OOIR: Observatory of International Research

Papers

(The TQCC of International Journal of Forecasting is 12. 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 2022-05-01 to 2026-05-01.)

Article	Citations
Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks	685
FRED-SD: A real-time database for state-level data with forecasting applications	347
Forecasting stock market volatility with regime-switching GARCH-MIDAS: The role of geopolitical risks	217
Systemic bias of IMF reserve and debt forecasts for program countries	215
FFORMPP: Feature-based forecast model performance prediction	203
Blending gradient boosted trees and neural networks for point and probabilistic forecasting of hierarchical time series	146
Survey density forecast comparison in small samples	96
Fan charts 2.0: Flexible forecast distributions with expert judgement	96
Towards a real-time prediction of waiting times in emergency departments: A comparative analysis of machine learning techniques	94
Adaptively aggregated forecast for exponential family panel model	89
Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach	86
An overview of the effects of algorithm use on judgmental biases affecting forecasting	71
A survey of models and methods used for forecasting when investing in financial markets	70
The profitability of lead–lag arbitrage at high frequency	65
Tree-based heterogeneous cascade ensemble model for credit scoring	63
Weekly economic activity: Measurement and informational content	61
Forecasting using variational Bayesian inference in large vector autoregressions with hierarchical shrinkage	61
Machine learning applications in hierarchical time series forecasting: Investigating the impact of promotions	60
Responses to the discussions and commentaries of the M5 Special Issue	59
Multi-population mortality projection: The augmented common factor model with structural breaks	58
Guest editorial: In memory of Professor John Edward Boylan, 1959–2023	58
Subjective-probability forecasts of existential risk: Initial results from a hybrid persuasion-forecasting tournament	57
Too similar to combine? On negative weights in forecast combination	54
Forecasting intermittent time series with Gaussian Processes and Tweedie likelihood	52
Fundamental determinants of exchange rate expectations	52

A time-varying skewness model for Growth-at-Risk	51
Forecasting with gradient boosted trees: augmentation, tuning, and cross-validation strategies	47
The decrease in confidence with forecast extremity	47
Editorial Board	46
A fast and scalable ensemble of global models with long memory and data partitioning for the M5 forecasting competition	46
Cognitive reflection, arithmetic ability and financial literacy independently predict both inflation expectations and forecast accuracy	45
How does training improve individual forecasts? Modeling differences in compensatory and non-compensatory biases in geopolitical forecasts	44
Improving forecast stability using deep learning	43
Forecasting and policy when “we simply do not know”	43
Forecasting football results and exploiting betting markets: The case of “both teams to score”	42
Real estate illiquidity and returns: A time-varying regional perspective	41
Forecasting the equity premium with frequency-decomposed technical indicators	37
Hierarchical forecasting with a top-down alignment of independent-level forecasts	37
Improving disaggregated short-term food inflation forecasts with webscraped data	37
Machine learning and insurer failure prediction	36
The M5 competition: Conclusions	35
A robust support vector regression model for electric load forecasting	33
Forecasting: theory and practice	33
Editorial Board	32
Editorial Board	31
Optimal hierarchical EWMA forecasting	31
Variability of the Lee–Carter model parameters	31
Combining forecasts under structural breaks using Graphical LASSO	31
Forecasting presidential elections: Accuracy of ANES voter intentions	30
Enhancing market return forecasts with an incident-based ESG indicator	28
An assessment of the marginal predictive content of economic uncertainty indexes and business conditions predictors	28
Model combinations through revised base rates	26
Forecasting South Korea’s presidential election via multiparty dynamic Bayesian modeling	26
External forcings and predictability of the Atlantic multidecadal oscillation: A model confidence set approach	26
Could the Bank of England have avoided mis-forecasting UK inflation during 2021–24?	26
Evaluating probabilistic classifiers: The triptych	25
Nowcasting GDP with a pool of factor models and a fast estimation algorithm	25
Exploring the representativeness of the M5 competition data	25
A disaster response model driven by spatial–temporal forecasts	25
Sequential optimization three-way decision model with information gain for credit default risk evaluation	25
Rejoinder: How to “improve” prediction using behavior modification	25
Post-script—Retail forecasting: Research and practice	25
Forecasting corporate default risk in China	24
Forecasting expected shortfall: Should we use a multivariate model for stock market factors?	24
When to be discrete: The importance of time formulation in the modeling of extreme events in finance	23
Forecasting GDP growth rates in the United States and Brazil using Google Trends	23
The structural Theta method and its predictive performance in the M4-Competition	23
Forecasting Australian fertility by age, region, and birthplace	22
Forecasting crude oil futures market returns: A principal component analysis combination approach	22
Modeling and forecasting intraday spot volatility	22
Whispers in the oil market: Exploring sentiment and uncertainty insights	21
Network log-ARCH models for forecasting stock market volatility	21
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties	21
Forecasting with trees	21
Editorial Board	20

A loss discounting framework for model averaging and selection in time series models	20
Judgment in macroeconomic output growth predictions: Efficiency, accuracy and persistence	20
Portfolio return prediction and risk price heterogeneity	20
Retail forecasting: Research and practice	20
Anticipating humanitarian emergencies with a high risk of conflict-induced displacement	19
Targeting predictors in random forest regression	19
Internal consistency of household inflation expectations: Point forecasts vs. density forecasts	19
M6 investment challenge: The role of luck and strategic considerations	19
Reactions to the Bernanke Review from Bank of England watchers	19
Mining semantic features in current reports for financial distress prediction: Empirical evidence from unlisted public firms in China	19
Technical analysis, spread trading, and data snooping control	18
Forecasting electoral violence	18
Counterfactual reconciliation: Incorporating aggregation constraints for more accurate causal effect estimates	18
A review and comparison of conflict early warning systems	18
Nowcasting U.S. state-level CO2 emissions and energy consumption	18
Discussion of “Thirty years on: A review of the Lee–Carter method for forecasting mortality”	18
A Bayesian Dirichlet auto-regressive moving average model for forecasting lead times	18
Hierarchical mortality forecasting with EVT tails: An application to solvency capital requirement	17
False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk	17
Forecasting stock market return with anomalies: Evidence from China	17
All forecasters are not the same: Systematic patterns in predictive performance	17
Partisan bias, attribute substitution, and the benefits of an indirect format for eliciting forecasts and judgments of trend	16
M5 accuracy competition: Results, findings, and conclusions	16
The power of narrative sentiment in economic forecasts	16
Accelerating peak dating in a dynamic factor Markov-switching model	15
Editorial Board	15
Mixed-frequency machine learning: Nowcasting and backcasting weekly initial claims with daily internet search volume data	15
Robust returns ranking prediction and portfolio optimization for M6	15
A functional mixture prediction model for dynamically forecasting cumulative intraday returns of crude oil futures	15
Demand forecasting under lost sales stock policies	14
Factor-augmented forecasting in big data	14
Volatility analysis for the GARCH–Itô–Jumps model based on high-frequency and low-frequency financial data	14
Beyond the numbers: The role of people and processes in central bank forecasting	14
Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models	14
On forecast stability	13
Quasi-average predictions and regression to the trend: An application to the M6 financial forecasting competition	13
Machine learning algorithms for forecasting and backcasting blood demand data with missing values and outliers: A study of Tema General Hospital of Ghana	13
Sensitivity and uncertainty in the Lee–Carter mortality model	13
Integrating nowcasts into an ensemble of data-driven forecasting models for SARI hospitalizations in Germany	13
Predicting value at risk for cryptocurrencies with generalized random forests	13
Physics-informed Gaussian process regression for states estimation and forecasting in power grids	13
Jump persistence and temporal aggregation of tail risk	13
Forecast value added in demand planning	12
Embrace the differences: Revisiting the PollyVote method of combining forecasts for U.S. presidential elections (2004 to 2020)	12
The uncertainty track: Machine learning, statistical modeling, synthesis	12
Editorial Board	12
Dynamic linear models with adaptive discounting	12
Lee–Carter models: The wider context	12