: Feature-based forecast model performance prediction	97
Survey density forecast comparison in small samples	97
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	92
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	86
Forecasting stock return distributions around the globe with quantile neural networks	72
An overview of the effects of algorithm use on judgmental biases affecting forecasting	71
The profitability of lead–lag arbitrage at high frequency	66
Weekly economic activity: Measurement and informational content	65
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	62
Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	62
Responses to the discussions and commentaries of the M5 Special Issue	60
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	59
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	59
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	59
The decrease in confidence with forecast extremity	58
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	55
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	54
Multi-population mortality projection: The augmented common factor model with structural breaks	54

Fundamental determinants of exchange rate expectations	53
A survey of models and methods used for forecasting when investing in financial markets	53
Too similar to combine? On negative weights in forecast combination	49
Tree-based heterogeneous cascade ensemble model for credit scoring	47
A time-varying skewness model for Growth-at-Risk	46
Editorial Board	46
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	45
Forecasting and policy when “we simply do not know”	45
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	45
Improving forecast stability using deep learning	45
Real estate illiquidity and returns: A time-varying regional perspective	43
Machine learning and insurer failure prediction	37
A robust support vector regression model for electric load forecasting	37
Forecasting the equity premium with frequency-decomposed technical indicators	37
The M5 competition: Conclusions	37
Forecasting football results and exploiting betting markets: The case of “both teams to score”	36
Forecasting: theory and practice	34
Optimal hierarchical EWMA forecasting	33
Editorial Board	33
Hierarchical forecasting with a top-down alignment of independent-level forecasts	33
Combining forecasts under structural breaks using Graphical LASSO	32
Editorial Board	31
Variability of the Lee–Carter model parameters	31
Forecasting presidential elections: Accuracy of ANES voter intentions	31
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	29
Enhancing market return forecasts with an incident-based ESG indicator	28
Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24?	28
Model combinations through revised base rates	27
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	27
Rejoinder: How to “improve” prediction using behavior modification	26
Post-script—Retail forecasting: Research and practice	26
Exploring the representativeness of the M5 competition data	26
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	26
Sequential optimization three-way decision model with information gain for credit default risk evaluation	26
External forcings and predictability of the Atlantic multidecadal oscillation: A model confidence set approach	26
A disaster response model driven by spatial–temporal forecasts	25
Forecasting corporate default risk in China	25
The structural Theta method and its predictive performance in the M4-Competition	25
Forecasting GDP growth rates in the United States and Brazil using Google Trends	24
Whispers in the oil market: Exploring sentiment and uncertainty insights	24
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	24
Forecasting Australian fertility by age, region, and birthplace	24
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	24
Forecasting crude oil futures market returns: A principal component analysis combination approach	23
Evaluating probabilistic classifiers: The triptych	23
Forecasting with trees	22
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	22
Network log-ARCH models for forecasting stock market volatility	22
Portfolio return prediction and risk price heterogeneity	21
Retail forecasting: Research and practice	21

Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	21
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	20
A loss discounting framework for model averaging and selection in time series models	20
Targeting predictors in random forest regression	20
M6 investment challenge: The role of luck and strategic considerations	20
Editorial Board	20
Forecasting electoral violence	19
Reactions to the Bernanke Review from Bank of England watchers	19
Nowcasting U.S. state-level CO2 emissions and energy consumption	19
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	19
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	19
A review and comparison of conflict early warning systems	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
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	18
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	18
Technical analysis, spread trading, and data snooping control	18
All forecasters are not the same: Systematic patterns in predictive performance	18
M5 accuracy competition: Results, findings, and conclusions	17
Robust returns ranking prediction and portfolio optimization for M6	17
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	17
Editorial Board	17
The power of narrative sentiment in economic forecasts	17
Accelerating peak dating in a dynamic factor Markov-switching model	16
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	15
Predicting value at risk for cryptocurrencies with generalized random forests	15
Beyond the numbers: The role of people and processes in central bank forecasting	15
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	15
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	15
Factor-augmented forecasting in big data	15
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	15
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	14
Forecast value added in demand planning	14
On forecast stability	14
Sensitivity and uncertainty in the Lee–Carter mortality model	14
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	14
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	14
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	14
Demand forecasting under lost sales stock policies	13
Dynamic linear models with adaptive discounting	13
The uncertainty track: Machine learning, statistical modeling, synthesis	13
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	13
Cross-temporal forecast reconciliation at digital platforms with machine learning	13
Editorial Board	13